From 9803702c81a3b80da56d389485362f91233d6561 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Thu, 19 Mar 2020 12:52:07 -0400
Subject: [PATCH 01/30] Size reduction (#505)

* Replace or delete images

* Modify links

* Update README
---
 R/datasets.R                             |    2 -
 README.Rmd                               |    8 +-
 README.md                                |   14 +-
 man/figures/cc_lines_exported.svg        | 2794 ----------------------
 man/figures/gt_datasets.svg              |  511 ----
 man/figures/gt_function_reference.png    |  Bin 302547 -> 290384 bytes
 man/figures/gt_tables.png                |  Bin 118862 -> 0 bytes
 man/gtcars.Rd                            |    3 -
 man/sp500.Rd                             |    3 -
 vignettes/case-study-gtcars.Rmd          |    4 +-
 vignettes/gt-datasets.Rmd                |    2 +-
 vignettes/images/countrypops.png         |  Bin 0 -> 175860 bytes
 vignettes/images/countrypops.svg         |   53 -
 vignettes/images/tables_from_the_web.png |  Bin 791852 -> 209904 bytes
 14 files changed, 6 insertions(+), 3388 deletions(-)
 delete mode 100644 man/figures/cc_lines_exported.svg
 delete mode 100644 man/figures/gt_datasets.svg
 delete mode 100644 man/figures/gt_tables.png
 create mode 100644 vignettes/images/countrypops.png
 delete mode 100644 vignettes/images/countrypops.svg

diff --git a/R/datasets.R b/R/datasets.R
index 0cc782712..248b87ec4 100644
--- a/R/datasets.R
+++ b/R/datasets.R
@@ -113,7 +113,6 @@
 #'   is headquartered}
 #' }
 #'
-#' @source Various pages within <https://www.edmunds.com>.
 #' @examples
 #' # Here is a glimpse at the data
 #' # available in `gtcars`
@@ -140,7 +139,6 @@
 #' \item{adj_close}{The close price adjusted for both dividends and splits}
 #' }
 #'
-#' @source Data collected from <https://finance.yahoo.com/quote/\\%5EGSPC/history/>.
 #' @examples
 #' # Here is a glimpse at the data
 #' # available in `sp500`
diff --git a/README.Rmd b/README.Rmd
index 940dcb545..998d28eb1 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -68,8 +68,6 @@ sp500 %>%
 
 There are six datasets included in **gt**: `countrypops`, `sza`, `gtcars`, `sp500`, `pizzaplace`, and `exibble`. All of them are useful for experimenting with **gt**'s functions.
 
-<p align="center"><img src="man/figures/gt_datasets.svg" width="800px"></p>
-
 Beyond this simple example, there are many functions available in **gt** for creating super-customized tables.
 
 <p align="center"><img src="man/figures/gt_function_reference.png" width="100%"></p>
@@ -92,10 +90,6 @@ If you encounter a bug, have usage questions, or want to share ideas to make thi
  
 ***
 
-<img src="man/figures/gt_tables.png">
-
-***
-
 #### How **gt** fits in with Other Packages that Generate Display Tables
 
 The **gt** package joins a burgeoning collection of packages for display table generation. Why another? We feel that there is enough room in this space to innovate further. Here are some of the ways that **gt** contributes to this ecosystem:
@@ -111,7 +105,7 @@ The **gt** package joins a burgeoning collection of packages for display table g
 
 While **gt** is trying to do something different with its own interface, it may not suit your specific needs. Here is a listing of leading table-making **R** packages, with links to their respective project pages:
 
-**kable**&nbsp;([GITHUB](https://github.com/yihui/knitr),&nbsp;[WEBSITE](https://yihui.org/knitr/))&nbsp;&mdash; **kableExtra**&nbsp;([GITHUB](https://github.com/haozhu233/kableExtra),&nbsp;[WEBSITE](https://haozhu233.github.io/kableExtra/))&nbsp;&mdash; **formattable**&nbsp;([GITHUB](https://github.com/renkun-ken/formattable),&nbsp;[WEBSITE](https://renkun-ken.github.io/formattable/))&nbsp;&mdash; **DT**&nbsp;([GITHUB](https://github.com/rstudio/DT),&nbsp;[WEBSITE](https://rstudio.github.io/DT/))&nbsp;&mdash; **pander**&nbsp;([GITHUB](https://github.com/Rapporter/pander),&nbsp;[WEBSITE](http://rapporter.github.io/pander))&nbsp;&mdash; **huxtable**&nbsp;([GITHUB](https://github.com/hughjonesd/huxtable),&nbsp;[WEBSITE](https://hughjonesd.github.io/huxtable/))&nbsp;&mdash; **reactable**&nbsp;([GITHUB](https://github.com/glin/reactable),&nbsp;[WEBSITE](https://glin.github.io/reactable/))&nbsp;&mdash; **flextable**&nbsp;([GITHUB](https://github.com/davidgohel/flextable),&nbsp;[WEBSITE](https://davidgohel.github.io/flextable/))&nbsp;&mdash; **pixiedust**&nbsp;([GITHUB](https://github.com/nutterb/pixiedust))&nbsp;&mdash; **tangram**&nbsp;([GITHUB](https://github.com/spgarbet/tangram))&nbsp;&mdash; **ztable**&nbsp;([GITHUB](https://github.com/cardiomoon/ztable))&nbsp;&mdash; **condformat**&nbsp;([GITHUB](https://github.com/zeehio/condformat))&nbsp;&mdash; **stargazer**&nbsp;([CRAN](https://cran.r-project.org/web/packages/stargazer/index.html))&nbsp;&mdash; **xtable**&nbsp;([CRAN](https://cran.r-project.org/web/packages/xtable/index.html))
+**kable**&nbsp;([GITHUB](https://github.com/yihui/knitr),&nbsp;[WEBSITE](https://yihui.org/knitr/))&nbsp;&mdash; **kableExtra**&nbsp;([GITHUB](https://github.com/haozhu233/kableExtra),&nbsp;[WEBSITE](https://haozhu233.github.io/kableExtra/))&nbsp;&mdash; **formattable**&nbsp;([GITHUB](https://github.com/renkun-ken/formattable),&nbsp;[WEBSITE](https://renkun-ken.github.io/formattable/))&nbsp;&mdash; **DT**&nbsp;([GITHUB](https://github.com/rstudio/DT),&nbsp;[WEBSITE](https://rstudio.github.io/DT/))&nbsp;&mdash; **pander**&nbsp;([GITHUB](https://github.com/Rapporter/pander),&nbsp;[WEBSITE](http://rapporter.github.io/pander))&nbsp;&mdash; **huxtable**&nbsp;([GITHUB](https://github.com/hughjonesd/huxtable),&nbsp;[WEBSITE](https://hughjonesd.github.io/huxtable/))&nbsp;&mdash; **reactable**&nbsp;([GITHUB](https://github.com/glin/reactable),&nbsp;[WEBSITE](https://glin.github.io/reactable/))&nbsp;&mdash; **flextable**&nbsp;([GITHUB](https://github.com/davidgohel/flextable),&nbsp;[WEBSITE](https://davidgohel.github.io/flextable/))&nbsp;&mdash; **pixiedust**&nbsp;([GITHUB](https://github.com/nutterb/pixiedust))&nbsp;&mdash; **tangram**&nbsp;([GITHUB](https://github.com/spgarbet/tangram))&nbsp;&mdash; **ztable**&nbsp;([GITHUB](https://github.com/cardiomoon/ztable))&nbsp;&mdash; **condformat**&nbsp;([GITHUB](https://github.com/zeehio/condformat))&nbsp;&mdash; **stargazer**&nbsp;([CRAN](https://CRAN.R-project.org/package=stargazer))&nbsp;&mdash; **xtable**&nbsp;([CRAN](https://CRAN.R-project.org/package=xtable))
 
 #### Code of Conduct
 
diff --git a/README.md b/README.md
index 2f0540305..2ee0892d5 100644
--- a/README.md
+++ b/README.md
@@ -87,12 +87,6 @@ There are six datasets included in **gt**: `countrypops`, `sza`,
 `gtcars`, `sp500`, `pizzaplace`, and `exibble`. All of them are useful
 for experimenting with **gt**’s functions.
 
-<p align="center">
-
-<img src="man/figures/gt_datasets.svg" width="800px">
-
-</p>
-
 Beyond this simple example, there are many functions available in **gt**
 for creating super-customized tables.
 
@@ -125,10 +119,6 @@ make this package better, please feel free to file an
 
 -----
 
-<img src="man/figures/gt_tables.png">
-
------
-
 #### How **gt** fits in with Other Packages that Generate Display Tables
 
 The **gt** package joins a burgeoning collection of packages for display
@@ -170,8 +160,8 @@ pages:
 **tangram** ([GITHUB](https://github.com/spgarbet/tangram)) —
 **ztable** ([GITHUB](https://github.com/cardiomoon/ztable)) —
 **condformat** ([GITHUB](https://github.com/zeehio/condformat)) —
-**stargazer** ([CRAN](https://cran.r-project.org/web/packages/stargazer/index.html)) —
-**xtable** ([CRAN](https://cran.r-project.org/web/packages/xtable/index.html))
+**stargazer** ([CRAN](https://CRAN.R-project.org/package=stargazer)) —
+**xtable** ([CRAN](https://CRAN.R-project.org/package=xtable))
 
 #### Code of Conduct
 
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deleted file mode 100644
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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- >Function</text>
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- >Total</text>
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->
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- >adjust_luminance</text>
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->
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- >2</text>
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- >20</text>
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- >11</text>
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- >12</text>
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- >7</text>
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->
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- >50</text>
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->
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->
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- >2</text>
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- >55</text>
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- >20</text>
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- >19</text>
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- >25</text>
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->
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- >119</text>
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->
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->
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- >2</text>
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- >10</text>
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- >2</text>
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- >4</text>
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- >26</text>
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-
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->
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- >42</text>
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-
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->
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- >as_rtf</text>
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-
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->
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- >44</text>
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- >210</text>
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- >86</text>
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- >99</text>
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- >17</text>
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-
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->
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- >412</text>
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-
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->
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- >cells_column_labels</text>
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-
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->
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- >11</text>
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- >19</text>
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- >5</text>
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- >6</text>
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- >3</text>
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-
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->
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- >33</text>
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-
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-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
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- >cells_data</text>
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-
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->
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- >1</text>
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- >10</text>
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- >6</text>
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- >4</text>
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- >3</text>
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-
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->
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- >23</text>
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-
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->
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- >cells_group</text>
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-
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-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
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- >1</text>
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- >6</text>
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- >3</text>
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- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="328" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
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-
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-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
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- >16</text>
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-
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-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
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- >cells_stub</text>
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-
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-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
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- >2</text>
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- >9</text>
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- >3</text>
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- >5</text>
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- >3</text>
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-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
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- >20</text>
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-
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-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="382" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cells_styles</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="425" y="384" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >22</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="384" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >62</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="384" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="384" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >17</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="384" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >35</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="384" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >114</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="410" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cells_summary</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="412" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="412" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >14</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="412" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="412" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="412" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="412" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >25</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="438" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cells_title</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="440" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="440" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="440" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="440" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="440" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="440" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >17</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="466" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_align</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="468" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="468" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >32</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="468" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="468" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >10</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="468" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >35</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="468" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >83</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="494" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_hide</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="496" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="496" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >14</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="496" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="496" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >7</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="496" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >47</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="496" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >72</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="522" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_label</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="524" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="524" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >25</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="524" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >9</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="524" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >11</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="524" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >47</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="524" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >92</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="550" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_merge</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="552" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="552" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >32</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="552" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="552" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >11</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="552" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >41</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="552" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >87</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="578" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_merge_range</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="580" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="580" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >32</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="580" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="580" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >12</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="580" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >30</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="580" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >78</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="606" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_merge_uncert</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="608" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="608" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >32</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="608" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="608" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >12</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="608" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >34</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="608" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >82</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="634" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_move</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="425" y="636" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >10</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="636" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >40</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="636" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >12</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="636" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >16</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="636" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >28</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="636" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >96</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="662" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_move_to_end</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="664" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >5</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="664" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >19</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="664" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >7</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="664" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >9</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="664" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >41</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="664" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >76</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="690" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_move_to_start</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="692" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >5</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="692" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >18</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="692" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="692" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="692" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >41</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="692" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >73</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="718" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >cols_split_delim</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="720" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="720" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >26</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="720" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="720" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >11</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="720" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >32</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="720" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >72</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="746" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >data_color</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="425" y="748" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >16</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="748" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >67</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="748" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >17</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="748" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >28</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="748" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >83</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="748" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >195</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="774" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >escape_latex</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="776" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="776" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="776" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="776" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="776" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >9</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="776" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >17</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="802" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >extract_summary</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="804" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="804" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >33</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="804" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >27</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="804" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >25</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="804" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >59</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="804" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >144</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="830" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="832" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="832" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >26</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="832" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >16</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="832" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >13</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="832" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >55</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="832" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >110</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="858" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_currency</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="425" y="860" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >18</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="475" y="860" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >125</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="860" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >34</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="860" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >31</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="860" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >80</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="860" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >270</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="886" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_date</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="888" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="888" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >19</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="888" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="888" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="888" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >88</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="888" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >115</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="914" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_datetime</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="916" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="916" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >23</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="916" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="916" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="916" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >78</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="916" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >113</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="942" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_missing</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="944" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="944" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >24</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="944" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="944" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="944" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >41</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="944" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >72</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="970" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_number</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="972" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >9</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="972" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >48</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="972" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >13</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="972" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >10</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="702" y="972" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >103</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="972" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >174</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="998" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_passthrough</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1000" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1000" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >33</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1000" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="1000" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >10</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1000" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >48</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1000" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >97</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1026" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_percent</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="425" y="1028" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >12</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1028" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >86</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="1028" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >20</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="1028" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >20</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1028" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >55</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="1028" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >181</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1054" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_scientific</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1056" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >9</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1056" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >65</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="1056" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >11</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="1056" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >15</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1056" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >51</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="1056" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >142</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1082" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >fmt_time</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1084" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1084" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >19</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1084" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1084" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1084" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >78</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="1084" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >105</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1110" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >ggplot_image</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1112" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1112" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >21</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1112" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1112" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1112" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >38</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1112" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >66</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1138" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >gt</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1140" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1140" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >85</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="1140" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >53</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="1140" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >38</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1140" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >68</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="1140" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >244</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1166" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >gt_output</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1168" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="1168" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1168" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1168" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="1168" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1168" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >12</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1194" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >gt_preview</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1196" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1196" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >62</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="1196" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >23</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="1196" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >22</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1196" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >41</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="1196" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >148</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1222" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >html</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1224" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="1224" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1224" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1224" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1224" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >23</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1224" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >27</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1250" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >info_date_style</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1252" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1252" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >29</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1252" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1252" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="1252" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1252" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >34</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1278" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >info_time_style</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1280" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1280" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >17</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1280" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1280" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="1280" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1280" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >22</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1306" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >local_image</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1308" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1308" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >13</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1308" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >5</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1308" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1308" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >17</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1308" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >39</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1334" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >md</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1336" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="1336" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >4</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1336" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1336" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1336" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >21</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1336" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >27</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1362" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >pct</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1364" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="1364" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1364" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1364" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="1364" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1364" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >14</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1390" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >px</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1392" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="1392" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1392" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1392" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="720" y="1392" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1392" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >14</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1418" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >render_gt</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1420" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1420" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >26</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1420" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >0</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1420" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >7</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1420" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >12</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1420" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >45</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1446" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >row_group_order</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1448" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >6</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1448" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >29</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="573" y="1448" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >10</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="634" y="1448" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >14</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1448" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >39</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1448" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >92</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1474" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >summary_rows</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1476" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >7</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1476" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >41</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1476" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1476" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >8</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1476" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >73</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="758" y="1476" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >123</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1502" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >tab_footnote</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1504" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="493" y="1504" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >9</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1504" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1504" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1504" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >52</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="767" y="1504" font-family="Arial" font-size="16" font-weight="700" font-style="normal" 
- >67</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="246" y="1530" font-family="Courier New" font-size="13" font-weight="400" font-style="normal" 
- >tab_header</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
-font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
->
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="434" y="1532" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >2</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="484" y="1532" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >12</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="582" y="1532" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >1</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="643" y="1532" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >3</text>
-<text fill="#000000" fill-opacity="1" stroke="none" xml:space="preserve" x="711" y="1532" font-family="Arial" font-size="16" font-weight="400" font-style="normal" 
- >28</text>
-</g>
-
-<g fill="#000000" fill-opacity="1" stroke="#000000" stroke-opacity="1" stroke-width="1" stroke-linecap="square" stroke-linejoin="bevel" transform="matrix(1,0,0,1,0,0)"
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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->
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\ No newline at end of file
diff --git a/man/figures/gt_function_reference.png b/man/figures/gt_function_reference.png
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Ef=2;Q4*&oF

diff --git a/man/gtcars.Rd b/man/gtcars.Rd
index 9af44eda4..0d9e2b475 100644
--- a/man/gtcars.Rd
+++ b/man/gtcars.Rd
@@ -27,9 +27,6 @@ both types (\code{am}), or, direct drive (\code{dd})}
 is headquartered}
 }
 }
-\source{
-Various pages within \url{https://www.edmunds.com}.
-}
 \usage{
 gtcars
 }
diff --git a/man/sp500.Rd b/man/sp500.Rd
index 5309c6558..1ac7c42bf 100644
--- a/man/sp500.Rd
+++ b/man/sp500.Rd
@@ -14,9 +14,6 @@ prices in USD; the \code{close} price is adjusted for splits}
 \item{adj_close}{The close price adjusted for both dividends and splits}
 }
 }
-\source{
-Data collected from \url{https://finance.yahoo.com/quote/\\\\\%5EGSPC/history/}.
-}
 \usage{
 sp500
 }
diff --git a/vignettes/case-study-gtcars.Rmd b/vignettes/case-study-gtcars.Rmd
index 467768058..958101a89 100644
--- a/vignettes/case-study-gtcars.Rmd
+++ b/vignettes/case-study-gtcars.Rmd
@@ -310,7 +310,7 @@ tab <-
   tab %>%
   tab_source_note(
     source_note = md(
-      "Source: Various pages within [edmunds.com](https://www.edmunds.com).")
+      "Source: Various pages within the Edmonds website.")
   )
 
 # Show the table
@@ -433,7 +433,7 @@ tab <-
   ) %>%
   tab_source_note(
     source_note = md(
-      "Source: Various pages within [edmunds.com](https://www.edmunds.com).")
+      "Source: Various pages within the Edmonds website.")
   ) %>%
   tab_footnote(
     footnote = md("Best gas mileage (city) of all the **gtcars**."),
diff --git a/vignettes/gt-datasets.Rmd b/vignettes/gt-datasets.Rmd
index 3b083590a..048b56e45 100644
--- a/vignettes/gt-datasets.Rmd
+++ b/vignettes/gt-datasets.Rmd
@@ -19,7 +19,7 @@ library(tidyr)
 
 The **gt** package comes with six built-in datasets for experimenting with the **gt** API: `countrypops`, `sza`, `gtcars`, `sp500`, `pizzaplace`, and `exibble`. While each dataset has different subject matter, all of them will be used to develop **gt** examples with consistent syntax.
 
-<img src="images/countrypops.svg" width=30%><img src="images/sza.svg" width=30%><img src="images/gtcars.svg" width=30%>
+<img src="images/countrypops.png" width=30%><img src="images/sza.svg" width=30%><img src="images/gtcars.svg" width=30%>
 
 <img src="images/sp500.svg" width=30%><img src="images/pizzaplace.svg" width=30%><img src="images/exibble.svg" width=30%>
 
diff --git a/vignettes/images/countrypops.png b/vignettes/images/countrypops.png
new file mode 100644
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deleted file mode 100644
index d9f903797..000000000
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z`ip#+Ys;f^zmRe(dGJWvDITvHC~`n}v&cpZo+1^e?`jc8@fq)YDW8*;WcGg=o;&tQ
z;`0OVM=@QzQz^z~fInXhSebtN;gi*;+@0A~s*MTf3)`~J|IeM!FRReM0HfF~J!bB2
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z<>Y_o*8kBzLxH;%CkbUQv;L<By}czEzY>LbT2?{+-VFc0Mo~)beM@Zhg0uAtYMuSw
O-K8k2Dua+R^!Z;WpIGSt


From 746101022f05d428d1c1e7928f1ef9471b7153b5 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 20 Mar 2020 15:59:24 -0400
Subject: [PATCH 02/30] Use `rle()` to determine colspan values for spanners
 (#507)

* Use `rle()` to determine colspan values for spanners

* Add a test for `tab_spanner()`/`cols_move_to_start()`

* Call rle() once before iterating on spanners

The performance benefit here is negligible, but I think it is
clearer to precalculate all the colspans that are needed up
front using the rle() results.

* Simplify headings_stack calculation; add comments

Co-authored-by: Joe Cheng <joe@rstudio.com>
---
 R/utils_render_html.R             | 64 +++++++++++++++----------------
 tests/testthat/test-table_parts.R | 43 +++++++++++++++++++++
 2 files changed, 74 insertions(+), 33 deletions(-)

diff --git a/R/utils_render_html.R b/R/utils_render_html.R
index d25700b1f..0dd7e7c43 100644
--- a/R/utils_render_html.R
+++ b/R/utils_render_html.R
@@ -431,8 +431,13 @@ create_columns_component_h <- function(data) {
 
     spanners <- dt_spanners_print(data = data, include_hidden = FALSE)
 
-    headings_stack <- c()
-    first_set <- second_set <- list()
+    # A list of <th> elements that will go in the top row. This includes
+    # spanner labels and column labels for solo columns (don't have spanner
+    # labels); in the latter case, rowspan=2 will be used.
+    first_set <- list()
+    # A list of <th> elements that will go in the second row. This is all column
+    # labels that DO have spanners above them.
+    second_set <- list()
 
     # Create the cell for the stubhead label
     if (isTRUE(stub_available)) {
@@ -460,6 +465,23 @@ create_columns_component_h <- function(data) {
       headings_labels <- headings_labels[-1]
     }
 
+    # NOTE: rle treats NA values as distinct from each other; in other words,
+    # each NA value starts a new run of length 1.
+    spanners_rle <- rle(spanners)
+    # sig_cells contains the indices of spanners' elements where the value is
+    # either NA, or, is different than the previous value. (Because NAs are
+    # distinct, every NA element will be present sig_cells.)
+    sig_cells <- c(1, head(cumsum(spanners_rle$lengths) + 1, -1))
+    # colspans matches spanners in length; each element is the number of
+    # columns that the <th> at that position should span. If 0, then skip the
+    # <th> at that position.
+    colspans <- ifelse(
+      seq_along(spanners) %in% sig_cells,
+      # Index back into the rle result, working backward through sig_cells
+      spanners_rle$lengths[match(seq_along(spanners), sig_cells)],
+      0
+    )
+
     for (i in seq(headings_vars)) {
 
       if (is.na(spanners[i])) {
@@ -489,37 +511,12 @@ create_columns_component_h <- function(data) {
             htmltools::HTML(headings_labels[i])
           )
 
-        headings_stack <- c(headings_stack, headings_vars[i])
-
       } else if (!is.na(spanners[i])) {
 
-        if (i > 1) {
-          if (is.na(spanners[i - 1])) {
-            same_spanner <- FALSE
-          } else if (spanners[i] == spanners[i - 1]) {
-            same_spanner <- TRUE
-          } else {
-            same_spanner <- FALSE
-          }
-        } else {
-          same_spanner <- FALSE
-        }
-
-        if (!same_spanner) {
-
+        # If colspans[i] == 0, it means that a previous cell's colspan
+        # will cover us.
+        if (colspans[i] > 0) {
           class <- "gt_column_spanner"
-          colspan <- 1
-
-          for (j in 1:length(spanners)) {
-
-            if (is.na(spanners[i + j])) {
-              break
-            } else if (duplicated(spanners)[i + j]) {
-              colspan <- colspan + 1L
-            } else {
-              break
-            }
-          }
 
           styles_spanners <-
             spanner_style_attrs %>%
@@ -539,7 +536,7 @@ create_columns_component_h <- function(data) {
                 collapse = " "
               ),
               rowspan = 1,
-              colspan = colspan,
+              colspan = colspans[i],
               style = spanner_style,
               htmltools::tags$span(
                 class = "gt_column_spanner",
@@ -550,7 +547,8 @@ create_columns_component_h <- function(data) {
       }
     }
 
-    remaining_headings <- headings_vars[!(headings_vars %in% headings_stack)]
+    solo_headings <- headings_vars[is.na(spanners)]
+    remaining_headings <- headings_vars[!(headings_vars %in% solo_headings)]
 
     remaining_headings_indices <- which(remaining_headings %in% headings_vars)
 
@@ -561,7 +559,7 @@ create_columns_component_h <- function(data) {
       unlist()
 
     col_alignment <-
-      col_alignment[-1][!(headings_vars %in% headings_stack)]
+      col_alignment[-1][!(headings_vars %in% solo_headings)]
 
     if (length(remaining_headings) > 0) {
 
diff --git a/tests/testthat/test-table_parts.R b/tests/testthat/test-table_parts.R
index ac2110265..e624e7536 100644
--- a/tests/testthat/test-table_parts.R
+++ b/tests/testthat/test-table_parts.R
@@ -180,6 +180,49 @@ test_that("a gt table contains the expected spanner column labels", {
   )
 })
 
+test_that("`tab_spanner()` works even when columns are forcibly moved", {
+
+  # Create a table with column spanners, moving the `carb` value
+  # to the beginning of the column sequence (splitting the `group_d`
+  # column spanner into two parts)
+  tbl_html <-
+    gt(mtcars[1, ]) %>%
+    tab_spanner(
+      label = md("*group_a*"),
+      columns = vars(cyl, hp)
+    ) %>%
+    tab_spanner(
+      label = md("*group_b*"),
+      columns = vars(drat, wt)
+    ) %>%
+    tab_spanner(
+      label = md("*group_c*"),
+      columns = vars(qsec, vs, am)
+    ) %>%
+    tab_spanner(
+      label = md("*group_d*"),
+      columns = vars(gear, carb)
+    ) %>%
+    tab_spanner(
+      label = md("*never*"),
+      columns = ends_with("nothing")
+    ) %>%
+    cols_move_to_start(columns = vars(carb)) %>%
+    render_as_html()
+
+
+  # Expect the sequence of `colspan` values across both
+  # <tr>s in <thead> is correct
+  tbl_html %>%
+    xml2::read_html() %>%
+    selection_value("colspan") %>%
+    expect_equal(
+      c("1", "1", "2", "1", "2", "3", "1",           # first <tr>
+        "1", "1", "1", "1", "1", "1", "1", "1", "1"  # second <tr>
+       )
+    )
+})
+
 test_that("a gt table contains the expected source note", {
 
   # Check that specific suggested packages are available

From d16bebafed49ac04817c0ab139e29d945a6437d7 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 23 Mar 2020 15:11:07 -0400
Subject: [PATCH 03/30] Fix to avoid error in `gt_preview()` with columns that
 contain dates (#508)

* Use `drop = FALSE` to avoid df conversion

* Ensure that all column data is converted to `character`

* Obtain two slices of data, then use `rbind()`

* Use NAs as dividing rows

* Add several testthat tests

* Modify comment

* Use `text_transform()` instead of `fmt_missing()`

This is for ensuring that the diving row has no values (empty strings).
---
 R/gt_preview.R                   | 25 +++++++++++++++++--------
 tests/testthat/test-gt_preview.R | 26 ++++++++++++++++++++++++++
 2 files changed, 43 insertions(+), 8 deletions(-)

diff --git a/R/gt_preview.R b/R/gt_preview.R
index c08aa8562..d16341c87 100644
--- a/R/gt_preview.R
+++ b/R/gt_preview.R
@@ -85,13 +85,18 @@ gt_preview <- function(data,
     # Prepare a rowname label that represents the hidden row numbers
     between_rownums <- c(ellipsis_row, nrow(data) - bottom_n)
 
-    # Modify the `data` so that only the `top_n` and `bottom_n` rows
-    # are retained (with an empty row between these row groups)
+    # Obtain the top and bottom slices of data
+    top_slice <- data[seq(top_n), , drop = FALSE]
+    bottom_slice <- data[(nrow(data) + 1 - rev(seq(bottom_n))), , drop = FALSE]
+
+    # Modify the `data` so that only the `top_n` (`top_slice`) and
+    # `bottom_n` (`bottom_slice`) rows are retained (with a row of
+    # NAs to clearly separate these slices)
     data <-
       rbind(
-        data[seq(top_n), ],
-        rep("", ncol(data)),
-        data[(nrow(data) + 1 - rev(seq(bottom_n))), ]
+        top_slice,
+        rep(NA, ncol(data)),
+        bottom_slice
       )
 
     # Relabel the rowname for the ellipsis row
@@ -123,7 +128,8 @@ gt_preview <- function(data,
 
   visible_vars <- dt_boxhead_get_vars_default(data = gt_tbl)
 
-  # Add styling to ellipsis row, if it is present
+  # Replace the NA values and add styling to the ellipsis
+  # row (if it is present)
   if (isTRUE(has_ellipsis_row)) {
 
     gt_tbl <-
@@ -131,6 +137,10 @@ gt_preview <- function(data,
       tab_style(
         style = cell_fill(color = "#E4E4E4"),
         locations = cells_body(columns = visible_vars, rows = ellipsis_row)
+      ) %>%
+      text_transform(
+        locations = cells_body(columns = TRUE, rows = ellipsis_row),
+        fn = function(x) ""
       )
 
     if (isTRUE(incl_rownums)) {
@@ -140,11 +150,10 @@ gt_preview <- function(data,
         tab_style(
           style = list(
             cell_fill(color = "#E4E4E4"),
-            cell_text(size = "10px")
+            cell_text(size = "x-small")
           ),
           locations = cells_stub(rows = ellipsis_row)
         )
-
     }
   }
 
diff --git a/tests/testthat/test-gt_preview.R b/tests/testthat/test-gt_preview.R
index 7a14f90e0..7586a2251 100644
--- a/tests/testthat/test-gt_preview.R
+++ b/tests/testthat/test-gt_preview.R
@@ -101,4 +101,30 @@ test_that("the `gt_preview()` function works correctly", {
   output_tbl %>%
     colnames() %>%
     expect_equal(colnames(mtcars))
+
+  # Expect no errors when using all gt datasets (plus a few more
+  # from the datasets package) with the `gt_preview()` function
+  expect_error(regexp = NA, gt_preview(countrypops))
+  expect_error(regexp = NA, gt_preview(sza))
+  expect_error(regexp = NA, gt_preview(gtcars))
+  expect_error(regexp = NA, gt_preview(sp500))
+  expect_error(regexp = NA, gt_preview(pizzaplace))
+  expect_error(regexp = NA, gt_preview(exibble))
+
+  expect_error(regexp = NA, gt_preview(datasets::airquality))
+  expect_error(regexp = NA, gt_preview(datasets::cars))
+  expect_error(regexp = NA, gt_preview(datasets::chickwts))
+  expect_error(regexp = NA, gt_preview(datasets::faithful))
+  expect_error(regexp = NA, gt_preview(datasets::iris))
+  expect_error(regexp = NA, gt_preview(datasets::LifeCycleSavings))
+  expect_error(regexp = NA, gt_preview(datasets::longley))
+  expect_error(regexp = NA, gt_preview(datasets::morley))
+  expect_error(regexp = NA, gt_preview(datasets::mtcars))
+  expect_error(regexp = NA, gt_preview(datasets::Orange))
+  expect_error(regexp = NA, gt_preview(datasets::pressure))
+  expect_error(regexp = NA, gt_preview(datasets::quakes))
+  expect_error(regexp = NA, gt_preview(datasets::rock))
+  expect_error(regexp = NA, gt_preview(datasets::sleep))
+  expect_error(regexp = NA, gt_preview(datasets::swiss))
+  expect_error(regexp = NA, gt_preview(datasets::USJudgeRatings))
 })

From f64b77638108c835895fb05776a89c01870399af Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Tue, 31 Mar 2020 11:16:40 -0400
Subject: [PATCH 04/30] Release gt v0.2.0 (#514)

* Update version number in DESCRIPTION

* Update NEWS.md

* Fix typo in docs for `opt_row_striping()`

* Modify development mode in pkgdown YAML file

* Make small documentation fixes

* Update package name in README

* Use `utils::head()`

* Update CoC link in README

* Add vignettes folder to .Rbuildignore

* Increase 4th component of version number

* Update NEWS.md

* Remove image and update README

* Update LICENSE

* Update version number

* Remove VignetteBuilder field

* Make necessary fixes for tibble 3.0.0

* Update DESCRIPTION

* Make doc changes based on CRAN review

* Refactor `dt_boxhead_edit()`

* Increase version number (at 4th component)

* Lower minimum version requirement for sass pkg

CRAN only has sass built to 0.1.2.1 for r-devel-windows-ix86+x86_64 so the pretest for that platform failed, requiring another submission.
---
 .Rbuildignore                         |   1 +
 DESCRIPTION                           |  21 ++++++++++-----------
 LICENSE                               |   1 -
 NEWS.md                               |   6 ++++--
 R/dt_boxhead.R                        |  13 ++++++++++---
 R/export.R                            |  25 +++++++++++++++----------
 R/modify_columns.R                    |   7 ++++---
 R/opts.R                              |   2 +-
 R/shiny.R                             |   4 ++--
 R/utils_render_html.R                 |   2 +-
 README.Rmd                            |   6 ++----
 README.md                             |  12 +++---------
 _pkgdown.yml                          |   2 +-
 man/cols_width.Rd                     |   7 ++++---
 man/figures/gt_function_reference.png | Bin 290384 -> 0 bytes
 man/gt_output.Rd                      |   2 +-
 man/gtsave.Rd                         |  25 +++++++++++++++----------
 man/opt_row_striping.Rd               |   2 +-
 man/render_gt.Rd                      |   2 +-
 19 files changed, 76 insertions(+), 64 deletions(-)
 delete mode 100644 man/figures/gt_function_reference.png

diff --git a/.Rbuildignore b/.Rbuildignore
index 9cc91d24d..bba2a0fe0 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -14,3 +14,4 @@
 ^CODE_OF_CONDUCT\.md$
 ^TODOS
 tests/gt-examples
+vignettes
diff --git a/DESCRIPTION b/DESCRIPTION
index 745bc834f..c1915841a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Type: Package
 Package: gt
-Version: 0.1.0
+Version: 0.2.0.5
 Title: Easily Create Presentation-Ready Display Tables
 Description: Build display tables from tabular data using with an easy-to-use
     API. With its progressive approach, we can construct display tables with a
@@ -24,20 +24,20 @@ RoxygenNote: 7.1.0
 Depends:
     R (>= 3.2.0)
 Imports: 
-    checkmate (>= 1.8.5),
+    checkmate (>= 2.0.0),
     commonmark (>= 1.7),
-    dplyr (>= 0.7.8),
-    fs (>= 1.2.6),
-    ggplot2 (>= 3.1.0),
-    glue (>= 1.3.0),
-    htmltools (>= 0.3.6),
+    dplyr (>= 0.8.5),
+    fs (>= 1.3.2),
+    ggplot2 (>= 3.3.0),
+    glue (>= 1.3.2),
+    htmltools (>= 0.4.0),
     magrittr (>= 1.5),
-    rlang (>= 0.3.0),
+    rlang (>= 0.4.5),
     sass (>= 0.1.1),
     scales (>= 1.1.0),
     stringr (>= 1.3.1),
-    tibble (>= 1.4.2),
-    tidyselect (>= 0.2.5)
+    tibble (>= 3.0.0),
+    tidyselect (>= 1.0.0)
 Suggests:
     knitr,
     paletteer,
@@ -49,7 +49,6 @@ Suggests:
     tidyr,
     webshot,
     xml2
-VignetteBuilder: knitr
 Roxygen: list(markdown = TRUE)
 Collate: 
     'as_data_frame.R'
diff --git a/LICENSE b/LICENSE
index abfde4f73..1ddfc7db1 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,3 +1,2 @@
 YEAR: 2018-2020
 COPYRIGHT HOLDER: RStudio, PBC
-ORGANIZATION: RStudio, PBC
diff --git a/NEWS.md b/NEWS.md
index a1990d3fa..e79532980 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,5 @@
-# gt 0.1.0 (unreleased)
+# gt 0.2.0.5
+
+* New package with 80 exported functions for building display tables
 
-* New package with 39 exported functions for building display tables
+# gt 0.1.0 (unreleased)
diff --git a/R/dt_boxhead.R b/R/dt_boxhead.R
index b7c11a1cd..a3e690ef6 100644
--- a/R/dt_boxhead.R
+++ b/R/dt_boxhead.R
@@ -60,12 +60,19 @@ dt_boxhead_edit <- function(data, var, ...) {
 
   val_list <- list(...)
 
+  if (length(val_list) != 1) {
+    stop("`dt_boxhead_edit()` expects a single value at ...")
+  }
+
   check_names_dt_boxhead_expr(val_list)
 
   check_vars_dt_boxhead(var, dt_boxhead)
 
-  dt_boxhead[which(dt_boxhead$var == var_name), names(val_list)] <-
-    dplyr::as_tibble(val_list)
+  if (is.list(dt_boxhead[[names(val_list)]])) {
+    dt_boxhead[[which(dt_boxhead$var == var_name), names(val_list)]] <- unname(val_list)
+  } else {
+    dt_boxhead[[which(dt_boxhead$var == var_name), names(val_list)]] <- unlist(val_list)
+  }
 
   dt_boxhead %>% dt_boxhead_set(data = data)
 }
@@ -130,7 +137,7 @@ dt_boxhead_set_row_group <- function(data, vars) {
 
 dt_boxhead_edit_column_label <- function(data, var, column_label) {
 
-  dt_boxhead_edit(data, var, column_label = list(column_label))
+  dt_boxhead_edit(data, var, column_label = column_label)
 }
 
 dt_boxhead_get_vars <- function(data) {
diff --git a/R/export.R b/R/export.R
index 4cddc35b0..f218e7b76 100644
--- a/R/export.R
+++ b/R/export.R
@@ -41,7 +41,7 @@
 #'   function.
 #'
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' # Use `gtcars` to create a gt table; add
 #' # a stubhead label to describe what is
 #' # in the stub
@@ -50,32 +50,37 @@
 #'   dplyr::select(model, year, hp, trq) %>%
 #'   dplyr::slice(1:5) %>%
 #'   gt(rowname_col = "model") %>%
-#'   tab_stubhead_label(label = "car")
+#'   tab_stubhead(label = "car")
 #'
 #' # Get an HTML file with inlined CSS
 #' # (which is necessary for including the
 #' # table as part of an HTML email)
 #' tab_1 %>%
-#'   gtsave("tab_1.html", inline_css = TRUE)
+#'   gtsave(
+#'     "tab_1.html", inline_css = TRUE,
+#'     path = tempdir()
+#'   )
 #'
 #' # By leaving out the `inline_css` option,
 #' # we get a more conventional HTML file
 #' # with embedded CSS styles
-#' tab_1 %>% gtsave("tab_1.html")
-#'
-#' # Save the HTML table as a PDF file; we
-#' # can optionally add a separate `path`
-#' tab_1 %>% gtsave("tab_1.pdf", path = "~")
+#' tab_1 %>%
+#'   gtsave("tab_1.html", path = tempdir())
 #'
 #' # Saving as PNG file results in a cropped
 #' # image of an HTML table; the amount of
 #' # whitespace can be set
-#' tab_1 %>% gtsave("tab_1.png", expand = 10)
+#' tab_1 %>%
+#'   gtsave(
+#'     "tab_1.png", expand = 10,
+#'     path = tempdir()
+#'   )
 #'
 #' # Any use of the `.tex`, `.ltx`, or `.rnw`
 #' # will result in the output of a LaTeX
 #' # document
-#' tab_1 %>% gtsave("tab_1.tex")
+#' tab_1 %>%
+#'   gtsave("tab_1.tex", path = tempdir())
 #' }
 #'
 #' @family Export Functions
diff --git a/R/modify_columns.R b/R/modify_columns.R
index 09dd03bf8..dad4b3fdb 100644
--- a/R/modify_columns.R
+++ b/R/modify_columns.R
@@ -137,8 +137,9 @@ cols_align <- function(data,
 #' # Use `exibble` to create a gt table;
 #' # with named arguments in `...`, we
 #' # can specify the exact widths for
-#' # table columns (using `TRUE` will
-#' # capture all remaining columns)
+#' # table columns (using `everything()`
+#' # or `TRUE` at the end will capture
+#' # all remaining columns)
 #' tab_1 <-
 #'   exibble %>%
 #'   dplyr::select(
@@ -150,7 +151,7 @@ cols_align <- function(data,
 #'     vars(num) ~ px(150),
 #'     ends_with("r") ~ px(100),
 #'     starts_with("date") ~ px(200),
-#'     TRUE ~ px(60)
+#'     everything() ~ px(60)
 #'   )
 #'
 #' @section Figures:
diff --git a/R/opts.R b/R/opts.R
index 3445c8f21..41b75bda1 100644
--- a/R/opts.R
+++ b/R/opts.R
@@ -107,7 +107,7 @@ opt_footnote_marks <- function(data,
 #' # Use `exibble` to create a gt table with
 #' # a number of table parts added; next, we
 #' # add row striping to every second row with
-#' # the `opt_add_row_striping()` function
+#' # the `opt_row_striping()` function
 #' tab_1 <-
 #'   exibble %>%
 #'   gt(rowname_col = "row", groupname_col = "group") %>%
diff --git a/R/shiny.R b/R/shiny.R
index 52a0917b2..5cae81f54 100644
--- a/R/shiny.R
+++ b/R/shiny.R
@@ -64,7 +64,7 @@
 #'     )
 #' }
 #'
-#' \dontrun{
+#' \donttest{
 #' shinyApp(ui, server)
 #' }
 #'
@@ -184,7 +184,7 @@ render_gt <- function(expr,
 #'     )
 #' }
 #'
-#' \dontrun{
+#' \donttest{
 #' shinyApp(ui, server)
 #' }
 #'
diff --git a/R/utils_render_html.R b/R/utils_render_html.R
index 0dd7e7c43..fe9b58cf0 100644
--- a/R/utils_render_html.R
+++ b/R/utils_render_html.R
@@ -471,7 +471,7 @@ create_columns_component_h <- function(data) {
     # sig_cells contains the indices of spanners' elements where the value is
     # either NA, or, is different than the previous value. (Because NAs are
     # distinct, every NA element will be present sig_cells.)
-    sig_cells <- c(1, head(cumsum(spanners_rle$lengths) + 1, -1))
+    sig_cells <- c(1, utils::head(cumsum(spanners_rle$lengths) + 1, -1))
     # colspans matches spanners in length; each element is the number of
     # columns that the <th> at that position should span. If 0, then skip the
     # <th> at that position.
diff --git a/README.Rmd b/README.Rmd
index 998d28eb1..07a0378d6 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -70,8 +70,6 @@ There are six datasets included in **gt**: `countrypops`, `sza`, `gtcars`, `sp50
 
 Beyond this simple example, there are many functions available in **gt** for creating super-customized tables.
 
-<p align="center"><img src="man/figures/gt_function_reference.png" width="100%"></p>
-
 Want to try this out? Then, take the **gt** Test Drive on **RStudio Cloud**. It's full of ready-to-run examples.
 
 <p align="center">
@@ -105,11 +103,11 @@ The **gt** package joins a burgeoning collection of packages for display table g
 
 While **gt** is trying to do something different with its own interface, it may not suit your specific needs. Here is a listing of leading table-making **R** packages, with links to their respective project pages:
 
-**kable**&nbsp;([GITHUB](https://github.com/yihui/knitr),&nbsp;[WEBSITE](https://yihui.org/knitr/))&nbsp;&mdash; **kableExtra**&nbsp;([GITHUB](https://github.com/haozhu233/kableExtra),&nbsp;[WEBSITE](https://haozhu233.github.io/kableExtra/))&nbsp;&mdash; **formattable**&nbsp;([GITHUB](https://github.com/renkun-ken/formattable),&nbsp;[WEBSITE](https://renkun-ken.github.io/formattable/))&nbsp;&mdash; **DT**&nbsp;([GITHUB](https://github.com/rstudio/DT),&nbsp;[WEBSITE](https://rstudio.github.io/DT/))&nbsp;&mdash; **pander**&nbsp;([GITHUB](https://github.com/Rapporter/pander),&nbsp;[WEBSITE](http://rapporter.github.io/pander))&nbsp;&mdash; **huxtable**&nbsp;([GITHUB](https://github.com/hughjonesd/huxtable),&nbsp;[WEBSITE](https://hughjonesd.github.io/huxtable/))&nbsp;&mdash; **reactable**&nbsp;([GITHUB](https://github.com/glin/reactable),&nbsp;[WEBSITE](https://glin.github.io/reactable/))&nbsp;&mdash; **flextable**&nbsp;([GITHUB](https://github.com/davidgohel/flextable),&nbsp;[WEBSITE](https://davidgohel.github.io/flextable/))&nbsp;&mdash; **pixiedust**&nbsp;([GITHUB](https://github.com/nutterb/pixiedust))&nbsp;&mdash; **tangram**&nbsp;([GITHUB](https://github.com/spgarbet/tangram))&nbsp;&mdash; **ztable**&nbsp;([GITHUB](https://github.com/cardiomoon/ztable))&nbsp;&mdash; **condformat**&nbsp;([GITHUB](https://github.com/zeehio/condformat))&nbsp;&mdash; **stargazer**&nbsp;([CRAN](https://CRAN.R-project.org/package=stargazer))&nbsp;&mdash; **xtable**&nbsp;([CRAN](https://CRAN.R-project.org/package=xtable))
+**knitr**&nbsp;([GITHUB](https://github.com/yihui/knitr),&nbsp;[WEBSITE](https://yihui.org/knitr/))&nbsp;&mdash; **kableExtra**&nbsp;([GITHUB](https://github.com/haozhu233/kableExtra),&nbsp;[WEBSITE](https://haozhu233.github.io/kableExtra/))&nbsp;&mdash; **formattable**&nbsp;([GITHUB](https://github.com/renkun-ken/formattable),&nbsp;[WEBSITE](https://renkun-ken.github.io/formattable/))&nbsp;&mdash; **DT**&nbsp;([GITHUB](https://github.com/rstudio/DT),&nbsp;[WEBSITE](https://rstudio.github.io/DT/))&nbsp;&mdash; **pander**&nbsp;([GITHUB](https://github.com/Rapporter/pander),&nbsp;[WEBSITE](http://rapporter.github.io/pander))&nbsp;&mdash; **huxtable**&nbsp;([GITHUB](https://github.com/hughjonesd/huxtable),&nbsp;[WEBSITE](https://hughjonesd.github.io/huxtable/))&nbsp;&mdash; **reactable**&nbsp;([GITHUB](https://github.com/glin/reactable),&nbsp;[WEBSITE](https://glin.github.io/reactable/))&nbsp;&mdash; **flextable**&nbsp;([GITHUB](https://github.com/davidgohel/flextable),&nbsp;[WEBSITE](https://davidgohel.github.io/flextable/))&nbsp;&mdash; **pixiedust**&nbsp;([GITHUB](https://github.com/nutterb/pixiedust))&nbsp;&mdash; **tangram**&nbsp;([GITHUB](https://github.com/spgarbet/tangram))&nbsp;&mdash; **ztable**&nbsp;([GITHUB](https://github.com/cardiomoon/ztable))&nbsp;&mdash; **condformat**&nbsp;([GITHUB](https://github.com/zeehio/condformat))&nbsp;&mdash; **stargazer**&nbsp;([CRAN](https://CRAN.R-project.org/package=stargazer))&nbsp;&mdash; **xtable**&nbsp;([CRAN](https://CRAN.R-project.org/package=xtable))
 
 #### Code of Conduct
 
-Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md).<br>By participating in this project you agree to abide by its terms.
+Please note that this project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/1/0/0).<br>By participating in this project you agree to abide by its terms.
 
 #### License
 
diff --git a/README.md b/README.md
index 2ee0892d5..e18b6817a 100644
--- a/README.md
+++ b/README.md
@@ -90,12 +90,6 @@ for experimenting with **gt**’s functions.
 Beyond this simple example, there are many functions available in **gt**
 for creating super-customized tables.
 
-<p align="center">
-
-<img src="man/figures/gt_function_reference.png" width="100%">
-
-</p>
-
 Want to try this out? Then, take the **gt** Test Drive on **RStudio
 Cloud**. It’s full of ready-to-run examples.
 
@@ -148,7 +142,7 @@ it may not suit your specific needs. Here is a listing of leading
 table-making **R** packages, with links to their respective project
 pages:
 
-**kable** ([GITHUB](https://github.com/yihui/knitr), [WEBSITE](https://yihui.org/knitr/)) —
+**knitr** ([GITHUB](https://github.com/yihui/knitr), [WEBSITE](https://yihui.org/knitr/)) —
 **kableExtra** ([GITHUB](https://github.com/haozhu233/kableExtra), [WEBSITE](https://haozhu233.github.io/kableExtra/)) —
 **formattable** ([GITHUB](https://github.com/renkun-ken/formattable), [WEBSITE](https://renkun-ken.github.io/formattable/)) —
 **DT** ([GITHUB](https://github.com/rstudio/DT), [WEBSITE](https://rstudio.github.io/DT/)) —
@@ -166,8 +160,8 @@ pages:
 #### Code of Conduct
 
 Please note that this project is released with a [Contributor Code of
-Conduct](CODE_OF_CONDUCT.md).<br>By participating in this project you
-agree to abide by its terms.
+Conduct](https://contributor-covenant.org/version/1/0/0).<br>By
+participating in this project you agree to abide by its terms.
 
 #### License
 
diff --git a/_pkgdown.yml b/_pkgdown.yml
index f71620eaa..2d6941e8d 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -241,4 +241,4 @@ navbar:
     href: https://github.com/rstudio/gt
 
 development:
-  mode: unreleased
+  mode: release
diff --git a/man/cols_width.Rd b/man/cols_width.Rd
index 7cd5d8a88..3af30a837 100644
--- a/man/cols_width.Rd
+++ b/man/cols_width.Rd
@@ -57,8 +57,9 @@ favor of the pixel values set for each column.
 # Use `exibble` to create a gt table;
 # with named arguments in `...`, we
 # can specify the exact widths for
-# table columns (using `TRUE` will
-# capture all remaining columns)
+# table columns (using `everything()`
+# or `TRUE` at the end will capture
+# all remaining columns)
 tab_1 <-
   exibble \%>\%
   dplyr::select(
@@ -70,7 +71,7 @@ tab_1 <-
     vars(num) ~ px(150),
     ends_with("r") ~ px(100),
     starts_with("date") ~ px(200),
-    TRUE ~ px(60)
+    everything() ~ px(60)
   )
 
 }
diff --git a/man/figures/gt_function_reference.png b/man/figures/gt_function_reference.png
deleted file mode 100644
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diff --git a/man/gt_output.Rd b/man/gt_output.Rd
index 1913fe0e8..06ba97dd2 100644
--- a/man/gt_output.Rd
+++ b/man/gt_output.Rd
@@ -62,7 +62,7 @@ server <- function(input,
     )
 }
 
-\dontrun{
+\donttest{
 shinyApp(ui, server)
 }
 
diff --git a/man/gtsave.Rd b/man/gtsave.Rd
index cc020a1a6..de7ebf11d 100644
--- a/man/gtsave.Rd
+++ b/man/gtsave.Rd
@@ -58,7 +58,7 @@ to \code{...}.
 }
 
 \examples{
-\dontrun{
+\donttest{
 # Use `gtcars` to create a gt table; add
 # a stubhead label to describe what is
 # in the stub
@@ -67,32 +67,37 @@ tab_1 <-
   dplyr::select(model, year, hp, trq) \%>\%
   dplyr::slice(1:5) \%>\%
   gt(rowname_col = "model") \%>\%
-  tab_stubhead_label(label = "car")
+  tab_stubhead(label = "car")
 
 # Get an HTML file with inlined CSS
 # (which is necessary for including the
 # table as part of an HTML email)
 tab_1 \%>\%
-  gtsave("tab_1.html", inline_css = TRUE)
+  gtsave(
+    "tab_1.html", inline_css = TRUE,
+    path = tempdir()
+  )
 
 # By leaving out the `inline_css` option,
 # we get a more conventional HTML file
 # with embedded CSS styles
-tab_1 \%>\% gtsave("tab_1.html")
-
-# Save the HTML table as a PDF file; we
-# can optionally add a separate `path`
-tab_1 \%>\% gtsave("tab_1.pdf", path = "~")
+tab_1 \%>\%
+  gtsave("tab_1.html", path = tempdir())
 
 # Saving as PNG file results in a cropped
 # image of an HTML table; the amount of
 # whitespace can be set
-tab_1 \%>\% gtsave("tab_1.png", expand = 10)
+tab_1 \%>\%
+  gtsave(
+    "tab_1.png", expand = 10,
+    path = tempdir()
+  )
 
 # Any use of the `.tex`, `.ltx`, or `.rnw`
 # will result in the output of a LaTeX
 # document
-tab_1 \%>\% gtsave("tab_1.tex")
+tab_1 \%>\%
+  gtsave("tab_1.tex", path = tempdir())
 }
 
 }
diff --git a/man/opt_row_striping.Rd b/man/opt_row_striping.Rd
index 8ebd374e8..070a787ee 100644
--- a/man/opt_row_striping.Rd
+++ b/man/opt_row_striping.Rd
@@ -35,7 +35,7 @@ body. This function serves as a convenient shortcut for
 # Use `exibble` to create a gt table with
 # a number of table parts added; next, we
 # add row striping to every second row with
-# the `opt_add_row_striping()` function
+# the `opt_row_striping()` function
 tab_1 <-
   exibble \%>\%
   gt(rowname_col = "row", groupname_col = "group") \%>\%
diff --git a/man/render_gt.Rd b/man/render_gt.Rd
index a1bd07742..88417db00 100644
--- a/man/render_gt.Rd
+++ b/man/render_gt.Rd
@@ -91,7 +91,7 @@ server <- function(input,
     )
 }
 
-\dontrun{
+\donttest{
 shinyApp(ui, server)
 }
 

From 34914cd25ec0497014f5bb13ff0d7d90c468391c Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Tue, 31 Mar 2020 14:05:45 -0400
Subject: [PATCH 05/30] Change pkg version number to dev version

---
 DESCRIPTION | 2 +-
 NEWS.md     | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index c1915841a..64d3c7203 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Type: Package
 Package: gt
-Version: 0.2.0.5
+Version: 0.2.0.9000
 Title: Easily Create Presentation-Ready Display Tables
 Description: Build display tables from tabular data using with an easy-to-use
     API. With its progressive approach, we can construct display tables with a
diff --git a/NEWS.md b/NEWS.md
index e79532980..6085e16ec 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,5 @@
+# gt 0.2.0.9000 (in development)
+
 # gt 0.2.0.5
 
 * New package with 80 exported functions for building display tables

From f02aaae563d1a96c2762e1600018edfe1b758eda Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 3 Apr 2020 14:35:27 -0400
Subject: [PATCH 06/30] Rebuild for pkgdown

---
 .gitignore                                    |    2 +-
 R/export.R                                    |    2 -
 R/shiny.R                                     |    8 +-
 _pkgdown.yml                                  |    2 +-
 docs/404.html                                 |  173 +
 docs/CODE_OF_CONDUCT.html                     |  181 +
 docs/CONTRIBUTING.html                        |  203 +
 docs/ISSUE_TEMPLATE.html                      |  181 +
 docs/LICENSE-text.html                        |  175 +
 docs/LICENSE.html                             |  179 +
 docs/apple-touch-icon-120x120.png             |  Bin 0 -> 17140 bytes
 docs/apple-touch-icon-152x152.png             |  Bin 0 -> 24241 bytes
 docs/apple-touch-icon-180x180.png             |  Bin 0 -> 30755 bytes
 docs/apple-touch-icon-60x60.png               |  Bin 0 -> 6325 bytes
 docs/apple-touch-icon-76x76.png               |  Bin 0 -> 8855 bytes
 docs/apple-touch-icon.png                     |  Bin 0 -> 30755 bytes
 docs/articles/case-study-gtcars.html          | 7122 +++++++++++++++++
 docs/articles/creating-summary-lines.html     | 5801 ++++++++++++++
 docs/articles/gt-datasets.html                | 5507 +++++++++++++
 docs/articles/index.html                      |  178 +
 docs/articles/intro-creating-gt-tables.html   | 5299 ++++++++++++
 docs/authors.html                             |  184 +
 docs/bootstrap-toc.css                        |   60 +
 docs/bootstrap-toc.js                         |  159 +
 docs/docsearch.css                            |  148 +
 docs/docsearch.js                             |   85 +
 docs/favicon-16x16.png                        |  Bin 0 -> 1441 bytes
 docs/favicon-32x32.png                        |  Bin 0 -> 2818 bytes
 docs/favicon.ico                              |  Bin 0 -> 15086 bytes
 docs/index.html                               |  255 +
 docs/link.svg                                 |   12 +
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 create mode 100644 docs/reference/tab_source_note.html
 create mode 100644 docs/reference/tab_spanner.html
 create mode 100644 docs/reference/tab_spanner_delim.html
 create mode 100644 docs/reference/tab_stubhead.html
 create mode 100644 docs/reference/tab_style.html
 create mode 100644 docs/reference/test_image.html
 create mode 100644 docs/reference/text_transform.html
 create mode 100644 docs/reference/web_image.html
 create mode 100644 docs/sitemap.xml

diff --git a/.gitignore b/.gitignore
index c3bb66933..f39cb0520 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,7 +3,7 @@
 .Rapp.history
 
 # Docs folder from `pkgdown::build_site()`
-docs/
+docs/dev/
 inst/doc
 
 # Session Data files
diff --git a/R/export.R b/R/export.R
index f218e7b76..535501b03 100644
--- a/R/export.R
+++ b/R/export.R
@@ -41,7 +41,6 @@
 #'   function.
 #'
 #' @examples
-#' \donttest{
 #' # Use `gtcars` to create a gt table; add
 #' # a stubhead label to describe what is
 #' # in the stub
@@ -81,7 +80,6 @@
 #' # document
 #' tab_1 %>%
 #'   gtsave("tab_1.tex", path = tempdir())
-#' }
 #'
 #' @family Export Functions
 #' @section Function ID:
diff --git a/R/shiny.R b/R/shiny.R
index 5cae81f54..419b76785 100644
--- a/R/shiny.R
+++ b/R/shiny.R
@@ -64,8 +64,8 @@
 #'     )
 #' }
 #'
-#' \donttest{
-#' shinyApp(ui, server)
+#' if (interactive()) {
+#'   shinyApp(ui, server)
 #' }
 #'
 #' @family Shiny functions
@@ -184,8 +184,8 @@ render_gt <- function(expr,
 #'     )
 #' }
 #'
-#' \donttest{
-#' shinyApp(ui, server)
+#' if (interactive()) {
+#'   shinyApp(ui, server)
 #' }
 #'
 #' @family Shiny functions
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 2d6941e8d..c81a209be 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -241,4 +241,4 @@ navbar:
     href: https://github.com/rstudio/gt
 
 development:
-  mode: release
+  mode: auto
diff --git a/docs/404.html b/docs/404.html
new file mode 100644
index 000000000..552ebe5ad
--- /dev/null
+++ b/docs/404.html
@@ -0,0 +1,173 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Page not found (404) • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="https://gt.rstudio.com/favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="https://gt.rstudio.com/favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="https://gt.rstudio.com/apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="https://gt.rstudio.com/apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="https://gt.rstudio.com/apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="https://gt.rstudio.com/apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="https://gt.rstudio.com/bootstrap-toc.css">
+<script src="https://gt.rstudio.com/bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="https://gt.rstudio.com/pkgdown.css" rel="stylesheet">
+<script src="https://gt.rstudio.com/pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Page not found (404)" />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-title-body">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="https://gt.rstudio.com/index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="contents col-md-9">
+    <div class="page-header">
+      <h1>Page not found (404)</h1>
+    </div>
+
+Content not found. Please use links in the navbar.
+
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+
+</div>
+
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/CODE_OF_CONDUCT.html b/docs/CODE_OF_CONDUCT.html
new file mode 100644
index 000000000..7f7bdb9e7
--- /dev/null
+++ b/docs/CODE_OF_CONDUCT.html
@@ -0,0 +1,181 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Contributor Code of Conduct • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="bootstrap-toc.css">
+<script src="bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="pkgdown.css" rel="stylesheet">
+<script src="pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Contributor Code of Conduct" />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-title-body">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="contents col-md-9">
+    <div class="page-header">
+      <h1>Contributor Code of Conduct</h1>
+    </div>
+
+<div id="contributor-code-of-conduct" class="section level1">
+
+<p>As contributors and maintainers of this project, we pledge to respect all people who contribute through reporting issues, posting feature requests, updating documentation, submitting pull requests or patches, and other activities.</p>
+<p>We are committed to making participation in this project a harassment-free experience for everyone, regardless of level of experience, gender, gender identity and expression, sexual orientation, disability, personal appearance, body size, race, ethnicity, age, or religion.</p>
+<p>Examples of unacceptable behavior by participants include the use of sexual language or imagery, derogatory comments or personal attacks, trolling, public or private harassment, insults, or other unprofessional conduct.</p>
+<p>Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct. Project maintainers who do not follow the Code of Conduct may be removed from the project team.</p>
+<p>Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by opening an issue or contacting one or more of the project maintainers.</p>
+<p>This Code of Conduct is adapted from the Contributor Covenant (<a href="http://contributor-covenant.org" class="uri">http://contributor-covenant.org</a>), version 1.0.0, available at <a href="http://contributor-covenant.org/version/1/0/0/" class="uri">http://contributor-covenant.org/version/1/0/0/</a></p>
+</div>
+
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+
+</div>
+
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/CONTRIBUTING.html b/docs/CONTRIBUTING.html
new file mode 100644
index 000000000..4fbbe35ba
--- /dev/null
+++ b/docs/CONTRIBUTING.html
@@ -0,0 +1,203 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Information and Guidelines for Contributing to gt • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="bootstrap-toc.css">
+<script src="bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
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+    <div class="page-header">
+      <h1>Information and Guidelines for Contributing to gt</h1>
+    </div>
+
+<div id="information-and-guidelines-for-contributing-to-gt" class="section level1">
+
+<p>There are many ways to contribute to the ongoing development of the <strong>gt</strong> package. Some contributions can be rather easy to do (e.g., fixing typos, improving documentation, filing issues for feature requests or problems, etc.) whereas other contributions can require more time and patience (like answering questions and submitting pull requests with code changes). Just know that that help provided in any capacity is very much appreciated. :)</p>
+<div id="filing-issues" class="section level2">
+<h2 class="hasAnchor">
+<a href="#filing-issues" class="anchor"></a>Filing Issues</h2>
+<p>If you believe you found a bug, create a minimal <a href="https://reprex.tidyverse.org">reprex</a> for your posting to the <a href="https://github.com/rstudio/gt/issues"><strong>gt</strong> issue tracker</a>. Try not to include anything unnecessary, just the minimal amount of code that constitutes the reproducible bug. We will try to verify the bug by running the code in the reprex provided. The quality of the reprex will reduce the amount of back-and-forth communication in trying to understand how to execute the code on our systems.</p>
+</div>
+<div id="answering-questions" class="section level2">
+<h2 class="hasAnchor">
+<a href="#answering-questions" class="anchor"></a>Answering questions</h2>
+<p>A great way to help is by simply answering questions. It’s amazing how a little conversation could lead to better insights on a problem. Don’t quite know the answer? That’s okay too. We’re all in this together.</p>
+<p>Where might you answer user questions? Some of the forums for Q&amp;A on <strong>gt</strong> include the <a href="https://community.rstudio.com">RStudio community</a>, on Twitter (a good search term is <code>gt #rstats</code>), and on <a href="https://stackoverflow.com">Stack Overflow</a>. Good etiquette is key during these interactions: be a good person to all who ask questions.</p>
+<div id="making-pull-requests" class="section level3">
+<h3 class="hasAnchor">
+<a href="#making-pull-requests" class="anchor"></a>Making Pull Requests</h3>
+<p>Should you consider making a pull request (PR), please file an issue first and explain the problem in some detail. If the PR is an enhancement, detail how the change would make things better for package users. Bugfix PRs also requre some explanation about the bug and how the proposed fix will remove that bug. A great way to illustrate the bug is to include a <a href="https://reprex.tidyverse.org">reprex</a>. While all this upfront work prior to preparing a PR can be time-consuming it opens a line of communication with the package authors and the community, perhaps leading to better enhancement or more effective fixes!</p>
+<p>Once there is consensus that a PR based on the issue would be helpful, adhering to the following process will make things proceed more quickly:</p>
+<ul>
+<li>Create a separate Git branch for each PR.</li>
+<li>Look at the Travis and AppVeyor build status badges before and after making changes; these badges are available in the package <a href="https://github.com/rstudio/gt">README</a>.<br>
+</li>
+<li>The <strong>gt</strong> package follows the tidyverse <a href="http://style.tidyverse.org">style guide</a> so please adopt those style guidelines in your submitted code as best as possible.</li>
+<li>The internal documentation uses <a href="https://cran.r-project.org/web/packages/roxygen2/vignettes/roxygen2.html">roxygen2</a>; if your contribution requires new or revised documentation ensure that the roxygen comments are added/modified (do not modify any <code>.Rd</code> files in the <code>man</code> folder).</li>
+<li>We use <a href="https://cran.r-project.org/web/packages/testthat/">testthat</a> for code coverage; those contributions with test cases included are helpful easier to accept.</li>
+<li>Add a bullet to the top of <code>NEWS.md</code> below the current development version header describing any user-facing changes made; include your GitHub username, and links to relevant issue(s)/PR(s).</li>
+<li>Ensure that you have signed the contributor license agreement. It will appear as a “Check” on your PR and a comment from “CLAassistant” will also appear explaining whether you have yet to sign. After you sign, you can click the “Recheck” link in that comment and the check will flip to reflect that you’ve signed.</li>
+</ul>
+</div>
+</div>
+</div>
+
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+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+    </nav>
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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+      <a href="articles/gt-datasets.html">gt Datasets</a>
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+
+<p>Please briefly describe your problem or your ideas for enhancement in the template below.</p>
+<p>Have a question? Please don’t use this form but instead ask on <a href="https://community.rstudio.com">RStudio community</a>, on <a href="https://stackoverflow.com">Stack Overflow</a>, or on Twitter (using the <code>#rstats</code> hashtag).</p>
+<p>When describing a bug, please include a minimal reproducible example (otherwise known as a <a href="http://reprex.tidyverse.org/">reprex</a>).</p>
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+<div class="sourceCode" id="cb1"><html><pre class="r"><insert reprex here></insert></pre></html></div>
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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+      <span class="navbar-brand">
+        <a class="navbar-link" href="index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="contents col-md-9">
+    <div class="page-header">
+      <h1>License</h1>
+    </div>
+
+<pre>YEAR: 2018-2020
+COPYRIGHT HOLDER: RStudio, PBC
+</pre>
+
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+
+</div>
+
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/LICENSE.html b/docs/LICENSE.html
new file mode 100644
index 000000000..bfaa91ddb
--- /dev/null
+++ b/docs/LICENSE.html
@@ -0,0 +1,179 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="pkgdown.css" rel="stylesheet">
+<script src="pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="NA" />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
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+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-title-body">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="articles/intro-creating-gt-tables.html">Intro</a>
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+<li>
+  <a href="reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="contents col-md-9">
+    <div class="page-header">
+      <h1>NA</h1>
+    </div>
+
+
+<p>The MIT License (MIT)</p>
+<p>Copyright (c) 2018-2020 RStudio, PBC</p>
+<p>Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:</p>
+<p>The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.</p>
+<p>THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</p>
+
+
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+
+</div>
+
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
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+      <h1 data-toc-skip>Case Study: gtcars</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/rstudio/gt/blob/master/vignettes/case-study-gtcars.Rmd"><code>vignettes/case-study-gtcars.Rmd</code></a></small>
+      <div class="hidden name"><code>case-study-gtcars.Rmd</code></div>
+
+    </div>
+
+    
+    
+<p align="center">
+<img src="images/gtcars.svg" width="50%"></p>
+<p>Let’s make a display table using the <code>gtcars</code> dataset. We all know <code>mtcars</code>… what is <code>gtcars</code>? It’s basically a modernized <code>mtcars</code> for the <strong>gt</strong> age. It’s part of the <strong>gt</strong> package, and here is a preview of the tibble:</p>
+<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># This is `gtcars`</span>
+<span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">glimpse</a></span>(<span class="no">gtcars</span>)
+<span class="co">#&gt; Rows: 47</span>
+<span class="co">#&gt; Columns: 15</span>
+<span class="co">#&gt; $ mfr         &lt;chr&gt; "Ford", "Ferrari", "Ferrari", "Ferrari", "Ferrari", "Ferr…</span>
+<span class="co">#&gt; $ model       &lt;chr&gt; "GT", "458 Speciale", "458 Spider", "458 Italia", "488 GT…</span>
+<span class="co">#&gt; $ year        &lt;dbl&gt; 2017, 2015, 2015, 2014, 2016, 2015, 2017, 2015, 2015, 201…</span>
+<span class="co">#&gt; $ trim        &lt;chr&gt; "Base Coupe", "Base Coupe", "Base", "Base Coupe", "Base C…</span>
+<span class="co">#&gt; $ bdy_style   &lt;chr&gt; "coupe", "coupe", "convertible", "coupe", "coupe", "conve…</span>
+<span class="co">#&gt; $ hp          &lt;dbl&gt; 647, 597, 562, 562, 661, 553, 680, 652, 731, 949, 573, 54…</span>
+<span class="co">#&gt; $ hp_rpm      &lt;dbl&gt; 6250, 9000, 9000, 9000, 8000, 7500, 8250, 8000, 8250, 900…</span>
+<span class="co">#&gt; $ trq         &lt;dbl&gt; 550, 398, 398, 398, 561, 557, 514, 504, 509, 664, 476, 43…</span>
+<span class="co">#&gt; $ trq_rpm     &lt;dbl&gt; 5900, 6000, 6000, 6000, 3000, 4750, 5750, 6000, 6000, 675…</span>
+<span class="co">#&gt; $ mpg_c       &lt;dbl&gt; 11, 13, 13, 13, 15, 16, 12, 11, 11, 12, 21, 16, 11, 16, 1…</span>
+<span class="co">#&gt; $ mpg_h       &lt;dbl&gt; 18, 17, 17, 17, 22, 23, 17, 16, 16, 16, 22, 22, 18, 20, 2…</span>
+<span class="co">#&gt; $ drivetrain  &lt;chr&gt; "rwd", "rwd", "rwd", "rwd", "rwd", "rwd", "awd", "awd", "…</span>
+<span class="co">#&gt; $ trsmn       &lt;chr&gt; "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a…</span>
+<span class="co">#&gt; $ ctry_origin &lt;chr&gt; "United States", "Italy", "Italy", "Italy", "Italy", "Ita…</span>
+<span class="co">#&gt; $ msrp        &lt;dbl&gt; 447000, 291744, 263553, 233509, 245400, 198973, 298000, 2…</span></pre></body></html></div>
+<p>For the purpose of simply learning more about <strong>gt</strong>, let’s reduce this 47-row tibble to one that has only 8 rows:</p>
+<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Get a subset of 8 cars from the `gtcars` dataset: two</span>
+<span class="co"># from each manufacturer country of origin except the UK</span>
+<span class="no">gtcars_8</span> <span class="kw">&lt;-</span>
+  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/top_n.html">top_n</a></span>(<span class="fl">2</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">ungroup</a></span>() <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">ctry_origin</span> <span class="kw">!=</span> <span class="st">"United Kingdom"</span>)
+<span class="co">#&gt; Selecting by msrp</span>
+
+<span class="co"># Show the `gtcars_8` tibble</span>
+<span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">glimpse</a></span>(<span class="no">gtcars_8</span>)
+<span class="co">#&gt; Rows: 8</span>
+<span class="co">#&gt; Columns: 15</span>
+<span class="co">#&gt; $ mfr         &lt;chr&gt; "Ford", "Ferrari", "Acura", "Nissan", "Lamborghini", "BMW…</span>
+<span class="co">#&gt; $ model       &lt;chr&gt; "GT", "LaFerrari", "NSX", "GT-R", "Aventador", "i8", "Vip…</span>
+<span class="co">#&gt; $ year        &lt;dbl&gt; 2017, 2015, 2017, 2016, 2015, 2016, 2017, 2016</span>
+<span class="co">#&gt; $ trim        &lt;chr&gt; "Base Coupe", "Base Coupe", "Base Coupe", "Premium Coupe"…</span>
+<span class="co">#&gt; $ bdy_style   &lt;chr&gt; "coupe", "coupe", "coupe", "coupe", "coupe", "coupe", "co…</span>
+<span class="co">#&gt; $ hp          &lt;dbl&gt; 647, 949, 573, 545, 700, 357, 645, 503</span>
+<span class="co">#&gt; $ hp_rpm      &lt;dbl&gt; 6250, 9000, 6500, 6400, 8250, 5800, 5000, 6250</span>
+<span class="co">#&gt; $ trq         &lt;dbl&gt; 550, 664, 476, 436, 507, 420, 600, 479</span>
+<span class="co">#&gt; $ trq_rpm     &lt;dbl&gt; 5900, 6750, 2000, 3200, 5500, 3700, 5000, 1750</span>
+<span class="co">#&gt; $ mpg_c       &lt;dbl&gt; 11, 12, 21, 16, 11, 28, 12, 16</span>
+<span class="co">#&gt; $ mpg_h       &lt;dbl&gt; 18, 16, 22, 22, 18, 29, 19, 22</span>
+<span class="co">#&gt; $ drivetrain  &lt;chr&gt; "rwd", "rwd", "awd", "awd", "awd", "awd", "rwd", "rwd"</span>
+<span class="co">#&gt; $ trsmn       &lt;chr&gt; "7a", "7a", "9a", "6a", "7a", "6am", "6m", "7a"</span>
+<span class="co">#&gt; $ ctry_origin &lt;chr&gt; "United States", "Italy", "Japan", "Japan", "Italy", "Ger…</span>
+<span class="co">#&gt; $ msrp        &lt;dbl&gt; 447000, 1416362, 156000, 101770, 397500, 140700, 95895, 1…</span></pre></body></html></div>
+<p>Let’s make a display table from this dataset. In doing so we’ll fulfill the following 10 requirements:</p>
+<ol style="list-style-type: decimal">
+<li>putting the cars into characteristic groups (by the car manufacturer’s country of origin)</li>
+<li>removing some of the columns that we don’t want to present</li>
+<li>incorporating some columns into a column group</li>
+<li>formatting the currency data and using a monospaced font for easier reading of that data</li>
+<li>giving the table a title and a subtitle</li>
+<li>adding footnotes to draw attention to some of the more interesting data points and to explain some of the more unusual aspects of the data</li>
+<li>placing a citation for the dataset at the bottom of the table</li>
+<li>transforming the transmission (<code>trsmn</code>) codes so that they are readable and understandable</li>
+<li>styling some cells according to basic criteria</li>
+<li>highlighting the cars that are considered to be <em>grand tourers</em>
+</li>
+</ol>
+<div id="row-groups" class="section level3">
+<h3 class="hasAnchor">
+<a href="#row-groups" class="anchor"></a>Row Groups</h3>
+<p>Let’s again use <strong>dplyr</strong> to help make groupings by the <code>ctry_origin</code> column, which provides the country of origin for the vehicle manufacturer of the car. We can simply use <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">dplyr::group_by()</a></code> on the <code>gtcars</code> dataset and pass that to <code><a href="../reference/gt.html">gt()</a></code>. What you get is a display table that arranges the cars into row groups, with the name of the group displayed prominently above.</p>
+<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Use `group_by()` on `gtcars` and pass that to `gt()`</span>
+<span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#wdxgxlbuhb .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#wdxgxlbuhb .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#wdxgxlbuhb .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#wdxgxlbuhb .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#wdxgxlbuhb .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#wdxgxlbuhb .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#wdxgxlbuhb .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#wdxgxlbuhb .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#wdxgxlbuhb .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#wdxgxlbuhb .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#wdxgxlbuhb .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#wdxgxlbuhb .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#wdxgxlbuhb .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#wdxgxlbuhb .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#wdxgxlbuhb .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#wdxgxlbuhb .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#wdxgxlbuhb .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#wdxgxlbuhb .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#wdxgxlbuhb .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#wdxgxlbuhb .gt_left {
+  text-align: left;
+}
+
+#wdxgxlbuhb .gt_center {
+  text-align: center;
+}
+
+#wdxgxlbuhb .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#wdxgxlbuhb .gt_font_normal {
+  font-weight: normal;
+}
+
+#wdxgxlbuhb .gt_font_bold {
+  font-weight: bold;
+}
+
+#wdxgxlbuhb .gt_font_italic {
+  font-style: italic;
+}
+
+#wdxgxlbuhb .gt_super {
+  font-size: 65%;
+}
+
+#wdxgxlbuhb .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="wdxgxlbuhb" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">mfr</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">model</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Ford</td>
+      <td class="gt_row gt_left">GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">647</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">550</td>
+      <td class="gt_row gt_right">5900</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Dodge</td>
+      <td class="gt_row gt_left">Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">645</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">600</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">19</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Ferrari</td>
+      <td class="gt_row gt_left">LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">949</td>
+      <td class="gt_row gt_right">9000</td>
+      <td class="gt_row gt_right">664</td>
+      <td class="gt_row gt_right">6750</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Lamborghini</td>
+      <td class="gt_row gt_left">Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">700</td>
+      <td class="gt_row gt_right">8250</td>
+      <td class="gt_row gt_right">507</td>
+      <td class="gt_row gt_right">5500</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Acura</td>
+      <td class="gt_row gt_left">NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">573</td>
+      <td class="gt_row gt_right">6500</td>
+      <td class="gt_row gt_right">476</td>
+      <td class="gt_row gt_right">2000</td>
+      <td class="gt_row gt_right">21</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Nissan</td>
+      <td class="gt_row gt_left">GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">545</td>
+      <td class="gt_row gt_right">6400</td>
+      <td class="gt_row gt_right">436</td>
+      <td class="gt_row gt_right">3200</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">BMW</td>
+      <td class="gt_row gt_left">i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">357</td>
+      <td class="gt_row gt_right">5800</td>
+      <td class="gt_row gt_right">420</td>
+      <td class="gt_row gt_right">3700</td>
+      <td class="gt_row gt_right">28</td>
+      <td class="gt_row gt_right">29</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Mercedes-Benz</td>
+      <td class="gt_row gt_left">AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">503</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">479</td>
+      <td class="gt_row gt_right">1750</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+</tbody>
+</table></div>
+<p>Getting the row groups in the preferred order can be done easily with <strong>dplyr</strong>’s <code>arrange()</code> function. For example, we can have groups that are arranged alphabetically by manufacturer (<code>mfr</code>) and then sorted by highest sticker price (<code>msrp</code>) to lowest.</p>
+<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#lryaphwzlj .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#lryaphwzlj .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#lryaphwzlj .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#lryaphwzlj .gt_subtitle {
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+<div id="lryaphwzlj" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">mfr</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">model</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Acura</td>
+      <td class="gt_row gt_left">NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">573</td>
+      <td class="gt_row gt_right">6500</td>
+      <td class="gt_row gt_right">476</td>
+      <td class="gt_row gt_right">2000</td>
+      <td class="gt_row gt_right">21</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Nissan</td>
+      <td class="gt_row gt_left">GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">545</td>
+      <td class="gt_row gt_right">6400</td>
+      <td class="gt_row gt_right">436</td>
+      <td class="gt_row gt_right">3200</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">BMW</td>
+      <td class="gt_row gt_left">i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">357</td>
+      <td class="gt_row gt_right">5800</td>
+      <td class="gt_row gt_right">420</td>
+      <td class="gt_row gt_right">3700</td>
+      <td class="gt_row gt_right">28</td>
+      <td class="gt_row gt_right">29</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Mercedes-Benz</td>
+      <td class="gt_row gt_left">AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">503</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">479</td>
+      <td class="gt_row gt_right">1750</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Dodge</td>
+      <td class="gt_row gt_left">Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">645</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">600</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">19</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Ford</td>
+      <td class="gt_row gt_left">GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">647</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">550</td>
+      <td class="gt_row gt_right">5900</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Ferrari</td>
+      <td class="gt_row gt_left">LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">949</td>
+      <td class="gt_row gt_right">9000</td>
+      <td class="gt_row gt_right">664</td>
+      <td class="gt_row gt_right">6750</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Lamborghini</td>
+      <td class="gt_row gt_left">Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">700</td>
+      <td class="gt_row gt_right">8250</td>
+      <td class="gt_row gt_right">507</td>
+      <td class="gt_row gt_right">5500</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+</tbody>
+</table></div>
+<p>We could also use factor levels to get a more particular ordering within <code>arrange()</code>. For example, we can first arrange the groups themselves (the country of origin–<code>ctry_origin</code>) by our own preferred ordering and then arrange by <code>mfr</code> and descending <code>msrp</code> as before. Then, <code>group_by(ctry_origin)</code> can be used on the sorted tibble before passing this to <code><a href="../reference/gt.html">gt()</a></code>.</p>
+<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Define our preferred order `ctry_origin`</span>
+<span class="no">order_countries</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Germany"</span>, <span class="st">"Italy"</span>, <span class="st">"United States"</span>, <span class="st">"Japan"</span>)
+
+<span class="co"># Reorder the table rows by our specific ordering of groups</span>
+<span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(
+    <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="no">ctry_origin</span>, <span class="kw">levels</span> <span class="kw">=</span> <span class="no">order_countries</span>), <span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
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+  color: #333333;
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+  font-size: 100%;
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+  text-transform: inherit;
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+  padding-left: 0;
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+  border-bottom-style: solid;
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+  display: inline-block;
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+
+#abkybxrxxu .gt_group_heading {
+  padding: 8px;
+  color: #333333;
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+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
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+
+#abkybxrxxu .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
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+
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+}
+
+#abkybxrxxu .gt_stub {
+  color: #333333;
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+  font-size: 100%;
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+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
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+}
+
+#abkybxrxxu .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#abkybxrxxu .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#abkybxrxxu .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#abkybxrxxu .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#abkybxrxxu .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#abkybxrxxu .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#abkybxrxxu .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#abkybxrxxu .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#abkybxrxxu .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#abkybxrxxu .gt_left {
+  text-align: left;
+}
+
+#abkybxrxxu .gt_center {
+  text-align: center;
+}
+
+#abkybxrxxu .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#abkybxrxxu .gt_font_normal {
+  font-weight: normal;
+}
+
+#abkybxrxxu .gt_font_bold {
+  font-weight: bold;
+}
+
+#abkybxrxxu .gt_font_italic {
+  font-style: italic;
+}
+
+#abkybxrxxu .gt_super {
+  font-size: 65%;
+}
+
+#abkybxrxxu .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="abkybxrxxu" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">mfr</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">model</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">BMW</td>
+      <td class="gt_row gt_left">i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">357</td>
+      <td class="gt_row gt_right">5800</td>
+      <td class="gt_row gt_right">420</td>
+      <td class="gt_row gt_right">3700</td>
+      <td class="gt_row gt_right">28</td>
+      <td class="gt_row gt_right">29</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Mercedes-Benz</td>
+      <td class="gt_row gt_left">AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">503</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">479</td>
+      <td class="gt_row gt_right">1750</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Ferrari</td>
+      <td class="gt_row gt_left">LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">949</td>
+      <td class="gt_row gt_right">9000</td>
+      <td class="gt_row gt_right">664</td>
+      <td class="gt_row gt_right">6750</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Lamborghini</td>
+      <td class="gt_row gt_left">Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">700</td>
+      <td class="gt_row gt_right">8250</td>
+      <td class="gt_row gt_right">507</td>
+      <td class="gt_row gt_right">5500</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Dodge</td>
+      <td class="gt_row gt_left">Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">645</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">600</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">19</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Ford</td>
+      <td class="gt_row gt_left">GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">647</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">550</td>
+      <td class="gt_row gt_right">5900</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="14" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Acura</td>
+      <td class="gt_row gt_left">NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">573</td>
+      <td class="gt_row gt_right">6500</td>
+      <td class="gt_row gt_right">476</td>
+      <td class="gt_row gt_right">2000</td>
+      <td class="gt_row gt_right">21</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Nissan</td>
+      <td class="gt_row gt_left">GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">545</td>
+      <td class="gt_row gt_right">6400</td>
+      <td class="gt_row gt_right">436</td>
+      <td class="gt_row gt_right">3200</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+</tbody>
+</table></div>
+<p>The last variation is to combine the manufacturer name with the model name, using those combined strings as row labels for the table. This is just a little more <strong>dplyr</strong> where we can use <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">dplyr::mutate()</a></code> to make a new <code>car</code> column followed by <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> where we remove the <code>mfr</code> and <code>model</code> columns. When introducing the tibble to the <code><a href="../reference/gt.html">gt()</a></code> function, we can now use the <code>rowname_col</code> argument to specify a column that will serve as row labels (which is the newly made <code>car</code> column).</p>
+<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Reorder the table rows by our specific ordering of groups</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(
+    <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="no">ctry_origin</span>, <span class="kw">levels</span> <span class="kw">=</span> <span class="no">order_countries</span>),
+    <span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)
+    ) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">mfr</span>, -<span class="no">model</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"car"</span>)
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#iqocbggiwh .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#iqocbggiwh .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#iqocbggiwh .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#iqocbggiwh .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#iqocbggiwh .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#iqocbggiwh .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#iqocbggiwh .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#iqocbggiwh .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#iqocbggiwh .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#iqocbggiwh .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#iqocbggiwh .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#iqocbggiwh .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#iqocbggiwh .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#iqocbggiwh .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#iqocbggiwh .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#iqocbggiwh .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#iqocbggiwh .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#iqocbggiwh .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#iqocbggiwh .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#iqocbggiwh .gt_left {
+  text-align: left;
+}
+
+#iqocbggiwh .gt_center {
+  text-align: center;
+}
+
+#iqocbggiwh .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#iqocbggiwh .gt_font_normal {
+  font-weight: normal;
+}
+
+#iqocbggiwh .gt_font_bold {
+  font-weight: bold;
+}
+
+#iqocbggiwh .gt_font_italic {
+  font-style: italic;
+}
+
+#iqocbggiwh .gt_super {
+  font-size: 65%;
+}
+
+#iqocbggiwh .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="iqocbggiwh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="13" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">357</td>
+      <td class="gt_row gt_right">5800</td>
+      <td class="gt_row gt_right">420</td>
+      <td class="gt_row gt_right">3700</td>
+      <td class="gt_row gt_right">28</td>
+      <td class="gt_row gt_right">29</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">503</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">479</td>
+      <td class="gt_row gt_right">1750</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="13" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">949</td>
+      <td class="gt_row gt_right">9000</td>
+      <td class="gt_row gt_right">664</td>
+      <td class="gt_row gt_right">6750</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">700</td>
+      <td class="gt_row gt_right">8250</td>
+      <td class="gt_row gt_right">507</td>
+      <td class="gt_row gt_right">5500</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="13" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">645</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">600</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">19</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">647</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">550</td>
+      <td class="gt_row gt_right">5900</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_left">rwd</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="13" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">573</td>
+      <td class="gt_row gt_right">6500</td>
+      <td class="gt_row gt_right">476</td>
+      <td class="gt_row gt_right">2000</td>
+      <td class="gt_row gt_right">21</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">coupe</td>
+      <td class="gt_row gt_right">545</td>
+      <td class="gt_row gt_right">6400</td>
+      <td class="gt_row gt_right">436</td>
+      <td class="gt_row gt_right">3200</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_left">awd</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="hiding-and-moving-some-columns" class="section level3">
+<h3 class="hasAnchor">
+<a href="#hiding-and-moving-some-columns" class="anchor"></a>Hiding and Moving Some Columns</h3>
+<p>Let’s hide two columns that we don’t need to the final table: <code>drivetrain</code> and <code>bdy_style</code>. We can use the <code><a href="../reference/cols_hide.html">cols_hide()</a></code> function to hide columns. The same end result might also have been achieved by using <code>gtcars %&gt;% dplyr::select(-c(drivetrain, bdy_style))</code>, before introducing the table to <code><a href="../reference/gt.html">gt()</a></code>. Why this function then? Sometimes you’ll need variables for conditional statements within <strong>gt</strong> but won’t want to display them in the end.</p>
+<p>Aside from hiding columns, let’s <em>move</em> some of them. Again, this could be done with <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> but there are options here in <strong>gt</strong> via the <code><a href="../reference/cols_move_to_start.html">cols_move_to_start()</a></code>, <code><a href="../reference/cols_move.html">cols_move()</a></code>, and <code><a href="../reference/cols_move_to_end.html">cols_move_to_end()</a></code> functions.</p>
+<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># Use a few `cols_*()` functions to hide and move columns </span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_hide.html">cols_hide</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>, <span class="no">bdy_style</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_move.html">cols_move</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
+    <span class="kw">after</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>)
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#euyfsfmrya .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#euyfsfmrya .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#euyfsfmrya .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#euyfsfmrya .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#euyfsfmrya .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#euyfsfmrya .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#euyfsfmrya .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#euyfsfmrya .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#euyfsfmrya .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#euyfsfmrya .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#euyfsfmrya .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#euyfsfmrya .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#euyfsfmrya .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#euyfsfmrya .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#euyfsfmrya .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#euyfsfmrya .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#euyfsfmrya .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#euyfsfmrya .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#euyfsfmrya .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#euyfsfmrya .gt_left {
+  text-align: left;
+}
+
+#euyfsfmrya .gt_center {
+  text-align: center;
+}
+
+#euyfsfmrya .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#euyfsfmrya .gt_font_normal {
+  font-weight: normal;
+}
+
+#euyfsfmrya .gt_font_bold {
+  font-weight: bold;
+}
+
+#euyfsfmrya .gt_font_italic {
+  font-style: italic;
+}
+
+#euyfsfmrya .gt_super {
+  font-size: 65%;
+}
+
+#euyfsfmrya .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="euyfsfmrya" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">28</td>
+      <td class="gt_row gt_right">29</td>
+      <td class="gt_row gt_right">357</td>
+      <td class="gt_row gt_right">5800</td>
+      <td class="gt_row gt_right">420</td>
+      <td class="gt_row gt_right">3700</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_right">503</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">479</td>
+      <td class="gt_row gt_right">1750</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">949</td>
+      <td class="gt_row gt_right">9000</td>
+      <td class="gt_row gt_right">664</td>
+      <td class="gt_row gt_right">6750</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_right">700</td>
+      <td class="gt_row gt_right">8250</td>
+      <td class="gt_row gt_right">507</td>
+      <td class="gt_row gt_right">5500</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">19</td>
+      <td class="gt_row gt_right">645</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">600</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_right">647</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">550</td>
+      <td class="gt_row gt_right">5900</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">21</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_right">573</td>
+      <td class="gt_row gt_right">6500</td>
+      <td class="gt_row gt_right">476</td>
+      <td class="gt_row gt_right">2000</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_right">545</td>
+      <td class="gt_row gt_right">6400</td>
+      <td class="gt_row gt_right">436</td>
+      <td class="gt_row gt_right">3200</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="putting-columns-into-groups" class="section level3">
+<h3 class="hasAnchor">
+<a href="#putting-columns-into-groups" class="anchor"></a>Putting Columns Into Groups</h3>
+<p>It’s sometimes useful to arrange variables/columns into groups by using spanner column labels. This can be done in <strong>gt</strong> by using the <code><a href="../reference/tab_spanner.html">tab_spanner()</a></code> function. It takes the <code>label</code> and <code>columns</code> arguments; <code>label</code> is the spanner column label and the <code>columns</code> are those columns that belong in this group.</p>
+<p>Here, we’ll put the <code>mpg_c</code>, <code>mpg_h</code>, <code>hp</code>, <code>hp_rpm</code>, <code>trq</code>, <code>trq_rpm</code> columns under the <code>Performance</code> spanner column, and the remaining columns won’t be grouped together. This single spanner column label is styled with Markdown by using the <code><a href="../reference/md.html">md()</a></code> helper.</p>
+<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># Put the first three columns under a spanner</span>
+<span class="co"># column with the label 'Performance'</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
+    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Performance"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>, <span class="no">hp</span>, <span class="no">hp_rpm</span>, <span class="no">trq</span>, <span class="no">trq_rpm</span>)
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#ybltdcxcyx .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#ybltdcxcyx .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#ybltdcxcyx .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#ybltdcxcyx .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#ybltdcxcyx .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#ybltdcxcyx .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#ybltdcxcyx .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#ybltdcxcyx .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ybltdcxcyx .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ybltdcxcyx .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#ybltdcxcyx .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#ybltdcxcyx .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#ybltdcxcyx .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#ybltdcxcyx .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#ybltdcxcyx .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ybltdcxcyx .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ybltdcxcyx .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ybltdcxcyx .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ybltdcxcyx .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ybltdcxcyx .gt_left {
+  text-align: left;
+}
+
+#ybltdcxcyx .gt_center {
+  text-align: center;
+}
+
+#ybltdcxcyx .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#ybltdcxcyx .gt_font_normal {
+  font-weight: normal;
+}
+
+#ybltdcxcyx .gt_font_bold {
+  font-weight: bold;
+}
+
+#ybltdcxcyx .gt_font_italic {
+  font-style: italic;
+}
+
+#ybltdcxcyx .gt_super {
+  font-size: 65%;
+}
+
+#ybltdcxcyx .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="ybltdcxcyx" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">trsmn</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="6">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">msrp</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">mpg_c</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">mpg_h</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">hp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">hp_rpm</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">trq</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">trq_rpm</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">28</td>
+      <td class="gt_row gt_right">29</td>
+      <td class="gt_row gt_right">357</td>
+      <td class="gt_row gt_right">5800</td>
+      <td class="gt_row gt_right">420</td>
+      <td class="gt_row gt_right">3700</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_right">503</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">479</td>
+      <td class="gt_row gt_right">1750</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">949</td>
+      <td class="gt_row gt_right">9000</td>
+      <td class="gt_row gt_right">664</td>
+      <td class="gt_row gt_right">6750</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_right">700</td>
+      <td class="gt_row gt_right">8250</td>
+      <td class="gt_row gt_right">507</td>
+      <td class="gt_row gt_right">5500</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">12</td>
+      <td class="gt_row gt_right">19</td>
+      <td class="gt_row gt_right">645</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">600</td>
+      <td class="gt_row gt_right">5000</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11</td>
+      <td class="gt_row gt_right">18</td>
+      <td class="gt_row gt_right">647</td>
+      <td class="gt_row gt_right">6250</td>
+      <td class="gt_row gt_right">550</td>
+      <td class="gt_row gt_right">5900</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="11" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">21</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_right">573</td>
+      <td class="gt_row gt_right">6500</td>
+      <td class="gt_row gt_right">476</td>
+      <td class="gt_row gt_right">2000</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">16</td>
+      <td class="gt_row gt_right">22</td>
+      <td class="gt_row gt_right">545</td>
+      <td class="gt_row gt_right">6400</td>
+      <td class="gt_row gt_right">436</td>
+      <td class="gt_row gt_right">3200</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="merging-columns-together-and-labeling-them" class="section level3">
+<h3 class="hasAnchor">
+<a href="#merging-columns-together-and-labeling-them" class="anchor"></a>Merging Columns Together and Labeling Them</h3>
+<p>Sometimes we’d like to combine the data from two columns into a single column. The <code><a href="../reference/cols_merge.html">cols_merge()</a></code> function allows us to do this, we just need to describe how the data should be combined. For our table, let’s merge together the following pairs of columns:</p>
+<ul>
+<li>
+<code>mpg_c</code> and <code>mpg_h</code> (miles per gallon in city and highway driving modes)</li>
+<li>
+<code>hp</code> and <code>hp_rpm</code> (horsepower and associated RPM)</li>
+<li>
+<code>trq</code> and <code>trq_rpm</code> (torque and associated RPM)</li>
+</ul>
+<p>The <code><a href="../reference/cols_merge.html">cols_merge()</a></code> function uses a <code>col_1</code> column and a <code>col_2</code> column. Once combined, the <code>col_1</code> column will be retained and the <code>col_2</code> column will be dropped. The pattern argument uses <code>{1}</code> and <code>{2}</code> to represent the content of <code>col_1</code> and <code>col_2</code>. Here, we can use string literals to add text like <code>rpm</code> or the <code>@</code> sign. Furthermore, because we are targeting an HTML table, we can use the <code>&lt;br&gt;</code> tag to insert a linebreak.</p>
+<p>Labeling columns essentially means that we are choosing display-friendly labels that are no longer simply the column names (the default label). The <code><a href="../reference/cols_label.html">cols_label()</a></code> function makes this relabeling possible. It accepts a series of named arguments in the form of <code>&lt;column_name&gt; = &lt;column_label&gt;, ...</code>.</p>
+<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># Perform three column merges to better present</span>
+<span class="co"># MPG, HP, and torque; relabel all the remaining</span>
+<span class="co"># columns for a nicer-looking presentation</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_h</span>),
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}c&lt;br&gt;{2}h"</span>
+    ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp</span>, <span class="no">hp_rpm</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp_rpm</span>),
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq</span>, <span class="no">trq_rpm</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq_rpm</span>),
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
+    <span class="kw">mpg_c</span> <span class="kw">=</span> <span class="st">"MPG"</span>,
+    <span class="kw">hp</span> <span class="kw">=</span> <span class="st">"HP"</span>,
+    <span class="kw">trq</span> <span class="kw">=</span> <span class="st">"Torque"</span>,
+    <span class="kw">year</span> <span class="kw">=</span> <span class="st">"Year"</span>,
+    <span class="kw">trim</span> <span class="kw">=</span> <span class="st">"Trim"</span>,
+    <span class="kw">trsmn</span> <span class="kw">=</span> <span class="st">"Transmission"</span>,
+    <span class="kw">msrp</span> <span class="kw">=</span> <span class="st">"MSRP"</span>
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#twectbdcrq .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#twectbdcrq .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
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+
+#twectbdcrq .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
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+  border-bottom-width: 0;
+}
+
+#twectbdcrq .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
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+
+#twectbdcrq .gt_bottom_border {
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+  border-left-style: none;
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+  border-right-color: #D3D3D3;
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+
+#twectbdcrq .gt_col_heading {
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+  vertical-align: bottom;
+  padding-top: 5px;
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+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#twectbdcrq .gt_column_spanner_outer {
+  color: #333333;
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+#twectbdcrq .gt_column_spanner_outer:first-child {
+  padding-left: 0;
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+#twectbdcrq .gt_column_spanner_outer:last-child {
+  padding-right: 0;
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+
+#twectbdcrq .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#twectbdcrq .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
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+  border-left-style: none;
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+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#twectbdcrq .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
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+  border-bottom-width: 2px;
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+  vertical-align: middle;
+}
+
+#twectbdcrq .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#twectbdcrq .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#twectbdcrq .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#twectbdcrq .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#twectbdcrq .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#twectbdcrq .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#twectbdcrq .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#twectbdcrq .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
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+
+#twectbdcrq .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
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+
+#twectbdcrq .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
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+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+
+#twectbdcrq .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
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+</style>
+<div id="twectbdcrq" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">28c<br>29h</td>
+      <td class="gt_row gt_right">357<br>@5800rpm</td>
+      <td class="gt_row gt_right">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">140700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">16c<br>22h</td>
+      <td class="gt_row gt_right">503<br>@6250rpm</td>
+      <td class="gt_row gt_right">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">129900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">12c<br>16h</td>
+      <td class="gt_row gt_right">949<br>@9000rpm</td>
+      <td class="gt_row gt_right">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">1416362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11c<br>18h</td>
+      <td class="gt_row gt_right">700<br>@8250rpm</td>
+      <td class="gt_row gt_right">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">397500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">12c<br>19h</td>
+      <td class="gt_row gt_right">645<br>@5000rpm</td>
+      <td class="gt_row gt_right">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">95895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11c<br>18h</td>
+      <td class="gt_row gt_right">647<br>@6250rpm</td>
+      <td class="gt_row gt_right">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">447000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">21c<br>22h</td>
+      <td class="gt_row gt_right">573<br>@6500rpm</td>
+      <td class="gt_row gt_right">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">156000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">16c<br>22h</td>
+      <td class="gt_row gt_right">545<br>@6400rpm</td>
+      <td class="gt_row gt_right">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">101770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="using-formatter-functions" class="section level3">
+<h3 class="hasAnchor">
+<a href="#using-formatter-functions" class="anchor"></a>Using Formatter Functions</h3>
+<p>There are a number of formatter functions, all with the general naming convention <code>fmt*()</code>. The various formatters are convenient for applying formats to numeric or character values in the table’s field. Here, we will simply use <code><a href="../reference/fmt_currency.html">fmt_currency()</a></code> on the <code>msrp</code> column (we still refer to columns by their original names) to get USD currency will no decimal places. We’re not supplying anything for the <code>rows</code> argument and this means we want to apply the formatting to the entire column of data.</p>
+<div class="sourceCode" id="cb10"><html><body><pre class="r"><span class="co"># Format the `msrp` column to USD currency</span>
+<span class="co"># with no display of the currency subunits</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
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+</style>
+<div id="kpobecsdpo" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Mega World Coupe</td>
+      <td class="gt_row gt_left">6am</td>
+      <td class="gt_row gt_right">28c<br>29h</td>
+      <td class="gt_row gt_right">357<br>@5800rpm</td>
+      <td class="gt_row gt_right">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">S Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">16c<br>22h</td>
+      <td class="gt_row gt_right">503<br>@6250rpm</td>
+      <td class="gt_row gt_right">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">12c<br>16h</td>
+      <td class="gt_row gt_right">949<br>@9000rpm</td>
+      <td class="gt_row gt_right">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">$1,416,362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11c<br>18h</td>
+      <td class="gt_row gt_right">700<br>@8250rpm</td>
+      <td class="gt_row gt_right">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">$397,500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">GT Coupe</td>
+      <td class="gt_row gt_left">6m</td>
+      <td class="gt_row gt_right">12c<br>19h</td>
+      <td class="gt_row gt_right">645<br>@5000rpm</td>
+      <td class="gt_row gt_right">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">$95,895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">7a</td>
+      <td class="gt_row gt_right">11c<br>18h</td>
+      <td class="gt_row gt_right">647<br>@6250rpm</td>
+      <td class="gt_row gt_right">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">$447,000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left">Base Coupe</td>
+      <td class="gt_row gt_left">9a</td>
+      <td class="gt_row gt_right">21c<br>22h</td>
+      <td class="gt_row gt_right">573<br>@6500rpm</td>
+      <td class="gt_row gt_right">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">$156,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left">Premium Coupe</td>
+      <td class="gt_row gt_left">6a</td>
+      <td class="gt_row gt_right">16c<br>22h</td>
+      <td class="gt_row gt_right">545<br>@6400rpm</td>
+      <td class="gt_row gt_right">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">$101,770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="column-alignment-and-style-changes" class="section level3">
+<h3 class="hasAnchor">
+<a href="#column-alignment-and-style-changes" class="anchor"></a>Column Alignment and Style Changes</h3>
+<p>We can change the alignment of data in columns with <code><a href="../reference/cols_align.html">cols_align()</a></code>. For our table, let’s center-align the <code>mpg_c</code>, <code>hp</code>, and <code>trq</code> columns. All other columns will maintain their default alignments.</p>
+<p>It’s sometimes useful to modify the default styles of table cells. We can do this in a targeted way with the <code><a href="../reference/tab_style.html">tab_style()</a></code> function. That function require two key pieces of information: a <code>style</code> definition, and one or more <code>locations</code> (which cells should the styles be applied to?). The <code>style</code> argument commonly uses the <code>cells_styles()</code> helper function, which contains arguments for all the styles that are supported (use <code>?cells_styles</code> for more information on this). Here we will use a text size of <code>12px</code> in our targeted cells—both <code><a href="../reference/px.html">px(12)</a></code> and <code>"12px"</code> work equally well here. We also use helper functions with the <code>locations</code> argument and these are the <code>cells_*()</code> functions. We would like to target the data cells in all columns except <code>year</code> and <code>msrp</code> so we need to use <code>cells_body</code> and then supply our target columns to the <code>columns</code> argument.</p>
+<div class="sourceCode" id="cb11"><html><body><pre class="r"><span class="co"># Center-align three columns in the gt table</span>
+<span class="co"># and modify the text size of a few columns</span>
+<span class="co"># of data</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_align.html">cols_align</a></span>(
+    <span class="kw">align</span> <span class="kw">=</span> <span class="st">"center"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_style.html">tab_style</a></span>(
+    <span class="kw">style</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cell_text.html">cell_text</a></span>(<span class="kw">size</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">12</span>)),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>, <span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>))
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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+
+#dpmwnzbpry .gt_table {
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+#dpmwnzbpry .gt_from_md > :first-child {
+  margin-top: 0;
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+</style>
+<div id="dpmwnzbpry" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6am</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">$1,416,362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">$397,500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6m</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">$95,895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">$447,000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">9a</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">$156,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6a</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">$101,770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="text-transforms" class="section level3">
+<h3 class="hasAnchor">
+<a href="#text-transforms" class="anchor"></a>Text Transforms</h3>
+<p>A text transform via the <code><a href="../reference/text_transform.html">text_transform()</a></code> function is a great way to further manipulate text in data cells (even after they’ve been formatted with the <code>fmt*()</code> function). After targeting data cells with the <code><a href="../reference/cells_body.html">cells_body()</a></code> location helper function, we supply a function to the <code>fn</code> argument that processes a vector of text. If we intend to render as an HTML table, we can directly apply HTML tags in the transformation function. The function we provide here will build strings that read better in a display table.</p>
+<div class="sourceCode" id="cb12"><html><body><pre class="r"><span class="co"># Transform the column of text in `trsmn` using</span>
+<span class="co"># a custom function within `text_transform()`;</span>
+<span class="co"># here `x` represents a character vector defined</span>
+<span class="co"># in the `cells_body()` function</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>)),
+    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) {
+
+      <span class="co"># The first character of `x` always</span>
+      <span class="co"># indicates the number of transmission speeds</span>
+      <span class="no">speed</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">1</span>, <span class="fl">1</span>)
+
+      <span class="co"># We can carefully determine which transmission</span>
+      <span class="co"># type we have in `x` with a `dplyr::case_when()`</span>
+      <span class="co"># statement</span>
+      <span class="no">type</span> <span class="kw">&lt;-</span>
+        <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/case_when.html">case_when</a></span>(
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"am"</span> ~ <span class="st">"Automatic/Manual"</span>,
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"m"</span> ~ <span class="st">"Manual"</span>,
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"a"</span> ~ <span class="st">"Automatic"</span>,
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"dd"</span> ~ <span class="st">"Direct Drive"</span>
+        )
+
+      <span class="co"># Let's paste together the `speed` and `type`</span>
+      <span class="co"># vectors to create HTML text replacing `x`</span>
+      <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">speed</span>, <span class="st">" Speed&lt;br&gt;&lt;em&gt;"</span>, <span class="no">type</span>, <span class="st">"&lt;/em&gt;"</span>)
+    }
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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+
+#gcnqemjpsc .gt_table {
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+#gcnqemjpsc .gt_heading {
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+#gcnqemjpsc .gt_column_spanner_outer {
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+
+#gcnqemjpsc .gt_empty_group_heading {
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+
+#gcnqemjpsc .gt_striped {
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+#gcnqemjpsc .gt_row {
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+}
+
+#gcnqemjpsc .gt_stub {
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+
+#gcnqemjpsc .gt_summary_row {
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+  padding-top: 8px;
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+
+#gcnqemjpsc .gt_first_summary_row {
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+
+#gcnqemjpsc .gt_grand_summary_row {
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+
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+
+#gcnqemjpsc .gt_table_body {
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+
+#gcnqemjpsc .gt_footnotes {
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+
+#gcnqemjpsc .gt_sourcenotes {
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+  font-style: italic;
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+}
+</style>
+<div id="gcnqemjpsc" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">$1,416,362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">$397,500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">$95,895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">$447,000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">$156,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">$101,770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="table-header-title-and-subtitle" class="section level3">
+<h3 class="hasAnchor">
+<a href="#table-header-title-and-subtitle" class="anchor"></a>Table Header: Title and Subtitle</h3>
+<p>The <code><a href="../reference/tab_header.html">tab_header()</a></code> function allows us to place a table title and, optionally, a subtitle at the top of the display table. It’s generally a good idea to have both in a table, where the subtitle provides additional information (though that isn’t quite the case in our example below).</p>
+<div class="sourceCode" id="cb13"><html><body><pre class="r"><span class="co"># Add a table title and subtitle; we can use</span>
+<span class="co"># markdown with the `md()` helper function</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The Cars of **gtcars**"</span>),
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"These are some fine automobiles"</span>
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#vuoznuokzk .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#vuoznuokzk .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#vuoznuokzk .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#vuoznuokzk .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#vuoznuokzk .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#vuoznuokzk .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#vuoznuokzk .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#vuoznuokzk .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#vuoznuokzk .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#vuoznuokzk .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#vuoznuokzk .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#vuoznuokzk .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#vuoznuokzk .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#vuoznuokzk .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#vuoznuokzk .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#vuoznuokzk .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#vuoznuokzk .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#vuoznuokzk .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#vuoznuokzk .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#vuoznuokzk .gt_left {
+  text-align: left;
+}
+
+#vuoznuokzk .gt_center {
+  text-align: center;
+}
+
+#vuoznuokzk .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#vuoznuokzk .gt_font_normal {
+  font-weight: normal;
+}
+
+#vuoznuokzk .gt_font_bold {
+  font-weight: bold;
+}
+
+#vuoznuokzk .gt_font_italic {
+  font-style: italic;
+}
+
+#vuoznuokzk .gt_super {
+  font-size: 65%;
+}
+
+#vuoznuokzk .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="vuoznuokzk" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="8" class="gt_heading gt_title gt_font_normal" style>The Cars of <strong>gtcars</strong>
+</th>
+    </tr>
+<tr>
+<th colspan="8" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>These are some fine automobiles</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">$1,416,362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">$397,500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">$95,895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">$447,000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">$156,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">$101,770</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="adding-a-source-citation" class="section level3">
+<h3 class="hasAnchor">
+<a href="#adding-a-source-citation" class="anchor"></a>Adding a Source Citation</h3>
+<p>A <em>source note</em> can be added below the display table using the <code><a href="../reference/tab_source_note.html">tab_source_note()</a></code> function. We can even add multiple source notes with multiple calls of that function. Here, we supply a web URL and by using Markdown (with <code><a href="../reference/md.html">md()</a></code>) it’s easy to create a link to the source of the data.</p>
+<div class="sourceCode" id="cb14"><html><body><pre class="r"><span class="co"># Add a source note to the bottom of the table; this</span>
+<span class="co"># appears below the footnotes</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">tab</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
+    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(
+      <span class="st">"Source: Various pages within the Edmonds website."</span>)
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#vytbtldugj .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
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+  border-left-color: #D3D3D3;
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+
+#vytbtldugj .gt_heading {
+  background-color: #FFFFFF;
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+
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+
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+
+#vytbtldugj .gt_grand_summary_row {
+  color: #333333;
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+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
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+  padding-top: 8px;
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+  border-top-width: 6px;
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+}
+
+#vytbtldugj .gt_table_body {
+  border-top-style: solid;
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+  border-bottom-width: 2px;
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+}
+
+#vytbtldugj .gt_footnotes {
+  color: #333333;
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+  border-bottom-width: 2px;
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+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#vytbtldugj .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#vytbtldugj .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+  border-right-color: #D3D3D3;
+}
+
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+  font-size: 90%;
+  padding: 4px;
+}
+
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+  text-align: left;
+}
+
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+  text-align: center;
+}
+
+#vytbtldugj .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#vytbtldugj .gt_font_normal {
+  font-weight: normal;
+}
+
+#vytbtldugj .gt_font_bold {
+  font-weight: bold;
+}
+
+#vytbtldugj .gt_font_italic {
+  font-style: italic;
+}
+
+#vytbtldugj .gt_super {
+  font-size: 65%;
+}
+
+#vytbtldugj .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="vytbtldugj" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="8" class="gt_heading gt_title gt_font_normal" style>The Cars of <strong>gtcars</strong>
+</th>
+    </tr>
+<tr>
+<th colspan="8" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>These are some fine automobiles</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">$1,416,362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">$397,500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">$95,895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">$447,000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">$156,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">$101,770</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes"><tr>
+<td class="gt_sourcenote" colspan="8">Source: Various pages within the Edmonds website.</td>
+    </tr></tfoot>
+</table></div>
+</div>
+<div id="using-the-complete-gtcars-table-and-adding-footnotes" class="section level3">
+<h3 class="hasAnchor">
+<a href="#using-the-complete-gtcars-table-and-adding-footnotes" class="anchor"></a>Using the Complete <code>gtcars</code> table and Adding Footnotes</h3>
+<p>Let’s bring it all together by putting together all the statements we developed for <code>gtcars_8</code>, and applying that to the complete <code>gtcars</code> dataset. At the same time, we’ll add a few interesting footnotes and our specific requirements for footnoting are:</p>
+<pre><code>a. identifying the car with the best gas mileage (city)
+b. identifying the car with the highest horsepower
+c. stating the currency of the MSRP</code></pre>
+<p>The <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> function expects note text for the <code>footnote</code> argument, and locations for where the footnote mark should be attached. It will handle the placement of the footnote mark and also place the footnote in the footnotes area. Here, we’ll use the <code><a href="../reference/cells_body.html">cells_body()</a></code> <em>location helper</em> function. There are several location helper functions for targeting all parts of the table (e.g,. <code><a href="../reference/cells_body.html">cells_body()</a></code>, <code><a href="../reference/cells_stub.html">cells_stub()</a></code>, etc.). Each <em>location helper</em> has their own interface for targeting cells so refer to the documentation for examples of how they work in practice.</p>
+<p>What <code><a href="../reference/cells_body.html">cells_body()</a></code> expects is <code>columns</code> (column names, which can be conveniently provided in <code><a href="https://dplyr.tidyverse.org/reference/vars.html">vars()</a></code>) and <code>rows</code> (which can be a vector of row names or row indices). The <code><a href="../reference/cells_stub.html">cells_stub()</a></code> location helper only expects a vector of <code>rows</code>. For <code><a href="../reference/cells_column_labels.html">cells_column_labels()</a></code>, we can either provided targeted column labels in the <code>columns</code> argument or spanner column labels in the <code>groups</code> argument. Here, we are targeting a footnote to the <code>msrp</code> column label so we will use <code>columns = vars(msrp)</code>.</p>
+<p>In terms of structuring the code, we’re taking all the previous statements and putting those in first. It should be noted that the order of the statements does not matter to the end result, we could also put in all of the <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> statements first (again, any in order) and expect the same output table.</p>
+<div class="sourceCode" id="cb16"><html><body><pre class="r"><span class="co"># Use dplyr functions to get the car with the best city gas mileage;</span>
+<span class="co"># this will be used to target the correct cell for a footnote</span>
+<span class="no">best_gas_mileage_city</span> <span class="kw">&lt;-</span>
+  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="fu">desc</span>(<span class="no">mpg_c</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/slice.html">slice</a></span>(<span class="fl">1</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(<span class="no">car</span>)
+
+<span class="co"># Use dplyr functions to get the car with the highest horsepower</span>
+<span class="co"># this will be used to target the correct cell for a footnote</span>
+<span class="no">highest_horsepower</span> <span class="kw">&lt;-</span>
+  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="fu">desc</span>(<span class="no">hp</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/slice.html">slice</a></span>(<span class="fl">1</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(<span class="no">car</span>)
+
+<span class="co"># Create a display table with `gtcars`, using all of the previous</span>
+<span class="co"># statements piped together + additional `tab_footnote()` stmts</span>
+<span class="no">tab</span> <span class="kw">&lt;-</span>
+  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(
+    <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="no">ctry_origin</span>, <span class="kw">levels</span> <span class="kw">=</span> <span class="no">order_countries</span>),
+    <span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">mfr</span>, -<span class="no">model</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"car"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_hide.html">cols_hide</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>, <span class="no">bdy_style</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_move.html">cols_move</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
+    <span class="kw">after</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
+    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Performance"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>, <span class="no">hp</span>, <span class="no">hp_rpm</span>, <span class="no">trq</span>, <span class="no">trq_rpm</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_h</span>),
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}c&lt;br&gt;{2}h"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp</span>, <span class="no">hp_rpm</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp_rpm</span>),
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq</span>, <span class="no">trq_rpm</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq_rpm</span>),
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
+    <span class="kw">mpg_c</span> <span class="kw">=</span> <span class="st">"MPG"</span>,
+    <span class="kw">hp</span> <span class="kw">=</span> <span class="st">"HP"</span>,
+    <span class="kw">trq</span> <span class="kw">=</span> <span class="st">"Torque"</span>,
+    <span class="kw">year</span> <span class="kw">=</span> <span class="st">"Year"</span>,
+    <span class="kw">trim</span> <span class="kw">=</span> <span class="st">"Trim"</span>,
+    <span class="kw">trsmn</span> <span class="kw">=</span> <span class="st">"Transmission"</span>,
+    <span class="kw">msrp</span> <span class="kw">=</span> <span class="st">"MSRP"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_align.html">cols_align</a></span>(
+    <span class="kw">align</span> <span class="kw">=</span> <span class="st">"center"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_style.html">tab_style</a></span>(
+    <span class="kw">style</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cell_text.html">cell_text</a></span>(<span class="kw">size</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">12</span>)),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>, <span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>)
+    )
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>)),
+    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) {
+
+      <span class="no">speed</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">1</span>, <span class="fl">1</span>)
+
+      <span class="no">type</span> <span class="kw">&lt;-</span>
+        <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/case_when.html">case_when</a></span>(
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"am"</span> ~ <span class="st">"Automatic/Manual"</span>,
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"m"</span> ~ <span class="st">"Manual"</span>,
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"a"</span> ~ <span class="st">"Automatic"</span>,
+          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"dd"</span> ~ <span class="st">"Direct Drive"</span>
+        )
+
+      <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">speed</span>, <span class="st">" Speed&lt;br&gt;&lt;em&gt;"</span>, <span class="no">type</span>, <span class="st">"&lt;/em&gt;"</span>)
+    }
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The Cars of **gtcars**"</span>),
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"These are some fine automobiles"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
+    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(
+      <span class="st">"Source: Various pages within the Edmonds website."</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Best gas mileage (city) of all the **gtcars**."</span>),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">best_gas_mileage_city</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The highest horsepower of all the **gtcars**."</span>),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">highest_horsepower</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"All prices in U.S. dollars (USD)."</span>,
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_column_labels.html">cells_column_labels</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>))
+  )
+
+<span class="co"># Show the table</span>
+<span class="no">tab</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#wtflhoisbj .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#wtflhoisbj .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#wtflhoisbj .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#wtflhoisbj .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#wtflhoisbj .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#wtflhoisbj .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#wtflhoisbj .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#wtflhoisbj .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#wtflhoisbj .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#wtflhoisbj .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#wtflhoisbj .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#wtflhoisbj .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#wtflhoisbj .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#wtflhoisbj .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#wtflhoisbj .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#wtflhoisbj .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#wtflhoisbj .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#wtflhoisbj .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#wtflhoisbj .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#wtflhoisbj .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#wtflhoisbj .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#wtflhoisbj .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#wtflhoisbj .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
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+
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+</style>
+<div id="wtflhoisbj" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="8" class="gt_heading gt_title gt_font_normal" style>The Cars of <strong>gtcars</strong>
+</th>
+    </tr>
+<tr>
+<th colspan="8" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>These are some fine automobiles</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Performance</span>
+      </th>
+      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP<sup class="gt_footnote_marks">1</sup>
+</th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Germany</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Audi R8</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">4.2 (Manual) Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>20h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">430<br>@7900rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">317<br>@4500rpm</td>
+      <td class="gt_row gt_right">$115,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Audi S8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>25h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">520<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">481<br>@1700rpm</td>
+      <td class="gt_row gt_right">$114,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Audi RS 7</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Quattro Hatchback</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>25h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">560<br>@5700rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">516<br>@1750rpm</td>
+      <td class="gt_row gt_right">$108,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Audi S7</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Prestige quattro Hatchback</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">17c<br>27h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">450<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1400rpm</td>
+      <td class="gt_row gt_right">$82,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Audi S6</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Premium Plus quattro Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">18c<br>27h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">450<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1400rpm</td>
+      <td class="gt_row gt_right">$70,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW i8</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h<sup class="gt_footnote_marks">2</sup>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW M6</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">560<br>@6000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">500<br>@1500rpm</td>
+      <td class="gt_row gt_right">$113,400</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW M5</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">560<br>@6000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">500<br>@1500rpm</td>
+      <td class="gt_row gt_right">$94,100</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW 6-Series</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">640 I Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>30h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">315<br>@5800rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">330<br>@1400rpm</td>
+      <td class="gt_row gt_right">$77,300</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">BMW M4</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">17c<br>24h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">425<br>@5500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1850rpm</td>
+      <td class="gt_row gt_right">$65,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Mercedes-Benz SL-Class</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">SL400 Convertible</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>27h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">329<br>@5250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">354<br>@1600rpm</td>
+      <td class="gt_row gt_right">$85,050</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Porsche 911</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Carrera Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>28h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">350<br>@7400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">287<br>@5600rpm</td>
+      <td class="gt_row gt_right">$84,300</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Porsche Panamera</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">18c<br>28h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">310<br>@6200rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">295<br>@3750rpm</td>
+      <td class="gt_row gt_right">$78,100</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Porsche 718 Boxster</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Convertible</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>28h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">300<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">280<br>@1950rpm</td>
+      <td class="gt_row gt_right">$56,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Porsche 718 Cayman</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>29h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">300<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">280<br>@1950rpm</td>
+      <td class="gt_row gt_right">$53,900</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Italy</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm<sup class="gt_footnote_marks">3</sup>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
+      <td class="gt_row gt_right">$1,416,362</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari F12Berlinetta</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">731<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">509<br>@6000rpm</td>
+      <td class="gt_row gt_right">$319,995</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari GTC4Lusso</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>17h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">680<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">514<br>@5750rpm</td>
+      <td class="gt_row gt_right">$298,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari FF</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>16h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">652<br>@8000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">504<br>@6000rpm</td>
+      <td class="gt_row gt_right">$295,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari 458 Speciale</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>17h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">597<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6000rpm</td>
+      <td class="gt_row gt_right">$291,744</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari 458 Spider</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>17h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">562<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6000rpm</td>
+      <td class="gt_row gt_right">$263,553</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari 488 GTB</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">661<br>@8000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">561<br>@3000rpm</td>
+      <td class="gt_row gt_right">$245,400</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari 458 Italia</td>
+      <td class="gt_row gt_right">2014</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>17h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">562<br>@9000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6000rpm</td>
+      <td class="gt_row gt_right">$233,509</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ferrari California</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Convertible</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>23h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">553<br>@7500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">557<br>@4750rpm</td>
+      <td class="gt_row gt_right">$198,973</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
+      <td class="gt_row gt_right">$397,500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Huracan</td>
+      <td class="gt_row gt_right">2015</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 610-4 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>20h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">610<br>@8250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">413<br>@6500rpm</td>
+      <td class="gt_row gt_right">$237,250</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lamborghini Gallardo</td>
+      <td class="gt_row gt_right">2014</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">LP 550-2 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>20h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@8000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6500rpm</td>
+      <td class="gt_row gt_right">$191,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Maserati Granturismo</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Sport Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>21h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">454<br>@7600rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">384<br>@4750rpm</td>
+      <td class="gt_row gt_right">$132,825</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Maserati Quattroporte</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">S Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>23h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">404<br>@5500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1500rpm</td>
+      <td class="gt_row gt_right">$99,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Maserati Ghibli</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">17c<br>24h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">345<br>@5250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">369<br>@1750rpm</td>
+      <td class="gt_row gt_right">$70,600</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United States</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Chevrolet Corvette</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Z06 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">650<br>@6400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">650<br>@3600rpm</td>
+      <td class="gt_row gt_right">$88,345</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Dodge Viper</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
+      <td class="gt_row gt_right">$95,895</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Ford GT</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
+      <td class="gt_row gt_right">$447,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Tesla Model S</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">75D</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">1  Speed<br><em> Direct Drive </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">NAc<br>NAh</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">259<br>@6100rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">243<br>@NArpm</td>
+      <td class="gt_row gt_right">$74,500</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">Japan</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Acura NSX</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
+      <td class="gt_row gt_right">$156,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
+      <td class="gt_row gt_right">$101,770</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">United Kingdom</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Aston Martin Vanquish</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>21h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">568<br>@6650rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">465<br>@5500rpm</td>
+      <td class="gt_row gt_right">$287,250</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Aston Martin DB11</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>21h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">608<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">516<br>@1500rpm</td>
+      <td class="gt_row gt_right">$211,195</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Aston Martin Rapide S</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">14c<br>21h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">552<br>@6650rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">465<br>@5500rpm</td>
+      <td class="gt_row gt_right">$205,300</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Aston Martin Vantage</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">V8 GT (Manual) Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">430<br>@7300rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">361<br>@5000rpm</td>
+      <td class="gt_row gt_right">$103,300</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Bentley Continental GT</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">V8 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>25h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">500<br>@6000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">487<br>@1700rpm</td>
+      <td class="gt_row gt_right">$198,500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Jaguar F-Type</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base (Manual) Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>24h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">340<br>@6500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">332<br>@3500rpm</td>
+      <td class="gt_row gt_right">$65,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Lotus Evora</td>
+      <td class="gt_row gt_right">2017</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">2+2 Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>24h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">400<br>@7000rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">302<br>@3500rpm</td>
+      <td class="gt_row gt_right">$91,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">McLaren 570</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>23h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">570<br>@7500rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">443<br>@5000rpm</td>
+      <td class="gt_row gt_right">$184,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Rolls-Royce Dawn</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Convertible</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">563<br>@5250rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">575<br>@1500rpm</td>
+      <td class="gt_row gt_right">$335,000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Rolls-Royce Wraith</td>
+      <td class="gt_row gt_right">2016</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
+      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic </em>
+</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>21h</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">624<br>@5600rpm</td>
+      <td class="gt_row gt_center" style="font-size: 12px;">590<br>@1500rpm</td>
+      <td class="gt_row gt_right">$304,350</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes"><tr>
+<td class="gt_sourcenote" colspan="8">Source: Various pages within the Edmonds website.</td>
+    </tr></tfoot>
+<tfoot><tr class="gt_footnotes">
+<td colspan="8">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>1</em>
+          </sup>
+           
+          All prices in U.S. dollars (USD).
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>2</em>
+          </sup>
+           
+          Best gas mileage (city) of all the <strong>gtcars</strong>.
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>3</em>
+          </sup>
+           
+          The highest horsepower of all the <strong>gtcars</strong>.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+<p>That is it. The final table looks pretty good and conveys the additional information we planned for. That table can be used in a lot of different places like R Markdown, Shiny, email messages… wherever HTML is accepted.</p>
+</div>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+
+      </div>
+
+</div>
+
+
+
+      <footer><div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href="https://www.rstudio.com"><img src="https://www.tidyverse.org/rstudio-logo.svg" alt="RStudio" height="24"></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
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+</div>
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+</html>
diff --git a/docs/articles/creating-summary-lines.html b/docs/articles/creating-summary-lines.html
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+</li>
+<li class="dropdown">
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+<li class="dropdown-header">How to Use</li>
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+
+      
+
+      </header><div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header toc-ignore">
+      <h1 data-toc-skip>Creating Summary Lines</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/rstudio/gt/blob/master/vignettes/creating-summary-lines.Rmd"><code>vignettes/creating-summary-lines.Rmd</code></a></small>
+      <div class="hidden name"><code>creating-summary-lines.Rmd</code></div>
+
+    </div>
+
+    
+    
+<p>We can use the <strong>gt</strong> <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function to insert summary rows into a table. There are two main types of summary rows: (1) groupwise summaries, and (2) the grand summary. The groupwise summaries operate on one or more row groups, which can themselves be generated in a variety of ways:</p>
+<ul>
+<li>with the <code><a href="../reference/gt.html">gt()</a></code> function’s <code>groupname_col</code> option</li>
+<li>using the <code><a href="../reference/tab_row_group.html">tab_row_group()</a></code> function on a gt object</li>
+<li>by passing in a grouped <code>tbl_df</code> object to <code><a href="../reference/gt.html">gt()</a></code> (using <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">dplyr::group_by()</a></code>)</li>
+</ul>
+<p>We generate the summary data through specification of aggregation functions. You choose how to format the values in the resulting summary cells by use of a formatter function (e.g, <code><a href="../reference/fmt_number.html">fmt_number()</a></code>) and any relevant options. These summary rows are automatically inserted within the relevant row groups (for groupwise summaries) or at the bottom of the table (as a grand summary), where each summary row is the result of a different aggregation function.</p>
+<div id="preparing-the-input-data-table" class="section level3">
+<h3 class="hasAnchor">
+<a href="#preparing-the-input-data-table" class="anchor"></a>Preparing the Input Data Table</h3>
+<p>Let’s use the <code>exibble</code> dataset (included in the <strong>gt</strong> package) to demonstrate how summary rows can be added. That table contains categorical columns named <code>row</code> and <code>group</code>, along several columns with varying data types. Here is a preview of the <code>exibble</code> dataset using solely the <code><a href="../reference/gt.html">gt()</a></code> function with no other options:</p>
+<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="no">exibble</span> <span class="kw">%&gt;%</span> <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#dvptuvigmd .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#dvptuvigmd .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#dvptuvigmd .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#dvptuvigmd .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#dvptuvigmd .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#dvptuvigmd .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#dvptuvigmd .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#dvptuvigmd .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#dvptuvigmd .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#dvptuvigmd .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#dvptuvigmd .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#dvptuvigmd .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#dvptuvigmd .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#dvptuvigmd .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#dvptuvigmd .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#dvptuvigmd .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#dvptuvigmd .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#dvptuvigmd .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#dvptuvigmd .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#dvptuvigmd .gt_left {
+  text-align: left;
+}
+
+#dvptuvigmd .gt_center {
+  text-align: center;
+}
+
+#dvptuvigmd .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#dvptuvigmd .gt_font_normal {
+  font-weight: normal;
+}
+
+#dvptuvigmd .gt_font_bold {
+  font-weight: bold;
+}
+
+#dvptuvigmd .gt_font_italic {
+  font-style: italic;
+}
+
+#dvptuvigmd .gt_super {
+  font-size: 65%;
+}
+
+#dvptuvigmd .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="dvptuvigmd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">fctr</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">date</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">time</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">datetime</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">row</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">group</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_right">1.111e-01</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_center">one</td>
+      <td class="gt_row gt_left">2015-01-15</td>
+      <td class="gt_row gt_left">13:35</td>
+      <td class="gt_row gt_left">2018-01-01 02:22</td>
+      <td class="gt_row gt_right">49.950</td>
+      <td class="gt_row gt_left">row_1</td>
+      <td class="gt_row gt_left">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">2.222e+00</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_center">two</td>
+      <td class="gt_row gt_left">2015-02-15</td>
+      <td class="gt_row gt_left">14:40</td>
+      <td class="gt_row gt_left">2018-02-02 14:33</td>
+      <td class="gt_row gt_right">17.950</td>
+      <td class="gt_row gt_left">row_2</td>
+      <td class="gt_row gt_left">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">3.333e+01</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_center">three</td>
+      <td class="gt_row gt_left">2015-03-15</td>
+      <td class="gt_row gt_left">15:45</td>
+      <td class="gt_row gt_left">2018-03-03 03:44</td>
+      <td class="gt_row gt_right">1.390</td>
+      <td class="gt_row gt_left">row_3</td>
+      <td class="gt_row gt_left">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">4.444e+02</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_center">four</td>
+      <td class="gt_row gt_left">2015-04-15</td>
+      <td class="gt_row gt_left">16:50</td>
+      <td class="gt_row gt_left">2018-04-04 15:55</td>
+      <td class="gt_row gt_right">65100.000</td>
+      <td class="gt_row gt_left">row_4</td>
+      <td class="gt_row gt_left">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">5.550e+03</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_center">five</td>
+      <td class="gt_row gt_left">2015-05-15</td>
+      <td class="gt_row gt_left">17:55</td>
+      <td class="gt_row gt_left">2018-05-05 04:00</td>
+      <td class="gt_row gt_right">1325.810</td>
+      <td class="gt_row gt_left">row_5</td>
+      <td class="gt_row gt_left">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">NA</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_center">six</td>
+      <td class="gt_row gt_left">2015-06-15</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_left">2018-06-06 16:11</td>
+      <td class="gt_row gt_right">13.255</td>
+      <td class="gt_row gt_left">row_6</td>
+      <td class="gt_row gt_left">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">7.770e+05</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_center">seven</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_left">19:10</td>
+      <td class="gt_row gt_left">2018-07-07 05:22</td>
+      <td class="gt_row gt_right">NA</td>
+      <td class="gt_row gt_left">row_7</td>
+      <td class="gt_row gt_left">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_right">8.880e+06</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_center">eight</td>
+      <td class="gt_row gt_left">2015-08-15</td>
+      <td class="gt_row gt_left">20:20</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_right">0.440</td>
+      <td class="gt_row gt_left">row_8</td>
+      <td class="gt_row gt_left">grp_b</td>
+    </tr>
+</tbody>
+</table></div>
+<p>We’ll create a table stub with both row labels (using the <code>row</code> column) and row groups (using the <code>group</code> column). The end result will be a table organized with labeled rows that are grouped together (the row group labels identify each of the row groups). To make the examples a bit easier to follow, some of the columns in exibble will first be dropped through a <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> statement.</p>
+<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Create a gt table using the `exibble` dataset</span>
+<span class="no">exibble_a</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="no">fctr</span>, <span class="no">date</span>, <span class="no">time</span>, <span class="no">datetime</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"row"</span>, <span class="kw">groupname_col</span> <span class="kw">=</span> <span class="st">"group"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_missing.html">fmt_missing</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">everything</a></span>())
+
+<span class="no">exibble_a</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#mgboivgpsa .gt_table {
+  display: table;
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+</style>
+<div id="mgboivgpsa" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1.111e-01</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">49.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.222e+00</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">17.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3.333e+01</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">1.390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4.444e+02</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">65100.000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5.550e+03</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">1325.810</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">13.255</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7.770e+05</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8.880e+06</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">0.440</td>
+    </tr>
+</tbody>
+</table></div>
+<p>There are two groups in this data table: <code>grp_a</code> and <code>grp_b</code>. This gives us flexibility to create both a grand summary and groupwise summary rows.</p>
+</div>
+<div id="generating-groupwise-summary-rows" class="section level3">
+<h3 class="hasAnchor">
+<a href="#generating-groupwise-summary-rows" class="anchor"></a>Generating Groupwise Summary Rows</h3>
+<p>Groupwise summary rows can be generated by using the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function and, importantly, through specifying the groups that will receive summary rows. We can provide a vector group names, as in <code><a href="https://rdrr.io/r/base/c.html">c("grp_a", "grp_b")</a></code>, or, use <code>TRUE</code> to signify that all groups should receive summary rows. Aside from the selection of groups, there is control over which columns are to used for the summary. Since each call to <code><a href="../reference/summary_rows.html">summary_rows()</a></code> only performs one set of aggregation functions, we may want specific aggregations for different subsets of columns.</p>
+<p>To make any sort of summary, we need to use functions that will perform the aggregation. We can provide base functions such as <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html">min()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html">max()</a></code>, and more, within a <code><a href="https://rdrr.io/r/base/list.html">list()</a></code>. Each function provided will result in a summary row for each <code>group</code>.</p>
+<p>Because each function will yield a row, we need to be able to label that row. So, each summary row will receive a summary row label. We can provide our preferred names by naming the functions within the list (e.g, <code><a href="https://rdrr.io/r/base/list.html">list(average = "mean", total = "sum", SD = "sd")</a></code>).</p>
+<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Create groupwise summary rows for both</span>
+<span class="co"># groups (using `groups = TRUE`); use the</span>
+<span class="co"># `mean()`, `sum()`, and `sd()` functions</span>
+<span class="co"># (only for the `num` column)</span>
+<span class="no">exibble_b</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
+      <span class="kw">average</span> <span class="kw">=</span> <span class="st">"mean"</span>,
+      <span class="kw">total</span> <span class="kw">=</span> <span class="st">"sum"</span>,
+      <span class="kw">SD</span> <span class="kw">=</span> <span class="st">"sd"</span>)
+  )
+
+<span class="no">exibble_b</span></pre></body></html></div>
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+<div id="hnsgwsmrlh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1.111e-01</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">49.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.222e+00</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">17.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3.333e+01</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">1.390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4.444e+02</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">65100.000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">average</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">120.02</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">480.06</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">SD</td>
+      <td class="gt_row gt_right gt_summary_row">216.79</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5.550e+03</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">1325.810</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">13.255</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7.770e+05</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8.880e+06</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">0.440</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">average</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">SD</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+</tbody>
+</table></div>
+<p>We can specify the aggregation functions by use of function names in quotes (e.g., <code>"sum"</code>), as bare functions (e.g., <code>sum</code>), or as one-sided R formulas using a leading <code>~</code>. In the formula representation, a <code>.</code> serves as the data to be summarized, so we can use <code><a href="https://rdrr.io/r/base/sum.html">sum(., na.rm = TRUE)</a></code>. The use of named arguments is recommended as those names will serve as summary row labels (the labels can derived from the function names but only when not providing bare function names).</p>
+<p>Now that the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function has been somewhat explained, let’s look at how we can create groupwise summary rows for the <code>exibble_a</code> table. We’ll create summaries for both available groups (<code>groups = TRUE</code>) and use the <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code>, and <code><a href="https://rdrr.io/r/stats/sd.html">sd()</a></code> functions with the <em>function-name-in-quotes</em> method (and this will only pertain to the <code>num</code> column).</p>
+<p>In the previous example we have an <code>NA</code> value in the <code>num/row_6</code> cell, and so we get <code>NA</code> outputs from <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code>, and <code><a href="https://rdrr.io/r/stats/sd.html">sd()</a></code> in <code>grp_b</code>’s summary rows (which are replaced with em dashes, itself controllable through the <code>missing_text</code> option). To avoid this, let’s rewrite the above using the <em>names-and-formulae</em> method.</p>
+<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># Create groupwise summary rows for both</span>
+<span class="co"># groups (using `groups = TRUE`); we will</span>
+<span class="co"># use names and formulas this time in `fns`</span>
+<span class="no">exibble_c</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
+      <span class="kw">avg</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/mean.html">mean</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
+      <span class="kw">total</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
+      <span class="kw">s.d.</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/stats/sd.html">sd</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>)
+    )
+  )
+
+<span class="no">exibble_c</span></pre></body></html></div>
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+#ulteajqemv .gt_font_normal {
+  font-weight: normal;
+}
+
+#ulteajqemv .gt_font_bold {
+  font-weight: bold;
+}
+
+#ulteajqemv .gt_font_italic {
+  font-style: italic;
+}
+
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+  font-size: 65%;
+}
+
+#ulteajqemv .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="ulteajqemv" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1.111e-01</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">49.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.222e+00</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">17.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3.333e+01</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">1.390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4.444e+02</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">65100.000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">120.02</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">480.06</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">216.79</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5.550e+03</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">1325.810</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">13.255</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7.770e+05</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8.880e+06</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">0.440</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,220,850.00</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">9,662,550.00</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">4,916,123.25</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+</tbody>
+</table></div>
+<p>Here we see that summary rows were created for both groups. However, the output of the summary row data is quite different than that of the cell data. The <code>formatter</code> argument (and extra <code>...</code> arguments) allows for use of any of the <code>fmt_*()</code> functions that we’d normally use to format cell data. In this example (another rewrite of the above), the cell data in the <code>num</code> column is formatted in scientific notation and the resulting summary cell data is also formatted in the same way (including the options of <code>decimals = 3</code>).</p>
+<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Define a named list of aggregation</span>
+<span class="co"># functions and summary row labels</span>
+<span class="no">fns_labels</span> <span class="kw">&lt;-</span>
+  <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
+    <span class="kw">avg</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/mean.html">mean</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
+    <span class="kw">total</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
+    <span class="kw">s.d.</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/stats/sd.html">sd</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>)
+  )
+
+<span class="co"># Create groupwise summary rows as</span>
+<span class="co"># before, supply `fns_labels` to `fns`,</span>
+<span class="co"># and format the cell summary data</span>
+<span class="no">exibble_d</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_scientific.html">fmt_scientific</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_scientific</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
+  )
+
+<span class="no">exibble_d</span></pre></body></html></div>
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+
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+<div id="gqhidwrqmm" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1.111 × 10<sup class="gt_super">−1</sup>
+</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">49.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.222</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">17.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3.333 × 10<sup class="gt_super">1</sup>
+</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">1.390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4.444 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">65100.000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1.200 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">4.801 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">2.168 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5.550 × 10<sup class="gt_super">3</sup>
+</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">1325.810</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">13.255</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7.770 × 10<sup class="gt_super">5</sup>
+</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8.880 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">0.440</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3.221 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">9.663 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">4.916 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+</tbody>
+</table></div>
+<p>The input to <code>fns</code> is very permissive in regard to how the functions are defined. It is entirely valid to provide functions in the various forms shown earlier such that <code><a href="https://rdrr.io/r/base/list.html">list("sum", avg = ~mean(., na.rm = TRUE), SD = "sd")</a></code> will be correctly interpreted. It is recommended to use formula notation.</p>
+<p>The default for <code>formatter</code> is set to <code>fmt_number</code> which is a sensible default for many scenarios. The setting of argument values for a particular formatter can be done in the <code>...</code> area of the function call (as was done above for the <code>decimals</code> argument).</p>
+</div>
+<div id="using-multiple-calls-of-summary_rows" class="section level3">
+<h3 class="hasAnchor">
+<a href="#using-multiple-calls-of-summary_rows" class="anchor"></a>Using Multiple Calls of <code>summary_rows()</code>
+</h3>
+<p>We can re-use summary row labels and fill the otherwise empty summary cells with similar aggregations but perhaps with different formatting options. Here’s an example where the <code>currency</code> column contains aggregate values that share the same summary rows as for the <code>num</code> column, adds two more rows, and uses currency formatting:</p>
+<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Create groupwise summary rows as</span>
+<span class="co"># before, supply `fns_labels` to `fns`,</span>
+<span class="co"># and format the cell summary data</span>
+<span class="no">exibble_e</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_scientific.html">fmt_scientific</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
+    ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_scientific</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="st">"grp_a"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(
+      <span class="no">fns_labels</span>,
+      <span class="kw">min</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">min</a></span>(<span class="no">.</span>),
+      <span class="kw">max</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">max</a></span>(<span class="no">.</span>)),
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
+  )
+
+<span class="no">exibble_e</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
+<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
+<span class="co">#&gt; * ...</span></pre></body></html></div>
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+
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+
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+</style>
+<div id="vwzdspbffd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1.111 × 10<sup class="gt_super">−1</sup>
+</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">€49.95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.222</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">€17.95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3.333 × 10<sup class="gt_super">1</sup>
+</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">€1.39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4.444 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">€65,100.00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1.200 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16,292.32</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">4.801 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65,169.29</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">2.168 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€32,538.46</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€1.39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65,100.00</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5.550 × 10<sup class="gt_super">3</sup>
+</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">€1,325.81</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">€13.26</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7.770 × 10<sup class="gt_super">5</sup>
+</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8.880 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">€0.44</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3.221 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">9.663 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">4.916 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+</tbody>
+</table></div>
+<p>A thing to again note in the above example is that even though two independent calls of <code><a href="../reference/summary_rows.html">summary_rows()</a></code> were made, summary data within common summary row names were ‘squashed’ together, thus avoiding the fragmentation of summary rows. Put another way, we don’t create additional summary rows across separate calls if we are referencing the same summary row labels. If the summary row labels provided in <code>fns</code> were to be different across columns however, additional summary rows would be produced even if the types of data aggregations were to be functionally equivalent.</p>
+<p>We can also store these argument values as local variables and pass them in both separate <code>fmt_*number*()</code> calls also to arguments within <code><a href="../reference/summary_rows.html">summary_rows()</a></code> calls. This is useful for standardizing formatting parameters across different table cell types. Here’s an example of that, which additional passes the <code>fr_BE</code> locale to all functions that take a <code>locale</code> value.</p>
+<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># Provide common formatting parameters to a list</span>
+<span class="co"># object named `formats`; the number of decimal</span>
+<span class="co"># places will be `2` and the locale is "fr_BE"</span>
+<span class="no">formats</span> <span class="kw">&lt;-</span>
+  <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="st">"fr_BE"</span>,
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
+  )
+
+<span class="co"># Format the `num` and `currency` columns</span>
+<span class="co"># (using the values stored in `formats`);</span>
+<span class="co"># when generating summary rows we can also</span>
+<span class="co"># supply formatter options from this list</span>
+<span class="no">exibble_f</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_scientific.html">fmt_scientific</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">decimals</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">currency</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
+    ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_scientific</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">decimals</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="st">"grp_a"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(
+      <span class="no">fns_labels</span>,
+      <span class="kw">min</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">min</a></span>(<span class="no">.</span>),
+      <span class="kw">max</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">max</a></span>(<span class="no">.</span>)),
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">currency</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
+  )
+
+<span class="no">exibble_f</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
+<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
+<span class="co">#&gt; * ...</span></pre></body></html></div>
+<style>html {
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+
+#rvsmkcqcok .gt_table {
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+
+#rvsmkcqcok .gt_heading {
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+
+#rvsmkcqcok .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
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+
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+#rvsmkcqcok .gt_bottom_border {
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+#rvsmkcqcok .gt_col_headings {
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+
+#rvsmkcqcok .gt_col_heading {
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+  vertical-align: bottom;
+  padding-top: 5px;
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+}
+
+#rvsmkcqcok .gt_column_spanner_outer {
+  color: #333333;
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+#rvsmkcqcok .gt_column_spanner_outer:first-child {
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+#rvsmkcqcok .gt_column_spanner_outer:last-child {
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+
+#rvsmkcqcok .gt_column_spanner {
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+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#rvsmkcqcok .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
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+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
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+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#rvsmkcqcok .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#rvsmkcqcok .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#rvsmkcqcok .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#rvsmkcqcok .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#rvsmkcqcok .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#rvsmkcqcok .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#rvsmkcqcok .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rvsmkcqcok .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#rvsmkcqcok .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rvsmkcqcok .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#rvsmkcqcok .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#rvsmkcqcok .gt_footnotes {
+  color: #333333;
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+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#rvsmkcqcok .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#rvsmkcqcok .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
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+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
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+
+#rvsmkcqcok .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#rvsmkcqcok .gt_left {
+  text-align: left;
+}
+
+#rvsmkcqcok .gt_center {
+  text-align: center;
+}
+
+#rvsmkcqcok .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#rvsmkcqcok .gt_font_normal {
+  font-weight: normal;
+}
+
+#rvsmkcqcok .gt_font_bold {
+  font-weight: bold;
+}
+
+#rvsmkcqcok .gt_font_italic {
+  font-style: italic;
+}
+
+#rvsmkcqcok .gt_super {
+  font-size: 65%;
+}
+
+#rvsmkcqcok .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="rvsmkcqcok" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1,111 × 10<sup class="gt_super">−1</sup>
+</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">€49,95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2,222</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">€17,95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3,333 × 10<sup class="gt_super">1</sup>
+</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">€1,39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4,444 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">€65 100,00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1,200 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16 292,32</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">4,801 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65 169,29</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">2,168 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€32 538,46</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€1,39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65 100,00</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5,550 × 10<sup class="gt_super">3</sup>
+</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">€1 325,81</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">€13,26</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7,770 × 10<sup class="gt_super">5</sup>
+</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8,880 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">€0,44</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,221 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">9,663 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">4,916 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+</tbody>
+</table></div>
+<p>Passing in parameters like this is useful, especially if there are larger numbers of columns. When we store formatting parameters outside of the <code><a href="../reference/gt.html">gt()</a></code> pipeline, we separate our concerns between data structuring and data formatting. Putting styles and options into objects becomes more important if we intend to centralize formatting options for reuse.</p>
+</div>
+<div id="creating-a-grand-summary" class="section level3">
+<h3 class="hasAnchor">
+<a href="#creating-a-grand-summary" class="anchor"></a>Creating a Grand Summary</h3>
+<p>A grand summary aggregates column data regardless of the groups within the data. Grand summaries can also be created for <strong>gt</strong> tables that don’t have row groups, or, don’t have a stub. Finally, we can create a table that has both groupwise summaries and a grand summary.</p>
+<p>Let’s keep it simple and create group summary rows on a table without a stub. We’ll use <code>exibble</code> dataset for this once more. A few <code>exibble</code> columns are <code>select()</code>ed, passed to <code><a href="../reference/gt.html">gt()</a></code>, and then <code><a href="../reference/summary_rows.html">summary_rows()</a></code>. Notice that, in the resulting table, a stub is created just for the summary row labels (they have to go somewhere).</p>
+<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># Create a simple grand summary on a gt</span>
+<span class="co"># table that contains no stub</span>
+<span class="no">exibble_g</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="no">num</span>, <span class="no">char</span>, <span class="no">currency</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>, <span class="no">currency</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>
+  )
+
+<span class="no">exibble_g</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#uyexgsegin .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#uyexgsegin .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#uyexgsegin .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#uyexgsegin .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#uyexgsegin .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#uyexgsegin .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#uyexgsegin .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#uyexgsegin .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#uyexgsegin .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#uyexgsegin .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#uyexgsegin .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#uyexgsegin .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#uyexgsegin .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#uyexgsegin .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#uyexgsegin .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#uyexgsegin .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#uyexgsegin .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#uyexgsegin .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#uyexgsegin .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#uyexgsegin .gt_left {
+  text-align: left;
+}
+
+#uyexgsegin .gt_center {
+  text-align: center;
+}
+
+#uyexgsegin .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#uyexgsegin .gt_font_normal {
+  font-weight: normal;
+}
+
+#uyexgsegin .gt_font_bold {
+  font-weight: bold;
+}
+
+#uyexgsegin .gt_font_italic {
+  font-style: italic;
+}
+
+#uyexgsegin .gt_super {
+  font-size: 65%;
+}
+
+#uyexgsegin .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="uyexgsegin" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">1.111e-01</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">49.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">2.222e+00</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">17.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">3.333e+01</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">1.390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">4.444e+02</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">65100.000</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">5.550e+03</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_right">1325.810</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">NA</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">13.255</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">7.770e+05</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">NA</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub"></td>
+      <td class="gt_row gt_right">8.880e+06</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">0.440</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">avg</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">1,380,432.87</td>
+      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">9,501.26</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row">total</td>
+      <td class="gt_row gt_right gt_grand_summary_row">9,663,030.06</td>
+      <td class="gt_row gt_left gt_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row">66,508.79</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_grand_summary_row">3,319,613.32</td>
+      <td class="gt_row gt_left gt_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row">24,521.60</td>
+    </tr>
+</tbody>
+</table></div>
+<p>By default, <code>groups</code> in the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function is set to <code>NULL</code> and will produce a grand summary.</p>
+<p>A grand summary can be used in conjunction with groupwise summaries. Here’s an mashup where both types are present:</p>
+<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># Using the table in `exibble_f`, create</span>
+<span class="co"># additional grand summary rows (using two</span>
+<span class="co"># separate calls of `grand_summary_rows()`</span>
+<span class="co"># since the formatting</span>
+<span class="co"># will be different)</span>
+<span class="no">exibble_h</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_f</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_number</span>,
+    <span class="kw">suffixing</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
+    <span class="kw">suffixing</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
+  )
+
+<span class="no">exibble_h</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...1`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...2`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY3` -&gt; `::GRAND_SUMMARY3...3`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...4`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...5`</span>
+<span class="co">#&gt; * ...</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
+<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
+<span class="co">#&gt; * ...</span></pre></body></html></div>
+<style>html {
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+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
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+}
+
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+  color: #333333;
+  background-color: #FFFFFF;
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+}
+
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+  color: #333333;
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+  text-transform: inherit;
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+
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+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
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+  border-top-width: 2px;
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+
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+  color: #333333;
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+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#fzzordqyyd .gt_first_grand_summary_row {
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+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
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+  border-top-width: 6px;
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+}
+
+#fzzordqyyd .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+  border-right-width: 2px;
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+  font-size: 90%;
+  padding: 4px;
+}
+
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+  text-align: left;
+}
+
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+  text-align: center;
+}
+
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+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#fzzordqyyd .gt_font_normal {
+  font-weight: normal;
+}
+
+#fzzordqyyd .gt_font_bold {
+  font-weight: bold;
+}
+
+#fzzordqyyd .gt_font_italic {
+  font-style: italic;
+}
+
+#fzzordqyyd .gt_super {
+  font-size: 65%;
+}
+
+#fzzordqyyd .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="fzzordqyyd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1,111 × 10<sup class="gt_super">−1</sup>
+</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">€49,95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2,222</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">€17,95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3,333 × 10<sup class="gt_super">1</sup>
+</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">€1,39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4,444 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">€65 100,00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1,200 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16 292,32</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">4,801 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65 169,29</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">2,168 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€32 538,46</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€1,39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65 100,00</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5,550 × 10<sup class="gt_super">3</sup>
+</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">€1 325,81</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">€13,26</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7,770 × 10<sup class="gt_super">5</sup>
+</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8,880 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">€0,44</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,221 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">9,663 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">4,916 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">avg</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">1,38M</td>
+      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">$9,50K</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row">total</td>
+      <td class="gt_row gt_right gt_grand_summary_row">9,66M</td>
+      <td class="gt_row gt_left gt_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row">$66,51K</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_grand_summary_row">3,32M</td>
+      <td class="gt_row gt_left gt_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row">$24,52K</td>
+    </tr>
+</tbody>
+</table></div>
+<p>Note that the grand summary has a double line separating it from groupwise summary that’s part of <code>grp_b</code>. If this default styling appears to be too subtle, we can elect to add further styling to both groupwise summaries and the grand summary by using <code><a href="../reference/tab_options.html">tab_options()</a></code>.</p>
+</div>
+<div id="adding-some-style-to-the-summary-cells" class="section level3">
+<h3 class="hasAnchor">
+<a href="#adding-some-style-to-the-summary-cells" class="anchor"></a>Adding Some Style to the Summary Cells</h3>
+<p>While the summary cells (both groupwise and grand) have a distinct appearance that sets them apart from the data cells, there’s always the option to modify their appearance. We can use the <code><a href="../reference/tab_options.html">tab_options()</a></code> function to perform these customizations. Here are the options specific to the summary cells (for groupwise summaries) and the grand summary cells:</p>
+<ul>
+<li>
+<code>summary_row.background.color</code> &amp; <code>grand_summary_row.background.color</code>
+</li>
+<li>
+<code>summary_row.padding</code> &amp; <code>grand_summary_row.padding</code>
+</li>
+<li>
+<code>summary_row.text_transform</code> &amp; <code>grand_summary_row.text_transform</code>
+</li>
+</ul>
+<p>We can also target the summary cells and grand summary cells with the location helper functions <code><a href="../reference/cells_summary.html">cells_summary()</a></code> and <code><a href="../reference/cells_grand_summary.html">cells_grand_summary()</a></code>. This is important for adding footnotes with <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> and for setting styles with <code><a href="../reference/tab_style.html">tab_style()</a></code> (both have the <code>locations</code> argument).</p>
+<p>Here is an example that uses multiple calls of <code><a href="../reference/tab_options.html">tab_options()</a></code> and <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code>. The cell background color for both types of summary cells is modified and two footnotes are added.</p>
+<div class="sourceCode" id="cb10"><html><body><pre class="r"><span class="co"># Using the gt table of `exibble_h` as a</span>
+<span class="co"># starting point, style summary cells with</span>
+<span class="co"># `tab_options()` and add two footnotes</span>
+<span class="no">exibble_i</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_h</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
+    <span class="kw">summary_row.background.color</span> <span class="kw">=</span> <span class="st">"lightblue"</span>,
+    <span class="kw">grand_summary_row.background.color</span> <span class="kw">=</span> <span class="st">"lightgreen"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Mean of all *num* values."</span>),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_grand_summary.html">cells_grand_summary</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>), <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">avg</span>)
+    )
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Highest `currency` value in **grp_a**"</span>),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_summary.html">cells_summary</a></span>(
+      <span class="kw">groups</span> <span class="kw">=</span> <span class="st">"grp_a"</span>,
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="st">"max"</span>
+    )
+  )
+
+<span class="no">exibble_i</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...1`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...2`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY3` -&gt; `::GRAND_SUMMARY3...3`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...4`</span>
+<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...5`</span>
+<span class="co">#&gt; * ...</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
+<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
+<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
+<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
+<span class="co">#&gt; * ...</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#qaanlwhcaz .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#qaanlwhcaz .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#qaanlwhcaz .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#qaanlwhcaz .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#qaanlwhcaz .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#qaanlwhcaz .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#qaanlwhcaz .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#qaanlwhcaz .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#qaanlwhcaz .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#qaanlwhcaz .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#qaanlwhcaz .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#qaanlwhcaz .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#qaanlwhcaz .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#qaanlwhcaz .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#qaanlwhcaz .gt_summary_row {
+  color: #333333;
+  background-color: lightblue;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#qaanlwhcaz .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_grand_summary_row {
+  color: #333333;
+  background-color: lightgreen;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#qaanlwhcaz .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#qaanlwhcaz .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#qaanlwhcaz .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#qaanlwhcaz .gt_left {
+  text-align: left;
+}
+
+#qaanlwhcaz .gt_center {
+  text-align: center;
+}
+
+#qaanlwhcaz .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#qaanlwhcaz .gt_font_normal {
+  font-weight: normal;
+}
+
+#qaanlwhcaz .gt_font_bold {
+  font-weight: bold;
+}
+
+#qaanlwhcaz .gt_font_italic {
+  font-style: italic;
+}
+
+#qaanlwhcaz .gt_super {
+  font-size: 65%;
+}
+
+#qaanlwhcaz .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="qaanlwhcaz" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1,111 × 10<sup class="gt_super">−1</sup>
+</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">€49,95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2,222</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">€17,95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3,333 × 10<sup class="gt_super">1</sup>
+</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">€1,39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4,444 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">€65 100,00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1,200 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16 292,32</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">4,801 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65 169,29</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">2,168 × 10<sup class="gt_super">2</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€32 538,46</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€1,39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">€65 100,00<sup class="gt_footnote_marks">1</sup>
+</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5,550 × 10<sup class="gt_super">3</sup>
+</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">€1 325,81</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">€13,26</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7,770 × 10<sup class="gt_super">5</sup>
+</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8,880 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">€0,44</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,221 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
+      <td class="gt_row gt_right gt_summary_row">9,663 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_summary_row">4,916 × 10<sup class="gt_super">6</sup>
+</td>
+      <td class="gt_row gt_left gt_summary_row">—</td>
+      <td class="gt_row gt_right gt_summary_row">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">avg</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">1,38M<sup class="gt_footnote_marks">2</sup>
+</td>
+      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">$9,50K</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row">total</td>
+      <td class="gt_row gt_right gt_grand_summary_row">9,66M</td>
+      <td class="gt_row gt_left gt_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row">$66,51K</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row">s.d.</td>
+      <td class="gt_row gt_right gt_grand_summary_row">3,32M</td>
+      <td class="gt_row gt_left gt_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row">$24,52K</td>
+    </tr>
+</tbody>
+<tfoot><tr class="gt_footnotes">
+<td colspan="4">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>1</em>
+          </sup>
+           
+          Highest <code>currency</code> value in <strong>grp_a</strong>
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>2</em>
+          </sup>
+           
+          Mean of all <em>num</em> values.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+</div>
+<div id="extracting-the-summary-data-from-the-gt-table-object" class="section level3">
+<h3 class="hasAnchor">
+<a href="#extracting-the-summary-data-from-the-gt-table-object" class="anchor"></a>Extracting the Summary Data from the <strong>gt</strong> Table Object</h3>
+<p>For a reproducible workflow, we do not want to have situations where any data created or modified cannot be accessed. While having summarized values be created in a <strong>gt</strong> pipeline presents advantages to readability and intent of analysis, it is recognized that the output table itself is essentially ‘read only’, as the input data undergoes processing and movement to an entirely different format.</p>
+<p>However, the object created still contains data and we can obtain the summary data from a <strong>gt</strong> table object using the <code><a href="../reference/extract_summary.html">extract_summary()</a></code> function. Taking the <code>gt_summary</code> object, we get a list of tibbles containing the summary data while preserving the correct data types:</p>
+<div class="sourceCode" id="cb11"><html><body><pre class="r"><span class="co"># Extract the summary data from `exibble_d`</span>
+<span class="co"># to a list  object</span>
+<span class="no">summary_list</span> <span class="kw">&lt;-</span> <span class="no">exibble_d</span> <span class="kw">%&gt;%</span> <span class="fu"><a href="../reference/extract_summary.html">extract_summary</a></span>()</pre></body></html></div>
+<div class="sourceCode" id="cb12"><html><body><pre class="r"><span class="co"># Print out the summary for the `grp_a` group</span>
+<span class="no">summary_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">summary_df_data_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">grp_a</span>
+<span class="co">#&gt; # A tibble: 3 x 7</span>
+<span class="co">#&gt;   groupname rowname   num  char currency   row group</span>
+<span class="co">#&gt;   &lt;chr&gt;     &lt;chr&gt;   &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
+<span class="co">#&gt; 1 grp_a     avg      120.    NA       NA    NA    NA</span>
+<span class="co">#&gt; 2 grp_a     total    480.    NA       NA    NA    NA</span>
+<span class="co">#&gt; 3 grp_a     s.d.     217.    NA       NA    NA    NA</span></pre></body></html></div>
+<div class="sourceCode" id="cb13"><html><body><pre class="r"><span class="co"># Print out the summary for the `grp_b` group</span>
+<span class="no">summary_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">summary_df_data_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">grp_b</span>
+<span class="co">#&gt; # A tibble: 3 x 7</span>
+<span class="co">#&gt;   groupname rowname      num  char currency   row group</span>
+<span class="co">#&gt;   &lt;chr&gt;     &lt;chr&gt;      &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
+<span class="co">#&gt; 1 grp_b     avg     3220850     NA       NA    NA    NA</span>
+<span class="co">#&gt; 2 grp_b     total   9662550     NA       NA    NA    NA</span>
+<span class="co">#&gt; 3 grp_b     s.d.    4916123.    NA       NA    NA    NA</span></pre></body></html></div>
+<p>The output tibbles within the list always contain the <code>groupname</code> and <code>rowname</code> columns. The <code>groupname</code> column is filled with the name of the row group that was given to <code><a href="../reference/summary_rows.html">summary_rows()</a></code>. The <code>rowname</code> column contains the descriptive stub labels for the summary rows (recall that values are either supplied explicitly in <code><a href="../reference/summary_rows.html">summary_rows()</a></code>, or, are generated from the function names). The remaining columns are those from the original dataset.</p>
+<p>The output data from <code><a href="../reference/extract_summary.html">extract_summary()</a></code> can be reintroduced to a reproducible workflow and serve as downstream inputs or undergo validation. Perhaps interestingly, the output tibbles are structured in a way that facilitates direct input back to <code><a href="../reference/gt.html">gt()</a></code> (i.e., it has the magic <code>groupname</code> and <code>rowname</code> columns). This can produce a new, standalone summary table where the summary rows are now data rows:</p>
+<div class="sourceCode" id="cb14"><html><body><pre class="r"><span class="co"># Take `exibble_d`, which internally has a list</span>
+<span class="co"># of summary data frames, extract the summaries,</span>
+<span class="co"># and then combine them; input that into `gt()`,</span>
+<span class="co"># and format the `num` column with `fmt_number()`</span>
+<span class="no">exibble_d</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/extract_summary.html">extract_summary</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="https://rdrr.io/r/base/unlist.html">unlist</a></span>(<span class="kw">recursive</span> <span class="kw">=</span> <span class="fl">FALSE</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind.html">bind_rows</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">1</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_missing.html">fmt_missing</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">char</span>, <span class="no">currency</span>, <span class="no">row</span>, <span class="no">group</span>)
+  )</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#czzpxmlttm .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
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+  border-top-style: solid;
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+
+#czzpxmlttm .gt_heading {
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+
+#czzpxmlttm .gt_column_spanner_outer {
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+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#czzpxmlttm .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
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+  border-right-width: 1px;
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+  vertical-align: middle;
+}
+
+#czzpxmlttm .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
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+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#czzpxmlttm .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#czzpxmlttm .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#czzpxmlttm .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#czzpxmlttm .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#czzpxmlttm .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#czzpxmlttm .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#czzpxmlttm .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#czzpxmlttm .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#czzpxmlttm .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#czzpxmlttm .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#czzpxmlttm .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#czzpxmlttm .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#czzpxmlttm .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#czzpxmlttm .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#czzpxmlttm .gt_left {
+  text-align: left;
+}
+
+#czzpxmlttm .gt_center {
+  text-align: center;
+}
+
+#czzpxmlttm .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
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+}
+
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+  font-weight: bold;
+}
+
+#czzpxmlttm .gt_font_italic {
+  font-style: italic;
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+
+#czzpxmlttm .gt_super {
+  font-size: 65%;
+}
+
+#czzpxmlttm .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="czzpxmlttm" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">groupname</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">row</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">group</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left gt_stub">avg</td>
+      <td class="gt_row gt_left">grp_a</td>
+      <td class="gt_row gt_right">120.0</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">total</td>
+      <td class="gt_row gt_left">grp_a</td>
+      <td class="gt_row gt_right">480.1</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">s.d.</td>
+      <td class="gt_row gt_left">grp_a</td>
+      <td class="gt_row gt_right">216.8</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">avg</td>
+      <td class="gt_row gt_left">grp_b</td>
+      <td class="gt_row gt_right">3,220,850.0</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">total</td>
+      <td class="gt_row gt_left">grp_b</td>
+      <td class="gt_row gt_right">9,662,550.0</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">s.d.</td>
+      <td class="gt_row gt_left">grp_b</td>
+      <td class="gt_row gt_right">4,916,123.3</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+<div id="providing-our-own-aggregation-functions-to-generate-summary-rows" class="section level3">
+<h3 class="hasAnchor">
+<a href="#providing-our-own-aggregation-functions-to-generate-summary-rows" class="anchor"></a>Providing Our Own Aggregation Functions to Generate Summary Rows</h3>
+<p>While many of the functions available in base R and within packages are useful as aggregate functions, we may occasionally have the need to create our own custom functions. When taking this approach the main things to keep in mind are that a vector of values is the main input, and, a single value should be returned. The return value can be pretty much any class (e.g., <code>numeric</code>, <code>character</code>, <code>logical</code>) and it’s the <code>formatter</code> function that will handle any custom formatting while also converting to <code>character</code>.</p>
+<p>Here, we’ll define a function that takes a vector of numeric values and outputs the two highest values (sorted low to high) above a <code>threshold</code> value. The output from this function is always a formatted <code>character</code> string.</p>
+<div class="sourceCode" id="cb15"><html><body><pre class="r"><span class="co"># Define a function that gives the</span>
+<span class="co"># highest two values above a threshold</span>
+<span class="no">agg_highest_two_above_value</span> <span class="kw">&lt;-</span> <span class="kw">function</span>(<span class="no">x</span>, <span class="no">threshold</span>) {
+
+  <span class="co"># Get sorted values above threshold value</span>
+  <span class="no">values</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/sort.html">sort</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/Round.html">round</a></span>(<span class="no">x</span>[<span class="no">x</span> <span class="kw">&gt;=</span> <span class="no">threshold</span>], <span class="fl">2</span>))
+
+  <span class="co"># Return character string with 2 highest values above threshold</span>
+  <span class="kw">if</span> (<span class="fu"><a href="https://rdrr.io/r/base/length.html">length</a></span>(<span class="no">values</span>) <span class="kw">==</span> <span class="fl">0</span>) {
+    <span class="fu"><a href="https://rdrr.io/r/base/function.html">return</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste0</a></span>(<span class="st">"No values above "</span>, <span class="no">threshold</span>))
+  } <span class="kw">else</span> {
+    <span class="fu"><a href="https://rdrr.io/r/base/function.html">return</a></span>(
+      <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(
+        <span class="fu"><a href="https://rdrr.io/r/base/formatc.html">formatC</a></span>(
+          <span class="fu"><a href="https://rdrr.io/r/utils/head.html">tail</a></span>(
+            <span class="fu"><a href="https://rdrr.io/r/base/sort.html">sort</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/Round.html">round</a></span>(<span class="no">x</span>[<span class="no">x</span> <span class="kw">&gt;</span> <span class="no">threshold</span>], <span class="fl">2</span>)), <span class="fl">2</span>),
+          <span class="kw">format</span> <span class="kw">=</span> <span class="st">"f"</span>, <span class="kw">digits</span> <span class="kw">=</span> <span class="fl">2</span>), <span class="kw">collapse</span> <span class="kw">=</span> <span class="st">", "</span>))
+  }
+}
+
+<span class="co"># Let's test this function with some values</span>
+<span class="fu">agg_highest_two_above_value</span>(
+  <span class="kw">x</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">0.73</span>, <span class="fl">0.93</span>, <span class="fl">0.75</span>, <span class="fl">0.86</span>, <span class="fl">0.23</span>, <span class="fl">0.81</span>),
+  <span class="kw">threshold</span> <span class="kw">=</span> <span class="fl">0.8</span>
+)
+<span class="co">#&gt; [1] "0.86, 0.93"</span></pre></body></html></div>
+<p>Because this is character value that’s returned, we don’t need formatting functions like <code><a href="../reference/fmt_number.html">fmt_number()</a></code>, <code><a href="../reference/fmt_percent.html">fmt_percent()</a></code>, etc. However, a useful formatter (and we do need <em>some</em> formatter) is the <code><a href="../reference/fmt_passthrough.html">fmt_passthrough()</a></code> function. Like the name suggests, it to great extent passes values through but formats as <code>character</code> (like all the <code>fmt_*()</code> function do) and it provides the option to decorate the output with a <code>pattern</code>. Let’s have a look at how the <code>agg_highest_two_above_value()</code> function can be used with the <code><a href="../reference/fmt_passthrough.html">fmt_passthrough()</a></code> formatter function.</p>
+<div class="sourceCode" id="cb16"><html><body><pre class="r"><span class="co"># Create a gt table with `exibble_a` and use</span>
+<span class="co"># the custom function with a threshold of `20`;</span>
+<span class="co"># the `fmt_passthrough` funtion allows for</span>
+<span class="co"># minimal formatting of the aggregate values</span>
+<span class="no">exibble_j</span> <span class="kw">&lt;-</span>
+  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>, <span class="no">currency</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
+      <span class="kw">high</span> <span class="kw">=</span> ~<span class="fu">agg_highest_two_above_value</span>(<span class="no">.</span>, <span class="fl">20</span>)),
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_passthrough</span>,
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"({x})"</span>
+  )
+
+<span class="no">exibble_j</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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+
+#jvnwisjetq .gt_table {
+  display: table;
+  border-collapse: collapse;
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+#jvnwisjetq .gt_col_headings {
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+  border-right-color: #D3D3D3;
+}
+
+#jvnwisjetq .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
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+  padding-top: 5px;
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+  padding-left: 5px;
+  padding-right: 5px;
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+}
+
+#jvnwisjetq .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#jvnwisjetq .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#jvnwisjetq .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#jvnwisjetq .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#jvnwisjetq .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#jvnwisjetq .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#jvnwisjetq .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#jvnwisjetq .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#jvnwisjetq .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#jvnwisjetq .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#jvnwisjetq .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#jvnwisjetq .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#jvnwisjetq .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#jvnwisjetq .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#jvnwisjetq .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#jvnwisjetq .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#jvnwisjetq .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#jvnwisjetq .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#jvnwisjetq .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#jvnwisjetq .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#jvnwisjetq .gt_left {
+  text-align: left;
+}
+
+#jvnwisjetq .gt_center {
+  text-align: center;
+}
+
+#jvnwisjetq .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#jvnwisjetq .gt_font_normal {
+  font-weight: normal;
+}
+
+#jvnwisjetq .gt_font_bold {
+  font-weight: bold;
+}
+
+#jvnwisjetq .gt_font_italic {
+  font-style: italic;
+}
+
+#jvnwisjetq .gt_super {
+  font-size: 65%;
+}
+
+#jvnwisjetq .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="jvnwisjetq" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">1.111e-01</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_right">49.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.222e+00</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_right">17.950</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">3.333e+01</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_right">1.390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">4.444e+02</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_right">65100.000</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5.550e+03</td>
+      <td class="gt_row gt_left">—</td>
+      <td class="gt_row gt_right">1325.810</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">—</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_right">13.255</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">7.770e+05</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_right">—</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8.880e+06</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_right">0.440</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">high</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">(777000.00, 8880000.00)</td>
+      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
+      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">(1325.81, 65100.00)</td>
+    </tr>
+</tbody>
+</table></div>
+<p>We can extract the grand summary data from the <code>exibble_j</code> object. Note that columns <code>num</code> and <code>currency</code> are classed as character since it was character outputs that were generated by the <code>agg_highest_two_above_value()</code> function.</p>
+<div class="sourceCode" id="cb17"><html><body><pre class="r"><span class="co"># Extract the summary list from `exibble_j`</span>
+<span class="co"># and inspect using `str()`</span>
+<span class="no">exibble_j</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/extract_summary.html">extract_summary</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="https://rdrr.io/r/utils/str.html">str</a></span>()
+<span class="co">#&gt; List of 1</span>
+<span class="co">#&gt;  $ summary_df_data_list:List of 1</span>
+<span class="co">#&gt;   ..$ ::GRAND_SUMMARY: tibble [1 × 7] (S3: tbl_df/tbl/data.frame)</span>
+<span class="co">#&gt;   .. ..$ groupname: chr "::GRAND_SUMMARY"</span>
+<span class="co">#&gt;   .. ..$ rowname  : chr "high"</span>
+<span class="co">#&gt;   .. ..$ num      : chr "777000.00, 8880000.00"</span>
+<span class="co">#&gt;   .. ..$ char     : num NA</span>
+<span class="co">#&gt;   .. ..$ currency : chr "1325.81, 65100.00"</span>
+<span class="co">#&gt;   .. ..$ row      : num NA</span>
+<span class="co">#&gt;   .. ..$ group    : num NA</span></pre></body></html></div>
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diff --git a/docs/articles/gt-datasets.html b/docs/articles/gt-datasets.html
new file mode 100644
index 000000000..14dba6a16
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+++ b/docs/articles/gt-datasets.html
@@ -0,0 +1,5507 @@
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+<li>
+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+<li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+<ul class="nav navbar-nav navbar-right">
+<li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+</div>
+<!--/.nav-collapse -->
+  </div>
+<!--/.container -->
+</div>
+<!--/.navbar -->
+
+      
+
+      </header><div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header toc-ignore">
+      <h1 data-toc-skip>gt Datasets</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/rstudio/gt/blob/master/vignettes/gt-datasets.Rmd"><code>vignettes/gt-datasets.Rmd</code></a></small>
+      <div class="hidden name"><code>gt-datasets.Rmd</code></div>
+
+    </div>
+
+    
+    
+<p>The <strong>gt</strong> package comes with six built-in datasets for experimenting with the <strong>gt</strong> API: <code>countrypops</code>, <code>sza</code>, <code>gtcars</code>, <code>sp500</code>, <code>pizzaplace</code>, and <code>exibble</code>. While each dataset has different subject matter, all of them will be used to develop <strong>gt</strong> examples with consistent syntax.</p>
+<p><img src="images/countrypops.png" width="30%"><img src="images/sza.svg" width="30%"><img src="images/gtcars.svg" width="30%"></p>
+<p><img src="images/sp500.svg" width="30%"><img src="images/pizzaplace.svg" width="30%"><img src="images/exibble.svg" width="30%"></p>
+<p>Each dataset is stored as a tibble, ranging from very small (like <code>exibble</code>, an example tibble of 8 rows) to quite large in size (e.g., at nearly 50,000 rows: <code>pizzaplace</code>). Larger datasets are typically impractical as <strong>gt output tables</strong> but they provide opportunities for demonstrating preprocessing using tidyverse tools like <strong>dplyr</strong> and <strong>tidyr</strong> (upstream of <strong>gt</strong>’s <code><a href="../reference/gt.html">gt()</a></code> entry point).</p>
+<p>In many <strong>gt</strong> workflows, there will often be prep work like this where the creation of the input table and any salient information (e.g., metadata for footnotes) will be done alongside the preparation of the display table.</p>
+<p>In the next few examples, we’ll show how tables can be created with each of these datasets. Each example will be preceded with a set of requirements that serve as a design brief. This planning stage can be very useful in your own work for the purpose of organization. The hope is that this collection of simple examples will inspire the creation of much more interesting display tables with <strong>gt</strong>.</p>
+<div id="countrypops" class="section level3">
+<h3 class="hasAnchor">
+<a href="#countrypops" class="anchor"></a><code>countrypops</code>
+</h3>
+<p>This dataset provides the total populations of 215 countries on a yearly basis, from 1960 to 2017. The source data comes from the <a href="https://data.worldbank.org/indicator/SP.POP.TOTL">World Bank</a>, where it has been cleaned and tidied up for inclusion into this package. Each row contains a population value for a country in a given year, where <code>NA</code> values for <code>population</code> indicate that the country did not exist in that particular year.</p>
+<p>The <code>countrypops</code> dataset is a tibble with 12,470 rows and 5 variables. Here are explanations for each of the variables:</p>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#ntmtsrqqnk .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: smaller;
+  background-color: #FFFFFF;
+  width: 80%;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#ntmtsrqqnk .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#ntmtsrqqnk .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: small;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#ntmtsrqqnk .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: small;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#ntmtsrqqnk .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#ntmtsrqqnk .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#ntmtsrqqnk .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#ntmtsrqqnk .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ntmtsrqqnk .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ntmtsrqqnk .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#ntmtsrqqnk .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#ntmtsrqqnk .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#ntmtsrqqnk .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#ntmtsrqqnk .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#ntmtsrqqnk .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ntmtsrqqnk .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ntmtsrqqnk .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ntmtsrqqnk .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ntmtsrqqnk .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ntmtsrqqnk .gt_left {
+  text-align: left;
+}
+
+#ntmtsrqqnk .gt_center {
+  text-align: center;
+}
+
+#ntmtsrqqnk .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#ntmtsrqqnk .gt_font_normal {
+  font-weight: normal;
+}
+
+#ntmtsrqqnk .gt_font_bold {
+  font-weight: bold;
+}
+
+#ntmtsrqqnk .gt_font_italic {
+  font-style: italic;
+}
+
+#ntmtsrqqnk .gt_super {
+  font-size: 65%;
+}
+
+#ntmtsrqqnk .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="ntmtsrqqnk" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">country_name</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">Name of the country</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">country_code_2</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The 2-letter ISO 3166-1 country code</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">country_code_3</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The 3-letter ISO 3166-1 country code</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">year</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
+      <td class="gt_row gt_left">The year for the population estimate</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">population</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
+      <td class="gt_row gt_left">The population estimate, midway through the year</td>
+    </tr>
+</tbody>
+</table></div>
+<div id="a-countrypops-example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#a-countrypops-example" class="anchor"></a>A <code>countrypops</code> Example</h4>
+<p>The table that we’ll create from <code>countrypops</code> will meet these requirements:</p>
+<ol style="list-style-type: decimal">
+<li>use countries from Oceania</li>
+<li>countries in different regions of Oceania will be grouped together</li>
+<li>provide populations for the 1995, 2005, and 2015 years only; they should appear as separate columns with a spanner group column stating that these columns refer to population values</li>
+<li>format population figures to contain commas</li>
+<li>provide a descriptive title</li>
+</ol>
+<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># Get vectors of 2-letter country codes for</span>
+<span class="co"># each region of Oceania</span>
+<span class="no">Australasia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"AU"</span>, <span class="st">"NZ"</span>)
+<span class="no">Melanesia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"NC"</span>, <span class="st">"PG"</span>, <span class="st">"SB"</span>, <span class="st">"VU"</span>)
+<span class="no">Micronesia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"FM"</span>, <span class="st">"GU"</span>, <span class="st">"KI"</span>, <span class="st">"MH"</span>, <span class="st">"MP"</span>, <span class="st">"NR"</span>, <span class="st">"PW"</span>)
+<span class="no">Polynesia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"PF"</span>, <span class="st">"WS"</span>, <span class="st">"TO"</span>, <span class="st">"TV"</span>)
+
+<span class="co"># Create a gt table based on a preprocessed `countrypops`</span>
+<span class="no">countrypops</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(
+    <span class="no">Australasia</span>, <span class="no">Melanesia</span>, <span class="no">Micronesia</span>, <span class="no">Polynesia</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">year</span> <span class="kw">%in%</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">1995</span>, <span class="fl">2005</span>, <span class="fl">2015</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">region</span> <span class="kw">=</span> <span class="fu">case_when</span>(
+    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Australasia</span> ~ <span class="st">"Australasia"</span>,
+    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Melanesia</span> ~ <span class="st">"Melanesia"</span>,
+    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Micronesia</span> ~ <span class="st">"Micronesia"</span>,
+    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Polynesia</span> ~ <span class="st">"Polynesia"</span>,
+  )) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">tidyr</span><span class="kw ns">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(<span class="kw">key</span> <span class="kw">=</span> <span class="no">year</span>, <span class="kw">value</span> <span class="kw">=</span> <span class="no">population</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="no">region</span>, <span class="fu">desc</span>(<span class="no">`2015`</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="fu"><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">starts_with</a></span>(<span class="st">"country_code"</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(
+    <span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"country_name"</span>,
+    <span class="kw">groupname_col</span> <span class="kw">=</span> <span class="st">"region"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"Populations of Oceania's Countries in 1995, 2005, and 2015"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
+    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Total Population"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">`1995`</span>, <span class="no">`2005`</span>, <span class="no">`2015`</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">`1995`</span>, <span class="no">`2005`</span>, <span class="no">`2015`</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>,
+    <span class="kw">use_seps</span> <span class="kw">=</span> <span class="fl">TRUE</span>
+  )</pre></body></html></div>
+<style>html {
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+</style>
+<div id="zjutxkuzhy" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="4" class="gt_heading gt_title gt_font_normal" style>Populations of Oceania's Countries in 1995, 2005, and 2015</th>
+    </tr>
+<tr>
+<th colspan="4" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
+    </tr>
+</thead>
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Total Population</span>
+      </th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">1995</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">2005</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">2015</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">Australasia</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Australia</td>
+      <td class="gt_row gt_center">18,072,000</td>
+      <td class="gt_row gt_center">20,394,800</td>
+      <td class="gt_row gt_center">23,850,784</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">New Zealand</td>
+      <td class="gt_row gt_center">3,673,400</td>
+      <td class="gt_row gt_center">4,133,900</td>
+      <td class="gt_row gt_center">4,595,700</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">Melanesia</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Papua New Guinea</td>
+      <td class="gt_row gt_center">4,894,276</td>
+      <td class="gt_row gt_center">6,314,709</td>
+      <td class="gt_row gt_center">7,919,825</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Solomon Islands</td>
+      <td class="gt_row gt_center">359,225</td>
+      <td class="gt_row gt_center">469,885</td>
+      <td class="gt_row gt_center">587,482</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">New Caledonia</td>
+      <td class="gt_row gt_center">193,816</td>
+      <td class="gt_row gt_center">232,250</td>
+      <td class="gt_row gt_center">272,400</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Vanuatu</td>
+      <td class="gt_row gt_center">168,235</td>
+      <td class="gt_row gt_center">209,370</td>
+      <td class="gt_row gt_center">264,603</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">Micronesia</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Guam</td>
+      <td class="gt_row gt_center">145,561</td>
+      <td class="gt_row gt_center">158,402</td>
+      <td class="gt_row gt_center">161,797</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Kiribati</td>
+      <td class="gt_row gt_center">77,730</td>
+      <td class="gt_row gt_center">92,325</td>
+      <td class="gt_row gt_center">112,407</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Micronesia (Federated States)</td>
+      <td class="gt_row gt_center">107,556</td>
+      <td class="gt_row gt_center">106,196</td>
+      <td class="gt_row gt_center">104,433</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Northern Mariana Islands</td>
+      <td class="gt_row gt_center">56,278</td>
+      <td class="gt_row gt_center">63,744</td>
+      <td class="gt_row gt_center">54,816</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Marshall Islands</td>
+      <td class="gt_row gt_center">51,015</td>
+      <td class="gt_row gt_center">52,055</td>
+      <td class="gt_row gt_center">52,994</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Palau</td>
+      <td class="gt_row gt_center">17,253</td>
+      <td class="gt_row gt_center">19,906</td>
+      <td class="gt_row gt_center">21,288</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Nauru</td>
+      <td class="gt_row gt_center">9,969</td>
+      <td class="gt_row gt_center">10,114</td>
+      <td class="gt_row gt_center">12,475</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="4" class="gt_group_heading">Polynesia</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">French Polynesia</td>
+      <td class="gt_row gt_center">215,196</td>
+      <td class="gt_row gt_center">254,886</td>
+      <td class="gt_row gt_center">277,690</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Samoa</td>
+      <td class="gt_row gt_center">170,157</td>
+      <td class="gt_row gt_center">179,929</td>
+      <td class="gt_row gt_center">193,759</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Tonga</td>
+      <td class="gt_row gt_center">96,076</td>
+      <td class="gt_row gt_center">101,041</td>
+      <td class="gt_row gt_center">106,364</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Tuvalu</td>
+      <td class="gt_row gt_center">9,230</td>
+      <td class="gt_row gt_center">10,027</td>
+      <td class="gt_row gt_center">11,001</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+</div>
+<div id="sza" class="section level3">
+<h3 class="hasAnchor">
+<a href="#sza" class="anchor"></a><code>sza</code>
+</h3>
+<p>The solar zenith angle is one measure of the solar position. It can be thought of as ‘height’ of the sun in relation to an observer. A solar zenith angle of 0° indicates that the sun is directly overhead (a different solar angle, the <em>solar altitude angle</em>, is 90° in this instance). With the sun at the horizontal (e.g., during sunrise/sunset) we observe the solar zenith angle to be around 90° (there is the matter of atmospheric refraction). During nighttime, solar zenith angles in the range of 90–180 are possible (again, depending on the location of the observer).</p>
+<p>The <code>sza</code> dataset has calculated values for the solar zenith angles every 30 minutes from 04:00 to 12:00 (true solar time). Temporally, these calculations are for the 1st of every month of the year. Spatially, the observer is located at somewhere along latitudes 20°N, 30°N, 40°N, and 50°N (because we are using true solar time, the longitude is unimportant). This is quite an extensive topic, and more information can be found by using <code><a href="../reference/sza.html">?sza</a></code> in the R console or by visiting <a href="https://en.wikipedia.org/wiki/Solar_zenith_angle">this page</a>.</p>
+<p>The <code>sza</code> dataset is a tibble with 816 rows and 4 variables. Here are explanations for each of the variables:</p>
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+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#mpwkaodbur .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#mpwkaodbur .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#mpwkaodbur .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#mpwkaodbur .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#mpwkaodbur .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#mpwkaodbur .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#mpwkaodbur .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpwkaodbur .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#mpwkaodbur .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpwkaodbur .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#mpwkaodbur .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mpwkaodbur .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mpwkaodbur .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#mpwkaodbur .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mpwkaodbur .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#mpwkaodbur .gt_left {
+  text-align: left;
+}
+
+#mpwkaodbur .gt_center {
+  text-align: center;
+}
+
+#mpwkaodbur .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#mpwkaodbur .gt_font_normal {
+  font-weight: normal;
+}
+
+#mpwkaodbur .gt_font_bold {
+  font-weight: bold;
+}
+
+#mpwkaodbur .gt_font_italic {
+  font-style: italic;
+}
+
+#mpwkaodbur .gt_super {
+  font-size: 65%;
+}
+
+#mpwkaodbur .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="mpwkaodbur" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">latitude</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">The latitude in decimal degrees for the observations</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">month</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">fct</td>
+      <td class="gt_row gt_left">The measurement month; all calculations where conducted for the first day of each month</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">tst</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The true solar time at the given latitude and date (first of month) for which the solar zenith angle is calculated</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">sza</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">The solar zenith angle in degrees, where NAs indicate that sunrise hadn't yet occurred by the tst value</td>
+    </tr>
+</tbody>
+</table></div>
+<div id="an-sza-example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#an-sza-example" class="anchor"></a>An <code>sza</code> Example</h4>
+<p>The table that we’ll create from <code>sza</code> will meet these requirements:</p>
+<ol style="list-style-type: decimal">
+<li>filter the data to just use the 20°N data and remove the <code>latitude</code> column</li>
+<li>
+<code>NA</code> values from <code>sza</code> column are to be removed</li>
+<li>reshape the table so that columns of <code>tst</code> (true solar time) contain angles in degrees (from the <code>sza</code> column)</li>
+<li>the <strong>gt output table</strong> will have the <code>month</code>s as row labels in the stub</li>
+<li>missing values will be replaced with an empty string (so that those cells are blank)</li>
+<li>a stubhead label will state what’s inside the stubs (months, at 20°N)</li>
+<li>the table will have a heading decorated with the HTML <em>Black Sun with Rays</em> (<code>&amp;#x2600;</code>) symbol</li>
+<li>to fit the large amount of data in a small area, use some table options to reduce text size and row padding</li>
+</ol>
+<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Create a gt table based on a preprocessed `sza`</span>
+<span class="no">sza</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">latitude</span> <span class="kw">==</span> <span class="fl">20</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">latitude</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(!<span class="fu"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span>(<span class="no">sza</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">tidyr</span><span class="kw ns">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(<span class="kw">key</span> <span class="kw">=</span> <span class="st">"tst"</span>, <span class="kw">value</span> <span class="kw">=</span> <span class="no">sza</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"month"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_missing.html">fmt_missing</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">missing_text</span> <span class="kw">=</span> <span class="st">""</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_stubhead.html">tab_stubhead</a></span>(<span class="kw">label</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"month&lt;br&gt;(20&amp;deg;N)"</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"&amp;#x2600; Solar Zenith Angles &amp;#x2600;"</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
+    <span class="kw">column_labels.font.size</span> <span class="kw">=</span> <span class="st">"smaller"</span>,
+    <span class="kw">table.font.size</span> <span class="kw">=</span> <span class="st">"smaller"</span>,
+    <span class="kw">data_row.padding</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">3</span>)
+  )</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#sutwoosmmg .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: smaller;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#sutwoosmmg .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#sutwoosmmg .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: smaller;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#sutwoosmmg .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: smaller;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#sutwoosmmg .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#sutwoosmmg .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#sutwoosmmg .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#sutwoosmmg .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#sutwoosmmg .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#sutwoosmmg .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#sutwoosmmg .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#sutwoosmmg .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#sutwoosmmg .gt_row {
+  padding-top: 3px;
+  padding-bottom: 3px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#sutwoosmmg .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#sutwoosmmg .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#sutwoosmmg .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#sutwoosmmg .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#sutwoosmmg .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#sutwoosmmg .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#sutwoosmmg .gt_left {
+  text-align: left;
+}
+
+#sutwoosmmg .gt_center {
+  text-align: center;
+}
+
+#sutwoosmmg .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#sutwoosmmg .gt_font_normal {
+  font-weight: normal;
+}
+
+#sutwoosmmg .gt_font_bold {
+  font-weight: bold;
+}
+
+#sutwoosmmg .gt_font_italic {
+  font-style: italic;
+}
+
+#sutwoosmmg .gt_super {
+  font-size: 65%;
+}
+
+#sutwoosmmg .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="sutwoosmmg" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="15" class="gt_heading gt_title gt_font_normal" style>☀ Solar Zenith Angles ☀</th>
+    </tr>
+<tr>
+<th colspan="15" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">month<br>(20°N)</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0530</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0600</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0630</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0700</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0730</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0800</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0830</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0900</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0930</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1000</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1030</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1100</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1130</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1200</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left gt_stub">jan</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">84.9</td>
+      <td class="gt_row gt_right">78.7</td>
+      <td class="gt_row gt_right">72.7</td>
+      <td class="gt_row gt_right">66.1</td>
+      <td class="gt_row gt_right">61.5</td>
+      <td class="gt_row gt_right">56.5</td>
+      <td class="gt_row gt_right">52.1</td>
+      <td class="gt_row gt_right">48.3</td>
+      <td class="gt_row gt_right">45.5</td>
+      <td class="gt_row gt_right">43.6</td>
+      <td class="gt_row gt_right">43.0</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">feb</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">88.9</td>
+      <td class="gt_row gt_right">82.5</td>
+      <td class="gt_row gt_right">75.8</td>
+      <td class="gt_row gt_right">69.6</td>
+      <td class="gt_row gt_right">63.3</td>
+      <td class="gt_row gt_right">57.7</td>
+      <td class="gt_row gt_right">52.2</td>
+      <td class="gt_row gt_right">47.4</td>
+      <td class="gt_row gt_right">43.1</td>
+      <td class="gt_row gt_right">40.0</td>
+      <td class="gt_row gt_right">37.8</td>
+      <td class="gt_row gt_right">37.2</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">mar</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">85.7</td>
+      <td class="gt_row gt_right">78.8</td>
+      <td class="gt_row gt_right">72.0</td>
+      <td class="gt_row gt_right">65.2</td>
+      <td class="gt_row gt_right">58.6</td>
+      <td class="gt_row gt_right">52.3</td>
+      <td class="gt_row gt_right">46.2</td>
+      <td class="gt_row gt_right">40.5</td>
+      <td class="gt_row gt_right">35.5</td>
+      <td class="gt_row gt_right">31.4</td>
+      <td class="gt_row gt_right">28.6</td>
+      <td class="gt_row gt_right">27.7</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">apr</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">88.5</td>
+      <td class="gt_row gt_right">81.5</td>
+      <td class="gt_row gt_right">74.4</td>
+      <td class="gt_row gt_right">67.4</td>
+      <td class="gt_row gt_right">60.3</td>
+      <td class="gt_row gt_right">53.4</td>
+      <td class="gt_row gt_right">46.5</td>
+      <td class="gt_row gt_right">39.7</td>
+      <td class="gt_row gt_right">33.2</td>
+      <td class="gt_row gt_right">26.9</td>
+      <td class="gt_row gt_right">21.3</td>
+      <td class="gt_row gt_right">17.2</td>
+      <td class="gt_row gt_right">15.5</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">may</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">85.0</td>
+      <td class="gt_row gt_right">78.2</td>
+      <td class="gt_row gt_right">71.2</td>
+      <td class="gt_row gt_right">64.3</td>
+      <td class="gt_row gt_right">57.2</td>
+      <td class="gt_row gt_right">50.2</td>
+      <td class="gt_row gt_right">43.2</td>
+      <td class="gt_row gt_right">36.1</td>
+      <td class="gt_row gt_right">29.1</td>
+      <td class="gt_row gt_right">26.1</td>
+      <td class="gt_row gt_right">15.2</td>
+      <td class="gt_row gt_right">8.8</td>
+      <td class="gt_row gt_right">5.0</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">jun</td>
+      <td class="gt_row gt_right">89.2</td>
+      <td class="gt_row gt_right">82.7</td>
+      <td class="gt_row gt_right">76.0</td>
+      <td class="gt_row gt_right">69.3</td>
+      <td class="gt_row gt_right">62.5</td>
+      <td class="gt_row gt_right">55.7</td>
+      <td class="gt_row gt_right">48.8</td>
+      <td class="gt_row gt_right">41.9</td>
+      <td class="gt_row gt_right">35.0</td>
+      <td class="gt_row gt_right">28.1</td>
+      <td class="gt_row gt_right">21.1</td>
+      <td class="gt_row gt_right">14.2</td>
+      <td class="gt_row gt_right">7.3</td>
+      <td class="gt_row gt_right">2.0</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">jul</td>
+      <td class="gt_row gt_right">88.8</td>
+      <td class="gt_row gt_right">82.3</td>
+      <td class="gt_row gt_right">75.7</td>
+      <td class="gt_row gt_right">69.1</td>
+      <td class="gt_row gt_right">62.3</td>
+      <td class="gt_row gt_right">55.5</td>
+      <td class="gt_row gt_right">48.7</td>
+      <td class="gt_row gt_right">41.8</td>
+      <td class="gt_row gt_right">35.0</td>
+      <td class="gt_row gt_right">28.1</td>
+      <td class="gt_row gt_right">21.2</td>
+      <td class="gt_row gt_right">14.3</td>
+      <td class="gt_row gt_right">7.7</td>
+      <td class="gt_row gt_right">3.1</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">aug</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">83.8</td>
+      <td class="gt_row gt_right">77.1</td>
+      <td class="gt_row gt_right">70.2</td>
+      <td class="gt_row gt_right">63.3</td>
+      <td class="gt_row gt_right">56.4</td>
+      <td class="gt_row gt_right">49.4</td>
+      <td class="gt_row gt_right">42.4</td>
+      <td class="gt_row gt_right">35.4</td>
+      <td class="gt_row gt_right">28.3</td>
+      <td class="gt_row gt_right">21.3</td>
+      <td class="gt_row gt_right">14.3</td>
+      <td class="gt_row gt_right">7.3</td>
+      <td class="gt_row gt_right">1.9</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">sep</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">87.2</td>
+      <td class="gt_row gt_right">80.2</td>
+      <td class="gt_row gt_right">73.2</td>
+      <td class="gt_row gt_right">66.1</td>
+      <td class="gt_row gt_right">59.1</td>
+      <td class="gt_row gt_right">52.1</td>
+      <td class="gt_row gt_right">45.1</td>
+      <td class="gt_row gt_right">38.1</td>
+      <td class="gt_row gt_right">31.3</td>
+      <td class="gt_row gt_right">24.7</td>
+      <td class="gt_row gt_right">18.6</td>
+      <td class="gt_row gt_right">13.7</td>
+      <td class="gt_row gt_right">11.6</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">oct</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">84.1</td>
+      <td class="gt_row gt_right">77.1</td>
+      <td class="gt_row gt_right">70.2</td>
+      <td class="gt_row gt_right">63.3</td>
+      <td class="gt_row gt_right">56.5</td>
+      <td class="gt_row gt_right">49.9</td>
+      <td class="gt_row gt_right">43.5</td>
+      <td class="gt_row gt_right">37.5</td>
+      <td class="gt_row gt_right">32.0</td>
+      <td class="gt_row gt_right">27.4</td>
+      <td class="gt_row gt_right">24.3</td>
+      <td class="gt_row gt_right">23.1</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">nov</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">87.8</td>
+      <td class="gt_row gt_right">81.3</td>
+      <td class="gt_row gt_right">74.5</td>
+      <td class="gt_row gt_right">68.3</td>
+      <td class="gt_row gt_right">61.8</td>
+      <td class="gt_row gt_right">56.0</td>
+      <td class="gt_row gt_right">50.2</td>
+      <td class="gt_row gt_right">45.3</td>
+      <td class="gt_row gt_right">40.7</td>
+      <td class="gt_row gt_right">37.4</td>
+      <td class="gt_row gt_right">35.1</td>
+      <td class="gt_row gt_right">34.4</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">dec</td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right"></td>
+      <td class="gt_row gt_right">84.3</td>
+      <td class="gt_row gt_right">78.0</td>
+      <td class="gt_row gt_right">71.8</td>
+      <td class="gt_row gt_right">66.1</td>
+      <td class="gt_row gt_right">60.5</td>
+      <td class="gt_row gt_right">55.6</td>
+      <td class="gt_row gt_right">50.9</td>
+      <td class="gt_row gt_right">47.2</td>
+      <td class="gt_row gt_right">44.2</td>
+      <td class="gt_row gt_right">42.4</td>
+      <td class="gt_row gt_right">41.8</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+</div>
+<div id="gtcars" class="section level3">
+<h3 class="hasAnchor">
+<a href="#gtcars" class="anchor"></a><code>gtcars</code>
+</h3>
+<p>The <code>gtcars</code> dataset takes off where <code>mtcars</code> left off. It contains 47 cars from the 2014-2017 model years. Many of the <code>gtcars</code> vehicles are grand tourers. Indeed, many of these provide the ability to cross an entire continent at speed and in comfort yet, when it’s called for, they will allow you to experience driving thrills. The chassis and suspension are in most cases top-notch and supply superb handling and roadholding on all routes one would conceivably encounter during the grand touring experience. The two plus two (2 + 2) seating configuration is smartly designed to deliver comfort for a driver and passenger, adequate space for luggage, and have room to spare.</p>
+<p>The <code>gtcars</code> dataset is a tibble with 47 rows and 15 variables. Here are explanations for each of the variables:</p>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#sdequqnald .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: smaller;
+  background-color: #FFFFFF;
+  width: 80%;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#sdequqnald .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#sdequqnald .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#sdequqnald .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#sdequqnald .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#sdequqnald .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#sdequqnald .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: small;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#sdequqnald .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: small;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#sdequqnald .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#sdequqnald .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#sdequqnald .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#sdequqnald .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#sdequqnald .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#sdequqnald .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#sdequqnald .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#sdequqnald .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#sdequqnald .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#sdequqnald .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#sdequqnald .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#sdequqnald .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#sdequqnald .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#sdequqnald .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#sdequqnald .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#sdequqnald .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#sdequqnald .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#sdequqnald .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#sdequqnald .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#sdequqnald .gt_left {
+  text-align: left;
+}
+
+#sdequqnald .gt_center {
+  text-align: center;
+}
+
+#sdequqnald .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#sdequqnald .gt_font_normal {
+  font-weight: normal;
+}
+
+#sdequqnald .gt_font_bold {
+  font-weight: bold;
+}
+
+#sdequqnald .gt_font_italic {
+  font-style: italic;
+}
+
+#sdequqnald .gt_super {
+  font-size: 65%;
+}
+
+#sdequqnald .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="sdequqnald" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">mfr</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The name of the car manufacturer</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">model</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The car's model name</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">year</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
+      <td class="gt_row gt_left">The car's model year</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">trim</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">A short description of the car model's trim</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">bdy_style</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">An identifier of the car's body style, which is either coupe, convertible,     sedan, or hatchback</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">hp, hp_rpm</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
+      <td class="gt_row gt_left">The car's horsepower and the associated RPM level</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">trq, trq_rpm</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
+      <td class="gt_row gt_left">The car's torque and the associated RPM level</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">mpg_c, mpg_h</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
+      <td class="gt_row gt_left">The miles per gallon fuel efficiency rating for city and highway driving</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">drivetrain</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The car's drivetrain which, for this dataset is either rwd (Rear Wheel Drive)     or awd (All Wheel Drive)</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">trsmn</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The codified transmission type, where the number part is the number of gears; the car could have automatic transmission (a), manual transmission (m), an option to switch between both types (am), or, direct drive (dd)</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">ctry_origin</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The country name for where the vehicle manufacturer is headquartered</td>
+    </tr>
+</tbody>
+</table></div>
+<div id="a-gtcars-example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#a-gtcars-example" class="anchor"></a>A <code>gtcars</code> Example</h4>
+<p>The table that we’ll create from <code>gtcars</code> will meet these requirements:</p>
+<ol style="list-style-type: decimal">
+<li>only include German cars</li>
+<li>limit the dataset to the top two most expensive offerings from each German manufacturer</li>
+<li>the information included will be the manufacturer (<code>mfr</code>), the car model (<code>model</code>), the <code>drivetrain</code>, and the price (<code>msrp</code>)</li>
+<li>add a table title</li>
+<li>combine the car make and model into a single column</li>
+<li>capitalize the <code>drivetrain</code> text</li>
+<li>format the prices as USD currency with commas and no decimal places shown</li>
+<li>relabel the column headings to provide nicer labels</li>
+<li>add two footnotes that explain the <code>drivetrain</code> abbreviations and that state the currency of the <code>msrp</code> prices; ensure that the footnote marks are lowercase letters</li>
+</ol>
+<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Create a gt table based on a preprocessed `gtcars`</span>
+<span class="no">gtcars</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">ctry_origin</span> <span class="kw">==</span> <span class="st">"Germany"</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">mfr</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/top_n.html">top_n</a></span>(<span class="fl">2</span>, <span class="no">msrp</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">ungroup</a></span>() <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="no">mfr</span>, <span class="no">model</span>, <span class="no">drivetrain</span>, <span class="no">msrp</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"Select German Automobiles"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mfr</span>, <span class="no">model</span>),
+    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">model</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>)),
+    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) <span class="fu"><a href="https://rdrr.io/r/base/chartr.html">toupper</a></span>(<span class="no">x</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
+    <span class="kw">mfr</span> <span class="kw">=</span> <span class="st">"Car"</span>,
+    <span class="kw">drivetrain</span> <span class="kw">=</span> <span class="st">"Drivetrain"</span>,
+    <span class="kw">msrp</span> <span class="kw">=</span> <span class="st">"MSRP"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"Prices in USD."</span>,
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_column_labels.html">cells_column_labels</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>))
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"AWD = All Wheel Drive, RWD = Rear Wheel Drive."</span>,
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_column_labels.html">cells_column_labels</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>))
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/opt_footnote_marks.html">opt_footnote_marks</a></span>(<span class="kw">marks</span> <span class="kw">=</span> <span class="st">"letters"</span>)</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#gvwnpsiqmg .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#gvwnpsiqmg .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#gvwnpsiqmg .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#gvwnpsiqmg .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#gvwnpsiqmg .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#gvwnpsiqmg .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#gvwnpsiqmg .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#gvwnpsiqmg .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#gvwnpsiqmg .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#gvwnpsiqmg .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#gvwnpsiqmg .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#gvwnpsiqmg .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#gvwnpsiqmg .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#gvwnpsiqmg .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#gvwnpsiqmg .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#gvwnpsiqmg .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#gvwnpsiqmg .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#gvwnpsiqmg .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#gvwnpsiqmg .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#gvwnpsiqmg .gt_left {
+  text-align: left;
+}
+
+#gvwnpsiqmg .gt_center {
+  text-align: center;
+}
+
+#gvwnpsiqmg .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#gvwnpsiqmg .gt_font_normal {
+  font-weight: normal;
+}
+
+#gvwnpsiqmg .gt_font_bold {
+  font-weight: bold;
+}
+
+#gvwnpsiqmg .gt_font_italic {
+  font-style: italic;
+}
+
+#gvwnpsiqmg .gt_super {
+  font-size: 65%;
+}
+
+#gvwnpsiqmg .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="gvwnpsiqmg" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="3" class="gt_heading gt_title gt_font_normal" style>Select German Automobiles</th>
+    </tr>
+<tr>
+<th colspan="3" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Car</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Drivetrain<sup class="gt_footnote_marks">a</sup>
+</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">MSRP<sup class="gt_footnote_marks">b</sup>
+</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">BMW i8</td>
+      <td class="gt_row gt_left">AWD</td>
+      <td class="gt_row gt_right">$140,700</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">BMW M6</td>
+      <td class="gt_row gt_left">RWD</td>
+      <td class="gt_row gt_right">$113,400</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Audi R8</td>
+      <td class="gt_row gt_left">AWD</td>
+      <td class="gt_row gt_right">$115,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Audi S8</td>
+      <td class="gt_row gt_left">AWD</td>
+      <td class="gt_row gt_right">$114,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Mercedes-Benz AMG GT</td>
+      <td class="gt_row gt_left">RWD</td>
+      <td class="gt_row gt_right">$129,900</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Mercedes-Benz SL-Class</td>
+      <td class="gt_row gt_left">RWD</td>
+      <td class="gt_row gt_right">$85,050</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Porsche 911</td>
+      <td class="gt_row gt_left">RWD</td>
+      <td class="gt_row gt_right">$84,300</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Porsche Panamera</td>
+      <td class="gt_row gt_left">RWD</td>
+      <td class="gt_row gt_right">$78,100</td>
+    </tr>
+</tbody>
+<tfoot><tr class="gt_footnotes">
+<td colspan="3">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>a</em>
+          </sup>
+           
+          AWD = All Wheel Drive, RWD = Rear Wheel Drive.
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>b</em>
+          </sup>
+           
+          Prices in USD.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+</div>
+</div>
+<div id="sp500" class="section level3">
+<h3 class="hasAnchor">
+<a href="#sp500" class="anchor"></a><code>sp500</code>
+</h3>
+<p>The S&amp;P 500 is a capitalization-weighted index of about 500 leading companies (where bigger companies have more influence within the index) that have common stock listed in either the NYSE or NASDAQ markets. The companies chosen are intended to provide representation of the U.S. economy. This index is a managed list (managed by S&amp;P Dow Jones Indices LLC) with occasional changes of the constituent companies based on their performance and changes in the economy.</p>
+<p>There is daily S&amp;P 500 data available in the <code>sp500</code> dataset, with daily indicators (price statistics, <code>volume</code>, etc.) from 1950 to 2015, inclusive. There are 16,607 rows in the dataset, and 7 variables:</p>
+<style>html {
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+</style>
+<div id="fqzkghpubl" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">date</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">date</td>
+      <td class="gt_row gt_left">The date expressed as `Date` values</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">open, high, low, close</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">The day's opening, high, low, and closing prices in USD; the close price is adjusted for splits</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">volume</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">The number of trades for the given `date`</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">adj_close</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">The close price adjusted for both dividends and splits</td>
+    </tr>
+</tbody>
+</table></div>
+<div id="an-sp500-example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#an-sp500-example" class="anchor"></a>An <code>sp500</code> Example</h4>
+<p>The table that we’ll create from <code>sp500</code> will meet these requirements:</p>
+<ol style="list-style-type: decimal">
+<li>use only data from the period <code>2010-06-02</code> to <code>2010-06-15</code>
+</li>
+<li>the adjusted close <code>adj_close</code> column won’t be included</li>
+<li>a title and subtitle will be added to describe the contents of the table</li>
+<li>put the column labels in title case</li>
+<li>format the <code>date</code> column to appear as ‘2 Jun 2010’</li>
+<li>have the price columns (<code>open</code>, <code>high</code>, <code>low</code>, <code>close</code>) appear in USD</li>
+<li>the large numbers in <code>volume</code> will be shown as billions (with the <code>B</code> suffix)</li>
+<li>up- and down-pointing triangles (in green and red) will be added alongside the <code>close</code> price as appropriate</li>
+</ol>
+<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># Define the start and end dates for the data range</span>
+<span class="no">start_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-02"</span>
+<span class="no">end_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-15"</span>
+
+<span class="co"># The HTML decimal references for the black</span>
+<span class="co"># up- and down-pointing triangles are: #9650 and #9660;</span>
+<span class="co"># use an in-line style to apply color</span>
+<span class="no">up_arrow</span> <span class="kw">&lt;-</span> <span class="st">"&lt;span style=\"color:green\"&gt;&amp;#9650;&lt;/span&gt;"</span>
+<span class="no">down_arrow</span> <span class="kw">&lt;-</span> <span class="st">"&lt;span style=\"color:red\"&gt;&amp;#9660;&lt;/span&gt;"</span>
+
+<span class="co"># Create a gt table based on a preprocessed `sp500`</span>
+<span class="no">sp500</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">date</span> <span class="kw">&gt;=</span> <span class="no">start_date</span> <span class="kw">&amp;</span> <span class="no">date</span> <span class="kw">&lt;=</span> <span class="no">end_date</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">adj_close</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"S&amp;P 500"</span>,
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="kw pkg">glue</span><span class="kw ns">::</span><span class="fu"><a href="https://glue.tidyverse.org/reference/glue.html">glue</a></span>(<span class="st">"{start_date} to {end_date}"</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_date.html">fmt_date</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">date</span>),
+    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">7</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">open</span>, <span class="no">high</span>, <span class="no">low</span>, <span class="no">close</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">volume</span>),
+    <span class="kw">scale_by</span> <span class="kw">=</span> <span class="fl">1</span> / <span class="fl">1E9</span>,
+    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{x}B"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="st">"close"</span>,
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">close</span> <span class="kw">&gt;</span> <span class="no">open</span>),
+    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">x</span>, <span class="no">up_arrow</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="st">"close"</span>,
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">close</span> <span class="kw">&lt;</span> <span class="no">open</span>),
+    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">x</span>, <span class="no">down_arrow</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
+    <span class="kw">date</span> <span class="kw">=</span> <span class="st">"Date"</span>, <span class="kw">open</span> <span class="kw">=</span> <span class="st">"Open"</span>, <span class="kw">high</span> <span class="kw">=</span> <span class="st">"High"</span>,
+    <span class="kw">low</span> <span class="kw">=</span> <span class="st">"Low"</span>, <span class="kw">close</span> <span class="kw">=</span> <span class="st">"Close"</span>, <span class="kw">volume</span> <span class="kw">=</span> <span class="st">"Volume"</span>
+  )</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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+
+#cpmgcykcvp .gt_table {
+  display: table;
+  border-collapse: collapse;
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+<div id="cpmgcykcvp" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="6" class="gt_heading gt_title gt_font_normal" style>S&amp;P 500</th>
+    </tr>
+<tr>
+<th colspan="6" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>2010-06-02 to 2010-06-15</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Date</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Open</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">High</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Low</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Close</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Volume</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">15 Jun 2010</td>
+      <td class="gt_row gt_right">$1,091.21</td>
+      <td class="gt_row gt_right">$1,115.59</td>
+      <td class="gt_row gt_right">$1,091.21</td>
+      <td class="gt_row gt_right">$1,115.23 <span style="color:green">▲</span>
+</td>
+      <td class="gt_row gt_right">4.64B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">14 Jun 2010</td>
+      <td class="gt_row gt_right">$1,095.00</td>
+      <td class="gt_row gt_right">$1,105.91</td>
+      <td class="gt_row gt_right">$1,089.03</td>
+      <td class="gt_row gt_right">$1,089.63 <span style="color:red">▼</span>
+</td>
+      <td class="gt_row gt_right">4.43B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">11 Jun 2010</td>
+      <td class="gt_row gt_right">$1,082.65</td>
+      <td class="gt_row gt_right">$1,092.25</td>
+      <td class="gt_row gt_right">$1,077.12</td>
+      <td class="gt_row gt_right">$1,091.60 <span style="color:green">▲</span>
+</td>
+      <td class="gt_row gt_right">4.06B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">10 Jun 2010</td>
+      <td class="gt_row gt_right">$1,058.77</td>
+      <td class="gt_row gt_right">$1,087.85</td>
+      <td class="gt_row gt_right">$1,058.77</td>
+      <td class="gt_row gt_right">$1,086.84 <span style="color:green">▲</span>
+</td>
+      <td class="gt_row gt_right">5.14B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">9 Jun 2010</td>
+      <td class="gt_row gt_right">$1,062.75</td>
+      <td class="gt_row gt_right">$1,077.74</td>
+      <td class="gt_row gt_right">$1,052.25</td>
+      <td class="gt_row gt_right">$1,055.69 <span style="color:red">▼</span>
+</td>
+      <td class="gt_row gt_right">5.98B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">8 Jun 2010</td>
+      <td class="gt_row gt_right">$1,050.81</td>
+      <td class="gt_row gt_right">$1,063.15</td>
+      <td class="gt_row gt_right">$1,042.17</td>
+      <td class="gt_row gt_right">$1,062.00 <span style="color:green">▲</span>
+</td>
+      <td class="gt_row gt_right">6.19B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">7 Jun 2010</td>
+      <td class="gt_row gt_right">$1,065.84</td>
+      <td class="gt_row gt_right">$1,071.36</td>
+      <td class="gt_row gt_right">$1,049.86</td>
+      <td class="gt_row gt_right">$1,050.47 <span style="color:red">▼</span>
+</td>
+      <td class="gt_row gt_right">5.47B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">4 Jun 2010</td>
+      <td class="gt_row gt_right">$1,098.43</td>
+      <td class="gt_row gt_right">$1,098.43</td>
+      <td class="gt_row gt_right">$1,060.50</td>
+      <td class="gt_row gt_right">$1,064.88 <span style="color:red">▼</span>
+</td>
+      <td class="gt_row gt_right">6.18B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">3 Jun 2010</td>
+      <td class="gt_row gt_right">$1,098.82</td>
+      <td class="gt_row gt_right">$1,105.67</td>
+      <td class="gt_row gt_right">$1,091.81</td>
+      <td class="gt_row gt_right">$1,102.83 <span style="color:green">▲</span>
+</td>
+      <td class="gt_row gt_right">5.00B</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">2 Jun 2010</td>
+      <td class="gt_row gt_right">$1,073.01</td>
+      <td class="gt_row gt_right">$1,098.56</td>
+      <td class="gt_row gt_right">$1,072.03</td>
+      <td class="gt_row gt_right">$1,098.38 <span style="color:green">▲</span>
+</td>
+      <td class="gt_row gt_right">5.03B</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+</div>
+<div id="pizzaplace" class="section level3">
+<h3 class="hasAnchor">
+<a href="#pizzaplace" class="anchor"></a><code>pizzaplace</code>
+</h3>
+<p>The <code>pizzaplace</code> dataset is unusual to say the least. It brings up more questions than answers. Why is it that the ‘The Greek’ pizza (<code>the_greek</code>) comes in <code>XL</code> and <code>XXL</code> sizes whilst (almost) all the other pizzas adhere to the <code>S</code>-<code>M</code>-<code>L</code> paradigm? Why is the ‘Brie Carre’ pizza (<code>brie_carre</code>) only small? Also, is any of this real (?), and, what is the nature of reality? (All of these questions are quite complicated… however, while I can doubt the existence of the material world, I cannot doubt the existence of myself as someone thinking about all the delicious pizzas on offer at <code>pizzaplace</code>.)</p>
+<p>We have somehow obtained the 2015 sales from the pizzaplace, where each row is a pizza sold. There are 32 different types of pizza in 4 different categories: <code>classic</code>, <code>chicken</code>, <code>supreme</code>, and <code>veggie</code>. It was a great year of sales, personal problems notwithstanding. A kitchen fire in late September did not help with the morale situation. Nevertheless, $817,860 in sales for the year! That was indeed something to be cheerful about.</p>
+<p>Let’s learn more about how this fascinating dataset is structured:</p>
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+}
+
+#qpiyasedvl .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#qpiyasedvl .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#qpiyasedvl .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#qpiyasedvl .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#qpiyasedvl .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#qpiyasedvl .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#qpiyasedvl .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#qpiyasedvl .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#qpiyasedvl .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#qpiyasedvl .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#qpiyasedvl .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#qpiyasedvl .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#qpiyasedvl .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#qpiyasedvl .gt_left {
+  text-align: left;
+}
+
+#qpiyasedvl .gt_center {
+  text-align: center;
+}
+
+#qpiyasedvl .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#qpiyasedvl .gt_font_normal {
+  font-weight: normal;
+}
+
+#qpiyasedvl .gt_font_bold {
+  font-weight: bold;
+}
+
+#qpiyasedvl .gt_font_italic {
+  font-style: italic;
+}
+
+#qpiyasedvl .gt_super {
+  font-size: 65%;
+}
+
+#qpiyasedvl .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="qpiyasedvl" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">id</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The ID for the order, which consists of one or more pizzas at a given `date` and `time`</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">date</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">A character representation of the order `date`, expressed in the ISO 8601 date format (YYYY-MM-DD)</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">time</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">A character representation of the order time, expressed as a 24-hour time the ISO 8601 extended time format (hh:mm:ss)</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">name</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The short name for the pizza</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">size</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The size of the pizza, which can either be S, M, L, XL (rare!), or XXL (even rarer!); most pizzas are available in the S, M, and L sizes but exceptions apply</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">type</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">The category or type of pizza, which can either be `classic`, `chicken`, `supreme`, or `veggie`</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">price</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">The price of the pizza and the amount that it sold for (in USD)</td>
+    </tr>
+</tbody>
+</table></div>
+<div id="a-pizzaplace-example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#a-pizzaplace-example" class="anchor"></a>A <code>pizzaplace</code> Example</h4>
+<p>Let’s make a reporting table from the <code>pizzaplace</code> dataset with these requirements:</p>
+<ol style="list-style-type: decimal">
+<li>obtain the total sale numbers and revenue from each <code>size</code> of pizza from each category (<code>type</code>)</li>
+<li>create a gt table where each row represents a combination of <code>size</code>-<code>type</code> (<code>size</code> provides the row labels and <code>type</code> forms the row groups)</li>
+<li>add a title to explain the contents of the table</li>
+<li>format the numeric <code>sold</code> column to use commas and no decimal places</li>
+<li>format the currency values (<code>income</code>) to be in <code>USD</code> currency</li>
+<li>add a summary for each grouping that provides total sell counts and revenue amounts</li>
+<li>color the row groups and summary cells to add a little pizzazz</li>
+</ol>
+<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Create a gt table based on a preprocessed `pizzaplace`</span>
+<span class="no">pizzaplace</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">type</span>, <span class="no">size</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarize</a></span>(
+    <span class="kw">sold</span> <span class="kw">=</span> <span class="fu">n</span>(),
+    <span class="kw">income</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span>(<span class="no">price</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"size"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"Pizzas Sold in 2015"</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">sold</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>,
+    <span class="kw">use_seps</span> <span class="kw">=</span> <span class="fl">TRUE</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">income</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">sold</span>),
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(<span class="kw">TOTAL</span> <span class="kw">=</span> <span class="st">"sum"</span>),
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_number</span>,
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>,
+    <span class="kw">use_seps</span> <span class="kw">=</span> <span class="fl">TRUE</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
+    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="st">"income"</span>,
+    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(<span class="kw">TOTAL</span> <span class="kw">=</span> <span class="st">"sum"</span>),
+    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
+    <span class="kw">summary_row.background.color</span> <span class="kw">=</span> <span class="st">"#ACEACE"</span>,
+    <span class="kw">row_group.background.color</span> <span class="kw">=</span> <span class="st">"#FFEFDB"</span>
+  )
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * chicken -&gt; chicken...1</span>
+<span class="co">#&gt; * chicken -&gt; chicken...2</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * classic -&gt; classic...1</span>
+<span class="co">#&gt; * classic -&gt; classic...2</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * supreme -&gt; supreme...1</span>
+<span class="co">#&gt; * supreme -&gt; supreme...2</span>
+<span class="co">#&gt; New names:</span>
+<span class="co">#&gt; * veggie -&gt; veggie...1</span>
+<span class="co">#&gt; * veggie -&gt; veggie...2</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#ckaehssopn .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#ckaehssopn .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#ckaehssopn .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#ckaehssopn .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#ckaehssopn .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#ckaehssopn .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#ckaehssopn .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#ckaehssopn .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFEFDB;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ckaehssopn .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFEFDB;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ckaehssopn .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#ckaehssopn .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#ckaehssopn .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#ckaehssopn .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#ckaehssopn .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#ckaehssopn .gt_summary_row {
+  color: #333333;
+  background-color: #ACEACE;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ckaehssopn .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ckaehssopn .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ckaehssopn .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ckaehssopn .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ckaehssopn .gt_left {
+  text-align: left;
+}
+
+#ckaehssopn .gt_center {
+  text-align: center;
+}
+
+#ckaehssopn .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#ckaehssopn .gt_font_normal {
+  font-weight: normal;
+}
+
+#ckaehssopn .gt_font_bold {
+  font-weight: bold;
+}
+
+#ckaehssopn .gt_font_italic {
+  font-style: italic;
+}
+
+#ckaehssopn .gt_super {
+  font-size: 65%;
+}
+
+#ckaehssopn .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="ckaehssopn" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="3" class="gt_heading gt_title gt_font_normal" style>Pizzas Sold in 2015</th>
+    </tr>
+<tr>
+<th colspan="3" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">sold</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">income</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="3" class="gt_group_heading">chicken</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">L</td>
+      <td class="gt_row gt_center">4,932</td>
+      <td class="gt_row gt_right">$102,339.00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">M</td>
+      <td class="gt_row gt_center">3,894</td>
+      <td class="gt_row gt_right">$65,224.50</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">S</td>
+      <td class="gt_row gt_center">2,224</td>
+      <td class="gt_row gt_right">$28,356.00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
+      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">11,050</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$195,919.50</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="3" class="gt_group_heading">classic</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">L</td>
+      <td class="gt_row gt_center">4,057</td>
+      <td class="gt_row gt_right">$74,518.50</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">M</td>
+      <td class="gt_row gt_center">4,112</td>
+      <td class="gt_row gt_right">$60,581.75</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">S</td>
+      <td class="gt_row gt_center">6,139</td>
+      <td class="gt_row gt_right">$69,870.25</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">XL</td>
+      <td class="gt_row gt_center">552</td>
+      <td class="gt_row gt_right">$14,076.00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">XXL</td>
+      <td class="gt_row gt_center">28</td>
+      <td class="gt_row gt_right">$1,006.60</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
+      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">14,888</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$220,053.10</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="3" class="gt_group_heading">supreme</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">L</td>
+      <td class="gt_row gt_center">4,564</td>
+      <td class="gt_row gt_right">$94,258.50</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">M</td>
+      <td class="gt_row gt_center">4,046</td>
+      <td class="gt_row gt_right">$66,475.00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">S</td>
+      <td class="gt_row gt_center">3,377</td>
+      <td class="gt_row gt_right">$47,463.50</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
+      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">11,987</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$208,197.00</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="3" class="gt_group_heading">veggie</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">L</td>
+      <td class="gt_row gt_center">5,403</td>
+      <td class="gt_row gt_right">$104,202.70</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">M</td>
+      <td class="gt_row gt_center">3,583</td>
+      <td class="gt_row gt_right">$57,101.00</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">S</td>
+      <td class="gt_row gt_center">2,663</td>
+      <td class="gt_row gt_right">$32,386.75</td>
+    </tr>
+<tr>
+<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
+      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">11,649</td>
+      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$193,690.45</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+</div>
+<div id="exibble" class="section level3">
+<h3 class="hasAnchor">
+<a href="#exibble" class="anchor"></a><code>exibble</code>
+</h3>
+<p>The example tibble that’s useful for <strong>gt</strong> is called <code>exibble</code>. It’s 8 rows, has clear ordering of data, and the columns contain data that can be tested with the various <strong>gt</strong> formatter functions (<code>fmt*()</code>). Here is a table describing the columns of <code>exibble</code>:</p>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#ptfncyashx .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: smaller;
+  background-color: #FFFFFF;
+  width: 80%;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#ptfncyashx .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#ptfncyashx .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: small;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#ptfncyashx .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: small;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#ptfncyashx .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#ptfncyashx .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#ptfncyashx .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#ptfncyashx .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ptfncyashx .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#ptfncyashx .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#ptfncyashx .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#ptfncyashx .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#ptfncyashx .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#ptfncyashx .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#ptfncyashx .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ptfncyashx .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#ptfncyashx .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ptfncyashx .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#ptfncyashx .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#ptfncyashx .gt_left {
+  text-align: left;
+}
+
+#ptfncyashx .gt_center {
+  text-align: center;
+}
+
+#ptfncyashx .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#ptfncyashx .gt_font_normal {
+  font-weight: normal;
+}
+
+#ptfncyashx .gt_font_bold {
+  font-weight: bold;
+}
+
+#ptfncyashx .gt_font_italic {
+  font-style: italic;
+}
+
+#ptfncyashx .gt_super {
+  font-size: 65%;
+}
+
+#ptfncyashx .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="ptfncyashx" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">num</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">A numeric column ordered with increasingly larger values</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">char</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">A character column composed of names of fruits from a to h</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">fctr</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">fct</td>
+      <td class="gt_row gt_left">A factor column with numbers from 1 to 8, written out</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">date, time, datetime</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">Character columns with dates, times, and datetimes</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">currency</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
+      <td class="gt_row gt_left">A numeric column that is useful for testing currency-based formatting</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">row</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">A character column in the format `row_X` which can be useful for testing with row label in a table stub</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left" style="font-family: Courier;">group</td>
+      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
+      <td class="gt_row gt_left">A character column with four `grp_a` values and four `grp_b` values which can be useful for testing tables that contain row groups</td>
+    </tr>
+</tbody>
+</table></div>
+<div id="an-exibble-example" class="section level4">
+<h4 class="hasAnchor">
+<a href="#an-exibble-example" class="anchor"></a>An <code>exibble</code> Example</h4>
+<p>Let’s test as many formatter functions as possible with <code>exibble</code> while also using row labels and row groups (furnished by the <code>row</code> and <code>group</code> columns). We’ll format <code>num</code> to display numbers with 2 decimal places. The dates in <code>date</code> will be formatted with <code>date_style</code> <code>6</code> (the <code>m_day_year</code> style, use <code><a href="../reference/info_date_style.html">info_date_style()</a></code> to learn about all of them). The 24-h time values in <code>time</code> will use <code>time_style</code> <code>4</code> (<code>hm_p</code>, more info at <code><a href="../reference/info_time_style.html">info_time_style()</a></code>). Datetimes as in <code>datetime</code> column can be formatted with the <code><a href="../reference/fmt_datetime.html">fmt_datetime()</a></code> function (which uses the <code>date_style</code> and <code>time_style</code> arguments). The column <code>currency</code> will be formatted as a currency with <code>fmt_currency</code> and we’ll consider these values to be euros (<code>currency = "EUR"</code>).</p>
+<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Create a gt table based on `exibble`</span>
+<span class="no">exibble</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(
+    <span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"row"</span>,
+    <span class="kw">groupname_col</span> <span class="kw">=</span> <span class="st">"group"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
+    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">2</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_date.html">fmt_date</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">date</span>),
+    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">6</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_time.html">fmt_time</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">time</span>),
+    <span class="kw">time_style</span> <span class="kw">=</span> <span class="fl">4</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_datetime.html">fmt_datetime</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">datetime</span>),
+    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">6</span>,
+    <span class="kw">time_style</span> <span class="kw">=</span> <span class="fl">4</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
+    <span class="kw">column_labels.font.size</span> <span class="kw">=</span> <span class="st">"small"</span>,
+    <span class="kw">table.font.size</span> <span class="kw">=</span> <span class="st">"small"</span>,
+    <span class="kw">row_group.font.size</span> <span class="kw">=</span> <span class="st">"small"</span>,
+    <span class="kw">data_row.padding</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">3</span>)
+  )</pre></body></html></div>
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+}
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+}
+
+#cyfkjzuccx .gt_stub {
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+  border-right-style: solid;
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+}
+
+#cyfkjzuccx .gt_summary_row {
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+
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+}
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+#cyfkjzuccx .gt_table_body {
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+}
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+#cyfkjzuccx .gt_footnotes {
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+#cyfkjzuccx .gt_footnote {
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+}
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+#cyfkjzuccx .gt_sourcenotes {
+  color: #333333;
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+</style>
+<div id="cyfkjzuccx" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">fctr</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">date</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">time</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">datetime</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">grp_a</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_1</td>
+      <td class="gt_row gt_right">0.11</td>
+      <td class="gt_row gt_left">apricot</td>
+      <td class="gt_row gt_center">one</td>
+      <td class="gt_row gt_left">Jan 15, 2015</td>
+      <td class="gt_row gt_left">1:35 PM</td>
+      <td class="gt_row gt_left">Jan 1, 2018 2:22 AM</td>
+      <td class="gt_row gt_right">€49.95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_2</td>
+      <td class="gt_row gt_right">2.22</td>
+      <td class="gt_row gt_left">banana</td>
+      <td class="gt_row gt_center">two</td>
+      <td class="gt_row gt_left">Feb 15, 2015</td>
+      <td class="gt_row gt_left">2:40 PM</td>
+      <td class="gt_row gt_left">Feb 2, 2018 2:33 PM</td>
+      <td class="gt_row gt_right">€17.95</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_3</td>
+      <td class="gt_row gt_right">33.33</td>
+      <td class="gt_row gt_left">coconut</td>
+      <td class="gt_row gt_center">three</td>
+      <td class="gt_row gt_left">Mar 15, 2015</td>
+      <td class="gt_row gt_left">3:45 PM</td>
+      <td class="gt_row gt_left">Mar 3, 2018 3:44 AM</td>
+      <td class="gt_row gt_right">€1.39</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_4</td>
+      <td class="gt_row gt_right">444.40</td>
+      <td class="gt_row gt_left">durian</td>
+      <td class="gt_row gt_center">four</td>
+      <td class="gt_row gt_left">Apr 15, 2015</td>
+      <td class="gt_row gt_left">4:50 PM</td>
+      <td class="gt_row gt_left">Apr 4, 2018 3:55 PM</td>
+      <td class="gt_row gt_right">€65,100.00</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="8" class="gt_group_heading">grp_b</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_5</td>
+      <td class="gt_row gt_right">5,550.00</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_center">five</td>
+      <td class="gt_row gt_left">May 15, 2015</td>
+      <td class="gt_row gt_left">5:55 PM</td>
+      <td class="gt_row gt_left">May 5, 2018 4:00 AM</td>
+      <td class="gt_row gt_right">€1,325.81</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_6</td>
+      <td class="gt_row gt_right">NA</td>
+      <td class="gt_row gt_left">fig</td>
+      <td class="gt_row gt_center">six</td>
+      <td class="gt_row gt_left">Jun 15, 2015</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_left">Jun 6, 2018 4:11 PM</td>
+      <td class="gt_row gt_right">€13.26</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_7</td>
+      <td class="gt_row gt_right">777,000.00</td>
+      <td class="gt_row gt_left">grapefruit</td>
+      <td class="gt_row gt_center">seven</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_left">7:10 PM</td>
+      <td class="gt_row gt_left">Jul 7, 2018 5:22 AM</td>
+      <td class="gt_row gt_right">NA</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">row_8</td>
+      <td class="gt_row gt_right">8,880,000.00</td>
+      <td class="gt_row gt_left">honeydew</td>
+      <td class="gt_row gt_center">eight</td>
+      <td class="gt_row gt_left">Aug 15, 2015</td>
+      <td class="gt_row gt_left">8:20 PM</td>
+      <td class="gt_row gt_left">NA</td>
+      <td class="gt_row gt_right">€0.44</td>
+    </tr>
+</tbody>
+</table></div>
+</div>
+</div>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+
+      </div>
+
+</div>
+
+
+
+      <footer><div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href="https://www.rstudio.com"><img src="https://www.tidyverse.org/rstudio-logo.svg" alt="RStudio" height="24"></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+</div>
+
+  
+
+
+  </body>
+</html>
diff --git a/docs/articles/index.html b/docs/articles/index.html
new file mode 100644
index 000000000..6bd5556b0
--- /dev/null
+++ b/docs/articles/index.html
@@ -0,0 +1,178 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Articles • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="../bootstrap-toc.css">
+<script src="../bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+
+<!-- pkgdown -->
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+      <h1 data-toc-skip>Introduction to Creating gt Tables</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/rstudio/gt/blob/master/vignettes/intro-creating-gt-tables.Rmd"><code>vignettes/intro-creating-gt-tables.Rmd</code></a></small>
+      <div class="hidden name"><code>intro-creating-gt-tables.Rmd</code></div>
+
+    </div>
+
+    
+    
+<p>The <strong>gt</strong> package is all about making it simple to produce nice-looking display tables. Display tables? Well yes, we are trying to distinguish between data tables (e.g., tibbles, <code>data.frame</code>s, etc.) and those tables you’d find in a web page, a journal article, or in a magazine. Such tables can likewise be called presentation tables, summary tables, or just tables really. Here are some examples, ripped straight from the web:</p>
+<p><img src="images/tables_from_the_web.png" width="100%"></p>
+<p>We can think of display tables as output only, where we’d not want to use them as input ever again. Other features include annotations, table element styling, and text transformations that serve to communicate the subject matter more clearly.</p>
+<div id="a-walkthrough-of-the-gt-basics-with-a-simple-table" class="section level3">
+<h3 class="hasAnchor">
+<a href="#a-walkthrough-of-the-gt-basics-with-a-simple-table" class="anchor"></a>A Walkthrough of the <strong>gt</strong> Basics with a Simple Table</h3>
+<p>Let’s use a less common dataset that is available in the R <strong>datasets</strong> package: <code>islands</code>. It’s actually not a data frame but a named vector. That’s okay though, we can use use <strong>dplyr</strong> and prepare a tibble from it:</p>
+<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># Take the `islands` dataset and use some</span>
+<span class="co"># dplyr functionality to obtain the ten</span>
+<span class="co"># biggest islands in the world</span>
+<span class="no">islands_tbl</span> <span class="kw">&lt;-</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">tibble</a></span>(
+    <span class="kw">name</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html">names</a></span>(<span class="no">islands</span>),
+    <span class="kw">size</span> <span class="kw">=</span> <span class="no">islands</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="fu">desc</span>(<span class="no">size</span>)) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/slice.html">slice</a></span>(<span class="fl">1</span>:<span class="fl">10</span>)
+
+<span class="co"># Display the table</span>
+<span class="no">islands_tbl</span>
+<span class="co">#&gt; # A tibble: 10 x 2</span>
+<span class="co">#&gt;    name           size</span>
+<span class="co">#&gt;    &lt;chr&gt;         &lt;dbl&gt;</span>
+<span class="co">#&gt;  1 Asia          16988</span>
+<span class="co">#&gt;  2 Africa        11506</span>
+<span class="co">#&gt;  3 North America  9390</span>
+<span class="co">#&gt;  4 South America  6795</span>
+<span class="co">#&gt;  5 Antarctica     5500</span>
+<span class="co">#&gt;  6 Europe         3745</span>
+<span class="co">#&gt;  7 Australia      2968</span>
+<span class="co">#&gt;  8 Greenland       840</span>
+<span class="co">#&gt;  9 New Guinea      306</span>
+<span class="co">#&gt; 10 Borneo          280</span></pre></body></html></div>
+<p>Given that <code>islands_tbl</code> is a tibble, we now have a suitable input for <strong>gt</strong>.</p>
+<p>The main entry point into the <strong>gt</strong> API is the <code><a href="../reference/gt.html">gt()</a></code> function. If we pass <code>islands_tbl</code> to the <em>function</em> <code><a href="../reference/gt.html">gt()</a></code>, we’ll get a <strong>gt Table</strong> as output. As an aside, we could have easily used a data frame instead as valid <strong>Table Data</strong> for <strong>gt</strong>.</p>
+<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Create a display table showing ten of</span>
+<span class="co"># the largest islands in the world</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span> <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">islands_tbl</span>)
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#skmoceplzt .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
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+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#skmoceplzt .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
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+#skmoceplzt .gt_col_headings {
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+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
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+  border-left-color: #D3D3D3;
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+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#skmoceplzt .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
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+}
+
+#skmoceplzt .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#skmoceplzt .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#skmoceplzt .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#skmoceplzt .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#skmoceplzt .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#skmoceplzt .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#skmoceplzt .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#skmoceplzt .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#skmoceplzt .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#skmoceplzt .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#skmoceplzt .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#skmoceplzt .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#skmoceplzt .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#skmoceplzt .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#skmoceplzt .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#skmoceplzt .gt_left {
+  text-align: left;
+}
+
+#skmoceplzt .gt_center {
+  text-align: center;
+}
+
+#skmoceplzt .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#skmoceplzt .gt_font_normal {
+  font-weight: normal;
+}
+
+#skmoceplzt .gt_font_bold {
+  font-weight: bold;
+}
+
+#skmoceplzt .gt_font_italic {
+  font-style: italic;
+}
+
+#skmoceplzt .gt_super {
+  font-size: 65%;
+}
+
+#skmoceplzt .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="skmoceplzt" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+</table></div>
+<p>That doesn’t look too bad. Sure, it’s basic but we really didn’t really ask for much. We did receive a proper table with column labels and the data. Also, that default striping is a nice touch. Oftentimes however, you’ll want a bit more: a <strong>Table header</strong>, a <strong>Stub</strong>, and sometimes <em>footnotes</em> and <em>source notes</em> in the <strong>Table Footer</strong> part.</p>
+</div>
+<div id="adding-parts-to-this-simple-table" class="section level3">
+<h3 class="hasAnchor">
+<a href="#adding-parts-to-this-simple-table" class="anchor"></a>Adding Parts to this Simple Table</h3>
+<p>The <strong>gt</strong> package makes it relatively easy to add parts so that the resulting <strong>gt Table</strong> better conveys the information you want to present. These table parts work well together and there the possible variations in arrangement can handle most tabular presentation needs. The previous <strong>gt Table</strong> demonstrated had only two parts, the <strong>Column Labels</strong> and the <strong>Table Body</strong>. The next few examples will show all of the other table parts that are available.</p>
+<p>This is the way the main parts of a table (and their subparts) fit together:</p>
+<p align="center">
+<img src="../man/figures/gt_parts_of_a_table.svg" width="100%"></p>
+<p>The parts (roughly from top to bottom) are:</p>
+<ul>
+<li>the <strong>Table Header</strong> (optional; with a <strong>title</strong> and possibly a <strong>subtitle</strong>)</li>
+<li>the <strong>Stub</strong> and the <strong>Stub Head</strong> (optional; contains <em>row labels</em>, optionally within <em>row groups</em> having <em>row group labels</em> and possibly <em>summary labels</em> when a summary is present)</li>
+<li>the <strong>Column Labels</strong> (contains <em>column labels</em>, optionally under <em>spanner column labels</em>)</li>
+<li>the <strong>Table Body</strong> (contains <em>columns</em> and <em>rows</em> of <em>cells</em>)</li>
+<li>the <strong>Table Footer</strong> (optional; possibly with <strong>footnotes</strong> and <strong>source notes</strong>)</li>
+</ul>
+<p>The way that we add parts like the <strong>Table Header</strong> and <em>footnotes</em> in the <strong>Table Footer</strong> is to use the <code>tab_*()</code> family of functions. A <strong>Table Header</strong> is easy to add so let’s see how the previous table looks with a <strong>title</strong> and a <strong>subtitle</strong>. We can add this part using the <code><a href="../reference/tab_header.html">tab_header()</a></code> function:</p>
+<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Make a display table with the `islands_tbl`</span>
+<span class="co"># table; put a heading just above the column labels</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"Large Landmasses of the World"</span>,
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"The top ten largest are presented"</span>
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#caiiyhzwxp .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#caiiyhzwxp .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#caiiyhzwxp .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#caiiyhzwxp .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#caiiyhzwxp .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#caiiyhzwxp .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#caiiyhzwxp .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#caiiyhzwxp .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#caiiyhzwxp .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#caiiyhzwxp .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#caiiyhzwxp .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#caiiyhzwxp .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#caiiyhzwxp .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#caiiyhzwxp .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#caiiyhzwxp .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#caiiyhzwxp .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#caiiyhzwxp .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#caiiyhzwxp .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#caiiyhzwxp .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#caiiyhzwxp .gt_left {
+  text-align: left;
+}
+
+#caiiyhzwxp .gt_center {
+  text-align: center;
+}
+
+#caiiyhzwxp .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#caiiyhzwxp .gt_font_normal {
+  font-weight: normal;
+}
+
+#caiiyhzwxp .gt_font_bold {
+  font-weight: bold;
+}
+
+#caiiyhzwxp .gt_font_italic {
+  font-style: italic;
+}
+
+#caiiyhzwxp .gt_super {
+  font-size: 65%;
+}
+
+#caiiyhzwxp .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="caiiyhzwxp" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+</table></div>
+<p>The <strong>Header</strong> table part provides an opportunity to describe the data that’s presented. The <code>subtitle</code>, which functions as a subtitle, is an optional part of the <strong>Header</strong>. We may also style the <code>title</code> and <code>subtitle</code> using Markdown! We do this by wrapping the values passed to <code>title</code> or <code>subtitle</code> with the <code><a href="../reference/md.html">md()</a></code> function. Here is an example with the table data truncated for brevity:</p>
+<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># Use markdown for the heading's `title` and `subtitle` to</span>
+<span class="co"># add bold and italicized characters</span>
+<span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="no">islands_tbl</span>[<span class="fl">1</span>:<span class="fl">2</span>,]) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"**Large Landmasses of the World**"</span>),
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The *top two* largest are presented"</span>)
+  )</pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#metfygbmlu .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
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+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
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+}
+
+#metfygbmlu .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#metfygbmlu .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
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+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
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+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#metfygbmlu .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
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+#metfygbmlu .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
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+#metfygbmlu .gt_column_spanner_outer:last-child {
+  padding-right: 0;
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+#metfygbmlu .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
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+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#metfygbmlu .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
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+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#metfygbmlu .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
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+  border-bottom-width: 2px;
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+  vertical-align: middle;
+}
+
+#metfygbmlu .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#metfygbmlu .gt_from_md > :first-child {
+  margin-top: 0;
+}
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+#metfygbmlu .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#metfygbmlu .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
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+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#metfygbmlu .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#metfygbmlu .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#metfygbmlu .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#metfygbmlu .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
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+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
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+  border-right-color: #D3D3D3;
+}
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+#metfygbmlu .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#metfygbmlu .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
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+  border-right-color: #D3D3D3;
+}
+
+#metfygbmlu .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#metfygbmlu .gt_left {
+  text-align: left;
+}
+
+#metfygbmlu .gt_center {
+  text-align: center;
+}
+
+#metfygbmlu .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#metfygbmlu .gt_font_normal {
+  font-weight: normal;
+}
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+#metfygbmlu .gt_font_bold {
+  font-weight: bold;
+}
+
+#metfygbmlu .gt_font_italic {
+  font-style: italic;
+}
+
+#metfygbmlu .gt_super {
+  font-size: 65%;
+}
+
+#metfygbmlu .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="metfygbmlu" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style><strong>Large Landmasses of the World</strong></th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The <em>top two</em> largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+</tbody>
+</table></div>
+<p>A <strong>source note</strong> can be added to the table’s <strong>footer</strong> through use of the <code><a href="../reference/tab_source_note.html">tab_source_note()</a></code> function. It works in the same way as <code><a href="../reference/tab_header.html">tab_header()</a></code> (it also allows for Markdown inputs) except it can be called multiple times—each invocation results in the addition of a source note.</p>
+<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Display the `islands_tbl` data with a heading and</span>
+<span class="co"># two source notes</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
+    <span class="kw">source_note</span> <span class="kw">=</span> <span class="st">"Source: The World Almanac and Book of Facts, 1975, page 406."</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
+    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Reference: McNeil, D. R. (1977) *Interactive Data Analysis*. Wiley."</span>)
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#juozpleoga .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#juozpleoga .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#juozpleoga .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#juozpleoga .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#juozpleoga .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#juozpleoga .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
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+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
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+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#juozpleoga .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
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+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#juozpleoga .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
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+}
+
+#juozpleoga .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#juozpleoga .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#juozpleoga .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#juozpleoga .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#juozpleoga .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#juozpleoga .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#juozpleoga .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#juozpleoga .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#juozpleoga .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#juozpleoga .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#juozpleoga .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#juozpleoga .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#juozpleoga .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#juozpleoga .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#juozpleoga .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#juozpleoga .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#juozpleoga .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#juozpleoga .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#juozpleoga .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#juozpleoga .gt_left {
+  text-align: left;
+}
+
+#juozpleoga .gt_center {
+  text-align: center;
+}
+
+#juozpleoga .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#juozpleoga .gt_font_normal {
+  font-weight: normal;
+}
+
+#juozpleoga .gt_font_bold {
+  font-weight: bold;
+}
+
+#juozpleoga .gt_font_italic {
+  font-style: italic;
+}
+
+#juozpleoga .gt_super {
+  font-size: 65%;
+}
+
+#juozpleoga .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="juozpleoga" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes">
+<tr>
+<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
+    </tr>
+<tr>
+<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
+    </tr>
+</tfoot>
+</table></div>
+<p>Footnotes live inside the <strong>Footer</strong> part and their footnote marks are attached to cell data. Footnotes are added with the <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> function. The helper function <code><a href="../reference/cells_body.html">cells_body()</a></code> can be used with the <code>location</code> argument to specify which data cells should be the target of the footnote. The <code><a href="../reference/cells_body.html">cells_body()</a></code> helper has the two arguments <code>columns</code> and <code>rows</code>. For each of these, we can supply (1) a vector of colnames or rownames, (2) a vector of column/row indices, (3) bare column names wrapped in <code><a href="https://dplyr.tidyverse.org/reference/vars.html">vars()</a></code> or row labels within <code><a href="https://rdrr.io/r/base/c.html">c()</a></code>, or (4) a select helper function (<code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">starts_with()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">ends_with()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">contains()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">matches()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/one_of.html">one_of()</a></code>, and <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">everything()</a></code>). For <code>rows</code> specifically, we can use a conditional statement with column names as variables (e.g., <code>size &gt; 15000</code>).</p>
+<p>Here is a simple example on how a footnotes can be added to a table cell. Let’s add a footnote that references the <code>North America</code> and <code>South America</code> cells in the <code>name</code> column:</p>
+<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Add footnotes (the same text) to two different</span>
+<span class="co"># cell; data cells are targeted with `data_cells()`</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"The Americas."</span>,
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">name</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="fl">3</span>:<span class="fl">4</span>)
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#hmnrehstnd .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#hmnrehstnd .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#hmnrehstnd .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#hmnrehstnd .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#hmnrehstnd .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#hmnrehstnd .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#hmnrehstnd .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#hmnrehstnd .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#hmnrehstnd .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#hmnrehstnd .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#hmnrehstnd .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#hmnrehstnd .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#hmnrehstnd .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#hmnrehstnd .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#hmnrehstnd .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#hmnrehstnd .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#hmnrehstnd .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#hmnrehstnd .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#hmnrehstnd .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#hmnrehstnd .gt_left {
+  text-align: left;
+}
+
+#hmnrehstnd .gt_center {
+  text-align: center;
+}
+
+#hmnrehstnd .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#hmnrehstnd .gt_font_normal {
+  font-weight: normal;
+}
+
+#hmnrehstnd .gt_font_bold {
+  font-weight: bold;
+}
+
+#hmnrehstnd .gt_font_italic {
+  font-style: italic;
+}
+
+#hmnrehstnd .gt_super {
+  font-size: 65%;
+}
+
+#hmnrehstnd .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="hmnrehstnd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">North America<sup class="gt_footnote_marks">1</sup>
+</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">South America<sup class="gt_footnote_marks">1</sup>
+</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes">
+<tr>
+<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
+    </tr>
+<tr>
+<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
+    </tr>
+</tfoot>
+<tfoot><tr class="gt_footnotes">
+<td colspan="2">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>1</em>
+          </sup>
+           
+          The Americas.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+<p>Here is a slightly more complex example of adding footnotes that use expressions in <code>rows</code> to help target cells in a column by the underlying data in <code>islands_tbl</code>. First, a set of <strong>dplyr</strong> statements obtains the name of the ‘island’ by largest landmass. This is assigned to the <code>largest</code> object and is used in the first <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> call that targets the cell in the <code>size</code> column that is next to a <code>name</code> value that is stored in <code>largest</code> (‘Asia’). The second <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> is similar except we are supplying a conditional statement that gets the lowest population.</p>
+<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># Determine the row that contains the</span>
+<span class="co"># largest landmass ('Asia')</span>
+<span class="no">largest</span> <span class="kw">&lt;-</span>
+  <span class="no">islands_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu">arrange</span>(<span class="fu">desc</span>(<span class="no">size</span>)) <span class="kw">%&gt;%</span>
+  <span class="fu">slice</span>(<span class="fl">1</span>) <span class="kw">%&gt;%</span>
+  <span class="fu">pull</span>(<span class="no">name</span>)
+
+<span class="co"># Create two additional footnotes, using the</span>
+<span class="co"># `columns` and `where` arguments of `data_cells()`</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The **largest** by area."</span>),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">name</span> <span class="kw">==</span> <span class="no">largest</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"The lowest by population."</span>,
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">size</span> <span class="kw">==</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">min</a></span>(<span class="no">size</span>))
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#pvhjxgvrhp .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#pvhjxgvrhp .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
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+</style>
+<div id="pvhjxgvrhp" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left">Asia</td>
+      <td class="gt_row gt_right">16988<sup class="gt_footnote_marks">1</sup>
+</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">North America<sup class="gt_footnote_marks">2</sup>
+</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">South America<sup class="gt_footnote_marks">2</sup>
+</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left">Borneo</td>
+      <td class="gt_row gt_right">280<sup class="gt_footnote_marks">3</sup>
+</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes">
+<tr>
+<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
+    </tr>
+<tr>
+<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
+    </tr>
+</tfoot>
+<tfoot><tr class="gt_footnotes">
+<td colspan="2">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>1</em>
+          </sup>
+           
+          The <strong>largest</strong> by area.
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>2</em>
+          </sup>
+           
+          The Americas.
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>3</em>
+          </sup>
+           
+          The lowest by population.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+<p>We were able to supply the reference locations in the table by using the <code><a href="../reference/cells_body.html">cells_body()</a></code> helper function and supplying the necessary targeting through the <code>columns</code> and <code>rows</code> arguments. Other <code>cells_*()</code> functions have similar interfaces and they allow us to target cells in different parts of the table.</p>
+</div>
+<div id="the-stub" class="section level3">
+<h3 class="hasAnchor">
+<a href="#the-stub" class="anchor"></a>The Stub</h3>
+<p>The <strong>Stub</strong> is the area to the left in a table that contains <em>row labels</em>, and may contain <em>row group labels</em>, and <em>summary labels</em>. Those subparts can be grouped in a sequence of <em>row groups</em>. The <strong>Stub Head</strong> provides a location for a label that describes the <strong>Stub</strong>. The <strong>Stub</strong> is optional since there are cases where a <strong>Stub</strong> wouldn’t be useful (e.g., the display tables presented above were just fine without a <strong>Stub</strong>).</p>
+<p>An easy way to generate a <strong>Stub</strong> part is by specifying a stub column in the <code><a href="../reference/gt.html">gt()</a></code> function with the <code>rowname_col</code> argument. Alternatively, we can have an input dataset with a column named <code>rowname</code>—this magic column will signal to <strong>gt</strong> that that column should be used as the stub, making <em>row labels</em>. Let’s add a stub with our <code>islands_tbl</code> dataset by modifying the call to <code><a href="../reference/gt.html">gt()</a></code>:</p>
+<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># Create a gt table showing ten of the</span>
+<span class="co"># largest islands in the world; this</span>
+<span class="co"># time with a stub</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">islands_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"name"</span>)
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
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+#hpjmvzyces .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#hpjmvzyces .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#hpjmvzyces .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#hpjmvzyces .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#hpjmvzyces .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#hpjmvzyces .gt_left {
+  text-align: left;
+}
+
+#hpjmvzyces .gt_center {
+  text-align: center;
+}
+
+#hpjmvzyces .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#hpjmvzyces .gt_font_normal {
+  font-weight: normal;
+}
+
+#hpjmvzyces .gt_font_bold {
+  font-weight: bold;
+}
+
+#hpjmvzyces .gt_font_italic {
+  font-style: italic;
+}
+
+#hpjmvzyces .gt_super {
+  font-size: 65%;
+}
+
+#hpjmvzyces .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="hpjmvzyces" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left gt_stub">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+</table></div>
+<p>Notice that the landmass names are off the the left in an unstriped area? That’s the <strong>stub</strong>. We can apply what’s known as a <strong>stubhead label</strong>. This label can be added with the <code><a href="../reference/tab_stubhead.html">tab_stubhead()</a></code> function:</p>
+<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># Generate a simple table with a stub</span>
+<span class="co"># and add a stubhead label</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_stubhead.html">tab_stubhead</a></span>(<span class="kw">label</span> <span class="kw">=</span> <span class="st">"landmass"</span>)
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#fekohyxzvq .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#fekohyxzvq .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#fekohyxzvq .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#fekohyxzvq .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#fekohyxzvq .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#fekohyxzvq .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#fekohyxzvq .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#fekohyxzvq .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#fekohyxzvq .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#fekohyxzvq .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#fekohyxzvq .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#fekohyxzvq .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#fekohyxzvq .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#fekohyxzvq .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#fekohyxzvq .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#fekohyxzvq .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#fekohyxzvq .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#fekohyxzvq .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#fekohyxzvq .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#fekohyxzvq .gt_left {
+  text-align: left;
+}
+
+#fekohyxzvq .gt_center {
+  text-align: center;
+}
+
+#fekohyxzvq .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#fekohyxzvq .gt_font_normal {
+  font-weight: normal;
+}
+
+#fekohyxzvq .gt_font_bold {
+  font-weight: bold;
+}
+
+#fekohyxzvq .gt_font_italic {
+  font-style: italic;
+}
+
+#fekohyxzvq .gt_super {
+  font-size: 65%;
+}
+
+#fekohyxzvq .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="fekohyxzvq" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">landmass</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left gt_stub">Asia</td>
+      <td class="gt_row gt_right">16988</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Antarctica</td>
+      <td class="gt_row gt_right">5500</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+</table></div>
+<p>A very important thing to note here is that the table now has one column. Before, when there was no <strong>stub</strong>, two columns were present (with <strong>column labels</strong> <code>name</code> and <code>size</code>) but now column number <code>1</code> (the only column) is <code>size</code>.</p>
+<p>To apply our table parts as before (up to and including the footnotes) we use the following statements:</p>
+<div class="sourceCode" id="cb10"><html><body><pre class="r"><span class="co"># Display the `islands_tbl` data with a stub,</span>
+<span class="co"># a heading, source notes, and footnotes</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"Large Landmasses of the World"</span>,
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"The top ten largest are presented"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
+    <span class="kw">source_note</span> <span class="kw">=</span> <span class="st">"Source: The World Almanac and Book of Facts, 1975, page 406."</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
+    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Reference: McNeil, D. R. (1977) *Interactive Data Analysis*. Wiley."</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The **largest** by area."</span>),
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">largest</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
+    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"The lowest by population."</span>,
+    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
+      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
+      <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">contains</a></span>(<span class="st">"arc"</span>))
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#xhzkicahqh .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#xhzkicahqh .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#xhzkicahqh .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#xhzkicahqh .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
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+</style>
+<div id="xhzkicahqh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">landmass</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_left gt_stub">Asia</td>
+      <td class="gt_row gt_right">16988<sup class="gt_footnote_marks">1</sup>
+</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Antarctica</td>
+      <td class="gt_row gt_right">5500<sup class="gt_footnote_marks">2</sup>
+</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes">
+<tr>
+<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
+    </tr>
+<tr>
+<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
+    </tr>
+</tfoot>
+<tfoot><tr class="gt_footnotes">
+<td colspan="2">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>1</em>
+          </sup>
+           
+          The <strong>largest</strong> by area.
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>2</em>
+          </sup>
+           
+          The lowest by population.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+<p>Let’s incorporate row groups into the display table. This divides rows into groups, creating <em>row groups</em>, and results in a display of a <em>row group labels</em> right above the each group. This can be easily done with a table containing row labels. We can make a new <em>row group</em> with each call of the <code><a href="../reference/tab_row_group.html">tab_row_group()</a></code> function. The inputs are group names in the <code>group</code> argument, and row references in the <code>rows</code> argument. We can use any of the strategies to reference rows as we did we footnotes (e.g., vectors of names/indices, select helpers, etc.).</p>
+<p>Here we will create three row groups (with row group labels <code>continent</code>, <code>country</code>, and <code>subregion</code>) to have a grouping of rows.</p>
+<div class="sourceCode" id="cb11"><html><body><pre class="r"><span class="co"># Create three row groups with the</span>
+<span class="co"># `tab_row_group()` function</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_row_group.html">tab_row_group</a></span>(
+    <span class="kw">group</span> <span class="kw">=</span> <span class="st">"continent"</span>,
+    <span class="kw">rows</span> <span class="kw">=</span> <span class="fl">1</span>:<span class="fl">6</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_row_group.html">tab_row_group</a></span>(
+    <span class="kw">group</span> <span class="kw">=</span> <span class="st">"country"</span>,
+    <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Australia"</span>, <span class="st">"Greenland"</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_row_group.html">tab_row_group</a></span>(
+    <span class="kw">group</span> <span class="kw">=</span> <span class="st">"subregion"</span>,
+    <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"New Guinea"</span>, <span class="st">"Borneo"</span>)
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span>
+<span class="co">#&gt; Warning in min(rows_matched): no non-missing arguments to min; returning Inf</span>
+<span class="co">#&gt; Warning in max(rows_matched): no non-missing arguments to max; returning -Inf</span></pre></body></html></div>
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+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mtfklilywh .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#mtfklilywh .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mtfklilywh .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#mtfklilywh .gt_left {
+  text-align: left;
+}
+
+#mtfklilywh .gt_center {
+  text-align: center;
+}
+
+#mtfklilywh .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#mtfklilywh .gt_font_normal {
+  font-weight: normal;
+}
+
+#mtfklilywh .gt_font_bold {
+  font-weight: bold;
+}
+
+#mtfklilywh .gt_font_italic {
+  font-style: italic;
+}
+
+#mtfklilywh .gt_super {
+  font-size: 65%;
+}
+
+#mtfklilywh .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="mtfklilywh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
+    </tr>
+<tr>
+<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings"><tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">landmass</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<td colspan="2" class="gt_group_heading">subregion</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">New Guinea</td>
+      <td class="gt_row gt_right">306</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Borneo</td>
+      <td class="gt_row gt_right">280</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="2" class="gt_group_heading">country</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Australia</td>
+      <td class="gt_row gt_right">2968</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Greenland</td>
+      <td class="gt_row gt_right">840</td>
+    </tr>
+<tr class="gt_group_heading_row">
+<td colspan="2" class="gt_group_heading">continent</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Asia</td>
+      <td class="gt_row gt_right">16988<sup class="gt_footnote_marks">1</sup>
+</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Africa</td>
+      <td class="gt_row gt_right">11506</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">North America</td>
+      <td class="gt_row gt_right">9390</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">South America</td>
+      <td class="gt_row gt_right">6795</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Antarctica</td>
+      <td class="gt_row gt_right">5500<sup class="gt_footnote_marks">2</sup>
+</td>
+    </tr>
+<tr>
+<td class="gt_row gt_left gt_stub">Europe</td>
+      <td class="gt_row gt_right">3745</td>
+    </tr>
+</tbody>
+<tfoot class="gt_sourcenotes">
+<tr>
+<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
+    </tr>
+<tr>
+<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
+    </tr>
+</tfoot>
+<tfoot><tr class="gt_footnotes">
+<td colspan="2">
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>1</em>
+          </sup>
+           
+          The <strong>largest</strong> by area.
+          <br></p>
+        <p class="gt_footnote">
+          <sup class="gt_footnote_marks"><em>2</em>
+          </sup>
+           
+          The lowest by population.
+          <br></p>
+      </td>
+    </tr></tfoot>
+</table></div>
+<p>Three <em>row groups</em> have been made since there are three unique categories under <code>groupname</code>. Across the top of each <em>row group</em> is the <em>row group label</em> contained in a separate row (these cut across the field and they contain nothing but the <em>row group label</em>). A rearrangement of rows is carried out to ensure each of the rows is collected within the appropriate <em>row groups</em>.</p>
+<p>Having groups of rows in <em>row groups</em> is a great way to present information. Including data summaries particular to each group is a natural extension of this idea. This process of adding summary rows with <em>summary labels</em> is covered in a separate article (<em>Creating Summary Lines</em>).</p>
+<p>Another way to make row groups is to have the magic column <code>groupname</code> present in the input data table. For our above example with <code>islands_tbl</code>, a <code>groupname</code> column with the categories <code>continent</code>, <code>country</code>, and <code>subregion</code> in the appropriate rows would produce row groups automatically (i.e., there would be no need to use the <code><a href="../reference/tab_row_group.html">tab_row_group()</a></code> statements). This strategy of supplying group names in a <code>groupname</code> column name can sometimes be advantageous since we can rely on functions such as those available in <strong>dplyr</strong> to generate the categories (e.g., using <code>case_when()</code> or <code>if_else()</code>).</p>
+</div>
+<div id="the-column-labels" class="section level3">
+<h3 class="hasAnchor">
+<a href="#the-column-labels" class="anchor"></a>The Column Labels</h3>
+<p>The table’s <strong>Column Labels</strong> part contains, at a minimum, columns and their <em>column labels</em>. The last example had a single column: <code>size</code>. Just as in the <strong>Stub</strong>, we can create groupings called <em>spanner columns</em> that encompass one or more columns.</p>
+<p>To better demonstrate how <strong>Column Labels</strong> work and are displayed, let’s use an input data table with more columns. In this case, that input table will be <code>airquality</code>. It has the following columns:</p>
+<ul>
+<li>
+<code>Ozone</code>: mean ground-level ozone in parts per billion by volume (ppbV), measured between 13:00 and 15:00</li>
+<li>
+<code>Solar.R</code>: solar radiation in Langley units (cal/m<sup>2</sup>), measured between 08:00 and noon</li>
+<li>
+<code>Wind</code>: mean wind speed in miles per hour (mph)</li>
+<li>
+<code>Temp</code>: maximum daily air temperature in degrees Fahrenheit (°F)</li>
+<li>
+<code>Month</code>, <code>Day</code>: the numeric month and day of month for the record</li>
+</ul>
+<p>We know that all measurements took place in 1973, so a <code>year</code> column will be added to the dataset before it is passed to <code><a href="../reference/gt.html">gt()</a></code>.</p>
+<p>Let’s organize the time information under a <code>Time</code> <em>spanner column label</em>, and put the other columns under a <code>Measurement</code> <em>spanner column label</em>. We can do this with the <code><a href="../reference/tab_spanner.html">tab_spanner()</a></code> function.</p>
+<div class="sourceCode" id="cb12"><html><body><pre class="r"><span class="co"># Modify the `airquality` dataset by adding the year</span>
+<span class="co"># of the measurements (1973) and limiting to 10 rows</span>
+<span class="no">airquality_m</span> <span class="kw">&lt;-</span>
+  <span class="no">airquality</span> <span class="kw">%&gt;%</span>
+  <span class="fu">mutate</span>(<span class="kw">Year</span> <span class="kw">=</span> <span class="fl">1973L</span>) <span class="kw">%&gt;%</span>
+  <span class="fu">slice</span>(<span class="fl">1</span>:<span class="fl">10</span>)
+
+<span class="co"># Create a display table using the `airquality`</span>
+<span class="co"># dataset; arrange columns into groups</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">airquality_m</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"New York Air Quality Measurements"</span>,
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"Daily measurements in New York City (May 1-10, 1973)"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
+    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Time"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">Year</span>, <span class="no">Month</span>, <span class="no">Day</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
+    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Measurement"</span>,
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">Ozone</span>, <span class="no">Solar.R</span>, <span class="no">Wind</span>, <span class="no">Temp</span>)
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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+
+#qnfyrrzvuy .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#qnfyrrzvuy .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#qnfyrrzvuy .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+
+#qnfyrrzvuy .gt_col_headings {
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+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
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+
+#qnfyrrzvuy .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
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+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#qnfyrrzvuy .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#qnfyrrzvuy .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#qnfyrrzvuy .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#qnfyrrzvuy .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#qnfyrrzvuy .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#qnfyrrzvuy .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#qnfyrrzvuy .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#qnfyrrzvuy .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#qnfyrrzvuy .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#qnfyrrzvuy .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#qnfyrrzvuy .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#qnfyrrzvuy .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#qnfyrrzvuy .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#qnfyrrzvuy .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#qnfyrrzvuy .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#qnfyrrzvuy .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#qnfyrrzvuy .gt_left {
+  text-align: left;
+}
+
+#qnfyrrzvuy .gt_center {
+  text-align: center;
+}
+
+#qnfyrrzvuy .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#qnfyrrzvuy .gt_font_normal {
+  font-weight: normal;
+}
+
+#qnfyrrzvuy .gt_font_bold {
+  font-weight: bold;
+}
+
+#qnfyrrzvuy .gt_font_italic {
+  font-style: italic;
+}
+
+#qnfyrrzvuy .gt_super {
+  font-size: 65%;
+}
+
+#qnfyrrzvuy .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="qnfyrrzvuy" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="7" class="gt_heading gt_title gt_font_normal" style>New York Air Quality Measurements</th>
+    </tr>
+<tr>
+<th colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>Daily measurements in New York City (May 1-10, 1973)</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4">
+        <span class="gt_column_spanner">Measurement</span>
+      </th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Time</span>
+      </th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Ozone</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Solar.R</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Wind</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Temp</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Month</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Day</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_center">41</td>
+      <td class="gt_row gt_center">190</td>
+      <td class="gt_row gt_right">7.4</td>
+      <td class="gt_row gt_center">67</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">1</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">36</td>
+      <td class="gt_row gt_center">118</td>
+      <td class="gt_row gt_right">8.0</td>
+      <td class="gt_row gt_center">72</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">2</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">12</td>
+      <td class="gt_row gt_center">149</td>
+      <td class="gt_row gt_right">12.6</td>
+      <td class="gt_row gt_center">74</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">3</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">18</td>
+      <td class="gt_row gt_center">313</td>
+      <td class="gt_row gt_right">11.5</td>
+      <td class="gt_row gt_center">62</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">4</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_right">14.3</td>
+      <td class="gt_row gt_center">56</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">5</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">28</td>
+      <td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_right">14.9</td>
+      <td class="gt_row gt_center">66</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">6</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">23</td>
+      <td class="gt_row gt_center">299</td>
+      <td class="gt_row gt_right">8.6</td>
+      <td class="gt_row gt_center">65</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">7</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">19</td>
+      <td class="gt_row gt_center">99</td>
+      <td class="gt_row gt_right">13.8</td>
+      <td class="gt_row gt_center">59</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">8</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">8</td>
+      <td class="gt_row gt_center">19</td>
+      <td class="gt_row gt_right">20.1</td>
+      <td class="gt_row gt_center">61</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">9</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_center">194</td>
+      <td class="gt_row gt_right">8.6</td>
+      <td class="gt_row gt_center">69</td>
+      <td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">10</td>
+    </tr>
+</tbody>
+</table></div>
+<p>We can do two more things to make this presentable:</p>
+<ul>
+<li>move the <code>Time</code> columns to the beginning of the series (using <code><a href="../reference/cols_move_to_start.html">cols_move_to_start()</a></code>)</li>
+<li>customize the column labels so that they are more descriptive (using <code><a href="../reference/cols_label.html">cols_label()</a></code>)</li>
+</ul>
+<p>Let’s do both of these things in the next example.</p>
+<div class="sourceCode" id="cb13"><html><body><pre class="r"><span class="co"># Move the time-based columns to the start of</span>
+<span class="co"># the column series; modify the column labels of</span>
+<span class="co"># the measurement-based columns</span>
+<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
+  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_move_to_start.html">cols_move_to_start</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">Year</span>, <span class="no">Month</span>, <span class="no">Day</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
+    <span class="kw">Ozone</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Ozone,&lt;br&gt;ppbV"</span>),
+    <span class="kw">Solar.R</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Solar R.,&lt;br&gt;cal/m&lt;sup&gt;2&lt;/sup&gt;"</span>),
+    <span class="kw">Wind</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Wind,&lt;br&gt;mph"</span>),
+    <span class="kw">Temp</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Temp,&lt;br&gt;&amp;deg;F"</span>)
+  )
+
+<span class="co"># Show the gt Table</span>
+<span class="no">gt_tbl</span></pre></body></html></div>
+<style>html {
+  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
+}
+
+#jjpqqgmdxw .gt_table {
+  display: table;
+  border-collapse: collapse;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#jjpqqgmdxw .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 0;
+  padding-bottom: 4px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#jjpqqgmdxw .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#jjpqqgmdxw .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#jjpqqgmdxw .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#jjpqqgmdxw .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#jjpqqgmdxw .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#jjpqqgmdxw .gt_group_heading {
+  padding: 8px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#jjpqqgmdxw .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#jjpqqgmdxw .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#jjpqqgmdxw .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#jjpqqgmdxw .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#jjpqqgmdxw .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#jjpqqgmdxw .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 12px;
+}
+
+#jjpqqgmdxw .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#jjpqqgmdxw .gt_first_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#jjpqqgmdxw .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding: 4px;
+}
+
+#jjpqqgmdxw .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#jjpqqgmdxw .gt_sourcenote {
+  font-size: 90%;
+  padding: 4px;
+}
+
+#jjpqqgmdxw .gt_left {
+  text-align: left;
+}
+
+#jjpqqgmdxw .gt_center {
+  text-align: center;
+}
+
+#jjpqqgmdxw .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#jjpqqgmdxw .gt_font_normal {
+  font-weight: normal;
+}
+
+#jjpqqgmdxw .gt_font_bold {
+  font-weight: bold;
+}
+
+#jjpqqgmdxw .gt_font_italic {
+  font-style: italic;
+}
+
+#jjpqqgmdxw .gt_super {
+  font-size: 65%;
+}
+
+#jjpqqgmdxw .gt_footnote_marks {
+  font-style: italic;
+  font-size: 65%;
+}
+</style>
+<div id="jjpqqgmdxw" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
+<thead class="gt_header">
+<tr>
+<th colspan="7" class="gt_heading gt_title gt_font_normal" style>New York Air Quality Measurements</th>
+    </tr>
+<tr>
+<th colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>Daily measurements in New York City (May 1-10, 1973)</th>
+    </tr>
+</thead>
+<thead class="gt_col_headings">
+<tr>
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
+        <span class="gt_column_spanner">Time</span>
+      </th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4">
+        <span class="gt_column_spanner">Measurement</span>
+      </th>
+    </tr>
+<tr>
+<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Year</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Month</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Day</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Ozone,<br>ppbV</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Solar R.,<br>cal/m<sup>2</sup>
+</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Wind,<br>mph</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Temp,<br>°F</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">1</td>
+      <td class="gt_row gt_center">41</td>
+      <td class="gt_row gt_center">190</td>
+      <td class="gt_row gt_right">7.4</td>
+      <td class="gt_row gt_center">67</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">2</td>
+      <td class="gt_row gt_center">36</td>
+      <td class="gt_row gt_center">118</td>
+      <td class="gt_row gt_right">8.0</td>
+      <td class="gt_row gt_center">72</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">3</td>
+      <td class="gt_row gt_center">12</td>
+      <td class="gt_row gt_center">149</td>
+      <td class="gt_row gt_right">12.6</td>
+      <td class="gt_row gt_center">74</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">4</td>
+      <td class="gt_row gt_center">18</td>
+      <td class="gt_row gt_center">313</td>
+      <td class="gt_row gt_right">11.5</td>
+      <td class="gt_row gt_center">62</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_right">14.3</td>
+      <td class="gt_row gt_center">56</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">6</td>
+      <td class="gt_row gt_center">28</td>
+      <td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_right">14.9</td>
+      <td class="gt_row gt_center">66</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">7</td>
+      <td class="gt_row gt_center">23</td>
+      <td class="gt_row gt_center">299</td>
+      <td class="gt_row gt_right">8.6</td>
+      <td class="gt_row gt_center">65</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">8</td>
+      <td class="gt_row gt_center">19</td>
+      <td class="gt_row gt_center">99</td>
+      <td class="gt_row gt_right">13.8</td>
+      <td class="gt_row gt_center">59</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">9</td>
+      <td class="gt_row gt_center">8</td>
+      <td class="gt_row gt_center">19</td>
+      <td class="gt_row gt_right">20.1</td>
+      <td class="gt_row gt_center">61</td>
+    </tr>
+<tr>
+<td class="gt_row gt_center">1973</td>
+      <td class="gt_row gt_center">5</td>
+      <td class="gt_row gt_center">10</td>
+      <td class="gt_row gt_center">NA</td>
+      <td class="gt_row gt_center">194</td>
+      <td class="gt_row gt_right">8.6</td>
+      <td class="gt_row gt_center">69</td>
+    </tr>
+</tbody>
+</table></div>
+<p>Note that even though columns were moved using <code><a href="../reference/cols_move_to_start.html">cols_move_to_start()</a></code>, the <em>spanner column labels</em> still spanned above the correct <em>column labels</em>. There are a number of functions that <strong>gt</strong> provides to move columns, including <code><a href="../reference/cols_move.html">cols_move()</a></code>, <code><a href="../reference/cols_move_to_end.html">cols_move_to_end()</a></code>; there’s even a function to hide columns: <code><a href="../reference/cols_hide.html">cols_hide()</a></code>.</p>
+<p>Multiple columns can be renamed in a single use of <code><a href="../reference/cols_label.html">cols_label()</a></code>. Further to this, the helper functions <code><a href="../reference/md.html">md()</a></code> and <code><a href="../reference/html.html">html()</a></code> can be used to create column labels with additional styling. In the above example, we provided column labels as HTML so that we can insert linebreaks with <code>&lt;br&gt;</code>, insert a superscripted <code>2</code> (with <code>&lt;sup&gt;2&lt;/sup&gt;</code>), and insert a degree symbol as an HTML entity (<code>&amp;deg;</code>).</p>
+</div>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+
+      </div>
+
+</div>
+
+
+
+      <footer><div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href="https://www.rstudio.com"><img src="https://www.tidyverse.org/rstudio-logo.svg" alt="RStudio" height="24"></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+</div>
+
+  
+
+
+  </body>
+</html>
diff --git a/docs/authors.html b/docs/authors.html
new file mode 100644
index 000000000..77c952007
--- /dev/null
+++ b/docs/authors.html
@@ -0,0 +1,184 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Authors • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="bootstrap-toc.css">
+<script src="bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="pkgdown.css" rel="stylesheet">
+<script src="pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Authors" />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-authors">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="contents col-md-9">
+    <div class="page-header">
+      <h1>Authors</h1>
+    </div>
+
+    <ul class="list-unstyled">
+      <li>
+        <p><strong>Richard Iannone</strong>. Author, maintainer. <a href='https://orcid.org/0000-0003-3925-190X' target='orcid.widget' aria-label='ORCID'><span class='fab fa-orcid orcid' aria-hidden='true'></span></a>
+        </p>
+      </li>
+      <li>
+        <p><strong>Joe Cheng</strong>. Author. 
+        </p>
+      </li>
+      <li>
+        <p><strong>Barret Schloerke</strong>. Author. <a href='https://orcid.org/0000-0001-9986-114X' target='orcid.widget' aria-label='ORCID'><span class='fab fa-orcid orcid' aria-hidden='true'></span></a>
+        </p>
+      </li>
+      <li>
+        <p><strong><a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a></strong>. Copyright holder, funder. 
+        </p>
+      </li>
+    </ul>
+
+  </div>
+
+</div>
+
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/bootstrap-toc.css b/docs/bootstrap-toc.css
new file mode 100644
index 000000000..5a859415c
--- /dev/null
+++ b/docs/bootstrap-toc.css
@@ -0,0 +1,60 @@
+/*!
+ * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
+ * Copyright 2015 Aidan Feldman
+ * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
+
+/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */
+
+/* All levels of nav */
+nav[data-toggle='toc'] .nav > li > a {
+  display: block;
+  padding: 4px 20px;
+  font-size: 13px;
+  font-weight: 500;
+  color: #767676;
+}
+nav[data-toggle='toc'] .nav > li > a:hover,
+nav[data-toggle='toc'] .nav > li > a:focus {
+  padding-left: 19px;
+  color: #563d7c;
+  text-decoration: none;
+  background-color: transparent;
+  border-left: 1px solid #563d7c;
+}
+nav[data-toggle='toc'] .nav > .active > a,
+nav[data-toggle='toc'] .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav > .active:focus > a {
+  padding-left: 18px;
+  font-weight: bold;
+  color: #563d7c;
+  background-color: transparent;
+  border-left: 2px solid #563d7c;
+}
+
+/* Nav: second level (shown on .active) */
+nav[data-toggle='toc'] .nav .nav {
+  display: none; /* Hide by default, but at >768px, show it */
+  padding-bottom: 10px;
+}
+nav[data-toggle='toc'] .nav .nav > li > a {
+  padding-top: 1px;
+  padding-bottom: 1px;
+  padding-left: 30px;
+  font-size: 12px;
+  font-weight: normal;
+}
+nav[data-toggle='toc'] .nav .nav > li > a:hover,
+nav[data-toggle='toc'] .nav .nav > li > a:focus {
+  padding-left: 29px;
+}
+nav[data-toggle='toc'] .nav .nav > .active > a,
+nav[data-toggle='toc'] .nav .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav .nav > .active:focus > a {
+  padding-left: 28px;
+  font-weight: 500;
+}
+
+/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */
+nav[data-toggle='toc'] .nav > .active > ul {
+  display: block;
+}
diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js
new file mode 100644
index 000000000..1cdd573b2
--- /dev/null
+++ b/docs/bootstrap-toc.js
@@ -0,0 +1,159 @@
+/*!
+ * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
+ * Copyright 2015 Aidan Feldman
+ * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
+(function() {
+  'use strict';
+
+  window.Toc = {
+    helpers: {
+      // return all matching elements in the set, or their descendants
+      findOrFilter: function($el, selector) {
+        // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/
+        // http://stackoverflow.com/a/12731439/358804
+        var $descendants = $el.find(selector);
+        return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])');
+      },
+
+      generateUniqueIdBase: function(el) {
+        var text = $(el).text();
+        var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-');
+        return anchor || el.tagName.toLowerCase();
+      },
+
+      generateUniqueId: function(el) {
+        var anchorBase = this.generateUniqueIdBase(el);
+        for (var i = 0; ; i++) {
+          var anchor = anchorBase;
+          if (i > 0) {
+            // add suffix
+            anchor += '-' + i;
+          }
+          // check if ID already exists
+          if (!document.getElementById(anchor)) {
+            return anchor;
+          }
+        }
+      },
+
+      generateAnchor: function(el) {
+        if (el.id) {
+          return el.id;
+        } else {
+          var anchor = this.generateUniqueId(el);
+          el.id = anchor;
+          return anchor;
+        }
+      },
+
+      createNavList: function() {
+        return $('<ul class="nav"></ul>');
+      },
+
+      createChildNavList: function($parent) {
+        var $childList = this.createNavList();
+        $parent.append($childList);
+        return $childList;
+      },
+
+      generateNavEl: function(anchor, text) {
+        var $a = $('<a></a>');
+        $a.attr('href', '#' + anchor);
+        $a.text(text);
+        var $li = $('<li></li>');
+        $li.append($a);
+        return $li;
+      },
+
+      generateNavItem: function(headingEl) {
+        var anchor = this.generateAnchor(headingEl);
+        var $heading = $(headingEl);
+        var text = $heading.data('toc-text') || $heading.text();
+        return this.generateNavEl(anchor, text);
+      },
+
+      // Find the first heading level (`<h1>`, then `<h2>`, etc.) that has more than one element. Defaults to 1 (for `<h1>`).
+      getTopLevel: function($scope) {
+        for (var i = 1; i <= 6; i++) {
+          var $headings = this.findOrFilter($scope, 'h' + i);
+          if ($headings.length > 1) {
+            return i;
+          }
+        }
+
+        return 1;
+      },
+
+      // returns the elements for the top level, and the next below it
+      getHeadings: function($scope, topLevel) {
+        var topSelector = 'h' + topLevel;
+
+        var secondaryLevel = topLevel + 1;
+        var secondarySelector = 'h' + secondaryLevel;
+
+        return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
+      },
+
+      getNavLevel: function(el) {
+        return parseInt(el.tagName.charAt(1), 10);
+      },
+
+      populateNav: function($topContext, topLevel, $headings) {
+        var $context = $topContext;
+        var $prevNav;
+
+        var helpers = this;
+        $headings.each(function(i, el) {
+          var $newNav = helpers.generateNavItem(el);
+          var navLevel = helpers.getNavLevel(el);
+
+          // determine the proper $context
+          if (navLevel === topLevel) {
+            // use top level
+            $context = $topContext;
+          } else if ($prevNav && $context === $topContext) {
+            // create a new level of the tree and switch to it
+            $context = helpers.createChildNavList($prevNav);
+          } // else use the current $context
+
+          $context.append($newNav);
+
+          $prevNav = $newNav;
+        });
+      },
+
+      parseOps: function(arg) {
+        var opts;
+        if (arg.jquery) {
+          opts = {
+            $nav: arg
+          };
+        } else {
+          opts = arg;
+        }
+        opts.$scope = opts.$scope || $(document.body);
+        return opts;
+      }
+    },
+
+    // accepts a jQuery object, or an options object
+    init: function(opts) {
+      opts = this.helpers.parseOps(opts);
+
+      // ensure that the data attribute is in place for styling
+      opts.$nav.attr('data-toggle', 'toc');
+
+      var $topContext = this.helpers.createChildNavList(opts.$nav);
+      var topLevel = this.helpers.getTopLevel(opts.$scope);
+      var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
+      this.helpers.populateNav($topContext, topLevel, $headings);
+    }
+  };
+
+  $(function() {
+    $('nav[data-toggle="toc"]').each(function(i, el) {
+      var $nav = $(el);
+      Toc.init($nav);
+    });
+  });
+})();
diff --git a/docs/docsearch.css b/docs/docsearch.css
new file mode 100644
index 000000000..e5f1fe1df
--- /dev/null
+++ b/docs/docsearch.css
@@ -0,0 +1,148 @@
+/* Docsearch -------------------------------------------------------------- */
+/*
+  Source: https://github.com/algolia/docsearch/
+  License: MIT
+*/
+
+.algolia-autocomplete {
+  display: block;
+  -webkit-box-flex: 1;
+  -ms-flex: 1;
+  flex: 1
+}
+
+.algolia-autocomplete .ds-dropdown-menu {
+  width: 100%;
+  min-width: none;
+  max-width: none;
+  padding: .75rem 0;
+  background-color: #fff;
+  background-clip: padding-box;
+  border: 1px solid rgba(0, 0, 0, .1);
+  box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
+}
+
+@media (min-width:768px) {
+  .algolia-autocomplete .ds-dropdown-menu {
+      width: 175%
+  }
+}
+
+.algolia-autocomplete .ds-dropdown-menu::before {
+  display: none
+}
+
+.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
+  padding: 0;
+  background-color: rgb(255,255,255);
+  border: 0;
+  max-height: 80vh;
+}
+
+.algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
+  margin-top: 0
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion {
+  padding: 0;
+  overflow: visible
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--category-header {
+  padding: .125rem 1rem;
+  margin-top: 0;
+  font-size: 1.3em;
+  font-weight: 500;
+  color: #00008B;
+  border-bottom: 0
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
+    float: none;
+    padding-top: 0
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
+  float: none;
+  width: auto;
+  padding: 0;
+  text-align: left
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--content {
+  float: none;
+  width: auto;
+  padding: 0
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--content::before {
+  display: none
+}
+
+.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
+  padding-top: .75rem;
+  margin-top: .75rem;
+  border-top: 1px solid rgba(0, 0, 0, .1)
+}
+
+.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
+  display: block;
+  padding: .1rem 1rem;
+  margin-bottom: 0.1;
+  font-size: 1.0em;
+  font-weight: 400
+  /* display: none */
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--title {
+  display: block;
+  padding: .25rem 1rem;
+  margin-bottom: 0;
+  font-size: 0.9em;
+  font-weight: 400
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--text {
+  padding: 0 1rem .5rem;
+  margin-top: -.25rem;
+  font-size: 0.8em;
+  font-weight: 400;
+  line-height: 1.25
+}
+
+.algolia-autocomplete .algolia-docsearch-footer {
+  width: 110px;
+  height: 20px;
+  z-index: 3;
+  margin-top: 10.66667px;
+  float: right;
+  font-size: 0;
+  line-height: 0;
+}
+
+.algolia-autocomplete .algolia-docsearch-footer--logo {
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+  background-repeat: no-repeat;
+  background-position: 50%;
+  background-size: 100%;
+  overflow: hidden;
+  text-indent: -9000px;
+  width: 100%;
+  height: 100%;
+  display: block;
+  transform: translate(-8px);
+}
+
+.algolia-autocomplete .algolia-docsearch-suggestion--highlight {
+  color: #FF8C00;
+  background: rgba(232, 189, 54, 0.1)
+}
+
+
+.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
+  box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
+}
+
+.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
+  background-color: rgba(192, 192, 192, .15)
+}
diff --git a/docs/docsearch.js b/docs/docsearch.js
new file mode 100644
index 000000000..b35504cd3
--- /dev/null
+++ b/docs/docsearch.js
@@ -0,0 +1,85 @@
+$(function() {
+
+  // register a handler to move the focus to the search bar
+  // upon pressing shift + "/" (i.e. "?")
+  $(document).on('keydown', function(e) {
+    if (e.shiftKey && e.keyCode == 191) {
+      e.preventDefault();
+      $("#search-input").focus();
+    }
+  });
+
+  $(document).ready(function() {
+    // do keyword highlighting
+    /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */
+    var mark = function() {
+
+      var referrer = document.URL ;
+      var paramKey = "q" ;
+
+      if (referrer.indexOf("?") !== -1) {
+        var qs = referrer.substr(referrer.indexOf('?') + 1);
+        var qs_noanchor = qs.split('#')[0];
+        var qsa = qs_noanchor.split('&');
+        var keyword = "";
+
+        for (var i = 0; i < qsa.length; i++) {
+          var currentParam = qsa[i].split('=');
+
+          if (currentParam.length !== 2) {
+            continue;
+          }
+
+          if (currentParam[0] == paramKey) {
+            keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20"));
+          }
+        }
+
+        if (keyword !== "") {
+          $(".contents").unmark({
+            done: function() {
+              $(".contents").mark(keyword);
+            }
+          });
+        }
+      }
+    };
+
+    mark();
+  });
+});
+
+/* Search term highlighting ------------------------------*/
+
+function matchedWords(hit) {
+  var words = [];
+
+  var hierarchy = hit._highlightResult.hierarchy;
+  // loop to fetch from lvl0, lvl1, etc.
+  for (var idx in hierarchy) {
+    words = words.concat(hierarchy[idx].matchedWords);
+  }
+
+  var content = hit._highlightResult.content;
+  if (content) {
+    words = words.concat(content.matchedWords);
+  }
+
+  // return unique words
+  var words_uniq = [...new Set(words)];
+  return words_uniq;
+}
+
+function updateHitURL(hit) {
+
+  var words = matchedWords(hit);
+  var url = "";
+
+  if (hit.anchor) {
+    url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor;
+  } else {
+    url = hit.url + '?q=' + escape(words.join(" "));
+  }
+
+  return url;
+}
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diff --git a/docs/index.html b/docs/index.html
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+<script src="pkgdown.js"></script><meta property="og:title" content="Easily Create Presentation-Ready Display Tables">
+<meta property="og:description" content="Build display tables from tabular data using with an easy-to-use
+    API. With its progressive approach, we can construct display tables with a
+    clear separation of concerns: you don't have to decide how the tabular data
+    gets transformed and structured whilst also worrying about aesthetics.">
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg">
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+        <a class="navbar-link" href="index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+<li>
+  <a href="articles/intro-creating-gt-tables.html">Intro</a>
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+<li class="dropdown-header">How to Use</li>
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+      <a href="articles/gt-datasets.html">gt Datasets</a>
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+      <a href="articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+  <div class="contents col-md-9">
+<div id="gt-" class="section level1">
+
+
+<p>With the <strong>gt</strong> package, anyone can make wonderful-looking tables using the <strong>R</strong> programming language. The <strong>gt</strong> philosophy: we can construct a wide variety of useful tables with a cohesive set of table parts. These include the <em>table header</em>, the <em>stub</em>, the <em>column labels</em> and <em>spanner column labels</em>, the <em>table body</em>, and the <em>table footer</em>.</p>
+<p align="center">
+</p>
+<p><img src="reference/figures/gt_parts_of_a_table.svg" width="800px"></p>
+
+<p>It all begins with preprocessed <strong>table data</strong> (be it a tibble or a data frame). You then decide how to compose your <strong>gt table</strong> with the elements and formatting you need for the task at hand. Finally, the table is rendered by printing it at the console, including it in an R Markdown document, or exporting to a file using <code><a href="reference/gtsave.html">gtsave()</a></code>. Currently, <strong>gt</strong> supports <strong>HTML</strong> output, with <strong>LaTeX</strong> and <strong>RTF</strong> planned for the future.</p>
+<p align="center">
+</p>
+<p><img src="reference/figures/gt_workflow_diagram.svg" width="800px"></p>
+
+<p>The <strong>gt</strong> package is designed to be both straightforward yet powerful. The emphasis is on simple functions for the everyday display table needs. Here is a brief example of how to use <strong>gt</strong> to create a table from the included <code>sp500</code> dataset:</p>
+<div class="sourceCode" id="cb1"><pre class="r"><span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">gt</span>)
+<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">tidyverse</span>)
+<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">glue</span>)
+
+<span class="co"># Define the start and end dates for the data range</span>
+<span class="no">start_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-07"</span>
+<span class="no">end_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-14"</span>
+
+<span class="co"># Create a gt table based on preprocessed</span>
+<span class="co"># `sp500` table data</span>
+<span class="no">sp500</span> <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">date</span> <span class="kw">&gt;=</span> <span class="no">start_date</span> <span class="kw">&amp;</span> <span class="no">date</span> <span class="kw">&lt;=</span> <span class="no">end_date</span>) <span class="kw">%&gt;%</span>
+  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">adj_close</span>) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="reference/tab_header.html">tab_header</a></span>(
+    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"S&amp;P 500"</span>,
+    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="kw pkg">glue</span><span class="kw ns">::</span><span class="fu"><a href="https://glue.tidyverse.org/reference/glue.html">glue</a></span>(<span class="st">"{start_date} to {end_date}"</span>)
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="reference/fmt_date.html">fmt_date</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">date</span>),
+    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">3</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="reference/fmt_currency.html">fmt_currency</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">open</span>, <span class="no">high</span>, <span class="no">low</span>, <span class="no">close</span>),
+    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
+  ) <span class="kw">%&gt;%</span>
+  <span class="fu"><a href="reference/fmt_number.html">fmt_number</a></span>(
+    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">volume</span>),
+    <span class="kw">suffixing</span> <span class="kw">=</span> <span class="fl">TRUE</span>
+  )</pre></div>
+<p align="center">
+</p>
+<p><img src="reference/figures/gt_sp500_table.svg" width="1200px"></p>
+
+<p>There are six datasets included in <strong>gt</strong>: <code>countrypops</code>, <code>sza</code>, <code>gtcars</code>, <code>sp500</code>, <code>pizzaplace</code>, and <code>exibble</code>. All of them are useful for experimenting with <strong>gt</strong>’s functions.</p>
+<p>Beyond this simple example, there are many functions available in <strong>gt</strong> for creating super-customized tables.</p>
+<p>Want to try this out? Then, take the <strong>gt</strong> Test Drive on <strong>RStudio Cloud</strong>. It’s full of ready-to-run examples.</p>
+<p align="center">
+</p>
+<p><a href="https://rstudio.cloud/project/779965"> <img src="reference/figures/gt-test-drive.svg" alt="RStudio Cloud Example" height="60px"></a></p>
+
+<p>You can install the development version of <strong>gt</strong> from <strong>GitHub</strong>:</p>
+<div class="sourceCode" id="cb2"><pre class="r"><span class="kw pkg">remotes</span><span class="kw ns">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html">install_github</a></span>(<span class="st">"rstudio/gt"</span>)</pre></div>
+<p>If you encounter a bug, have usage questions, or want to share ideas to make this package better, please feel free to file an <a href="https://github.com/rstudio/gt/issues">issue</a>.</p>
+<hr>
+<div id="how-gt-fits-in-with-other-packages-that-generate-display-tables" class="section level4">
+<h4 class="hasAnchor">
+<a href="#how-gt-fits-in-with-other-packages-that-generate-display-tables" class="anchor"></a>How <strong>gt</strong> fits in with Other Packages that Generate Display Tables</h4>
+<p>The <strong>gt</strong> package joins a burgeoning collection of packages for display table generation. Why another? We feel that there is enough room in this space to innovate further. Here are some of the ways that <strong>gt</strong> contributes to this ecosystem:</p>
+<ul>
+<li>the interface is high-level and declarative (general instructions versus very specific)</li>
+<li>the formatting options are ‘batteries included’ (scientific notation, uncertainty, ranges, percentages, suffixes, localized currency, dates/times + much more)</li>
+<li>there is excellent, pain-free support for footnotes</li>
+<li>the output is ‘camera-ready’</li>
+<li>it will eventually support multiple output formats (including LaTeX) with the same declarative interface</li>
+<li>the API closely follows tidyverse conventions by adhering to the <a href="https://style.tidyverse.org">tidyverse style guide</a>
+</li>
+<li>a focus on making the package documentation and examples the best they can be</li>
+<li>rigorous QA/QC measures: high test coverage for automated tests, and thorough manual testing by QA engineers (with every proposed code change)</li>
+</ul>
+<p>While <strong>gt</strong> is trying to do something different with its own interface, it may not suit your specific needs. Here is a listing of leading table-making <strong>R</strong> packages, with links to their respective project pages:</p>
+<p><strong>knitr</strong> (<a href="https://github.com/yihui/knitr">GITHUB</a>, <a href="https://yihui.org/knitr/">WEBSITE</a>) — <strong>kableExtra</strong> (<a href="https://github.com/haozhu233/kableExtra">GITHUB</a>, <a href="https://haozhu233.github.io/kableExtra/">WEBSITE</a>) — <strong>formattable</strong> (<a href="https://github.com/renkun-ken/formattable">GITHUB</a>, <a href="https://renkun-ken.github.io/formattable/">WEBSITE</a>) — <strong>DT</strong> (<a href="https://github.com/rstudio/DT">GITHUB</a>, <a href="https://rstudio.github.io/DT/">WEBSITE</a>) — <strong>pander</strong> (<a href="https://github.com/Rapporter/pander">GITHUB</a>, <a href="http://rapporter.github.io/pander">WEBSITE</a>) — <strong>huxtable</strong> (<a href="https://github.com/hughjonesd/huxtable">GITHUB</a>, <a href="https://hughjonesd.github.io/huxtable/">WEBSITE</a>) — <strong>reactable</strong> (<a href="https://github.com/glin/reactable">GITHUB</a>, <a href="https://glin.github.io/reactable/">WEBSITE</a>) — <strong>flextable</strong> (<a href="https://github.com/davidgohel/flextable">GITHUB</a>, <a href="https://davidgohel.github.io/flextable/">WEBSITE</a>) — <strong>pixiedust</strong> (<a href="https://github.com/nutterb/pixiedust">GITHUB</a>) — <strong>tangram</strong> (<a href="https://github.com/spgarbet/tangram">GITHUB</a>) — <strong>ztable</strong> (<a href="https://github.com/cardiomoon/ztable">GITHUB</a>) — <strong>condformat</strong> (<a href="https://github.com/zeehio/condformat">GITHUB</a>) — <strong>stargazer</strong> (<a href="https://CRAN.R-project.org/package=stargazer">CRAN</a>) — <strong>xtable</strong> (<a href="https://CRAN.R-project.org/package=xtable">CRAN</a>)</p>
+</div>
+<div id="code-of-conduct" class="section level4">
+<h4 class="hasAnchor">
+<a href="#code-of-conduct" class="anchor"></a>Code of Conduct</h4>
+<p>Please note that this project is released with a <a href="https://contributor-covenant.org/version/1/0/0">Contributor Code of Conduct</a>.<br>By participating in this project you agree to abide by its terms.</p>
+</div>
+<div id="license" class="section level4">
+<h4 class="hasAnchor">
+<a href="#license" class="anchor"></a>License</h4>
+<p>MIT © RStudio, PBC</p>
+</div>
+</div>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <div class="links">
+<h2>Links</h2>
+<ul class="list-unstyled">
+<li>Download from CRAN at <br><a href="https://cloud.r-project.org/package=gt">https://​cloud.r-project.org/​package=gt</a>
+</li>
+<li>Browse source code at <br><a href="https://github.com/rstudio/gt/">https://​github.com/​rstudio/​gt/​</a>
+</li>
+<li>Report a bug at <br><a href="https://github.com/rstudio/gt/issues">https://​github.com/​rstudio/​gt/​issues</a>
+</li>
+</ul>
+</div>
+<div class="license">
+<h2>License</h2>
+<ul class="list-unstyled">
+<li><a href="LICENSE.html">Full license</a></li>
+<li><small><a href="https://opensource.org/licenses/mit-license.php">MIT</a> + file <a href="LICENSE-text.html">LICENSE</a></small></li>
+</ul>
+</div>
+<div class="community">
+<h2>Community</h2>
+<ul class="list-unstyled">
+<li><a href="CONTRIBUTING.html">Contributing guide</a></li>
+<li><a href="CODE_OF_CONDUCT.html">Code of conduct</a></li>
+</ul>
+</div>
+<div class="developers">
+<h2>Developers</h2>
+<ul class="list-unstyled">
+<li>Richard Iannone <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/0000-0003-3925-190X" target="orcid.widget" aria-label="ORCID"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
+<li>Joe Cheng <br><small class="roles"> Author </small>  </li>
+<li>Barret Schloerke <br><small class="roles"> Author </small> <a href="https://orcid.org/0000-0001-9986-114X" target="orcid.widget" aria-label="ORCID"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
+<li>
+<a href="https://www.rstudio.com"><img src="https://www.tidyverse.org/rstudio-logo.svg" alt="RStudio" height="24"></a> <br><small class="roles"> Copyright holder, funder </small>  </li>
+</ul>
+</div>
+
+  <div class="dev-status">
+<h2>Dev status</h2>
+<ul class="list-unstyled">
+<li><a href="https://www.tidyverse.org/lifecycle/#maturing"><img src="https://img.shields.io/badge/lifecycle-maturing-blue.svg" alt="lifecycle"></a></li>
+<li><a href="https://cran.r-project.org/package=gt"><img src="https://www.r-pkg.org/badges/version/gt" alt="CRAN status"></a></li>
+<li><a href="https://travis-ci.com/rstudio/gt"><img src="https://travis-ci.com/rstudio/gt.svg?token=P7T9dzi5RLEq9j2Yepx5&amp;branch=master" alt="Travis build status"></a></li>
+<li><a href="https://ci.appveyor.com/project/rstudio/gt"><img src="https://ci.appveyor.com/api/projects/status/github/rstudio/gt?branch=master&amp;svg=true" alt="AppVeyor Build Status"></a></li>
+<li><a href="https://codecov.io/github/rstudio/gt?branch=master"><img src="https://codecov.io/gh/rstudio/gt/branch/master/graph/badge.svg" alt="Coverage status"></a></li>
+</ul>
+</div>
+</div>
+</div>
+
+
+      <footer><div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href="https://www.rstudio.com"><img src="https://www.tidyverse.org/rstudio-logo.svg" alt="RStudio" height="24"></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
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+</div>
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+  </body>
+</html>
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+<title>Changelog • gt</title>
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+        <span class="sr-only">Toggle navigation</span>
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
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+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
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+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+      <h1 data-toc-skip>Changelog <small></small></h1>
+      <small>Source: <a href='https://github.com/rstudio/gt/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
+    </div>
+
+    <div id="gt-0205" class="section level1">
+<h1 class="page-header" data-toc-text="0.2.0.5">
+<a href="#gt-0205" class="anchor"></a>gt 0.2.0.5<small> 2020-03-31 </small>
+</h1>
+<ul>
+<li>New package with 80 exported functions for building display tables</li>
+</ul>
+</div>
+    <div id="gt-010-unreleased" class="section level1">
+<h1 class="page-header" data-toc-text="0.1.0">
+<a href="#gt-010-unreleased" class="anchor"></a>gt 0.1.0 (unreleased)<small> Unreleased </small>
+</h1>
+</div>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/pkgdown.css b/docs/pkgdown.css
new file mode 100644
index 000000000..c01e5923b
--- /dev/null
+++ b/docs/pkgdown.css
@@ -0,0 +1,367 @@
+/* Sticky footer */
+
+/**
+ * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
+ * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
+ *
+ * .Site -> body > .container
+ * .Site-content -> body > .container .row
+ * .footer -> footer
+ *
+ * Key idea seems to be to ensure that .container and __all its parents__
+ * have height set to 100%
+ *
+ */
+
+html, body {
+  height: 100%;
+}
+
+body {
+  position: relative;
+}
+
+body > .container {
+  display: flex;
+  height: 100%;
+  flex-direction: column;
+}
+
+body > .container .row {
+  flex: 1 0 auto;
+}
+
+footer {
+  margin-top: 45px;
+  padding: 35px 0 36px;
+  border-top: 1px solid #e5e5e5;
+  color: #666;
+  display: flex;
+  flex-shrink: 0;
+}
+footer p {
+  margin-bottom: 0;
+}
+footer div {
+  flex: 1;
+}
+footer .pkgdown {
+  text-align: right;
+}
+footer p {
+  margin-bottom: 0;
+}
+
+img.icon {
+  float: right;
+}
+
+img {
+  max-width: 100%;
+}
+
+/* Fix bug in bootstrap (only seen in firefox) */
+summary {
+  display: list-item;
+}
+
+/* Typographic tweaking ---------------------------------*/
+
+.contents .page-header {
+  margin-top: calc(-60px + 1em);
+}
+
+dd {
+  margin-left: 3em;
+}
+
+/* Section anchors ---------------------------------*/
+
+a.anchor {
+  margin-left: -30px;
+  display:inline-block;
+  width: 30px;
+  height: 30px;
+  visibility: hidden;
+
+  background-image: url(./link.svg);
+  background-repeat: no-repeat;
+  background-size: 20px 20px;
+  background-position: center center;
+}
+
+.hasAnchor:hover a.anchor {
+  visibility: visible;
+}
+
+@media (max-width: 767px) {
+  .hasAnchor:hover a.anchor {
+    visibility: hidden;
+  }
+}
+
+
+/* Fixes for fixed navbar --------------------------*/
+
+.contents h1, .contents h2, .contents h3, .contents h4 {
+  padding-top: 60px;
+  margin-top: -40px;
+}
+
+/* Navbar submenu --------------------------*/
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+  position: relative;
+}
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+}
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+}
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+  border-style: solid;
+  border-width: 5px 0 5px 5px;
+  border-left-color: #cccccc;
+  margin-top: 5px;
+  margin-right: -10px;
+}
+
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+  border-left-color: #ffffff;
+}
+
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+  float: none;
+}
+
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+  left: -100%;
+  margin-left: 10px;
+  border-radius: 6px 0 6px 6px;
+}
+
+/* Sidebar --------------------------*/
+
+#pkgdown-sidebar {
+  margin-top: 30px;
+  position: -webkit-sticky;
+  position: sticky;
+  top: 70px;
+}
+
+#pkgdown-sidebar h2 {
+  font-size: 1.5em;
+  margin-top: 1em;
+}
+
+#pkgdown-sidebar h2:first-child {
+  margin-top: 0;
+}
+
+#pkgdown-sidebar .list-unstyled li {
+  margin-bottom: 0.5em;
+}
+
+/* bootstrap-toc tweaks ------------------------------------------------------*/
+
+/* All levels of nav */
+
+nav[data-toggle='toc'] .nav > li > a {
+  padding: 4px 20px 4px 6px;
+  font-size: 1.5rem;
+  font-weight: 400;
+  color: inherit;
+}
+
+nav[data-toggle='toc'] .nav > li > a:hover,
+nav[data-toggle='toc'] .nav > li > a:focus {
+  padding-left: 5px;
+  color: inherit;
+  border-left: 1px solid #878787;
+}
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+nav[data-toggle='toc'] .nav > .active > a,
+nav[data-toggle='toc'] .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav > .active:focus > a {
+  padding-left: 5px;
+  font-size: 1.5rem;
+  font-weight: 400;
+  color: inherit;
+  border-left: 2px solid #878787;
+}
+
+/* Nav: second level (shown on .active) */
+
+nav[data-toggle='toc'] .nav .nav {
+  display: none; /* Hide by default, but at >768px, show it */
+  padding-bottom: 10px;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a {
+  padding-left: 16px;
+  font-size: 1.35rem;
+}
+
+nav[data-toggle='toc'] .nav .nav > li > a:hover,
+nav[data-toggle='toc'] .nav .nav > li > a:focus {
+  padding-left: 15px;
+}
+
+nav[data-toggle='toc'] .nav .nav > .active > a,
+nav[data-toggle='toc'] .nav .nav > .active:hover > a,
+nav[data-toggle='toc'] .nav .nav > .active:focus > a {
+  padding-left: 15px;
+  font-weight: 500;
+  font-size: 1.35rem;
+}
+
+/* orcid ------------------------------------------------------------------- */
+
+.orcid {
+  font-size: 16px;
+  color: #A6CE39;
+  /* margins are required by official ORCID trademark and display guidelines */
+  margin-left:4px;
+  margin-right:4px;
+  vertical-align: middle;
+}
+
+/* Reference index & topics ----------------------------------------------- */
+
+.ref-index th {font-weight: normal;}
+
+.ref-index td {vertical-align: top;}
+.ref-index .icon {width: 40px;}
+.ref-index .alias {width: 40%;}
+.ref-index-icons .alias {width: calc(40% - 40px);}
+.ref-index .title {width: 60%;}
+
+.ref-arguments th {text-align: right; padding-right: 10px;}
+.ref-arguments th, .ref-arguments td {vertical-align: top;}
+.ref-arguments .name {width: 20%;}
+.ref-arguments .desc {width: 80%;}
+
+/* Nice scrolling for wide elements --------------------------------------- */
+
+table {
+  display: block;
+  overflow: auto;
+}
+
+/* Syntax highlighting ---------------------------------------------------- */
+
+pre {
+  word-wrap: normal;
+  word-break: normal;
+  border: 1px solid #eee;
+}
+
+pre, code {
+  background-color: #f8f8f8;
+  color: #333;
+}
+
+pre code {
+  overflow: auto;
+  word-wrap: normal;
+  white-space: pre;
+}
+
+pre .img {
+  margin: 5px 0;
+}
+
+pre .img img {
+  background-color: #fff;
+  display: block;
+  height: auto;
+}
+
+code a, pre a {
+  color: #375f84;
+}
+
+a.sourceLine:hover {
+  text-decoration: none;
+}
+
+.fl      {color: #1514b5;}
+.fu      {color: #000000;} /* function */
+.ch,.st  {color: #036a07;} /* string */
+.kw      {color: #264D66;} /* keyword */
+.co      {color: #888888;} /* comment */
+
+.message { color: black;   font-weight: bolder;}
+.error   { color: orange;  font-weight: bolder;}
+.warning { color: #6A0366; font-weight: bolder;}
+
+/* Clipboard --------------------------*/
+
+.hasCopyButton {
+  position: relative;
+}
+
+.btn-copy-ex {
+  position: absolute;
+  right: 0;
+  top: 0;
+  visibility: hidden;
+}
+
+.hasCopyButton:hover button.btn-copy-ex {
+  visibility: visible;
+}
+
+/* headroom.js ------------------------ */
+
+.headroom {
+  will-change: transform;
+  transition: transform 200ms linear;
+}
+.headroom--pinned {
+  transform: translateY(0%);
+}
+.headroom--unpinned {
+  transform: translateY(-100%);
+}
+
+/* mark.js ----------------------------*/
+
+mark {
+  background-color: rgba(255, 255, 51, 0.5);
+  border-bottom: 2px solid rgba(255, 153, 51, 0.3);
+  padding: 1px;
+}
+
+/* vertical spacing after htmlwidgets */
+.html-widget {
+  margin-bottom: 10px;
+}
+
+/* fontawesome ------------------------ */
+
+.fab {
+    font-family: "Font Awesome 5 Brands" !important;
+}
+
+/* don't display links in code chunks when printing */
+/* source: https://stackoverflow.com/a/10781533 */
+@media print {
+  code a:link:after, code a:visited:after {
+    content: "";
+  }
+}
diff --git a/docs/pkgdown.js b/docs/pkgdown.js
new file mode 100644
index 000000000..7e7048fae
--- /dev/null
+++ b/docs/pkgdown.js
@@ -0,0 +1,108 @@
+/* http://gregfranko.com/blog/jquery-best-practices/ */
+(function($) {
+  $(function() {
+
+    $('.navbar-fixed-top').headroom();
+
+    $('body').css('padding-top', $('.navbar').height() + 10);
+    $(window).resize(function(){
+      $('body').css('padding-top', $('.navbar').height() + 10);
+    });
+
+    $('[data-toggle="tooltip"]').tooltip();
+
+    var cur_path = paths(location.pathname);
+    var links = $("#navbar ul li a");
+    var max_length = -1;
+    var pos = -1;
+    for (var i = 0; i < links.length; i++) {
+      if (links[i].getAttribute("href") === "#")
+        continue;
+      // Ignore external links
+      if (links[i].host !== location.host)
+        continue;
+
+      var nav_path = paths(links[i].pathname);
+
+      var length = prefix_length(nav_path, cur_path);
+      if (length > max_length) {
+        max_length = length;
+        pos = i;
+      }
+    }
+
+    // Add class to parent <li>, and enclosing <li> if in dropdown
+    if (pos >= 0) {
+      var menu_anchor = $(links[pos]);
+      menu_anchor.parent().addClass("active");
+      menu_anchor.closest("li.dropdown").addClass("active");
+    }
+  });
+
+  function paths(pathname) {
+    var pieces = pathname.split("/");
+    pieces.shift(); // always starts with /
+
+    var end = pieces[pieces.length - 1];
+    if (end === "index.html" || end === "")
+      pieces.pop();
+    return(pieces);
+  }
+
+  // Returns -1 if not found
+  function prefix_length(needle, haystack) {
+    if (needle.length > haystack.length)
+      return(-1);
+
+    // Special case for length-0 haystack, since for loop won't run
+    if (haystack.length === 0) {
+      return(needle.length === 0 ? 0 : -1);
+    }
+
+    for (var i = 0; i < haystack.length; i++) {
+      if (needle[i] != haystack[i])
+        return(i);
+    }
+
+    return(haystack.length);
+  }
+
+  /* Clipboard --------------------------*/
+
+  function changeTooltipMessage(element, msg) {
+    var tooltipOriginalTitle=element.getAttribute('data-original-title');
+    element.setAttribute('data-original-title', msg);
+    $(element).tooltip('show');
+    element.setAttribute('data-original-title', tooltipOriginalTitle);
+  }
+
+  if(ClipboardJS.isSupported()) {
+    $(document).ready(function() {
+      var copyButton = "<button type='button' class='btn btn-primary btn-copy-ex' type = 'submit' title='Copy to clipboard' aria-label='Copy to clipboard' data-toggle='tooltip' data-placement='left auto' data-trigger='hover' data-clipboard-copy><i class='fa fa-copy'></i></button>";
+
+      $(".examples, div.sourceCode").addClass("hasCopyButton");
+
+      // Insert copy buttons:
+      $(copyButton).prependTo(".hasCopyButton");
+
+      // Initialize tooltips:
+      $('.btn-copy-ex').tooltip({container: 'body'});
+
+      // Initialize clipboard:
+      var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', {
+        text: function(trigger) {
+          return trigger.parentNode.textContent;
+        }
+      });
+
+      clipboardBtnCopies.on('success', function(e) {
+        changeTooltipMessage(e.trigger, 'Copied!');
+        e.clearSelection();
+      });
+
+      clipboardBtnCopies.on('error', function() {
+        changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
+      });
+    });
+  }
+})(window.jQuery || window.$)
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
new file mode 100644
index 000000000..a09c55328
--- /dev/null
+++ b/docs/pkgdown.yml
@@ -0,0 +1,13 @@
+pandoc: 2.7.3
+pkgdown: 1.5.0.9000
+pkgdown_sha: 2254f318a4c1cb12419e27155cce74307bd844ea
+articles:
+  case-study-gtcars: case-study-gtcars.html
+  creating-summary-lines: creating-summary-lines.html
+  gt-datasets: gt-datasets.html
+  intro-creating-gt-tables: intro-creating-gt-tables.html
+last_built: 2020-04-03T18:28Z
+urls:
+  reference: https://gt.rstudio.com/reference
+  article: https://gt.rstudio.com/articles
+
diff --git a/docs/reference/adjust_luminance.html b/docs/reference/adjust_luminance.html
new file mode 100644
index 000000000..cba4a745a
--- /dev/null
+++ b/docs/reference/adjust_luminance.html
@@ -0,0 +1,284 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Adjust the luminance for a palette of colors — adjust_luminance • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
+<link rel="stylesheet" href="../bootstrap-toc.css">
+<script src="../bootstrap-toc.js"></script>
+
+<!-- Font Awesome icons -->
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="../pkgdown.css" rel="stylesheet">
+<script src="../pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Adjust the luminance for a palette of colors — adjust_luminance" />
+<meta property="og:description" content="This function can brighten or darken a palette of colors by an arbitrary
+number of steps, which is defined by a real number between -2.0 and 2.0. The
+transformation of a palette by a fixed step in this function will tend to
+apply greater darkening or lightening for those colors in the midrange
+compared to any very dark or very light colors in the input palette." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-reference-topic">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Adjust the luminance for a palette of colors</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>adjust_luminance.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This function can brighten or darken a palette of colors by an arbitrary
+number of steps, which is defined by a real number between -2.0 and 2.0. The
+transformation of a palette by a fixed step in this function will tend to
+apply greater darkening or lightening for those colors in the midrange
+compared to any very dark or very light colors in the input palette.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>adjust_luminance</span>(<span class='no'>colors</span>, <span class='no'>steps</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>colors</th>
+      <td><p>A vector of colors that will undergo an adjustment in
+luminance. Each color value provided must either be a color name (in the
+set of colors provided by <code><a href='https://rdrr.io/r/grDevices/colors.html'>grDevices::colors()</a></code>) or a hexadecimal string in
+the form of "#RRGGBB" or "#RRGGBBAA".</p></td>
+    </tr>
+    <tr>
+      <th>steps</th>
+      <td><p>A positive or negative factor by which the luminance will be
+adjusted. Must be a number between <code>-2.0</code> and <code>2.0</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A vector of color values.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>This function can be useful when combined with the <code><a href='data_color.html'>data_color()</a></code> function's
+<code>palette</code> argument, which can use a vector of colors or any of the <code>col_*</code>
+functions from the <strong>scales</strong> package (all of which have a <code>palette</code>
+argument).</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_adjust_luminance_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-18</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get a palette of 8 pastel colors from</span>
+<span class='co'># the RColorBrewer package</span>
+<span class='no'>pal</span> <span class='kw'>&lt;-</span> <span class='kw pkg'>RColorBrewer</span><span class='kw ns'>::</span><span class='fu'><a href='https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html'>brewer.pal</a></span>(<span class='fl'>8</span>, <span class='st'>"Pastel2"</span>)
+
+<span class='co'># Create lighter and darker variants</span>
+<span class='co'># of the base palette (one step lower, one</span>
+<span class='co'># step higher)</span>
+<span class='no'>pal_darker</span>  <span class='kw'>&lt;-</span> <span class='no'>pal</span> <span class='kw'>%&gt;%</span> <span class='fu'>adjust_luminance</span>(-<span class='fl'>1.0</span>)
+<span class='no'>pal_lighter</span> <span class='kw'>&lt;-</span> <span class='no'>pal</span> <span class='kw'>%&gt;%</span> <span class='fu'>adjust_luminance</span>(+<span class='fl'>1.0</span>)
+
+<span class='co'># Create a tibble and make a gt table</span>
+<span class='co'># from it; color each column in order of</span>
+<span class='co'># increasingly darker palettes (with</span>
+<span class='co'># `data_color()`)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(<span class='kw'>a</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>8</span>, <span class='kw'>b</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>8</span>, <span class='kw'>c</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='data_color.html'>data_color</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>a</span>),
+    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
+      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='no'>pal_lighter</span>,
+      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>8</span>)
+    )
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='data_color.html'>data_color</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>b</span>),
+    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
+      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='no'>pal</span>,
+      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>8</span>)
+    )
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='data_color.html'>data_color</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>c</span>),
+    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
+      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='no'>pal_darker</span>,
+      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>8</span>)
+    )
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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diff --git a/docs/reference/as.data.frame.gt_tbl.html b/docs/reference/as.data.frame.gt_tbl.html
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+
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+
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Transform a <strong>gt</strong> object to a data frame</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/as_data_frame.R'><code>R/as_data_frame.R</code></a></small>
+    <div class="hidden name"><code>as.data.frame.gt_tbl.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This facilitates conversion of the <code>gt_tbl</code> object to a data frame.</p>
+    </div>
+
+    <pre class="usage"><span class='co'># S3 method for gt_tbl</span>
+<span class='fu'><a href='https://rdrr.io/r/base/as.data.frame.html'>as.data.frame</a></span>(<span class='no'>x</span>, <span class='no'>...</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>x</th>
+      <td><p>An object of class <code>gt_tbl</code>.</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>Any additional parameters.</p></td>
+    </tr>
+    </table>
+
+
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/as_latex.html b/docs/reference/as_latex.html
new file mode 100644
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+
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+<meta property="og:title" content="Output a gt object as LaTeX — as_latex" />
+<meta property="og:description" content="Get the LaTeX content from a gt_tbl object as a knit_asis object. This
+object contains the LaTeX code and attributes that serve as LaTeX
+dependencies (i.e., the LaTeX packages required for the table). Using
+as.character() on the created object will result in a single-element vector
+containing the LaTeX code." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+
+<!-- mathjax -->
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+
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+
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+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
+</li>
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+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
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+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
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+     
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+    </div><!--/.nav-collapse -->
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Output a gt object as LaTeX</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
+    <div class="hidden name"><code>as_latex.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Get the LaTeX content from a <code>gt_tbl</code> object as a <code>knit_asis</code> object. This
+object contains the LaTeX code and attributes that serve as LaTeX
+dependencies (i.e., the LaTeX packages required for the table). Using
+<code><a href='https://rdrr.io/r/base/character.html'>as.character()</a></code> on the created object will result in a single-element vector
+containing the LaTeX code.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>as_latex</span>(<span class='no'>data</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>13-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Export Functions: 
+<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
+<code><a href='as_rtf.html'>as_rtf</a>()</code>,
+<code><a href='extract_summary.html'>extract_summary</a>()</code>,
+<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># add a header and then export as</span>
+<span class='co'># an object with LaTeX code</span>
+<span class='no'>tab_latex</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>as_latex</span>()
+
+<span class='co'># `tab_latex` is a `knit_asis` object,</span>
+<span class='co'># which makes it easy to include in</span>
+<span class='co'># R Markdown documents that are knit to</span>
+<span class='co'># PDF; we can use `as.character()` to</span>
+<span class='co'># get just the LaTeX code as a single-</span>
+<span class='co'># element vector</span>
+<span class='no'>tab_latex</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/base/character.html'>as.character</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/base/cat.html'>cat</a></span>()</div><div class='output co'>#&gt; \captionsetup[table]{labelformat=empty,skip=1pt}
+#&gt; \begin{longtable}{llr}
+#&gt; \caption*{
+#&gt; \large Data listing from \textbf{gtcars}\\ 
+#&gt; \small \texttt{gtcars} is an R dataset\\ 
+#&gt; } \\ 
+#&gt; \toprule
+#&gt; mfr &amp; model &amp; msrp \\ 
+#&gt; \midrule
+#&gt; Ford &amp; GT &amp; 447000 \\ 
+#&gt; Ferrari &amp; 458 Speciale &amp; 291744 \\ 
+#&gt; Ferrari &amp; 458 Spider &amp; 263553 \\ 
+#&gt; Ferrari &amp; 458 Italia &amp; 233509 \\ 
+#&gt; Ferrari &amp; 488 GTB &amp; 245400 \\ 
+#&gt; \bottomrule
+#&gt; \end{longtable}</div><div class='input'>
+</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+</div>
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diff --git a/docs/reference/as_raw_html.html b/docs/reference/as_raw_html.html
new file mode 100644
index 000000000..bf9c40c5d
--- /dev/null
+++ b/docs/reference/as_raw_html.html
@@ -0,0 +1,243 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Get the HTML content of a <strong>gt</strong> table — as_raw_html • gt</title>
+
+<!-- favicons -->
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+<!-- Bootstrap -->
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+<meta property="og:title" content="Get the HTML content of a <strong>gt</strong> table — as_raw_html" />
+<meta property="og:description" content="Get the HTML content from a gt_tbl object as a single-element character
+vector. By default, the generated HTML will have inlined styles, where CSS
+styles (that were previously contained in CSS rule sets external to the
+&amp;lt;table&amp;gt; element) are included as style attributes in the HTML table's
+tags. This option is preferable when using the output HTML table in an
+emailing context." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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+<![endif]-->
+
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Get the HTML content of a <strong>gt</strong> table</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
+    <div class="hidden name"><code>as_raw_html.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Get the HTML content from a <code>gt_tbl</code> object as a single-element character
+vector. By default, the generated HTML will have inlined styles, where CSS
+styles (that were previously contained in CSS rule sets external to the
+<code>&lt;table&gt; element</code>) are included as <code>style</code> attributes in the HTML table's
+tags. This option is preferable when using the output HTML table in an
+emailing context.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>as_raw_html</span>(<span class='no'>data</span>, <span class='kw'>inline_css</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>inline_css</th>
+      <td><p>An option to supply styles to table elements as inlined CSS
+styles. This is useful when including the table HTML as part of an HTML
+email message body, since inlined styles are largely supported in email
+clients over using CSS in a <code>&lt;style&gt;</code> block.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>13-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Export Functions: 
+<code><a href='as_latex.html'>as_latex</a>()</code>,
+<code><a href='as_rtf.html'>as_rtf</a>()</code>,
+<code><a href='extract_summary.html'>extract_summary</a>()</code>,
+<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># add a header and then export as</span>
+<span class='co'># HTML code with CSS inlined</span>
+<span class='no'>tab_html</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>as_raw_html</span>()
+
+<span class='co'># `tab_html` is a single-element vector</span>
+<span class='co'># containing inlined HTML for the table;</span>
+<span class='co'># it has only the `&lt;table&gt;...&lt;/table&gt;` part</span>
+<span class='co'># so it's not a complete HTML document but</span>
+<span class='co'># rather an HTML fragment</span>
+<span class='no'>tab_html</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='fl'>1</span>, <span class='fl'>700</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/base/cat.html'>cat</a></span>()</div><div class='output co'>#&gt; &lt;table style="font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif; display: table; border-collapse: collapse; margin-left: auto; margin-right: auto; color: #333333; font-size: 16px; background-color: #FFFFFF; width: auto; border-top-style: solid; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3;"&gt;
+#&gt;   &lt;thead style=""&gt;
+#&gt;     &lt;tr&gt;
+#&gt;       &lt;th colspan="3" styl</div><div class='input'>
+</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+</div>
+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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diff --git a/docs/reference/as_rtf.html b/docs/reference/as_rtf.html
new file mode 100644
index 000000000..d420eeefc
--- /dev/null
+++ b/docs/reference/as_rtf.html
@@ -0,0 +1,217 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Output a <strong>gt</strong> object as RTF — as_rtf • gt</title>
+
+<!-- favicons -->
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+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
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+
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+<meta property="og:title" content="Output a <strong>gt</strong> object as RTF — as_rtf" />
+<meta property="og:description" content="Get the RTF content from a gt_tbl object as as a single-element character
+vector. This object can be used with writeLines() to generate a valid .rtf
+file that can be opened by RTF readers." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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+<![endif]-->
+
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+    <div class="container template-reference-topic">
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+      </span>
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+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
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+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
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+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Output a <strong>gt</strong> object as RTF</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
+    <div class="hidden name"><code>as_rtf.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Get the RTF content from a <code>gt_tbl</code> object as as a single-element character
+vector. This object can be used with <code><a href='https://rdrr.io/r/base/writeLines.html'>writeLines()</a></code> to generate a valid .rtf
+file that can be opened by RTF readers.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>as_rtf</span>(<span class='no'>data</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>a table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>13-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Export Functions: 
+<code><a href='as_latex.html'>as_latex</a>()</code>,
+<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
+<code><a href='extract_summary.html'>extract_summary</a>()</code>,
+<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># add a header and then export as</span>
+<span class='co'># RTF code</span>
+<span class='no'>tab_rtf</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>2</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>as_rtf</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+
diff --git a/docs/reference/cell_borders.html b/docs/reference/cell_borders.html
new file mode 100644
index 000000000..f09565aab
--- /dev/null
+++ b/docs/reference/cell_borders.html
@@ -0,0 +1,300 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Helper for defining custom borders for table cells — cell_borders • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
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+
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+<!-- Bootstrap -->
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+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
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+<script src="../pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Helper for defining custom borders for table cells — cell_borders" />
+<meta property="og:description" content="The cell_borders() helper function is to be used with the tab_style()
+function, which itself allows for the setting of custom styles to one or more
+cells. Specifically, the call to cell_borders() should be bound to the
+styles argument of tab_style(). The selection argument is where we
+define which borders should be modified (e.g., &quot;left&quot;, &quot;right&quot;, etc.).
+With that selection, the color, style, and weight of the selected
+borders can then be modified." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
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+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
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+    <div class="container template-reference-topic">
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
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+
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+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
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+     
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper for defining custom borders for table cells</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cell_borders.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cell_borders()</code> helper function is to be used with the <code><a href='tab_style.html'>tab_style()</a></code>
+function, which itself allows for the setting of custom styles to one or more
+cells. Specifically, the call to <code>cell_borders()</code> should be bound to the
+<code>styles</code> argument of <code><a href='tab_style.html'>tab_style()</a></code>. The <code>selection</code> argument is where we
+define which borders should be modified (e.g., <code>"left"</code>, <code>"right"</code>, etc.).
+With that selection, the <code>color</code>, <code>style</code>, and <code>weight</code> of the selected
+borders can then be modified.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cell_borders</span>(<span class='kw'>sides</span> <span class='kw'>=</span> <span class='st'>"all"</span>, <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#000000"</span>, <span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"solid"</span>, <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>1</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>sides</th>
+      <td><p>The border sides to be modified. Options include <code>"left"</code>,
+<code>"right"</code>, <code>"top"</code>, and <code>"bottom"</code>. For all borders surrounding the
+selected cells, we can use the <code>"all"</code> option.</p></td>
+    </tr>
+    <tr>
+      <th>color, style, weight</th>
+      <td><p>The border color, style, and weight. The <code>color</code>
+can be defined with a color name or with a hexadecimal color code. The
+default <code>color</code> value is <code>"#000000"</code> (black). The <code>style</code> can be one of
+either <code>"solid"</code> (the default), <code>"dashed"</code>, or <code>"dotted"</code>. The <code>weight</code> of
+the border lines is to be given in pixel values (the <code><a href='px.html'>px()</a></code> helper function
+is useful for this. The default value for <code>weight</code> is <code>"1px"</code>. Borders for
+any defined <code>sides</code> can be removed by supplying <code>NULL</code> to any of <code>color</code>,
+<code>style</code>, or <code>weight</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object of class <code>cell_styles</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cell_borders_1.png' width=100% /></p>
+<p><img src='figures/man_cell_borders_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-17</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Add horizontal border lines for</span>
+<span class='co'># all table body rows in `exibble`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='tab_options.html'>tab_options</a></span>(<span class='kw'>row.striping.include_table_body</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>) <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+      <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_borders</span>(
+        <span class='kw'>sides</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"top"</span>, <span class='st'>"bottom"</span>),
+        <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#BBBBBB"</span>,
+        <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>1.5</span>),
+        <span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"solid"</span>
+      ),
+      <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+        <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>(),
+        <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>()
+      )
+    )
+
+<span class='co'># Incorporate different horizontal and</span>
+<span class='co'># vertical borders at several locations;</span>
+<span class='co'># this uses multiple `cell_borders()` and</span>
+<span class='co'># `cells_body()` calls within `list()`s</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+      <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+        <span class='fu'>cell_borders</span>(
+          <span class='kw'>sides</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"top"</span>, <span class='st'>"bottom"</span>),
+          <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#FF0000"</span>,
+          <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>2</span>)
+        ),
+        <span class='fu'>cell_borders</span>(
+          <span class='kw'>sides</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"left"</span>, <span class='st'>"right"</span>),
+          <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#0000FF"</span>,
+          <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>2</span>)
+        )
+      ),
+      <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+        <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+          <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+          <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>num</span>)
+        ),
+        <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+          <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+          <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>currency</span>)
+        )
+      )
+    )</div></pre>
+  </div>
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diff --git a/docs/reference/cell_fill.html b/docs/reference/cell_fill.html
new file mode 100644
index 000000000..5c1f0320d
--- /dev/null
+++ b/docs/reference/cell_fill.html
@@ -0,0 +1,262 @@
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+<title>Helper for defining custom fills for table cells — cell_fill • gt</title>
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+<meta property="og:title" content="Helper for defining custom fills for table cells — cell_fill" />
+<meta property="og:description" content="The cell_fill() helper function is to be used with the tab_style()
+function, which itself allows for the setting of custom styles to one or more
+cells. Specifically, the call to cell_fill() should be bound to the
+styles argument of tab_style()." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper for defining custom fills for table cells</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cell_fill.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cell_fill()</code> helper function is to be used with the <code><a href='tab_style.html'>tab_style()</a></code>
+function, which itself allows for the setting of custom styles to one or more
+cells. Specifically, the call to <code>cell_fill()</code> should be bound to the
+<code>styles</code> argument of <code><a href='tab_style.html'>tab_style()</a></code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cell_fill</span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#D3D3D3"</span>, <span class='kw'>alpha</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>color</th>
+      <td><p>The fill color. If nothing is provided, then <code>"#D3D3D3"</code> (light
+gray) will be used as a default.</p></td>
+    </tr>
+    <tr>
+      <th>alpha</th>
+      <td><p>An optional alpha transparency value for the <code>color</code> as single
+value in the range of <code>0</code> (fully transparent) to <code>1</code> (fully opaque). If not
+provided the fill color will either be fully opaque or use alpha
+information from the color value if it is supplied in the #RRGGBBAA format.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object of class <code>cell_styles</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cell_fill_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-16</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># add styles with `tab_style()` and</span>
+<span class='co'># the `cell_fill()` helper function</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_fill</span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;=</span> <span class='fl'>5000</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_fill</span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"gray85"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&lt;</span> <span class='fl'>100</span>
+    )
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/cell_text.html b/docs/reference/cell_text.html
new file mode 100644
index 000000000..df1e85e32
--- /dev/null
+++ b/docs/reference/cell_text.html
@@ -0,0 +1,328 @@
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+<meta property="og:description" content="This helper function is to be used with the tab_style() function, which
+itself allows for the setting of custom styles to one or more cells. We can
+also define several styles within a single call of cell_text() and
+tab_style() will reliably apply those styles to the targeted element." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper for defining custom text styles for table cells</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cell_text.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This helper function is to be used with the <code><a href='tab_style.html'>tab_style()</a></code> function, which
+itself allows for the setting of custom styles to one or more cells. We can
+also define several styles within a single call of <code>cell_text()</code> and
+<code><a href='tab_style.html'>tab_style()</a></code> will reliably apply those styles to the targeted element.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cell_text</span>(
+  <span class='kw'>color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>font</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>v_align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stretch</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>indent</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>decorate</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>color</th>
+      <td><p>The text color.</p></td>
+    </tr>
+    <tr>
+      <th>font</th>
+      <td><p>The font or collection of fonts (subsequent font names are) used
+as fallbacks.</p></td>
+    </tr>
+    <tr>
+      <th>size</th>
+      <td><p>The size of the font. Can be provided as a number that is assumed
+to represent <code>px</code> values (or could be wrapped in the <code><a href='px.html'>px()</a></code>) helper
+function. We can also use one of the following absolute size keywords:
+<code>"xx-small"</code>, <code>"x-small"</code>, <code>"small"</code>, <code>"medium"</code>, <code>"large"</code>, <code>"x-large"</code>,
+or <code>"xx-large"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>align</th>
+      <td><p>The text alignment. Can be one of either <code>"center"</code>, <code>"left"</code>,
+<code>"right"</code>, or <code>"justify"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>v_align</th>
+      <td><p>The vertical alignment of the text in the cell. Options are
+<code>"middle"</code>, <code>"top"</code>, or <code>"bottom"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>style</th>
+      <td><p>The text style. Can be one of either <code>"center"</code>, <code>"normal"</code>,
+<code>"italic"</code>, or <code>"oblique"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>weight</th>
+      <td><p>The weight of the font. Can be a text-based keyword such as
+<code>"normal"</code>, <code>"bold"</code>, <code>"lighter"</code>, <code>"bolder"</code>, or, a numeric value between
+<code>1</code> and <code>1000</code>, inclusive. Note that only variable fonts may support the
+numeric mapping of weight.</p></td>
+    </tr>
+    <tr>
+      <th>stretch</th>
+      <td><p>Allows for text to either be condensed or expanded. We can use
+one of the following text-based keywords to describe the degree of
+condensation/expansion: <code>"ultra-condensed"</code>, <code>"extra-condensed"</code>,
+<code>"condensed"</code>, <code>"semi-condensed"</code>, <code>"normal"</code>, <code>"semi-expanded"</code>,
+<code>"expanded"</code>, <code>"extra-expanded"</code>, or <code>"ultra-expanded"</code>. Alternatively, we
+can supply percentage values from <code>0\%</code> to <code>200\%</code>, inclusive. Negative
+percentage values are not allowed.</p></td>
+    </tr>
+    <tr>
+      <th>indent</th>
+      <td><p>The indentation of the text. Can be provided as a number that
+is assumed to represent <code>px</code> values (or could be wrapped in the <code><a href='px.html'>px()</a></code>)
+helper function. Alternatively, this can be given as a percentage (easily
+constructed with <code><a href='pct.html'>pct()</a></code>).</p></td>
+    </tr>
+    <tr>
+      <th>decorate</th>
+      <td><p>allows for text decoration effect to be applied. Here, we can
+use <code>"overline"</code>, <code>"line-through"</code>, or <code>"underline"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>transform</th>
+      <td><p>Allows for the transformation of text. Options are
+<code>"uppercase"</code>, <code>"lowercase"</code>, or <code>"capitalize"</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object of class <code>cell_styles</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cell_text_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-15</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># add styles with `tab_style()` and</span>
+<span class='co'># the `cell_text()` helper function</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_text</span>(<span class='kw'>weight</span> <span class='kw'>=</span> <span class='st'>"bold"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;=</span> <span class='fl'>5000</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_text</span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&lt;</span> <span class='fl'>100</span>
+    )
+  )</div></pre>
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+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/cells_body.html b/docs/reference/cells_body.html
new file mode 100644
index 000000000..351226778
--- /dev/null
+++ b/docs/reference/cells_body.html
@@ -0,0 +1,281 @@
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+<title>Location helper for targeting data cells in the table body — cells_body • gt</title>
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+<meta property="og:title" content="Location helper for targeting data cells in the table body — cells_body" />
+<meta property="og:description" content="The cells_body() function is used to target the data cells in the table
+body. The function can be used to apply a footnote with tab_footnote(), to
+add custom styling with tab_style(), or the transform the targeted cells
+with text_transform(). The function is expressly used in each of those
+functions' locations argument." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+
+<!-- mathjax -->
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+<li class="dropdown">
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+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
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+  <a href="../news/index.html">News</a>
+</li>
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+      <ul class="nav navbar-nav navbar-right">
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+    <span class="fa fa-github fa-lg"></span>
+     
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+      
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting data cells in the table body</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_body.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_body()</code> function is used to target the data cells in the table
+body. The function can be used to apply a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code>, to
+add custom styling with <code><a href='tab_style.html'>tab_style()</a></code>, or the transform the targeted cells
+with <code><a href='text_transform.html'>text_transform()</a></code>. The function is expressly used in each of those
+functions' <code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_body</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>columns</th>
+      <td><p>The names of the columns that are to be targeted.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>The names of the rows that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_body</code> and <code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code>cells_body()</code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_body_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-11</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table; add</span>
+<span class='co'># a footnote that targets a single data cell</span>
+<span class='co'># with `tab_footnote()`, using `cells_body()`</span>
+<span class='co'># in `locations` (`rows = hp == max(hp)` will</span>
+<span class='co'># target a single row in the `hp` column)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>ctry_origin</span> <span class='kw'>==</span> <span class='st'>"United Kingdom"</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Highest horsepower."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_body</span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>hp</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>hp</span> <span class='kw'>==</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>hp</span>))
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='opt_footnote_marks.html'>opt_footnote_marks</a></span>(<span class='kw'>marks</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"*"</span>, <span class='st'>"+"</span>))</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/cells_column_labels.html b/docs/reference/cells_column_labels.html
new file mode 100644
index 000000000..07fb7338d
--- /dev/null
+++ b/docs/reference/cells_column_labels.html
@@ -0,0 +1,283 @@
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+<title>Location helper for targeting the column labels — cells_column_labels • gt</title>
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+<meta property="og:title" content="Location helper for targeting the column labels — cells_column_labels" />
+<meta property="og:description" content="The cells_column_labels() function is used to target the table's column
+labels when applying a footnote with tab_footnote() or adding custom style
+with tab_style(). The function is expressly used in each of those
+functions' locations argument." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+    </div><!--/.nav-collapse -->
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting the column labels</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_column_labels.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_column_labels()</code> function is used to target the table's column
+labels when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style
+with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those
+functions' <code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_column_labels</span>(<span class='no'>columns</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>columns</th>
+      <td><p>The names of the column labels that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_column_labels</code> and
+<code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code>cells_column_labels()</code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_column_labels_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-8</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sza` to create a gt table; add a</span>
+<span class='co'># header and then add footnotes to the</span>
+<span class='co'># column labels with `tab_footnote()` and</span>
+<span class='co'># `cells_column_labels()` in `locations`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>20</span> <span class='kw'>&amp;</span> <span class='no'>month</span> <span class='kw'>==</span> <span class='st'>"jan"</span> <span class='kw'>&amp;</span>
+      !<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>sza</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>, -<span class='no'>month</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"True solar time."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_column_labels</span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>tst</span>)
+    )
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Solar zenith angle."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_column_labels</span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sza</span>)
+    )
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+</div>
+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+   </div>
+
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+
+  </body>
+</html>
+
+
diff --git a/docs/reference/cells_column_spanners.html b/docs/reference/cells_column_spanners.html
new file mode 100644
index 000000000..2fe98e951
--- /dev/null
+++ b/docs/reference/cells_column_spanners.html
@@ -0,0 +1,275 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Location helper for targeting the column spanners — cells_column_spanners • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png" />
+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
+<!-- bootstrap-toc -->
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="../pkgdown.css" rel="stylesheet">
+<script src="../pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Location helper for targeting the column spanners — cells_column_spanners" />
+<meta property="og:description" content="The cells_column_spanners() function is used to target the cells that
+contain the table column spanners. This is useful when applying a footnote
+with tab_footnote() or adding custom style with tab_style(). The function
+is expressly used in each of those functions' locations argument." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
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+<![endif]-->
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+
+    <div id="navbar" class="navbar-collapse collapse">
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+        <li>
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+  <a href="../news/index.html">News</a>
+</li>
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+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting the column spanners</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_column_spanners.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_column_spanners()</code> function is used to target the cells that
+contain the table column spanners. This is useful when applying a footnote
+with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with <code><a href='tab_style.html'>tab_style()</a></code>. The function
+is expressly used in each of those functions' <code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_column_spanners</span>(<span class='no'>spanners</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>spanners</th>
+      <td><p>The names of the spanners that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_column_spanners</code> and
+<code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code>cells_column_spanners()</code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_column_spanners_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-7</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table; add a</span>
+<span class='co'># spanner column label over three column</span>
+<span class='co'># labels and then use `tab_style()` to make</span>
+<span class='co'># the spanner label text bold</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>fctr</span>, -<span class='no'>currency</span>, -<span class='no'>group</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_spanner.html'>tab_spanner</a></span>(
+    <span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"dates and times"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>, <span class='no'>time</span>, <span class='no'>datetime</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>weight</span> <span class='kw'>=</span> <span class='st'>"bold"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_column_spanners</span>(<span class='kw'>spanners</span> <span class='kw'>=</span> <span class='st'>"dates and times"</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+   </div>
+
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+
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+</html>
+
+
diff --git a/docs/reference/cells_data.html b/docs/reference/cells_data.html
new file mode 100644
index 000000000..2ef2e97e0
--- /dev/null
+++ b/docs/reference/cells_data.html
@@ -0,0 +1,191 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Location helper for targeting data cells in the table body (deprecated) — cells_data • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
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+    <div class="page-header">
+    <h1>Location helper for targeting data cells in the table body (deprecated)</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_data.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Location helper for targeting data cells in the table body (deprecated)</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_data</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>columns</th>
+      <td><p>The names of the columns that are to be targeted.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>The names of the rows that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+
+  </div>
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diff --git a/docs/reference/cells_grand_summary.html b/docs/reference/cells_grand_summary.html
new file mode 100644
index 000000000..b393f91df
--- /dev/null
+++ b/docs/reference/cells_grand_summary.html
@@ -0,0 +1,294 @@
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+<meta property="og:description" content="The cells_grand_summary() function is used to target the cells in a grand
+summary and it is useful when applying a footnote with tab_footnote() or
+adding custom styles with tab_style(). The function is expressly used in
+each of those functions' locations argument." />
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+
+      
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting cells in a grand summary</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_grand_summary.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_grand_summary()</code> function is used to target the cells in a grand
+summary and it is useful when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or
+adding custom styles with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in
+each of those functions' <code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_grand_summary</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>columns</th>
+      <td><p>The names of the columns that are to be targeted.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>The names of the rows that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_summary</code> and <code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code>cells_grand_summary()</code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_grand_summary_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-13</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table; add</span>
+<span class='co'># some styling to a grand summary cell with</span>
+<span class='co'># with `tab_style()` and `cells_grand_summary()`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Spain"</span>,
+    <span class='no'>year</span> <span class='kw'>&lt;</span> <span class='fl'>1970</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"country"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"year"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>change</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>) - <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>)
+    ),
+    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>)
+    ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_grand_summary</span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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+</div>
+
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+</div>
+
+      </footer>
+   </div>
+
+  
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+
+  </body>
+</html>
+
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diff --git a/docs/reference/cells_group.html b/docs/reference/cells_group.html
new file mode 100644
index 000000000..3e3ec301f
--- /dev/null
+++ b/docs/reference/cells_group.html
@@ -0,0 +1,187 @@
+<!-- Generated by pkgdown: do not edit by hand -->
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+<title>Location helper for targeting row groups (deprecated) — cells_group • gt</title>
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting row groups (deprecated)</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_group.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Location helper for targeting row groups (deprecated)</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_group</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>groups</th>
+      <td><p>The names of the row groups that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+
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+</div>
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diff --git a/docs/reference/cells_row_groups.html b/docs/reference/cells_row_groups.html
new file mode 100644
index 000000000..57dfd7e36
--- /dev/null
+++ b/docs/reference/cells_row_groups.html
@@ -0,0 +1,287 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Location helper for targeting row groups — cells_row_groups • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
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+
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+<meta property="og:title" content="Location helper for targeting row groups — cells_row_groups" />
+<meta property="og:description" content="The cells_row_groups() function is used to target the table's row groups
+when applying a footnote with tab_footnote() or adding custom style with
+tab_style(). The function is expressly used in each of those functions'
+locations argument." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+     
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+      
+    </div><!--/.nav-collapse -->
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting row groups</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_row_groups.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_row_groups()</code> function is used to target the table's row groups
+when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with
+<code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those functions'
+<code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_row_groups</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>groups</th>
+      <td><p>The names of the row groups that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_row_groups</code> and
+<code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code>cells_row_groups()</code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_row_groups_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-9</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `pizzaplace` to create a gt table</span>
+<span class='co'># with grouped data; add a summary with the</span>
+<span class='co'># `summary_rows()` function and then add a</span>
+<span class='co'># footnote to the "peppr_salami" row group</span>
+<span class='co'># label with `tab_footnote()` and with</span>
+<span class='co'># `cells_row_groups()` in `locations`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>name</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"soppressata"</span>, <span class='st'>"peppr_salami"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>name</span>, <span class='no'>size</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(
+    <span class='kw'>`Pizzas Sold`</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>()
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"size"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='st'>"Pizzas Sold"</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>TOTAL</span> <span class='kw'>=</span> <span class='st'>"sum"</span>),
+    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>,
+    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"The Pepper-Salami."</span>,
+    <span class='fu'>cells_row_groups</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"peppr_salami"</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
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diff --git a/docs/reference/cells_stub.html b/docs/reference/cells_stub.html
new file mode 100644
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@@ -0,0 +1,283 @@
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+<title>Location helper for targeting cells in the table stub — cells_stub • gt</title>
+
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+<meta property="og:description" content="The cells_stub() function is used to target the table's stub cells and it
+is useful when applying a footnote with tab_footnote() or adding a custom
+style with tab_style(). The function is expressly used in each of those
+functions' locations argument." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+      
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting cells in the table stub</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_stub.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_stub()</code> function is used to target the table's stub cells and it
+is useful when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding a custom
+style with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those
+functions' <code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_stub</span>(<span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>rows</th>
+      <td><p>The names of the rows that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_stub</code> and <code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code>cells_stub()</code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_stub_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-10</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>tidyr</span>)
+
+<span class='co'># Use `sza` to create a gt table; color</span>
+<span class='co'># all of the `month` values in the table</span>
+<span class='co'># stub with `tab_style()`, using `cells_stub()`</span>
+<span class='co'># in `locations` (`rows = TRUE` targets</span>
+<span class='co'># all stub rows)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>20</span> <span class='kw'>&amp;</span> <span class='no'>tst</span> <span class='kw'>&lt;=</span> <span class='st'>"1000"</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(!<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>sza</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>tidyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://tidyr.tidyverse.org/reference/spread.html'>spread</a></span>(<span class='kw'>key</span> <span class='kw'>=</span> <span class='st'>"tst"</span>, <span class='kw'>value</span> <span class='kw'>=</span> <span class='no'>sza</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"month"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_missing.html'>fmt_missing</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>""</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"darkblue"</span>),
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"white"</span>)
+      ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_stub</span>(<span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
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+</html>
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diff --git a/docs/reference/cells_stubhead.html b/docs/reference/cells_stubhead.html
new file mode 100644
index 000000000..3a64270dd
--- /dev/null
+++ b/docs/reference/cells_stubhead.html
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+<meta property="og:description" content="The cells_stubhead() function is used to target the table stubhead location
+when applying a footnote with tab_footnote() or adding custom style with
+tab_style(). The function is expressly used in each of those functions'
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+
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting the table stubhead cell</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_stubhead.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_stubhead()</code> function is used to target the table stubhead location
+when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with
+<code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those functions'
+<code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_stubhead</span>()</pre>
+
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_stubhead</code> and <code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code>cells_stubhead()</code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_stubhead_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-6</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `pizzaplace` to create a gt table;</span>
+<span class='co'># add a stubhead label and then style it</span>
+<span class='co'># with `tab_style()` and `cells_stubhead()`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>month</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='no'>date</span>, <span class='fl'>6</span>, <span class='fl'>7</span>))) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>month</span>, <span class='no'>type</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(<span class='kw'>sold</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>()) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>ungroup</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>month</span> <span class='kw'>%in%</span> <span class='fl'>1</span>:<span class='fl'>2</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"type"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_stubhead.html'>tab_stubhead</a></span>(<span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"type"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_stubhead</span>()
+  )</div></pre>
+  </div>
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diff --git a/docs/reference/cells_summary.html b/docs/reference/cells_summary.html
new file mode 100644
index 000000000..a5cfe03f3
--- /dev/null
+++ b/docs/reference/cells_summary.html
@@ -0,0 +1,315 @@
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+and it is useful when applying a footnote with tab_footnote() or adding a
+custom style with tab_style(). The function is expressly used in each of
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+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting group summary cells</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_summary.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_summary()</code> function is used to target the cells in a group summary
+and it is useful when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding a
+custom style with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of
+those functions' <code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_summary</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>groups</th>
+      <td><p>The names of the groups that the summary rows reside in.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The names of the columns that are to be targeted.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>The names of the rows that are to be targeted.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object with the classes <code>cells_summary</code> and <code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code>cells_summary()</code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_summary_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-12</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table; add</span>
+<span class='co'># some styling to the summary data cells with</span>
+<span class='co'># with `tab_style()`, using `cells_summary()`</span>
+<span class='co'># in `locations`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Japan"</span>,
+    <span class='no'>year</span> <span class='kw'>&lt;</span> <span class='fl'>1970</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"country"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
+    <span class='kw'>decade</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='no'>year</span>, <span class='fl'>1</span>, <span class='fl'>3</span>), <span class='st'>"0s"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>decade</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(
+    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"year"</span>,
+    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"decade"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"1960s"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='st'>"min"</span>, <span class='st'>"max"</span>),
+    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>)
+      ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_summary</span>(
+      <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"1960s"</span>,
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightgreen"</span>)
+      ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_summary</span>(
+      <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"1960s"</span>,
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>2</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/cells_title.html b/docs/reference/cells_title.html
new file mode 100644
index 000000000..09db0a020
--- /dev/null
+++ b/docs/reference/cells_title.html
@@ -0,0 +1,279 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Location helper for targeting the table title and subtitle — cells_title • gt</title>
+
+<!-- favicons -->
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+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+
+
+<meta property="og:title" content="Location helper for targeting the table title and subtitle — cells_title" />
+<meta property="og:description" content="The cells_title() function is used to target the table title or subtitle
+when applying a footnote with tab_footnote() or adding custom style with
+tab_style(). The function is expressly used in each of those functions'
+locations argument." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Location helper for targeting the table title and subtitle</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>cells_title.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cells_title()</code> function is used to target the table title or subtitle
+when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with
+<code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those functions'
+<code>locations</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cells_title</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"title"</span>, <span class='st'>"subtitle"</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>groups</th>
+      <td><p>We can either specify <code>"title"</code> or <code>"subtitle"</code> to target the
+title element or the subtitle element.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object of classes <code>cells_title</code> and <code>location_cells</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When using any of the location helper functions with an appropriate function
+that has a <code>locations</code> argument, multiple locations can be targeted by
+enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
+helper functions can be used to target cells (roughly in order from the top
+to the bottom of a table):</p><ul>
+<li><p><code>cells_title()</code>: targets the table title or the table subtitle
+depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
+<code>"subtitle"</code>).</p></li>
+<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
+only available when there is a stub; a label in that location can be created
+by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
+<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
+appear above the column labels.</p></li>
+<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
+<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
+groups using the <code>groups</code> argument.</p></li>
+<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
+argument.</p></li>
+<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
+intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
+<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
+<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
+using intersections of <code>columns</code> and <code>rows</code></p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cells_title_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table; add</span>
+<span class='co'># a header with a title, and then add a</span>
+<span class='co'># footnote to the title with `tab_footnote()`</span>
+<span class='co'># and `cells_title()` (in `locations`)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
+      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-10"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
+    -<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='no'>adj_close</span>, <span class='no'>volume</span>, <span class='no'>high</span>, <span class='no'>low</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(<span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"S&amp;P 500"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"All values in USD."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_title</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"title"</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+
+  </body>
+</html>
+
+
diff --git a/docs/reference/cols_align.html b/docs/reference/cols_align.html
new file mode 100644
index 000000000..f85ee09dd
--- /dev/null
+++ b/docs/reference/cols_align.html
@@ -0,0 +1,255 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Set the alignment of columns — cols_align • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
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+
+<!-- headroom.js -->
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+
+<meta property="og:title" content="Set the alignment of columns — cols_align" />
+<meta property="og:description" content="The individual alignments of columns (which includes the column labels and
+all of their data cells) can be modified. We have the option to align text to
+the left, the center, and the right. In a less explicit manner, we can
+allow gt to automatically choose the alignment of each column based on
+the data type (with the auto option)." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
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+
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+
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+    <div class="container template-reference-topic">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
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+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
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+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
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+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+</li>
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+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Set the alignment of columns</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_align.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The individual alignments of columns (which includes the column labels and
+all of their data cells) can be modified. We have the option to align text to
+the <code>left</code>, the <code>center</code>, and the <code>right</code>. In a less explicit manner, we can
+allow <strong>gt</strong> to automatically choose the alignment of each column based on
+the data type (with the <code>auto</code> option).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_align</span>(<span class='no'>data</span>, <span class='kw'>align</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"auto"</span>, <span class='st'>"left"</span>, <span class='st'>"center"</span>, <span class='st'>"right"</span>), <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>align</th>
+      <td><p>The alignment type. This can be any of <code>"center"</code>, <code>"left"</code>, or
+<code>"right"</code> for center-, left-, or center-alignment. Alternatively, the
+<code>"auto"</code> option (the default), will automatically align values in columns
+according to the data type (see the Details section for specifics on which
+alignments are applied).</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>An optional vector of column names for which the alignment
+should be applied. If nothing is supplied, or if <code>columns</code> is <code>TRUE</code>, then
+the chosen alignment affects all columns.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>When you create a <strong>gt</strong> table object using <code><a href='gt.html'>gt()</a></code>, automatic alignment of
+column labels and their data cells is performed. By default, left-alignment
+is applied to columns of class <code>character</code>, <code>Date</code>, or <code>POSIXct</code>;
+center-alignment is for columns of class <code>logical</code>, <code>factor</code>, or <code>list</code>; and
+right-alignment is used for the <code>numeric</code> and <code>integer</code> columns.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_align_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># align the `population` column data to</span>
+<span class='co'># the left</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_align</span>(
+    <span class='kw'>align</span> <span class='kw'>=</span> <span class='st'>"left"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+   </div>
+
+  
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+
+  </body>
+</html>
+
+
diff --git a/docs/reference/cols_hide.html b/docs/reference/cols_hide.html
new file mode 100644
index 000000000..12dade009
--- /dev/null
+++ b/docs/reference/cols_hide.html
@@ -0,0 +1,270 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Hide one or more columns — cols_hide • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
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+<meta property="og:title" content="Hide one or more columns — cols_hide" />
+<meta property="og:description" content="The cols_hide() function allows us to hide one or more columns from
+appearing in the final output table. While it's possible and often desirable
+to omit columns from the input table data before introduction to the gt()
+function, there can be cases where the data in certain columns is useful (as
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+
+      
+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Hide one or more columns</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_hide.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cols_hide()</code> function allows us to hide one or more columns from
+appearing in the final output table. While it's possible and often desirable
+to omit columns from the input table data before introduction to the <code><a href='gt.html'>gt()</a></code>
+function, there can be cases where the data in certain columns is useful (as
+a column reference during formatting of other columns) but the final display
+of those columns is not necessary.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_hide</span>(<span class='no'>data</span>, <span class='no'>columns</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The column names to hide from the output display table. The
+order of the remaining columns will be preserved. Values provided that do
+not correspond to column names will be disregarded.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The hiding of columns is internally a rendering directive, so, all columns
+that are 'hidden' are still accessible and useful in any expression provided
+to a <code>rows</code> argument. Furthermore, the <code>cols_hide()</code> function (as with many
+<strong>gt</strong> functions) can be placed anywhere in a pipeline of <strong>gt</strong> function
+calls (acting as a promise to hide columns when the timing is right). However
+there's perhaps greater readability when placing this call closer to the end
+of such a pipeline.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_hide_1.png' width=100% /></p>
+<p><img src='figures/man_cols_hide_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-7</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># Hide the columns `country_code_2` and</span>
+<span class='co'># `country_code_3`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_hide</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(
+      <span class='no'>country_code_2</span>, <span class='no'>country_code_3</span>)
+  )
+
+<span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># Use the `population` column to provide</span>
+<span class='co'># the conditional placement of footnotes,</span>
+<span class='co'># then hide that column and one other</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_hide</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>country_code_3</span>, <span class='no'>population</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Population above 3,000,000."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>population</span> <span class='kw'>&gt;</span> <span class='fl'>3000000</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cols_label.html b/docs/reference/cols_label.html
new file mode 100644
index 000000000..8f6049cc7
--- /dev/null
+++ b/docs/reference/cols_label.html
@@ -0,0 +1,279 @@
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+<meta property="og:description" content="Column labels can be modified from their default values (the names of the
+columns from the input table data). When you create a gt table object
+using gt(), column names effectively become the column labels. While this
+serves as a good first approximation, column names aren't often appealing as
+column labels in a gt output table. The cols_label() function
+provides the flexibility to relabel one or more columns and we even have the
+option to use the md() or html() helper functions for rendering column
+labels from Markdown or using HTML." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+
+      
+
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Relabel one or more columns</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_label.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Column labels can be modified from their default values (the names of the
+columns from the input table data). When you create a <strong>gt</strong> table object
+using <code><a href='gt.html'>gt()</a></code>, column names effectively become the column labels. While this
+serves as a good first approximation, column names aren't often appealing as
+column labels in a <strong>gt</strong> output table. The <code>cols_label()</code> function
+provides the flexibility to relabel one or more columns and we even have the
+option to use the <code><a href='md.html'>md()</a></code> or <code><a href='html.html'>html()</a></code> helper functions for rendering column
+labels from Markdown or using HTML.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_label</span>(<span class='no'>data</span>, <span class='no'>...</span>, <span class='kw'>.list</span> <span class='kw'>=</span> <span class='fu'>list2</span>(<span class='no'>...</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>One or more named arguments of column names from the input <code>data</code>
+table along with their labels for display as the column labels. We can
+optionally wrap the column labels with <code><a href='md.html'>md()</a></code> (to interpret text as
+Markdown) or <code><a href='html.html'>html()</a></code> (to interpret text as HTML).</p></td>
+    </tr>
+    <tr>
+      <th>.list</th>
+      <td><p>Allows for the use of a list as an input alternative to <code>...</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>It's important to note that while columns can be freely relabeled, we
+continue to refer to columns by their original column names. Column names in
+a tibble or data frame must be unique whereas column labels in <strong>gt</strong> have
+no requirement for uniqueness (which is useful for labeling columns as, say,
+measurement units that may be repeated several times---usually under
+different spanner column labels). Thus, we can still easily distinguish
+between columns in other <strong>gt</strong> function calls (e.g., in all of the
+<code>fmt*()</code> functions) even though we may lose distinguishability in column
+labels once they have been relabeled.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_label_1.png' width=100% /></p>
+<p><img src='figures/man_cols_label_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># label all the table's columns to</span>
+<span class='co'># present better</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_label</span>(
+    <span class='kw'>country_name</span> <span class='kw'>=</span> <span class='st'>"Name"</span>,
+    <span class='kw'>year</span> <span class='kw'>=</span> <span class='st'>"Year"</span>,
+    <span class='kw'>population</span> <span class='kw'>=</span> <span class='st'>"Population"</span>
+  )
+
+<span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># label columns as before but make them</span>
+<span class='co'># bold with markdown formatting</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_label</span>(
+    <span class='kw'>country_name</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"**Name**"</span>),
+    <span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"**Year**"</span>),
+    <span class='kw'>population</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"**Population**"</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cols_merge.html b/docs/reference/cols_merge.html
new file mode 100644
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+++ b/docs/reference/cols_merge.html
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+<title>Merge data from two or more columns to a single column — cols_merge • gt</title>
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+<meta property="og:title" content="Merge data from two or more columns to a single column — cols_merge" />
+<meta property="og:description" content="This function takes input from two or more columns and allows the contents to
+be merged them into a single column, using a pattern that specifies the
+formatting. We can specify which columns to merge together in the columns
+argument. The string-combining pattern is given in the pattern argument.
+The first column in the columns series operates as the target column (i.e.,
+will undergo mutation) whereas all following columns will be untouched.
+There is the option to hide the non-target columns (i.e., second and
+subsequent columns given in columns)." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Merge data from two or more columns to a single column</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_merge.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This function takes input from two or more columns and allows the contents to
+be merged them into a single column, using a pattern that specifies the
+formatting. We can specify which columns to merge together in the <code>columns</code>
+argument. The string-combining pattern is given in the <code>pattern</code> argument.
+The first column in the <code>columns</code> series operates as the target column (i.e.,
+will undergo mutation) whereas all following <code>columns</code> will be untouched.
+There is the option to hide the non-target columns (i.e., second and
+subsequent columns given in <code>columns</code>).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_merge</span>(
+  <span class='no'>data</span>,
+  <span class='no'>columns</span>,
+  <span class='kw'>hide_columns</span> <span class='kw'>=</span> <span class='no'>columns</span>[-<span class='fl'>1</span>],
+  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='st'>"{"</span>, <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq_along</a></span>(<span class='no'>columns</span>), <span class='st'>"}"</span>, <span class='kw'>collapse</span> <span class='kw'>=</span> <span class='st'>" "</span>)
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns that will participate in the merging process. The
+first column name provided will be the target column (i.e., undergo
+mutation) and the other columns will serve to provide input.</p></td>
+    </tr>
+    <tr>
+      <th>hide_columns</th>
+      <td><p>Any column names provided here will have their state
+changed to <code>hidden</code> (via internal use of <code><a href='cols_hide.html'>cols_hide()</a></code> if they aren't
+already hidden. This is convenient if the shared purpose of these specified
+columns is only to provide string input to the target column.</p></td>
+    </tr>
+    <tr>
+      <th>pattern</th>
+      <td><p>A formatting pattern that specifies the arrangement of the
+<code>column</code> values and any string literals. We need to use column numbers
+(corresponding to the position of columns provided in <code>columns</code>) within the
+pattern. These indices are to be placed in curly braces (e.g., <code>{1}</code>). All
+characters outside of braces are taken to be string literals.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>There are two other column-merging functions that offer specialized behavior
+that is optimized for common table tasks: <code><a href='cols_merge_range.html'>cols_merge_range()</a></code> and
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert()</a></code>. These functions operate similarly, where the
+non-target columns can be optionally hidden from the output table through the
+<code>autohide</code> option.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_merge_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-10</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table;</span>
+<span class='co'># merge the `open` &amp; `close` columns</span>
+<span class='co'># together, and, the `low` &amp; `high`</span>
+<span class='co'># columns (putting an em dash between</span>
+<span class='co'># both); rename the columns</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>50</span>:<span class='fl'>55</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>volume</span>, -<span class='no'>adj_close</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_merge</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>close</span>),
+    <span class='kw'>hide_columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>close</span>),
+    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{1}&amp;mdash;{2}"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_merge</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>low</span>, <span class='no'>high</span>),
+    <span class='kw'>hide_columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>high</span>),
+    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{1}&amp;mdash;{2}"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(
+    <span class='kw'>open</span> <span class='kw'>=</span> <span class='st'>"open/close"</span>,
+    <span class='kw'>low</span> <span class='kw'>=</span> <span class='st'>"low/high"</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/cols_merge_range.html b/docs/reference/cols_merge_range.html
new file mode 100644
index 000000000..3ce796ac9
--- /dev/null
+++ b/docs/reference/cols_merge_range.html
@@ -0,0 +1,286 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Merge two columns to a value range column — cols_merge_range • gt</title>
+
+<!-- favicons -->
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+<meta property="og:description" content="The cols_merge_range() function is a specialized variant of the
+cols_merge() function. It operates by taking a two columns that constitute
+a range of values (col_begin and col_end) and merges them into a single
+column. What results is a column containing both values separated by a long
+dash (e.g., 12.0 — 20.0). The column specified in col_end is dropped from
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+    <div class="page-header">
+    <h1>Merge two columns to a value range column</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_merge_range.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cols_merge_range()</code> function is a specialized variant of the
+<code><a href='cols_merge.html'>cols_merge()</a></code> function. It operates by taking a two columns that constitute
+a range of values (<code>col_begin</code> and <code>col_end</code>) and merges them into a single
+column. What results is a column containing both values separated by a long
+dash (e.g., <code>12.0 — 20.0</code>). The column specified in <code>col_end</code> is dropped from
+the output table.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_merge_range</span>(<span class='no'>data</span>, <span class='no'>col_begin</span>, <span class='no'>col_end</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>"--"</span>, <span class='kw'>autohide</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>col_begin</th>
+      <td><p>A column that contains values for the start of the range.</p></td>
+    </tr>
+    <tr>
+      <th>col_end</th>
+      <td><p>A column that contains values for the end of the range.</p></td>
+    </tr>
+    <tr>
+      <th>sep</th>
+      <td><p>The separator text that indicates the values are ranged. The
+default value of <code>"--"</code> indicates that an en dash will be used for the
+range separator. Using <code>"---"</code> will be taken to mean that an em dash should
+be used. Should you want these special symbols to be taken literally, they
+can be supplied within the base <code><a href='https://rdrr.io/r/base/AsIs.html'>I()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>autohide</th>
+      <td><p>An option to automatically hide the column specified as
+<code>col_end</code>. Any columns with their state changed to hidden will behave
+the same as before, they just won't be displayed in the finalized table.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>This function could be somewhat replicated using <code><a href='cols_merge.html'>cols_merge()</a></code>, however,
+<code>cols_merge_range()</code> employs the following specialized operations for <code>NA</code>
+handling:</p>
+<ol>
+<li><p><code>NA</code>s in <code>col_begin</code> (but not <code>col_end</code>) result in a display of only</p></li>
+<li><p><code>NA</code>s in <code>col_end</code> (but not <code>col_begin</code>) result in a display of only
+the <code>col_begin</code> values only for the merged column (this is the converse of
+the previous)</p></li>
+<li><p><code>NA</code>s both in <code>col_begin</code> and <code>col_end</code> result in missing values for
+the merged column</p></li>
+</ol>
+
+<p>Any resulting <code>NA</code> values in the <code>col_begin</code> column following the merge
+operation can be easily formatted using the <code><a href='fmt_missing.html'>fmt_missing()</a></code> function.
+Separate calls of <code><a href='fmt_missing.html'>fmt_missing()</a></code> can be used for the <code>col_begin</code> and
+<code>col_end</code> columns for finer control of the replacement values.</p>
+<p>This function is part of a set of three column-merging functions. The other
+two are the general <code><a href='cols_merge.html'>cols_merge()</a></code> function and the specialized
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert()</a></code> function. These functions operate similarly, where the
+non-target columns can be optionally hidden from the output table through the
+<code>hide_columns</code> or <code>autohide</code> options.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_merge_range_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-9</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table,</span>
+<span class='co'># keeping only the `model`, `mpg_c`,</span>
+<span class='co'># and `mpg_h` columns; merge the mpg</span>
+<span class='co'># columns together as a single range</span>
+<span class='co'># column (which is labeled as MPG,</span>
+<span class='co'># in italics)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with</a></span>(<span class='st'>"mpg"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_merge_range</span>(
+    <span class='kw'>col_begin</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>mpg_c</span>),
+    <span class='kw'>col_end</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>mpg_h</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(
+    <span class='kw'>mpg_c</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"*MPG*"</span>)
+  )</div></pre>
+  </div>
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new file mode 100644
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+<meta property="og:description" content="The cols_merge_uncert() function is a specialized variant of the
+cols_merge() function. It operates by taking a base value column
+(col_val) and an uncertainty column (col_uncert) and merges them into a
+single column. What results is a column with values and associated
+uncertainties (e.g., 12.0 ± 0.1), and, the column specified in col_uncert
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+    <div class="page-header">
+    <h1>Merge two columns to a value &amp; uncertainty column</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_merge_uncert.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>cols_merge_uncert()</code> function is a specialized variant of the
+<code><a href='cols_merge.html'>cols_merge()</a></code> function. It operates by taking a base value column
+(<code>col_val</code>) and an uncertainty column (<code>col_uncert</code>) and merges them into a
+single column. What results is a column with values and associated
+uncertainties (e.g., <code>12.0 ± 0.1</code>), and, the column specified in <code>col_uncert</code>
+is dropped from the output table.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_merge_uncert</span>(<span class='no'>data</span>, <span class='no'>col_val</span>, <span class='no'>col_uncert</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" +/- "</span>, <span class='kw'>autohide</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>col_val</th>
+      <td><p>A single column name that contains the base values. This is
+the column where values will be mutated.</p></td>
+    </tr>
+    <tr>
+      <th>col_uncert</th>
+      <td><p>A single column name that contains the uncertainty values.
+These values will be combined with those in <code>col_val</code>. We have the option
+to automatically hide the <code>col_uncert</code> column through <code>autohide</code>.</p></td>
+    </tr>
+    <tr>
+      <th>sep</th>
+      <td><p>The separator text that contains the uncertainty mark. The
+default value of <code>" +/- "</code> indicates that an appropriate plus/minus mark
+will be used depending on the output context. Should you want this special
+symbol to be taken literally, it can be supplied within the base <code><a href='https://rdrr.io/r/base/AsIs.html'>I()</a></code>
+function.</p></td>
+    </tr>
+    <tr>
+      <th>autohide</th>
+      <td><p>An option to automatically hide the column specified as
+<code>col_uncert</code>. Any columns with their state changed to hidden will behave
+the same as before, they just won't be displayed in the finalized table.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>This function could be somewhat replicated using <code><a href='cols_merge.html'>cols_merge()</a></code>, however,
+<code>cols_merge_uncert()</code> employs the following specialized semantics for <code>NA</code>
+handling:</p>
+<ol>
+<li><p><code>NA</code>s in <code>col_val</code> result in missing values for the merged
+column (e.g., <code>NA</code> + <code>0.1</code> = <code>NA</code>)</p></li>
+<li><p><code>NA</code>s in <code>col_uncert</code> (but not <code>col_val</code>) result in
+base values only for the merged column (e.g.,
+<code>12.0</code> + <code>NA</code> = <code>12.0</code>)</p></li>
+<li><p><code>NA</code>s both <code>col_val</code> and <code>col_uncert</code> result in
+missing values for the merged column (e.g., <code>NA</code> + <code>NA</code> =
+<code>NA</code>)</p></li>
+</ol>
+
+<p>Any resulting <code>NA</code> values in the <code>col_val</code> column following the merge
+operation can be easily formatted using the <code><a href='fmt_missing.html'>fmt_missing()</a></code> function.</p>
+<p>This function is part of a set of three column-merging functions. The other
+two are the general <code><a href='cols_merge.html'>cols_merge()</a></code> function and the specialized
+<code><a href='cols_merge_range.html'>cols_merge_range()</a></code> function. These functions operate similarly, where the
+non-target columns can be optionally hidden from the output table through the
+<code>hide_columns</code> or <code>autohide</code> options.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_merge_uncert_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-8</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table,</span>
+<span class='co'># keeping only the `currency` and `num`</span>
+<span class='co'># columns; merge columns into one with</span>
+<span class='co'># a base value and uncertainty (after</span>
+<span class='co'># formatting the `num` column)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>currency</span>, <span class='no'>num</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>7</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>3</span>,
+    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_merge_uncert</span>(
+    <span class='kw'>col_val</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>col_uncert</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(
+    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"value + uncert."</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
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+   </div>
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+  </body>
+</html>
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+
diff --git a/docs/reference/cols_move.html b/docs/reference/cols_move.html
new file mode 100644
index 000000000..7a54a73ae
--- /dev/null
+++ b/docs/reference/cols_move.html
@@ -0,0 +1,258 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
+<title>Move one or more columns — cols_move • gt</title>
+
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+
+<meta property="og:title" content="Move one or more columns — cols_move" />
+<meta property="og:description" content="On those occasions where you need to move columns this way or that way, we
+can make use of the cols_move() function. While it's true that the movement
+of columns can be done upstream of gt, it is much easier and less error
+prone to use the function provided here. The movement procedure here takes
+one or more specified columns (in the columns argument) and places them to
+the right of a different column (the after argument). The ordering of the
+columns to be moved is preserved, as is the ordering of all other columns
+in the table." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
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+
+      
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Move one or more columns</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_move.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>On those occasions where you need to move columns this way or that way, we
+can make use of the <code>cols_move()</code> function. While it's true that the movement
+of columns can be done upstream of <strong>gt</strong>, it is much easier and less error
+prone to use the function provided here. The movement procedure here takes
+one or more specified columns (in the <code>columns</code> argument) and places them to
+the right of a different column (the <code>after</code> argument). The ordering of the
+<code>columns</code> to be moved is preserved, as is the ordering of all other columns
+in the table.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_move</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='no'>after</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The column names to move to as a group to a different
+position. The order of the remaining columns will be preserved.</p></td>
+    </tr>
+    <tr>
+      <th>after</th>
+      <td><p>A column name used to anchor the insertion of the moved columns.
+All of the moved columns will be placed to the right of this column.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The columns supplied in <code>columns</code> must all exist in the table and none of
+them can be in the <code>after</code> argument. The <code>after</code> column must also exist and
+only one column should be provided here. If you need to place one or columns
+at the beginning of the column series, the <code><a href='cols_move_to_start.html'>cols_move_to_start()</a></code> function
+should be used. Similarly, if those columns to move should be placed at the
+end of the column series then use <code><a href='cols_move_to_end.html'>cols_move_to_end()</a></code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_move_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-6</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># With the remaining columns, position</span>
+<span class='co'># `population` after `country_name`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_move</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+    <span class='kw'>after</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>country_name</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
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+
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+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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diff --git a/docs/reference/cols_move_to_end.html b/docs/reference/cols_move_to_end.html
new file mode 100644
index 000000000..dfc8db1f9
--- /dev/null
+++ b/docs/reference/cols_move_to_end.html
@@ -0,0 +1,260 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Move one or more columns to the end — cols_move_to_end • gt</title>
+
+<!-- favicons -->
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+<meta property="og:description" content="It's possible to move a set of columns to the end of the column series, we
+only need to specify which columns are to be moved. While this can be done
+upstream of gt, this function makes to process much easier and it's less
+error prone. The ordering of the columns that are moved to the end is
+preserved (same with the ordering of all other columns in the table)." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Move one or more columns to the end</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_move_to_end.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>It's possible to move a set of columns to the end of the column series, we
+only need to specify which <code>columns</code> are to be moved. While this can be done
+upstream of <strong>gt</strong>, this function makes to process much easier and it's less
+error prone. The ordering of the <code>columns</code> that are moved to the end is
+preserved (same with the ordering of all other columns in the table).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_move_to_end</span>(<span class='no'>data</span>, <span class='no'>columns</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The column names to move to the right-most side of the table.
+The order in which columns are provided will be preserved (as is the case
+with the remaining columns).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The columns supplied in <code>columns</code> must all exist in the table. If you need to
+place one or columns at the start of the column series, the
+<code><a href='cols_move_to_start.html'>cols_move_to_start()</a></code> function should be used. More control is offered with
+the <code><a href='cols_move.html'>cols_move()</a></code> function, where columns could be placed after a specific
+column.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_move_to_end_1.png' width=100% /></p>
+<p><img src='figures/man_cols_move_to_end_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># With the remaining columns, move the</span>
+<span class='co'># `year` column to the end</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_move_to_end</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>)
+  )
+
+<span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># With the remaining columns, move `year`</span>
+<span class='co'># and `country_name` to the end</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_move_to_end</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>, <span class='no'>country_name</span>)
+  )</div></pre>
+  </div>
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diff --git a/docs/reference/cols_move_to_start.html b/docs/reference/cols_move_to_start.html
new file mode 100644
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@@ -0,0 +1,262 @@
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+<meta property="og:description" content="We can easily move set of columns to the beginning of the column series and
+we only need to specify which columns. It's possible to do this upstream of
+gt, however, it is easier with this function and it presents less
+possibility for error. The ordering of the columns that are moved to the
+start is preserved (same with the ordering of all other columns in the
+table)." />
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+
+      
+
+      </header>
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Move one or more columns to the start</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_move_to_start.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>We can easily move set of columns to the beginning of the column series and
+we only need to specify which <code>columns</code>. It's possible to do this upstream of
+<strong>gt</strong>, however, it is easier with this function and it presents less
+possibility for error. The ordering of the <code>columns</code> that are moved to the
+start is preserved (same with the ordering of all other columns in the
+table).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_move_to_start</span>(<span class='no'>data</span>, <span class='no'>columns</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The column names to move to the left-most side of the table.
+The order in which columns are provided will be preserved (as is the case
+with the remaining columns).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The columns supplied in <code>columns</code> must all exist in the table. If you need to
+place one or columns at the end of the column series, the
+<code><a href='cols_move_to_end.html'>cols_move_to_end()</a></code> function should be used. More control is offered with
+the <code><a href='cols_move.html'>cols_move()</a></code> function, where columns could be placed after a specific
+column.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_move_to_start_1.png' width=100% /></p>
+<p><img src='figures/man_cols_move_to_start_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code>,
+<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># With the remaining columns, move the</span>
+<span class='co'># `year` column to the start</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_move_to_start</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>)
+  )
+
+<span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># With the remaining columns, move `year`</span>
+<span class='co'># and `population` to the start</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_move_to_start</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>, <span class='no'>population</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/cols_width.html b/docs/reference/cols_width.html
new file mode 100644
index 000000000..fe056238b
--- /dev/null
+++ b/docs/reference/cols_width.html
@@ -0,0 +1,269 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
+<title>Set the widths of columns — cols_width • gt</title>
+
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+<meta property="og:title" content="Set the widths of columns — cols_width" />
+<meta property="og:description" content="Manual specifications of column widths can be performed using the
+cols_width() function. We choose which columns get specific widths (in
+pixels, usually by use of the px() helper function). Width assignments are
+supplied in ... through two-sided formulas, where the left-hand side
+defines the target columns and the right-hand side is a single width value in
+pixels." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+
+      
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Set the widths of columns</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
+    <div class="hidden name"><code>cols_width.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Manual specifications of column widths can be performed using the
+<code>cols_width()</code> function. We choose which columns get specific widths (in
+pixels, usually by use of the <code><a href='px.html'>px()</a></code> helper function). Width assignments are
+supplied in <code>...</code> through two-sided formulas, where the left-hand side
+defines the target columns and the right-hand side is a single width value in
+pixels.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>cols_width</span>(<span class='no'>data</span>, <span class='no'>...</span>, <span class='kw'>.list</span> <span class='kw'>=</span> <span class='fu'>list2</span>(<span class='no'>...</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>Expressions for the assignment of column widths for the table
+columns in <code>data</code>. Two-sided formulas (e.g, <code>&lt;LHS&gt; ~ &lt;RHS&gt;</code>) can be used,
+where the left-hand side corresponds to selections of columns and the
+right-hand side evaluates to single-length character values in the form
+<code>{##}px</code> (i.e., pixel dimensions); the <code><a href='px.html'>px()</a></code> helper function is best used
+for this purpose. Column names should be enclosed in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>. The
+column-based select helpers <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code> can be used in the LHS.
+Subsequent expressions that operate on the columns assigned previously will
+result in overwriting column width values (both in the same <code>cols_width()</code>
+call and across separate calls). All other columns can be assigned a
+default width value by using <code>TRUE</code> or <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code> on the left-hand
+side.</p></td>
+    </tr>
+    <tr>
+      <th>.list</th>
+      <td><p>Allows for the use of a list as an input alternative to <code>...</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Normally, column widths are automatically set to span across the width of the
+container (both table and container widths can be individually modified with
+the <code>table.width</code> and <code>container.width</code> options within <code><a href='tab_options.html'>tab_options()</a></code>). When
+using <code>cols_width()</code> though, the <code>table.width</code> option is disregarded in
+favor of the pixel values set for each column.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_cols_width_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>4-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Modify Columns: 
+<code><a href='cols_align.html'>cols_align</a>()</code>,
+<code><a href='cols_hide.html'>cols_hide</a>()</code>,
+<code><a href='cols_label.html'>cols_label</a>()</code>,
+<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
+<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
+<code><a href='cols_merge.html'>cols_merge</a>()</code>,
+<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
+<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
+<code><a href='cols_move.html'>cols_move</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># with named arguments in `...`, we</span>
+<span class='co'># can specify the exact widths for</span>
+<span class='co'># table columns (using `everything()`</span>
+<span class='co'># or `TRUE` at the end will capture</span>
+<span class='co'># all remaining columns)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
+    <span class='no'>num</span>, <span class='no'>char</span>, <span class='no'>date</span>,
+    <span class='no'>datetime</span>, <span class='no'>row</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>cols_width</span>(
+    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>) ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>150</span>),
+    <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with</a></span>(<span class='st'>"r"</span>) ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>100</span>),
+    <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with</a></span>(<span class='st'>"date"</span>) ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>200</span>),
+    <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>() ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>60</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/countrypops.html b/docs/reference/countrypops.html
new file mode 100644
index 000000000..5a52d2a44
--- /dev/null
+++ b/docs/reference/countrypops.html
@@ -0,0 +1,227 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Yearly populations of countries from 1960 to 2017 — countrypops • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
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+<meta property="og:description" content="A dataset that presents yearly, total populations of countries. Total
+population is based on counts of all residents regardless of legal status or
+citizenship. Country identifiers include the English-language country names,
+and the 2- and 3-letter ISO 3166-1 country codes. Each row contains a
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Yearly populations of countries from 1960 to 2017</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
+    <div class="hidden name"><code>countrypops.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>A dataset that presents yearly, total populations of countries. Total
+population is based on counts of all residents regardless of legal status or
+citizenship. Country identifiers include the English-language country names,
+and the 2- and 3-letter ISO 3166-1 country codes. Each row contains a
+<code>population</code> value for a given <code>year</code> (from 1960 to 2017). Any <code>NA</code> values
+for <code>populations</code> indicate the non-existence of the country during that year.</p>
+    </div>
+
+    <pre class="usage"><span class='no'>countrypops</span></pre>
+
+
+    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+
+    <p>A tibble with 12470 rows and 5 variables:</p><dl'>
+<dt>country_name</dt><dd><p>Name of the country</p></dd>
+<dt>country_code_2</dt><dd><p>The 2-letter ISO 3166-1 country code</p></dd>
+<dt>country_code_3</dt><dd><p>The 3-letter ISO 3166-1 country code</p></dd>
+<dt>year</dt><dd><p>The year for the population estimate</p></dd>
+<dt>population</dt><dd><p>The population estimate, midway through the year</p></dd>
+
+</dl>
+
+    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
+
+    <p><a href='https://data.worldbank.org/indicator/SP.POP.TOTL'>https://data.worldbank.org/indicator/SP.POP.TOTL</a></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>11-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Datasets: 
+<code><a href='exibble.html'>exibble</a></code>,
+<code><a href='gtcars.html'>gtcars</a></code>,
+<code><a href='pizzaplace.html'>pizzaplace</a></code>,
+<code><a href='sp500.html'>sp500</a></code>,
+<code><a href='sza.html'>sza</a></code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
+<span class='co'># available in `countrypops`</span>
+<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>countrypops</span>)</div><div class='output co'>#&gt; Rows: 12,470
+#&gt; Columns: 5
+#&gt; $ country_name   <span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "Aruba", "Aruba", "Aruba", "Aruba", "Aruba", "Aruba", …
+#&gt; $ country_code_2 </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", …
+#&gt; $ country_code_3 </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "ABW"…
+#&gt; $ year           </span><span style='color: #555555;font-style: italic;'>&lt;int&gt;</span><span> 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, …
+#&gt; $ population     </span><span style='color: #555555;font-style: italic;'>&lt;int&gt;</span><span> 54211, 55438, 56225, 56695, 57032, 57360, 57715, 58055…</div><div class='input'>
+</div></span></pre>
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diff --git a/docs/reference/currency.html b/docs/reference/currency.html
new file mode 100644
index 000000000..f9513ff4c
--- /dev/null
+++ b/docs/reference/currency.html
@@ -0,0 +1,267 @@
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+<meta property="og:title" content="Supply a custom currency symbol to <code>fmt_currency()</code> — currency" />
+<meta property="og:description" content="The currency() helper function makes it easy to specify a context-aware
+currency symbol to currency argument of fmt_currency(). Since gt can
+render tables to several output formats, currency() allows for different
+variations of the custom symbol based on the output context (which are
+html, latex, rtf, and default). The number of decimal places for
+the custom currency defaults to 2, however, a value set for the decimals
+argument of fmt_currency() will take precedence." />
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+    <h1>Supply a custom currency symbol to <code>fmt_currency()</code></h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>currency.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>currency()</code> helper function makes it easy to specify a context-aware
+currency symbol to <code>currency</code> argument of <code><a href='fmt_currency.html'>fmt_currency()</a></code>. Since <strong>gt</strong> can
+render tables to several output formats, <code>currency()</code> allows for different
+variations of the custom symbol based on the output context (which are
+<code>html</code>, <code>latex</code>, <code>rtf</code>, and <code>default</code>). The number of decimal places for
+the custom currency defaults to <code>2</code>, however, a value set for the <code>decimals</code>
+argument of <code><a href='fmt_currency.html'>fmt_currency()</a></code> will take precedence.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>currency</span>(<span class='no'>...</span>, <span class='kw'>.list</span> <span class='kw'>=</span> <span class='fu'>list2</span>(<span class='no'>...</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>...</th>
+      <td><p>One or more named arguments using output contexts as the names and
+currency symbol text as the values.</p></td>
+    </tr>
+    <tr>
+      <th>.list</th>
+      <td><p>Allows for the use of a list as an input alternative to <code>...</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list object of class <code>gt_currency</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>We can use any combination of <code>html</code>, <code>latex</code>, <code>rtf</code>, and <code>default</code> as named
+arguments for the currency text in each of the namesake contexts. The
+<code>default</code> value is used as a fallback when there doesn't exist a dedicated
+currency text value for a particular output context (e.g., when a table is
+rendered as HTML and we use <code>currency(latex = "LTC", default = "ltc")</code>, the
+currency symbol will be <code>"ltc"</code>. For convenience, if we provide only a single
+string without a name, it will be taken as the <code>default</code> (i.e.,
+<code>currency("ltc")</code> is equivalent to <code>currency(default = "ltc")</code>). However, if
+we were to specify currency strings for multiple output contexts, names are
+required each and every context.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_currency_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-14</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># format the `currency` column to have</span>
+<span class='co'># currency values in guilder (a defunct</span>
+<span class='co'># Dutch currency)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_currency.html'>fmt_currency</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='fu'>currency</span>(
+      <span class='kw'>html</span> <span class='kw'>=</span> <span class='st'>"&amp;fnof;"</span>,
+      <span class='kw'>default</span> <span class='kw'>=</span> <span class='st'>"f"</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>
+  )</div></pre>
+  </div>
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diff --git a/docs/reference/data_color.html b/docs/reference/data_color.html
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+<meta property="og:title" content="Set data cell colors using a palette or a color function — data_color" />
+<meta property="og:description" content="It's possible to add color to data cells according to their values. The
+data_color() function colors all rows of any columns supplied. There are
+two ways to define how cells are colored: (1) through the use of a supplied
+color palette, and (2) through use of a color mapping function available from
+the scales package. The first method colorizes cell data according to
+whether values are character or numeric. The second method provides more
+control over how cells are colored since we provide an explicit color
+function and thus other requirements such as bin counts, cut points, or a
+numeric domain. Finally, we can choose whether to apply the cell-specific
+colors to either the cell background or the cell text." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Set data cell colors using a palette or a color function</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/data_color.R'><code>R/data_color.R</code></a></small>
+    <div class="hidden name"><code>data_color.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>It's possible to add color to data cells according to their values. The
+<code>data_color()</code> function colors all rows of any <code>columns</code> supplied. There are
+two ways to define how cells are colored: (1) through the use of a supplied
+color palette, and (2) through use of a color mapping function available from
+the <strong>scales</strong> package. The first method colorizes cell data according to
+whether values are character or numeric. The second method provides more
+control over how cells are colored since we provide an explicit color
+function and thus other requirements such as bin counts, cut points, or a
+numeric domain. Finally, we can choose whether to apply the cell-specific
+colors to either the cell background or the cell text.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>data_color</span>(
+  <span class='no'>data</span>,
+  <span class='no'>columns</span>,
+  <span class='no'>colors</span>,
+  <span class='kw'>alpha</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>apply_to</span> <span class='kw'>=</span> <span class='st'>"fill"</span>,
+  <span class='kw'>autocolor_text</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns wherein changes to cell data colors should occur.</p></td>
+    </tr>
+    <tr>
+      <th>colors</th>
+      <td><p>Either a color mapping function from the <strong>scales</strong> package or
+a vector of colors to use for each distinct value or level in each of the
+provided <code>columns</code>. The color mapping functions are:
+<code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_quantile()</a></code>, <code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_bin()</a></code>, <code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_numeric()</a></code>, and
+<code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_factor()</a></code>. If providing a vector of colors as a palette, each
+color value provided must either be a color name (in the set of colors
+provided by <code><a href='https://rdrr.io/r/grDevices/colors.html'>grDevices::colors()</a></code>) or a hexadecimal string in the form of
+"#RRGGBB" or "#RRGGBBAA".</p></td>
+    </tr>
+    <tr>
+      <th>alpha</th>
+      <td><p>An optional, fixed alpha transparency value that will be applied
+to all of the <code>colors</code> provided (regardless of whether a color palette was
+directly supplied or generated through a color mapping function).</p></td>
+    </tr>
+    <tr>
+      <th>apply_to</th>
+      <td><p>Which style element should the colors be applied to? Options
+include the cell background (the default, given as <code>fill</code>) or the cell
+text (<code>text</code>).</p></td>
+    </tr>
+    <tr>
+      <th>autocolor_text</th>
+      <td><p>An option to let <strong>gt</strong> modify the coloring of text
+within cells undergoing background coloring. This will in some cases yield
+more optimal text-to-background color contrast. By default, this is set to
+<code>TRUE</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The <code>col_*()</code> color mapping functions from the scales package can be used in
+the <code>colors</code> argument. These functions map data values (<code>numeric</code> or
+<code>factor</code>/<code>character</code>) to colors according to the provided palette.</p>
+<ul>
+<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_numeric()</a></code>: provides a simple linear mapping from
+continuous numeric data to an interpolated palette.</p></li>
+<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_bin()</a></code>: provides a mapping of continuous numeric data to
+value-based bins. This internally uses the <code><a href='https://rdrr.io/r/base/cut.html'>base::cut()</a></code> function.</p></li>
+<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_quantile()</a></code>: provides a mapping of continuous
+numeric data to quantiles. This internally uses the
+<code><a href='https://rdrr.io/r/stats/quantile.html'>stats::quantile()</a></code> function.</p></li>
+<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_factor()</a></code>: provides a mapping of factors to colors. If the
+palette is discrete and has a different number of colors than the number of
+factors, interpolation is used.</p></li>
+</ul>
+
+<p>By default, <strong>gt</strong> will choose the ideal text color (for maximal contrast)
+when colorizing the background of data cells. This option can be disabled by
+setting <code>autocolor_text</code> to <code>FALSE</code>.</p>
+<p>Choosing the right color palette can often be difficult because it's both
+hard to discover suitable palettes and then obtain the vector of colors. To
+make this process easier we can elect to use the <strong>paletteer</strong> package,
+which makes a wide range of palettes from various R packages readily
+available. The <code><a href='info_paletteer.html'>info_paletteer()</a></code> information table allows us to easily
+inspect all of the discrete color palettes available in <strong>paletteer</strong>. We
+only then need to specify the <code>package</code> and <code>palette</code> when calling the
+<code><a href='https://rdrr.io/pkg/paletteer/man/paletteer_d.html'>paletteer::paletteer_d()</a></code> function, and, we get the palette as a vector of
+hexadecimal colors.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_data_color_1.png' width=100% /></p>
+<p><img src='figures/man_data_color_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-13</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># library(paletteer)</span>
+
+<span class='co'># Use `countrypops` to create a gt table;</span>
+<span class='co'># Apply a color scale to the `population`</span>
+<span class='co'># column with `scales::col_numeric`,</span>
+<span class='co'># four supplied colors, and a domain</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>10</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>data_color</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
+    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
+      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(
+        <span class='st'>"red"</span>, <span class='st'>"orange"</span>, <span class='st'>"green"</span>, <span class='st'>"blue"</span>),
+      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>0.2E7</span>, <span class='fl'>0.4E7</span>))
+  )
+
+<span class='co'># Use `pizzaplace` to create a gt table;</span>
+<span class='co'># Apply colors from the `red_material`</span>
+<span class='co'># palette (in the `ggsci` pkg but</span>
+<span class='co'># more easily gotten from the `paletteer`</span>
+<span class='co'># package, info at `info_paletteer()`) to</span>
+<span class='co'># to `sold` and `income` columns; setting</span>
+<span class='co'># the `domain` of `scales::col_numeric()`</span>
+<span class='co'># to `NULL` will use the bounds of the</span>
+<span class='co'># available data as the domain</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>type</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"chicken"</span>, <span class='st'>"supreme"</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>type</span>, <span class='no'>size</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(
+    <span class='kw'>sold</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>(),
+    <span class='kw'>income</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>price</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"size"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>data_color</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sold</span>, <span class='no'>income</span>),
+    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
+      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='kw pkg'>paletteer</span><span class='kw ns'>::</span><span class='fu'><a href='https://rdrr.io/pkg/paletteer/man/paletteer_d.html'>paletteer_d</a></span>(
+        <span class='kw'>palette</span> <span class='kw'>=</span> <span class='st'>"ggsci::red_material"</span>
+        ) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://rdrr.io/r/base/character.html'>as.character</a></span>(),
+      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+      )
+  )</div></pre>
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diff --git a/docs/reference/escape_latex.html b/docs/reference/escape_latex.html
new file mode 100644
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+function will transform a character vector so that it is safe to use within
+LaTeX tables." />
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+
+      
+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Perform LaTeX escaping</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>escape_latex.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Text may contain several characters with special meanings in LaTeX. This
+function will transform a character vector so that it is safe to use within
+LaTeX tables.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>escape_latex</span>(<span class='no'>text</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>text</th>
+      <td><p>a character vector containing the text that is to be
+LaTeX-escaped.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character vector.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-20</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
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+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/exibble.html b/docs/reference/exibble.html
new file mode 100644
index 000000000..3b941eeb9
--- /dev/null
+++ b/docs/reference/exibble.html
@@ -0,0 +1,242 @@
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+<meta property="og:description" content="This tibble contains data of a few different classes, which makes it
+well-suited for quick experimentation with the functions in this package. It
+contains only eight rows with numeric, character, and factor columns. The
+last 4 rows contain NA values in the majority of this tibble's columns (1
+missing value per column). The date, time, and datetime columns are
+character-based dates/times in the familiar ISO 8601 format. The row and
+group columns provide for unique rownames and two groups (grp_a and
+grp_b) for experimenting with the gt() function's rowname_col and
+groupname_col arguments." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>A toy example tibble for testing with gt: exibble</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
+    <div class="hidden name"><code>exibble.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This tibble contains data of a few different classes, which makes it
+well-suited for quick experimentation with the functions in this package. It
+contains only eight rows with numeric, character, and factor columns. The
+last 4 rows contain <code>NA</code> values in the majority of this tibble's columns (1
+missing value per column). The <code>date</code>, <code>time</code>, and <code>datetime</code> columns are
+character-based dates/times in the familiar ISO 8601 format. The <code>row</code> and
+<code>group</code> columns provide for unique rownames and two groups (<code>grp_a</code> and
+<code>grp_b</code>) for experimenting with the <code><a href='gt.html'>gt()</a></code> function's <code>rowname_col</code> and
+<code>groupname_col</code> arguments.</p>
+    </div>
+
+    <pre class="usage"><span class='no'>exibble</span></pre>
+
+
+    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+
+    <p>A tibble with 8 rows and 9 variables:</p><dl'>
+<dt>num</dt><dd><p>a numeric column ordered with increasingly larger values</p></dd>
+<dt>char</dt><dd><p>a character column composed of names of fruits from <code>a</code> to
+<code>h</code></p></dd>
+<dt>fctr</dt><dd><p>a factor column with numbers from 1 to 8, written out</p></dd>
+<dt>date, time, datetime</dt><dd><p>character columns with dates, times, and
+datetimes</p></dd>
+<dt>currency</dt><dd><p>a numeric column that is useful for testing currency-based
+formatting</p></dd>
+<dt>row</dt><dd><p>a character column in the format <code>row_X</code> which can be
+useful for testing with row captions in a table stub</p></dd>
+<dt>group</dt><dd><p>a character column with four <code>grp_a</code> values and four
+<code>grp_b</code> values which can be useful for testing tables that contain
+row groups</p></dd>
+
+</dl>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>11-6</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Datasets: 
+<code><a href='countrypops.html'>countrypops</a></code>,
+<code><a href='gtcars.html'>gtcars</a></code>,
+<code><a href='pizzaplace.html'>pizzaplace</a></code>,
+<code><a href='sp500.html'>sp500</a></code>,
+<code><a href='sza.html'>sza</a></code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
+<span class='co'># available in `exibble`</span>
+<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>exibble</span>)</div><div class='output co'>#&gt; Rows: 8
+#&gt; Columns: 9
+#&gt; $ num      <span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 1.111e-01, 2.222e+00, 3.333e+01, 4.444e+02, 5.550e+03, NA, 7…
+#&gt; $ char     </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "apricot", "banana", "coconut", "durian", NA, "fig", "grapef…
+#&gt; $ fctr     </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span> one, two, three, four, five, six, seven, eight
+#&gt; $ date     </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2015-01-15", "2015-02-15", "2015-03-15", "2015-04-15", "201…
+#&gt; $ time     </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "13:35", "14:40", "15:45", "16:50", "17:55", NA, "19:10", "2…
+#&gt; $ datetime </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2018-01-01 02:22", "2018-02-02 14:33", "2018-03-03 03:44", …
+#&gt; $ currency </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 49.950, 17.950, 1.390, 65100.000, 1325.810, 13.255, NA, 0.440
+#&gt; $ row      </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "row_1", "row_2", "row_3", "row_4", "row_5", "row_6", "row_7…
+#&gt; $ group    </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "grp_a", "grp_a", "grp_a", "grp_a", "grp_b", "grp_b", "grp_b…</div><div class='input'>
+</div></span></pre>
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diff --git a/docs/reference/extract_summary.html b/docs/reference/extract_summary.html
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+<meta property="og:description" content="Get a list of summary row data frames from a gt_tbl object where summary
+rows were added via the summary_rows() function. The output data frames
+contain the groupname and rowname columns, whereby rowname contains
+descriptive stub labels for the summary rows." />
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Extract a summary list from a <strong>gt</strong> object</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
+    <div class="hidden name"><code>extract_summary.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Get a list of summary row data frames from a <code>gt_tbl</code> object where summary
+rows were added via the <code><a href='summary_rows.html'>summary_rows()</a></code> function. The output data frames
+contain the <code>groupname</code> and <code>rowname</code> columns, whereby <code>rowname</code> contains
+descriptive stub labels for the summary rows.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>extract_summary</span>(<span class='no'>data</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A list of data frames containing summary data.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_extract_summary_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>13-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Export Functions: 
+<code><a href='as_latex.html'>as_latex</a>()</code>,
+<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
+<code><a href='as_rtf.html'>as_rtf</a>()</code>,
+<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table with</span>
+<span class='co'># row groups; create summary rows by row</span>
+<span class='co'># group (`min`, `max`, `avg`) and then</span>
+<span class='co'># extract the summary rows as a list</span>
+<span class='co'># object</span>
+<span class='no'>summary_extracted</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
+      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-30"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='no'>date</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
+    <span class='kw'>week</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
+      <span class='st'>"W"</span>, <span class='fu'><a href='https://rdrr.io/r/base/strptime.html'>strftime</a></span>(<span class='no'>date</span>, <span class='kw'>format</span> <span class='kw'>=</span> <span class='st'>"%V"</span>))
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>adj_close</span>, -<span class='no'>volume</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(
+    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
+    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"week"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>high</span>, <span class='no'>low</span>, <span class='no'>close</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>),
+      <span class='kw'>avg</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/mean.html'>mean</a></span>(<span class='no'>.</span>)),
+    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>extract_summary</span>()
+
+<span class='co'># Use the summary list to make a new</span>
+<span class='co'># gt table; the key thing is to use</span>
+<span class='co'># `dplyr::bind_rows()` and then pass the</span>
+<span class='co'># tibble to `gt()` (the `groupname` and</span>
+<span class='co'># `rowname` magic column names create</span>
+<span class='co'># row groups and a stub)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>summary_extracted</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='https://rdrr.io/r/base/unlist.html'>unlist</a></span>(<span class='kw'>recursive</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/bind.html'>bind_rows</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
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diff --git a/docs/reference/figures/gt-test-drive.svg b/docs/reference/figures/gt-test-drive.svg
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6V4OvNEYVzrZuqCwrBfMJuPRf77E9qSo8Dgw9p2zENmjOU4ksM8VfTCtuYTEZPAnDhI+Q4WnqJK4RVJj9fumYFfGkCsigR6Gfv2Y5lGnneG3I7pMf7nH9an2nbSabPkOmoN7L21uimno+UapnZfGO88IfvWHmRayAFSwmiC7j3vY/gFDKUxPcsbA4+giLpqGt+yQhtSeD0cH+3oe9t5J1W3gXvA8LMG6i5e379YYkFob64TbpYYbWrZ/F5jrjRAEkHPvfXLGdxr6/xeLwbtafvbf5gaGk4+sxI1xTwdCPCGla96cnM13xnjNh/MPzX3O5d581c4GmPnENRnAKch1+Dut5n0EpwbXVTZtnVGDUF2YHIoYH46yyEe9IbNcOv4hlg3mgQzU7wwZc9DuWrrTyZ5XFPBpM2X9WVitjY5RuAcnZiKcCyFakAP9jU0Gv48RHxR5TJFU0MzxM+7RVFZFstdEdnBw8hUZ/MaISoZqPxH3CU2rBmr+Fjcoug0ctgy4wUhEYBGD8TzxKGWRpgSYlaFezmUNB+Rw/sdsZ/ui891MDFvyLZK9ET28Vj0YUgbcLPqHbz1hvs28xuGer40upZ+/lecVW9DkLaNR9a22ckpVHJATx9KzyRl7otbIh3YgQO90r9rXwm6vG3PJmKABgqEqJiXhx6rfhiIivITXpvMpHDj/RZRcscyeQNKXh1vb9cacHsoXc+1SwmMoBv9fTLY16T/iigBeR8StO4mxLoOo+qtQRy42qYiqaDchHy4J1qygx6K27b5Pk/Cj7Vv/E3DsKNH0krcnb2MvTI8Ln3EUGkAiR5KJMnDHxzAYsnuNEAcwc1tlp3Xo+3i2UMkGn/kjYbxRRkqjPyZPS9KQgzVV4eiLWPCtlbqMHNtPVRGYtqUQBlRTZaMJ4cQSuwyu3jr0OplQ62A5GEeLOgNxI2N64GK5nRMF4FN1ssRxHXo3BMZacT+mQ+otIF1XDymVrbQOoKbjKKjdS8FuOhtJDH0KvaG9f6pwnZQGuBL9oC3UTqJ1pbkDqt9ESm89IzrVOYekEQnAa7PyQtkUG5ptvlUEj05b6Hqe2DTSyfDPQC0NgkFqTSlPkONdMJZN5XRQQVFDVy62rGPF7VPfUkvcugD/M2ToHMyofhxap+7Ke/CK+BTJ5DSqaSesfkSh0I2j8p4SDBSzN6Bm1cUFZxb8qq4BKypKrsXG8YCn7+3VI/eFDHvWW8fxTCHWvjlcxeJ/K0gswtdCebULMTXg6wcAvVKx4RatKqdvA5f4GmPm+sFL3B/X+uRhFNtmBnPW05ZaHhh4lg3QPlLc1Wpzw+35KHKvP4BOw3pR0axFhkpPO/a8B5P9BLi8arjRTNrG9Y+gyg1eS7JCC8X7nZvmncJJLCL5EIgs5vti97+0+9wTavvVNU4JPCsm4o+HvO7e6lngtLe3pLgT3LIRLS4umByPt69dxK8Q+qPX3wSJVyhDY0zd/3l2EogZ6w+O6PStq4Ert4/ZHeK2f7z5W89N1eRek2h96gIe+yDq2QcmqQDeTbwf7AeGENegZmJ5tNbASuBhO21JrWh/Js8y7RJ6C1M+8mN9v8uyB3zeKEBKCBTS2hL2AIk2JBDiht6YkSwC5fTjzEiu/zyWW85nMhweNAndvrP+1hrFpFExVVPlOPDNNIiJLcWrVkjAtZNpaC7eM+8YhHftIqyNLEIkwzk/jjNltoaNsNbn9QMSNCVzZ714779yHS7Nq7UaZgIuIuIgWDulvltVlY0QyZM2hpLZwxZetg4U59m6FXpeLKLip7YHxK7pY28EubuBeZJsUwhu6zgUKIvDkMJFrD+OMKzkApOQfAXPVrkDahs53mtgG2jh4EeqdZs7jpXXu+sOQM4/tLzLW+tosNWrYOtMLMDB8Ja9Vz66MVOL7sS5CFHDwu+msJShG/ToZRMbivAtRBNNL6aD288bmzNBpNlCuqdGeiym2ZMXqlTyEnyHgeOfN+419cUpp5O1oBv8ObRxnxYXosBm2rlV0g/FuSaenFgIbwNJgDc8w7Xm6DCkIlsvhAcYNGi2plteRvm+iHF4sPBel5xwe0tkfjy3gG8Cd5t8TAKVlfbpPbajDnfTN+khf+oQLgYrjMS7ZaIRQ4rHAS81OI/UgIyc4ZKxtySsBFO//5Tc0WTlu6QmhqgEWkJsSBHVuxywEZXUfpB0+kPD0S1YgVBm3OK/4PI/K6p7MWLy6SOZS+iBd+glgOcnPl8+1wR+8Ht6HNPPb3ivZ4RbnEiku73DkRL3ifFaJkI/EdoxXYy8NI9pZiENR+FImoVPgQM+xoPSD38TPMFnzAhM/Hlmrr1rYpdSzEIT4ZZuM5P1a3Sw7TBnYu5s3Galk8rhTdW7/zioFuwkB/giGOUsAqv7BmIA0SjlEYtii/sfh+HO6BF4aKrmuOFy/F0u4yT7XG6yF+QInFu48z3XI+d/tDLIz4tuQ2yCeYD1B7jktSW3q/oHet6yOoSVKEYfdSk/HPuz1ZD6+pFKCKiS49nmXFrNvbE1jkiOrgIEC9iQVFbGiSfkjTNsB7rOxpysRqz3khLWRc8YXIHSS5kCSkY8YVLTzBhfXqp7l1Ufzd5rpnZAr0ZrU0SN7m6RA+HHsSwJF70L9V8BwNBjEMfXcI2mdRfH6NoGvxQ/A0C7WVWZfUvPgskwHkBOBZqv2PUiDzxC2/27WCZKCSeEZjsbBW0U/FnQCGaZTKgXTVwyxHZn0LyDTtzH05fRRZk+i3BPRY+DoriF/iOYsMjd7mA+wiIet05hXCyGM2Y+sO2NQ1TDSiwnBHQ7KXEVslPzIyRjwdMeSIImSTgCSDklyqCUTWCXWisjLJ3f4h8Vujpd6E5CwKchujhMcOhaGacbO7VM4BmJQPwyrOwoA32zd875dYIVBzJD6V/7okLMUNcpbAcFOtYyli7BUkGIKluYWy9PThBdowvZkBCoMu62lkGTkLUrV7ZVLcAATvr8+4qqFiTBbl0lVi2CLWr78i9vs8qIyU0Lw9Fh5V5OVrKbuqXF6ptxev6j/fz4ZwnkMVwNxNBTquh3feUzg8YTBn/PgDs+sSvkhmPf7R8/mciuZdYz776Yhn31RNTfA7LUJiK16Up8Xb4xMoGlIGg1UJL98yu2KjKu15SzR9tB2NmFq0uvVbRzUDMCwX6o8343nO0QRjddUstK2YEw2bRoG78j9KhqzFqmybByI4/kvUyvz/BxGVwceEbN7sHz4lE3FeOdOz08Q0c+5VvB37wP2V4At0VRms6ylV18RPwWqB7/ig24bmg9WrxQtrVDwEyIb5MZQVr6f2ku8MXso4bXMRpLa8+QJfVEkotSfmUyXMBpvk46tQQaeAPs9eax5ap7KYCOopnqcVkDOE6wWDmtUfh64DLWCoMZTWzIYuEBkIGyoEPJlqRSmUxlhI4r6vvQLyhTLgVWCAZkgyxHjMApht8OlVFcFV9FXnvcKajztNxzB14jU2B6OCdpBYqRlooMKsinh7G5zUMmpp9DAzI35JFNOKvpSC26Kd9ng88ZaU/h0a8BRNWgoRtSvkp2HKnpoC/XP6W4BZMyO0QyG0JHJKcxX5k8bZH71FwaRN0RV0rgsaCoD37twPa/qIvScFaWePSVeWqzMsR/YPuNAOViUIZZgjuj76bz1qhfrtnhjvmvifXexL+2Dg12A4VkVqy72Iur5WWQYMOKyEjZ4p/sXPxOEPtyF6SjPEPWd/Ro4QtK5P1c0MNUQDXSczjZKBDVPlwa18pMeT6hIbRa8bg8eAPgRYf0NQuT6sQTCX8hFHSimvi5iV1SXGXvGPt9rHg2ZUzqD0UGB+UVgEYMSsfYUMWRVpiI8lIWfQ4HuMFCM89qhQpJ9TlBY556Po+Mb8jshag46/5gyp1ZPkmsWQasOziviQjaX35FDUNBDziwiq80ShqX6Nf7y4jQoSRLKJB/F/E2wKXhSlOYqyrYWxy4lLg0L3jJBxUjQK/G0bqDLiv00trmRL7iJYnwGQVdRa2WM9SBx0Uy+tAfF9Ln+m5p2hL8mjpFRwI/+KZUYCTWwLEk6MS8dTizP1eH4eA+2iOPvZEkuFIcVQCqRlXDHiGRnxMXxiXyDKFc6csdLM5L5vsaNCTVabfNml3jDsgBCqAERe/FkS5YlKEibS3lWRVHsOWBVxZs0CK2O1Pyxj9FL7TnbPixfWen9ECKzU5hXLgpF7ekQLwxCgtNcXRSNc2eSREcSXYfG/7L+EmxDjj2bB9W8oT4T5fxKc3OvrelzyyeXF1yYLQVZjSFkLIv8fXZAekP1j8l75gkLf0suyxmIGXSxCCnkZEq6HahkqO7qrEwVFOfrnMWpOLDA4GTYAL6c70eNv2PU0gfZfQBRjVtNsEhKxlwyAhgKhHJt2t8seAWi/nhPA4riAtVAkV3jzRa9WmPXX1wnQJcuZt1H0NIIXy/jB8LZ+XNg3o0xsdwerjQbv75gF2AfekbbX3RcPxxjWfKXP87mNTSa1Mi3oUnw0rTT24IpbzOumaNNlRRhmH+SGd+ZihO4XhCBQ/b0EgRmYlR9N/idVAUy1dCvlSSgQPq791qbEpjcRXxr6K2NW+ojLPvflBqCOIlbxurxNm46BwOoYAR4Qn1Iz4wb0yrpCk0hCe3TkasvM8gauvSVjSX0VOnZicwZSjz6N0b8U8UW/n/tYZKLEB3eo/+jDvyWh6MtKX3ih9uo4ZMKFCJ4iZxz4itDlTgVtJ0S9leRXFjzR2+1STMUwq4gfLzL9CuWvsJ2SDX301o4M4rXm3QxRbk3loJwb733eI5XqY4weM4w+XOwcs6ghShtXDDYZseE/XlSAwBAlncISQgaqpJC5CoBru1zWy7gCYTwqIMKdIptoWWkSzOt/jFta7BJwRgdv4junBDDhakFfClgAMIuOnYRlcj2JjjY/kfQEIOmqFMX7FyxytrV4E613fg0GtwFX59oQNdqinQP2NlLUULJ2QQdHcl5RTqX8PTRFZPHtGCeJ+iaYXYNXy8lbDcCwr9bZLCldtyXqT1D9d87lkPh7WmdkysNDGTEVXrPqt8C7FJIV0Ig81jaLYYzFmjxawLE8d+yY+OdR1po17tIvUrDyJuS0InEdMcxyaVxR2Rg06wGVx4/lc+ahLFwpsBYLcYyg1Jn7ASjOCFKD1aCQjMlC+ToMqFpzeTVmHfy9gVY2ORNBgCoJrgKaKKnBfWBQHgmEhBp7g/2lz4oD68/L5H0vBF54J4Aa1PPmBxsxFPl0ircPHB5SFwkJxyxfCadKcDaVMZgfhCjp1eLLhyz3C6ssLyMKPB8z5mc5nJ6I77Naz/0RI4nlx69qjjqqQ3sidsN6PiSP7/DzjiE3uK7s0JRxVxvNnXBfIuE7ewH/uM0WKm6aP57+chS7WOn4Ty/7JLGvfkqezzI85GHYdHz9x+g7QlmvGZMS+xZ70RI+wCIqUZgt/OUV6tzx3yZhxFUJji6UlDEvuIZMguZr1m+2CO/nbeDMQngWsKEJ4MtvTxqIcpP8KvzwJvhuYMsw/phgIc3377DOXpfGQ/jaOF85oKYi4AcABEOhAPPth4/GHmSIWYoBJofCzCrKc43KOMVMtb7XrwisOKBfFSuJnsx5KhUP3X57/6+OWubEPfc9MgZs3zBWhlTmeVtQmijiAPftW3vB3UmtP3HBb1YRY2U6dxOwUhDlvC2jFK4118g6fDxcOy4a7D8ky+UJ22xUpoHEaCI+C8ItHjEj0cVd4iqwnpDy4kJLX987Nzvj9fcGM0UGK62uRcuMNFJQ5rfrTeJ1MQQiHdKzETWUM6A0R/+Lto3qxq0Gr4WvrgC8X9KwhE0Xoke7VUCZsaLoFXxebj0wQ3cWQ+YN9ELkhDtp82RC/jnR/4WCS//mbyNZK3qOULx3YgIEwzTu5/NbAKG3jAYLWao2uBZstpDehcXSpNLW68hsVJjcTrVoL0FRHR9mPJM7joi+3eGasZGrFgnLt5LLDJ69CIx7BQxYYDphBlNQPFJrxf40pt2V66oY+95tOOMT6QID8RtfgSiXv2++gDAAvy7x3Ca82knEKkWEf1uJEqUFZqb2VeavrNBnDIR5kLYWevE+YWriK2E01iyS6VFzxiSDnHwMNrtoB/qy/kytu5EwIbURkfGDuBhYsbGZQDUd1oqLyUbn8xiDtWqSb5DcdxPXUt1Q35TW6J3USMvlM+0rObytUXr3v1OETP86ln7nEC3HFQy5AHPqVhuA8L2qICZgaF3qC9AhoYLPcvsrWlfJCJT6uWDN1jTBqzRSApGV2BRvsTpYWDeFoeLm6sZ8RD0cAJfudez5jJ9o2YPhF1Bn2V9FymBJEULMoFSsuCmH676kmhXRKEQEY7/idoToUSatE9Ihax4VgWxFFf7qQLszPDJUhcLLiqZVKrG9c04h0bdBnbTxxPd2Zy4ldvB3Em44e7kCw6vsvoUqgB55JM0OuCepqSfBCYHaqt5E1UCsk50hEx9/uxIj5gLpi3vxGoDD2ChcJD7JP7hZkbr7iCfu6Ckbu2ViNhc5vhLVMEH5xsi5JONDI/u5DCv5pi9hBjDKR4l/2Yd0ytIqnE36QnYBoaDjNI203dtvEu5jTX/UBqrf1W9VoTxO1NBdLvtpxuT1fKsXA2R4zNq4dykBA+lGO6KVj2Kke6OiTAvjxymH4ujwtFosoWykIdXdKgQPZg6qT+b9tkmzMczutMp6P0R78+5RbtGGjXr+/faMQZLHdEQuQsJC3KQo/+SOOiVAgnWjKJvyai58hTsU0CROKUqqIp6mTI3/kO+4zbK8kint5kAB7s7k3/6uA0LXqen1oYXRc3nUH1MjCgf0b/L9om5FlOL38sBlCipzGrS4RzCjG1IYX47SihQZRu3I29srhrQa3JliZ6mqRzLFZg8Wy/RVmEYol2KIYJAtdED+fwPAXjq5/9vJeKFgOSyMKiEibJtiXehgNeSau9ds51GZXsv6JFsoQm74HlWd+0Vh03HWEdUblpNO2w+AsF5JRBi4aITxD2JsuXs2Vch6PsXJr6XHPaXU8IQWp/DbdBB116YAGgB5HC0v6WVxVyrrLq4iBwx49hAV349dWC3Az365mxqSxeiw7ce/4C3Uwi8/hURNjysS442Q+Bd2abjFsVNzP4fd9IBxdBS8N8usIME6o/GeDl/Y1pLZRbrdPvNPlVP4D3XwqnhAdyhOhxnKwRZOAXuJTwEeY20RHk1oMH+GRHCiyxFXERE7l5Ika67pY5+0EacI1N5ELTONt38sD/w3fO8HlEV6/l1erv9tLG6kj+Ql/34DqH9gvkev1NGLXTxSWUtmb81nZPhfIcXfFub1zBfKDMD3ITGtuVAt1civtoyjoqUAtf8uhN0uaAyMzo60Cg39IdMTxIby6JdWC+8zSkQx3kR2zeKHFsNMMmjj3Jk4gRxRg5SOQCotqCJ4pR0YUhQMBmaxNTGrUTR8k3UBDvHRyix1r06hRG/beV+R0a83CFLCLJbuiik6TPyFQG8hLAAXSxG3g3Ktgd49mlas0xKPhpNvFx5g2uyXaJamtiVNPbPBc/gwDqGQUa8J71mHIe5/bi8CeXDBthjMeYR+p23wrR/TpOHMuGUIyah1kFuYOYh8vQZaMcDDwom0zsFB/SIsAiJ1WMWlz1QifpWEv/t0gVtotCzVMKxyGkvBaaM+7cyWAL2Z6MjRiIOBK6xhRG6PK7bGZJtbVAXvg8cHb/exJ1eKWOf9DhyPzWoxLhFlYnXryI8X+Vq4TNjsHDY7eh5d6CfRW27SINFijV89A9HTliWHLM9++0/Nbv1mVr0X5t2nEtxhkweZiuMFp+xWV54o8njpKV+jDp+j9S9/7nZs27w5SI1E2dBHiSgiAmxapvs3fSvDRlKlJt0rdfDMQRPbfxfm6Y4Rz64o4iMsHrqCURfVAg3e613zU3D9f1g3ir7aO7+g+LyJUia+sqfiw4oG+4HUQFcIgkbZBlrJvgflh/ZntANUI1/B+Q4PQ4SVdUOUVoIISz2isyYl344p0/R2POYjSWT2n0fhxcyFTlba7UZ415Clp17say/o+7KWlFGg+wwz2r7Y2yevDVqBU4WUBa3Us1y/ck5T2pGgx772rEjWnhzNfDdcjFZbkVQSqagD70jgoMSMoWbZRPiW8Bu/c3+E1KxP3TU8n8tO+9ewPiK8apY/tbV8uB2LombS83Rk/t11VqPYbAJYEg37v6HPuiQKaelIKWwjU9ZQC3QMLYZ6YsjcU7ycLX66X7EoZs/o1/xLZs6Vo6UzlwlkkHR5Y9yTM9+J0tSTUg11UOFahO0zpOI/p/f+OWZxnxANPsYdVtWWiHBYRwxGhjTv4BJQF/GKbJCmvYlmXMEuLYE2NHzVQyEUVR11R6LFWAdA4jJ+nu+oDNL4AD5NQLJ/L/nz9Dk47Cpsv5rSUH02KRTLus/Toqh7AmK81OfQhEJk0SJpLlfmkIKZGAslgWHuGWZPB4n/EargJfFPB8y8p9bf6jnfX8Oex+cVKVLozyEvveYnQCsz1c62Cg8mnTjy/9yY3G9IAeQql8q1719u1+cEq194CXI0FuAW15odAP4bAf2NFybWRb9zY6g5xz4hQTT1GPpKAi+wN+9/VPzlNWta2Kl1U5nWoaZHsjRPqmFW/wm8yiGmU7RrjbBtGJ/O+MmhfmqjoudqWfwfL9xKozJiL5dVYB+Z8jh8HvWht8V7QnMCXgRwUPgEuijT6W1CFJP/lR2i6LxLjMKvQRZl7/n1/jlijjj2Fjul6hEB3eFwA0yjlfXg9ny09Le0oPdhntwXjOPEEEGvvvm58LXzhPnYj5uhlReveug4WBdsfjNB+EIg3JYnTrjNtig5RI5ywR8901krQzhG/yoph1l1B2GwfNGDYMrM350IjKkd2MkRA4gam1i0sEUPmrOwHWW3dWG1ak0bcQRvOB5eltwWngmZtpYcSqrAmrRUN+NcmUafAaq60Veh5TDpK0Ob0zhAR1qC6u6PODKa2cFnU1ahhDCvB3Rt1CfNBUqCjBE6jxCuSVWqTNC2UD3kmEo4gLpomlQ72pYWgWi2uUIvBP3RF1No9R+etqRwxMXtGvsLkJiCtjrkCn79Q/NID52BfqBfy8O0bRKxtH1uLDDlyMR3u0S9rCw7NMBE0n+S5lSRW4+ElPjVgdj5ypVyslQLNcOORO8zVx2NhbmNQkfUK94t3zU/xu7KN1kXVo2treErs7IHoYrw6I0oHlOPPk9EmcT9gxHRHFIynCHG7UDwSgiS2Q8ovx6IIhRSAkFo/c1StrN5N5nA79qc7Jvc1Wnt5l/sjm0+sq8oy1ZPO8yYWjVjM4+d5EPQuOvnp66aerlxWi1bP2gYONCMtngyI1GZrWt6Ngbcw3ueUB8+GLOmRhntXFgjViG8dztSMUYI/R3WmsbXzp7StTgzQ/qfz73i1rzEyA1Rj2EWUcHG8QKyfi8LE1e6/YpIYTn10Dup/BPXTsHuQSso2iKrTbZbolk+W+qyCWX2twXq7/SPtsRySsCEAkKiFVxWfDlQm+Amtwau4k19xCPGnfPHiCO+ZwZVRVQv9EWZyuH7hKFJWOVpukiUuUKCWVOikoHYrp2XK38z578dO/qJIaKVxO/B2NjcFexVQlHXNqSK88BUHmM51pdtDypaKMHuTszsM5VRuldjWg1R+v83FDK2vFzbr/NYxdS53xhFXx4iyRlQey6NkhMp2l54/nKm8z68EKy1u3pVTdbOYoY4movvKLWdO2bYb8470XcwQku0wqL+OI2vel2cWa54rSVOSTeL//jcrzSLkevbUHKGFLk4XiAfxjj55ZezqvfDsxPSjNArG9vBM9SXUcjPsnfir6N2KQdSOWkAfexbrN2/hWMmfz/sTJEBxXKr/WGYl1X0cynn8JXFbGMS8SygLFJazU08mjPcjApRQoH8wKxaArGey211SmqYFn1EePBrbhQDnIzMz+0YbUtEI2OHpvGPh6XURqzPvFAg8xztmZoRkJNz0gpHffwkKX6DPtdbdyaECBInjT4fQUad0T4gVn4JtxrylFkrhCcG2DNiqP2Q+VZTOqPw6J8fmGZjAwkffZ7h9UcJZiO1HhtDGcsMNBp1f43CSqbCXmC6JdOeVybRS5fLlGFhHWEQZdNBmvUH/oqazDRdinILPXxH+6mE28y1KewXwgVznhJ0DYtFIng2pGTQYPadJYx1QQqAGPblb/ttCiSMPb0L8vgCZcrDhSqITpNR8sya98htD+OGNi0U/8SZ88jxPsel/RamzEzz++ScgGnigUQAc6tteZ9UidH7mNefqlEGRnpuAHGM3DdJTUNqREqDN9ucGEVZvUAlZh2TndJhDwg4NENMy1qS6syw8Boff40f4BrNrIKXUG5mhTQEyqJ+wAziA1TuC4mvHq0gb/QvGsu+nUz6MWJ408UpAp5uPXZrPyT66F+6QI4p1uPIFnk0XW91Nk2W/X4DaxLWp2l6oHbBQHC6uud9IherbR+JG+bcCxQ9208t1VMF+hfp9R28oWPxMH+WRrLnA+s4OizVW3ORx9zclkyjpJAvT7hPeK/Vc6zRfSJHtAWkNl2Kae1kfFqM8MM7v+P+s0+rp0jby7SGx4G2KsJJht6C/qgpQx/CRTrgqlz+jqHe/Jr3m29XYYbzxEgaKHlkcPRPpNuCzlRJOyyh/kHi1gfglEExB1p2zdVRHZMq2tA6mlJRHUi23r+p+PAKluZfDEYYoP8+47GKlerDrzTZ24HwoZUErWnF1fER4ZPTPlRyFaIu9z2yhPG2AQCHw8GJQwi0L9fsahWBlCZKlUgeBtL0rKk8iRrRyp2wximgRFiy+ImHjq/uwnwbn/XkMCblueG80ofMr0W+59ZDacEkij121NagcLUWZJPWz2eh1yrDOx6Px2Z8DTdg9RNmHQRw8bgwwCF2Z8z7nNrrs1F3Figx0qcfg20c6kjVQXzPAzCtLzLbusta2tC6mcS7kAOjKXxdJVe4LbdQgRn8Ts0AYmAnpmUabOSjcNpkcVeBJZJHYt5WAZjTFZ7/hBjdPuPSp0Zuzrb6WTz1WZCJ9mYrq3STprIDUlQIDPCDWXjgLceDusSrZvXd0Y0BSvAQ2Y8Urlym1+zH9v6gHd5XIpgs9JiFzpEBs/Vm9GL/z0SGIKAlh9uiXYcTSIOzv/Pfk/9X5ikg4WqUijNGz5g9kyTQv6UuL4KMr/7F1/LQbfgbZhtULiF4oxXC1LXM/6iHfXeXsejgQiot4C17KSBq+fU18YHjYZF0jfCJXfNiWqvK8IB7AUHFr/SGEu0w7FrfgqiQxhstQ94WOrKqjbwVMgskVdLlH4QwpmggVKfGgomCpf+YddhK2jRv9YlQmfv4njH1+8mfsxIDiYpCbyuxUu2gKqxiP3hjhhOtvXJNYFT4fBzMir5D885EKBwfEBeWX6td4Nh3BfsxGMsrnTcMYyMlYQDxszllbU+zE2MktrWKmFsnHvhK8+nJl0eL/QTDuiL3fDEG0+rzXeCk5Zi2DyclA7tomse/o9ll6HaiKHG/NH33h6JCWKxbLIdfXyw0GGYAQj7JZsehzBELTcbDkYbP6LnNTsYB0NBXN/tXa/eK1b5XPVVNKIciHsp2eQwYxKzXWR7t1EKa8b+KED6w9/O2GosJN1gcUmqF7ILXH22bmtko4Bf5kmzylvpWIyM42tgTnD3LKzBCAkMUCKPVu2FvszQ/L5I/EtAYtsYm2Z9Hz9NKixE210aWlAid5IJcH/adP5hStod620LhIFI0Dzl43IaxvTZyFeIM5aomjVkdX80Qj/j53XSsfHtV92srVTO1C72rJDVCuo9I0XkwU9lQEU9gMYM5Fsm2Rr27HyZkHcGjI+Lurszs5aVZ4Jv9IDMCiDe2+y0kZJN+KcvbI0B78uxvOgqIzvNYY9LPzKDkwIieQa7ggKaBBEPb7RUTQ1P8Fb3gBqyPkmvD3QFNTen6KXOTUwnkqjVIqegVs8IohgR6NhfOoaKXiitbqOX2sbL4pF1UNYgT3WlSBDTi/kVNyB2/pS/REXFGxkdoKEMvCnKmt2w1RrvmhXh3E2duMJalD2YYwMKmkEDiOve5Pq12VGzMlZGoFvES05GKdjPrsfIHMI1YSXR6Pi+zSrrruRIIgVJlfSMrKrlitJ6uk/25jSxNaeMjLlB/DY8YCSo3Vf36pLzfVho7saEKNU3WUXGWZEnAr0on98Qx32ic0JZfUbafgN034DJH40UfR37uaHti/C8zA/sgrML64i1WVUcPopQezA3Xqjg32gGKNcjtf9+31b0d1txiTOuCkR7c6mSC3kwftpi/ahN7rJ4ZLQh6vPbaqRSWjdfGiKXM2zjybJln/xWp7tc2eVSpzYSj7NqVLY719S78+95hZ1UnSyiocubBTXNV+sblFXf5YLlDSQEUhq8zJ9fOZbsqRJ1eFOkwfOEz0EfeFAHacXgul8Vd2xtAPvIXRyuCXcXJSd+JUpjMirDPKc0dGUTmn915rCfopeLx+MMzxrI1OpNALglnsTAoLYSh4x5UCYeHTGWpZyVdZK2KKwcbb+9leOGwxQWA7Si5oQfPflWtneb+CK3C+037Ox76Xcu+WCaSzD9YrUGEGx/o3GnAyi5u+x4l0HYfWXjiJVC7l02fH8ZtGWolCODfdVdKWkJ2kGb+6CXZjIE8CAxX2o8B3e1rqytEQ7KxZqvHsqLLxiyxFl/JirY9CJlHH0iICp6FA+tpnnjy7RPpvedbHGq3aCigLlGWl8kzQp3F3sy/8c7oLMgwXgc9NIi2fYo2P6nGMavCXUtS67aswGcr3VKMgxuiJtVqEMifBa2utt2cv7JLyM46IHgJhRveMQwvETK9Tmm0HBuof3LDpibO5b1zZ495CSLFrGodBQFcz1YayGHXcWrxCEYDB1PrQyJjn3QFpDwGS846hD8/xp5bBdTuKPYh0EbkOoY1sgOWXYrnIX9zw5ml2uzxJoEbCsxi+yqUI+8FK3qiL4cuCjPtdpFlgJxKoHXjYHVjhUeFArx3kUfdooriryu9pevARL6EPhDs9CWaY6wzv8lCbTVcgTYjURnRKSyLgk/xKZV2Ub4zYTvy2PNLgondfxG1Ld9jgbDmghpIVpFnPgw+V+RY6JMOQMLiftGREiqghWhbzCe0IYINjfBZbK8X1j/ppqQLYzFSenXsnUQ3A1jjbdraoJYpR9rf/cZA8FCPhTzHEz9QOXi/4vPwd4nNDXaGOl3QnhnxThKG92fgWdY0nLol9HDxgIxd+P1vz5c17U4bHZnLsiny/7wR8n77bmpzq8JC5uH5LKNHbqlGuCvAIdYP0Mz50zF71sLq5OMb0zABKasGFYwX3jcqi4WLInYRdFw0xL+IL+tOMpvoq6/4aEInfGm715p+A8k9/dDIhu0F9SiOm95KOWWkb2jPsMe6MP97n16bPlEaSH52bwTTXu6SgoRMp3xFsgjPY/3KB42D4AgdEg/u4M1oR+2Pv7RlKyQIsYkZe1KBFc53pHEA3F/VrHUh8OtYMuwN5WS3zlzWrOSLaHjfYv6f7ivYRDdB/WJyCpwnF30+Th8V/kMBL3jNwn71lbNZwmEqzbSZgWbEUYyYqcKnVcVRKfw2o5wMQA9M5Mk3Izca843QzdjSGPAolSjHOLbb3B+qmLBWEIComIUDw1Gzgh8v09aQ/eQaDtaMEubmU7eMcl2bEp1uBcu8MiKscy7AOcsOsqowPvVestvMPac8OLpTr2ItvFW3GNMPSRGPWO1U5xNCdOn+2fLOkbaHne7eKj9GKO3YI3RXhiPhtfvO2P3dGq84u7j0AKtIIHCOGCqpmtEODqgZLQK8IrKh9mRfgnXio8n9wzEpSvJYN3J7aJVPy0sPecADKUhwe/YlnhFJGtBmWYDsO0IMRsshGVGXgxBKcw+YpKGJaHXgCl3gHEhfCfELNTKsIrQe8zooxBeeBAncRRliEA70gqQofhlCsCBapRaPOEGFS8w+JBb3iHGUhAAiSqRaeIB9TG96GFp371Ofh22SujuYwh4WUf6innFGNAgl2I39Y/QxCQanx77XqNQV3o/pdy6mC/BKKdUa6vBEBLzXUGYMTwdMM00N0iKQREoLeDYhPvyT7Bw1iVWnEMpqVee9Jshkp1c3Y+oCB9ijLVTB6OXHC4yaDJvaHfUu6RGiuQdjGxXkS7/HgY6iv0Tlo0pjEalpwi0JKV7+B9p7S6wChAJGNlb89liHDnpVJsV0BAT7KPLnpn0CkHH8MtL3iWdKKgFXxXwxcAKMeQR0OlGI3B+hyEY4aHCQvT5DyNaWRq+VS+rBN+nFoZMxgRc1kSqA74RNs08Hh07s/ZOq+lSkQUEd11zCrtlnQp7NNZJkJUmzrEPBcDjjjiwABMTWIHlfELQ2pi4SuWpIjvQ7Ajf7fHoKLLtIq62TyL6EsLDO+Zs9vcJbA3XSKeJKs/NKl+jI+qiEoyhIKOpx5A/RzMOUkxF4XOs419STFpWs3yN3cyK605a+RQ6FqSExgfjlJHECUnfW4hvMkcXvxvvXRJYZnqcos2KqA/VJtJ0Vg4z2fqfO3HBOS4Jbs71LnKAwt8xjYfnz84WyYlj2cG3kWykLCLzx63ypZS0+T2cbeEY2tnaP7I/QAeZtQoShsC/A61pHpkT1Q5F0k+1FGbVvuhD4Yd+HJaoVmSNN91xvReZDROUUNvx8HRbut/W9CFInEhLlC9dav5pqxWW2kGjjhv5Q4ilG3Wk4xucBa/QQTTXkjalT+diUykoLHWVolA7eIfH2B8VxruydclIHKsGqKNUTKvvY/khgVDtrrCwCPc0LknzkMxfHXxUykXGw6UwWe1WtJrx6ZrUUSqD/wt5oZ7wt3rXdYSvPUHXi6Sm2V6TxTnXJM5TF1Idv34nus5syyZJZCWduhru1D1nkZzyP9v2zsyYO2VWjDAnorSDfs6/Y1lCZ+FJTQ467zmJUuR+ChMJEcfynTHRCFHL6Qz7Ee5Zl+RVk7V39d4PSKC83KU31YsO9h6UrF3NkW4CTRaB1KCLIlCghzXw7aoaWnpkNJlVPbA3Es145oQw/JrAjVZQy3Afs3WJ98rfSK/FnSwd65dwqdwRAFBn+kXUnZvvt6yyNEBVMxLlr2BbFqzDuHCeQujn25CaH3TDY+Fv3ueUkOvb94/VpfqjmVwuXPnk/yoh7R7VVAREDeAdEqDY039yhD1MzKgIDai09+p9ttkqYi/xaLIWr+KRd6jS+fElsG6GSa7KOghGeUAV+9wGgVDACLb/cuh3eRiKdspb18jGWq1qohekIE9yyDQwot5bPxVtQYVCqxLIMoQSDYadxay3zvUuAt23NtCQwVa1DAKgSYUd7bSYR4KXawBdokq9QvESMRhoHztYV3lC1cHaapeR+gHBRy8mdZfpYE/6WgZlMaE7S1vDdZHlRxUiLn7l22BEInN0EisWDiOGl+pdRKBQTwXXt2wrBBNIxvEdoSmGX/PtTR58CiowDvfF3WtpR0qhXfRtZhAJgFOKQQkX1vReSsHr47xj5zP5oHkxxDypZLurQrSV4k1m0IDLXHvw7eVNG/FAi6PMTAiSstULDIB5G3E9Bwhs7ATY1k9vQ9V5TkC8fuX0zPlXaNQPt9UMp/v8pGJIxHj0/DZwVkRYW+ZuPyuAsyzpSQPwKNx6o1P/z1YampaiC0b/wFKf7XJZZweQlgtvmJ3YzelFtizVIBhn658faPCrkY8ybMNvBSYD0bqO42ZI0t3UQibJbpsPI3pWxVmQH/i2wyJ2dD+aqsSXeInhXpFRG3fh7TGvZ2eomi5kEpiLeMuNpsd5Pvmp7hRUwC3LS4ZTfNDSBNBtRQJ4JPgXzhjk1ROoyC36/2+WvFSGXpCZ6Kblfn9Mai4igCFrX4/WIsROmzjEmeQ6NF3EDwORMtz/pM3r7iUm2CNpS8h9dvMoenTIguQvx5QNRfVW6cq3OrY92yGymKVfB4E1ySSpmPreFfhoMjN6M1tVYidSY/McPF+utr/rX3f1SDfrAq9fOsmI7kVrfEDRAtPNgXYfUHLQ5YKeUAVFnnTmHVN1lPx9NJHA7+Z0C5t9lJaRnUQYc0TleEcRWXPQ5HoR+0+Hl77uJCYQ2Ih1Z9UrWfb32NgpV77qB7QzBs07pg6urucCfeLNynb3/5ha+ejeOqwQbN17tbB8tEE7FW/+tMmWNjheeypSoExUM5Imm2uoSEnFkfxAS6/RcWID1SoRgV2FoWGFizQN8cOy/IDHhRe5kLwsgCobMDCS9AvnjH5Qf7DXtCH7ge8+1pg6ZbYeTKwKr4FNQtPzCw30QH/QkIQmhQgXi7Ci58usoTu8emJ5iDyIPECqFnlHBGUFg3EGDvvwbnC2355sntiz306ohMbRB7AugoAwp3LbMPM9OEtW8fXJU03EblkgB9ezX8TC5WkvnuP/YBmYgMGQ4y5J8129QctCh42k/bPiBDLaOVzbkOopHzxcB/gMvfH93XAzZICLYyD3aNRAi+xUfIkTmDASfuhucfEx7CzZKfFjsv770f+8xEbIdTywZo/Aj0BUvmUEU7d88wRKrpMCKaEHjkYJmtE4KPMVmsXEf0ypwI6+GeEvsVQudO5QzMakD54n5hQ0wkA1kCcLXz4YISZfAaQxiTkhXWOyvgR/sRXYIKCugT+Ae8WkO8JdlQTpPsTYq33WWc54APxMp2Kk6rKFD/hS8Tp+T1QOBoQlVYm3HxV1Zwm199BJILj8M45AbZqZxX+jmlULKj8I54juZK5TyiRUYJabQ7lanCRu6Q7KWvi67MhmvMhRiAsJhklN4D8vUHOhzs/96W/mUAYU+qIUcoCoAbl+o1Mu+4rUiQBbHx4xWO8mKj+s7L0KAaMPgwyoXjPqyJad9xFEVHpjkbYhEwApus7WmxrWSEogKtnPbqs/hNlarWMDAeKD5SFhLdR8lvWVmHScorQ57P4xzlGIW0ZX6xjMk4GviCP0V7vut3x8EUvONltquMd1pqYq+CEM7HbzcxkwCX7/SElJwD5+sNBOuKREEAlFsvEMAAEAASURBVLuGWbWtU0sLMTEYweUFzj/u6T3qWdXVWARcw16izESrY3/B16K/hK5s340jdqBSykKtrqZ/uFtHZAMUiFWtyKOxtbup8Gmds2lDqUFLW3CUhBrtzkRtv+XCPoj2CnyYSPSmoSCX9Ch8VX0rstBAENwHfvuWMPWdaYYR+w/BHa8+G9DNkjTudm40kFcRuiQz/s/hXcXLdAI2C6B1Ynjz9wojqxPTTxCWGM6NTZeD42omerJ/wgjPbP5yMJmFw14MxHTbL/M2uSMDSA7Xbcs0+TkMCn6Bldbzyr3h5voKuHCEJFWpsEasBGI+McVaKfNApOOdVUcvxSPFbBQXpq4rGKS1C3YE5aYycAzuLWTKxoJ+fRBrquUoAbVbIj1TlfAbR7HsFqoUxaQijh4mnDGSC6Q7J7AWMUPPUaFKo3hf9QKnuxVjBkC4Pbccl7jhtnnBDAD5f6QgJOexEILvatFdykMyLK4tao8R2gWh0JJwJ7YkcyhY5r6/jgBmXBMdxMAg3u4/ofCsz/4wHSZ2WlwyZGNr+KQ/FzlOZBYBSnO4+U1j6QyA+tkugN8E3BWD/b8CWgRjK3gDFh4ujAudADxRZplSiw2hzyqIe3H66+HA5nEqZjhTWeo6mlKjVdpYthoUckH8zgqXsAK0X2qi5bYD7d58tQ1xq4m96Mes7zAS81E8CRcLLGEtn/GP6AFxBYEkgT8O+qfj8oWgys7S+Sgw1MmF0CYctoGfA/q0wqKMn46BMAj7cTHTRAFDp7m4XAEsKI4s8Clpai+z1Ne7kHRyUqXfpNsYbaD3Vz+txeLDDEnyrDwPCocNtIgZM4HsABHB5x4bVK0I3BHQLU7koeif6YBrwvqVKK2Q/RkOr+ifEpqfKGci+3rh7CTw/m+Lv2kOEAj4+FKoP6QXR5AXy8CpJuXEGLw5vCskCA8SodBio1T72sGS4R0mForAQZ0jtQJVWBVOEd2OTZD9q9bicGkRHjW4blZAmLZmDL5zBaaF8CEaB05CidQtY+5j8krjov9UlzkaU91daWmP0ZaJN0K+lqDzpxh30a7TvoT0UMG/v0lyXMRsPrN66SVpEG5HbpzhtBH/fZJWFUqPk8wNQmyL+CkKhGMNQjBYBPuj/awVfm/V5onFR+cUTNwDk2ilnX4zgWhcRU5HEdLe/xmVn6QsxsJZ7LMu7ydFaVpztT4kwumYAjmjbFi2DcUmpIaEFBNzcOEG+mtvfXkNrFQfnNqaf2mjQ7IbaIXw7LjZg/tWrqv+7f4uMj5EF+r3V+bV1spFrxUJZ3kAFDefDh36KmR26pYmSEjK/JFUk6lf2jLf7g3rZ8vjE3vPpj7kUSisHeSaQq/PFdYYwq4jO5NDi76eFK5zU9s7cSPRwrw0Lo02xCDLQp6X2U1F4ONrzlJt6ciWIkMYOsfEiMLoD9QffRGmaDTwbDovRdMBqq8wdhO43ngRXk/gTf2J5mbiiNjlvEufvsUkmuhkzwnxMDJwJnmOhwwR6fxe5c72/sGfIDpzPcxgky9rdVe7EIQQI3uzN11p7G/7MnjUHPhUHFT5LOBsilIBqsCmlr79M3E0CAHrIYNkhRedqLZRR2Ux/4UpqzDMRWNcPQIfex6x2NfvsCLBILsXOc625SYiOkDJe04L/t12vBJKh55BMRRzWo7eY7p+RQWu1fjVqBhKF85HfOdG42h0o92F2Z83PKjMexG/Un1lyN7jasX3SiZGD5efqP+awk5JzxZAUYlxki59wguhTr5spx2wYaM7wLSIaezz1qT6zGywLXkmpQvXVO1wmqjzOhQcHtHi05YMCLT+Dv0FY418Ifv7mycP4NqXQmLKFpxSzmKu+W/Dh8WLsXHsKfGnsYQrB+7s96u9jdYVRv1D9Ws7oMr+whWLQdOcJBHt4UP8dBTcR8yTkkztEFPKBExuGvmuj1mEFkRlPYgqDNN4UEvzQabV56dc/Gx6f6UvcfPeYieejhxlS4CqkvZKktw+DI6LlTmAn73DnJsvgOq522se+xPe9IQW8Gal6FIhVfs6/mAx6pNtRGCmVD3UhNetnQR1yjEfo8JBToVZFyy/9PtCQx4Ms/kXACWabrVfkuUfoj5BrPxQk+pdy4dpbIVJ8XN47w0vRzQk3+iEsfKqX4TJr7NQZcutYcs0vw4ZB4qwKHsnImv+pb36094fD/QrFkPhd0wLfrPWsvHfyt41lkb4fiS5L9XFlvQtabVZ76M+WrR1pKgHI0JR5N/+hSOFNyDEJE/3YrzSrC14ykh/MFZwZsZ5wwZef/+XFIGh3Qpt5b2u9PmQEpTQWdg2VE0JFvAFtSYYDjxPbWMHOZbnqRhCkjVBiQU2mZoUvghKFvdd/61sH0mXjZ3loWq+OHblGr61BYDtCBVhbqAkdAIlzQpV6n658pGz2ExpamX39WRqZYbZKMTIthcqgop+FlDy8IKZ8WXcJi1aS6hc9ymr4TksIqfyN68HXn1IxEHCtNY3omv64F2Wlh4C3PHcFj8AG6FsjKwBR6jnXkDYU5JCoRXqjQjozPWygZDiov9ouMd/m1Y9X8rE6E/oahLw5Setb/yhZfFw+I8aVTCkKobo3Bn/xjw6XUZ/PvzdMJQnFFtHRNThWjLo2tQeSU7zutfCms/VSHPkva6yz6W0f5pNlA8rBZbHTIaxyqtUAEYciCoOLqziDwrbKBVUqMtZ4p+HGcYIPgO/IOJAdBpvZrSxIWGUel9GniwnyopiFBJ5epQSS2N+91CdBJeVX+iQ9LKdfjCiLnITTcsm7+f0csWWp5KOet8zWJ+59afJQr2NIgKLo7FLq9uecAXksFATdNvnIlUI+ofIlNjLXfsqvo4e8r4HfPCbSq59bL3C91Wz0eq0CnNZUyGebb771Wa+G4rXJHodgCovf+tVhIZRVkPknwTeLWYnmwPfs/bV/EyCl2T2F84GZHicS2J9AADBlC+cZncGwX2ZW2PRJWLWwCXa9sn5DQHN25/oWGxGKIBqaSuMUg2Vtt3TSxcR9/8YlUYRrxqhQKOnn2h9lP6FDPFMC1BPQAyLmaTQazZWHKLHLpjKEszQ1M5DrtjiIJ/Xi2Gtc+Oyc5QI5GoGsMyLmE1RHSAyKDzPnPxQSGMNhpZNjQ/lT7NXZO7GEksQUqqAZIOrLo5ZqxDTOKG5x/R21qHtxTiiFGVaxuNnz+yLqNfA0XlpVNYM5ZT2Fsq3x9We7qVjtGZkCuz6DkiWdq9ORkfpBG4vGb0ApCnQDjFOHGcXxuwfreHhjPf75XOidk2M9tH6xnI6TZSfAbqiSY1PfNJfu878bG9koq56Eyn0ZoCBUPPG9SNekbbcIOFOUImjT9B8UwV/OAyFzFnvxWaBNegbYR8xWCjPvfIukXqjHMZ4WzgU+NpetNUcpHNC+35VRm0T1AyQMfrpkTeDIEaqdeRPXz/OiOtNhivXYPkbJGusJdKJk7Fi219Z85+Od+kJzuAgMXdjtSllOApYxwETzRCBBHYXJFRY8Em5DUgalw5ao+GHRdzrWSX0hiLGtXVpoFuR+qymSKD3tUTwlL0Whzs/p7I3DufNKAuZBiUl1UFhv5UbKiXVzhL6MZnBlvAR4XfETg1pdO7YGRjmFbrY8zZ+N9o/T3FiaNAbKudJfnGpylDKS39MR/1WlAnGEtW8mqzhum2g7pPJJ0eeH9rEF2by/jtGEVR7yC9SxDxZL+3wOy89p9/SOAcdBnMdrSin2dDq4EMR2vs/fGGdFnKYBhDbmR72Hk+5taKXmItjwkcHiG5CFX2rVkahOZsQ9GwXnYwW0vVeLyHEISBhmO3ccHMOrRMwiRJfbVbwZumShNQuYR4Ni269Hq3Bi4eWLh4UKa+AuIFONFy7Uth9Die8ocQ0hmDmQQGwVaHF/y4aTx2C5sooSLk+LyetBFO9UZ1lWvnUUUtasn20eRrLeCV66E1wui9keWxbFCYoE9Bfa2hbGC1JtkzhtSJMdDfxqCYCXHeys8B4qyE/fyLA9NuCdrFM39mW8RlQEQvFVp5h84KdXgWP8g6Jw+rTAWKqEid0/UVnCbRV+L2Jmaf6owIwgOA2EM38eAOFmor3o/Sg2A/wNm3Hxij74EA0BPW8xypMKJI8JQcijJ/4VOdQcfzyBiZxkGu2VjTfXKf3QyKnWSxLi0f/57U2GbjzAE8c9KY/qGmHE/v91FRv/E120dPaZslAmJsScurHpnWR/0TPvDVV1sCqOqXNQzQVGFxYMPuHyX6hi75603zmWInF/mW5iXp6D5Q+ZIocqYIwrsrGmsOtQB6Ub7g+C6yZ2QgjyVp78d1OWDnZmswPKQBy6uz2tL/wFnT+rJSg6FEiupEuOnbiun+bvp4CzKBxxtxoXSt247MYV2927nU+6mPMj34MJ5xWJrriw2jXFqxwOt8WoeDD7KUoDmq+6I8XETWt9KTk3cPZpQ+91KIm44RwjwIgXQX3Rfi5o8gfkmBp821Lb4mWrHk25lhUFmfYLhLCJN1IGaHBYDqGXAj29FwLfHBSpg+89oWgKQy4wtf/GRjSMEHWaIU3Ur/G6VpYkBtlbVBjzeE6zPf1zVvxEjo+loqYbLZnp9+mshp95wNKsteS9o05AgXoJO6gckxjxRA1VWUvSIVI2qjqlQuF/SFD8mUVlwett86Tk5dfcB2/MugbFFzPyjWPm1/qfoTf3ODROqgKvvlNVq8SNsq89oRkzZh4T9fc+aXMltjbHlWCd0GYswAPIhjzeZ1uu451O9ZjZZjEBprvvccyKswqVgSp4GbIUN5gejuVNKv4ccKmBSzhLX/25ogJgz2nCGEI9S3SfvDKHnm6fH8hlZK0STuVeS0AWqz1WYHcPBCDq2+84XA6PlF5uarf4DaOgetOrcE6Fxt3/yS3Gj46pj18A2r6xYC6Qo53AudOWNATbmvZvLePlEt88/lEduJ6n6/Gg3/w9RJ+eAmni2D+1UQ7emhQ15esr44AdRAcYWmDVlg2niiTokqC9YLIihnsy/vIKu8XCu66jxL2sfDbVvt95PaQuCyjOW5HmTn0azxpFFK+wdWPHuHeIS1noscMvaUiSZP8t3ru8SHzoAF8ik5yo53IoAt3janB3rjydR9csyJR2u9jrOKzuJfcRvndjESR5S/KdY5uH3GpeBKMKYxASMaLOCYmAu/zwn3vEq5LJe4WiBbAK9dlevE+080+hPctaxHR4H7bnzm0+fPOyBOogkKlfluRMqSi8zAZHO1L7/mt+hL0x52gK+gT4lJIfmBVTNOxpxUdcm+bSOVP8yvnifnWdgF3WkIeTW1pSFyDHRWMfKMUk+JLOzGW5MENlfEZqq0RtkqQf3zNmLFow3i9BGRwfZNMDog4sVwT4z/tpZBsU9BbI69w1oWKgTCENNbVl/dUlZHgLaB7db4ToVNhSUtDLSc6Mi7ywwe3Ldi6PN/hZvbHszREs8kmsmJIpF2ZiRkRlVK10sRfTRpK4CtBe5mrWYCHiT2hEo/DenCuvRFSSOdrqqgUNbigAPtTA/P2vdrAMRCdVWK72mWhcLQTj2dbeswb3miWJQuRsvOcy0BZCfsU4rGfQxs5MyhHFa9/GuUHSFlFx/Fl1k6hbmIdviZwiNWtz8+XRL9bHfzB7pqofYKsgdNMAqOCAnKoUfrqcBMl9zozptKOr04OckTJWQIRkYqVNciUD3yl6U6RFHpIEWFgV1OUaRU/R4ad3iYEmlMhKbWK2jmgJDrHc6GWrkNYgtG5cMgItGayo4rpCKCipKWqj12lsJWvCbUFZow822rPTG2/OTgmvYgU83gsT++2P8so6eyF6DV4lo3Z2XKlLOsRvvalTmUWqrxubwez+/jUmF35hlv4v8mzOQdI1IJEOMSvAAB+zvSfVyuXGn8A6UJJm/N5VXN5uLPE7hMfMjgH1cSurfEcXQCdU+QYnYMLXKHbh/K3hUVojIjez1t+Zh8uSAZ8YiiSLFzED3ZqywcUlFtKrZ63R8RmU8E77GmgGTyS2o+J0dlh6HMLyxuK5ate8ycSP+kGQC3LSiJO8Lmx/kUv3FtoCI2TfXgXPzYgIznsJ1w9HGeR0PIoXq/dZAlo1/WLGHMqDC1o62eqHn8bRvWi/vywjWhshyAP3C+yeGMcRhD4NcstdGW2gGFax9UFY1T99IEQf6XfBtfnN76Y1MzPhmC100FMFGc/5y2KaWbWZiZHDxLZv/UAQuupET71SY2HcpgaQL3FnGy7frDL66zyZ+Ks4fUU/6Cz+bGLAKTu5rsXCTJJmCCiAxwnU2y5YyxeTX8zaQYSpo85yOlTf/wV9k8jQ/yFrSjAo/w0dWBCz29da5BtSzRrNtkUV1M3xYTc992n5S0/rLks0KLa9T8gUAjxAXXRIASCWAN8G99miQ6030A3V3cO1kvZmIHR3VEgHLgEY0QcU4QvknoIh2acbwlVAdnPhcGT4KyoTBZMZ56Q0wm/uI9+MxMLgrVdYTVqoKF8MffT7GZmCuXVRx5sh2ryOhJQSv/+856H/b+BPkjyIFJIbRiiqLdX4gCyF0tzHINlKSLutXQlUrjO9Bir/uQZ+luW1HZqnlY1moI/D8X8j0L4iVHcmmbyMY2AdmsjUWEMQgoxXXzYHJpQTZ29CRd72XSyfOSOswE1qtEwM0AIs19MdvYbl55+2V9OouKsibRvWj5QecNdW+Xi95Sk+sg31JeSlQ2AZrTKUNcMkS930naxCJl0wwszgmzy+Qc/9BqHIcOBWEy29TX0p3MbuQfySZhaB+Mq/U4PSw2/vC4yD9XtJnuju7sZpHbht2KMsmVIMSdGY4T3br/1jI4vi9DDZ/z75Si/hySUUeklgfhpOB75Krth+/87/piRneeen5DdoqNWgef39vVRFwXXKB8PZvBposJhhi7J4M8LAaob3FiuaFsSXN4HN6lbh9JqMEC7kkoWHuEFy96a5z9tR8KoTEzMvw4oXyZ5K9AuRAFO/qad4ESLoaHJ/ouHtQuTTYC4T4AEFZtEgoL7ytFD/gawSFBR7RYO6N2DCZVSBvEW5emJhoTaCeH9OWhgNM+WmzYk2kRAT6M3YUe7hdnIQjT4ymtluAvtpPZsENJfC3/92GuaSD9Es5NDsbPDysj+n5V7vVUdtR3xKuBvX2QRMOgl+OEghnt+nCiQ8eE91OvULHG5lIltYYCgm2vFKqPXmcziFS0lOGK1Oqa9TO14DEOW0ArDId+Tk3QYRacbDKVpzzN8aiqZWkVkzmv7TsEQG9CtcZl0E5FsfmnEaHnrE3iNa8VU2Wl3j2nY/7KskM4uT9NG4kTEMhWmvmhPeG94wbcDDZVwl7TNaK3WDPfrnIHgA257b+hICiLimvaWKjvkH19wDYGjJiME3+klJYq12nNNqTdLR0PYH8+gaoq4Cev3DDuF0RPg9GMc6JHl3ULdhZ84Im1iAaZz5fNL461MbcY2arUzp1qjWHpN0ljId9PpkLl9XQJCq4irZ2fnoOHxvpfyElLROgrjP1mBhiC9CUOGvLQMACcPe7IRTH4Q8VN0kn4nrwqio0ceEv0xVx6laiQSdLh2fq2DeC/GV6HuNWvF7f2ZORv8iumtL/vIyyUIJ5aBpkhvt5qbqut+KwVxIzH+JbY3Sh9kx1/4dEXp5GTKfzPiG42UieE2oQLpGtQQDGGQIzueHLFG+/K9/wQM3dDGlIM/WoZa/LpdIswGh99OwAmu2+hscnsRWDVuQc17BkFV++KkJ6wiYTSQFvn07/z34Batq4G3OszslBVFpuhxgk2CuPfbbNzoNlXTfM5LFK3sEflo3JNk8bqoWDgBPEQNwXIbSHg3Di7Qp1BNCML/iujJfYpAAm7VQUBSedhH/y5XyuDYu6EnP+NKUfG+y7amL7KyOdKqbflCyeTQj4ng8Gmc6q83ulnAxwX+UZHfBX8kHK4CibmpWYXTXnsFIXXF/Qk7AETQIAcT+re/5u+0839QuFzIwzJV9BOtJJWZFzE69KCwn/p/TJ0FoFbF8/cXFFGkFZEWEelS6RQJCemuS6d0I3DpBpFOL90i0t3d3d3dXft+vnMefv93733O2Zid3bNnY3Zmdk7yMopa2JGIj/Ewp0iWsCawCqqk7HrTvDNUxlm/VurDbHQKTLQYAaktEdT7Z25N2S5zin4pxP71OZsmZW5jJMr3xXicviT0EeRYXro7fYJ5B8B3pfWpF3GP2QOMChRzH0ikXs5fmsgmZEUXZqmkrBxek4Naju3Wl7qlqmDfDvln1yZ4kCp0InoM4Qbgmy+cuMpVYWi732LqUNctMVDZUrm3TSRZbmFFu7KuW9+12Ce0XuVG9nMsAoBdYSrtAaNQnb4Iz7zQv8ihgdmVMLTUaW4J+rLxH8duo0Xl0MesmDZY7zPDsn6tuqO1lo9helo6s1Noik/8rDvgfg/UUorAcR1ZA8bLaJ334W8qS0jweMwmtK1Mug8f2kD6BrwJQXDdweW6jr0Lkn8xw2RrRLI8vtnNSRsDTW6MlVY3SH1DRCCqCVRO0kpqssDDmS449HdfMxFbd3pBGRanIYbU1pHyoMnoezMh2WIZlM312F9WxViUroJWh/a5HLkk5BJ9tsufmUeKzNCMYlMMTGC3LRUvfxyH/+IJcHNQx3jS30T68CfBZe5fL5aYbVPvq8Iurrv/fRTKgcPQBOrcSSTq2WvS4+b6q8PObu2nYyQVpwU8Z2ZdkYoQe0HNxlpnIUcTXoQOPhlfub/UoING02oSOHgqkGLXtVytWppRNU7jI32v50QkMF11hV9Z/rDEIP/6wlcEIPdGJT3+T/zZtwQ1EY2iGO36jO8/WUDSPwL8ET9FQ0r+xBprDruWLwbj+wwpCklN8Do3JUiDiwWVjt8Eg/B59ex+teZVzP04950sFMyrLIzHpGx0gw/bFI4T6Fv3U1k31ANvCsvWiYLC0fM4afZxSkdDDXIP65uCqXP3Zw8s53go05PfAihNPcE+mzpofofn/u9PxaqGNZup32UTfgqV8A5BT6WGX1boPMRdnmKPg2hOdfyGry8CVDkq4JN9alaCfc7tAa+PvHxZFHc6qBZ9162ji1PHv1S49iQWmvTzEALipJlbELUd0g3Ls009dmYoe1Fs/foycwDVzLUKZpyxDHZyo59rJ0xn7QUZNBu2nhBn7TerYgHL3E5XSrzGqM+vJH14TjXoNeSrC4H9F7+3PYhk+UcfwWLcKTSVSa2gDutgRmmxIsz15Hr3zOsvcthj8/EyO9MnpAyFccXRuNsdQYhJkAmDl045SgtuX1lvCsYf37Ks9ZLEhP6/zTqA74q4M507ScH/JscyVOXa5DqljFpz/mBQSGG+n1Dlhzo9KbzdSDzPytCAPuPc9GfSSKgFwH6UHY5Z1hsSN+F+T4xRbXnGg0Cij85ivisCPV6tLTUV6Acajc/TjRU/YqVYXuZ6/CselIsTsqut+hmeYJpU4faJuC3inOO2sPHGZ0N8Wt66smgcSIdYw9usVV5sDjGGDAnXy/9RKeWIIC6TxY6JyzSYwB9obkBiSR7oOUAUrKo/x24vZbNN7uiKy33ke+sfzv0MT9YOR3l9L8qbYEig0Oed0ugO6S/NK99oITbUIFHxXgNp0SR4ROwwtFtPkn+ai/GYVSYcnkZUjLJuTyxYgeN0HNC3X2ecLAj4L1RxnQnDvcAiFq05QmZI0/tvWEuYNWJpRMdU7lbiMmh5NetXeqVyJOihdh4RiqiKOWrI5MOVnPzUZY1YV9k3MqslNAikDq9a+TAa9wtzgx9UPfgy4wKo/vcYByBqeqCdw0YAmxbAMoeVrXHWX2Sdmc4yt1oqZk+ddITgt9PWKW5yZZqrZojbwtzJlsrUS7R/p6jLPnn9maTd+E0UIMRqA5171jlPQgst0y+3gEwSfbR6bHRE2N+7lhkEOvtK49i97FiqKJUCLHSjMaznxj8jcY4fkY19RSIw3elcUdbUTHQx7AppQu8GcvEV/9jAxP/+oO/NMk5PVPeaEm3wTKZjnzVHfOKyz9ZnOkuLRlA2MzQh+h53CWV9yVwJ2FviznuOp7Sl/LCjnDBIyM/Wg22G4kqCpaSWvsesw7jayvxndCXRSUPaxQpookBR1tjQCq3RSw45576koK8f1PCtOssIqBEwK3/1tbUWtTTrR1D4HbO81hElxqkt4o9fXd3GQ1Dql3SnfZljqxRhniGTXV39+w2TpBgeZWJHVk1mBkQuHycRAB/+QLVHRUe7psNeeiZmbKYMOXdp1H77ABcNJhasxKLqk/lQz1QmXewgqWYFZuruI4RTCWITcU0H83mir1eT3X8q0O+5y2OEhUAgl/L4WCtXhrIYNqnaNBCCPthnvTKYpGIEnsM5uVCBpO5P/6NHtqHY4/02qnQYX6qD1qGzvXY9wceizjVxUdMbhaIud72pL3Melig7881wLZqb+Up0Xv7tjHXRoJGO8WozKBvv7g6XWuvshBjktEXesSLiGCFTWUAuAwuHUyezKijqhB2TP714Xw87kTRMUFYTWnkgZNn0UDC49QbvTdku6FQAPD7yW2MKXZkeZEHSsSyCmdkfsDXF0OzAsKDxlLYYzxz04CBrE+jNn6KLDQHD+CeW6sMba6tsuIBaBn4OKWGKI6V/MebsZE1wnMmWxGpuH1O5a1wgAAFskvLLKWbfRrS3ljKV+xu1lojFziCz1EOcdZllOjs6zxxuxiZb+gPlycWuNZ1bbRgOCjYzPx2F7qCAy52CAL3JHCJpIhsiaE7tq4noeehSrdJuh4chwU2K4w//AIE3lSlArhUPMCTxGpKWrutlMdrxF87nYuexDOwmy0Av06+nXJKWhB6YBK6thXH2WRpFEYP9+7WW/T9m1G/xPQkLsF2Zm22ktLy6Bfqjb5WdlQTqNoZvvbleK5/oY/SxZOZuX2j+NoMXiIrS1RUvZVBk6WXFYKfvi7q3qZCz7II9RQWer4VgmYS3+QZXa/ovIAXzO8ZJpPArQdGhqqL8rN5qmf7llvX787WaCSLojgYLf7OcfwIZXc4l/0f2z/RMwaUHPvcMScHSMEDvvbL44COh1KKWZddFB884iplb2fSM+qktZ27j2RSIx69kFFtw7jVt3Z9O8pPF77KixHNePzCkwPGYnmq5yIf0glG77Ia2mq/FdtEAjv+R7v6qBe+BZoerPffzcYI+/oXbHIbnE4MwHnVyq8vvfvdSdpattivh9ghsJA/DhD1q8q9ZYAXhNkI1aHlR3UtKIQeOEu690u7G6vajhiE9qskM3TgcZZyoHPhvh91S1KNm0s0jz4Gxb+kDYgLcLiUbFs99giq1xbHXHqUShZ2r6PM2iLdKSo67VEZH/wTupLv4V2Oo9B07nJ2MBdVw1SU9smYp22gBX2ZHYF+ZyRQiYjGMmMKEgsmpJCfr/zgMB1JroU/f+tc9a8KFQJuzDfYoLKbc55IaW7uMhMrKluFXItmcpNM1+F2wdyb5SClXrCX6ndNIKOfiytSEuX0IHNMaeJcgQjmv+Bq/LeklU6qc6FBbNDUzdGGFlBjtLAxvtZZcVNqclWEzy6i4Oq0Vd9A16W2l56q6BpZ06QrF2zLc//GvoQq6gPKOP7+yWQqWExHA4oRarU2l2WQce9nvIZG5nkNrjMv0kXqQHhV3cQpDYyLvzHd55H9tClGdfe5dsa6kOiTbw6qgu4AUklde0pcKbC5gw4joFvl1hWjSpHUHyzg0h97GqRnQHZbUgcaOlU8S8rZjOFw0Q+u6VP/SXro+a4/pvgoBTlVOESzBKH3ctc3LI+KpA40HrpOBCVMEZgDLEFhQACm7rRsS3O5rZCC6bumtRgUU4JnkdK2JOcqd+tLj+o7QS8xyWEKhyIOj/belNQvzOnyfNtJfC70Gey+WFZ2PX92aPqvIxhmz/6ropj9hDu7wqWpaiG3Mfj80Mu9EuyPETRktE/Swn/MCc/jLLfYMQdxkCATb0DCrSINZrr8v/aag+10yuuqfSh5uKmEoYbiCJw0hpxBdOLEHVpd5Zbh9wsdCqsSGXCP9bgMzHl7IULgxp0H14zHxju+ukUpAWyLDAnh8Wvfrbgm2ET2Mui2THluyxIpbiGPMdxNLY1Nulxe6WcWIqUn3DhrXjW1cSNg2Mv0UZt7MD2UQ79F30iE3993SBj6S1qe7ylrky7x0tV9CWZcQwzEBlqpvBCuVBw5W7dZu2oY11cDRGKLKEaK668uIyXdcRYczzv1q9p/LJ4s6C7napA8x3eidOkHHR0D968d+RDI0joRbrqVu9oCmRi3WvEINhvFhKtEGuenKzhf/RB+tuuGbXgZ6eyNizE0KdEPyRAlQnC9FVYoxuQXrm9XX4Nq85gZzODVbkbY6hC+bHceXl7GPlYFL//ab0/btLIW2dt6urQjRbOMqu9Hu5htUK9587VcPgC1v0Kzs1h8efWP8E2YQmTGIqRPKIz9sVfY3zJaN5ZcF1dW/aobS4qNLLLz9oX2SvDp3fyzkE47SB/uk1nB3ZbiXInC1YqEFRMG2+z/BVoyJfL2lABAWAqID6UGJ1uq+mWayI+9Pl6FQkiU6SYmCHDrCoixN+PFPR+L2hUh69RaprrBqA/6mi45lOzMTpp6GP/90fVgSz9Fe6rJmMVxId1uksK3wb04TwQO4LLApU++rjEygCCHZuniiYQZq0UdBTeX5nxsV+LoiAdB7o8pSEJH7Q2ewjvw4wDhAa4iwx9TBmSj2nWlhWcNF5I3gcUfZmH9Faf5qPLE/fH8GwXW4/EwlPCL1uxg1rclxlHiS3xOQMqJ8vSsX9zSxr/+QggSed7mV+drYIcqbhp/yoJig1UJ6stAqins7i12kvH5dFkXYswZmS1KKvavRFkw/Oja/cCqwN69xGbBvtkgtKYfg+NDPjsrEllCAyGzbdfzW/Bx5VV8rplL0aA7xGyYq9D5Fu/MPk3iu7gcttK/JFSQfv53vJdmpojFqMvPBFKyZgUeGB6dLLU0fdjPugcrgaYAL3D8+6u8mslRUC60OQbMXSErRu/PuteXdVWsjdUWd1mR3/Rk5ZTJXWuVlAywuaU9SfyaQB9pzL9ymA27RyUiAqIGQmooBLQaMys3NRNnfv/54zsPgDCqRyW8GbL4VrsZyd75CoNfT/+0iWeG3gwOG5hAiQERfU5a69++I/ZM0mvQdszRoE1u9eckU2dFUmPynZ6erPEuYOyu9/378Z90i3vrzozpyHmYcKcjcdPFp4VRZ1SzOb711w5eI61vfThbmb+gNop9QlysLG664IAsiNVaegVwaK1YuHhEyG/Sn2PoX/77aMu8zOuu3RswdfZnXDZWG+0LluwW0GkZ9S77mqsByeuQgYr8iM0HbWkJRvAxApOhleexxoLDu5qMw4AZw6t1HABSlvp0tHz2Wh1pgCtpQLRt9lutiK2z+jm6w0PJSRPPuwOcUYj4p85Gh1XlVaevUcAk2sRYk8LsrWAurmgkAS853JLL/4NcmQ4d5G3H9pFt4RghUVy6cxZWH/t4wJuHq7Nhr0VtY3hlWZUhwj75Q8lHVmr8TvmH41MsoWbRULK4SH6wcLXXZrDZOA0tNQZIoCg2c+D5SIFB7QUAHy0sovbNfFBG8cYN+ldwPxpPHVK+arPoECHPD/MaPfcnfZtMNJwQxZSkZgomawjpAdTG5v8KMl8ddkEpyatpbuxOcVBCaMxMRGMGU9TF3NyWHi5TA1ds0/DMfruc3QoCdj9dXXEPuuHaMxp13LmnWhvAelVNWL5sJ4hIMnqLKa5aysI92caR27dozhgUq9Zk4CatSXRvJG/rGjqZstDtRUttA/XiaaHSBVPJhPRe/wDOFNM5gJ032skMel7/XtmOQP1q7zvoivHVXAKNtx7tV5+VL8+GNO1fXz4RwjCaClhmFt/O5ISC5tjpXL5mlsDYUIaWTo6IUdNyN514CFyOHhKY7JDvRo6lqN55LFOFmHFZF7EeXtvt/sw2H/89GldKw8KZ8OsEXNI8iq2CMht3lSflDokbOe1yF5bBb9nstloZTJ6AbAaOCpxCKMHkd9BmHPH5XKtOevyAksOhUtR7lueyp/vwDJaINTNiQS8HONO60X+HHwdk0ZafgE6LKy0OVlq1rYTgNKnPLuUJLpaXoxtHd0czsEzWFLwSMVbnZN12425MF1qixV2EIFovt5LfpRY7l940GDeenBuKXQ7eBlyGPDgAFBDjSg3UZJ7gnYS7GTxd1ul1oe55YJVpB/3u5MuTNMQWpbxPNRNzObb7N5mU4rOlLQJTeTDSu/RRfghfKN+dQW3S1MmvZQr+izi+DuPfSm72HvJfne1r7j0WXQKhswaMEnnwwHsjzfRxMnzJn+VYb2Sdt8QNj42dr+AZpprZyam8cPWo4t332OT4qnl+Rrfyo+cLJbHj41H5atcNAVvLFVgpbJFEJ0GJ+9de8LfzsH/2Q39tfZHrEFfi36aZd7htiLWkl6u7TteUdyWzwF4TN1rWwfVwfSVO7MhibHRQcjgrxKsmFdDqanX1Bf20vW9LVJ3yr4imG+PKD/cyMTIEC5gGmr8mlXOW0ki5wmZjV4rvP1jMrrFB0By5g2jleR1xUlY4IC9Bk9X8lKgoAcGxolGIFJgF2uPpoVVGO7iQnX1YB0ByK6byaY7/A6vsFUVjOVEU6+1+iOd6rDGYKKcfg4e3ZLhZP8BlVKFx7ojawC8ty9O+idYWdt27CXQVeaX7ELz4pA1TOvTDpuuHaPgOIpqEaajF1jThtyIrjkvH727QiSD23e2RQMjVHw03FZRVzOJeMP8rR5CrlGermFibk2r/RwRIa39LGqt3x9pD8eZ3Sr0l+3mU6C/fzIA8QD0s693UlU61VvQ3ZHGQbXV+L9U7wcoOphrB2W2HNOemZg/junpsmKUYq/0+tmI2cf0m6yOxDMMSgnvynMw5ZKZm/0629bZgB/7IDQwjrtZ1dYz7d5SSUfsiaR9m/MYEuZJ3QyQ0wH5Jlk2GTvm3Wn4Pwe1tDbKBR4sulyhWYCinE8KETkW850/DXhUF6kJZdauTOe23fGSVI4T4TalxOhnBULTFU92p305bwOa6QQKX/7xNvdHmmB2inlKoCophA5cd9no59iiG0hWDWXJYI1VIOG2zMfH9T2WPqo5yVqqgk+o4//pn6HSCBShO+CG0L305W1KUX4muTxM5LCwFT+ymJRNsIx5/0bxNlcHUopjCShch+quLrpPeZhL5GOiP0frjkwJKsvBG4nhij838yRR12e4yqtaz9/vUJMiChId0giDS9sh+gOtF3U06L6lwGCugB65r+GMi7DrFzsLSPSb8gTs4ieBNrDEmv0tIh4FjaE8sLXOcztNTqNAGuDJP908aWUqip7z0j9AQ0GHGuyNRjUNkbob0Z7ght9FGlKEsErZLPcLE68Ghfr5TcoFuYQxASFqqWaNv8wB20vrU7AUbpfd5f7oVyLyzCOA73T6MfMmRuGtRk9iNU6pyPxhiHKhRTDgeJAMKcksGkhhiUju902/BgBb8KzUoWFmopVvsj2T/hpZm2nXKGXM4Z1jZlnxHetorpQ8E8nB/4y3OK4fOEzlXRKkW+KYquhbepX9xIskO2XzojDjyOQnAiV/i+lcZxNKIqxjpq2pxQgsRfJjGC2AvcZ/pOU+wUPf6cmZL6k81NTiIzVXBFhQVAn690sikwqc5aIJZdbyu+gSV3kJf//QXU1PzCu49VRuKGQkSNl2phuFI++aKKFkZ80q1HPkxLmnGULIztppyTI+EEqeUwEEynZgX0R1n9c7Aqme5yNxPDE3ApMqVPaM1tfCdMq+G+4gnAp07uN9usSWd60b+dZC8QNBvJFrEwmN0TAbLT992gKsL+4papVgpk1dqSc0FJ7xmLHFWuzbHsYp1Gr4S7f3GJZj4KYMNb3mXmdo7FRSZ3NH0Ca5IZeqRUuLlqBbovG3fMy+FlgfI5d+iKq8frOQKfg75TPuptlu04bITznLdU2dBRW50oyn21naRUkRkCgc91ZXcG41vEsEBwoQZfsBFneoNVmFlbK9+ZsdhdeYUOt8zua8WA2Bts3RO6PjdIThCkO9uznRfUpGxceFfiov7Mjd8rAIVsXWGyVBc1xUMoIz6y9F3xp3pDbEGFHJ7pkvmnRwbU9J5y/6y0J6Ph+efDx+RUUFqLJS1P/F5+3w2KxJKobwjLsZYRN1ehSSFppJYRlA++XJCOM3f+XynNVhiC3hYzpPlPYt2kV0lEjyqsT9FQwXaKkAassbl0E1WnStlcJPJjGjyuVYrYrhGUUDBa5nscK8UjmhOmYcmkXqq8QW75+js7iaWIIupPIGkUAEBaz7wMqQlU1XQW9ZXvMnYCOi4pFRdC42AzFWiBZmo7Ic3K5Boz+gZ8OXsHJ1gVSw/qrCx448mmrk94IKGP/YkieJnzD0oOyT97loyAxPezaI/1hIHgNKLMMTd1l+axTOK6+7GnlUif1Xq2TnF1Qd6o+dgv5Q/KKRuQUx+ffJYPksxaKkja/GDXp5H1qocJRcgCiD+Qj5zsL5NCx+lIy062G/ZO4rZMWT3Izdv0ES6/Tg3KIE4pi1U2VG3YDqF3Ii8o70j7PHhYZHvmHb1FaYrUaewzUkJmxezk9zOWj15NgHDAeJ0ko9v5RiZRWD2Z7bhr3rRHGsy9ZQ/8vesWZFC6Etv56NwjUX4hiNvo3OF9PFKDNpk0GgF+TJRtKepzX+P2XySUWEfRWTy716i9QZnlsPCDqvM2cehgCQgP7p/HUQKP791wnzEgOET3F1GS27wXsbjr+PEhCpPhClZnZGkSku6C8kPimb2xd+gCMtmYmty96xLLQs+aTZ5NRLeHDWtcDiCQEDBuwTUKnhAgt26qofDkd6epvrRjVJBrnYdW0zuA9zSFzspzipxTeIDni1gAjff91/GFcCJrE1tXSwX8FjeF2X71n5of5LjN3+Kfl5W/kDp4OFEV2TyfcLsD6kcwhwRdmZJ/kdz8IqIjwr+SoqmHVoRHzt77ui9wSt8uwLUBmn6lybheD1439FUxPsnWUMjYrkPF4uGcFNXm2Vv5HyLggE33b0TfwqINu4B054dJW0gfJhqrIz/2utcOcwBn1pFAbhjZb/Qu3xyheNPeTysDxKcShdjnWvVh0u5kQVvNHZrF6zC5Cu8KkLYqYrkMzxgzllBf9H4dgiyqdI9m/42EIi77qdpqRWyVaDiEqARAjGMg1GhbqvKytn5UoqtBaiT7hIkQHR1yxK9aRAtgdsMUoenqqE5os0TqesRKyt5NmANHiKiCGCS653fVAQiKfwRx1diHJXz0zl/pKhbnjl/ppcWNeeYz9w5M3diQXyQsSO4+5rZR/l/uMlUzYHyH+qzYyxSlBaEdbTKHe8f7dAs9X3SX7ry4rjkkctrrfs095w93WR91fSIurU9+/05+alFL+WecoARcE5XkZh/u6vssZ2pU3A2u8egbku38zKqLgipbkRt3b9Ok6GA9VwbLxROzXuCIuMDtlw8J/nh1H/6GmNgsgyxWgmArOFVrvxYL7Tjk+uuykR/JvGLxoPQRlwh8JK2nCjkUy2qtmby2REpyDksNYzjTsVwPbW5uXzF7rHjJDpcZN3HsHYtoZZt5+7oyJ5vWagtArte2EWBRGj0O23+DeFAD/snwmyWhcLyVklbtMua1qEikBF3mZLXtBuKBvBt0HFvsOBzC/MWa7Q0vZPcINpMWNF1xnTvExGS4b53K9qqkMZB/IDKbMmj6wZGBdUdHj04y9nncVImDp3HR9cwFDGEq9GlKtUBa4C4MvEcM80p1ZW7JSn3+NBEPJtcPin7cRTyWbbZVsSI4ZONbN/E9GvvIxXqeIc8afhos/gIeHLmxLf/AyiFw9Hg/cqzmXRNz3bn/zjErrHw8WYuUQFlwfLKrV9HXfWfZ2xIHX3svaZ1OKmZg6GUEh8+KSAIn8zC4wa+D84Zvp/nC2wKuZR9OSFApMh8auRaFR9FrbGNVkGUZbncNC/UH4l2U/tkHd6C5WLdgPo4hcrGBB/A/CsRyhnZcqwraadCue4icIhRMeRPrC4T5xHUtHSC9r2wHSDxOiqGr/xiQozbanMsD+WtrJSKlryJDczVKJwwTANXnj3rY3Lzkb+UtTHxYp03Wf0+ybKDTUs59qRS/+ow/yNSLrya71LO+1Tzfu/bfcSxGsdZbmRlMMKHgP75r3QzWGA381k9h3eLyAmnPyOUEG2Ki9BtqcVL96lZDYIH2mSZMpY7SZWEyZTVRljSz65Eyb7BfmTi9f/c7Hy/dfvkubWDjMsV9DM7MJkt1v/m6spJx2RZ51FOFZLsr4N/ijdmh7zXwRIPVeHVB24qyZpP0lOWgg0GXIFUFuq5jaqV1txKh6t7zhZhRmHTxM6UZziVTkNv9FqHZUWs+w21qcJIACkkFBFCQ30Xw/gcMW1UW3XESREsiRzFWLinu3rUP3lP+3rLZqJyS1lg7BSYBAdTREjgvOd5CyCvvDMQAF4omZFpJ1EX6yWyxVaTjvk5GrXx+ltI0tvbDUkIsfUOqGHjohIxG8rF+sm2PLtzwDbnRzMzhoFxAEImsUnym7FzW8Av2qSRTiq/AzKOymS71EK4oXmRFRvbNZAJREiYKdbOXV0oeET4NhUm6tftsUBZ4SLoKM0gD4gKNyzSiqNuPIQXleWHPKXVUGYjZGoW7qVDwelhUNmQiOJUGxy3gNRG5W1fNjPGOg2AykgMJ3qzOXGGf1j6mFsZlDfQynPtEHyNUlHVfmXz6kUBAAUjPej5pY9pfLeHy80Y4og8ykRNyV/gxC/QDIvhfgeowhSZWeIIukPmQQvODCqQB6AocUk4xndK7kusVzqVus/OjKD3uYxKnyK4ajQnUJgjLBfgC7LuZUR9GTsxubRUxDQIR3wxL0yWncxUk9GnPsQKrTIQymoSBK6VpligHIGtLfx0moHLBoCxyWHphx1Eh/6g00i5YlOsRTdAx9/mtzDyL1XzXyOxm15myR0JY3CxdYswayqAYybsaSqYFIt4B5W+ys1lItiSJaa+BMDpCCRCLB9UWn/BWqpYad8o/rCjjK+A6Tz8RTsPu4+7agwXbzKJfguN+Naup3lp6gViSwF+fY4BvCOfm606sjkHeDSngZlvSEnSXY96cetQ02hSDFr++t0uFdmm3YbVhMBjnTrkzVFfGAlKnDFyQiV4TDKDg0RT5ndNUE+ukwA7dZDFRBwi5StwrZSj3qmAxd3ZDO7/5M6NkPqQHOBJCY0i4iEMd6zSJZagee8kIUSdHg76fUWT5Lt/qkGtADy6g49fKcEUr8rDmDAw9UV/dnuFph7bh+RYy3fpdUNavo1zklNNNpNhnodTVmEcCM5P5BeDyrXDzDiHTdXmaLtXwCnj/eje+Ayu7WUJQrOaBzIPwtMvTX8Qqy3+EBspPmEKkb692pxIO/JxPN6srNfTxV0bbB8gXkk9LAeydBFwT1OaE9cti91pfWsAu79LvYah8R7ycvRUf8STlvZhLWRjWkpMBJvITCZavtxVTBQN9h7MCLHYgILJHnhQeO0sjyw23We8JJ9SGUGB8g8PFcrsFwv9LXRUfTSDD8A3swvzP3y71PwiH4KMSMBowewEzniNFn79UjmQ8A3bdAzxR9rgUPfqp98XEIDG37ey/DvmzizP6NVcC6jGeMlF9UlOZBS13uL1P09TsXVISEzw6b1ya3Wz+x9VmwVYc6he66ps6qitPx1UuYpDYN1qJ3YB/FPEKLgPTGy3diVUzb1AlUpkhAp0DZrfrOiaqadIES1XoCeYvaE9hXiHvItMxUTXhFffFBwrE0vvZmdlV+NlVBcBWyCpm5SRHlld17kEe4kHOJ83k6ZNMn+/2PYha86q7//0ixEW7KyIc3Y2E3Yi9PlZgysHvVRL3+tiHoNu7L4Zb3lPxFehCUEXNbAgiNwF7WuK1fM6t4BNGQOGxCaaaYDlBQksqyNJLJ85n2H79DXvsvRv67NGK+m45IYj3v0ARrqevwSjTc8XeDthddOzPIvCgY8eQ2cA1JERjAltCWmya30Y1flM3OTEMOyFWXlbA/GeVXjFxsuYkzVyPWHAGibpF8LskTyhazA46rwbqe6aMXzma2VGs1YWXhc/5sX/MNBVJ0hvV8A8ilZDRWvvAEZvfuwDEG8gG6fkRv20MeIAqCY+TZpLXTK5i0VTyBoIb/fUVs6WHOWtCAEqcPBgynEY6ROvagIbs8kjg2mVZJQUxBF9NNL2IgplwRB4zO8u9oJF3/kJtx7domCNmdASev7I5AvTBZ+QRcOwaSm7+/OKseRnvjaXjJ+Pnvnyd9b7NEtegGUSVlP/ouCFX1o8WU8dyKedbXfTLrCMu+GZz2cKYP17YcmjPX21xBvOjfY5o+6IyDN8GBugLue/FS7q1eb0FOtpVA/y+yLdlNvFIVA2ejVYWxzm1CuIYKpylsvIdn8L0A8+fVjUKi43zh9ImBC/qnH9dyzc/9weqb8uhSkmNUKoOsdK7G7gwf65wAT0RKeN2+1cZUGuoYBB7/y1Am8TSO5EMfNzVPoXFrk/ROLOPydoIiuFfcZGt0bsDpJDBieBK3yjGnZ3H9QlcOrqODKhdhNOzwDfdaboBwDXy7X6dKBRpj2vpl8+uTLpWnKjo1U3Ee2PNO350ntLHsVMH6GCgHjyEpl4JNJiVfZ2MDkPRLZd91kQ/fmugXJAXVQvh9xew56ioBlq8gv6+JSHEq3fhJkZ7iKoo1AtA9D2cmuRHZZ7gB423MJc8TA41fdRJfOymV6CB/MBtl6TEHFhdTppVuXDLAg8YizmY3NYDFUXd37czCN+PKUn9TIulbvyC/1N2zsVF/iqvLTProJ+KKy1IVYaqJuwHzzF4pm+I+Ehp/FpgjRilsQP+q1YThyHASiUmdjplsbPrzVyHRv5OJoJpLGr2xmLCqj4H1QO7GtYy3nqIji8oSwHSuM3wm2Yb/UfiaUQWOMgZ7mvYHUOZp9OJuZqCNJdBd0u/cM9sSTiRiERlUcLIpWi4xuDlCrwWEZT5+8a4eOjK/zN/l4c3UYU4oAxTV/9PBIRK3OzERLkq7H19qYlQHrkXh0oFEkwiR8zSrDL+B/D3X+gbecAYGuFjZ2KBKm16Af4glLiBpDB+Oy4VAGJNXkZeTMPMNu9bzQ9yWsJ+TjLJSDueotI97z71c+nbQJ4OQHTdqItxWbrjyZ3XXx3ENjJtBbroWxICbvnCya4QRpvPGSunGxiYjFVgPhZCy4/6ItRB8Pio/CjtAZlD+pAG2683eTaToG8s+RSnWNRzajfItkGcPrIol1/YOnSQPncqmZdA7Q4+WJA0L12tE7TibR9lFWpCzCJuGB8wgYEx4kYLm5OEY4aqtsV3+glcWY7MkqkMOW0ZynHMRFqXv9F5rCwdmHNDFkS3UAbGrMVu+9g3WDrgBFtYdZ863f2lmQGKFZjPCfKxkZDn8g9KKCltYplQb+vCdYz8MknF7OMJonhUdFzR0dOPjKC0Fhcf+MiRle35QqWeQ6gjVfIkzBFLiCDqj/NaRfDuhcGob9KpLBdFZN2KcXUTKS9lMpKE/FyC6brR1FzTotseFV5mHwbrAZeYbx8oKfR33y3IracfRH39V1F9fhNGfCKATRNFEZUivhHWZH9Wrn8sowr2aPVDQj26bQGSDqQ8Rnl/VRLiysUCjkwh32ZUKMc12ClU556wtGm8Du5/k6c+4RpSVUXIsush9i0BZgDGsgSmmyEU3rOQjoftCIELLEI58WaGwn7OSJcjs7Z45CnqY6VmvePPVMLYU4ZeMor3nWvEhxKojQrIcHG/gUkzUhso5fNt1zEB12Z16aztGjEjkQ0jEzK3y33LRKgpUG+bb86I6M4/yCoihVeLXNUK6B0YEb8D+V1WOS33ctsZFmS3UheRhtYl+LoD/ZgSs6glM+RabhgVJ7qS8Bzz72LojpNIMEI43iHZV9iPb8470kFmtJX/AABAAElEQVTKwElUR4pzDMZMOTO/rpBZ0lM546HV1Ms0xjPM5lJNgUtF6d0xguC+JuEsS8V+Qeizr8aoDyqsqO1sE6u5t/vc7bf3erW3lYNjNuCFTtkDGIfFzl4ow8Kr4vkv59sfIhuMCb1cV0h+HZMO7qrkerzfidfzUJFyDWdj4Exw5ARgjTtvSWqO9W6s1p2KaIotNfyAHw3zP9UvA2BBv2xCFUGhvUVw/EGRGHiuQA0PItqOplrPw25PVf+b1gQrcBfXur7zIQhcbdRxoS+XiO3POBukeTNawERhvqXXR/HJN7KXZmrY8JWw/OcaWr6zXLsGKELIV1PuXKVxnKRM6mfMfbi7VVsyXM3tPul3NBCs69Dcv3JbDmtOAoNU0Auaz8dZM1cN21JAk14rl74QZndryfowXrZ/9uc0WuX/c4JwS4emUC7N88Usy1oEOUxHzKWfs5ljsoBroXMr1DKDH/Dyls6kWk4uA4XtoeYMY1WAh8g9w5l6xBngbBgyHxuw8z7Z7/t/EXeBDQKADUMyPLV+UOn869QJYZPj9Y3QY51JQ6jGfcXO9jHpnVW6JYeLEzRLNM0mrgFduqzyaf7fBLPBddDsN5Vh5F8T3QTG/olh9AebUBfo20s+RqaVqCNUg5JsHFTjUxX2F12JfdNKM6VEbj+2A7Euvx/aKpYq+CcqbF2ZQC6lEHOthNTng+pWc7OH01J/h87U+6Ljh53I/ztfjdLB2KQiOfuC/zV6L+PNgAHt9drHtqmDelBQMt77DECYCghusulOFaiuy8SJxOnh3udktYKSEczfSoEtJNMXKc0fXEjaEfWfwA6XK8CU8P4EMCXduzOku5bt6fY66wtpwhge4uuOhPOQ+7qRuFAN37jqOh5izeu+7+EvzpnChrYtW27wiqM7FpLr51wzJvv+kzrrSFAXYtfz23tScoKG/7XHr29znnerWtGaFyJGE4FqQI6GfvO1+l8VZQ4jQryhI3QuDrTorY9a8aPFdqy0C3OJVLAnpCxGDHg0ltBPlMUdXotq9li1dxMxA0RYun28yZ+I6QsEozSSAP3kE74DGzE5CH56vvLAA57nGy6Gf8ZbYKImaklWXUHmU7bGkpdy5FNl/IAfuDhWB3LywnFf19CVkaCoFfosjf91lpkFaSPUNB777s3d39vi5jKK8WsnGrjmFaX0UsgrBQcQVHXoPMsn31CtM66XyBsxybj+HFQD/VarlKlo8bUtZdTvMb8uXYSxmi78nCvU2ksSEk6YvjSjVS7mngHu0GhNTBunCeawi+W/2iUxcx7B7DfSrOII+dlH3UqMAmLdAVIIuckxMLObw6sw5NqKRQu6G7P9Lai7Vs0ZQ3Ol9gJ8nyQhKZ0mfbFm1L+YQs/w6UrVz3e4lUIQbHpZ5F35LKMaM7fWFnKSDYKvs8sLmXYtiPW3hMSdatrmf0CzUB7aj+4lE4mmIHOWmVEdIBHo/iwsbrWNAxOA1N30b+n3UTElO/YHZnc97m4d3bmMzSOfOZ2aVviu+rfwYuB21IZzssZ0upTAumJrAb03ODaYPlBoOqOi3Okpidj72pHhFACOx4YJAvvriKj957f4DK6cpnuZbmZA8Jp5oYcY4D5rjUUq1fZC3MEBt9l1+faRssDRHStdQOo6hbSqEEd04YmCt+fEEkbgYQ+B8RnLkdRi9N3wpXckBj0tlP7fklwfxse3zU7mu/vzEABGuHNnKnXy0WeBb6CfcDk35esze8yJ9NmftG64HYUbqDQhubAQff7UVF3O6lqeLU915qP1a1PGEUS/S2wzhiqRHwUfV8aGLs1bDw3jXJzQJp/kL3OJX/WfypJKAOAlLBO+FhGEbLkX9SO3LhuPHtTBwngZ4r19D3s2WHM52VDACEd7XBafeKvDDPqOD6SMecllhK7lpuPnl+eLACcSYo7sxEZlH6K1uz4ETEV2Kg0hBQRi3XlBLs4RoI9RJRRQ8qWhvmot7s4noVDdv5pb/Ae/+oZWujbMQnGIHMPUCNuWGuIQZ1FljhkTt9CK4NC4HvVbaJKOMu8pJn9JjhmAwY0QyXjQ2oDpmHXjIdG80usQzcIwWm/CXVtLg+/2AwujL1AG0dFwPcBOCV163/TVqt1yx85389k1i6sibrxufvln+LO1+lgT9rtbQzSuxTxVUod/dfuVlXYyoawktPSn8x4ti72Wm8JgiDLiSYPvGJyQvy0O1EpNQOkQYs1IY19XSywZicKUVlYnnLT/umhBPq7nawI6pfu2S6fqLLwQkGDApXsf+k6i8OapPxthE7PbO8bykiv9KSLT8qZ+Z3Lh+P1CPpbevTAX1654odLr009m3LqM2EFuvl2FpZ6+4VBeugaYjkElMonZluPctRI5D8wVChqX366Bsgezm5ryB7+rbUa/sfMAxEkdLEPA18I25yuC0SyKrSwVEjLWd83NhkcXeCFS3HMfizkWxLaXIlF1/O0QFEZAy1hOPRCFjfMjz2RWVQTOf7xPZSlZ5CPuFcr+LEPp3EXW2jDLAVwlXm4rzeO887XJHhOzw390A5kpz0XOd3D+Yis3jmDl4OZiRE6fd70Vsl9tQtogRt3xA2xWGMWRvjITMv8B0EamssQ0YSmY7AsnY4o2eL9JUybGXBmgc1368driU+OcQWpTf7JcOvqwa0UnkMk4X+04I1UPSVCAx1ifubMkbRD1oSNQoTTdTwlMX0wP4gjNS0xgYWChhu7LKLMFOXwKSLBp0EgWoGr5uaeltEaLSEzBeCDPK19YX0gZ42hKiyBzDWJ4BYVsfV5gRyOvKE/hwAqFdrR8dLOOoqAT1rMQUJsXNisH71lhvUMKQwWTiVhLK8sJr2CprosJcuhonG6+9y+fy/LCvEzfKIk3NIlbLcZXH0STafwM9NZ2+Soaf0FXEBSBv9GN1euSY8t/1O54H0X4Ld1NPF8XqPW0n7tY9Cj7ZAiVQ1lg5OwQmtGWTxY3v/sX71zxDjfAIhjUUlXCse7BfFAFC9L+L1C4zID+hRJVD67uSIkxSfBXmGlCBr9AM8Jy116j39+bIcXgqwIzaOFhU0OE9KGe1dM+/57i/Iaqv+gmc9ZAj9sj70+tgpJODqp2g16gllOzIZOAcZr2sUrPKYyGwM3suUmeyhBO3DtL7Ky+A1PnmjJNUG2HZLAp9fz/1ecVwFiAeiYFeGXHZe5r3rE6yBIIeBVb/2PmX3sIqTFmx3vIv1/mMw2uELRGGJyWvwWozPxVifAvhhNoSKAB9qY/uI8JTxjl+/8bOnyv+BlhROL2+/GN53NwMPh4jcZEjy8ZAf+fqII+TR3+WK0iOrkxnc1oOoHLw4g4GzwAaxCeQR+bpk3omQ7Z2lZvGcFMftVmDuWtzZe/rZDtpNhAaVigylkCWUFa8//vRRPKaP129VqZy9KOnMeWMUVVnJnyW24RhOSoTnm7E4d/hEVymSXeGo6MiGTsW5Lp/RQixjFvDNihJOZArrOSM7DTsXuSStFlqsT/db8lNbsjaLm7TAJ/5QYs/DeASyJEgk3MFAvTD+2TNiRko4yN/mlDE729BYhPI4syL202oXpvcreebPTtC6sokogsQ07uOrkggXxanY3LAtVIDYxzTo3hZiEuWdoNWu74W8sHvUk2Znw5GXVwR7Ld7OG35pluWgzp1xP9HusAmfMuIf2EoCaii4D/fFt/l5GGT6WHHGxMhVYoGwMehehwS73aKwSgLU8TqbUygg+2AFSzBx8AVLIgp/bcRHCpTliuNYEZR8w2k9RCiSopr+D0tg0h1wmL/LOEBHIzR/OIWpfzBEfXLYOPsd5H+VZZWXPgu32r42fM9F8FURcFrLQNkjdUfY5v5uPvtATg04ko7nCJ7eqGmKX+pUTAVJpp0uyCmgLcSEmPDAa25H7miqZQiFfOBWbpHMt6O5ChtVMDnZTqLJqlY+7ExAg7h4baleY4bNaSAelok5ev9oXfHyF8X/Cjq+uoJYQ6q8o8YqMebCBsY7nILeJQiSrEf39/nwmgZmJrqKjEtIYe+Fs4Qu6b8OqRrZFkyTPMue5RoHWDvARz0npizOO0O1C89e90YqXKwOYMK4XZtaY0MAikoca7/lbi3i16OXuRvB0wIEePZSUMVcxQAYW44nNuK48ZL1OA/NL7UcPMQMjpXJKhQXpeI4FX0B7VnH+geVxtxKfBe58a/w1r40zTODXct/9E5hRwRmfushIKff/1FApiYSCo5hmZqV7U6QyHtVYcHM/qo61i3WVL0s4uKwGmCFvaOv0Zdld1KtC5T6OcFoLfsrbV55WTBpaMvBO/Escna9lXJOQ0H4HFYiynkQ3zQA2K+hI9pRW8lJr0jBNfWpYrLJ/agKhtv9YSTRUfoUYz7AMNIKiuTAlfuNPn8dK30rAO+PtMJNlrkW8AvZRbxfaxBVm0gD76yLmqpr/4P26maUnUAoLqalFUKSzi6HaSH24uSQwivSwYE8YFUIMoKY2vcpBtF7gKWBiioTIpaKx1NY17wWQn3JIJN53ALFugelUcIoguaXGzYcKEQYyx3Qaqx07Mo2gFtDOWfculeIA/efpgH1cRf1/WcytPtMauHkeOSsRpVVr9njszQ+pQBWc/H3qM3mchcBcrukpeOiXUkJN1n28IQid/r7rk9bFbvZ7DxkYTKyonduXSAOPUxZhh9/S8rEVaMw5Qfuxa0g6UxAen1uUg0JFcf4rx5nRsZRtcDhhSTxc++14wctHtdDmjEeBLUNI9KHaj0Uh4HvsYJWuTgoiC/v9Jcx/BoN6mbDP5uQbV/Op5XZT19yHzmgjuutLUYGAzlLr5G68JHn0WRHzk4AGRviuFH731A6AMfBmon1RTeB5+JCwp3M6WcYl+Vr41pfjDT7iwEjDT5PT1QsQJnb22LBL/g42SRX3oYGxwiHvqE2+Z53f1WnvO0C6Z5uOS4XgOY8Gzpvh+P/tzs/8BvJcBhCoi5FrIcEFMDXpgSiKRbykO6R8/PCv4JRLYeVihzhVgjZ4wTeElwRdhOEN1t/82obNTer75v6V0PIeB6FDv+VD37rYb8282+G48cJO7QtCIH9nW1GSDrpJeUaPNZAyiXZJqdWJy3i671QIum6pJGwVB6kbYzZwpxVdtntEpHSwh25y2vwCHds7SRaQLhuBydgiwBid4ND0ChWv619nApPMuQAb7lvmYkNV7KKAUMLhiqaLrfqdDL1bwS+3xQoVcJ8rF/aV9Lf8o83O8optEvvll2gsPbjVUa0PALg8zMdr62yR+RVywQzqLUFh1p1afBho811yJB7eZnxRdxkfwMTuAEcbraj5lZQVhcsMR8xb6CBuLLsKquR0GoX9frQLcgg0+i8vB7hoqrrNBCsECFTULYvQRio+4Me7BSW1kOCTKJNlG0nUVE8CLZ0dgShbCh7Cm92Q6n54KCj7lDzbay5Tnf59m4KEMIO+2MLPVhBi1tb5QHBjQ8C3ziFb1myubIii+tqS353z8vu+MoO4v/o+PtpkLCWrtAj/i/bMmK3eHqRxWULRqd2LRHeK3Koi71SejbhPM5GYned9haXAqU3ID+vAJ1Ku+s1w65qZpVQpuN7OPloff9JFaRaXkYBFE1XsQ4O1rEWR1K+GFqeQoyHVXa9a6+NIfT/Sa9G9l3aiczmQ6/4KhIYfuXhMJ69AJ3MYaoRj+b1wT8+upTyIqrWkrOrcr9c7/d4k9rD0Fb0lKRScE38tyKKNkx37IMpOUvczP/H1AqvWAFj4HOwIANrwfnV8on5QomGoTVJ3p57aCcVHs9ucCNOysERnskK4INr64/c2pYoGajQwquaVnsk7nyQT6mG9udPLHb6CABLGMqKzfRth5YcLj51WUmQbzskcJoYbc1W7G6BhbqfrDTJrETHJnB/IulpUVQEobUw7Seac+xYOvLmd2aK+77twdFBWIEJLZd5nCCGQyWP99Ie4fCtIs+0DackzArvjc66ywvZXsX55EfPOnaGJxstkEg0jxT7Juiyw94ZIEFzIUbvYo6e+d2Q83R6KKjT6zlgzcYlXxJ/P67x/6GLF9+fs/E6wVVIrcNcQl16dS48McEc/2GR8H+vedGQ4w4aEQneBcDo02KECqKrw3PryPVa2czHto2yANKp9MKhJ2XDFMETl3Ks1WaCqP4/I/j4KPuYymSXQGyJqprkXYd30sQ3p9bYxs7sIZf6I3DSnypQRRisula30sm9WPIjFngfWBBDUqPSo/W1YduBsNwSF3AXBpBw5U4OH/zDIdYXslJIIKeNs+CwtrDGKqVpe2Npk06c74Gkp5pnhMe6kqES8jSeVlB+tQnc+kYoqa/ZDTuiUfxllSMHZgrx+PIR8NHioxSjK3Sdwha4R56+gUW93aTv5LmJB7fSbI4E8DoFeAuw2CG7U5wkeHfBDKckyiev/8HeJAQRktJP7InnksJqcC/AiyH3PuEMrmBd0rNsVEMm1yvYI5LFT+rxVz2KpXwfeZaWUw/+GHanZn+EIX3y8LmelhBwVZ+lMc3+DF/46/vgzeUSof8TQFeX4Yonlz0I8Ho6T3F05/0Ir2mY79qgaiPiX7+v2NAdyCDtEliYXabNBHYHAup5YTVTmADCrvcz/PJN/l5z6MSeGoyPCAXsJTZoQESYznggQQqViW0w2qpvORut01KqndNyP0HQcztaXba5OVUxdmEYVFUcdhgcV1I6hWtHh/FYDBE4KYoLOUAX4qlDDL/SCBGnHEiROiGyMNkTs9pwTn4TcIkC3Y3OboVlu8mnvCBjgjADMN8b2A34GhE7CNxGPunUM2RsB97Qbm7y6gV3eDFPf4WILKSpOE1/UghaUrOMSX8kxn8RCE493e0a/88mNs6QiOAqhs8D1ZTLVZF1xKlLQyEXjJB/VUP0BPAD0nzYp16EpvEucRy+gi012SZ7JLrVw2z5Tzk4LpRzK5Nd1u3WP9STILEZIgDGiW3bbqmlXzBoYhrQj2CoKQortO1RyFLMCt5qf0ZWKGRsHDUiwmIwzvLQF7unExADr4Ld8H7yodtJwhjNSEnOdd25v0nJRTmOcrK1e9OolI5sRuhE/JDqhcfkX6ensezfJ/bfGp7saVqoLF2U1SEb5Goss15gn6HucWl9yQLm+x0Pd4RWx1BKXINL19XDa7hmOtYJakNGjR8kB0IvixjheR/uY/GjuDfILYAszTbAfcdRu+i7rusKxwz8QXpjgoFO1u6PujZUqeU450oiLcKTHCTXFD1k0H6ai6kshsILqyErjLyZdFF0Vs8dEXK+5U7/wK8nvI9aHIIteFCGZh2Y5bOFbqhwHExS8HjybF1yxfpFd8licemu/MAubfj1C8Tr2IXRAcvXjRkdkPizcWUV1jJ02G+T34vPRK8de06YCPzfBhJSA0UKpsaIgSUDeUbYyNREB+fkMbsYj5r1mHZM6DvUwHghKtADhjBzEDVEbkRGhjMa377swU1udQMyF+GjpODYC8vsPvGSrAJr1XFJNs/9UpmtQcpAoA7OvYbb1YK45uGSYt34mmRdsZfb8Iqg2zLGxBWUDWSP3bKv22013VhbdN2I4yCM9mP2sade4tdTFzBEbxzdRuPtva+Y/IiCSlEXvh4sYZHy/doBnovbRoZ8AbUjbnztoyqZrIINt/+ePlwPuvNmhy5QCPrzdIpNB1EvPAXHW+84kn00uS5wqYooM87mlX/+KmzhmUJof+x5EM9ymBWUuz3JxYPxTbjEwccQX7WFRSf35nSxPahVp0ZheyxuOwHahZapAt6XmIayb4YO7ZDalEjAi2cCLtkzvX8djaQ7izvvvg68/HwLyeUKbUjeCVXPq9Zjoce2k+7K0vDUwQBog2Tjpclu+jm7kEcOcD84a4UqajiFFMyQeC6kgsFFbIZ9aS/5x3pHbSH45bLlWdfUc9Gv8or5paDFGEK9eRKFwSN29Kj4nr/td8W2D1FFoNCN1AWCw7KsF9IBOy+e8fW6za2n35j/kv+81hLPFCKie6r6ssSfwvr1LQXFiosq0R2ez8fMhW9JSWr7Cr9ZzhAdycQv7PygxWQzZ/m8a/mFPpwTAxIIStzIAaLuznfgngBjFrj1gZXJQ3eJbN+ramAnSxv5h1ds0Oks304E0b07P0GCS2YYvDjB9h2UH5pXIxGL7+yapCgE3oyCA7trf85TVFLcAlpGmqBhlVsN7cMHYCBk5SKQjoqJiDSLMQKAmCr35gbrY8Rg9Z6c/vq3UauLKZ1EP7z4aR9YQZtCeyKhHyftV8+KXugrR3cZNV1ZRD1jNcUL8btfMftkCwSNIqLXKp+xVeyBM8omqV4hZSE3gQzj4yirXZrTfdpTpmmEO1uQ/rcRQZ8tIJEtr2FHpIjynn7pet4DcUUSNMqz6L19HTFOPjxMplpPJLQFj+BDn96zFzxMifgz+t6KmZDZQQ+UQgSBKMLSP/BcfsrjJROzd7N3PdGHHWCISptdxRziT/iVwhxtYbwlyePrRXiGQw7LiU9KJl9Nn6+XWLZqoV9GS6+cZXufglqHWWz7AMORWx//GmfA84Xs/EUcaxj7cErm8vCiN88WTcJzlXVWzxMb5oBcCELoXd3AHexiSsUQ2+z6Mvi7QdrErVT4dAUtv9RiM0hLLeOrkctQNzudpoaMjJjkDIaI0F98Jer4YveoADZC9dHeSrqU2RQnv6+IsxzdEYCQll3BIGfYkJPAShAS0CP1I8UhJb+IzTKNZJFfEpe7CCDNDT2+lI4nkfp2b9voLB045kSVVxmbVBjlnPlR7roDioRXFl+Zi9rhBvOGzC2eBZvxoA/LxyXACpz3UAEHTOf925Zcx4PVteI2GAv0ABguEPR4j70tC5c1j7x5Ja/pBCl72rgVEhH5hAe6eEVeM+IsNt9uUiWuf6EU93Hjjrww0XCbGOcHEHc1EDnE6B6voPn4120j4PpyFQhu52Rva/oVwgqN74TqqyDhlAvXwSyte/iU4BTOIkh5YbbXnW0pkM2QxfupnUd/29PZlIgh4lT27lvLyaWEK5detsx1FIGqIQTw4HTFbEbI01sYNildTZj9jPZyEufKizcWnR9eE9ki4Q8T6UavJNYzEFrJhQ0SdDYB8F5+eMGlIuy+oPM30ifA1g2p3hPvu50KJQoyJjqYQJwVcmBIho4S7MnhrK/CdK3YDgrZTpNmGt4rq+E/IuU+FOTH767L0yBZ8/KibfgHy6Ip/iGmbgPtJjwgzJ4Nw3R2nhnEkxka7HyL6Q6xPmoF91FqyTth5kPATs2mM3Y3FLwXTEVDLmqSoy9Y7r3hQ0cklsYWhcuoTwKgpoHL4btwM+dxAtM1Xmqmc68rKxL8262lg9WYuOJuL9FvCTDvz+Qpm7zIPhwON914pSFy5BamIcLhXAL4KpU9rXzFBQJv4Sk4pSMlgBJpzTPqGFvzeXYXMsO2mfWFLctftm+f2p9QxhQ8VkVxFV/MBG/Qyt6KgSOoo7s4O7WJaoN4VC8SH7fUGfcqcOWPQkyIP8/remcOcaf60NATUqTlns4N1nWxG1VXtMI7oMo6RQpPox4v7IQaf3X3c7aYebdHq2+gslhTGv+n2MegBN8CJsGOJZBu28k0hNA0v51Yaxyr7dz1PvziGLSieVR9BDpTjCRkwKW8gSlxNpSZFcz8vMCVQOKLsrHjLmUMSiaZ2IWjmLYHN/TIOWLTYwkBQC4WKr0vrB6E6sKbslO7c5Psy32gKl6Rb+5L5QhdVBb3KtogxN2Ww1ZOZe6759Plm9fa1ZjWE5qyuUC3W5ay8PVpvqdFtzgUo2J9kBG8z5xMWGpkW7+UA2avTe0pPZIzAxMRGpgvuUaR5+7VItu2ifAoTPEWLyY+d/PqYx75iyKkd1Wxf7WX1Q8cMJXJKQ+lr08Ws+VVuAOI7bnlGqkNsZn18myONTnvTx4o8hzW0J08d1guN84jFylDSG5tfHH/m6LWxLOoGGgJT3+dXdy1s55MuJbJfIE6jkW8GQXD6ZP4ntTolG+BJ1ZHsUYp1L8qNu/MIXaEM+8NouugpBDdwM5js1D/2Qp63dibvI8zfAEDk1l/gazd2PFOV7tgKWbitXzW/QzYUxSOdCFO7QhwOjcvYcE9JRNMadWccCffDfLpIbu4nGtS+L2blz+3LPw4C5zGr1m7U7XKFIOlatpheHbH2DI8qDe4j+Pqt0BC1n58UPcrqsyF5jJzTytxtpzTioPltFNYX31tG+MpfTL4Q7qSx8lpqsw12kIKTXpPOa9DvS6RQqvkU0P3m/QAkwQTFj+XUvBGkuo42SLX0oYKtOSW0jhT8hctNP/9xPXv1rxqB28OxImlUGjy8SHx1cqTcbLjj5DSJ2Sp/PxV2M2sGim/dWumZuXN457rMdgL1VZm1qv4XQsTIkticSd01EQGCyg9AK9tokqA5c02IzADuOBB6d6Vk9MGXhH0ZhKqNKn+i0w2FRzoLfwlgyH5fVhA9sknCeLzcIk6s+07RQ8B6WruxB/6TZCKjBxmJoKP0SHZQbv/I/ukWbOW6XXIF1Y0bunrdL8hEcEcw+Pfx3UywYBYaF6rm2ODewsmN7d+1X7bcFqjDvkjWvsLxsHCdpXzmNSk0jtWhr9qJbSGGMz7xNt/a1phA6UTUwdbBeWcxU2QL5Im0lNE8mwlHFUUTXYnZjYRwmfQjE9Jj4N4em6Iv7LYEHObAILchK/wM+fzvhhEb4llsumZR6b2Jo32t6sB4SPVyDDlJM6G+zdxtEo+phmPxHoMgpHexEy9EzoeUDgtfnIDk2IVXs4wj/OS9L3tkaznzh0OZEYfDpT+5cI7h/uazlN5oB67NN5JIvODFCXDhqXkPcXXw4Os689dflU23KFEb9919587xSGE5gRVMuwtYis3mzN2g0QfKQ1Ix+KIjR8LFw1ONHLsTAEQscs+KfiuD3DTbB9SWhPIQaQuHLzgxtfsgwYIYhjuVAGkDdS415pznCfdtqBWqB7mo2ls3HSrdKSkzMKSAzfhZXfBaN7j7HfY8TUFnWJgGqT/r5baP7SosX9xfwKqoGfqudu8V2HZcv+N56pV6xtBXx53iNgRn2zDAJqmSp115Q1H8oOiHjlFXGQTopDiuWrodhyzuWN76Jd2fmw/yW+rwMYyG0Bcppv7Mfa7myXm1jjsiPaQkhZvvtYF6J/BNqxZAjgRYoo7ooLbfFI8FS4mA9hNtwdwG3X7z7sbsiJTYYLzu75IeAQaN2mrxuRBbIppk6lgFMOn7dBKxpvo8+Ee2j9XhHsSRGbSYIlGkU6MeluRtyzlBwcZxq0MFef1pbDoLwXxg2QP7Iyq7hsgB9lVXplVgZ0v+KktzVJK8FI4TcpXotJ8LDpxrZgNgU/vZUJVk8VTvh98VToJu/zirn+nb8nrd9OfXB12Gy8XnEb4S6UR+JyW8Ye01gWeZlHtncXF9ropkv2UAzo347i/0Ye62OPl+Rrpq7ATrdTMW1Kzjx5OnLlqc7u+EWrB4BrmK6890MhVivP7bbiKl50WP4z92xRPhseQS0RHqaFSsOoXu3mxA6cPVVgU6Wg9d82HqbhdCi6OnrNSxMC7h4N5ARuaM7WbESr3jfqln9NcO31+tmlIEMzhoPzddWQ5FVGR4FXqnjw6RObPJG1S2o4Yod9Olo7mhdNWNvnVYkvufvlghhKij4/Rh2+JDBfbrI1Iiyogcz/YxP0ERHNpQpcM2pF9qP+wgdUow7nU5JfCoytWz8r7ikBZJzJDyD3/LS5vNdr9s+9AUV4etECyEaxubebaPLD9/pyp4WIvZSdNNZ5uW5cvYIPQACqo4mqNsj3Wxqk79E9oBx8D+AMzyY67GO0zo6YlwwMZKFvtYLQ8xcVmF6fDAshZ8nmCHRWVZ/6z0083fMwRpaP9EOlfVeQu610ecbPgQxk/PG5m+pE4ViE/mHRee3yct5Hp752NS3UhP8REUf9Bv9uTn0X4p23/bz0Z4QScPKxbEa4Hm+U+9PUSE6M+JzBc5dsZljkPwkMZAgO3PrmMJfGmTKrUfw/uJ085h/rg+z3nBPp9S3BkgXGmgk29pzpFahg7dAS7fE+1yTrK95Rn79XZDkEBwNg6Wqm1kfBdFo/qpqcdpM4Ed9puuPPvgK+KTqN7St7SYD1RvijVHQRpSN/5SRP2ACnt4Cyk7iRUk43brWN4hES7pgpk/Rs6ERXsx3JVS2Ytl7UnGdahC2vmICVXt1NhDI/GZckDjiBKfzlxPRIeQCinGg1n/pSW+zPWJUP53Octw23wbFRfNY8RggjCVeuEvj1pXaQjTD1p8t9mlQPmzjJSnljRMFPR74rBDiEQ9UFWE3RVlbwPAnZtOuODF56cnyCUhbfTerj6nwWnLN8krYjZ8FDe+DkpqVOr5mp5j0j4iaZCuBQudEfZfoIyFpAhTcH2U6dmiINP/xUms2dzB0GWHthYbpP/rRnnQCxT6jwuEFUCooBiVXG/hfOJohRb4AsA0xiKKkGmMuL5TWG50bK78UqTN6fauI7ur5APIUPHX5CkQdYlUKrBcaig9JbPHxKTlozvck9MoiMiEcmFZqJ5isgsa5TudQCxvt3wxL499imAh6iBTV0L5AUT6f4Q2A2RreWY1eWvGhNDKLRGbOvVwUkkjTtyFf3+v7jdK80VZZyM74cuej6mgpgSuCm7An4So1l1QFZ0LdEU8gISn/8VN8a1YZUTXHj6f2Me8pqgk1nmK2MJkWLm/ZJ1NjRMMlz8C14lzffiJ3KYkvkGiK1o8WTJTF7UmAFbQudej/QVcmgDUW1DNOBagI/yQg9nnRYZehenp1t44XW87gPNQXpJ5iypRzCNq+ph9KS1HE4Tg266v9RhIHkFhprGAeQ044ttezzvtT4Tt8v9UtwqurQnP+y4TBKa3XOqh6ZseFATIrroMH2xnPQPTnBDNERVHItXinGMob2e7X3EdlMrOBFOYUyDM24HWtCiXilku4cmHLup4SMegp9v9Ae7DLS8XmzOxoFOZ25R65ghEdE09afkMS+N/WoSBwWlKxOK7hS0SL84CDMJap2nsfaetRni0GS/uv7o1hCDcjGeKfUg5z5KqUEdz1xJf8+UF/qgy50A3fBE2+O3I2DmK6ctPEZADOHbdDd//QCV3nWcmEc67S2D7UgEFVGyiViryaF015ZzjLoNc5aCSc15gMgKaENJbs8GYYHv2zTTbyV0YcL/msz9Z+zoPhCrrwMNh4LBiT/I+DGTGAGjrdedTl6oOaCWNYgrvJe9B36/3zE81p9HgK/cbnZQDS4JB9cnZDkTWfoOmgqX6HGGVwTDllkYv75WTEyV16x2r/4InlaxfGDTqEBcxUp9AjSQ4dnJYOVNGAjeUnpeeYvtGmmeKqW41lm8TqC1BxfnSZDppWUVXaNZT6QMXnkE4KKcWuoftRroFhCy6WsQXGpViuIHRMRyWzTI8NDE2Ehps6pQnkk+SXBBc30+TQQ9zLtoAsp7+NgeNRgekMVJWsSQIzvj7pBWR6d1ypLQvcykzo7UQZ4FbFbOzntwHQxO1zsvU85WtdJxiuJYgWYA5qHTK5wqSEect3JMYNqqJnxZeEy8blc2BXpgniXzwjAY6QDFKPgyEhblvaBNfppn3to0V0/o6uNa8nb/COVI4w7dW1DsVEFT+WvQ0g5YjifXbiqlR+qYDO4DcEc0GDmDAtf7KdLKkfnNRwP5x6gCOBqlSj9Uoz4hVEnWVTUTM+6CoFZ33CSWZZ8hu1ewvVh200AEW1Jy6t7NBTOFMZspoolf/AWR70Beb5s+nqjohKBzNzTzzQ3od+XA4/d6xDgSS2jzMptuZLK4TMdfjkdRELKSabFKgKYpusD2pQ7HztmV/Gbn3auT5aJ4/SKFd1iGJ+O+1gsJBPC7JSoBBCPV2G7K4M9aDHF3KlEs9mbrjsTxzIH6rl4L+tjvUB10CVWnsbn3KlVj0grkfK6fKO5GQPb/+RYoijflGYYtdLjy9+rVnizwTR7atiQXNl6DuUapWfEY66yXTutGQCi5rlLzoyvmYgKuo+t4b61A+4EKrNfSayMZv8+ptAAvV3Yd2Se74LJcf79z16laiJ8c7fpFhFg0FONZfg3e3JJQg6BrZKfliEcHgNj3lwpBS2ITwK/kEiCw3OijSfVmJGVvGu7rkGPf8r/I6Vll5y0zyLcTWKq00eKiCVJd1HcUQetrv8r/i1PsYbIjRJZ/gEJbeIn+tyQ3wi4pZ0Qsdui+L/dzCtmJG2pEEPC6n+M9n1b0mA1d+yxRazTkmz0NxnEsGx4G7nRpMSjdS6gqyGTFGKHLQU10Q03nP/8zoAujX9QaRQhGX+u7m/IPEEbw20u4RApsDoQKoj1KYKC5zzqQslUSQpGbn9YcC2W8f3TQAUZxGWQXgM9AmGZSaK1qH//eyPfc766jMFFFvxEWaWQWaB/0SM8DKOW+VywBaoZltH515dEZVPVT6TdEZOsi2ospiwHrVbJmIP6VpOkrB/4IX61E8FyeKZZu/QGCSwAe7gq83fTWTVwiQ947XKuYRZXbuSLahjCWGADbsPKcYUsaIJodys2+0kj5cH1mAXaI3SUxuwTaIvAlPeYhWXcd/3oRlJTs1CWOZId+rc0ZdgPchuOdL5K+DpaxUuoxghms1vH4z9VO+L7ppMTIQWW3rt1aXLPtJ6LUZcUJz4LGfHaWP7yN9ZYlhIqKUXIEQmh+vqJ26SWFP7MzYXB/1jegxvUF8vOSWiNdxq3koHgH6zTGKmGAKJFrU9cW9n2EutqVKXqRsDi2Pc/DnfQC8qWJFR6n8ekYsDBzpnTV7+axiXwk5OCcbnmteG1aQkSXEZmf59rNKi4U5sUNqHWtOAPBlkZW0swSjy7kZiWkwo4xfXNYXIRoJmTtvgvweWFvy2/VWOBRSLQmzN0jvfWwP8ldT/VTjUS32FeFi7a8xmOE6XUjplrPx/JLQbEgCWeRhJ0v7XNjTlLywvAlmh/t5qLX4BuvEGjoDWjNax29zwwGqDlUF9oyVU/1V5zcSs0HUaT2SaIPsBXrykzOXyLTkNzesjtxXSx/npXQ0unaKVt8Rh466js8RrpKqrNLCPvwvxxx90SxTQP6vOgIAXo5IYQkE8KfnUrrgaFLejtBNdIA6L/i7LP8TeJaWEEDFdLGCZ6E70E7PDbqiMOFE5LsdYNBpjQ9QrYKeg8HRLhPh4yn0RYvP9F2X9XzXvtiFVMDBtJuqGq7n785HzVOjOAyjsKDmcgBScZBBPAiYRs9jFjcrMtUZnEn4R84iPHhI5gZ+1/CUNiMrHoVuZVcxde+YjCqr9oAm0Gv/YVGd00ZOIzjB5aiBvaUd3EzI66uUswezwjnhrSJWsivbh91qq5Fbre9ySTVOSBbP93UXzVLbU/gHsR5fxLnuBnsO1EB0d+H71VpMuqA1d286w4dj0NK5OXrlNbG42+ttt+UZHY4jvD2pKmukukuMvny0CKG3E5/wcYviJDIVEgXquzmwSVVhgKPqbf/vUvwYVyteEnUcGjeCt6fzoswvwsNnoBRUIM8OH1R+tOlwzZk8SX43Rx0lLpsgLt/ybfLzUYStZAKjtOx/1NuvBJBSuM6g8KFHW/YXuckbGIA8DGv/2qJDzQ2N08d+mlc8OQnpoFpctnHvcL/fLqKs0K8mFUaYPJJKFaVVcaXcBHQSOLCsz/79AQEemAV4bHvhT9bX8jQVym21ygnOrzVWx3ESeIs9M7gF0Kj90kutY12hmYRO56lr3xHuks5gguLi+/7hAaZkCawsoV0jKccO6v20TyVnQ6qOKTn4SWxnZcFohoYt7+Y3fXcPnZxb5FiTbi0o0ehiwm4HG1VIiczPe6ar4+EEK4mr6HU94Og4eafKLISNgBIvwcgRXHbqeRBXdk1WsHccDN7tXyo18XDdaUrlPBYYYXLoq2jPCifggX1buVMov+UTXQF6nfLjjft/ldGNZHjnCVTrDS2I0kx3SiUwCU4ES4JVmFwV80gKKKDNF4XuiQhqxYEMT3dMePn614PWprOaQWq5bfjENL/o+PQv77eOQHDbzH2n+lknuBGQWrs12a3vx0oqL3y/Q1xU2WjQpn/JUzUmNd/sng62KwjVMg4yJ/PCLyglcJdetjV+YMSqkCTBCTILj7JauaIMEcUbGgKxhYd/2gF+WDCCNje848fydLA5SqDGoF2IIFb4IIVJhhdXuI7UZEDnfsRKEQG0l7CVGpejThOnMA4SYi1GLzsX3Yg+j075VQ+RHSCrgLcJnhQRNZQy0Yaf0UO6GMNgBXLR4WCdVqK3C82+tF3qtY5r+9c+lQeiLd1CxvP8bEBRptbKzfqls8ZcC+/KCDtWOW3doIcIzWbXYQeKCi7LcMUuQpSfKrEet025vN2W0c9HuLyjv+P5NJiT69VktD4sCCodIEi6Gm4DkFAwKkz7cQd/hbhD5yH+dM8tKS2dhHDsLn0m6dKii7g/AXFcnn2Ktyno+/SGrv0EzuMSgkrUiCIwn/j2TyZfEPaKY6Dpha1/vJUJF81tFA2zE16mHRSAEd1NVh2SBPoQfmzr5ReDC37tTTdoC8sdrKFPSidsgj/usFn28zxG8+foStEQmNQDGrBPvy5pWCY+wcTVsh6VEIXUXv48I7V6Nh/syE0rkJeMtf+oqVYViV96A42MyPcB4w2+JGs1O5u6lxrIwn14g/sUdiF+dFv/ZT/sxyDbVn0zgj7D5UvokXXLqYi4T9F37D4EWbsoM2X51JeuwEAMe+s8TFYy0MB1ygWBLSiXoe4gHJPmsY0dQH75qy4Qh6g8VdMtMlOiz7MOZgT8BUZvM10ktCJ5ufkftr0MczHGgYBnwTzsAMqpeevfHRdkRMTfsPIbpAgltSbgbuSSMwp0o4nZSrwr6Kjzu/P5YRC82Kv3eF0R1sI/bbN0Eu4nkvdBdNFVcmY9Q9kwlfPMHMn+qHsx0xzV4U6XpSOOFcNawjYrz6Wt/SMNiT2p9wM++V2Qg0sss9XDFY//D8+YtkrFMwndQN8xMFrTPiaDHvqygEnf4cP/LURWymzT6oLAeFpYProir9/RXovuUJCZcc03gYpOb6BauD63dUXQ7doptExgfOTerzp3wAPAzU25f6cvTwlTCzwfHZLd+q6uxBuIVJJDRRpjxrsS9MEY2FLQRHMmZQAIyntdWMMu7CqqfeslwAKo+otlO+L2T9vjRLXwBkiKoEpPdJyo5Pz9DJzMRCOhZUIlx5+5yVSm4Bu52clkKomCfuBvylo1Sb6RD29HJFFFCYLJc4yutP4nEYUEXvgU8V4+BFbWgBew8YYN3rJCfE6vPb6T1U2eeE/4UCl+D0/Onlai626dDqiCzoK1ZWvx3D2o6989/Cqxsvc9QYojr6KCH7X3XNbt9onf2JeA/3IZ/JVEAHewLfgBW8WWntz5mVL3rrcFJ3BOOP3THa7OMboExE7o/kvZSCLl9JRvGBDvF7yFkwU+LsNUBzu0ev/qR+3ujWHqh+f9DMxT28zlgwToc14WXvMqhRyAEpPN18BSpXBsptR8iknc81VIYqj7Ry036LkkAuhA1s7RK4vJc9qGHICF3Vx9PeNLShYdgOOemTw+53zuj+8mMKJKwU8ur2IMwffbRppN+MwRsdVDDWAlPrFQWC3MbgkR02+axSYnwD77kI3iSbDgZXVNi90XjfaQbBsaFE4nx/Dsg6kbyy76cKIyR0gSHK0kzPV1y5bGSeINV5NFjfSrLv/5db1hZqNTgyh/XeRNsLZ3uXVk2Z5laAsg5JLqK9IIq7kcB3lTRk88HiqtqQpHpahF9pai0CoUw+Ya4A/5hxjEiBc25wSTYv7uiiDOSHEQXpZV4M5cF/EQE4e6wusaEsCfABEKrti09mxRL+92/6XsrtIBU1tfgqT5dnx1V4G75WvmHkamnFgVOF5YOBC+RIJnMucq7NYVow7AWsqro9mORHcxX1jSr3CDiu/iXTCco6bLs+f9H1VkAelU88X7FAERAQQyUklJaurtEpEO6u7u7pUOkL3HpRrou3SFx6e5GUnrf5zvnx/+9t/f+ztmYjXPO7uzszOxsxp2+70hZmFH6FKBCBKX/dV8wFZ1AiNtRRQcnkoKPx462onSpohfmZt0wmunl8SUPcgoS3ZH2/yjZVoWGwQ4Q0jJsj6XrpQbO3j2VR0hBPH4DIgnsEyOvkKyMQqymE2Ahf+NmP2Suvcm3pJKayi9LsHnGn0FjQFHAfSBgc9t936+IWxfF7dhPRC86oYDGOvjI1e1dK1NRzI74Tevuw4EaagXYUjGqihJMXBU1i99Bfbv3qsF+x3TSWmmNbQWRoDscNeV74R/1wvLhLSivXTP96CwygM0OL1JQPNMhQKt9zujAE4OsAsflSHBGXQ8FRh7TdaXvs/w/H/+AAJiPekwHDYMQSHlfpfzoFJTgMt0iJ1NmMnEWYHlh2SP8Tg30kUe0A+qGTClNBRDGPZ1bRCMcvnJlFdPAF26WYrDffA4429Bh5a6g44HOaSTfItIPBfCKoDcgS7qj3KWmSvQjywgQSnS43OIYCWUpk6memDfYK9ZeftQCP+KqRoMnKVniRtebYCHF8Yl0ac3knnGFkq/rDVHVTgVsj4jS5VwvoluJaIGqQjVjbh1kCazMXDEdWbumZQdgFhOMLuAZgdZCUAWf/HCXPsngGGQgiZnuG23bf9ikuN/QxlpG7LxJXDpok8GMP3+h/NRqReFtg4nl1baToHqZ5NtZ/JwtPs9ov2WKGavLbM28GJDC/1qHDO0tsn1bVWkPJYANepX2C7fi/Z+bvVEqjKO0kfmB+/oL4AIbwtQ7Jnj2Q8R9yYCK71MfNM5wo/h+ybHkcZTalHXCA7J0B/whv5nHiyUXfRip8lXlyH2+87fiyiiwqY922Zx17mbVbH5bpN85PZrqg+x9RGoyg+nufx4gsguXy387Uo+CPkuQH/06imEwpyFiB0s+10g4VbC6zE9BmbuBd3EXXNhv0Y+1EJSPn0X4QqcEDnviwHHKbp7YoifiBRcAUdzXyOTLQn9Qb5CjWc+yUEfCQTVUwks4H0fS7VHic8FMd0c3QQ9uJUyIL+Offefzg1htIxlR9yV/Fvg4aJoZF21rV3VsBJv1HVfUSDBSe0T4JBWw59gYlRPXZIA+NWqo/76ecFm5o0FPobyNz1/iO1Zq311enWl/15+mywhL9BLf1WJDLX+Xhm1Nbk4FxYV+Nsn+otWeDYev/N2120nSt/zAhW31tfRR/Y83QX/Zcy7rBGpLQd5/UOX7wRVdbloCgPvfoBmjMUdqvSIXXKvGoiXu3vPdjIaZiqOsinv9/Trjw3ks1N/WCU72qoMMhAzDxNRgv0ZcHEgORJKJLw4kazMi7JuUDKQMkGTz611m1iTbP6TlRU8QCmuL4YbPdaaypEjvzTM37puOlfxSKGbFkecZnlNXRDDMD459JCzqgYCZccXLMro2wCn8BHW4OZgkjZEezym/OtRwAo2N0TMIX/epb1T0vRMTuJEbrImvqGrjr7i/egQgaUe9fgt166698+N+1+TbYgoGAGvy6KWhkpTvAn1hsWWCwHKBVuJ2v5KxNteFSQdkLFCRwgS3m2WmSCprxTrsPva4IE/JKC6QuGPBe0oZWyS9/7s+oKvyiKQitaxt0j/trpyb6c5D8OCGunOjdYZlU4VAghIRgAsCdoAeyIq2+wVVQjBHIHuC1/E4SHZJutfyzeYSmI5u1dyLar+Ygzx6BBQnr9Et00iqVMm9eJH9ktkPDIoqIUO+FFtMO6iik2146BTDF6roUTnML1RUHYuZ5gb31ESB26AcH8mn8fU3ISMNZOcj4oA/1PPcRNLRdeqLngCYeZxOgq4c51sfbYYq1ThoKYA+aASWuSsWcFt3nrPziMeRXJ7MW1WHspuj8e3xIKkCnX8nz36LZ0ZDr9r/JeBhnzE9i2HhY/wG5npJ1GnELzJE1+uA3/gp3+qVUqOaBbXjqIY0UVA842DGgnnyVYQ0t2XkSwl8zzHcR7FF9hJ32LsksbVLifwmujplBUbcW/G9UuKL34qYL9zlialNZNNMkv0GrQEWc1Ta+7jaeFjZzb0JZoUqX2YpF9f+jFqGim2wUMWPsJXO8ibkgqSA95b0unFnjt8jJAAjQX9u7dYni69G8Gupwm0dTnJ2eafTLLqBJTNl0bBSlHeEn7vcEobMIjtktiFvbBRdJbFh1ak9UJNE3upgm9Bn1+vxclpRgVoQsiTQUAoQfx+NiGT+xoCQkoOIKgzG/KVqO11T/SP/pSVmBloh11Td5BffPLPojxelk6SDEhHbQGn8zmhDVxk1TucSfcIcxag90ZqL3/yXrY9DgIK+9+aVreue9fe9QU8i/SX16dVZJ/x1O1+CVpbYrSd3NzuTZAMFMGLSYyiPOTyZNKZQilpNFBy3YPUWvClRS4ZqrF3qr/n4xfyTVOif8X8QsJ7xNw05Vxt6rqh/CRZhU85t3zi9yvIV3/Gt/8GLDBF8epan8iParjAeH92/LXP/HhBfWqitK3C3Y9Fc5mrBw978752KuBQw07SXWX3t5Imgceg1+sPlHl0nMh2/D2RDZPTvqnRxOCUjLZHfZv4MS361IhW22K+G2bS31ZdpquFhjtcoPV92X9E5xY2gwafl09+5YlaDytRfWTFo4iijTAX9PgEUbtTxOd9CxQgEZY6B2sY2VcFO2u8h1RsFwCXTDtWh66cHT1jlyGHXw2XJqq8Eyk6N2t1VF0fQSZfy7VtXNCiFxV1oUPeIprOLeg3D+ugbnVQSAjtYdlepIR0VXVGWTjYrs68Q5hyTU0PfiZGsKqFXqvpvG/kvKDn/iTU+Y8eBTOjUDl9iOKwpjWDRHl/TYdL9Fhe/HOtEc7BiA4cZxjMZ8d5z++ic4fRNnI1d/4DxLtVfVidDfyzb5oWeZpqZexS/tB/bYc1CWoSa0zeFqaOeb+PSUPJpYSO+3pduoBKXbVODW2UyjpMqRhciPqQHPr0AYkqDbRTCbdDlJhw8xVv6iGl3N9FBEJua1X0nmRILHdGI+/23zYK9jDLUYlI2gGpJuW2m89NrQbH9gzxXhY2Serxqw0Qsmi8qHJJADEWjdBTGjdJxSlHRqYL6JJXYzlmZCxtrX80wxeD0dqA3hqwMqKdfBLnMwMHmvvz2tW0deOIkR2bac0vGx2Nd4btqqYTjUeEyY9CID8YxdKynrF11KOfzpkRNI+3uKmqZgirIF0Q0tIod5u/i+RKZ1IxfidW9S0JNG/RzLSEYZ3l04rOgG3E7FfSddovoOETurZV3rZLQjN6pW04Bzvm13cd9lKoJtjNEMikoy4AmTJ0qox8aySvLrdgNIMhspav6PMlmvdwxBdZ7PlNL47X6S59aEbCPY5hoZQRDafVPskSNm+qqV08SpGtBgA9y20a58ZV+L+M7XqMJegekoTvkry/ovUMEDFbjLmMw6RcGg/A2bD2UjlszRbO8llaconCzTFHMdn6qjCKUZKWhWtMWIvAOcV1rZYYoOzCD+HacLkGPLtAPcYPAcD3tloLramtEVl2/NzHQ2jeoRs3rv59NOvoSHFFR8oS00Xzp2aZVefeSNEXoH1W30x8+1tnS0B/vT+tQ4YR+g3fVLprY/EtEA6rOfxrqfgiZu9RQiWnMc7n6S/XRX36ZWrOJOfAWeEfW2qtzG32Gy2DRD7sV+Q8XRm5XtsxUTKRClouamusTq1MQdF8IteLZ8nEG3bcLPifMo0ONiPRrErXqb0YSVoliNWMqMHkvapRYk8SuENxRFWEEH6oy+BQ8JbqHlkWnxRbBnCcoUyN/qGz9fH5C43OQSv+DCaZ1yFN698/++T8RdA7cY7tyNMtW82iLB1mXM5UQ1mZmw7gTirj6RLSEYa740KgyVWlftrVyznIvR/oPqyp1M3kj/ULQ4yNXJdJV6aJ0OhqrKYSZwTxmMcyY7uupTJ1Wlz0zs1v+VWBD1mqJgGE5reXC9b48dAyDvwlC7wAAQABJREFUGu+3HcFyou9a8jDoxqJWg7v82fkmn+JdEPhvJSqG526NvA9VUnnaWE1Tp/W5cJMtDx6ILL0V5ieYTYaHBuUYZRtCo6pURfOjCwYC9IrakbLa5Z1Uiy3dE32Cb0Pa+gI0W6+I2Tr4yCX+szBeRryLRPY/zsVcXD2ic9Mh2cSepuDgC5MYj6rvEzOSvV+f6Yh6IYV1KB5i6KICh/FWT/EHqdCwfk3WwPprIZ9j55eB9W0dOqv+iJB8Ha9vtb+38l50f51pK1eeq5CkVlFCAPQoVUWg7YNYehCFGeIPZoya2lpo3xtuOnd9Ylz7pPXkeem7tR10KeD4S4E+OB9ooiSY0cSf/TfLKW08VkYa8D8nvnqeXgRvFHNbxsI2zCYJvgosxeCIz6QVEECS/whbMzkN28KNOQ5SZJcAFbuYEP6MP88idD+IK5XNJgqWhLwvNNRKBwwo/11WFSMXc6OuGHI6oT2PxA1iOfXUReikBjnI16/M82dSuKVLymhMwlHl41oJOpi2iHWRaooB/RVCDFhBQAST0CI8d0AlCn7EV2ENkztgqV+PKH8ZZCxhU6Ty4sbdBC2WGynv/YviaYUayfwAq7VUpqQRcWPd/eSUqc6yTxkEnTuAyIeIZpcvd2j+QcMIHF+S5owEo8/USx4Ippou+leTVIHr7WZflem1QGRyvGheordakkFUcJXis/qdyUiADlB2DNSK92zYJ3dJI8N4DSRDrIvm1oMJmMU7V6sl1V9oeinnu5CCMVTE4SbFqkh8CwxqtefiwRFQh01zPonias4qi/r2IpISjSvD1Yo63UFlBNpV5Vg7tyoZhBPYzdCbjznoq3iA+OE5uCyHhacAmPg1177QpbZTzHe2B9a0Hh81MphHTGTAXfYLYAPpQ+eStNC/pOBm993hMeWxv47f/kepxBDPX9SPxnkU9pfWxmsY7fsI3zfSo4AyhzS3rncBweMjfZm1X4eNNXNPP1MketjSiSAttiDiggOH91XCkp6gaPjift/YdTLbXNlM5tkS4Zv3kgYVyb/cbresy46h0BsiA82YcPVdtivUYRyQVSqFlXsd0JDZILozykKnHOuQJ7elthrF1AklessnggQy6EcDQPR4/5j/cceL4oLmN4yiEDdMLdmZW0HWlwlsHsloO0IX04cXVvOLI04xkOaym4Umov0h5d8sAfVHmHyK1pJQXnYYfhfCIaVoZ5EmfwTRraA/LpkWXx54OYzr2cQ3AOM0ccWfko1yVNRwQUPJyUDDSY3UKvspnuTxn5CQzC2uyu0V7HG9LaZuYxnsUXeFMyq9Oi68IJGtatZ7ljTotSxJ7uKf0kdg+TPZN7/V5457XkOjngXE57kDaYfywyiGPQN1aa2Spv5VCsonnfcfIiAdrFz/QUtAq2h5iVNNhoMDqdFTQuXgCGno8T9oX3qlB25Obe6CL9gKzc695k/ANRv0cgG4RLiepOsDYf6dhDZ1D4gZLi9/2U5qLGoDcizNSqyiWAPMWjZKc6pz8dxJNy1OKnzzUFvspLfURUUGTaZfsYbtLnVfeAW2midNZx8x5Q1nBrZtlH2M/VKeytrF8oklMHEPempnSCsQkTl7L8cfqWAcobP+Bq8hj/wWM+mbztel42Euht/Da1IbDu4PLUiDgqBxZMC4Wvn6J2hoD0AKr5Qgi8ayWJ8OuS/8K6DgmAHuT8Z1ARmerQG7QUmbdbVatTXslwheWTjgkXQgM04hBfEujFx4QsW/5kNbvYHujHCGKhIkSGpzzUHyKah3Vf9AM23ewnfZriAcX6bjrB18U8JEXwl5mKYZGctkVga3QZezEgCTXF/ZJ02u1D6YNnM5d52cceE1g1qmApBFYJRW3PUoAmzvQl07KZwQKUoqspJyKLFJuPkui5MLNipCBLWH1He+l7jMMbZuJ9SXBG53ULdqHDSCcC1msej36N9ijLmRc7mKqoDrGJMrNGi3/FKyTakARwFInmsurQwNKY7doS3E5YQKt0GlKnxu8CCipudErX3BhWd9JJ4d0DMIQhJs4ynrEMZvv+8QcL75cIjS6pmBf002avtD1JXPnH40AOnCS5Yh4E5liPBXP/cVz0KZDZKdqb+Uz6z/lT5uSuYw07K6w4iGrHRLVDWeYzAlIsNZ0HVIO+GN+cdr+81FUUZyi4KbuEEqIY5FWhz9Q/aFnHvtatuh5zOWEh+Af5DGnz2/XeQShFu7dyXIZR/Er7nGoComMqkh3xnwL80egkjmMumDzPF7b7FKmBj4ZpTQ83Zb7DkQiuDCgBUlsbkIYfo2JhePQE0xF9Ir5156ymCfyje96ZvttELAEmJnzc/X1ZbtFGfvoeYNrQ5EgKlff74dCbzxFJlxjNzRbQm/0+8fyJo2EanDMLLEZxwF81oR3kd5f//8mdcqd7eVzaJMkygTkNrMJSbaPl/5F4T+mk+MilSSzrhkhtWGU1aWu5SwU9VcvWAQvCT/6JjU8OvazgWCiUiNTJ26PQtBrxFWp5kTc5WesLOAPwKFHOlT0mNjMafv2fnKpmOd9qvibGD6s2DJoNc4dt18+bdVxGwskJ4SOYP1TdN6AjE8u9gKOBoYNLn4AMsRGBa/hUmI3MwdTAb+epG+KqQtgZoVXL9RCuC4ddHTmR8sOgB/DpX3/MJyv3P0B9DrxPpT4AGonfky5lebjsJgcaXP5xf+iU8yMyj5ygSKEVaoyqOlKnkqlxEqUidUwRlD9qiEKrGCFids6B/xMNpZ/3yhX3nvLhwBM+paQcuHQRdZNdx5DErvdreWvjfFPCR+aMVU7/qm9G1rS2tFijkXiCT1QVqkA/AfCbzZATPD+CJJSMF2fN7xGYGYR6/CRa1+Sre3yXwtmzdWEWCbzljfozLLux+UZiWONh/+rX7x/etex4oERo9ETdHV0LrBFvf5oI+Q9lD50Fl2YazHaQVsO/5i6yJcqjlbPe9jM0Nschti6sUm0kZQS7akyA82WNdQusGk6m8niNBF+U56hipgmp3Z8561J0l5XHvBKFNfzUB6Mn8g491AT1Ia5DRHMomupFhp3Jap1LPwE7cJyT9xC9VYDdzAPfC/Nkzavu5VInuoZPtxqhKGKVX/jU8tpqFPRKAOZKzuoPi3hcx4tkH302LFoLW1sxdGtmWQvmO/C/Pft4E8dJq3w3WXaghyoEuYx7CgaqGbzde89DkplHQogtLMTiL8JBfZbDGz1G/+RVHpUzWdBN4eAWcASJ73mhacm11vXy5TypKr6K2qkqgUP7kabr9Kqz9HBsxKFmANdg7bVLyFqrdQJCYJwD66qSj8XNdLrc44SiVKSpQ/oYYS/B/fGoBtepvI6OqqSliWsQygR3LJkYNVxRiV49yNQopVoXxivbMS2ownbFMrFdwWEHNRAZqz+2PbuirvqnTkv4+SN372XKT+kDvVG9RS/BKT3maym6V9c5MIxk7eyjjv37mhJYDaD70AWgCjmz0hiOupk9YTfuantJ1Sey0+Zu4jIepgQFI3FDl3ULz6A88LcUvXae63HfaTSgUp4GWpO1B6PaEFa8tWFbSqA3i5s7QCZCZ1uxLpRM8Ifb5Llt6W/zAV/DITOUopLBt0r+7cJZeVwcfaltmwrWZHzdxwkWbp02e1OlCWhvXlY3VAYAuhG7j23UWfgUt2cba1Wiyl1WnayiGE3kEoB2If3QPbG20fUhlbCotSeBg3V6/3hVBpcETIZ68WmkKT0vmnXK5LJWWYn0FXxulB734IUGlaoogS2uU3DK++vRTH5QrrMpQhzB53PfI0TRS+28qLVJAfvTRaJs0Cte/Es1pxHvuyvC/sZtVRc/MdiU7KEO2FREgwB6q3jmWYKjMaVeimuMqBOpZqO9DPTfw5+CRk9+sr+bOgPXi0VyoUYsZz00GikG27C7RRRp9ouD5SOlUHyeIPzRqceCp+V/C2osQA5cOarWuJEJqYydJIANe4Kf9BJ+Dctf1f6I5zhR9gIERvRdtp3OE+8OTUJv3EpLuvJwloIPdBmSisVhs4RyEvIIo7uoraudb8jAR9X6Yhz7SLrq/wM63ghxgnEyrW0DvJ/PqYdCP6X1IqSSEf6cEjGzMk+S6f6JXiNK4/gTr84jU96CuQW0/ExgtFIv89SEuBkwKy/KIRKKHD3a4yt6rYbJpUQm6xz/7X55BDrfyBemaofq4J60idMMxf+l/ddQWOTkOgKhjZ9QG+nyO4UFJSrg0uWokyPaNIlh0T8oC2CTyEDmTVlrL19Bs8UodZkEQzDILQXU44ZPFQrQU1aVkql0EaK2tlBgGAh1bavLrBRl47L1l9313/22cswvSzSESXXNgFRdtUOERhzXB1KQK5S17fyxd9fdXU+hmKe/0wXhLAehcqzBhTGxSYzNR7aTfIx1yDQn5XX/meB2JUQLeQDYztNoY6vzJ9s1m7k3DdVJrG/gZjbCuN2FT+bg/3G0hZWyp9n39Nf1ULtUIysa5RX+XhDjjbgk4MfP/OXSSlGuAiCMjyCuQkLn0ff9Fg8POoC2k0Fo8a9hRTjq6C3IJlB2nOgXplmBhvqWpccaKZR0i4qUWqpUwG1Sy+xVujPzJKM/jMhf1+hmHqtfZWxGC94LQnLLq/VJu1qjIJlev+xK3SIDmkKLaoul092K/E5u18zEXL82kgJzG4URgFHymgH3Txo/KwlMORrltnWY2SnN9C9CD+hUVZ3muZRXRaW7anFTBPxdgI5WRqZIjqH2GXY9+GO/OlJLYaqGQszK8mLfiTAMKPN5D1e1XgZfdO5Qjx62yKU0APnf4/Lp8l/clMlYvk31SlhLEtVGCwNMQWVqDMMZH+e4l1B+Pfbfwbhax4vwCTiB8R/r8q3GpeN1tvBJXdL9yZCF7wNrqJXEsdj7kql0mvFBbITnnulRiJf5NGQft070oFKUERkAQ7pZdi8ngMK1fTg0hpybmmy4QkZCZDUVxCVvt5bJepiF9QiG1EU9/r91plrVVyz8CAwcp8QS7xYonVph0U3PzqbK5qtJAsjklxOElC+yzHy0tYsi0pPIubgv/IJvwlsoLkfqZuNYEOTjdjEKGhgKjGlFn9pVY6S4/kxFr6Thec2/oDE0l+Rf5nSR/Iaz8kYrzCs77cxqiSy/h8c1Sslb5gBooYiSJTAte+U/sRvo96F32nF2JSZT4opjb6IKuEZMBr9Dk0t9qJ30jp5WZH9aUHIJdIVsW7CGrdmEGosDdUTWxgefWHyQz1yODMDmk1p6zeOrL8kj5fBj+asd/yls+wREXBIP0MrT98oDUBJeImj792fLG//1QvI5tPkc8tLSrJ9973qdml0VMMAc1j3xpyu8l0Bhsai5ZT+zfMw6UfxvN2iDkRKrWNPLZFuThA9LTmAJVVxdxhKeEL+11ByIdMIYV3VmNsgfiaVzHPjQ1LzipBYJqtcIOnvJ6Qxcd84u5288+6iTeBpm3ihP6SLIoFx7bJKpqP/g7kxduaRdGqD/dFVjh0jPrzDDo9J6XqNqx8b1tiqxG4a93EkgwXv1T6JT5d62YiccaJjQGmLhZJpoEwkCC6z6mEFsxnzIRtlXc2+uQYcsDnhp+V2oy67KbndgSL+zYjTFMUOf8h+ZTE+/Zm9B4EZzd528dIw4uHJDGnaIdgQvpvOWs0V4iDkvyygfYCLVNxibT9uUmis+gHHYN8bkgsWD7TBZEUuyYTQpUp/Ebn4fnG1+9Az0eZCt5TZ/Av0vryFSfJxpAQ3pEJfyPLn7X3HvVVJGwseer8Rw1lmWPyK7z3m8FOyfXVBNoVPEMawQ7tG+BIMaNmz1MWUyyScrLUEBVOwAMxHjPlB2kTdo5ncMu/r0dOvSQrTnOIuDHz1Lfldz7CMo9iTTRNMf4Vkv5CWmzncRvWMVdR1GIRMGrMT35HsyKCX8Eoqcz3b4r/qf+sg7LilaWmyxmfTVE5Fq7Alfi5/kUh+CDyPt2mgeqmGMx23wziC3JC3yzAGjbRLzDGpm+Z0MQaLClckRKBSNUkfX800Uzr/u1pxFmkyWiZ42FzxLWCVJHMkXyIBKhnVgSciWVaVbFXlc5erX3c+vswl9kmSFDFl1M4AAV8rndH2lyUnIIcGVhTOJs/ie7hpxPLChd/+aU3Es3U62fiGaEZQkQeVSC1GIjnUy02l2hAvvr+r3RuupARyVd03ljTloDBGKrdlOs1eSUdtwGEwdvLok0DsnOm+3FTvrLJ3a7WVrJOQpb7NRrzsfVXUEpCIh6RI6XvTbahDazhoK3SKoUBt+ldgA043o+576sKmiD/NcNt57Wtwh/bIzhopGm8tI4x8a62yfgX8ierWFrKGwm6/4U8lIcuJRGlmvKr8UukcgJe/EB4ojDYDF6zErmWbl/8tB+727aGDYBfUkBK0bjvWKlxUJskd3Lhi7VSIw9l72Wmis3Sy8Wcy77fhkKqzXijZZRsINuRArM9AKo5CN86CPNtLf2W1LWBBNUKEs/m1jpDbUHh/igv13+QDnzpz4y0xYkKTMm6HQBTNoXLkMVfnucPCaFEFFH377iPzcOEHmhx1sYdXezOVxx4zuo+iHal9Jjk3E4xj1SMs00dF3yOVXo99xQJJ0zqbLijKDzR5VVfS4J9O7lVvQqLjWUtcBOKbQqeivB6/7w7IOpEIIHnmJI0pdGT+1yCAe7sqAF8wZBD4pRHilRBIboyqPX+k9eA8DXJnaSeR5TChgN9be4pg8nNua1vtY7zP1AB6w0BtTmBCkHkbEiKW72IjHvUp/meu14repAMMXl935lt/gxXj1GKIoI7JHbxmP6wBRtzTfM0jDdeUfTSKgBLor5madukBqt3ZSFlllDL5e0V8rqfGyAQHhNIEhLolFzXdZCdUBPkqI0cH0tL1diLco58oBVwr1bB/3CjioZEIgDfKBVN33HVHX//nHfV1W/NyWz25BCftEWJQF29mJ5CndCeMIAbxgpEDb2gYqxm6TPD170RwkRA561K0rf+wKqBdJVFjEIOZTRghjA9sycbY+BmFVGcBG6LKWb3r5JwFbON2oqm16Ndq/LBJTRinLsoleGnbvOdSCc2ptQw9U3F2/h+pmNBHCbA1WBxtv/+955UKADLWcB96/H53WWwyit9NfJ9YlsnSVLoLkicjlo6DjhZ4NKPFVAeBRpC/eGPqxR4b6YZnffOG6ucC5/MlBPwfh8cAQEI2bBTpztSrogQt41atO50Pc8NsEEhIFxz9Ad8mjSFfKlL4igPKKeep10almp+FjX5CbEVVhl6IBuccxn2yjb/3VnJ01iB0Fo1GLpNf0HOhfelAG/OSBW6tTsHVqxWgLgEZ/2eeuLjwsUcu1ZErJyAudbiCwXV3/Bhrvi2oxpOcMWG/GYnBpaHiPL5tJRddxksT75m97+fX1k58vlZY867advHvFUG2Oih1oy0oDSPA26Df1Dhwyf+RX6ivw9E0XSZgVcIPjPetJYZzXkv4Xz/Yw+IPqDGjaMjHxSzqhwxaxYk4goPbMLdKNAL/ZQ5rRaOs2RKursG7yZ/jzV94K63jpXAX92qLIroqxtwbDzJ6qrgN5VW7nX4XVYz9VwfhqAX2JZ6v+mqH374CmlqTCMEGTlZPsctd1MDWqdtQ5ejVqbifRdGodybQyXzmUdiNIx7k7f14SACnRz/Uxy3XPiU8uQkZarjehGeBYVUwW9MA4MmU0YIX9I0zR2qvc0oYnAHaq/kentBWa+0wwQ1fWGFAFWctMBAgnO4CMFz83vKaGnc5tAAGV9RhNwTZsoET32DAAkR/aep8KQOhiAA9QEUmltf4ccYESw/DzCx+RYZrYAxDIqebindzIJaTADLgLhEvzq6dZzCVZZbWqi6nEBmCQQV47p6X4vR2DwaZC2D65hWrbidstD5lpUPLrnlfRHKrE7p4X3LBB90cChWdSoBhE5fee9Q3lP0p+OEnw9rZtUuAbm4vsJYf/sAid1L+HvPiFG/16t0k/mKG8GEorfbIFERQ+AHWQDgGZ6ewSSOz1kL4x7zyVPlcDBa6kBqvMUkkbKXVVlad3Ar2viBylQ8r+W1uF0gbLAxluxTCyXxZtEoUSG0rVhkIjxLAb4EsQLZGE2L/erlpZ8ic/Z+cnzEHPjXEy1nxLkYFH+ILYdM+K4hugN4HbufOgPyJuwPuKhla7GPQbF+cLhp1Z2mBLTv4KpVE1ugiIzPnZ4Nt11W4ZCTHZW4czmtgX03ZL/PUAJDEEi00J4fDqPd5z3vroFFJ1GBuPv9tHmf2dFldc2aqBatX4eJEfTolh7huBjDgWMDAgDPJtHlBGe2qlzNx/C+SV8FU/qSbUO2V6aoinfy19brkwFkl5h73MHnpZVSabgi5ZT6FQVVY57bqAiKIiq7lqczI56KKYKzMohW2p9uqpZVFs2lvcxjozSBUNRiEf6Q6F5PD2zHfb9ciMcfT0zmR3yZ+Wx7M7ed6el+UAzhjTMDkbjqxkWx67wB3PLzk+2Ia5qwWOeN8H+8fBE+QKIcYO8ZoE/k/XTBYa1y050tOqgncB1RG+90HuXr8WqTxbFX8pEh4Gxt7gmdKNcY3ZpAxDCFbVyevo1FaihFgI9+5msCtOImp9OBMSzw1G4t41Zfd97fms16K46msjOW1gHhzDtOdKXGQmVUJ55kDj3mBPKKb/qHO0CPwLH36IzrsqO3GEsuQg1cbAOApNmB6AWfithvV7KDuNCPbuD/+RrJ3x0U/JsTKbJXUHHndh2jexYwAY+G16HeVPq1+DqPiVqxw8AUH4NgYh2gLqcDDuuYRiNvQN/RLxOCsALsehweo3o2gf94GlxzfuFiNeOwbCJKQMNqSGz3IlLWcFyf/b1IOhcQm89DZbnmm2PAQPbrFiFqVjnIv7LM5I5LwpykFd/XVWkE7IqLVk9eX4CJwazAy/wt6pl7VTek9hY7MwHJ33/XZ6WwrUB0ElyFoIHIHA+41AkfU02/VlIVEnUa7YlzFRv6Uavd94IK/nX7+2SC3WK30Kn8zHoXROH4HvUftyFt0l2wDyAbBac85yK0vudFdbr3Tir2DAZFz5KSKJ5VtvEk1IhnQ4hK+cAAlIrT42CuMQpZyonbO8cSpbEM4SZ6Cmxahuz3BTy1hrtH+gb5A6Fv4JP2YOCuf9RPnDGc3vY4fNGV8KAFEUP8J6nQRQ56ftcltnbnFWvBPf4/DvSDnUKt3/MdwfoVPrgWzHxu6mL/2TOK46NGgUGr7AqBjnrphL95CilCt7E9/cMlV/DwLG2uaAt7kBI0iGXV3ZwfBJYDgkztmJqTBHn3+QiDvSDhjE/YQTWYE2NuN+hMcG+1TImV9oklgJ+5P6wSR/prMl40/Km4q/wXLJPV0kTta934cCy6WgRu8Ua2sLVCZJXyttCmYXbjCbEQ4+Zun6hl+TTEvMOqS4kcRza+mRtXHT6MW3iKbIZmfbUEHUkvahn9KZQURMP8/87CyK79jpymEq285YMHy49/5wgUcxldOKVonS3vQ/n1/U7KGnJ+RW20BIgAbL98LPiN1xYcql/mrGZHqeoV1OMwfwhMF1eLQRGhMizmFpgyHJ6kBVqEg7KbCvBUr1C6buAMXlRO416uFCRU7rYqKiEVl8N8gGD9a2VI33ACtnFWgfio+ndq2iYAjudWS7Ktdek3u3t/s2mYkQEqhddYA/oiIPpd1GMhClpKXHoc57JtQWpsRZ9VBthUO1Q1njXJVYPFBTdGYyoDha3enagDSqOgHfqIgQyKDI2Ji6d40fJyiaE2w6SwRAy91O4mRmJ5526HyzwKOJmxcHC+aYxkQrezJgigjC+u5Q/EPaUyVy2i1+FLvklxMMFI0183emc2iyK6ywJ2kPAmV6VS2hJicFfTDG9A6doPYM2v6K9MPATLKCPHhVHk7PcmHqbEgexqIGIpZWin+St4HhEuNkRNTqqD/1sX5VdjRlB8J9s/uFMqGn77bpXMfw5T5lTggf86abqgAb5zvxE57lnlqrB5r9O+2p8bfI2TygKyqi0wJSuV3Rq1yS52qs+WSwZ8KxNos1SSw7T40lnP/9UPSGbmMojJutR/j2K+38dyrvcgaciBuloxK6T0d4aK0uKUPDkzKwmWyyB/g694kppTFA/xJwEDl2Pz1SIkVRiFX+HzJhNbZCBHjE1nu5dSzJA1uCUY435tpDWUnMrsW/OKDYwLz7Tctuj6RLVNl++KT3s1GxN3exjwLu0uAMuBN/wNelsrhowy4iK0iOmHrmCtwRbT/yq3ZsTU9k1zzDju507KDJJ8rleidINZGdN0O9gY0r6VynDTmqDWpGX51QKVyogC6QmuQEdAJ0vMGoh3jf/jGhrJMf2iJv8Z5ZJA39C+QEguWdsveM3D9x5e3rfPDM28kWRMtrDuRgxiUzJL86B62NSY2b/tz54QDJF7aZW7TUeAYzXX/T5pQ257O0qKg2+4byExsMVxN0ynqtEHJnapzvdcjxk02IdlePn3iAMXLaq6ktTtWidkdf+l7dXbx6v6kal7LCIeGPszSgWBtVCbjEdk3gUPAu9k7PCCAfTdhxr4NGEc5YHFUFMQUi/geqHOOG4fPI914GydOgZJCrzIgxDNTAD+m9ZnBauh003cR51Fi6PxaKdtgKValzDfyhd9rOLk6uuyXErWyxWz3DVKToTNamoEH5PfFmW7wQTwf10vVtKaohcbR5KstVkJMGsI0v5T2ZmAstPkhxSXau8cU/ElF+15UB4NCLYadlTgE+1WlEelvywHTsah4Mm1BOJCt3wvvsa+2b5dUrR1A/UxamlrzvmpW2YINPh9gSfw3qRrINTYBhXtyHhrxSC4yy0GuNoLQn0ATQ+VaTVGVI+N74Vv2j6IGNVOpQSNKYEnCWPM5SlvEYjAJ0BZZWr0bBPZYS9gAyk46SdMjSIulHHKG/EcGbNrhXjNkfo4k5/OVHVEFdCSU4wnVuNMBGdNJzR48LEGbcN9bTR91gfFPzYVJVciP8iCR9GqtTxyJFWoOq3qvoofQXhuaJNl56ApAsC5zEsFbHyCuvI9so1QbtkSApfDDOpIsCsZjKmVHfFMBi/8f4nllYLMfP/1OB5Ie4pxv9mBBvKtZwn7UzCNu5Pt2qM4HiHehLkVDI75HBvLpwlTxGp+A3jQ+5pFfyk3y3bWvYStJfLJak0hMLkISPFVdGAsc1cwdRy+07TM6gldAGQtUiqXkfklgbVdZz/o1GDcj7MVkciimY9//mHdEzHeFQ7q+FS7UgCRW2fXMnTEWhR6ni2oozb6zhCZpg7P1EweIK/5qhMlk1MBVaCqxErlSwI3RjPr/h0IyuvqAzK1+tpvGmYS5hCPUxo1MG/c5j1+ffmQCNFKRCALQaUWPYGTxJ0vIcYYxMVWLnJ8KC3XxoKSY/lJq/7U4Kf3TOPdDWVL/1Z1Jdy2+otCD6Z0y5uN6EaERhln7wqdrhkhQfmPK3SNyN4JKWoBEx8px9ykJNbyGxYU1htCNGarZzEYa5HjvuQoKjkNv36w3ddq/TZymk54a0DCayViH7FAUD6BJP2VYaks+Nzlg+GYxMf5l9n1RLRFZhQUqUuwd5jFMaPhvZvvC79U8hOIdyfhTFpYuUVYaRw4+j4XebUo7SsuzAwCqd7nzeh+GwBPp0rnWBajOpKKnp/T1d+qCYnby6K/oeFKarAPUl6KLYnK6ORDHGRXep4ZvMKZDK7dT+L/0W27MfHkMV5Y6Cn3/SGz/FYK74zuw5KX7yPjGqW5kjQqvhtdDO8yWqK62Pf8UsJv+W3b4hWLjHHZdM6kc/enn0BTXKtSoe2THzbP83HXe5kwFW6GQphrRlgW1CCYF0PLi/EW5YZN8GNj3ROL1ZRD4IXCihoFttQsjkTHbaNe+4/U3jd9ZgzmxNb8JmrhCfwnvz/sGTXlUAuvPAo12szkhz/fR3L1821Fgi/wtdj5lkirQMFU5mzHM6jaZneJrdjOgXLEQL7M0/Va8lIaxCPVbSSoO1gqbArRmqtik2dt31TDxaWzl3KNqTz7EjjHJJz7M09U7ir2XBl79kXY96M8I/dKxLCHUFAuEoz+AfbHLMC4LT9a/Q+nDNVc4uO+RK+qtlWIqHoUyauWDuEZ9eICQH0+crs1k2irg1e8zV3o7hvRAT6jKvjMJKlrj7ogGFPB970M1mei+x4RQf2xqpQIcz3d4Ov5WeEXpAEYukFSERdY4nDVYkFhHwNu0SlfpRf01IDYPmmhN+gnY0JOs1HhZ/5AvpbukhUGJXhcy4g6hDpQ8Uk+jkbTOx2ruV181oCvVQ8K+Nxn1ZSnJ+vms5Wo+GuEUNBwmCAS5wplW6WKxqNjlwBV42lIRLkpUqd2Rfg195nbLf3rSilbgJO0xbJsxtcaOoWZRHmge4mAqfCh/7Sc1DSJJNbl8z1rAz9nNX6LgNn22jYWxSb6EFBP7+CZ6aOd8jM7ut/nVvL3EjVK4VdEpSONbNeDNHUJsto6a5j761DtZAvimHowkZtUqer5RRCpCbxCC1KRbFFLx1X5wmfkT6/nlR93ArNM3H68zQcC+qJ/NcnK+KM5WkWsYzADachSkSV1Bq/ESajK7GTHLFMzfdeeeLn/JPtGydRaAlDR5DlJgvr+ELIi4bVei3q1O94RrOLHCKFMfTOykynF4J8m+PqSjWpfhwJcz63jqMdtiBEkqA3nGnXioABd42ejkJ62vfGNRLDKIQ4uiDRU7JSQXe65FHdE5jX0V9b0vWtwQgyxk3/d7OstUrR1N24fiyZZMdgt/IP61AqNhrNM7jvxnROHQeuBZuOCz//r26Y6c4ZzDPyDaZYmeuUjLYp/yB6OSBWx3SQUMviyLc+Rnhtg/ziMMkxVqaAUvgjwbcY3Zw/tDn8JGvEtUYpVr9EJ9XaTHSvYyycVVSKM6y/2OPaipAMPwSO25sh3vmeY2UVYyz7TQ9pQH4A8gm3oogBjLpbwVlubF9y5mnCVt4pvWMk9JbU/unUMKaq9eOGUcsvqCnrMrU1AhciKtN3qVWMHF1VhORUBBHT7BO8TKUr8t5vB7vDbUESv1yQklbkOKNS2/JjvZmIvKOzC6qjdh1nrfvU5CtFSqEWyWlErdA8efSXeEypTicweO7hC+eW8IIKDmgsr2rS+4NoTfpfTjHJKvce53v5OfpJPC+J5wn31FzGEhSoXckKxtVpY+gq/FgBQwRWug4+5qWOJkmQGnNIJiX6jGerT9EvA2Y6oltjXUSbpZOHArxENOptOHzC8OEFqA1PMizUL6xwwKRFvIXI+HWpVE9lfL3uug1TGZNlRyTKU0DIwR7DfNCWIcluqcJ2LJ70gcJqvAN/gv2ZcKtg9+nbWhDPXJvxd4TrgQhU2aSxX7fd8KVLbXJF4PKZ2qfsp5Qv5+RF0dmquBRigxbKpZQslclD29b4u6ebVe8k51g/cPN2PfwbsCubHL9NBc7QsKLHq8wa2OAXYNIqSAZ44fYaN+XY8IaKTL8P+BRdTmlIqtptWn+7TXM2YVhUWeQFp/MofZrXQCWGHdqzwZSJJQll87GhnljSS+AX0N+Tt7GFK6TqQM6VyfwfQLfR/lqskuSGRYnCwFxEstz087eAo0uiB2UIYYWlDmDsqQlGZQcXTKyN/KqeKAle9mvk+JGbinfkWlxXqNcxMIbnaROsEnDcg+sjo7KqHxP1Q8x2ZPlKRYfYe8ZRm5VtYRX04y3+VGBJ+sX8J43ApX/Jxs8HaDQbvAx4UIE/ynFNjQ3OBSoE8VlYNn06z33+6jeDnML+j0nyrQum3wxC3dF+W1mC5zPG9LDMDRFHGyed0iQ+a0nVA/MNs94eevWeAW+/N12pUy3TVTvwRifj/ky+K4i5Byeo+zU331RfhQQJWy29jETzq5Ohg/buX3sz4Mj6p0gU+w1WK7ceAirqdIf8j4n7yLQaHEm3x5XaXUhDJbFer4ehNEEskQjImR5XgD61ZKizksFelInWhT3K9LdmXpWj3kDZZzwqWWq4IQQySTEiBQWLb0itwc89YwIT7CEbn1P/FWZpNoXt/n1ZjpllYTVlKG/bhxYrX+ZlK88cSa7Np2sBSlxryhZH3a0Il01dfQ61Tjra0GhX8A/Wg2KCK+qkEuYRGeljcQD924RDFQe0kQp2hTpiiIajvIxu3F2mbDi0jQwyhLZR7UEw3n7Ei3p9XQtUT01D4oJiSgt87nxoPVVbzs+a4hnQdSTXiMTDhE/P15X4KbpHlgHt++D+fWMzK3ZhsWEGCzEjHG8ZjONeEjUSXUFqakUgcPDtdcQ7pGPe6Ca8jehgVxcrtOivTdn9RS01cTN+0QfVrWMzoopDRsyJ3H9Akl3zzUJa3fkrpQ0qMXcVlsSwGSO6vzPNejLilnSS9wtdV6RYooWxDLtpqC1EZa0p/hqURrFsAHvKz/1Dnwj+4sKR4+RU96fqIQbtjNznZqEFtERlp1P4NUZRiPx2bOMHP3K3QJKWx7USFilKccxbcFEDZ1u4D9+wABo6yhwRpKcafmzwXDvFSO177U1NAye4TXQjX022SGYkm+0ySexA1VZPthjC2UfqqTLNUN4Bj8INJ9heIT6X69Xu0GWjuLjPnJ7hJdVnekuRPVBBqZQ4t0YXoEbxaaV5cFrOPxtJyvjSL7hrg+sApU+iImFAMt6smpZFZDgp5Z3sAyJyb0EaZ0NBWNuZWvQf8thwCjsB1lKEacu9x0YolVYz9ALCRP0YjDYy41HSoLSSUpa2XNIP1kWVAPsffI+FCJ1f/ksQPFL/qalbiTVzAnZnTiq7Ao4cxWmeq8OJEx5nsMEgc1oVloTSqgnr07Dtl3k3F/RIVLqNlviZVHHOfXhCgmmyDt5c4/a9A0cyIO2dpGt3CroUhc5dA/1uLXErpZJrA6w1vcopyqy5WSfIGLhqYPu8UKZuCIPg96EgSh1Nfmm3KAFmYTCd3dttWEpuI30DlfM3q3IWBCXF1uB624iYTiikfHWo205o0B/pp3iKOKZ06NdEFrtcKQ1TBWupfMGrFRKd8qdskrjVuOi+p+0GmQBRmlzb068b4f+dRAusU7YsTy9SyJwV+E79t08r7jiPRrtr4CBoEXFe30CQsxd2L78d1x44gGf7n5G0SxhzToQmlf+v/6O3HfKkTtaAhcE/TsQKQpwo/uKd0UDEt+opELM+8MypMie1LqzEyWzCCEb3GXzwkYAnfA0fJFWYTE9ff2v3fdLaPIoraQqKeJwwQO7zZDg1vaiHiG/jevgVE9UT3RuvyjOw+nt1dkK+l9/bDF6KCQ29viuX5nbTpk/ZM8p8tI4xOD3IQVvur1Sx3BaqgBSyqRoe/rsGK7U4vZbbv33H9RdYl0INnVJqmsdg2YW4H/c30PejCJCZWCqqYKbS4HYBJcUVqhaj1CFImscD1Bf626Ljo+3T/tZGxBJhphUL92sMJxvpqmrX0n9+OhXjeG4z1jLC0q6TX69ZYsuABEyEi19Q4HCcoPy0UhbYsTKtF+pv6miKa1zAYgYM2w9aUKKrwpo5sMqHXD1Dh/AagwANEEeFIf2CnaapsCJKwJPE5XJHBwIVeJ1ReF/9olOuFXAeYGrTDpUrU5TGEfW6dQtZFasOi+BKFn6NX11bV/DdWx8YNv8u2Sn35+d29NDqu+6/WaKgR27h4OXey/smRuW4SvBKA20RJt0DmClLLbpEFfX8Nq2CGjTbHY/u5hz0JGIy+yWxxwg9jIH6rCYtJ9dA17p8JQjM5n2USYQVHIBIZCcWBEvFPIsy3+cGHDcqnn131ZsvRyDlzBJB9paYzHAOas/0wBrrffQK4xVpsXWW17W6/aoRWMaDNVNgS5vKFss2a1x3sm0gE7tS10pXFkVUqTz/zSk1kIEP264htSatBR0Rqu6YWFo/cAL6dkcUlXM4PtI1SyVcEqPgZymVv+mZn/98vQgXmaMR9QTxRqL/LMCyQKhJQLB9xEBPUVvy9LJj0mUiJfQTMSDXxzPm1QsRTkMV3v+Kbthjuu+epTTdQHP938OFO2TXeLt0CtWANf3rUKboCFMd4FCNsSfSKyIzZ/ZI1ZH4qnI+TYAD3ldBzhthMb18TMd41myijtTwHRIUg8MnDzklXvRpr0rmE510iIYI0QfB/3w4oJw4HE/Mp0WGKn6+IjnQz3z6nlVLSwPfZvkl5gTFNMhd9kjQyfgpTBoYtiAzZAy8RgENMZ9WaaALUcgRkjjObg24IfreiOPtK3R2hNivOeBvf+VPVRY37lrOBpvOYiwXEScz1t+Jea01r5c7HSFGJmCr5c10ZK5ux+C9Hc7GbzXR/F/lsGZjTZwZQfkaukcbGfx28nTwbyF6gMgVYDRNiqKi4wRwJr1AviDkXeR0zO10sv3YVqTr9SaN2smUMDCkQX5vgo0if6v6GGRn1jH1bnDBAFHUgVfdqySwOyCXLhf4cvBr/dLyUu9b80EzGjjPoZR+soXT+9/ox5bjlEhYUthk+OWT37YHGI+gBN16AO27iu4HvgJC//5I3TUeBipNzUTV4LvOLvkMrXUx7sSVfKdtz+I5lpb3RRF+v+fCTxNHtGJni9VPuC8awAGX5oKvu++G/Sx9svfsiPHjcVKO0iFTsVOOFwKtL6E8dIDuNmBM8vY9yztdSecGEdPwvrNEzBMf4zNQGWzuoTOUb64Hl5oZ71b+AvVkBPLaAeH80Zgeyi+ALL6fhh5su8B/9JfQt8VW9KdJeSIjSiGHnq4AaCoi/i0cFlAipUotqikrHc7k0jYCQFgOXOHBvFvH18W65p4Lw+M/T1RA/nlmaEndpTY5+bJ1/R7Arqsb8kcAYicTSrTlJmmYsn3MXJzaHM3Rl7QNXrz1R8LofzWy5bF1aXl7LBkAxyjnBLAB/n0tZcSqC2sYHWyctTNnpYBrD0N5waT/pxeB2pmoFNo/0Xd2quEhtXuj00uH1NWvTu90hMDLehOSmj7zOhN+neMSrcUmv+PAh1wgGOjSspCv7rQf0+lOn8edrEs2qKrlIqZ6wECOEZB1YPldoeZ+49AwgmIo07bKNxp53G5Qo7gjt6u9Q7HQllpdwf+f6zz9X71aRXJwsulYd2L7lv4qD03wnqeRVJRdB7XyXqsVW1JNThQlOieJFqUwL+NivepgW7DNiyrdT2yyhw9/SDcqWMrV/MIYU/6BUA66Fzv5EhU1ZL33KtCgXcK7xVLKWkPehFfAPO3CXwPdwLvJ60EKrHSOYVvyfyE+JvkpGMKarLZC8Z45u7sDsgf+2tj9owWFlzbRzuLMow7WC6RULrZfW/ZC1ItxIQo/8mkvQTcKr492PWpLjPjc+N4X7d59yIQ4izjVL0FuJ5j6JWsfuBh7PKG9rG5EtLcEmjrpsICb6OxEi4kerFZZDHZSJKrXdiHI1Ne/n5LWAzLUFJ0/6LcFpQlUR1mxeYnDBSzMlXZUiwHqwgd3kFLQFqTQbSBj4ii9qLEQ0YAXmuqRkVxbePTEJVrWiFJwYVSVYMf70ZnlvIQmrxeYGFBrYRvD7cKXGM9Ipo0rqbaUFGUbRZqbb2aqLMYjNeUHgOTQcJafs+AcO3IuwIiXSO1JyKxfKngZ0wyAbB/hAelGpEKl2FLuQXRpiAOmNu51dNBXr3L9CPh9F10Qa3Ydhfd9UvpwbxcuD3FGJ6vL3oTaEjhaoOr9ulR3kq1r1ozhX630Lw7u8k9ow7qzSsuBpsDKo8+C8I6ZusgdknWIbgy3IbPcnMMn40LUQ87nvHjb0Zy6p22JY11LjBrBcg9MP1pOzBIEsiAapGI1MX/WQrEQn/ZK2zItgmMUEKYtZLg4/PjXb1w3WqZ/Q4Gyr4bEmVSTvuOEIfd/G8rt493S1BmtBOgSfphhpzdQonQQssEFn0tmiBB2h7ai+mJXVTgajpZdeYypCzfilpQIBMx+8c1kWm/8MLzs+EqwwCOeg/hX/1yytAwtJu6K0FXdF11SRkIbdVUpCmrpTe7Xd5RPktrIBiBlfuxf99aXqYZaPW3cZf1PgKErBn8gziqY85Tdbj1NLROyXip69+MWjOQtLiOeiNzDtLCD6f+KXDojh1iSJEJA55xYtNw+EV8pkPu/Nlb78YWYTjF+l7GDNOaOsjQ4nDF6Y9A8DzrnLlHJTvRwkzhSllsLVj4LyBpWkL8Bh8ALiAjrI3uBculeQPAuqEI5UPAkxNvtxW/4+xkbHnYSQFU2ZXMH/+ohDnhooK5JvbmVOzDFgGbxj14W6C9FJ7StqozfoHILcrzooYENZuhG4pPkdd/oMeF8Rod8TMy8kejnYeu73sOqbQCrI/KxmsUscxY6oRiwwYptV4AIN4f56gsc3i+Ff+7518dGC5G6on3YeKghnqTw57cjq8/JpSl0mu/WQdP6nbVuMUxxis/j2PwWNufa6n3mGMuJFotTcZbtSZLdLMy8FtEeDUF+MceoatpRIoJIPR27EUQlsKqN47OPCQZCcm9ajEpCsFkSTGs6CStnAKkusGW4t0KXFyV/N2t+fSxBttbUOdI4rCQG+WMIE3O4NUdd+tgCPpehA4Sef+CHThQuJrJpfW4ECFYstfoYWVAVh1yDphcUARCUYZsLlfYP8/yEku1/nU7ADZ+7S3H3KDMAWrjEgxqozoLF6qqL5X7aFC54ddmWxG4HHX/2Bt/Cbop52S1PQL08BhHPhvblNI/K5tjO5q1l2Ka9KgZbQtfA8FQvCnR9S/CcxKD6AOtUN8pT1U+4C2kvx54JPXILEACgOl4eyf6uK519nqKqLf9JslfLbkHPBRKSeukqiUD80kW1H+UcEpHY+2h6nxZS2Gm9HKtQE6fJrBfMKXJlVVmrM3QitnAIEdpZYehxYBM8ZXZF1rBY/SKyCbG/r49lD5Cm9Tbl17hJXaLYL3Li4XLSxcnxbhlVWVPwzW/yIY+KnTciwvJs2zV6UIs5dG55qQ2Z6E3AFsVr6edUnnylgBKpzSZTcSqokasYOndOIKUMis4jDxHjUeVcfs3ACNfv/4HCiy2ZydoFLcU7LDJRBdNqBIjgNgwKJ6c1H0R6xD4yyDyX2rYbGqNlZiKYWCBROX0w/Oz7sd/BgxkAjfbzStNPnvQMfumtbgK9iedT7BBHCBQpNKRPAfvf8tsq9fc4n11gx5xr57pOw5eArvuVJgAYN/+U/KEp7+4F56wov4Z+vY+OiZFTBmQ88qwQg/EsRKHhqa777xursrTCT5F524kC9wnd4ZBFun/O9NsJbJDEXe9P3qW54AiqHXdWK9nkGDfBz1WURUtVwm8YTmdw0ZHemEJRp6NMcgZKXTxH4KNSHg0/Aue/3kJEwq56B2YUKVINdjoxmusCf2Hcv6j+sfiiDsFc1fcph/qG+/e/+7O1QwW+UiwW9hDVYQZKfZTaq7dxiEdXNqIF2vtA/cJmZW2FIFbjrl3wBjdDIYLH3Ul5MDnFuKCsW10xFtpPkIzbjf4s9oaAKRrAvstCA4Jm43oJ2n7c+yZUdgxiwUBJPHPZAmf8d6tPtVpIpsxDxzu1/wc09Ts7ASyhjVDUEJ1tIXLPWaqsA4Pc0Zo4PQ3vaBEeXiQo5NUBNyQHbkrn8lq8Nyj880+hq3weyGPfhN4eNz2cIlSXt2GAiM2XNnGLXzIsJ3O+7rKCfA7Vx1QCLSIXj1mG33s3bwoMQxdZfV6k0awSSKiOHBA/g8ozOYMLMbCOUh5lNGUW/y2GX0L1dpLAbV3y31IknBfJQS+XLypgnb0WfU3uorNtjodzyouwclNbDY/+h/NOD0iNU81TwU9eur16waYe41q/9p+kUbf+lZRHsen2G8WHiEvltcfgKSppqeYmr4G7vZLonbmWDsR8N970tYbOu+/XeVdQBN6VJrstm6L8B1q3uKA5dpSBV5bmSR/jwtg+LUDUroqGyKpH5dHb673UQ/ChyDCCKxeMsm5cDCHAiYPEr+l8YlfFZiepE+Fl+WZ7Drvm2r6RaMFn6uKpO7VnHT7igcQGiZIdIQhLcNL5/CITbhuvgguCQbGXcJAifofRLfzsznhT8DBbJmJ+wcCZn8hD8U3Vw15c4bskImBsoZiwUz2rboic0eAqBugDdSfXVFZLJDPb/vJH+mjDX8bzQknOf68HZ4aKCcXMy6fJ553xoXR2AI2KRJlF6p6Kmx1WEtA3NTWGRQz7+EyucydTG+lhJk6tngVHB9xt9SosJqDlFx6zF4k9VYQhnhctS8kM7wcsfHhsklyJlFGDcEoov0ho0HQ5W6kmM+1dyErbuWEu7h08466O9mvDBJ0xURVTkFh3XwaatwcxU+8RVEINEumMqrcDujSZUQgUhL1aRZxfW57O/IwC+ZJ4QlBtRUwR4lavE4darPCl+x5dw56msPNkRsHpjgn/8PXnkOMFS4ffvEN/J64HSF0o7ImRM4qX7K11EhCfQLTc/zpX8guVv0AD4ryooVFjWcniyE3yo75BGzw1ykS2UtvF1vzdMFBhrNHv9XRg6EEccMWBD+amny/wNFpju/07OXLB8chzooGkSh3TXYw1WCaoqqE+FDMX/KVOqNCrMNQtuJoolVoSD+wprO8lCuaqIFcvTaqThlmqX13w/5sByAv84FEP0TpKSS5p37kBjNN7j6FuW/1ObKiz+QtYv+vl60DcsfYgZTJE1bLMt5gBm32rkcy8zQD3XSop5O730Vl8zcsZstvdtDIZL+vh9E5MyZI0AVaYKah6GBwHIgWWYSVRkclG9o0/43Pf9y4l6WNu0UG8vozR6kE3z61AmgrUwAJWeSBf7PcGT+KMgNJJnvQuDEdxZsyvHSKD/HNVdJA1QJlZRula6tkXpKLsFXJnbdsEHZNLJABnoLqhQOXes2iHbM1OqjW1vXuyWV1lqrDgl0u/6Bqq+FB1kqfPpdRaVG32fjpgqWrzfvuPnVpQK42sLTu9cGjQqg4VCpUB6F4KyG3bL54RZiZ1YSG2SdmrlzeL5o15RMqfuoqwjpa1pUO9vFDenZI/PTD5IQuQoDXg8xQFY0xviLZftcK5ouaK5tp8od0BUgOLwvpbSl9xlMMI1LSJ5QoMuKLK+zFh/SVqLIVfYl27bC05kLlTKd/wGK1gvjzQmJCny+vpp5smH6up83f+QiFbfnK4iwHdKe62XEb5V5wC5UlPZa7ICMlzJcJRAAd3l/e1xDPVd/zwg2MAPyhn+i3p1jItGQ9+UKasgfqBmCP46wSICANj83PrBUmcKM7d8ex+6JikHg+Wl/NBpS+gNmtc/ZMwit9NQU0WSOjTHV8+nfqiETbrIiViXuyU7p21PKQbHIn0TDR+mlA5viXs5qPXeC6+1H5u/PGTlXyvLcQbuBzTVNs0mQLN5V2kscIdIY2+9P32yIJuI/dRj88NVmmpjtE6wmSK+32WT7XYxB/Q+/1/Hym6I5JcS5Z1iKfFYBQ8luLC1wKRujrvaQotDkkZD32t/i/AYrlFGxXbTRamAN3K1de/vwpTOLmLIzZCDS4bLB+geP2riyh1tYC/6D8EJ3GDmwNZ1W8MeB8AH0SSI4F2mDrWXW1F+8eipuX5c5qee9AtTA7m2bZjpVKxGp45CVNJkMOYHC3R+Mgui3Uz5iVEibSuVRSJkqXK9vz9hqL9/cwRzizKcja2Mlj0l0zmrewi1mszxS99vlimoZFoHCqVjHw0UBjyfnfBhLsSy1ngt5TsLqSa1Dty7mo41InUuIuhXUBCQQgIPXXNYToTucIsUrXkfQWmwcJZGUuuarPayVfAVPveZV5Npb4gCSiyGoPvtgn1n/1vjUHnTJOGurvHkL2k9sK+pZobiqPsYnqr56pqPNLpFDDJSslUKKQxWXQnGq8xD3uanlPvVTLNenWkuv4EBS8z/+HW4L1fCXkbewjCE71IJ/3PMlBvv/JqPOtyYI/+SyRwPQW96I8mJyjU3tMYtOP8nNitCerWaOv/n5kE2PoRYFY0j91qSIdEosZkvnam8J0RbDlqlk0oc0wVGDyRrTx4o1vud1vl9k/Nj/VvWHrMg4FWSNZy6iZcAAEAASURBVNM1rqU1MkMwKyQlcbWlpYLe3nPtJChHNYD14sa9RfEvXH6bbdRKYkwxeo+SrCyIX1t5c/2WNL20/a74cfFHfY7poiVxreCnCJzNopZp+VhXpx0cynQ+HiA1iMPdhWkDr56WoAchVo5V4ZKDxCf42iNdr8/eirszmHUGAvLPlE0EUTTlDdwzOo8SpXvla4x91VtBKDjQ2tMQyCAEa2eIW5t0ZhCTVje3roWpNcobNAZeTa9nskGwTmcdKe4XlVUW1GXBbYrL3ndim9GiGv8kIAyhpONxrQQGSCxSZP/cwhDoD813WrBQuHymr1SkD7MWC8u4rBEoQ+7A1xa6BJoEH6wQ2ImHIID64oGgqHGZTJMPv7GGKvGAEaLQvtjq0dvGKBhpRVFxWBFweq/ytcx1l9kfLUVQQvuhMR3CXBmuiSic0VLPFzxHy0oQU9dP2QfG71qe8ow2587/T6whzH3dyo8eSqfuqC76OLEd8pAHdh44W5Qf9ewTfO+QyTC87pMhJG2hNxSzEn70ie2MRgIDYrsjPj8shDS7wXWBG/Qt6X5jAkIVMxYPlxHBnpx1i2xJPBrVYtMDvlHXF3BdROTn12jRMf9qTqW7UDHM5KxYBSl3FiWdZb1sO8VlghCSIuAC6nUJQHpoonUojRk6/B4p+5fpLY7of2I590dR5mT3/eoKskYYlNunQJL+J3309Q2k+qcoZtzTcR9DceEbwryGwFVfFjdByVn4SlAx074NdkIh+oQTAhCMPG1uv7/kFpDAzStqWqwL+brDldk9z8SVR1KiT7yR27+g9EpgUkX4bSuMnRUikKZ/w6vSswk1U/witW1LVkUY/H6//k3gpYNbjIb/MDOLAv8ev4Yye96Vj99pQamg+aoNHtKwGwqP0JHfQQpADdhMDMMhraL0u+XYY2Cpy30BkZCQsxNQ7WBSfh3Kpjht0PKDfrEjkVyZIIEY2neh1B9+8YagMPBHQTdRfuTk7DlG5DB6BCqZe38nh/N5dkpv3c95aYa68VXXsBJLCpYikYGLcJnBCzxGP8JaDd8ZpO6Q1x9OFp+Y9aRccr+8+YEtg7nhuGBaIprLvxdIoI+ZTmsDM82jV8Ii/lXQVcX49k2Oza/lM0pggHkdUWnt36b5iXHhv7u8vw9s+v1YhMcdkeTdZkTmF7VBZWc5piT6t4VkZWvjtq1jwALRMd2gxWeqYJ+Yks+1uTAiAD/YX1oUKkFlmM5lxgzySZ2lV5g8zVZYks/nvomhMC7q+wnZd50koYrawG8ZFMAPOutxjeXAxtGDPe58u+xu7Pd/a/Jnbz3CIX8gEfo30B71ZT0AxI+qRg2/Y3dQy+zXiSjqHxanhivr/GDK5LWwYGJ1CJq2fk2q3Df469ps8JEdiKq4EVpgAQf77vZ9gKXNaG6yBLaBugDJbVQS5NkS0lG7CEAwYOfCQWgn0ZWDunng3g4pjccVDjovXtBk4ILmVtWp9Ni7TaLx6E/SQROySIvgDTHoEBSIguCZBeyuuebQ3GLnrMKgvLX6e8LaVqObDaLRGzQ8779VB3+obGP/1DLf5w7wf3lFKQtXJypZp0bDlOkTim2K8TrtcOW0lYCiHJ55+KWxJK6NB4qAvyDmwZudKuWNyvCJXWL8FSoLH9rx4rOWyhO0uC+zQfPK7Fcm/BCeUB3O/XT0KBksINZJcwYHPfBzQmEiXpVUakGBYOxXcY4uVHJM/6DeFHni7PcnednRWgZn2CFDHBlOQzbDEy8/FgOYHSDOTVnjNxH29y921gIo/xBllRYAJ3Pj4QvIPObv8vktmD8x1WBrbv0XtcDT/KXmTa5WrlH2diwLO9OUXb1ti/Cy3sDz2QztSaCNwUFCMMektKL9pFkfsM6UNths9fDfeI7xS92N95zvtxS2ih/FsEW3uiEELQ8/G1dMRZtqJAsq1akQ7wqSlq/dxQK8sm7TjbIv4S9MF5lqhA5vp6oYAzAVEk22rFHGsOSjw2DHhPAGGWfpbkX+HJTLO/ONIkta8fVBQUlWAbZRhz+npUL3ImhLlx0BXaqo2zNrw0TgkWqyDrKPbu0zI469Kc1yzN6nFgch1fdG9LGC/vEcLlHUYxWaEQAZA099KRmxdUuvYwNKcuaNfHcg2+5SEGM4cHRTaRfRqzfRlB8pQVQ5fEhQvPDRJrTpqpwLrMkQtLbYLMrwnCr1z04uOf0WQ/8ktc2MfL6Xe5aVyZE1lBlZqQu9ZO2+a81725ZAN3nnPrCmYikO4gPEfWAm5ROf+Z0awagJZ01XhcfaYZoMVoa2a7uta0lWsPRu5ZC/p27nybc7nv8a3b4J0juA+PX9IZoL+oEzdMxOH2W6deojnjM/4MraP8QXV3aWLjv8+PUp/sMryGLSxYn3QBzk3McnPwrkkJEsYREWAXFd+acgtpIDnP+WTFSkWEwPxdSxafr0qMKw+1yiTkqAYB5/cq/ZhwdwiSTndQEFORDH0Y3UnOe7gK2ocn+2ZRCs9nEBp4F5So5avtX+DdBgZYpB5qZ+YzUrMj77jrERzC+9j3AZNhlndPr+BLHUOsayuaK6vnxyrzZY/TMyxbDsPvNc+PiyKIEar9Yfphy9CO5yLVFtyeg/st/caBdJ1g4diBQVzmVPVUyclZKzRjhntZq319ePyrzeRmL0dWQI+/qVgPx3rnA8dAaFGzfD13ihOBIszYqJD+ayVc0fpCiNRF33W8/2F74k8r6oAXGuEAg3+Ndq0zyIw7Sc3NQqF9TTP2PbYdmMPp9KENJ+Xod8E92IGBcF9NAPP1k/vJIaDnZBeglXGox6E2LkhsrMxg8qgrxbxROHXhUmg5N5BLNTOmxTYM4VbeTz72C7pqWRDNJ2OsGTVZdKhqoTr9MfmdK3g9+yyS/+CwOMmyWwCR5791t626Xdb475fb9R3HsOo84FoQzYQI+tCaI/4cWoxw+IooR4En3TXJjGbsBQliDu44cgHwld94ECGdQp2ZIwHZ74PAFJ4riiOZiTJUV8vwU5F9wm9WOcVTTkiXQ58ffn97da8pNP+ttGyAjm6ue5tSLkSMxZkh9LAChKiCegEJdTxJ+byHDR+OptcsMXTt1CMTI1U+4gvkv/XBT1OstGA0NfS69nbsIVPP0xqN3NNbkxxR2MUB7lnFALH9JXvFPdDn1vlYU7nde8Z9nCrLdMXBQelBmJz3fHjj5HolCElNh2HmHsE3hLirtkzgw5PdK3Nc0Ncg2vWPxBkDYuuFWOpEyMQMs8w49ESYdrH+op+t7ZrAkw/ws7lA78Fp5SDiuDB/nSSdSam3p9LWNOlwpksFYmNvg7G9A/tYHiDSNsoF87GGW3VcrFYoaE8Y1HZd9VZFODRmeWUcw5NsW3NvsW5ZGeuFZrFEcu/rOWRktDQQtx3dvC1ejnj4q7hpvc0f/GNI+jopW6a+1g79JdhAU31v+ZdM9tTpvoIyNCKqPqZtD06ErrAZ0lUP5jvgB9+ePLk1jItZrrq1Qm4rzxjfeJHn/n6z+F1bBROg3xeKgvX59H0ntC2U8CSbecwXY7FJ/emznXKRdtbzuz9ahS+Y1MHPNtCilZKFeABIgO2iqZkaLdfE2Zchd+9m9GzJB/LFROeFkE8vTNSaEePdv9wFmGU6sEfOpE5PmpsX90rYJl9UuNaxjbLPOoBKzbHUAoqlMcpZBG1AgmV5fHhs5jOwOMyIY6AgYJJZMkWbqcASfh0h0NOKAtsCvDV1SD04lFZ+V+GNw26x0whcR9ZOq3nf3DHYbQ56sAuD2nQwoBhBIOBkavA26BUn3UcnDQKCxoZ4vavm5Zsc2Lq1/7tCd0JkKqgr0UMKc5d87SwP8mBsPuDP7H8bi8G+az2gIhpDqJqW7f8eq1goLl6W9mLy5fVV1+MZZRnbchFops5QVjpA3t6H8VWWas6IDFyoFNkmUbYBh3eVOHsTJJecvpouaq4KDdX9rdOjtxb6SfcGeSFmcGUb1IV3+sY+gzR1qeVSnywj7/U+k+/1v//RfmuzTUbsiMF4Z22KCVVaDNXpCadrcHalgBE6SeP5AjrqJuq7xa+lAZrtpBI5JNqVUM4KN9WHBZI6Lnp/pJqe4ph0XIE6XHjh5vuH87Bm4lRieFHpMqQbtFdDpjbIaYipK2l6SVsgHImN9pIGMtgZMmpik4MSapLkNNTksXgXLNBXOkSvvfalbW2D+SPuIupkZf6iLlTvKnOtMdmMcpo7tdP8ZXXUF2ZwdR+BemGvHYfzYawwA/oyCC6046GpWZdTb1M3uiovBY1BVkNVCSpbDszJg9XZLlGmmdafy/y1GgAvSOgGprtSpBiZACpzoQ34PAt1hgdNlOZP1RveFi4q7UIXVcv2GN//Gg3kWu9V/AN56pHeEt1ALons6Htp5jkXKHV7GHsFQ9DG3Ahx9tQuWt5xZP20rK9wheWBsnMd1vZPRVWsg6kMoIucPk7m1Tzha0dKnuKUpwHFSN3hdKEP6ijNkAHqW11ihxbWI/6v6n0d/Ot9y30zhkLoQv66nF2uS3sI42fThX4nZL3+40ZcyZ2kPiI5J7W91tfK4VeGoKOX0tBQ/ffSSfeRoAcNIoxFx65fjFlsvZ9TH3s6NGid1IR0wf6aPuV6vpqz0yoUVys6TK3iKI/q7JBAVYgxfRlWPi3GUSVLYUzFUALvowrX58LW3m+7RxRZKPlzWLIHCRJ3HiAAxX5Ti5WOsU/4lL97tlm/qQlubGe/ER3aEu7IpiGGRwy0IjVTv7BXfsGByU+f7XjumeWDZiB68/lI/+qWAT/wT0Kn2yIzLWJzcSbfAqNC11oJ5xJ2gkjS1B+uw4BIWH6GoBeH6e97i7B5nNeyPKfTVZ54n3CfY4WBuiazC4D1v+JfJ8Ifr9UBiwlLeptoe0/dQS73aAw0lNP1HCWeNxysgOxhb0bue2Ceqi/AVKxbLAP2z08l8OsxDLMvaOADgHxEhNXYBTq/mPrr0JTD2IAyIIV6PQUfSl0aAOhs1RVpFu4eO09ilED/rY5zUipJTrR1AV5Zzprzqasyq/oypkLkryKxjDKp/LYdfQlYqBZxnE+O9Enm7uJ/7DXPsvtDT0xr2j6CEqky9/0xahT0H863xlZhw2ptwX70GSSXf4FgP26jSJ1EmBDN6nAwOShnWVlcfNT42Rs0+7rp+pWly2J8BtVRvDow4FJaaD4Xjetv9Qc8/l4qSUFXbzKQnLDb+PTJBGke0QP5wut/gRvZxaryvOPwQv93l8vrnxgz7zi4YUXxY8KnxbkuFXf28mDludwDKNjK51uLGLeCh8FZpDL8sKf8JoFqK2QEB8442tCDof3rraqTDK/zqp/IRgkvE79mvzhyQwoeWCAunOYMzAVKoVgmQ2sxfLkbkmJLjjgemK4atMK1vqI0IE/lL8vmd5hPjWibEU8CZY8+0kruAIxgqNtYfSu1YOCzzv7n6PeRe9LV7+qS4IbBUbdYx/OTw44dHMclh/IOFjx1otVAjbKIAcuiSIKKMCtTxYhazoOsivWVAF1kTaPRagf1gtA13RN32t0NP3qTRXq7njsEUFZG6Jta83k0FobQtGtMSLeoWi3PxL1foOidPa4Fl4r0RPQH+vRit1WoUoVGjNMAi3X7oQgLCxuPng9K58tR/LS6YqqnUCZf/xlGHORMOe63ls+V0v1hGPvubKt6pYjkEt3a89Hb6xOu4rmOfBI+gpqo6aUyAwRGFTM9fhJVMoI6hiqB9Pnzei2Jonv1+3c042fVIdONOKGQUDHnqvm8m56zp50TkA2dxjojNCGUAYFKw9lTeCNQUgUDzCDmpQanzd/LqL3FCrIN7SJDBcRMytqVxqYtdRT4uyMW3TWRUfwqwC1I0pMm58Us6rUWY581RvMBNi2JkpGUhU3hk47EP/qKOpjbAzZG+CkOZGDFQK9zBLBTm1fC0bKqMtJNfPt1RFBGOcFVRaLVlHIsKeW2EeKnkmzm3p3Lgzaq4awKMsVhOsoUCcwScyWObPYMr8H6bOAlCr4vn7K/IDEVBpMAgJCQUBBZQOAZGQkMZLd3dfurukS1q6Sy4g3d1wAenuhn0/3znP9f/uvc85G7Oze/bszs7OzO5RiDoxNeEm/liGKTqPK3+9LrE5ug7Rct/X2KxEnguG2DKg4og0DzopZI/VdpM8SHj0hgKMGqILW9F7jV2DXO7+0dI+nJlWchZ4JMZdAB2/Jdkn86vGz7EDHYo2FDSBVHvqQGKVEONfldBQ3i06x2QZvrn8NGxt3dmGm/zuzR2/rW9seRkaD3l5rFxULyKGoF37M4mBnfUJ7toWUWWTbNcVoH+aMSKSU80uVz4gISn7GpjRDKiRVs6qNsFIHcYwqHTZxZYi7AW42Krm1IRXYVSN7mAF5YOg1cM7WAe1h3I7F2+EcA46EWAGX0sZ3TVApn+djWC0wHGKOepaZLAGPIDMditlpKkopP5LJlfVqVtKlyuvYZjONbGW4D338spK+zni5nQUynX/N31HTKO5qURPBuIH/09OCJs9ik6txqmBkI+M+RD/bQ5sXMMDFGLvxwrsU7dDDGEzSEl2wmUMk7mQx3Qh5W+MTZ0UHg8qZcnCAdSVyNaBrwdU6pIhN4s/pfkhR7jw+ukHd464jfB3P7GXj4oNUCocIUlhzS9s0OsgV/ayFWHHyFmU6p4bEVXnXWlu0JzmnL7TEHJIFpjUviNEjsz8mqJe4XFfyiLyvI8YbDMctYQ0TY7Q0PbnrYv9PcknLZLFsiEQGfSxtjJaG4KqaYxTYEIjLg5XvpnFN+LrOTGytCKYFcYfcNMlYtwuRowpNo3W8WkBfeX7t+3vBi7yq37TKsrFYmb2t9fAh4kP2uj2t4CPyG9IYzewXe9xEWLVa/g06jmR7uCuDRvyBZ/mUNnUPQ8xCJFl1+4jt1inc59CV+Bwif0SSeLeVFCNKsqJEwbDIn0anM8NVkBA7jRs5bP6AXSD+Dl8ajJid5ilnL3pDVaUWXEGuX8L89db7j5lzOnFIGqvPwXFg0kQpj2cv/QnoRKwQI183tp40yVDcqUmDnA5WETZbsj0JVxZ6pAgWQ7/O2+6FILDn5nVUgGi3jZWEBpnbBnX2/A0xEfzEfDBQUcDgJjT/HAcop8NGSduPyNx6n5UvKa1Uwe/v01ZMZN7y3XhDyqHN6QotKBrtOrFt1DTnsGNMauOjEQ2L8MFMzESzlAz7mtFjeFcFM/loqw1LIBcTvt3hbUJRB15pFSpABXotnda7cqCjiCNOSMAl7JI+uApwOhwgm5+GvYYdKHAuU++Gka6mA3l4M+V2m43hS8LiC6kpGtcUEpBgghQzsTly+1jNIv9cJYwL/3mtwJR1uBinprEnGhg25GprHiM/FXhl5tOeeo2fApkKbSEVd3Fw3TYcy/NrIkJXhgKcTsceMUhJ8BLtIYGhIv024oginO3IBOPiaIRSj8tdlCSWbYmNAoPEQtg251TjlH8Qq4Y7+9hEfRVX6DJ4fw3IdLeoFPfw9R8JNWZHlVZID1+YWkV0Id4UTJL0DH+zFb8AHPz1/t+K03feE5BxcnxfUID7hUECywt+S5kYdLG7B3zpIB3Zlgzq30VhzxDsaJJIBLVESSXZaPA3VVgoP91pDc8xY0VevHv+aPFVEDeqGLUGT+JCb+0wr28AbeBjhSXu1c1F6doZbNqyUB4Br9cud5Hd+If7hNAY52uau7SmYD7EXdd6l+iNrnIW0HaxU1itfjfpcOOuU8cQvo4fHe72FZdEhuOHJw9gIZTngSh7T6W4PAxXRwHyX8BQMdYI9UmW8hJCcesTCKSKrxLl297D50q5FALxBsi3PjLlgjkpJrIJx+4H0SW0AsQYNCmob7ib5TVmxGvJCuvswsTCroVPzfsLPoNk9ZLJx89y8w8OQLu3X0GZMOrv4UEpV8OkFTw0Feu9xtyBe8NhvQCeV/bW/c9QPeI9VFQPiNcR/QxqvhYqcQkTZzNv0HqZpgCYlXRFlT4CQwEsw181z4xwkZsnY9x17sFWtDRdQxYGUJiHoo8Y8GdXPXMgSRFAUVPlP3pAJvKvvzObNglB7KvOA53tzUKe46xBUiX/zDr67Z8FzMoqCuUq5YIe+N1hhGOqySQMz9ZedO64S0wHCeCh1JxcFOuyOIQqpEmx/m+q9gzGUrYcu3hkkrADRQwOTp2ZUiiJOigsJFWRV8VUcJSZkzlyoZ2tLir+FqrZgXsSKFDUss/1lHbweZTW3TKVFMEUme4WV1uVcf/q5pEdBBH7PA/4JtrqCCsI4K4RZaAP4N9xFxQ1wl9/q5Gzv9x2Mga/Frc8Apb+wOly3zh6x2tS9nPmsHsVvX1Xi2nkMVJsJobwyTCIwNPoweKIKqEY3iqFlEbS066Pms19QC5M6Wl413js78fIlSqD2n8qwcppy6rHHyoPlEPLka8WygqDcxxdkQhYhEeheG5sM4bigcSIEdHvMFatmGACHrB4ORALpNJcK2ZV+x41tUCPV+Ci4p7eE7W8Z0MfU5qKVqKTIzS+FKKwRQTCzTKn+CV+DwLAGyh1avyyv3sH8UnVI2SagxW9GzFSvYj9xcTpCjv86qx9F5vJw62kl9rmbbpKqRdqZUBFwGVg4+Sn+VMNO5tXcpxiP5Ms4MBoVl5CdI27WZn4/2jV6whLcanGZR/ySf+wqkCLCq2uuW1mWkxP/C3b9OUUJKgnrH9n+nteOG79crZg8mqLy2Jb8WTsJqsT98Mbf4KRI5lDDsn3eC6l+c7GkJFoRHTJOD4CZlUPsjiWZ1TtqvExk+0Hz4NMDc27gWwmbrBZRmxVOoPMYmvSliT3UMOAgILGX/NwzC5FCzWn3Qzz7xOL0v4o49kKYsuyyAFL/HBAMHQ5C+MNGOjRyELiPlAk4O5A9o52w62IOVRLF2mMRLnXAs08g+G+IONAqBJ67WnRfsR7ZwS9cXm0O8S2wZPXilNVTwiagVHHSkDOxpfMt/fDJYYryhT+5PWcZbKaSXH1kVdbnfn/w4CYrplEE226kZnsN+Mp4o31wXQj6uvCHx9LdzVp2R0V5DZY2C/aWtef+ks2f+GZ7RHTKAje7TLpKRoVixJpP3JWFr2tvD1s7W2r9zDfh5xETclIPvOMIOAreTMorV9/m0rNEHpmGi9NJxVISaeqwrhXKnRXGvy3j45f7gRyfyPYqUnwNo99Njy6Tp11CEq41a47Ec28BXrQ7nv3vaFuiC3DPdNEhjMEN8Ac9vssuVRtcVqHpHJ13d6XT11DKxOzUacyyMwKM9vEN6H2kaNii7N2KCkSFfg5jl1JFm64uA4oJ5pdIS9/2Hc71KCb1Z16ELI8oLPQRao+MyXPyYrRrnvittNF03Rfm7vlIOtPlaAwRQRBm2sNEfLEEIM4Sey7rCyFf9jNcjE62NEJPQdmElk+80VTq2r/3RfiMNT9OAx0PtIfXxhhfLJatm5MC7pdRzsX/5UJboXvYcCRqvYzrroICrFbOfFKfxXqW8UKa8NUd2D0Gd4mkjsILfXhxMNlDPLprXW0uylxoVYZEEZFvfdce60U4Qy6ERRX0KiwWkyBPJv8v4AYAFhNPCycdoqJ/uCvmSZPkKb2iI7DZnn9mUmzsrz0yt7kam4guKOm8Bvrk93KyNBWB6iH1VO+wLPYPZM7Io/34D8+9AJdtX7yiLxZtX8RW3uCX2njbcReA0i3+ade1FqQ4v9o2j6mNZi13F2sKTuppGt0vTzXedIUwLPv4tAFbJg36KUD3nEo8DoW2I87OwvzYYy9CpLWVYW7ufOGCI4DU1I+C2haODBUPt501AUn45BWACv9g/CSDVx1gv5D5vZyMI3wUmi4lX0Gr7LowJHoJC4OKqBWRwwOsdSu2vMjTuqYYfD6s6KsT35YVT7Fy3A64/BF3rd+DL78ivteQFl9B+wekBjydpnabC7GSi58XUMWwHWsqi+mUwCNGPvLa08PKKw8/klcy6tXjI7jLT373FRFaETGEu2oqVYphWAgNTL18XXW0tSRkRjNcNNY2aT19bvyxe18g8ipQ6qfuqTtmcUddNvWCWLOelk+ULdZWbtNVGjiPeEtLQAhV04oSc2y1ufW69Hf3v4GSPa4yfh1A+9g2mY/9Jm8c2ap9vE9i9SwlSXIPXR5qeTawChXcRtlENZRML9vA5cwnmwZEo+GOJEv1Qy78HHeTn7hsDP++796P0SmT/urqI6GIoJNvHf/tzqkKMuj9isKkDu6VtArAxCZzUtfUWwk1S7SsaKO/IyxCeFQut9hiUmq5+p+bhN0ad2+kWQfYMA5KW0aWzfZP4SHWS016irhImzdXL49TtRRRG1TfHmjrZFbJIceoFL7GIgygUTMy7CGFw9y4MJQbGrP1nf5gJluMG+dhlKh9ws+ib9tpwJ+AbcI94+a/CS++N1O1BFRhfg265wi5quNj9mnw8b8gWG+9Uv4GkKvvw+vKS4hQPY2Cb0l47AxzCApPGlvZf5ciV5+UjtelGDAjxqSeh7HjXvzYmbtxsqt7qTPzvJPSNyUUbhHkb0TyVnuXP9zEz1R3Zz9t1KqivahCm/70WEqDL4qF52l5b4XvKdveNW1S5wYSwh3gMzgY6NPxfbN+QBJjN3X6S8Y2ldrhnAs3Mr4OACibCyzNFXUAoa0/u773qjKZwhbWD9SGzsJXyf8RGpIYwB5W8aATqmlz5cOonRN9aYBP3jcvi4EjjepnaKE69w6uKAhYZP6eVsU8bWK8xzlqc0jwbcDXtRpCfnMCyb/rwetfq3wjs6jcOkB5olFxTzKVxczKvaJeZPh0k4x/pOmIT0DGSzZRtty3zPL2rE152CjC+7hLIbhrXfAPo78ixFlpTc/2c7YE+nYArJyBHEM8COnootiI1C3k3TwArL8nM4/edsY0saKrvqA2ZxpTDuKJP1Q8bmV/hbgi9j7xeGVV3UCpQ5xhP6yC/Fjzb0xbYfVyaX9aQ/N1OjHcIdwDG7RDnJ9BL7LN3paLTRgMfjheccYAf1DnBuPk2rT276nyrDhd4haro/1117djSBTYaPlQwrUsF+QS10otgSgi/akQZbCsl1w6MRMSLx8Jk+V3y9/InqkdvQTEtKsCCRNguXVvtIwtTU7rD1jyQtiEFcAcWkYHP9n8keqcU2hXbycPQLbM5Df3SBypRjTXUg0Rg9wcgZWTlYOL4ZCOgYn5kmkEZ923gvGNz3c/URia9AnDKrsYqhz2mC45xr+KQVqGSzrdIMr6gew8I+BkLkfotlYcrYtxUh35BtoUEWgCdDNCIbhyoEgxia4zKE0Rz0wafrruVjQjOBRNiDGWsFKXu1JcpPg9/6TZBPZfeQ2837wnBMUpTLcq0MVwRzmd7jC2Hn/PainG7Zi81DSG5DJ+Fbek5wJoczZTwN1A4FOhgdG0dh5dtSNz/lO0JGo21d85VPviWX8X3bia8vq+V4Ag6ylNLto0CRVd5Xq44eWagajFkeSOeWUSW5+8aXTLTq57EYwI5KAY3jcbed5a5Rfsf/wNw/ikMwrQhd+ByyH8WgeSRxB0FLGQkjkFFnGxBX7a0fs5vJ/R2pRZ8JBoul1uoOXxRSbVYGuDb56QxO+V9o/eo/oK0DN123oXARuge0Ya68OnUzPxkOsT+G27FgAatqqhYCt9tlvt4SPGdFqcwCL8Ti8AafYSXTCllR2cowNkiyYlA9vb+QlAqkdDdkKW/glW4SMd0v5xjR7N64hqHlYzHmLCmh8ZlqpReI/s0EUwQ4stCGIOySNqIlC0sTTiJHAqBKETOGQ4whYYkV38EvZMnkXi7TOWyGqqHu331qgWx9LAfyHdjkXG7rHZlU4d7DxtEs0Dv5N1vwCRWqBTUWnf4L2dxAs6GCGbfBofF91r7VoPaazUz9lVWVpk2BjzqanZR4iD+QZQ9wb6ADWiXDdvJp1AB9JmWRd9H1gv18Zn1+uLxNdtYC2/2KtRcYju2ASHYyZPAjcFyMEuwsMXVWmY1Dg6jAvhBVZRULlwptl03PSbrDMIcLiYEYCaFCgSq/VKCPddlaUSvNb9yG76+MJJg5gou7mD0lizQNfgKd/eGu3DGmCups9Kg880XJhYtvnSPOKq1Wo0euRbS1XzEbfNJG2oLud/Ty6dns8eW14AmghEzsgd/Ny3RhStAb+9hn6Sdp31E2yHY+F+8aqowp/sokCd/5ewOqwLn2kOWcYmqIcpiSfMaRUEMG6nSdeqbyfGcZdKb+rzIofEPGXGNDmdUfAkR5mplv4OmO+oxH1SWl5lr8KWL3QcThZoR9QQte6q9ovNBUxTQ+ke9vfkdKmukqBeC3F1i/pm8zxU7xEk3CjLtip6AMiBDz7Z9WkHMR45Uj6jnQvZaZxTlKAWR/mlvEqirm7219nUBOhyhWp3hF6Up/wZck67PulFH4v8doZTvdzM47IGxubUY4G3Onwf1KlE7F6gtcWs1eobrMA+9JAigo99pvvt4gK7xaOt+9SvFtsGD9+hE937cqys2VFGmi0oiK5E7km7AUIWAivANS5Ide41bp0tgKUVE0ITkmG3b5qtIJ6T17TGBVO6v/tQIHrtB6WyXOY4XKWV7XyCWxp1Y5CRgvm38P5VZrSd7YNvEkvwhizAG2DOb3Rq7y7+rNyKUwTCoGOWvwxRXFh2If5Ygoc0LI/wZINHgO5IbajYcSt1e2k6TwjDV+5ZOMPjy+AXLJaEa6aDTuy+YTOHf4NeMhP56ROvln310wkzXG/UWZuK2eRuiTRb7+WYloYO/0BSCoSs2qnC2Q8CutGL5RFUxYN2gzksu9Cuh/PnNnE3ZkrSDCnxme4rJLWtdAFXYpAzPVJ9klfBInbLn84RybzCChnSLYUKsV7yB7FiTaRFxrK23TIyMBa0lbtuFs8BQfaKf6oef+xFtmplic040R//QpmYrXosgC9L00VvQBYUV568LItcDfPITR3Ncm9MVuKZ2lVS6mj2G4vlQpvWtu+zVtT51a2CyfXbv1Ou5JvdndU1PZq0jNZDOz2FhW7cR8pdnsH7/gHoEdNtx8S0gVArHDVGQinh4s9fdZlfbsJKjFC6d7WBkEhcNd1ZNdkXpl12lF1YGMmXLoliQGU3v9IigVzkUDQTYUKWcoSOQWfz+cWSiKqTJJukSErHeZXc9DX6ZP3ONnTBe0Oag/rqo/NA3D64qYKDioLzYlMj5gjpSQ07Zl6YGl/fbrjGZCEelLzElU8wMtOoUl2JjaGR7sMDoKn+5fMW9Yo0DyqVryDp8wC6dfN5VRZrVvoMRVSO+0U1Yg4C/oYvN6/5Hl4c5UvhArTZvoSLuLbPLfU78B9IaNsZxRjDyATIdaK6uf25TCCX8TYsSJqmrfQ4/AfihjX7ipBxXq2jMcIVuXi6e4TmP9RRZ2L8RhBMgJIS459/jb/ZNdQbh9xSficwapiecf1u5OHWduwIqCn+nY9HJKy2niFKVD6rUtXAimhKYXizYlG1xf4IylwRxidXBqJjXaLwtQdZmp0ZF/MMMKA85uOuponU1vk32mJutrHvcnaYRXqM0XG4i1Kj64iHdRfjIGr+6JjrEgxHIHyzmk0gA+OXKCZMeOAztzuTZk9ChKjRsE76qmgWOLB1bw+IUz6gy/3gsYwcgNcUeFYnBmXcslYm1XeN9wvrZRnhTaDVcqUQt/WXTVvz6MAM5VoBvKIE76j1ZaFFFWHb81hT3kVe3/yynlcVAaUI+rSw+xzw1sQORl9TUOMhIKMYm7pSyvZyEqKE/fVz/gwyMW3DwsYZ7TrKnCWF9TSYsbqvdWpEM1g9l/akXXRNONZePQkObVjeNwx35JRbcocsjP/1dZoLKS/PBCH8pnHLV5uOSlsq9c3b6G2w4WRn9CUfTKwLlWzbUWcl9/fCQ9/ZeJeFapIIWHx4KtqG9cVeHUvtPfrM0udsKvplb1/KhUwaqfcdSc4Adn40qxy6F/2APvWbVHW6nhZvlJarVsCTLd3wF7iPGbsUPCcRA9zPZg86LPAB9hhwUzv/1i72iqyrGiGO/aTVCGwET4B6yS1WBKm5YVMngcv+TCql61BX5oAUsrgowkM93lbCqob06gLyHFVP/CtUNanbYr+dtcD4pooVvn5v6p5KgdBKIz0Fm6voiJPzpKQnMZuKJYVudiHQnQKl8CKVZ7X7EPMUxFkwWGj/rpqhA3XpIi7NwiwjWdq+tcreKW7p4dhoW7YMDlBMzWtrTc+vnNCl3VRf/CFfUbw2p6RodUXcPY69wmcQ8rbY0+mrSrr3sgIy7I5CSow2FONGhias0zXG/RHC/AAj8DugTf4JleQYhnmA5BnEBqswog4VedR+iOsQqQe85+uIySY0HJY0EFrD7LqU14UlXJavf0QhL5sml9+RtToiUoMfC5j7d9F3jdZu5B6smpd/3d1nHiIN4h4kNgyTybW0sKB2Y/5NrszwmootXYIbgQXRjT6/zf4xK1ebaE1B2AkgBygxC/e2KHEzO5b0S0ViG/1g25e6vENUV8O4cayrtxxIUqQ3zgNPHtz8/F9QwtvpeG0hz9x/eYc+iZgd4MwPGfS/GQZdcMfRljFpyvOgyxtII+8iCoeWGmM5c3+XjGF+vHNtGU8nJJ6zW+W1nfgwBKOlJgi875VKOySQDwPuF0HPaK9uDdQqOICGOY48ScZpHuGdsu2wjTD55OQi9rrEEotdjtO66Ku/hwgixKiqvc6lBW42nRyzs2XUqdD3+uSsCJZuaW23H8rM1a+YRIZJbU/qQgddfxCjRrA668dEuh09CtAufoDNiPcinFr4wsH2JVGYRorZHik/LTxn4/+DKXOiDfbMY5dX8vjk1pYPqsEtkZL0tulHyG9x/faxTwsBpZJeL78RxUwaxEbT1weUQgUM2+XCAMUfHmBX2qFSF10BhFQ8B/sHv0ROd6tdJXlvxrCJmhLzZNKcW3TuQa9Cq9vo0+kuBGg7lOSmtJs91duBpyuastlmUw33yYncMtt2gxqohUGLam2uy/HYDfT3rFlCdZN8W8p6L0bNSSaWGT5uPm2YgsjqhJxkakEWLLBk3bGFnwKQIIBzIx1mh6UmlZuFmRZJ10w1/QZ0F7kC7gkvdWBqQ3YBHezXyrm9Cge/GmskSzwvvoxurAXT8i4XvJAxI36pHt5PrwNt2gXoByZBvCMlD4HtSFfWi+06T4hJiIvgc0tsyaL9pZr0gfpm+X/rmz2Mn6yvE1lwN+1p45HZEpaROGnz5QtbUtSi5XdxjAq+73JNmv/6iC/dTqiLNv3YfCV1uNmdmMeYDyx7Py6mP66HuWMiUQIesrkFwSQdrgVAjutz1+1axJCdjX69YB89F5008B9wr+VTXPESYzbzQGA4QDuoAVXUOUGjksFeup8F4yH+Bhe8LiAlIfvroQB5n2l+BZleYnRjyV2DSxn4q6P962yGjWXIys0aYo6JIBBzkifI9ddDDSTGq+F0+2FmZBQcw8ScDSLGbiIzqCbBchcL8zHEoLh57ev/vI7u5WN986H1mCWEuyED7GV5Z/P1fDXNOx98S0fTG6skG2xtTkCD7oPunzEqGbKyQrnMXDkAjGEgKOijdI+fjXFDVUXpXjD9NrEaL3GELwqYv8oBNx7hBNNnvC3TIG4ZteZUnWkY8GNeHtv/E/qF8KEUcql/VPpgjoTCCulYD2MbIaS015J7bg/KPeZ3SDodrnv+gWlAqlDtw81cP9pZfFLCAwFgdWN14rgaV7hV4OhngTmyUrXyuirTlB3KUYXTGqWzr6jADmBHHByBwD/09YgK01ha7VoJYVHt1QrSE3LTjSBLDZpfyJYpllOPFfafnxPkJIOgPVQLOQBIB6QVZ2gafKc/b6IRN168+I1p0+lhXEegOS12IGtUYltyQsV+1Jj9VNuHMcq4ZSPT3emGcqqWst9vBaNQ9qG0cR4t5tG+drnKw4wLe+nWERLCfMbDyGtuYEiKuA/YCitcH+bYITerq5kVoo6gTxCfA7psE1vsmUAtCMpXZKgR4bqBXKgRNVlyH7ZkmbmRujdE9WiP/4jEujc5TJ0mojgPPeKR4MiXrBbu46IxTMcpCsFn5RL20CX4jKcwIyKMHlmD9mFh0mat8cUdoZU4wzOfSJq0xLC7uLH88xPltI7QBNELZgjs0ixEe0nU5T1lstSLuJshKNzhcr9b/xGSM2iIlPmSP94GAY8ZYIjtKK+BDLkVYP/PQ0MM7wCwuinfmQT4qNFO5EboUI+lc+jKuvs0VDk7od9Wu3UM6oLIo9GauZdgOozKYKIxrmEpeI4hTlYmhzak9i4gtCf3lz4dl6fPR1JilIaiflCdK4ZrkWzX9bTFG+495KJEDcn33WAg/M0ABEqwLWhYeXjgt6DslFjNj6hCLVg4IDGOga/r3NQC7yi5YfHeH+ngFkWBwWxeVYqBDP/5fPXmIJLx2fa6fcAWo7q+CRymjlM0NpxCX9n6PWLZT7ywt7fazo0wyPBKg0JLzLKqOKS32cbP4edOYbJT9/BPM7phQofkH6gyod4XvBAKGWZP7oec7dbS7Vgv8FjjLk9JA7x6sh249W1BRfYrua/5KyGMMbTY/wbbBBehb+z/WW3CPoEcwgK1DVUrA+/t9Lg537n0HbzcVEPYS4/MBrzpQwGNmt6OWg05GJvjoZ13EjXPWt6HpWKcB3h7iEWf7NijisWXm8UmReS/xfkTQxvQNEHU9A3if4T1+4ba2Vzac8yATRVk2NG6AsUW6JPM9/JiqPoutZkvi0XmKyY2gFDsfU3sAPKREsJrnRDufzUlkNtm5BUrt3YBg6i6flQArCP/p+pbvKg2Oe8398yEIpCML+omVDamvinIIXxjytSK6Why+Ko8AFjfHvZzcEX8YU9eIa6JWsn2RCYvpbf78UkRy0M9f/AP9s68t7Shd7TlP0k/dH90cqxlWmRcJqTi2ctAl6T2lBuw8NSbq1BsG9g8KQ8LsOrslDeIn2d6o6ZX1ahL1zmc47QxwAeQ49M6W25Qudn6WE+1LNob+zAtt2vpeaNSuNIiz7t8P5XPSxbkzRq4JTgAGx7FDj7TmijKJUHOBTilAOH+jLNoFwDU03yhMqDab4e9HQWTrV3v4QRlgiMvVkAWDUsPI7pp1m1QHHHeS+jzlKhjJ/3haqWy/8wUvDOgd7fNmHGkKBCgT3RJdJIeyM3ZqsHp5cUaSOovjAD6t7TVL9ulQAIQJumL0bPLInGsCyzf8zIZESOL+NuRaMV7TYiIRwMClavGJhbWZnYMtCueBkSETtXbV0wOXQ0Vi+7yi2Lvh8GYDF8Js1BzLFKzPVqXJxBuegV6AoVkPECFpMR+c5F/pbSZlhWwYHU3BqAvq9dUFRYSrPX+MxOBTKrWbhmjIDeV5lIyK3Sy4RxeNAVsnY+NNvWQJiMB7joDnAmDwa00vWJTUsEyR14RWifvjJLz0RzE0CkqNzNmBti+1G7pxcGS/Y/EyXxYJ8wjXUzs/TEGsUF5aeUhZZJY9YQbJfE+jVn+BcESQtIo8NYIYCVYmTTDzczN+EzG+5qEYwpNzuwNifzk0b5jIM2MB8GZWoc+LeTlvD2h9OzzZntLFsAGI+J/CO125ZjLo380s8dLJH/dXJ+KkHENW0XZw7RCqhr8kKOKMvQqvVauV7fTqeLrqFKB0z+T1dqAW+60Cvl+qfc4nKKOOyvCl81nU8Qyce4wNSidMTqXtj/NG30IVBC/BQ0/tK5CQE1L8k3S9gW+wO+HXlSS7B9OnOaxt6DH+pSQth2W/fnQhr4mtIQWJmo9xfkbKvmiTv2AbpmVxjtSLnHqm40zG48FcKFtR8cMz56HJkZE7BFbBPvUH29KkcYHpDiI/rANNP4LISzhUjDfvUnGlvreWiTReSraUFXMcFmHYME5NYWPscdnOKkZDGnHRJt9b5b6PdwFOA3zZhV7n8o4u/eBqjt/qTFMfAfuo75cajXQbTW/12Cu9TUtRif0q0fwWP2BpQMKcr3vLRXWYKrf5kcudnjPL3ebvr/bLVvM3hRNoEpC+fyJaJr6hsYR/0xTlk325Wl0ITuUF4o70QvY4UIpkUwkDWIK3HB8W4Mthr5hZHGHIVdByBurUy6mSjWEfDWLPn4CHTswrCaqNLCWyITg5jvKbnFzirs3NffE2vQkY3fxviuJ7TVN6vGOnvl17BN2XWCJCiv2NhoVR4r/PLzW6Y1nLoTMIEEWqCBzqLIOAgLzEcw6n0CMumWOFare1uKeC0f7dWyrePfqPplGPvnEu21w3NpA5MuFdRSZwsT9C+QiONnrBkp6tGZ7G4Oua295SXWMaVkljjkKAIfnt0EApCArwYcccRHB+IE2svAF1EKRRpASJgd/CX8UOzIFpzBZ7GVuqqoxVzGMgjheCxXDMm2tt+yaV+SPhQQRzpO8cf/JdEm9Sng2GwOrAJHxIifgXvb4zoP/3k48EXoc/QdyDjbD5gwzs0SxwSQRXCJVI5zXuYUHjbahBj/3AlguLepIu5hI/WyYLu5UtMPEQTb7pk8VNKDz67KhgaGJhvBsHbu5eCv9JRUuiY3MxkL/zUFKTqpE4tUKxQLl0PbBvI8Q+E2ZnvwgILSXRTYYCi16GskwHOIAvL7Vrw2sFLd0vuz6NNWhsuQytQC0GE5VMxtFgHhSRSgmsj7h4jGPHd8YoGXPGzYEntEK5nsEzwb1P1LsJO+w7dlHFQDKggDQZBfP8cCvl1WII5Jt+4KmFmWSDAK6NaVy8Cb6W/FKKqMqSRBySpA5DGmYm6LjL3NXkbPsDziEMQj4EByHx8AUMZLJPvNVhaF+QWc1Rfxc5JyG0Ebz4FoYL0rP9hQFXeIRVzf1keI4zumtg8mEE7PuymHZwcWAcYltoiWx/KzgZ76od65O1wd6NY6Fwk4SF7/FmDQPeitnKs8tVZBLTW2RWM1kQsiLnri5Z6Z2/xfcc9xrz2bgWUUknk/8UVYqCUMEDVZZ19lIMgLTG9iT2jCecz+sqXoLsm5kvPCrZxODQ0ErhH4kl4z1DScc8xGWQid+7gFKSGrZLYk/KCQHPPfRXIZNnC4nZ9UagoZQn76NW6zqVUbnm/IVbbNZWlz8Cg7xici7xJZPyGA1na4F4IYjCXPNoqbFGjFR94JzcNDo0YqY/JH0P6pC+kZPkBO0jO5alvYK+5jvJJUlAnHh9lAG5xTZ/8UIhdyh4swPsI4RB+G60M2WqKqLSyL1MpamT0wlyvtmxbxEeod8uFbuzZkK5Y6zSxols4VigfPptt1GDddbgaoW/bK8PQFLK/s5bAKMW336B3j6M5NjOPPPHt+3JeA5A600atdE+sjTw8x19VKvjNPmcnbZe+N1FA/G49IPv/8M2EO8LL5L8PPllIM/4A9+EG+ZmbukUqbAjN80VZATgTfn78q+wD1ZeS7PU+LI0vseytgPbr4teWPUmXHoH9mcig5UKhPgRChfKe7zQqStXDhMZu/tNkHIvtM5RvQuaI4IN40oXj9DIA4mXpZtk4w766DqjHMehNzK0U32iGbdYCpsZjwUZHug15l3O1nro68A5nfePShKDi+rgXgkDT1kJhA+5BG2j+pXNbSbpuwA/9r2IPMcK/ac+8+MJfGWRW1lLIUUxCu8KN5XU366mwmf41k2GxHUFJLEqn+YK73mn0v3jvEG+qr4BmIM67bdW2i+/HygZELt5adlCGmuxgz93C3Vnd22O4QnQufdUIoz+GOd1bGY7AMd2U9hhXxLn7yeX5z+nMQ220yauYu88O6mMuEExxH3frxxx6rig9Dcn/E9evx/hX/mJdJd2wXaPj5JWU1NUf5WY9do1VAlKoOx9W7UCxem9BPTuGNiOQHMkP5ybz6pas9uP5TCO1PuEexnyGVNYt5IR0t/SSlsEJguyrXIaLSPgN2f3NkI57KX1ytrUsv/ovkdiQaXEqUGG1uY/73YMb0ilino/WLjX3z0la7pIi13CbvlcCFJOOZLluKYhv5A550rMNpEEswkkuPHBz2+iMky05lNzOyCTTo5jqtTO78nxvVp0noa/L15tAssbTlL8Iv0e+W0nzMHTELt8h7ixjc1Abwh9JgYLjkGuUbtPd17VYdr/pb3HSX/LOfg20eOP1ySlBMlhbBsw6oSu+0878irTPHEy29CE6xJb27rwpB2FLxMz/40rBzhwEcCkY31BpWXsyV1/HAM71rmHcc0VR+afhKNep5RidlqUVu8CoC524gJQF6sWsr239rDUQawr4gJ/1iv+645d/G5sOoSw492ys6d6xGGq1IerF6OV15vce6/A7qmh52UDT3puUI+brXelFZTBJAONgPButBsLIrwI3XCddWhK+WVjlcrJqSfHSbskwgoU34Q05+YKuh6fDO/wJXcGYfvGbLALXtqu4eonmCliDsCYtwHdOHxPV5QPFA7h3tp/Gff77rQ3Q78v4gX29lOO1lymmD7JJsxPseErgKJXra+mIZECm3K3AsUVgBJdMkOdQD4ihVB3SiHMtwieivkHphFfJUuS7EyNkj/KY5Pk+v+/Skr6kRGuAj2l1BAH9SxlwmF11MRrHNodGrC2f+y++9IkySfEtd03cGqN+k59V+7FxiiJ4tHrjNBrvuOzRVUBHfFdlSKXl/jbov/tqADKP63Zk4UR15EcLfJ4PVZUh0eAx8fz/e+h05B/920w/HwJjjr3FWKDVkf9dy34Zvqns45cWWIuanF9mS8heUkM3KFefr3MxQDrDHeAyMgVNZPGN19qlOp5FpjEoqtyKjvo/7TeqYdVhcdi6U+/K5GIkhbvlWmA19QPHammEKyuQ6VTesBgmIVrNcKYc59dV8WtY5Fol9ooLgTpHuVIta8ubEsJ9zmy+SEpHxGK6wjUadE4IVAiRYFRkFQparc70yiANys0kPUeRAWzUNcEKYuhghHMjxUTdyPZDLSrc5Y/bPKdinyK3ik7MR9t86gjMHf9Bi55B+HAXaiAksR0OWrqiFovp61WiKX868vkDUKrp/OgJKrEJXwdr6Ged1JlwmzjWQSkd/JqeZLoWrC8VI5cpPXJ8eibHfek0BxXFvPeZkrpj9PRGnpBzl3uYr6dj2XnRnoEKnyfuHyYMWmirkvV0lynwFP41apYUf6Hhw0wJ904VWSuKl2441fwIlpRt5F9IXwBzeC4ByRsEQj/Gzdohk1wtaPy8f7lHaIJsgtyIOVTuyG3VgbECKixPmPTl4xWUxNR59HyD2cCMdcgln/dG3xF2mXb/virSjar6pts8v5lH45yi4/5omwyp5PVhSX+iyiI1XxBs4Pp9rsrMx3+dAvhnAuOgNnfoJqrpa8R8SRHLMANBEFoAJUAbNV4gAggEat1i7LFKgEu82sfDR2lr3j8Vv7PuxXaVvwdawQAVN0ksITf65Y9qghFWIj4NUkH9aaCN7VlVx61Xp5Oat9T77B3FI8ZFWXiCZkGGGRr7sFqZJQtToqExyY8f+kwwebRY4f93Dbnxl1nuQp2lU+GMTIPv5iMCiiSZsvKrJNw/Va5y5UAW3Csswl7d9y+pU/O24sxUCX6rkG4Evkt+9rYB41IirSWDqs7U1P5NHfwIhO619HewppFgzJy+c6LdtwHVYxsQfcOSypJxRn3b0K4JwyIpof18ZhYDSMc1jITN/S/3Gk/Ujw0jnBgA/uA3MMFmQvniqk58cznH+9Qb/YlwTJ8n5s03x40ci2Bohg8nt83SgQYGArMJjhXwLCd62bkgwnX7fzMYAH1UKPO5/zlptmDF3/pyLGXHIbnsR2XFpX/nH1EInqNKeEpnVWAbF+fO0iVMuRqksr57w7mb7TWvQyhfaVn5rXL58m+JMFf5OrdRC+Do3dwVrmLDH32H1378dGWY3VaYmR3InjEEH1EMDcS3SpVsuAhjcDa+mEjxgrjQdev/1/qu/cduQNFaAS6B/RG5gFfxRKB1szkN4CBNSA2xkIvndu5/z2TgwQumM0e5Eu7+vlaox9xpBuVjDmNykXEjWR81lqPNAABAAElEQVSUa7eQ94ZraKevyhdHFnCMtOntDG8TsS+BGnltTjgoUXW+4Rkinq7yVKaWLowfBjj2xww9O2UE6mYVhCDtk90rhL4atNFU1UyOa1gE2gzM+jF1Xkx/QfJKhZuDNv8rfhUc1sUUqf56F34Zhd4UtGWaqdy17Qca7COq1qaIWxnPThb88ACDapFKRpErrZUukG2eOpwInYkJKBD2Ug8oEzWzi3tLoPPCv95VCjEQQicAHcKOEDSfjptZgcw2gyUEiUj4MIo7yeBjpQZ6fRo1IVPPjarK5/JrK6vt+IrCpdN95ExjbP52wYH9WmzZboyTu9cgSAs/p3032GL1IHYdaXoOrmih99+AXceVvMLF/UnnPKOgnbP2lQEZqJmeumum/STiBCCP+xmgLqaOfDmxmuAVGuKPpTbfAxkQGII/XRtSIMkjmZm0jBh4xOaB2kegtfog4kJadaZ/uyNGAK/s7Pj4BfqCFLBK4v6ovlKKq2+hhMOpfedw43SKrvcbz8KTf56MHIMgCjl83+OhrqqnlLjvsrKw75+qnIJjDI8T8bMS5P6RwRwdYF+OKFItSH/vhTVRsO1eMWKWOLTe8Ii1TRfxx8gfdW6RLaqzfZ2O5bClOrd9Oyq690iwNiSWeF62EESwJKOzw5KdVTCIDHwENruka8+xwJgsZmdEKBnR11E6HCUydCI3X63ctjusoG2vJFaib9zuO+F4VS+WxXQJjNesPM1zKwMrRNN3kACzrw0qVb6H0/WPw4GFZK9igNKV7+0Ud7NTWV9CJM3RUvYEAsB9bVuqdbxycGbwRX8iosx7JKJD368+n4WX2fwHGc4Qd8VVLIiwYp722xSaw4X1Wjwu0ILoYq8Ntxu1+4Z2hHHkO+uJHAW6GPkYrFqgxzxgQGK6zp4EnC9vocq07f5Lt/oTriHGTszUL/2yLDx/qKaJs5MZ4UyJIC/6MWh6haA07/LDlkF7x1CNIB2K8bVfMS1gk25ocTTVnlbty/D+439sNJkGxv3TkAZNNw3CO6qSEdtJ4NzVVnAJzLFb/I67LhKUYtet9lkZCEcIrvzLYpE+kiAHRhZYU/pLy1XOnVi33J9fE5yIaMnuNu/GfTVsaIQd9KJdFnfIkdqUnuxnmO3CUhL+xs86uME9vjBXpTmflJ6Vwd2P5ufkAwstxTanPQdMHOA6NBiRxj4SsKApSQwEe/gL1rj98+nIsYKKS31OR+tIASwLdZvLPyYMt6IpVxIf3lmwd8Cd/yjbpP5KlGMFxQNMmtDqn/l+4pd5fe6sNtUL547iqsrpL6ru89XDfe4uHI2BeldvI5NklFhOUXWTTqnO1Xm3oBN98THNkK/F4qVEZCOtvfZv/qPodyDW4brCL43W5SjTLqZbFO2l54WfK2ypM4XHjcfsf6mAZ8/T65D72w2CaBc0vVOJCzpzqCXc0i7JaoT0KlZX3Pd3YKlk8C1zKbqRb324szcSL000grxswHek4rMQICVH0G+u0mtWOYIPfh9Yh9AY2GdzrgyTSNNPHN5nGc77Td1+XST4TPTbLutlzyxEGtshMCRxTIKd6yo+rmL1xlle7M5DX3c8LOLvJ1wy+wtP8v3z7p2fUSDBC61szW6SbU+CwBRB6NJ0zf8vU6bCLmfX4LiK6grZmQOiCyqgDcaxGs4BnOoxiJc5uIfS7Bc+fs93WB28L/DbidGfcdad/JL74U714/7vA1gtZTjCmIf9TMKC+5CDd+esfH3E6RvMIdPCqDQw2d418UZkbrFiLXn+N7Uwy5C36oAcrMDEIc880l3LqX6aDJIeESOX7jUXXjVZN6gfY6xMlo3biX2txdjbu/E/Jro5dIqqqPrQRLMlwxbI4N1f5/3CLysxEeDgOgASDdG/jztDONxKqL+CIhxrOwpEug5U3sOzJqnrVk8oSNQmXqIr/z8DE6jWxG4TZomNQ1GyDNMQSliUwfkes8Es7bU541pAqHEVEM+Dt2Eb9N9maT5C+R4RODvyk8Aybup8zt8VaiY97l/4u4+yuc8ZGh385V8lmTl5l6NmMCRaqQ1HMomHkI+zDiI2LO0f/V4UdClz0HY7tBUPHbrNhRKn/GqrEvIe8dcP+uFnErIMDjdDWyvRGg57B5Vbt6cOkhmUFO/vrCKOb4ICqjqfvPTPmH/e+Vs9iLjRSbFEH2BHBjdQPyMY7RWf58xPUoy1bKtq4x9uIOkmidXcR5WINuciGpBDuZOkNY/85fW1Gh7pDwmL+ZxkrNvNbX9mkOUbQMLMe1Wl4cYhtm6MfyopBPf/tEBWd0KqIE/SF+1h41TwKoQ1piRplB3EPbdzw9B+ROdRyj3Zo9iHBV4LrsUt4EY0V5dyvjEKi+aE8etgwxXyWIiGQ+MkL6Oo+vNcfl4dF+7eM3KS2D5ZaIBMDVuD3SqnnzcsFoBLDTfdarPimG9z8pw0IdSBtql0jLbyRRH7oY6wjQWTI0tTSIIaZ6epYJ1spvMR+BsHkSvlnm1jD6zrdACO4pUhz0USkuELv3FNnnl5XYI1eS1l3LNLxMiy9zQoxqPHmaFRmwDCD72ipyrVX+zDoXlw2YfNPM0VsJ0hzK+l98zLe8tvTw3PC5GMW58UavuHw6Br3DITQZ4LZOFC83+OelZm+V/Lb4oFs/0TT1RZr4EajjSbhhlt46UK2pOop7BxHVV5fz113/PczC8d6KZm+El1KW+6tY9/MPxuubtaDI4isCgHa/KCL4Aij+1w/JBF8ihtrdzkOtyAEVWvvnVYfGjI7XGFgYVsViraAoyXnYSZuNE3drIxiNVgKwL2jnQ3gWYy9/188lyig/qUN3aoLDk9D+Q1wgIo/3htyiGHf7KPpIwk2iyUgAiI3IUBSFcCzIXd/fRaAE1QCX0/gn7HMyNtX8jOYnjIsUZ6pJ9oYkNGt3rtShWPDVNrEhwk66Snhd2jvGm7DUqwabChzLWOtJeuBX2LAgEj+Ft7A9HlDkEp2HSN4IeLkdO2AhwGdhnj/WwnFlDzfcG7pMOC+JYVZi2Y2VvcfSdo0xe3zkJufZ4IIZiIzHC1nepXllA0ftgwnNbNSvYlmNuAY2bIbzF2RmdXdVF4/xJHj5BmvUIskGq6mgWI8PLrbdYVFq3jtohpbhbT2QTIeuOLVqHdXfm8TvYWAAcMcb0MD55wghnauv2tiZ1x3T9fwJID/Z2rgxRSrgq/ie5dODdnXzv2O0IcRExjHQJ815kF1P94uM5/ozCnp/yL1kUV4JQOpI2joLSx/L+rrwb1zH6Ae1AAzAPMazeF31FIKN4BYAG7thJrEKTUNvM/O8TtwVVQYFkzUqj9tx+BL6ds6n2aTKvEDjmXktcMBZO15dBERPjTf9jH4MbKtq2gMKIU9xurAWpVfWWVWqlaq3bTWALHX0boGdtjrAbhzNXkiqFzRvcCobK5+V7TufzLrzahEvrudH9wMChLll8UYaZB7Rtt/Yr0mTTi5xH++Bq0H6xZSROW4Gyp2dwHA3MlARy+czHx4jh2FvPZGkHAvxL4u+7+91GKYNGOc+HP8lWEsXLTxMl8LHRyKfnRJjfowlKjrSWowWZOIG0JBu9gYk/Crf3hZjQECXdsWYC3HAFTRyv61dal4y2vMo3FF76bb7x2VEu5sF/qKGl9Ay4uexXmqL4dFbHVlGs7TMa+SFwbLgKFAfJpWu90qmULxv64WRRTok3W5eOXIgYnVQFED7vmSb4g5+IvvE58qyEiqnJFBbP6o4FwZMiW13FNfOeuPY7Ubsc1N/NddaJ9trjp/bzs4tzfrSK4l+0fU45k78P3hfQxuE0Ib0pG82GCFMplJrGVMG0bwU3EnDysJBdz6h9zXZaSajLB/aQDXNGCD8OPvqQOlEvyLy7nEc9M4+3GaGJW64qCcJAJ3zeI8gf583RF2+SqIjOW58SFfIqwl1/HMYH5SAKLHGOZPH+o9ENUbDlRmo5jQ/6VohELmJ0MLN/XE8IEulWk1p4FktRDCVrRmDXbChhSMP4D71DjRx3/5O7Yrm7Tg11EfVZZMj6ByHiU5pRlWp3XuQ2J61lAWGfx/NuJoCqM98CTWvfnxC26QTfTqa0DIvzII37t6lO150Ggm9vZv2gUeSFsnKKAcQjAeOtCePWdnwwRCtzjYR2XGCNMkho6G5sh+zWjrE9j+lfsCbO6+R0TVbzl4JoKsc92WPZ2hk7x2kUf4DvzVneXcJVPtb+VcBJaF2XmiL+0Xw6vI5iW90GJqq/Dt/SU6bx94aHqSmPZMu/pS26X4pbFMHKXku70mNlSa5eRdlREZyG5iOGQ7qUsi4lGCRWRaBfcXRRbK0iCeYJpWsCbshr9LQbIENTkKsWoBRWlrASaYy9zmuosVgJ5XOQ6bIiNQVcMZ4aCwpWiS9Rj14g6iHZ4DpdcR+B/i18LMMEULRFKJiPYXXztN4EO8vmHnam5pRf8JZZQmO8SyZEn56MavXiAYmNtU+OwoKsUehvlcn8H4HAlc2/6CHSwshITLEV3Upj9FoPEhAhANO0bIX7rCqc6OdlWsU19/6LnlBdh5odi4iGhGs+xxypKdQP+M00t7exYbsXSoYOWm/DPQKQ1cT9XJHAsUTXlsoqcH2xoBkoGzt1Q0Elq8eyKb9u4W7d8vtpc/zUd1jJJ80i9kMigsHzk510OzUNBuc49E3XM9RGrO1UL92MsdHV7Ii6H7E/8c9YoFINjlSSOiQFmPsjEH8i0qE8JSMlhnzPxKNLDeMgAXFXeRoy+fxhNxen4Smkw2TQYzT+GuNbP4NfsRY/PbJgYuKkls3Ptjpg+ibHxyhtVNv54/qO4PlMcf+ErB0HtoESd1WpmRKj4/HW6tgowuijJGG6KRi40C55QSf4YQ05QXbm+L72poj99IXbF3ncAFQ+JO33RsNUvoRw4y08G5MBtqCfuQ8RHB2UwwDQMRYb2CsaVDRdUlhoERw9E+4SxXuIXxHQb3t+y4aW3dL9CUsJOvuxxbcjTtOTLZ5yaye9qU0NaJEHypa/vUcj9ZpZhl37IAwv5JSkNgrq4D/MaDIWV03MEWTYqI6G+WImbGZMF35X1A5l7VwJjYJDaMOavc+6bvwnDLm3IztgdrWmlJlK91DoENtbYbgKGVbEs+GoKl2zqMEb3+bnl7EN4icu9XYU3Lak6uOWj3LhkZoRjx+GGZHZW7qFFrHXLLQZsXYQiynBZjeAHJBJ+cU9cyDQDMAiNXP65M/OxglVqd1TXwFQEtJnG75HA+jEJy6ifQh8TFNgG3nU87KiG8Kn4kGoNnXRc/PoiB3MiB4HY/nzf6jbPRoun/Xc2iVOQY3KTgnKzeWAH3LdLUZ/AABfNoC8sSWFM0jJ9+RYBiursXnb2nZ9qhe3DFZTjZdurWKgIUN5TTqHWJQuSB6i4PuXOQr4OnmItXXtqYXmB0aS3EVB+954GeRi8RQHIJ0qZ0YwlFV+YdY2Js23yFkdmuwZd4wummhBGflQmkG5dUAn+9tKMSDggNIXd6g2j28jezblqyRjKVf0kOJMpk1BTa/7Q/3YaZniNFEIzfp3/7vHIHOVNl27P08f/3pSUsPwJdq68ulfj7OxDivibhXVHtQzigUdcm1K+FrK4xb7g5GAJcEEUwYqwBCWzfO9ePAghesFDBzc3Uteq6KXCg61wa/KPI1mQKoW+6l5K13aSj6+rH+z7R12T2K9CSwbAvvFdh8GeCJH1gyhNL0wa4+N7oh9B7RTCOD33R5YfEyzLADewbYG2iZHGz19OuICXnZLXuIRl4Ak3YCiRNm8UTMJQE1Byg5RCHLLUF93x/Uo3lDUXO0NFJ7xLcWr3BMXQYCDpxPxexv+4i25Lp5pZdBkPVcTg/OqVCVDD5N5NpnpMd8oTg3nscNBZtBrxLWB4Rg7HW0eRMZg+1QfJQC/7xarsSh4sNFViIX9/mVZoEeBWPU6Q+1YVYC/h8Ss2B0XaXrvSLsVMmehqntd300wsZ9aNg9XqE5ioyQJzYLvw0ejg8s71u3e9T30v6VtpsArklaUJ3vBmoXU1EeH/+PjT4emWKVUr7uubtrCMj87s9LmO8U4yoHEFRnh0v7ilnuKJxLTiskUvr+WdGMvzdY6PpOV3U+jo6isUwGQg9/aVWX0g6FWY7dKW+iCLDSjxJW0Vq93GzpcOshBS/yy0wcUbIr8B9Jnus/zVhkJEo+/q5e2VaIZcmHnuIWMnlaqPeGiX0gdKaILBbZCbuKzyoWtUecyJnGXR2JZR/nRvumx1v5zH0X4AOMmfZXnUizy96AULWZC2s+PeoM1SihS56TJPwMtCeLnVtzqQ2hME4Yhp28WLE8zOwWdLYdpS4sfieAa32jqCVwdlUTi/ArJS4cUzUF4ywI8Xzke0LV8E0I3L5gCS4c+Dkdhe2UppLhcG/b8rrIDZu2ifOlLaNRo4L0mrr3juI2tz3cQS/Js2hfGNcN8eIaE07CsTNY4nklIRCZ/Nyxa3hPCf+IJSuBXjuAt/n4ZvqThZNMVV8nKWB2rzADKcuz/MtqAf+RAmqq0qiibxnOS6WtIk16reuQu8gbf0Ygzkt8DCQODiQ3bFN7z2D8oBUU32ehXSc6wz0Y0ASIpSJJeVYyi1e5OWROvyVmEdUd1/t3/dJV8PWwvbqtYUhGr9BRXek1RPTq1YlcuEslbaOSYR7HNhMRAu0r74AlFd0ins59AqyuJIyewkIhI3uOw7+zymGsfglUfLdIYlXu1qn0yTb7JoA0HTFBzFkEf6+kqSWKoodmE792LXr9XOwm3NrcdH4ArcTi4OPMUz7Z90Oza69p/BQTabBzW67VlcylX7Q0cvHwElw7+W1Krari100onvGqqvGTPWj3oNXci8VVF2cRBhYegwIOVpMYqW5YnPkU9SfQJ82aOFlKwVsYa4DJyawcWOjAzahNbS8gs9cRZ8yU5S6BsoZ6PqbuRjdjbDClyju7Yh7bwKfBcbHzsd0x63czAuuviHN34EHcVhDajSZJ0bKM7xv7ln48CqygKt9t12OxKqgn5xySZo/QXOpD1a8+OPPfV5CvjIv177sDtvXLsrtJgtujYoWoMelxIOg2xaz8phrLWfHm7m/sZEBdFaorg8tVoA94CYsVY+UQvk+UNSZzixoRwdOnQdyWzKVEXkuA/QRj9OfLBO4T9YfCzh+/ZlsWmwKZzK0kAwx1lwlG6Lx851zj0S7jqV5cdCb4w8DUgLZ89g0MbKIpb5QEx/YhQTXzbePU6JwbBs7Xtnh2pNtGHusw4qc60bLwllj4aaALc9BIXQBLXyRXn9vuMBfWU9yv1hX25kt5q1r2Lp1Yf5vri1chSU7kznVdWeo27o6RvyeuuN+OQfvO7oWUjW2TezrdpxtCs2cGl0I3LB06tcf0HDJD6gmE4bUJ2k7Jfx32gfQYVn/qwoeHlLwqfT8Zb2kSLEdEC0sI2bnz/kLeHyQoNxGUTj5VGF2yUQ3aWW7uQeX7ISViX5lKRKDDXJPh7XcITmwSN+6G7j8ihB+fntR2ezPY7B236lTjooy8GG3fZ7y/j3Iy8HHEd0QwjFhRslnUvQVKhSulVwdfqzZsyiffZoffrdg06X+hBD0qH+9DjD3GBsxx20gzZLknftJUnEdC41rp6vj9G3fcXSRSqV/4HuWlFMkr85V9z/JKLtXeG2E4Bdg9fEh1is1IwSN8ALLhLHjeNyTXs+8A5fyOW52Dpikb1cOBAoZnqNJaKglkNs8AxywctVBziabw+8MrdDAmvuL1b1kNeMRG9tfTynibGVKa5j+H1uxgPxg+OG/DkVNKuxZZPF43KoNHttKoU+fKQ66GzIJlabX/yMrS6jrcOVQfVdIU9RvBkdxmx5FUIIoCiY8Ux+mmD0Cx3FMU6zGmF39oejh5lPP1GSP4YS2E95T2wbLjAjwzteH6CGoiH5gUA793GremJA/6BDGBwyuNDLDOvGUjcdkWltCyNbXknQb587ZQRy7JdBno1sOsIny9B723cOPaOq4GLavpAPkmETQfE/s6Jxx1DutK3un2sUP+BXRdn4MfHOY2kvH5xm7Q1QiVKpDOejKQ9rScCpwE7QXsKjtym5Gb3csrshtwfVJH4dhwCqWx9EfPq5bY/RETFE0R+ZZnih2q4AqkliWofVDGbpu4qO7KCrb5eVnnWb18xHqXjQyzotaA9iO/LzQEd+YwixLCPFdNFriGUEwf8/8ak7+dmUm5KkN3ffcb0syQH0AH60oe8UlyZY0CIcYDw3qXgSP2sWspCcQqzZ/CJXiZP7vvQ9r2TA71O9R9G28OfgNEWYCEHLx0+TaUcrDcWnpcSo/CecFhCvuzy4hO40drlsDqeAQOLX8dOqS900AjbW1ku26dbTtCx8So6zPGL2yJjnMZdYDeEkuBMj3lDWXIX6/nmsKISS79g9RHauIV7KjuBbL7oM1NmoXsQ8MpgGuOKnZM2m18b/drBppMsACoqjMUZ0UW2QVSEDh2uvmtw0KaWVBTH7Oa64G0FFJAXgfU7U01vCgi6S69VUwKFFMO0dMlLxAl2EAMctFp7rx2wRJ9Hepa32TTANW5InSBhMcTGbZtJCXblgeB+9HRGRDlGJ6BTG+0DU1lD065k+j6K3EVAIPYv0BXENDHrDm+8V+FlGtDOBn86hiiQO+M4mWcRTQnzeGt/v+Vk7Ns9Q3cX8zv2LvFNTwwOkB8JTdqO11QR6TEkfoy5FJhlm+jHSUnSBlaDrWj2sAIQFNZQLkZlWr0p4ze+yNfs2gH9WalfVPRoe14i596JRLgghyRgQC2Agv9uuXJ4+B3yGrv6DBNqffkkG5GKjGCTrumJq0FIGTEUHER4VVYHqCIKTI63VO6mT1+U7R782qf/bxzc1Vai2U117rrFNeSxkYvJJWBTayGPnYBLm3Z/Lvtgv3TntAqwjOyOCjkUnDLX7OR+pQbDxDYXl6Q+NtKTrFAF6XsIlHZ8uGZz6YTwz0ovaTejLfwjEjS2PTlPyX0OzDs8uncfoBYWNwmhhu3PMb6AXJr9nMxe83xMKt+88WZjPV+tUKKUYmC902i89aDZd9DBF47Zcu9Gxu8QnFnHbpZW22D4pnpqYlYctmu6S2BUP116E3gZos5/5VL7/rMMlrkOZmv9OFJ4LsnnL0q6p5Gs7GrzSvGa1+M1uGtqr/Y6Cvq5a7IHv2iyHVXB3YCIXaj3MMraf+A6Aq5bJ8i/RIuVf+3iTu5BH1Hz0Rcb0vvp6RNoSEubbNPZnIU6wJXSWRMHoKCn8VXU5o2i5svr+Gi95/bda/Zlro6SdkFMcvvd47ACa0zApzOVprbWhcbQBDl+7HZ2emMPTZWVp3naStpZg47cMEnXUOO7X/72Ybx49ilCbPtD3iBagGaDYGpIlt2ah0nHRT0EuBL2j/JzlwO/OTw9ySdL4NtVO2v4hFPsQQx0uDd951vmPj+OpwijJrRihq8sKmp5ctl8NhHXSeBPNx3CDxG6dV9Ov3BEdeuO/LS54XDefNgybBeWTBlZPemEIgQMIKMRuzunJVjRcJKuSg8/szK6hIF6klakdMOf+uRL0o67KLeeK1kXbnJSPl2do1bbwjgUWGaRYct8golxi7yLgWl5T1xJwurLh5T0biM8DL6DgrKjd6eJv+6h2mmyUBkBQ4KpK8w20XiESO6UuwuiPG1mKtNK9tYtZaayA/ZsEu3vog+ewDqx5htLHnJrzpA7ByqPo+nqbPFpbZBmsMcl1mTtRcBrWlAL6U1OfUc2FAPA/TRBKn54WnyD3wi1+HCSCH+V33hqsLsrQEcH3kBnTZU3nT95pIUbhwFOnPkuuFSy5DQ8Skd9ZwX1kRoRiG3AJtBkNPRBNTqteCCJZ20fi01Zy1aSxvMgzTE7jU5qgKyxHT/8UMpNxwlAyzuFgdz3ISOVnC2EKrg10XEoCBte//uxU3y4ROLK2/dUAODWXRuoRXVuUWN8opwq6IXZluny8Cpln50lLkoIjdrjDJfFsvDXNhLkfCEQJ0RG+4qvAGy6nkxOQzg4iKpeWVDj4XHeXmiViWr/pp/we6KAlv2voC+VZuUNQfFkkoUqpGVJnIj8jejPy3w1DsIW9lNtg6v9ZhkE/9ZMXGAF2NLHacFWAqScO6U2qCUhajUrcZn+hNifVlX+z3td95j8f5B4yAuTgaVeIZAYlW6P1ZMzcJGIfXSnkGrjya2A2mJSwsxDoJuysRyxic7yhVYOJVe5X1OCLhXKts3vQmoa/NVfzmBkaNFJkVTh15bXLM7ghd+v4p2rCUBBgTWsOdOXl4bRm1Agu4y+mXXC1djMr9kZ6xurKwba3NcJkOYKXFZRYkxdRyM8dqEcEq3EzBnRX1677mVqQn5A6b70i9vnMWPL2ZQxMhGY8eyMpRKRz20zHI5nQEpSPM+mWv0mcc9vO3eEN2Bod3ok6Ns6Wz9cuByp9Z4CDb/yUznSnvr5VAaIi3Sle0RlrDYKfCYzaPuTWNlqGoN74tTsjg4+h8swgwF2cpjZy7+oIhDWDFINMGdqQxoVmY4jjZMfqCn5YsRmxP7FI1SEGyoi7Q4rxIpWJgmVszVlqbKgX1kZK79iM0cO931V3rwi6jSCbYgIUv9tcM5Jp9GuBpwuwhhLfKurPYyhNyumJ/eNxbltjX5jyAEtUDgm4T1j+Tk12MPT2r/pvBZh4FfErl+8ip7Z2vbJYJMvBh0khAsMAmD5nzlFFpuow1L3H6vpnFbkiKFjPEHqw519vYcD9zWelmCw2vLEDT/yhtQLWWwjcIJ9y7TCiTh54eJi54cL4qASs2f7Az9QLOv1t4ad/Nqm31gSzAa+xmGvw7DexvTonA+4h2/ivSW5ITsgLi+WAYPfIRLpQCYnkp6ZXt9rOipSu8Wbmx0ojMXcTptP/IIvgz4KYaoTiyBnjg/SgGUNI2hbhcztLcB1PtG9d19c5aJGjfmMQZQjkGQvLuTflSxMdni/lTmGmfZXRAJH0NQzH24nozS0Lo4HyVXLpy6IGAejB2wLtq1NBOVW4vQIUGYE6axGiu8cGB3covvJAR9Ie+MgF3FYLfSc82/S+PubnOyc14BG8EkYO+NUefDiJqdvsPeiNcsksQdNvUAWieNNyjJQiS2bZQtW/ecGutNvonBuok5hjS+hJ23lLRtYOi4MCjoVSee8H8Cb/upLq+EnA+fwgmItEYz6XPIWUKippcLgUcZftHAoWWV/78XvQqSfSZrzneTVocgKH1imnaFASt/JDJBtbVPGJTrggBNrT00466OlY3K3aeZrhdHAJsW+PaTNNbEqxJ9JltnKQNP460mR9f/TUZlJvzSUtpo+/cS7SHlnCVQEEsqp5i4XZI9kMbSOq5c9cNHGFXqnh8kmZj/4AQVYLgm4zdJxnih4mQL2lJ1bLKlp72PlnOm6icLCQr3nFNrwAecnfmCAMZvyPrVxfvaaJ2uP0QNajsCSiDpwtBKNGk6QQbNFArqcRgqNWSK87sOdTJqOR2tig2J56cNCu9qXq/iAvFS3AzaYtZsAC8wygNU3YWeeVoRHgjDFWk9FUqFbabV3cS8qobRyavcd2XaXde8GeE0tQF3fxDURhuTgQ2araXUBKaV+mFze+OvZCDA82axhEunhsnjh6gB4ZMnupDmitxA8ShrsPTTTYk/dj2WE6ua8ca6HQ5RqkIEdSn0x1n6GvCDaCd9nIsl8VxIVhe4noHfru7iABUf186uhKwfsNW8Y7+mj9FNxBBH9fXhUpITUv/QuQgb4zLYmr8cJBVuS1T2TSoa7iL6mt3j3aT2R1xutvbwX80+2LbDJUK/EKgJYjtgV7upE3pVTzkD/1Cx2l6F75m4NP7gflAMXm8Z+EqXvNFkRf29Jr0CuUuEOXXP78s3sucS/mbqybSWTk4NaX19D3f6fX1Srol36KDCUqIEmYOz3L9FfEPQfkqDFJvAikyZWpsySxqsR+2Kc37OiYJTSxOS7M0G0gvZoEFkzd1KSH9hsdpxu5CIwvzaqkM4KSysDK9PA2WX9mv+oACWGYgegpE5tzw0GqJd2xu0VsYX1/zDdZJUapZ33MEOHfPpGQb6sluwZpXPIzVxNel4ifLdK+TVXX43u8yA2PdQ3zvfL6nyHx9nmhg9zT2tk6eIAwo8sOn/dMYEF9oYNvea0eqbOHVFGrBKooPDpY3eI2I1hLEUfC9w05mMn1IuB9Xi/G7kjpfsIjem4pPOUzPQuHL53yN8KTXXAtzQwSzePc00ZmgI5JI9SaR3xXAkkRxbsKqd75Lm2w0Z7ZbcgZhsNY1WIBA22IS5MJeYl7W1tnBfVK4yt/z3zg1miJAoJ9rNFU/Of8OjC2BsADKuJn6f3dDDtOnI04UKXBBncWL/kmIqoYnYchS7bBAUn6b78J6VBP7C3goFZtE7f2WNaYU16xHyfkMnOP9AeH9j/gd04A3j5roWXaHjYqRZjAHIjaRkSu+ov7TkDnKVWtTa+knaRb1yJpJTHnrErBZSxgO/VctTIF33nCOkZbajQGnZtGqmYpGaDIaOWyUOEjTZf3hrIJp/7v5meK6TpePOtZEu7lgEXPetPvmCQwd6vVLW5ZY3O5qawd4FjifrJQaQyUtiOb1WIDzkKY30ISKAPxLdOGSprnkmt0pyZuoYkXfZUPtH+oTTaf+45mTDfdu9F0jRZBhVRV5j0t9iUkr6kdPR/gHWnJOtkro8rXWkL30MXpxLTdFtRRdBSQ5IdQstlTnjxWXuYY9uzbfb6T+Yw4STBjbsqqfYzWJ0ILDjfhLV/IO/I3SbUDVUhbQdXtptfzeSy2ngVnZShy/S6IG7bHfueHTLWu4u+2QWcaxF6FCdt6JHxWUc5mUiRUEFUDtc2poqyWQr+FURP2BxJQHz43EGGSitxXQP6TR0gnAJILU0QId6MmFrDvmPQmlvWZnMGJkUqjk6BwQYx28Ws3V6CmNywspuhgewyiKfanqIINtvOSI859pXqvg2WjYXC5wrkxoHVxB4qEsG7YTVLBYQLA/g29S+VEeHn7VQU9s6kZebl7XSBxuTE1U65W9e1GXz6CQZr5txKdjo3zaqrczFsE+YfVALv24akCtSvF4BrGD/bUPi4/EHv/m3RvTaGzH2hHlkixZUYmIS2X+Rlj8tj3h63alJJzqz7l5QtAmjDq0IO6Oc9Dk8W4kOiAnm9HGgulvm7O2S3bzYvEr5fbG9oi5MYltEjRtFNN5b0kseDn0UvdV8C7HLc5PZQ7do3Y7fLWn/0V21AS5/+uqqukIrHgXbbfWXTEMsF19QF6g68z9M9etqdzKWCvbbbGUG0w8tXWe92jZb9i6JEEGfJTn/wKIs8jFGwfqCLvn9VbfG643snuMThmOZrKWtB/8hRRUQahczRxteMuQYcBoiDRGOHB9wFuODeys6SuLn+3+/7V89hdVm6wOmt+sxqfSMm9gXk170by8YgB2vDenyPymgD6IA9D8h3lobKO14XdpYE5xhCKVQd97VJydpII5X9OfUD/5jTCrCM/f5k6FPd4GkuzbUCURpdGWuuGBQycnspxHDnlb/m1Mguetx1kWxYpNtAo/GFsOqZBhOHxLqgXw174RJ0Aznn/Mtcoq3kvUzn1CMTim4mWEn1wMR3uS+Tbg6MXI7NLBDn5vERsiYCpKMYzcRq53d0d80dtYcI8XpYxnPoquf3g0zLoHhlUSNbDHMIho+unlN+5788Grws8wnIfdQy4jhNwK5r0VkKNe/Zeb+wbfhPWc57pWTY9xygc/rIrApi1AppQvbS412HB+S6FPpvj72QLBjaVeEdRlF+Kqy1a1imHFs7qmTh3cYzNyXi7jO/ixg1ic3ewBd1SdUHmfsYv6X8NovIL67cZ1sJnSFiZRgTEXBPQa5D+32Hfvtc87E4/FhnqR9E4up1s5PpB+/9Ui/qKnSdKARpy2fyLya66QPnV1A3i6heYr15+vMQXVNfleSCX2gIJMYV6z3uZ6XCQLEW4O/D+c0xba6MhFexvgCAHj3DjZuZhwb5u8CaZuhK39BV0au0TL5uNJJuk6MuTTuRlaHp/poAAcvULdaUVKpIZaUocIeR/sx8/KcVfkmS9qwlg3xdcIg9IQLUMH6+hvgjw3Pt+RDhSy5gMhFHSGwspL+qNbrd0BBPCyh0H/YoGwipKZ8gxcT7AAeUCChw8XOXvOR911sfYfRxx68QX4IRNTXHR5Sp/w0LBMQezWd9bOtqVxfKImSioDhqMvxN+7bUpJjVRhaQRlvn5BMOgnXXykPKrsvp6s/Lqseovl8ERL080e9dxg9kYbs2PWriQhJIrSEGgKMPkT0k/eVRAzTg1I8Nl6QsvgvUVXPctjsuxYsG2SYw5W/qZaWPgAcqv0srhsQHA9w3SUtoMOIRMcgoDE6B5gxeJuKzZ/kNBlFgHqUldtTwFHmroBO450kesLyxQLz1MhYiPghs5lg1h08arFj6cm9i58ThA4ZidbsRilYjlyuj+TCKzpHf1E6EMZtY4J1wkqItw5AKsz6n1hlFYpwaal3oWoYuAWG/ueX47EEexHfEGcrsdzLEs/5A8J5SSiH7a1oAnIr8Teu1mXhihsxVc91UdNO/MazEypr/e4XIDn+BRbDsB/KVWheNll2QjiRpx3NThJtij+LEMluKfGSqYyerIidgR+EiYtUHePTD6o1J67qd+MulqX0NpHYfpat0sBjY0KxcmA2gaUXRrBn0612SJmJnpCslBe4Sl0bGCeH5QzEqLgOdUE/HrokgqlIHewYlN16oCLwJiVEmjByi5YT00zeubQrbwDeYI6gYvgZvcPLtuu3Xx35dM5r5cqKMMIJTTQxiwdtUuvNDa9Cd/hr6Lc1J9flhRTzGivA4kYrJwIzCCuiMCCt+vW3wAfzvDY1NWARiqTS7xD5UDvCOZultaFbT3jiYeyIS/3T+Y7LfN8nFuueB7lc151kxIiljXvf3927809hJqiDP5uK7fcXGrk0jCnDkzxpkzJNkNdAiqIUThGos+26ZPESlMcwe7611dCeHeV+4+Pl5jra/yMtPGIi8dSk4tTH1MYCWUesHf1rkUfZH6K87EBQDd+tffqcEr56upaEZKKgkCNs4EYJfBgeSBrxFCD3271YRsKuwjqB/rs166h2dFJwX9hCLDMPzS7JOsuy1JxvisDVl5kUQxw30FLcPZwobtjqEVaqTOdgyV8rfU5aSEuXYckXKV0RuYNGCpcFwMJrXJspjCHazk1zzUjnuz+NtsTIgxM66sJqp2KL3XzgRVIO9Lt08m7qDULO97DN6Q9AqWnExgQjWhFbNyKrxVLDiHWKbwaXyKgjZrSQmR6k4Iv7+sJp0V9lVyrvdmrGK2yqf3iXvFr6oPEwNa0iEYS2eSrNJuaXO/ECZIjkbUbLsqDP8Cqs5iMInibSHgyyY3K0FA08fSGljwPe0a2J4qvB0dVDvOA2Q998sDtqkWPPQ3sbgCbNrY5Rc9/tEyJEWI79fbbJ/WDxWFrFLzvB3DIKb8IarHoELkvQEb6VyzYMYeYWNZBE5DX9ud3Rsy76dX9lY5/L+2JGV/WDCRQamNIFo4qSb0/uRG27Wqj3jmwpiTWxH8xWRNIiYyVm7VVZ/7uoWogu8lEGXoUXEIw8B6p2GLC/pVF1/7pBlMI8qQ8afEoWG8RYMHO9j8JQ5o/QME1IG/Hz8/LeTtGQOz/bPBqpfQZUYuOPQHWf7uC9F41pb0h91jBK1yG+xZgY+Hj6UYeuWjt5aS2D1tGNSLYC5GhkrJyg8pKmdQisQZAh051O2lSsP9huhnCjq2xzXR8+lwF1y2mcOvW7K6EtvsZVW2yqQ9hGibH4r3nrajCyM8dASIPitjBSMSo7S0ypScHxre8YrY5k+FE/eJNTseOTq5QTBf6q6HZ9mp4VCB39OkKYnl8EZ/NYcAOR4bekFUL2AHtEoz3H+rBSnngPrRLV3Vun5qbH85MZDU24VZDt6LeLZRviYvjo6oEoQhLvdC/4+pswDQ4nb+flpoKbRQKBVaoFAoFC9VrEiLtBQr7tzh7hR39+Iuh7u7Hu5wuMPh7u55P9/Zh//vzd2zG5lMsrvJZDKZTKjWARRLQNaDDqs/La9qFVReZKJU/1eD72l9uK2qFSR+H29TREB6igf6lax3kkQiTo132t7VrQwNU4gyMXRIJ3TErX1G0jy/WnBrxS5ES4EjZ6YxeqPu697V1nXzNTXwTDCV5J/8RPx2iGN7PBkRIJyxYzAY6sNrHitGeWoEO9kEyg3qugWKxSCAkIhsPyhrMvh4V/ngtOc+PCexkH9+STEeRRoTp/dpBc51bmt0N0CC/OdHKY3gygbWTM/47DV0+sNbdy/vPTbOukDHjSluIdTrqv7DdOCj/feznR43DxnpUmCjwSciRYH6l8zvSG2RX+nYUXZ6ixynLTGtJVGXc2W5DIJaq35RuQiIRr0xPaMxM6IUDT2SUj60AbogwOAyApv15ubbDNM+q/rHtZ9TAtTkMs0OjXQuXWkH05C9zPNPN1gGfbaFNruLUviNND+Yx+iNyyWXhdwC71S3gkj5pLV/8I6qx3EyL3yfcWi4amRrYRub+HL/BFttNcNfF+SZPFHVfCLKqPaXqjusfs7AEkwD2xuhWNxD2CNABuqbwndHET1dgiwi9aSw9H78bIVO+92nvjYNx2r+zocC1kvBFWTVPoMfCFtnq1S8Vz/oZBMX+9K25C3Atj0cslZLHPJz9GZckmSchOYzDfCn69dX7tv91XNlNcVFp+POEx7muty3G6JkgvoSkZthbwALYBs59RAxqLO3909PzxWG84u4QADSQlaE8C8u+/XK/mPI/JaIUSX8bpr4Z99Lb9j0nU1mqBTBy2n/gPEAKw3Fv4VsCctHBom6Zoxg2FmzAv1ZApYt4VemX+FYUrBwmZJoFTuNXa8DtDY0yMsveSiThVZvH6C4X6uUiCe7oD5tHHsTBiLJeAlxOYJwdfsGJgM7UcOJPO+Je745r4NFgM9+OwkMe3jhMYzvhT9xR+r5ZqkRKgkd50TwEj7TVt3hRBDz0b+I+oK61uu+ECp+bY1POPNzoSkT2pStIeGlZgJr4R1CrrPepbRIQ0cKpBKKTGWOqgyN78EhzZf5KpqlW0mmE6xM0nX2k6vWVfEwzFq4/EIwI/pru4FFhpOw6ByaGcGmt2ubWdRh5JbdgAd8VepxG8xSkrC664PKucXi2HqQoH/D75bDueMiyIQ8eYxM456oGyal1vH/JzjpLDRkWeRrQLjgEHk/QiANNWp0PIUa/8RKirnR2jWRPGveqFdVR4cIL9xLFZ/j5rbdViZ4UHy6woXKvIz+ciS+bnruQowczYKqEVUshpXZ/zPgw4NVxJmyLIUcMIttXWAmZ6iIsacUxkXuxuAgtLY8UwM2HkoHnPmobeqieok7ShhOvlxucba13MesPMz15jChmgZA7ob5Azpnj0xEiVH+ImMpbo5KqCd9QnUdXTV7tBUdbljSTs51Ij9amvaHKLEh81JudjqvO3Kl6JdufYITXaW0RSTmfphFVBFXwy5PwHQJF79N91AyDxQfXexoYtTb1/Ej8pH/NMyNdbmSQhvQPwCOCX1Vs7QqYRkDJd1agAZeqxyCv16EEsGSBRoMcZhds38zBOC+n6ESJU5JpE9M1h6+4kwiWjEzL0bwHUEK5JLYmG5Q31mso6pGxaRNBOTsbw93iKqlXVxsE+TXT/svifeQYjz4SsPM3RngcxNkieuiqR6fEUgygeGkK29ZCKMuMsz1WecTZVSM+DOpC9jJG1P5fAb2cp02KkHXlcq/eV4/1MEoBAMHN0ZH9pH2KtmpLU4SpRISJ0YLqLVvdl3ra7+hwPh5XdrjTcZv+IBUWWk4AjB9R+7b+7ddLhUCRdm+EUvk2cq0JKqN4qcrSYzyHz5fu+Kw7ButY/Uca1mIt0dwrFEsVh874vv8lE+rdsqbjqwyoJ0RqK8pmO0tUpuhQlZzE8Ux4IVearif3VfzyveA4I2HbJ0c165uQtCXXo+n7Qn8i0283d5XG1Rlyy8wNTAbgujK9R9+PBAF8J8rbz4qktPUMVWj8u5CQZaCTuZt6Au1tYU2Nxfa9YrMOFmTnquhLKSr8BtR75fsrGai1jjND0sAxRkDLBRy+gqiAqtTpJ4LMPQ0ULV0HX2VIAxIxfAXtawIPOPq2P7Krjcl6UTJGB/TJLJihT1nbeD86L/Fd7xPHVT5vmTjxR+DCD9hxHrRHfKXXikD/R/WQxlLf0boRv2A1hIqxZecRuaCe5iFfUz04j3dCDLU4k/ZJFSa3x5lOc5N/OiXLcoKTyLJlkY9n0+tCNafscazaVYpbFfup7UeFaIlsXdpfPJa4r++Rm96QXkYHndF0L5TEl11Ho+cXtxs7pdLI+NWFINUOeUMSG0A8v3b81A/DrDGJnqVYAMc1SZfMUXM+C764XPLgYSAUu/zd+vvzXB8rmkBV7XjRO2MruRvrXRZBkoFl+zr/6iTVDnkPmQww0XwyzAEds8WV1qNjSa83p4F+Be+M0GxT0cdCSp/FYvQNi9JPVWPzHzf7dz2/jEf9YelFyCqO7p72DXvpPqiYRPkg2XZQCjkIDJnWkAfFcN/xQq6m5nCU/D2/b+WHAc3ya7IF966Njq67q37DFHXaLdiEYKfaVKXGM/AaHVaEiaQcOiyRlmJ84PZBR8zV2if4XshTSG9lTZHNCZUraqqUA8fB5nlNkKQ4AlacGPezYkj2eEAy22DMtZoL6ia1SRyTU4i2azUZVhAg3T2NMGrfxgGB3WZBCi28ZFdAKzCqDKKKKJraJlRuGV36MgE/5VeOsRhiEXyEbnzVwIPwyFG8Uwtj5CKc27HccvbQ2Pzp8rCmdSqoZJ1SaPLRN0TqzhZ1jAhaBTvyXImOnGDeVMkKfYdETeyn8T31uBn8Nw16w2DD3BaI/LJ+ygpo2p1q4LJyMxu0bsChGWdi+LPHtksua6guJSc4wq/+C6eSoPk41KcBqQLD41tojB0E6bck5SlHikDnjFmab1I1wU7dbLlQKbin5NMVIL0Wt9OJplodvQ1rf6cwDCP9WzBL8sk7ugFTYUYdXuGyRyMB+VHaAGlF8OQDGUCmVZv2Ig4cBtBPFkfYN6PtrTykjWzka9IYOwQMKMjEKDCF6OiCUzxcSozn1Fx0kTCzXwPyyFNs2kF5gDtQayFuS2vBYNey0o7HcXiujeDFBeZDFVaYBobLSME7Nbz0ZGvJTC0vYU7M96WijxWEV9/YqbezFvzkNtPEXL6GhsAXGdE41lF1LDa+w3KP++W0pmO3kSAV9ddSXLvF5blSxL3jhJuQaowUgbCpPZquRxL/a1OvDS5FfGj2jKxoLkybIRs5aNCsaVsFT4HznXtTVv7Hl8WC9ucMOCGQfoLWJgoPa1pFogq+06qkc+qGZE8bkZ186Uo4I+2wycHC0XSrsgAwndmYQJzi1b6kxxBrppeCykPA+NTl4SI7pJ4rqjznmCv2jJf7OQx6TbY8S8mtT5mYN1mbOL++AUX2k4BO5bIx6vOhqTF2YUcJZQoQ6h643apMrizrCX7wmtW443mUwWg/oP4vuuV0sTtslbZUNFLPizFtdKeyB0QmsTs9BsnDCU16kJvD0KQ3TOdomKy3gDTq25ZRYXYqHleTIRfeZLO5GMvrSV8w/GaPm9Z57KmJBDwWUwR580Sffve1NeaIkuuCV/MW8wnqmAdfAjAT+x1gujMsyIU6TpP0N6axz8Jj9BjJN1t7lNSwTyuVyu9mLzjrEsdwosrasJoOo6LmqEHPfSJb1KvmZ5JqhVFdX8hVEiYiMkJAdlryzgSBox+K/yw1vFOUCv/blFfZCUINIgnUV64HF7z6bHk5/9vypIPDftnaJ+j2y1LVcSwQrrtCpxSCkuHjmrmOPlXQtZRtDPJMu5R7g+0S6yGIsSOr7K3AEdtiALsl3UTb3ZU8stavtpYTCncN6sBfwiwkgQ9e/y9aaga7IFhlHhpzg9k8bWXnNfGyzWDtERfiojDSHlJOK/r8aXBrpJdL1ykVIAaZeJbrFVF5IBSfRicOJ0xVlGsjeG+RxrMgNJYhpm2kLi7O0ENf3LWS5mviAq3jdlyHApAUoTNYYnQmD85B7LZg9Xa5aXVl+HGFVjiRO1xLx2g0YMnMu9leE6+0MDav55z+WHB3AxVnTs3WdRWiLBUO+uXXVKEOJijZb1Z4Ae7dTxTkYJdzu0ogfSGNMOdPNZpv+W4dx+rhQcIfScWSmkyB1qwPL8hO8C+0VK/P5H2nGT17+eE/idv/t1AV3W6HfGndOAZLEbcK5FasojSS5yYNV+k4zC6wNMfj6pyLLPIBMf2oO3B733v69NkRndfUAbChKujSzZ+vE5YRNmqkIESxZboCEHBtvemA0JEL6ulmuqfC1dogo/We3ifbqh9f2W11QKOu0DIfvERAVbkXXLP7v9t5ys+xodbjQDXqDbZTtsAO5RYKYFBofvNEE41EJ9mn498nQT/PswJQfe1lM+lC2wjLLsqIQPNyvsX8ot1fp7aou9cfj9puzAksXK/YSLEkitrOWI89Kxk7FEevz7jlcIo/Cfy53KgRynxHamRKh53yR9f1Jy7HjaI4jpmDkzLpXPEbLAXZwmdVvtSRZsAmkdY0bhJpUbqH7Wk1+NOpsS4mdSu2Ps0/PK3Jvstwxz5hhKhFWIKdhbs2YAlZcIXc4eslh1lA0B365jLXa37nDMqYDaKjvelT5iffqUSMe8nTG5/NQ6xwBMHGV7qykSMFx/BA1OjLVCmhrQP5eM6m18+5nSIwvXlPjKYnyNgyyVqg+C4tS1BKHDXvuOAIZvzBBlTEeNSdRIKJCE8lIs9eiRLQq/fL+2rCpdSYtqtgcFIlUg1f08EQpmZsbEdDJJw9Tmhhnzxx37F0KdVUTILN0N5ljmUlyy1XLoefnBGIbYPoTJq++bV/Vb6D3HoPsScCjv5io5e7+VlGWFj0sCPEWT7wxgXN1JKmi3Kuw0Zu45lm8yZRhLX7d15CopB8tFJWRnPz8xDJf+QMqocNW7D/7Vfe0v+TATfbJiL5mEbh1HB5ge/PbPzkUDyD1CJwY+MC5NzkfCfTWyt6ZcaaKvyS8u7omdgYtBgIc2AoOnwXMiRnwdz6EPqUdMhks/eExo2C33FaGXrxMfVnXC54DCUg81nZup526CM689e1OLNQH8ZdpcUGl87Gg7NQ2BMuzKoQovppgSD46sMO6qDF4ZbzdOQ1HB3cP7u1SfrziKHhfBo2t2V4RxthcwqFIsRQQ8mt2Xj6no26KbtMnGhjVojvQ25kXUgU4s8KDhtuCLrUcui5mW1QBA01rdapko+U5T1bHkkxdtgBYxZBiQf7dO/Wfh61FlTA0pdwy8o3Lh0ecUycLFnwtgkHrwbifjga6J3JjIBHwQlQtKBgLmmlxTAe+Ac4/8moG8o94zINTubsnLysrDAWEcjrovInhU4/dwl1DF5HqtATh2hRr0I5f/BffEd65OMsIjmfu9v8LPF5kU0LcsSvxRAoWu0vUYs59xCP9z3p+nBXusFC/llu0pgXSW35E/EJfpTAs4PxwQpCVjSttmJiUVDAgqS8vb3Q0918S/jLwwt+lOdXdrNFUOzL4RmVnMxRp9YtYv2wNg0RL/MtGnB1mhJFwORNR+IOb7vvBth6u9kG+bClOQcprIZAzlOqqk7DmOHG4zk7N+yjfCNcJj/L2L2qJ6dayZ5HZIlfXSxGf38jQta2xZh59kynj3JjST+q/E7Q+i3Q3dknYHm9sD1y6/S+LeaAgDgBN20wneucw5Y2CbXFGlGfeRprMWn8gIYv5axKLHypwh2sgiHlsg5HbCLr0D5iqjlZ2zQ61Eng2gx25nw3ebEPoU71Imwa7qGgVmeouDmPOGGCrrUM7YpEndeo7rWP+LQEF1yVEE1hQ12Gz7v4fMzUu9Oaa+VRfjtvm1bZQJTFxgmkQBmHBVeyOKMxEhVwgAAQABJREFUVU4bF5a7twoVPiH6MIJ5ShZ7gfb1TC/cstYczTJXJXR1/vaLEhjAtb/gg//8yA0TcaTxKl8GLfQF208mEllRtkzl6vjL/Sof9pcxvGBrmIjWTs8GsLi9lwCmkLHDyFZuB6ovsFUTM7PC88REd5UfCuoVvw2D2LTzkmF3+IWVQU4M7uxye3b6e7D2sy8zDqjGwUNe9r8mlRquRha4XibDi5VoANw6sufpvE/fXUKj5130aXDHDOK+dMgrajYc9pkvmbAEuXJPD7tH2vpl/ml+fUfoX6mUUGRc2uW64jRddweCQlTMiwL9YIILif1VUKm2a1FS3ImLzY6GiN9m1Xfr661CYSSRDQHnBe/f+MPMy8mEWFyp3P17vNZ17f12FpgUk9iWsOSv6kbH+wuQhxDpN+PGjNS+XssBL8yuTWgg+81chOVSzrvosfoyo+TF5kAJMxzYQXba3HZe9UqJXSy7aS8gw2ujiJ4GbkmDUqwjMEUji1w6X+ywnbw3VrkADQoaLSbYQgqbjktcmEDLwiSsmjyBnaX3/e3L6EUMBKjob90DgMx+HhXTFk9cailyWNFCqQPXUe4Jo73rvRr2tH5vlCCmE5wDLre/45qlPsYGqbQujAZFKsn1P58k6BvMKXXfMljKWNKqGWR7an9iltOPD79+CmTMTGiPSkAyq+wq4plA/ZS6S15zsyb4rd+dhqT8VgsJoAX2xIeHNLzXEnGPb+M+7XU27uezlVsuffDZ3g1qrixyf+v9Qvcn5ALbhiE+7CbTjGySEukdY3x/h2b4VRANT/icSX7zh1fDla2i7/+Dr5z4BN7fFDaO2oirMrko97CCj+5BdxJr4J9QR7nQGSLaC32J6Oi3endFqM2n/AqjFWEyODT8LcNM+jLKXzLzwGIIvSot7xKRqKY0z+cTx0RAsmUKSYa/IzRveEj+DDVw53rrO50WqrjXzgF12D+t5N9UU3YYDUaRIQ776lIGVbX1KnJ2u51dK+zmpsW1tpE2xCgZUAdYK43eaaf7LJWGUqV2BNIhuLyvLHXZ0Dex79097mXvGZlvE+HGZANxYrB/+UkDlcH/j6x26APj+ha121iXF7pTSvVYFJBUqmjEbIoP5wj42iTU/QFZPI7nAm7Tmn9GhvHF2NMrFR1JzP2uZS3AL5HIKW65kUswLZCVejfX1nXxVPdFy6sOue4O6KIvw//uN/5UDSGO9GVohbhh/FpP9Hc2km4MdYXD/uv87py241F2D+0AnYeIBLjvgXDVBsUDspsfxwgBwglOPJtwu2Z9hUISLBGgSEW7c8kZivBAgP9D+tT7O/xVNNZsLNPWf/M9c1ZLPquFRPesJIH6An9LCGRntqxhZa6l6rAUnxmANQLiZM0DkMZ5/+zW+wXRACRqDWWePJq+a/qDVZiO2W4FOz2OQWw1+WLRF0um6uyX29R6JXjS8IPsM1cJxjJpONgLS8l9OsoW4W4NWp5sEXruwjv40g39x6KmZPockfdEvAS04VruO45m1vAIrazAduGlS7bR+sRbuni9iukJcNuvCb8el0c5voxur+LcwxTbCvL8OnANd3sFCs0DhJnAYz56G/zSCbDU/9zRHRcDL9KHL4gLBfoWUA7NPeyc+eHvG7hd+BYuhuyAyakqcXy9QlNeWdD/dAlZdqItUkmDk82CcDTGFySVhfIKt2GH8A0lpG8alDbb13z+mfKD7PPHtPxUzYzd3JaHZtHMry/K9I21ebKbCXSkFpqWGxPi962+ANHNry4NTO9gWTyjK/8zqNGcy3qPGzNYobbyGtmu/hE9iOooO0m4ZfgXIUxjqigXb7HmCiF3P7gzgGgURYYd2EwL8EGptCYQuOC8H1ag0Wr6O4jqCHiND5ls3mR67+qv6qxddT5toXANF+pA6u5s6KWKWsNsaJ9swItghTaoW0Il7vvgRxmt8IdeE0BQTivXhtTgmTrhmSCVm6l4iEs2x4CYsk7dC7V6pNi91UUp87iUHdA+RI3Wqt9anxt3sJuQMlE9h36Gmm4nv6dks/D33m69GcY+2hQArB5nkka/orspwiI+KYfu1zQtXQ1p5F3n463QdbCZxA/lWBg2J8OladzkbIxoJ1z3Ej0ovGs+6sqICmxMHU501Kr9GT0PgSKla7+V7g+FQA03wDRJm9MaLhmrpMnBk9u6JkZ8iOqFcE8fKASeL8LMLNHmcimm3JNgR6FOZpY20srwxC2Xgb+Xpjt6dhblCyI6OTCvLhhmaP6s2cE24aMOi7j0ZUsBgKIrx/jt3Nm2MsHif2T4a/kFSNmZDhCmvhg8CWr+/Tshmz5N/EdvtGFUrqSbwMyHpQR3i5mHOfcuIoiUPI37Ia53SSAyYt8SuSFuIssTsioFQt9hM6OjFCSEXHXVxS1Npk4kV7ttdDGNjovxK0VxsXTfZwQND1H9FBth//2ZFGwnFCx1HVY6DQh3RIBy3OhOcjmkKKpYlHhXcHvaZbDGJty11d9pRZ2U3bpoJPyN+wYNQjWJ0bp6uQixIkDBhJQoFr08q9TEzvOgBVh/czu7IcgX66iHjA5wAW7vyNPUn4jRdYje0fkM16wFHoVPD8JxF7yL1j4VPVpj5UzNu7Kk0Dx53kshIkqJjL+ab5ligswx+Btr7PmgkN0vAWAfuoLLmIF5IRkKAzHdZ275vWs/Vvm/ku0BxggoLqHu/d2dCgtgu52sgVEBhmFzZ7m69rK8gtiXQFpEF05aRp9fHwNxcJdNotYfFKLjbxW53PMcQtLLUDhX2b1V4k0d/VR7nE7/ZCml7Mrla6CjKiTXg/O3SaQdnhCkLFA854TsvgGg6v1lDH80NUuEN44wzzsT5IB3ZkQf01KhwFVDDXJVF/P/I5S1gWDwwYXLQCJR5Vy5263xzVCWWd9zZSoFlFQopcc91CcV9d89LUtHPbuS7KoA/H1X0swZvZlbxqc89FFIe2YIzYMaAdgCBbRAKf2+T5BPA7A/eVmF6xjwckH+Ezb/Hum09V3s9s+0Z+ceBA9ipUZqSgs5H6eS4WQea0x0R6ebHCKkMQWucUVZ48d1kS0+FeLrz4b+d1WtpfMC/yofwe9bo4vdEUsLJQ4pWtJ9XLL1uq4r6YvEPAHg5iKBhkUKtST1iaT+32ihraqljxOqSyXrEzzVAN8O9pPHNvXter7bTHlxxX1U2zaaSroH2VU0/cfMWCCKkPUDVZKtFdoCVdAWDxD3OreTWL7R/JOs4DHPTz1ELyyABQN/UFVzyq3p2pHuxfGMdssft7B4X/2L0Diq4NnXPKCbQT/OqdAvfsQRCNJv7wcYiWrNwM/LZ1DeigzqunYFKxQqsk8ySDTv3GVJNdxnq4qf1VCrR8ECvu5QxqAA/CLGnAXZpDOpz5pWyWXKg7v82rkyPYAqc5gf1VTAeeJrmDMyVYuszfmdQMmmU3OQ4oTaPZzGG1DnbNzN5m0Z1HdXk94UOYLa41mooPZxvW2S30GpNVMB/LUGsqK3TeIh6tVzKZ8QpDsOA9JHy956smvwX9xbYr1RVLMIP5xqgMQq8HKfEMSlDUWBpZEl+lvM8NqGtro82kQ+BI88Ia5wyN4bMz3WhNzKcj7uhPAgk+9Am9/1YpjvmukKirwHRgLSsSpPVkwl74uQVawo9kR8jqhsXh2rJ/FOextuuf5GC0NFtoqBxESzJQmJ4B06ZDo5wsqobeo7irz+dTvNEaCnvYF8eZ35zd+RSMC33/SdwfnvIv9pjyE8hSFZ7LNj+dZ9Yzi4UNZgfzG2vZCVXN8p6De0IpccfcZFt2WaSl56baAe6kvRp/yrVeoEDwKcCev0+S1eZqGYYeeZXyJvA32DlkSByvX6/e1SgMLEVPRJHM8VuPaMoKLqpvjUnnGzVGZWLZ2WizqKpPGhjqCFu1frzr4GlXOfMWMVXtbBevh1tYlO5Zs1ESTxPyEAHRuaEipssUjkk8Iz16gIUnF6bCpQ3XdNtHVCRZpsnhvNnI+pDnSdWNzkfawLlsns+r96756k8SWU+xfbL1dCw5zv2GXNn773XXr3TlJou8J8hjaayvdMqt0L18Tgqx4B2TRjrD8w1Fw2/IuET3n2wJ0Iyrgc4bANQsrmsl63KurYDTz5H7mFk/yqHkqpznykuIrcPs42QcEb4LLpwsaWryMtgyFThEsVOkO6/s88ldLsyZFvklslBpCsFMll8999iLqdDXhYruHBBcOHHkEnD8E+d3Gbv/8Ou5yk6HVqiX/8kXI2Ai6YqASFZBsGPysv37mRJCA5mW8RrEfkxqN+6Bhl2iWigviwq6rVGFncDl9gWWpOPJlq9XykpbdGpvHi/FcfGCwJZG2/uiahXLBxG2DxZ/kRtFDH6ouN0yClYNxmPNlHcbJNdDKjgTLotoLHT5GWiWJ8e/AfWMpjAD53amAmtodr3xJ5i75FEJhPSxfLVfzMNs+4ZGCVKZD6pzYK5kQz0Ss2eCdmnsB4KnasANOkkfeB287hlwVh/fK8b9wM1hvcQ6YRSCLq+nFRbBUExh/sLnlp9HD381UFjVZ9LQW74AlCm4b1ydrZd/E3KGrgnEIPY8m2kj1CCJJx+ZVYFAX5WawW0dTvA1uonCd4FdJKzn6ILCR/47233gknZyDjfcOP85HtjU2GhYkAI5CrS+/BdbonlWaEF2sr3zH6HNLZFXpNAeweVGmhh7t3C2NN/Fj16OVO1OE2MkwkAI/0X/x5my++Y+wI3/nFRe8jo4RkeGBq0ITsBsyc9LwStKDCKDAU4XZ/WhojAdjOqcBnDvFcoIhvawWqySiJZH7VusHhob7+O2p8woYrXWttjvWm4XxKGO7pmBDaSgSXYCdvjUnyUo8RlVHXhFsQ+dW58aHXnc0gfQn2RXTwpzfSkogwZwC54VThIupI/Y6eHnImJ9UuH9zNV+SwTOWZA1FJ1SOlpN2aYor6pmuiu1v9iT/UaLpBJmbmQSPrLxLtG25eRZa4hsRSDcOqrj53QgaleT4nH0hapxNVitoiwZr+XMb0l+nZ/Y/5Svuk/PpjkLCui507EVQo0MuaqcDmGFSCinFBzngc4HtZ8C8KvQVLs8JdaqYIsimvNVhoR9sDynQeQ2eip7xqQvsND6RkOGRCC6a8IVxgFgfySzZBcHFzPrISfJ5eXfma0PWuzO5bDXTRftQ2SZHo9PYlah5hz/O7ymPjFYNukM/lktFeuglsyKmaN+sznbUdJIqg71opY7q4Z53I97ttexQGo0fy6JsZN+tvP4S7EE5+LbspSbaifZfhI82vy5TqXIBoxS+W8MPP90zse0d31PIbaQ0T2o0hQ4reAkCW5KZ9EHHXPZUYM7CSKSTRfuYO7ufctlJ0nh/86ylEfrgrnRisjLXnqx7XF6gNILli6szITfpWv/+yqrCfX1ZJvPyDv6xA4EY8hu3cJCgCcS5wT1YiRNChlCdJeF/1wbpSK4gVui03g70Jd5WDPLMM0ST/+odrQL3StnxDdifQ0Etnyd8Zdob9i3+0cnM3xBsHuzPFTY3ty/wmQQsl2y+e5f3fpcNu7G0o7T0lqwMhWY/+yjf8h+aj+iqjZit297dL1yqmXfcDEI+w2GgLgbazhYrdEtVoxTIO0cWVwZV7g0UFrQBaZkwkzD2rZXJTcxNapl/oeVX0/zFA/V0aKBh+It3Peru+CUqR2p/FuLlvGMTxRTBdFSsPYYxQCT3Zyqx35C0khMTG3qbR52V2/OWQKP5Q3xbCXOyx0HBVWQ7+z6T7BE2twb2B66gArjwk0rZ2c0vBuGvc/B7lwI1TZn60yx9oReZX/FYtAOnEJEaNcX4F/EFOew7CfNAuknwzcisD3HMdLRs+hgFrtq5sEbfgAWIUpkAMBXKg0aNX/h5iR+i+iQqJ7ELIFlmDBXbES27zUOlk6tnHQon2bhSnwz5+QZrNlGc+d48CtGX25GgB2+T/aMKpCNiPRkDdt5DAp3758Lae/CAB2Ly3L8m/+RPwDoVhZXNVZOKS8uflL4j41vccNYL1bwde9/GXNuLgeyOj5EVGD55yWkhgvpwvn/dv3igVQ9a3+8xhKN9D347PYbu6YUDumHFq5ALEAH/LblyQX9hBldnZ1ZjWJUMYyRs9RRWAgvwx9jCenpkkpqu3r15GL8FFfnzPcmq1oQ++C+qKncgg5zrZLY35XxLHd+HKP70RjuWCHvlEaQOihPxKaUmIm39cAVqtVRD+7mKh0YDetysX2ZZbo5swuEdJmeeO1S6RL3ITZ+k6vzLk1fpuMZ8aTgMOBOuVqreS2ETIdVFpnZapaQqi67UbAht6dB9BPJ6+sUVnv3EhoNDxR2YpQYqozHW1LbUaUHDoLly4/CTKt0MDldXqJVEwLoZfH2c+d1eMz+V6VVB6bGn9NdUmsgCyUojcfCc69ptyPZQ61lzBshFZ2xLlRF/5qvwWoONUoxPT66IDtUDh0mnb89oB15kMG9xTjLgsXYXMemy/J78voxRa+FOseoFi7FVhpVyx5eElfayP9CBaxVh9uLGUCahVTz/0fLiqNtr2XXOWp4Yowv7Iv8rcTqXcZS4aS3GWYp6t8oO5lI7APlpqgen7BSDSHmB6T/slXSbuaBGxBy5Rolu24S2j9vkqBkfNhffSDccY5hVElPc/jZYhoeB4H5VnY7Sfn+aCkC2Do+itWOHGXMkBmnBJ1CthP/9MOstdgLTb62+iBxHQqMZDP8CTn2b9/fCy262cYMRCkazJEp8OOUArWgGSt/Xw+QlPGIQhl2E5efhj/ZebiEx7U4m78IMETbxVJqTZsUdCzSBm1sN/8W26FgX6q7wxqYFcVR3pJDOLqUfVQ8X1vhCGsdqiYZFncGgbSXiyeLWe+n/uB87QYMBPISBEqHeUkhzCC6uLW+KL8M7NWFxW1Q3HKo4OLDrF6HDVx/98Z9/rgl+82z2bR3rDTH6iwFzdd7Fv4VNnhAx/hzwoOE6KhBmMAYFGa+W/aZir3eBdEk4kIBMCCeBwW6WlYA5dtuTESeMUyZYGpXGpn9gHL4IoHYlILzJoKAtlhbhv3el/nzPCfZ30dALFnvdFqnX0b4LuS8RVlZGY3wnXehTf1LY7SyOZ5tPVpYzVHKw8XlcrXkXvM9TVRmAJ64oiXXgLS4Me1CrUHRJqodbXHztOo3TdGgJBFOLqosE+J1QdWTv0CRjNQimWjjVnmeX8wISt/udypI5k/qd9ysqOOAtB3Jo5GsM46sk9X2exBA5Pc80QzPj7SJG4Ie/s53dPxlesEakXhbyEz7Tvl3FhCCb4rFt8u6/3CuM5uHaXdyBWHKsH1tFPSAyTyaqPAIF35AOpoESScoR9vVzYclkmUgNLBeqNq4O013ocn3WuYPjTxU+0VbXpC/rQ8JaINAxfDUwHMixoImi26BicL7tA+kzEl//9kLv116MoP7qfi/V17lbTQFPTsVwFmyBQUW/E6xANxMdvaEi0gDW+sBq6NFAjZfEULUl/OH2xJOJ7hqEvc8Vf/o1938rJ1ivtsCHFavi54tbB9PpCf+vp7AkLHJirN98OE7q8fKLA7Q53vuBnb8CLa+tjF4C8usqw5YHTnSqGHGNkwOSOksdWsPBsCATaBf3tiVIhHMmiaYqCvjE8a7YoOtlTn496UVSbtXoPTcfqiQLHyc2HoVU4yq/0lkzujFJ4pe9w+FFWDIaOVLp6ErmsWETf8eaD5PZbRPuca6MhL3D7Ig0y0KE49N1T9y25dmu+h3vAyACBe4OyMauUMaT2oBEaTGNJnb3ZVF+Az/BP8Xt9iFl+kvc62kwtEDtgUND7NJNINTGcYUOOa9pmZjLO1YEmsURxYcIC33UAugfZAXwN2XGoNrwUvouUlL6xWWH5hehTrt5sbnRU4t3p/Jmuyfej1q1OjQH8M1nZFKOE0wrtH0DtPx3pK+ZSOCAVSsucvDxB2v9XW4SIxEeKlrseYaAaeeWMZW3W1vw9knX6qLYZl1EOWVgziGeIFfhQtgMA1ndpKGceJRfXkovBTbLlq0E8FE0WrmlYM5SDRl2icI2xAlE9Zvj/FsnXSQGNzhUJXeCEy7WEeRm4NRymjSAdgEs2GSJqkC3qk2oAwodjnNaKcH/F6lScm0T/zi8RLEHsvVHrFH/js7DRfKJzlvNjd6EAcfcqHWibylep1BkcJR/m1okLGBsnI5+m72yflP7qNpCWDIKp6pNWWuX9iJdlEe0gfWFiFbLggustPJjdrXscbUAbRyzF9UsRBo/C0IiLkf35aaDdqC0ElmjOYbgZV0OO7n1UpaViWq+F2BGybrWAGQXfv45gevrj6KfN9KodxTYvLX3RtGX/DOXXTXXEFHEyVuHabGTa1FSR54n6QgPJJjxyr7pC42sv/CaF5LI7iNh7yMeaIx3vFFf+Mwj65Vk8bY+4OocyQzHAvFOL1cuFwEThMOG4OP7w3m9YthrCXMvkelYzgC5YSSh/QNQEeH2se70SH/b6ZHcBY9Z4/vOL/6VKz0jvgpYPKd3xjvdhEL1CJMxf+42vf0M0zNBOiSn5Ia4ga5GvksHIjVMosL2E0sra0gtEWkFj31NpYNQL8Ytry6+ybYcE0vtfFRFy9NANrOVRj+hIxjb7U4l0ybLI5t2PzwE0LikCD5yEUPIrHJzhc52ACbylUiTXyT/NpY9uA25VyYSN0VleCZEv39Syy94HKL7QmjJzsX+JndKIBgJlQhyTRxzXSfrLOkoKbOkO8y8+1AxDVninVxCW+gXtuCV83Rg6maSy31PQjWvJcP1B7Ep1DQ5OKujDGUOYMfrWrTBSz3g+xLZ46wAs5XD1h22Ub6ymvSF3EkQkLbtbLqtiDjFAo9/gdFqYEsIUKZBmOzvPhm1bz0OU5oWUIJVYy4vc8mkFVI1H8zgloarxyMGrQCHHnxud0PX8w3Bo10fEzxPwN7OtYwBExyzhslHLt/twogtnN5T6rMdRRBB2qjTho6Agrk/oFGc7EF/IkuaXEExv7Z8ZjFD7bXOIiKHNU4P7AQPD5apPb5qAKbPsWMkFIjM6W0X333YRZ8S9J92I3u0vmV+PfYgGzy1BkVzuzOyIHA+UzQ+i7g31ULNkaS0Re6nHbrjDknPtjoGkUG8E3iyc+WpCv/Cef1RfuS4gegha8xySewKz1p2UylHrkqqSiPxW3eUSB+/8ngWemvlLE5uukcUUujJvVz3hSWZbgeyVTnCOOXp3v+3ras/d1TnBvkkhc7NhiJTKpde0FGKYKFpRg3JYPDQ5ZnVpImWlyyBHZUOm4vd2vtY8ayuJQk4QhPXwGyuRNpMB01ysTkj8wZMFcQTIG/nMsMD7iSGu8LiTrTb6aLMqL74LS7k6n4CUDORdotLtC7mU7uPJ+f5t6ZOJpZ9Ho23aWkuh1mUk+19/fdQsyW5v33J9ypUTgmFMhCkDyb4dKojoI4oXa7h1RdLtuymRWRS12t+WJ5AyhoqLFCNGCjn/kFTCuXpF3NVdAnibnwmR7fuhi54SGQXmFq1ZD/XQTx68Eh4ezQwmF0no6bQMKLu1v3cNRVzBw6ce0rKQPqFK/U3lyb9yyu4otwBb07wfoj7foDw6uuvhUiMN6y3o8n2wb1jAWUVJZJ6gFO/vJYu4wiI82Su9PoBAw9dsMA6B38GOZtSGxFB6PO5PpHcXp6nuj8YqD+NbN8vuw5IFMw+1mJ0+XUzLZY9gxmNg7tDS4ZT6aUKYQNP6lL71UTeyYAOwRH8UTMqVwASemSXZcyb067dBj+oph50JoJIgPW8ehqrUBaJCiirC9ehS9EerDcZHiYv2C5itACPd9TfixSKx7krSEoaNU0BHBjsD6BmngatQJC0dHIrfSvU4c1ib71sdFmbf6HT3YW6z8Lu03ox4KRaI+0JvZmoonpkVc6gPVjJBqtHSpn9Uua8gg1bF/RE/1bMeF6G7HGl71rSdx95JVlKBGEJGLCT/g6VPMqAbBCnr4vdOQsozy+1ViRP91NETxaLK9VMe/8lXeJlQqv8Li2r2TC+OYZpmUZq4Lf4lE6voNoGd+CAzgN2PopXg47Rx6xhcfBY+qhRvDozi3oAfiAJ8k61yq93xl8kk6iYhji9ynbfaHYBkU6tbsTWUY5zqIA9LXw7pwtleh9XHiXrg28/UXHFcxCdccypKUxWWpL+xDLRtHBEGbdoOz0AVE4hNR4kT51mlfbAXwABXpapFEYmY58w+R7IyBvldH2DRB43c4mvs10Jmn4NKG53eH7grGLnxPtHA/sTmc4+RgErvK5Sdw7O0EJHDhzcBbP4d4h/ptF4/dRBeacReEihHFwWF4Uuj5T938SRF7fA7Dmg+BVkuR2c3J8s8UibRQgQY7pbaGw4HpuIa+s+/0O57P2LFLb+0Kwybw4zTPR5mMKkz/d3trQ1OsHD//P13Hl0mgu+ocNwcXUx0pVvLzroGro3rhGQtu4GFKSssA4N7YUj8CQwRq1lk9C1zxmV575sMBgXCVrSAl6OZJ6CY8Q6iq5/EoxD/nuwRhLUJ2QPhGMrVuy3+O79xKrODZygit0FwTi72KOnAXh6hS+cZb/zex1bNd7HLM1S+xlOEbl0iidJY2uXL81eKdgI7B/NyyN31Yy7ZA7jkME3Aok4oIDmWDBeZR9y0wv/HIKtxMFvAzVM8yxrju2aXh5FPUnP43iWuuWHbZABKs7/5mEOQ6tbvAiLmOwYsfbeU2pfEnTh0kCUJZ3BnMr0kWyY//vew598QWEyn5+8CKxXwi4LFfDkRHdJuJ9cV5Y2jD+knH7dUpWsMlCz7D/9isOYsuOaijjtN0G7F6VLTDdoMEzASW9rMjZ4tgexdJNpvea8ynLpVzPehjn7dh1AjwvDTf3W59tc8kxG57azsGms1hqSIy77sFcHwf2INLC9jSbqgl9KMfjmNfReWDbZ1IodWOnWzVyMPTvtdA1rmf49FqtZN6Uwf+mPtc4nwXNtsrVnEp56oR8KwJlDHm2RcFRJBbYVeMplpHf9T/ygj07IvxEU076BiYos3NgNDgNy1zzVpTwyl3GlJjBzk5kvZbur+2B6KtD0B8y8oaj5DfYS7LXcrTi5a9kui5csaRGDxdB5rgSPMLPB+l5B1+QoAO6mpwzeaY1uA8Dh3NwX3pAFSKU8TV9Jd7ixM70jpaEjQ7yhWs812GNzUiU0lbfth7MF7WPYLqrHjtg4PczMb2rKaRaKFbXfGDxnxBK7E3Q80O1BdGH1Uga5WiVnDXr/YVGfqyhU6lOgPWrPWiFzG+vLgqvMTXFASPhxDYGL4/7/fRusjD3VZM48NeqGQs9PYNx5xj72HsuAwl4hIfmRXW4xpKMfElNLJqRusUHYmcqsfeOc3k6szsVhKq+awTYmQ5b7UZR6Gqtge6tuISdrRIagQBsLpnuAd1yKiBcc1Z2BMeVgSBafaol20H2NY5MPl8t2oSQl/bOVJalCJGNVJq4axqhrAD5zNQicsXzsMrS+truhZ8VgBmH3SS6nuT274u/dPm5X1z/HQ2ZDtq409SOz/XfxRehvXXELml39vJIrJEa0B+ssU9V4+rVQsoAUOgCHAaJjShZ1PMZFbYR66pq+AUK7mWvYN+QgSt0hBNQD8NLinszfZ83O9W+V2qGztovlQJTZ9GONm2xyLuKI5ZXSpENGAfWEPzGN3NUWIk58M9T8xf+/GehmVIode2ER+mt/SViDrG0BOGW5ex6Ao+YcwIPkMKQbmEMdPK1i4iN3mr1QNqT2hvHpUKPyl9qrY1KDGdMM8TL9TlyJBsn9bDloYUvoXdOA688FLWYkmUi/4CBawvzC/0ICOC16D7oe4gC3TPUgMz9cXwvTuAEamkZMEb69FHaBjiescrldoVGvm3EskNnafAGWoGhi2t/KY2xd8DMNeLRgWGkinSoTPvxefaRQrXj01QUloWfVObF8Syp1mK4hYyMsB31SMUk8+G33ezq7/WXd+jxpn/cO8HMfpf3E0UjrzawROeL69yYUl8WEbbTGU45fBP6XZnYMax3/nK9SA/CJODDCxOYTPs5eQwsJdxSiw0nEsVi8xu4dtPq43HRVI1uDZJIQuUCj3Ocy5RiJBIufZy7HOUIP1dBiGPp/pPmIKOF2GZmN3XbjJR6YIqf7RN/h8OXORrUWZUBGzmgk7du81IiFgdI6NQ8T2qKCzqAbWZYBol29auU+Z/vLiVDPcv7Zvj1BLX/RdMNCHVe0ZC1v+u5a7rIFhbGWPri3G62rlck3X6cy0tnAH5u6W0HaKD+Vv5wd/ulmytkpVoJyxxW7RgjG1G/8FMuJm1X8D5nMrvTZjr5vfvOo6Qh0Yz9eXcnPqIeDV3PzxVl/kEc+dQy0zPhL0vn5/r2g64BXCbInl0hNEBPawdaqLCl5G8IJW8LZ5ZDj52QkC4MyLAterCqCltz7H7OGqdSibtsqM5O13NmyY9chySdBxlTIyysyCeJRhTMeTynwvg7bpQGM7egTEtOxHd05mgpz7lgZbIk1jVoOtSpiwpIsxHsV4E3QAcmmCJ1D1byvS7mdVF7Ug55Np65vbnN0vWcNeW3OrZBPTHB0oXx8JqGbWACjyxZDB5BhI0sgexjbLLL2cwCmrW4SF9hDkLczUTVrBSoXX2b4ezxN/to3ekI72q0s4bA38y9+NAhCWIWWQdoLAiQGsn3tI374H/a+kyHWK496qjhvwWp4iioXZ0CxfDiVBQx5MHW5TzkV/7ErubRZ5PkgzemIF9CYiI7n6Wl6z0mBnuqxS+LrOBLVVAqTW6ghDJe3hT63tR9VT6tgPDtzP6ZZVOPNfPxu4fsYakBj8iy1VwCwrxco+cuccGfEOEQYeH3GXU2GpFcqqiKTICZKrGcW1T4JOyBU3VAn/c7I3ooh3Xlh0PlmsZV676kNt1NLGQQMX2fMJY75UvqQp8N/4/FeTUyrVOFXItJhBmHOeC/nNY1nzJozppLGsfXQ2NLyFGnwi8Uzkcs0joc0x8eHyE8NxwRfkV5os914Vc2vzF4v934Wx7OZmf2ZWMcFaFRgARrQhtBBkZxWLLS4c42h7hTSHAu4vLRe49yAJ961QK3oXADijrlJszWRBccH6/0ZtE18XeL/AsOJrYYKCkTqOpD37NJ26NYtIwR+u6BrT2ZRHhoNGo4OdyZpU3ZN/tSC2u5ISy9xkGsEbmtW0iSV8OXKs8i8UeaApAU0P2w5nBqA8byBUNHNoxMSpgqC0eTe5xu+o0JW9fr1xLJbQAAGU8iuBXyOdqYybLqoTmHGRGZHGfsHmZ1L7Y8UHEldS9luk9AVr8MYN4o21mQfTpO/CX0S5PI/8aSIITEQq68olYLqSHsNAPkk3xgP+sEyZ83Je19k32aApKM0ARkAF4ly2Sdo6QgP8SCEkvtVttjFWcbsFccNFNta9CvxnXGkgnDYzyfMkJtfxEyW0IdKfvQjvNNGwHv91zF5eLMxSd/BtUVEdAL0nisNypbkviD3Unt2KJNJHUai9kkAJkIPiPP+5bIyJBui/YeynMTJfq85mCxXQjZlpHx5Y6pMyNF2vNpNnX+bnAJ568zL1MDgo5//nkKCK8ZrjBl8Pp3ZiuTQrs3MGfnU/ZmzoFq99STDLaiaRJWdNR405UFAyUTsJfuNw2uBD1WAOHZMlCeIm+PwQSMlbnnL7Kp8KbOOezGNyr/cpN3UEOjVbVJJGc38O2W7c0MzSbKygsEa0wXPJwnwohX9XZg0V94g3BV22ZEj01obZJYcQsE9Mx8IjIaf75h+exZ2tp6UU3DS7DpMXx/vxucNHdhNzWBv7bzS+/OLHpADNDHSOb7KJs3t7aqNhGA/VyDap+gO9eJ7bfiKEgPd5Rp/0FGi/p3RNbEcKM+0hqIOurjqiIH0qLqKHOZUYcp8qUksO71gE5GuJ6r4lbvxrtPn1agTfydSQtb5MPuwP2w8G5/etL95RkOVoP9zYLOwjn2vFsCYBypyshvJeWS2A4ZIFFF7+E2aagw4ky09MJ5Q3gqv0R/LDIVJDORAm5gWGB4FN4BxQ26XNKXGFi+c7WbQubmsg9sAkjcqtqE3KcEiaIsxxK7/jTfJiBMcPjovGgf/SgDp+2hY1bQnpRN0UbUAjtDvBl0xCIBtxXaQzwLHZJwtqXQfwmExu++Fp5/6JZVnMaBUkOqOKcBG6xkSrMuIO2dzaSOWxk8kqgmchbL30zJlBlayoyeEyNTycdHqCTUt42vg0fdz01RoecKUgZErNbCH5kgcjrR2OQROcktAOXzrisy8vo5cXOg4IYfn7vRp9Gyziku3RwdGkHT9QWO/BsRWK6s1hdYWkXEiCb7dTVhSZT0gamSQHHab7ya2kLj8uQzPYiMT9oYdEy6Kz+tV+EEBntdD8KcOEBoC1QVVb7/Q5z6UE/jdjHPLtpN25ZhWT8iYaEtuiO+fslMYzc2by5xqzLVdhUqPBMZ3gcvfBq+JlCSipi7Zww425lgdUYuRri652XeKVwpo+48jLihuesXj0j1t/y3wXaG9IUz/9EDmb20brxKGKlUVaZ/tLaTJOkCzf+JPBTgXmE8/QkgyQMKKiJudds3mdMV9N9w3KMyzK2dLl3tFa2RXTUsxVpi4btBQvgRWaf/Y8b/PQjQS6ntbzkJPQT6vNJ/brLvzb3ae5qQXryxm1QcvAddvloxe+PsUQQ0wt6RnYMUHl4uO576+FC9ny0sxPNuH5hh3JDfzPX0N29sRiErrTl20dlFtlJ/mzfUUbc3Qo6EWpPNrSLazDzciBvB8Dy36Xj+HfvmJor5P+Ne/a9ajAuslEMX3rbgGUWYZ77zIjEicdn46/oRZ4/jPRrrrLsfDDwXDM6mxnPUZxtVHxRPyJ4cGlXMAleEaLgb8ggjbmurE7sr3W+lq8L5D4qpH963LlEMtDxwaYmlFH3y1Sh2MRLVZuuNsqFJK6FqqO3X8ee0kBRXSTAY50gT7SaL+vO2QuprQo1X1OkwWvJD8tehGFG2mizLbECZ0chOCtF61U8T0HgzYaim1PTxKPom2IvM3kFt2cqzyn2QYGh86OooWdBGNomdzh54hG6e6hgouImc6Ha0SCTA0aqdToRetkMsug2QAWmX6kfMLiWvgNRU2V6xWM7r7PlJV4+pWYrL05uG0wUF9rnH+0Cu9FCQaInmzjjVFU2n8N9MCl/pycNNql0K9Zj6TyKhXdrqexdbYVvjwTNFhQOYsk01lbkEX+ZHE0qFuwdPoetnuwlO78wSB0Mu8nhFdYAd49TagzhodXe0mKbRVmpt7J/IXiV/JN+kr1y7Jzg7+Tf3RlpWfsd1g3pmPal8vyjnaurfL9TvE85RgrYn5d/o8BwBeBy4I28VWCAW3MneeuTF4zoIGoegFLNE/2CA0OhHqi0R+0C8c3rdRDjVIkDb+v1OIJ9r/mFR3w82Bo2/vEUcrzoOg5pZnLYvJD61C9d2CNRI0FJnCj7YxG9it4CX81zfIHXy9ligOH34C44OHjYJrPYa7Dr425772qsfyEMlmAFQKME+JGFV8MBfxsovyqJwLxrfJNZMNGCXRyu9DxleY3rnJ9G97bbn6B4ZqlmSs5Ldm6ZuFraTURJguJPpwXAH8oSkroFxZrFVAunB+l735qlk5VD/2Hy+6ReReoCsbSlO0hDytQHyCo1XjzkNnSaCK28oqCinJKAhHHBUauUrryNd5F5iI2sUj4G0QpJH5cxi95RQNs48MQSTY6CA9kOqrA55ls5UMkfRSyAJ96gxVPpuPIPBjMNnLJws9X7Mpjvt4kwa4Ks8HtCL5xMpLYVFjG0N/2SwjZjp6PpE1Qtv7dewk+OBA+cM/uB/3Gemzty3xBWRKP8B8N0+tTZw6cY9+9Swzhe0K6jlrJNOXD6x6BiwQSDB6s59ZbilCXTOtya583Y95h1FCD5/hGt7/Op+4tJuI/vd4mHQUCtsA90nsaodK6/KZkVZDxCU9p7s8fTZrBfKE8jTaXUnH2sEy1y7j+Pmbc2WhZEhdHMkNE8TdNJxZI9uAfs47jbz+VXizfnNxxGEee3w69L2P0K5v62BRJUTGMavNNPH/xe1hXhY0Fioxh/qzzeehunJOaAGMUqcHRROmk6VfY3y9FMOSqkAzr2rOa27cXItNKEIGhnOR83oXKEw1W/jYx7kTFDyQkLffd0vSqKX2qSX5ANKXAXXRhEtzIILVm9V+QAtVRpQprS6JPv/j+ZJZkQ7Uxe5BxfJ63zxjDP7oAFVQN8nP9ijtMbiqVPaBWC2tIk4jfp90xEmyxD/L+4AGwWneA2+k3PfhbJSkX/eWKb/ACHQLN5SxKA0pVibjZ32ePc47G1iOVFZdHeTAPlOEf7po6ZAko5bKfXENgqWC0rbWzUkf3lBu3giwTLXPrZw3iii1QtWm93TVGPfNzb/mvi8iGKYPbDAQICX9YS7ZkVJMR0KxjjSJcm6GKjFHInSJ9iTeqhomGdVfgY0QnB/Pd9FNiKEazJFV9ns1BSV9kGYhZ7+ppAVFugSrCZ8G7WpqK7F465ZudUxIsDdEP/IL9zDYzKEauHN/vfQ6tcYkSYqfAolRVdP1PWcBqcnj3K9fgAVOgQGFOCeDiRRaRaKGTeEpR9MChfz/xEzPgFNTvrygTgI5XiBEOOYfNygUM3UOp5lf3kOd61w/+RjvtDmNgcxWAqqzGEGg2wRbK/Je6ZRYXtVDdXlkjerX3r8yv8iELsAlbhLi12cYFyMa4nsSokSjomlrm93yO0i6TkQaiP1UCJizsyQVm6PuEVAbo4bzqXMR3vqZdrz0A+E3rgBzDpNOgOevFLZ4oDZDKXf32rUSY+0QqWiDaCuO9ahJR7/eH8xLmifw0A6ecuohv5KxS0FCdR4KUKZH0GeRIVg93G0wCxyZ2AiNhdoN9PS4sWCfFKFRQ5a9IPp+EC1RVK0iXpb2HWqAuofeEniKG9il8UZJVkpzqya1WgjFPKAg99gnnv0RnJV+QNBVSzyRPyao6PxESWIWbcC89EMmh2+P7z4cpWE9jWBo6bXUIDL/l9yvKAhHUk/d4kX5Gkzzho47NvandeJpzVjoNz2VI7boxnI166BMMgy3c4VOcV9Gfad0V28NRVk2WGwQ+fRkrlwyceNtn/41w/E1+wEmXaxJjoy2jkec0vkcAWO3Fbagqy/UcSinovxnGAj8+w1uGW8dG8gJkWSzFt0BmrCj2t8G3bbcTHiyDkmUJdIPaUntBxOcJmdl+4efdD1eY+J2iTa2ocU0rnMu9oo18TYhY6z6Tn6MsKzCRUxQDoeI+6wsus7so7vSZbpLnmYStU27aqvYvpEYVRsPxDzBcaTI0O/pMkFTQrywuW9uuM28M3pA/ubz33+M6lEYrkMKKGndVVxwihSQwA8TPseBGhr5UvK1iCqUhOusd3+KxuKNAY1igmi+sQXFkLfs4rIz5qrPf/cJsCbYQMpGjfraxzoRP5Frs4wKbBEKJVZRKiQE6MZuIY3CozGHyqzicvno28wkjbkJZkkXMtYqDG47EYJLIVW4tRbOPLbGPUoPFae7WxjzkpUs3lsYRfPiCt3Fmb8yfiZfGZDW8VnuW/ZqjiTlgG8g/n7MJp9ebNIdZioeC6uF2+qkDAYSK7frH6nROBsMErdWvrrMKYd53/8pUoNwX2Ijosa0CyY/gLjOpYEmS37HPBzeDm9sTqT3DGMSfl/rXDcqow3z9K6QZsr0ld1gvaUoFd72MOhaTle+bKdqNP5vfzUSO5HIrlB8sHYUyyeHIBMYI4G/0C1/EeJgp01THKtCgStbmGtVt8MpqnUJaJIzGCEqKxXxK8YBxrXwa+w0vivK2L4FnXQZrLAixtpF4X8X0fpAmhxRcgC+0yEYkl+NH96K+rP8qXWMx4j9qTKimNaC76hFJzW4tFDCCDRlim/aKsunV1i/0u+XjfRIsYFi0Tt94j0+GDQ23r7ep6Bmso+ms+dbt2ZOeCrDnWEIAMmd5l0vZHP5M+gl45sSLy9siV/BU/nmtx4IKhex0m3dbsgycRToFwOuXEgHwyICgFVDYHAvXfs1p1ZH9zV24uDZBWgo/aCgSl1GIs4sFAn3gGSM26Xo1x9kYBBe6iXWfcG+EVIAjSPXC+FsTjNuu7jnGW2NqlHMgi0FXA11wrPyxhqQSSVCa/+Ky+U+xNrlIvXNjN72jqZY+RSDWcafLJ1e9kDsnlFolqxa0GMkHNRnbGLLqZPPC9mbQLPhmvUYGeZ2rtjHwqe8q08nP3OR2Pu+XFpjxBZ/WKvOfXWG+H68QPOcz6WbF6kEtlRV1m8rDIGA6FZfzsSv3IiY8KRIiYH5rbmC02Sm8LBnQpREl9B2YUBcc54u0k7gdsJ80PdBUG6dPCFUq4+vQBonqbyQB9qu/0qN8OEvQKn40s9HcliGa2F4zj4TbgkPABNgqPkBPmf+iMp0MRIxXwWLi3CVWhq9GrSBGWWU35Jhf+PXLWAD8tFiCb7fypl/ZRPxUnjyqQ5BBtyi/f24azgiOMLUi6grhsWqyj5Ux+6i/IUEm3dJ3H0nqDrYcYA0kKzmRTdyGvRx1LHONSi45mfr5ImuyaC628bB/dFZfcS/KZpow/qdVtoTSQUn/fasQlwCGgrzEDSUTW4Eucd9gxZzQl8wqr/nF+7/r5lOCjt0xp7gWX411IVTkzspymblZyBmQkfuZUcRbxZVQdduk/1MlV1h53XyXry4lRiqC9vj8rWlS8q2P7MKzaBIyws1pVmnx+fO26gigWsVYfsp0lF8tvAhG4I58I74W8e41N3naZIMWy/sD+pQs65u/k1b77O+E6Q0bJlJc3sZ5YEMJ1nGjZp/NQDZIQHlJYPWJUpvwh2HINLm5XeMZNEWxCmknzDlJqM6p3Dk/uURX27B8EMy+P5KSEKta/nZ+nUzkfl3ygO0GLtp1gq9ipqksZYVILuIROi8uZSPCri20c5YiV3eCfmcXnP1vSLKMyabO1TpeVYte2lTAvFRPYt/thAce0OV0AeMr8ef/iU6kWC5f2ZXLWtqs3idOmU8rPTr6Qz94IRGgUjNvMGXyxwcEUUSAeQWpPPkhmLjLEMcTKpluOyPsGrssGYBtyToMOIRiwovPiEqM2CZ1k75CiO1U0irQ5SRmYe37y/0XMeYStzSHCqEU1jp2yKM3CKHV8SwvXR7lQpsIsyJaT5elxrbq4n5VbBKKXIJjiUDtbihMmXAJ1urAifWJ1PIGIFfqRIxhcSlyAPAvvVPFnAjIAD5creVaeZP/BvVQFLi4sUGIeTimCp93ktRw9I+kwJlK4M+EqYbIu4Gp16mUGoqIT6C2P5W1IGl8iY+nMoEafyKPQJbpTeZVdaoDzu3F2JkRyqPMCvtSJf2V2ffcN5nx66hBudY3F/fgtpMfQlfcYot/z0fL2iP5NKFgkhGudQ0hs592WEy1JcBTM00VPSMEUaY0zCVAZAaAxIdCAR0yrZOH8jdhaioghkqT0RNCt5wqcLYlC4XEVjUi8vg7gC4rh6+72Zf4w+dZeaq4llHpTXIDycfNTT/QOHRiC5xLBpZ5SmuB1VA7rLiYpMKn1dd7TI4k038xlBL1PKjNkNLEb12ZbJn78Blyd7fsPjq1/tRaMyeQ91IOlRBfhdk003WbxkOfd8O+I54+tbaORFiBHlEDmUaDMulhCjOMnoB2HDETFwdsqVycCsIe3qAVb5suj3clknZ/0p1Dn2EkQjTnKn3FnqcfjVj6sBgN0vijN4MMyaEhPyUw/8rtrm1+NKSEaz8/mDLibxR4jkqK35YYTTgikxPZVNx9LakyalZcG/RRN0JKq5qSEfaJ7rm+l3zsFHQ1G7+HE6054RWh9Cv/FRgMrUvKKLm98mstXV/1vdcRqfN9AKr5Bv8EZlvfoup4iGg2YZq7IL7csKh4MYyNLP78H0RnNIURwqSpcci5T+ddtcV+xWbzhXq452KzMlvL/eeba0JDe8BtOaoVqPR0VAiLYfc/LXff3xAkQgYe9pmucbX1ZavPuip0rLmBbiDF5X3JZVCsGIi0+wlhap9s1hHMzCkNCUW8UcHYG6xWC5U5xvnjV68HQYriFEZFw2ZrMTsptMleiJblctna8adBtpBx6YCEAW5/mkUfVvotHmkjCCriXx77CdgZT2HEQoyRivE7EtHM56hqWGzQuepyc1xsaKVqs04w8v1sIAhFyAX/+dwEWyjEfCgoOZeqlS+56OhMhWl4rAj1OFaljX2CUWYmZAVTh+1h2hcQqGjoZJuSZ0E3KyjKED3sS+oBfmJIbF9aw3wk87pZ5pvku+VU7BuOqulxkJUBSGW4IkSPA+f6X5v11s+H2BHEhgV6EVbOBr9DD57rxG8vKimVgHIXC+1zg/C41g/h89IiSLTSnKQolrW5o9kxdjzxk59axhdneHNvi2OKygIbZsMVwYDBAFoEbx7G6t+vaN1Rr45dIO9szcf9p3UqPCVx7/swfM0aDJr5FatJBlOECFKYl2Rk6SANwsV+Iv7Of3iYsSGBlYm1W7Ah9mL2VsGPjmC4mJ8l0ILp4Wcx23FVK1+DeVRtcMz9F4zz92uw2gGjypxr6z0rg053BZYS9620eq/umHkuk3tZRYYhWMV38GpmLO4Dl5mDHnzy2AimMoaTc5jJWtB+RUTH0gLv2qQ4Gqw1dAdvDs/NYVxwZl8d1s4Gjyu+M/oglDCDyVJYEEe/4J2dwK5ytE95Q4FBsDRmLkKK2uUhnq5wEVmIPWbC5DGaeD8G4CR42F3cgyvDy2kLaWHgvu2LUSnJDjw3BXq0G+Ft/hK4jv7tUI/crtFnCkN0LykaKSJvgSZqaLCvkwrtFn1Yznzq4HYVBWLwvy98FL2SN2aTX1hbYgnzaM2pVVFJFiHYNbUb20/h00uzfUGgfP+f+33xHmvgM9hns64es4CtZq+0rHO9xrgNQcGqz0H/fhJ2L8eTQtjpaMoztqZZZOg9g5RpRMGekeI5Zh32x6JVA/78ju2t/qMqHFNDYCIK2XEUK8fN3dtgAV2yE1Stte3pBQdnRfQWANaMZybMoVhXUNIA60QsaCpm09kAlamx/XnFn3pUk9GdCXBRVqjhKZUpHFKxVsJS2nIEpKK7Cr4CtVSH/kB06477Q+XgHnMudODL7AsR85FfWL0U93AUFHpI0LqMzpyJPfGUnpJVImXqRCNnOYPeueGRf35SaGhypNCDcaZsZYIN9xGzN7dC7L0OZYDs3khiuzPPAPZoc2X3CKVsZeDSj18zmh4cPsFqQqTo0MW8ff3OyahKbN2jFhelhbPCd2P4Jicgrl8LsoQuF8kx23/yOsrNPIJpbNleaVvdJ4MaIwEIFeZafFJex3ZTMUcvWyrD2aJ6iAxW+zNh3D+akJXWMk98E4d7aYxk/v5An6AzfXK/+ta48SdAl43fldqrq+2lylZdUnTfy/pWxT0p8GVbx8VP1/uRohiVp2Uc9D4S5nbsEiJv+snNGSlmDQZ9OVZadkCnAsEtfeFfYRvK/s/GGsF7BkVo4+1oeRkrFoGtkw+7NRMafpHJxC9fMGpeRmzWB9rl546v+KcA/9GG3Id4rHLaFM4R3kaSWFUEwD7Bh9xO+hQpBVPZFcjTdtN0Ps9cPiXlhIBcoQl3hUVIuUGrlTL1b6YkHD+VTgu4Nfpn8v90+EIQZoni1bfa5qkcnc1eZW8GZOsdj4hNRjT1ShwmYqOXQyVYXFj5ejctJI1fxSK4jkpgnbCx33QX8RDy97ZE2byinRURnOFAWczcrRzNHNzwbAzanfWgUEaEgisgQhXSOZgo8TE+W5iP1nyCN4+QIcSlzMpNStqKqitrWvzYhOA6NtvsZ8NrEXi0SQlf4D9LozlumoEEmPSWQyl1KbhCjt7nr99jq+Rbpz5GhuN+eym/9KlEJcWdj5b6mW+U1pX8y+85yGkAtGlWjZWH/JfzQHztg6tJ69HkUiL2ipCH5VTcB7SjUflNj4vPSbbRyCYnfLZdQwBzvl8EE2T9UGIChaYJkUkAAEAASURBVAJU+JGD4oaiQ2qex9THPks1CcMY/06nYxeOQHL2aqwPp9cxeDff8oWwmND5za8kj1/JtO0KycjsNCBWgdimcU0/WdfWFmKEQTNmOAhXcT/+bxnDrRLXPj2V2A6AX/iRmiyS/5UWb9WBpWbejPeHQLkfanTP50U3DQMN9BY3iKRJ/H4H4yZNR+jNNNZK8jitOERruGIMSGJqqf54BT0AdO1qbYFMjEMolnz8TviIhNBK6vecIHY9FRlZ+F76oewGuMJ0MinhFkQ2CNWvPmFcCsHh0hK9yQ23kFt7T7p7bNh1iL0gMjIIwwvdKcAZyAPkhKbOo9tdVBhU+c2LGam1KkSwCBDXnkvCHrgvqT2tRe5VcFMpepLA7XTxoxgrpXMAK+a2aXjMrm2spmCGgQW0tQq7IVP96wyWpT5FIzex5xAeiVP+JA8+Xs6cxKKKvv5Uv4n+8kwbMywtGNTfgnFvTJdaEkLyKtFsxhwge4gvVaSYGX3pkmkacU2eTjpKJm5Zw9Cz0M49WUgCsENGDd1JM99jO5GCSmAa7Kjqr2QmA8EAiN76a8uhXHm8a7zkPs0Md/P2rPxIk32uRXXp62L3avBqaYmkwV9AtfE8MwbDcFo0l+O/3plYCmnILm0RMOirj0yUD19VQYI6iBLlc52z9j1mis3Gy37Dg4C18t+ksyx29AJ0R+add5u++kclwY0Linc/6GXDoBLTUE+D1khWS/4V+zwa64GsN0xxqcKaFM3gf+ZTuprBeqqP19pvUbdKxSFhY4Acp+6g7Yaq2GMVRJcvJ6n2XSFKdRO+Zxd99vBgIOpca6cCKwYSUUyGHvz8OkxbV0HCPaujy1xdRwub6m9fq07H2xnPqgCl0rm7XfarZHsDTXY9Si84iLTDmsOkNva5+Ui4UrLmuqA7e42omyvA2mn5/bdVT0l025ctyG49qs7vfYvTxSGcUPqob7m99uNWvtvTMsNm8LDytugPzZPcFb90ixw8jfz836zm/MdxTd2McPSxNFLUTcJQIsmAHojjuaJN5VVlrOjjH0dx94VecxIj99j86jH/0nagDmYQiohPXO4zmjSwJNLXPxtYrIQ4oSqSXt28+5lVFaCganoXqogkuUGNEvsxjCMWRweIf3/7FEJhCtNva2RwJwey+LeOuNCEyjKvkmhTPvG6hvBbbr+/aqEoxcMpJPh7LbOYbIw5qMPkhHBQE2z5GICEfjMCKQtxxPMhHeerdNK0x697wgWaI8RQQgCuMh3NkswhBXnw1BD4qzBk9oY0mNGuEwMHBTJNUasYqeSHWEoQ1d0vP0Q+BJGYylmpGi4nYa5hSFS4OaO+/+/dNWGz9+UBqIyNnSMAmCgUnd+neHA8KL+rUnIhMcVfyOkEle9P1etscWkQr1uZNi2hRg0RltJ4jggINvosw7qmRD0DKWFvRdIcv17E3UHxYq2y9bVoSTeifWtYO2XsI4VTs0EA26B648rblUd+4h8XzVucx9BU8WpPn4xt9hd3qNlVBRTmpeAxgUrhyLA512A4k/T5vnRrMQ56OIGpoDft+8jP+IQdBzTNaLHp/Y08/vK7agYM2e2F6BnMNGLFnr76Xml3SCR9/ReZG0DxteNe6biwTRDHnO+OpHLEJ2XZAMHXX021QDk60AcjHlC50TCF8NthKtbnn3GYqJyPuRDW1bXVJrPyZmsZIqNYUs+kv+jcl04a/g4WMoCVX0/QGV4/Sdqn/h6MWJ2M/tAqG6S2CErPKdMlHFAp5MECm9Z6CCRez3XJQaxCvrQk5z+6fQ4m6aryREKh+maoJjkpq+aOWRMUYZLhS6LMpeoZZm311uPg5ulCw4xn+rdsaXmRT91X/2MlVb1qfm3wMjamg4H7Rl38Ebq22/bpkCDCT36lBXvNdONPJeqWmzENolZmpvbfjb/Zum0zzTeCbTZ886LS5JAI+SA6P+BBR8PwWJWCipk1dBhKD4vxga0ZT93cVGsZJbe9FXW8Q0bL4f7rXsnyp+dVzYlzVP5augT4aAX46EdyNBIpeOWUX8nNJgTEOY51aM5Wcce/k7bWuzxwO5nkRbiFYT8m4G7uWfdBg3KWLY5KRmcF+UKf0PdeLYz+3cmBXIJlbEK2XyQHgwqBU9T9qCJ75NYDJ061O4XIVy+1og8MaVNT9gGkwRaxyiahtZdDAIvvwcOOqE9KUYtRpuHkRkCZojNymskezL7fA1/p/oNAsKREw1OSEm2qE9ex4LTCzz5THlC5Ttz4R+7TidFpiEYMe7Y0QTrmewp+I8hTJVznjyv2UTOXGjo3ekQm8t5aIBGQiNbzKlxmaemDQSVc+fmvr+sztglK+p8KgDOv4LwzIeyJjLq1ibDpRaYB8hovKOScm/1P4BUS1/vP+TlRCPmdKA6cRfLxmg28NfjEpErQXljVEX1/Go/V9ZqWk5jnr7l8JiAq1h4d6QjB7/QDujRqw0RW46RerCRdgfZDoZn0L1vh3rf9C3UYUuhlNw2QIGvYwH8pcEYlVW0J2odSqGyguJbzkdN9ZavfKCrUZboSyVSe3YXseqNHvHd/AdPNhr/0sM2/wNdDpmgbeVQJtqyBT2g0CpX3nQ5bYKoPQ0lS1tKQbx6FjxvNi2wxQKdkYUmSHE5rQDqkePgrVrRUKUJ8bj2bMKGDUCEUSw94yjCDgHCtrpZ5bQzzDWbl+S7rxgwkQWWQb4uihKU+R8QdFGBYQv8JIVlQRQPqGmFZWQU6bh5OB9GwQUfxPRhVaNPk/URLfRmL6rgsLRcNE+SY9JvFDJ4NZWekge8zldUoomDy6oKf94p0VNt2ryPRwu8SDQIzdw04/5rM8aolzFQ3VMp8u8W1AftpwIGNJFqOGpaFXAHwQpByCW6tQa1nuejBLwq7BqxEkWjpbuRJCaTts2pHY0dxg/pcSaGcerly9gAF4fH2/CfNDjsSW/nLNrRkm2jwmYLtXD5rFb+goyUcCtJBQrWwVRdgk3o1q+8YVB4EK8cbiJdApk8EAR0SXi0p0HiCXT4E/4JjuEb8BCXjWplBg/lLLOAqFfDbpvq73+xl9egv7PosfQSOlKRZ/yg0UNqPA90f9oZESWe7BDtUrCnCf2w4YGnklix9sljVwHvEdAsMjPXwU4ArwZ5nHcmEyjKVUCSnBmpig/SjY3TE938aoCQQrtD6I0AeY6mm8hXoP2gxaQAP+3gcVxbemtwl90/mR/kvvjIW6KOB6umXvs/XQbzrBbOWICidGPiI5IcGdjrjf+cFf2Klq6qfy5dNOVxMuvG/NrsklIz4EQyM51gUiTwHdfddm9vTcYA0AaYcp8hygkEyDBlq8ODFifF5EzNt3YXo5N4M73oopcgkYedXPZdtMVcodLgpehBa04d9GjG8jnFx0p9vSbrK0hBzuSX3nfTIo2SzgsYKFTxHe0wI8Sr/IrQgifBbHl6ejAEL8q3Gm6aveicR/Fi7qrNvo8yMy22LiZENXsdpoYReOif9BMva6lSAUpFiya74M5e7jZhxm+AEzZVy+KezDQfWupwYU/REPqGMDMr2tLvvtwF8y0136dYUMG73FTqSUtlNXUkIKwtUkzD0fhRW5THFTEjVKIkCCBrkybMFHeinv7V22YlREM5yw5kd7FQfAZ2eUExlk2LOzd+KWlbwN9gfBRgnRtkgXhgpRRzVjzddbCQFj38hu9mM95o1cHp6rZe+5dS4gdZll2AThliPLTn2+WQAlI9o0iiSe/GR4/2u4i7X4BZCTHNbgIbxVhJ2WUUgi1eCEhVU9S26CVctayhODWSKYBxq4dyhyp0vOKZmRcTyT5XmirZVyCVA2rT19rwgnz8VPzdxhfkmymtbrknpKlRZoO37qxYB9zxAWJa6q3LZsMkuUhRgW5OhhOt4jDQrF8KeiKNUVhjZ+pC4+7/68fv6P/5/TJ0FoJe19/+HhEpLCNIooggCgkiHoIAIApIi3R2CpHAv3d15aUS6m3vpDumQ7u6O/V/v83z4/v679/M829nZ2Z7n2c7Ozs62UVNDCK6I+uOBWW3pQG+gp4zj6bUUPQcbftBHpEL8Q6vyh/gtN3gE2OBD5axsojAi8POW3S2l01TMfTv6B8WYcosOk+kX4VVVkXw43rKfNManHQO2akBC8r8o8rUPO/hRl0UisGLXqE/q4ZVGE1WR1ePuAN+z6loqd0Qwx1nSJYrerbBMOaDkP9+tgVrewUqlz667NvULUy+wZq+O8GLhZ1OAt4472U76pt8HSG94Ok3vuYcIH8GyW1WYE9Aoa+/buZqnCMjm8BJJkhx77Vt/jof/wQ0hNM6zd7YOBpjsM+Ux5SZ7jdQn4n1l4CSnKTkXej3zrGNl/Hjfd0yH2gBa0gnHAMUMaQJcoaH1lpnG36OoQNNlxsF0vJD0xf8jvpe2v8GNqwmqOobZT9VP6mXkgx8v3yAavjqSsNKVq6mNtku1G2NGQo9lH1FZCJvptRKiGEHY6chreHueNF8iwa0IdnrwJ67UAmJUV+9t2TcwwX3fh98H6hesvnXzijy4HzgrVWziwFv0TtqQK3oriQC3LFI5IZg1IcDaT4bSfJgFiBIaRfq2U7BsAsHsIbgWkSD1fkW2FC9tQx1pkNeltk5hoY+NRZVzyQwdXL1lHJXpt9jsIg7bsPfDwJMe9S6hjxAG3HfON2yp10AyGPwP5vGjrREZawvKFxaUglR/234R2jLfnBh5PKbW9BDaLUcvVNWKKiVABwJOZ6MuuirAyKmG+NZ36M6HilAI+UIzU/AnJVil1Ld1sYIA2Zha9g8D3uhqFlNaThXsxey3ZCgErIQiEE8W3BY57H/L+K40+57oLQPOBKx3lSGKOqodFMQYP1AI9IZ/HNFNCjboXyDWumaE2DmKP+ty8mGM7OrRmr87Jz58OMiHzTX2FVzN4503WpdZLkc1Qdsz/ZrIyAlx/cKULp6rPesF357vepC9Wz9muWmnOrS/NottQI7M8YyKTO24xHNQb/WxpMawXh+vKjb/49F/IV9p7rSGqxF6xZYL/RJoCwyzpBKjgLEn9tl7rmeYHcM/SYE5PO0FvMkLkvSNtoGPhShLWCnlRvq86v7AzuX6wONp5S8Y1Auk6bzHrHh0SR3TcDpwQY6ZmCVoDgbrNGSGN2gjwDVqwb2skFLbiGamixLMIqP50U/c5lZkHE3MvkLyoAhqc38a2ScFMOC8emYWASnWSXaAhTrP/NUTfkQMp66pojWtvbCG5RyOhnnaAfoCv27g0nvKpReUZHSq7XpXmP43r2XeQKVTDYNtOl8zz8f+51QUqVX4Ry4tNSoTMZgp54JenqVk2joobloNaNj3Z8cAxW+19Tz6HqGlqfTO9EE0KQ1wMnKdKTT7FnrelueI2ajHeJsc/opotORIsLMXOLdoGXyC0ngbB3vVrIKApi65zmME2woSViN2qFMqrDgR1fXdIomRKZBu6tkYMvL4F1ncJqKnYWMgJFn2q/Af/7g4HwBsn9zpYSKQEqD+5aj6auhBULuGacZgiKTrUa0+X4V6qOUbrLVbCb9oi8VTbFSF0Gotlc7iq0VEoCDqArmHtSEncxMtGu0rurg3GoMSmVVr0g8IQkB7qXJ1HUq/r7Et64bG+AvXfKTicLxlGQSf1dqThCxV2RLA3brCavDmeEJXyz25N/ucVonyQP9aLuTEvCXudwa8kF7thtyC01nz3lW5GTDjf2RzWTXDGlok0fcLAOqr3INzoz6lq9DEx+xPpZNC+XrM5NLFsDpJCP6OGPY9orZxf0iX/gd1wt2+xbDMTxqCiAyt5Zr6FElElIn4qHxvpkt51YPdDnHSE+Am8r4B7l+kG3mN0RAElbrZHAphsy7DT2lKK8/PoDBgf8ZxW9VYSdxF9N125gEfHqTfuQZjTyhk9M8j2yAxgjuGRoQoDtpq3+jLvDGVp+CAevL7itpAYPBJN/4VmbPBJI+0A95SNhLEi0yt6JVZrg+4/22WkgJE5aDHuADLayC1bl9RfOd0nOLHloxxoZzKrPlvvIeKVOM6QiOsTxXVz0XRD32tfkVBn6eNu/J7Takt+ejULaAIOGIMd47brnoAEh77Zhc3qSUxxhCKfuHoeIrQqbq8kavTEdNVaw4yJGC6fKENH0C5Ra8pcW5jTOL5JF9x83PbwVRgQjuWMXilXW1LVslfwmRCcR38tcfmsQFqbIhX9KnWNfqRR+7KLISxrmY2XShL2hzMtCf9Nw8zSG/09Pw99rUYmqGcLkHS8XAmVe0GivrtBiW5W8/FmODfrlhVbeXVg8qPgXt9rjxPGkLrlvjzelt8qXmK1SjgE4bRvE6GOMgQxGCIuq73t1MniSbujmmw8DjH93nAsoXhPxNxUnF7U5zB28maaozFwrE0D0eJaSwzhbXZ6PsmTF66hdQfbGsKK4ujmPZlswRc5i7zMy/ZoE05TvhTRGYZrX+SZGa0insNXAr1hMLwZerbzXasZaKZEZ9WCV/pjX1M3DvEO5eOI1RerWFBjRBVZfne6Xr/8S1DjCZij9oBzP1c2YdRLzdYCi6wmb9co/I6lMvo/6Rd9reZNvqzZiFZ3Kb+MrtwLKENh+SvSMpD/KUxHW4NESzsLAa7owHJtRCq9ov7Hc1M0dk+Yar0QLOn8ufNDlVbrLZ3BW7RUMD7TWSFn1UdzpcQJ7Dq7x9c13GKUYiavlNqgGR+a4/Wa4ExL7mhv5QEsAdVQfs4h8G1FJYKZuY3XP05WQDsD2yUv5fS573a0ZBqlbMPlbiuz/d3nuapqdUkXZIn+J5MtmLuWwXIJ2/jTgXGC5wJoQsoOZD8hnHpzdF/Lqoda2dkcvvUNJMi4erVaxffheQo5T0kw9nkv6uqEMuG0KPS1TS/wwDxc/l8uZ1Wm0m7TRqUm/Z1ov8jWue+k+yKr6QZuxt69TgnJpgtdzQFv11mwNf7MaDomO+gMvGv9qMbxQTJTWUbFKIH+g1NZsBMpKydZ+QszVLWwnKsxwzS1ETZleuCQYlXu7F3BJt+ovUS/xjZYwwNSyN2LbHoTn5ztf3QTKA4OmVlXEwxh2lazo6E9Jc+kAEKix2loiFn/5xaUlFYUiZHkhVN2VX9iRjcyWfYk1c4jLiOA3T7aS3GoCLWzw+83PQKawKi/K+HsH3xOcKQqqjfI4bsXs8zg31BUw1j95HM5kGR/Hea7KW4cz3J6alRleqb6Z+6mcW1Jfq3zZq1DYbPsZROhBKcKwwrixCW/nGdNN3pXMIEL9joxt6ejN1dpEX6Aft9xo2MuMfOvS9AOoHr2MBDb03uqs+T/gd5ymQgWZjPypK2bSbcnGg6xZpakM91lqtyxqjcS+SHH+hU1iCXsC5b50JODUoTqWgWBts0uG9R0PYz06ABeexoH5sNcnu7507hs7VE3hHuE78KKVa75rgraVX8fgb2pXdhVxXmz9FjoX8VBv/WfZ3IZG1h/LA2sgnhT0fwMLy4dvYazM/wgpMe3vrqsaLxegCdh8hX/f1wNeg8G3SEL1tzwMPCTXLhHAhliuEmqh/qwf2sJMG5Uj3srb9BlxKUQHA7/nFvPJscnOtclPEY/0rCxuCHWPZYGSy9plWLq+sfbanxFGyv6k4IkWO2Yf6hMDOhe5QitHrX9uLfZsOha8HqdgSDCQg47t7TY0oVFE9EWTxk+TGg3nlSgLLScpm5HJqMbrml+dqswttCOkvAZbNQNDqgb+6jcTa+rj4tMdtfZj7LtkE3gNArvn2XkxDwd0vJXVt4i4ApOYVALWWMhzkWKGewcTwhpZe15nBh3amlK+5FHqyENF7jBDsus3kdZdAfGgXKoK4eHdtL3aCp/HTSBqNdF9aUl/uXa6D91dKxP91woh8jXNAnQUUHiclUm0s29x3TFKgsSDrZPbx3gsWGL9y9ljkiMKaz4z7pt25gDNW3tPaVGARM0nTgUAMkzizvJur3CDoJ3D7TioMSXXMXq9wabM2hjTik7KLAgB0A+X1f6ABYKUQwThfSPTzcRf/dpSV+TGcEWQDxk8TlZMZj22ofKb+vU0vLJKiC9GfgPPVzZtRl+NGNIexJ5HTp0q0dm1GytqHQfNVl4NVdit4XqwQ7Z8lGSYs9XXlG/vGIxJv/6xZ++AG6TpVIl+wMnZSjfnLv/MrbX0zwi46extvFfXgEvI/l17Cc+YcA35IsjM6blqU6rtB+IwJe6ZvujRug5NTZIwaNcBPLMFcLWlsK4+KlacioEATc95qP6gJPb43hag8JewALwGqh3KezhaaqA8Nl1oY69UWAwELkF3H3dYvoxof922S1Xo9RrEw8EjbfS4nkom9141oeZCK3aAi0Wh1zTOFbp/yev38PC6LnOspPojNZDFwGD2vrs+6L7TPVWAsiZx6I/Is6rNkP/+WsEZrm26i3WEwnyyBToHzCsW3w6hfGYyVlIBTWHP2IFY/o3VpzM5BmP9enIwmQWfxgovDNE4daA+jsou9htNOIWEITe2IFIy9uq3+hg39MPdlRgnpXhsEL/VsgKt4t5M8ReGsIF5mGzhH328yLSIo49Fy1bAP4+xTN1jR+4h9+y/CjouldRKEcvSRtqgHmC4zrSTN5u6VcVJ7kfZULms3Bbp9qMoIgoyA8H0ouI+Y6fohogls33vFHSoxGs43dmCDY4J98o0j+zH3NRCSBo48QohbRuIHf0Rk7zJ5pXf+/Gv8bqtuxJZQkfiDUQ3a8f6W9E1zvaQRsToLjAviiCGD7q1Ev/xqX1vdq1mOO27aDIZkKRRNLoOvzmHe3tyRNg8fSPj7F0oqT4Pj08aiAPXKaHSQtdHYBzWhlAN/fyxl7VPnf/mBNOBnJ1Z0ui+AlIuoKC5DWnfhGDEW5rPCPI3SyylJM36YCgUkYszkyYY5faay+mT//GRFdfg3qyO+JLJ2IKb2Mi8MUM6Qs/eyIljELE304HRflfoj+ycxUYLNo94DAzB7H8Z1LXNPXtfRC1Y5lBNe+oebLKWo7E0Bj35bVS3DNu/ksUk7Xgt+5l+sMx8es4SPxlWEl8lxLI0q1Gvrfb2kfvhpu913EjA6ofGonDUVbrafKSYZBVnnexeedQg+Lf1Ka1FV9cuQmc0IXtCpj/jnjErjM6bOrqDUEZJkaM3gXbodn22CcYBUMSufDasylhWH7sfNIW0ypw1zVTf5MVxZDbGXlffCsVUc9lv0RPOHl5vSq/Q38S9cDuY6ThYRSCskHds8+htXG1/9LegqrqrfK6S2Qzp+5qisN9Xuu7s5qLg6t8+TVzwy+bvklNIXyiuRISxXJVpoqz5Sg6i+hPX1jyFxgX9J2v/Y/NgsStZV6yPKaHHd7rI14z1kQZv7fUnycvPtJoR2MqRnQogpN7BY8N6hiGLjE4t6DTucQI90U8Bl7bLgAW679xlND+wlDjCyrmVrWQ8MU3EZWzKJ0HkxKDYee8LEefoWxX2t/rwxaD7EQczXW03+4txlGvi6kzSX/mwnUzXodq94cRVt1QxDYNM9GfCOgzdyXbQ4CA//1GnWiQ8J8GLMr1zPtmOGnfyVZ2saBdfyrcMbGfSeMJbqYBmrvE1mQePgPpvLxOPQwOBHXMfYU6b2TI8mpK/l+KIzfuDz1O6opyuL7DfAvStMPTDOmBEwyjK0Fi2wN8Z1WXnT9fSYpSUtmR+LioW3tsRk8EVntd2Th/V2Ni6XdYR/jJnJFKuDIsmDGPKZ0lX2L4UZJgubmt4D0avyJgn52AwYjiViF4XfzEXOyu3Eh8Is9Hz8/kAjUB4oCl7VL0eHWlB+Ld5NY9TZL+putJgDSp14gEQNsNJG5eZBz4B4heDQcA4d/RovMZB+2Eis1sVX9/BEUJgH9TGcUZlZyqRbsbbHT4wBkE1DqUdGF/U7xl3ui9o2tAh2z/o6YWTID14TpJq55xO0VlMVC0cY+bkO8btIqruNYg/LwQIR0TnLiZ7n3cNeaRBdmqWpqMtlODNbsmEDwnxtV5fXF0SzNryjSlKiH8mgW+L/T7l85zL/z4i+W99D93CLpzqC+3DWfHklQire0Udhe/VIFXNt/AW11lKWzlS62fxiLUfhA9lIMq48y0jQktlVOXYvp8AaaPYZzse5/ug5c/e2QdWy5lXERs9WiC/v088FV4t0I8clFQG7vIKpQBTwlEUcYELoSJnXNYLpXHbnjeb+MVC5PLLH/GyaYRmEXr7MgVPDC4TIWvRlYXD9zA2spE/5WIgliaibc7giL02Q0oCex3WhvL5+OmcxGrS85CjgbAmjwkCS2usC0At5mPq4YpFH0W/qQuIsI2qoXlAG16ICJU364h/wyagn1CVUQEn0h8DwiO4hCRV6uuzmLnsxPviqhHskAvPO1R+8G2TH48vsPfkhn38aldik1RBCVt8x/4KkVZAEktaZeKspcg87bkIj+Qci4mql+EazhO/hSG3cHIa7u8nlDw5uzcB3C5X3ui20MxOWBK6zEwXvwA3gN7n24oVjTkCAnWg5Bfj+bFb5Tl1TuLT341hANNxTGeojpBBDNcA2tjk+vRCpXMP95s8luOgyZ28u8NTF6GbSTZ/wKxN/btxXRuVMCZpLcpyJBacKVHK5mPKe+tEEuY/SXoXK6ncPoNtU4WCxbIzeoS0RCSVC9Lmhaepx8d0VIwuNSLrP2qCgCY+bAPb4mZK7h6dxPa6vifD7lD7fFWO7POiqih2GiFmOqYdmEAeq6g8S60lN31FxgEyG1hCwLlRsX12F4NWDCdK5bfLNhqM4i62kUbXpDmQDlKS9x1fsIVAWQcZwGP153/ioG778bsdGUw0k/tg51oF3QAODA/ggMboJSw7ctUW1R8IUpg6uY17fAhM/fW/zGYxTpR/YWIk6khD7v9WJkOvPvMbstmzzwz25pg1AXa7Hw5JgGZS+Pr2kfazgzwdzn0shLKNG6HmEsE53iAWVEQue3HHV159A8U7kxv7mgp/oTzHQfU9W0gsChe8UGs4uf2wfGnnO1CjTHDN/wPNU8SsxgmwLQKz73P/bqAfESG5TQ3G0pn1w6gswgI6mU/L9v3dFfm9lE4wtpIzsxV5aLu8rHvFvV9cyhQRz3Gp5+l+3xgjhZKfJq1d5h3kIvut//x3GaP6X5KIJQn9ZXXSw2m/Fz+XZl1uqAeR+Ht9sJ5D6wz6ZInlVpAbKA92EaNABB9nAfFLevOAMWTXcg+w5q6AK0YP6bF3Bkyx3NwjzslgY33Ua40/1XyfyoSiYfmfDyE33bA5b8wGRx93NrqEHOlRV6gDlkL7+nW0ObKZs4HtAwwQNXlgFtGkaNX2KoCM9Xshj2bJUG+15TfLSmsFWf1o8p5FrldS3zEBUHaXOzRpO/84Wj/Uv0AKwDsBKfjWwzOxlDynA1Yo337N+xr7N/KH5F+H3f7x4Nuy+Bh1Q4fef3uO4IM36IwFVbghIWC92B/hdbJnfIHkbnKhDnI7+CdYsWEiCr0rfiyc4LcogUtjM1kb8H8ap8YXyJie2AKUXjwfPNKqwI/kL7Eu6AbYyAQWAl8mEwotUomCEXm2aEpanK69f+byREGppiURoFSTVOtaSiimSVDlzQiJwjlM+8geEeQhwcDO0Kf5/8x6jMlY6jBmf1Dbyc/B6f9zsHaUPE0F5HD1NbKedSWNdxCp2RRG/Gm98AzitdDBF0Ea3c7m8j9AVbZ1YJeG9KRhUlfmdopxBbWwoATgDr15q5RQg3vpbKcyuXjzP8skWGhGcaERFDRUAp7JEHUt/Y9yybBOcQS2tNJT5t2SRjmlPQs6CUYligNajuyEztJqf18UYAioPNMDD9iATvjTqe4jJd51h6zhq2aOuWIUlPBcG1EFDH2Erm5fe7A9oJ5ON7Iuw/XcWO5wytlbHMdRDVWJv/xAYY/u2mvV9JvrcGLgTHNIIeMhBW5cEt4Z5MzEKTafMNVMjNFJL8CzbLXt9CH0md092fI8JtkGGnK5mEA7Rm6tik3T5pMoxGMfAD7Bhesl0T03wPRYRn0vgeUN06d2xeuSUA8fe5x9BJ4m+jRRQiSwXTDqMTEdWP+xgSdDTTIJyDjLSnWTH+bAAwKBwpbjbyqePRZ7oIEXL3+YJIDoeEEuDQftglR65PzWCwMzuvT1QqnNiB0qJKGnVtw/R63YGjMh+u6Y+cjHILXprKQFShRk56AHchgz+ThO0lTkeoxKhBVLjb7ocGwqvrI1G/964QIXsqAF2Dfh3WYdPwcHK/v5wKlgLjYCWY5sJa7vQvk4Ac3eyaEOf/Esc6y4By+g8b6LdXoZv/ScjC51JFi1URcSzMp70k40E73Td9IJ5RIOoBO0K+jDV6I+2bdifkWD63zvgRFRGDhQK9YTSlRxH8tCvCFR5GW6Ivfs+A1OpPq7tashVL4N5SnfTAH2xrz+7JpJHJQ8gKOuvFwPqdcDJmp2O5mE30isyRVXYQkV6kZdaXLz2joR9VsjYs/7UMjnF88pVL1cpYVPy5hO5paEtULOaE3NkYtk1wP7bDYfspvvZljsqRHieQUO59ZoMXv+4YACSYWW74ZPrVV0x9dVRteT5Zowxfb54qShE2tuHpIX1+A8Aab93efylRJjrHMAr/r/9XtZBDYtUxmiM25TqflmeVaWdWer8d8/AvpckOegraT/xwVs995RIkTklwWWW/7shlenSXfkokYUwnjBehFFfXWvcwIC2RdtpI0q3oLxQ/LFGNwLz8mjqnaT6c62RwuFFlAqP17y03KQPLuwe++TbiMF0rAlJPQ9zj1w0TCvJZgJlpmo/MLctO3IfquwvwVeVu8q5eN2NWJfrQADe6gbXIGIMEvaJPkNpsmpvuJpoiMcaenkF3BcwVK3fJZ28IZAsbIp50YqO4UoYxY5tkgmocNg6QhrKA0BhfeJqqQg+z869T3y9KqFEvKn5t+VZciTc/g1HR2ofO7EToU9KWJzWEf1MsrpffJ6GFfx0Wi3Nu20wFpT1xKWKvdh+gcBO3JsZPgrFtw5pH1ngBMjagT+Yjb99diiaNVMIKtNhNtMfWOCrPFqSY7byf9CWb+D/q+p1H1KUGHcmUYAGEC1+N8CCjxpMXCouIttlhh7N6+YBOEKcPWpjMnucRWCCbv+HZrAQEVbjlMit5/iX6BIUz6bbPZcjTRDh1HMsypMBUwPBv7cLzvob8L2FTSC6qM/4mFe7gdDzOWMFYjE8+I3AdeQYuoJT0xtzOc4nFJjVVuDcg6SC3r6o6Sn35upowUEbZxSNOyj4Zdd6GRzwBZFFw0Lj967gtstJ2fZ8bBISgVXbSK/I6Lo4BgJiufZjlRGtElGpovNHvwqQd8DI08kA6egduDG7LwkqSvzRioNt/rLJS5+cy6cNCEvqIak0Ca7TZV/p0wtXBsmORESULgtHDn6gHY/QjGp5IP1cytkhw/QXmVsdnKWZBJnB1RuiSLup/vMsPx3vu2haBS5ghkPJpW4VTmeVh97uxthu9MO3UdcHSY0KwsA8+s8yWzTtbUYDeW8wf1lFclgHmYqEPSXheXuLlzlGz3QjV50X8UgiEUzikhiL6lGVssgbgrXtUkpJccre2oxGQJapY2dqg9Kjj2tMvBEU9U7hly5ANMM0mws+pEcMo+X+zUrIn0FKR/e/iAKQ5yWKFmvj2oi7OZyvIBxOhMbIVdYVUG/hvYA0PxGWp1COYQ1Msvwq1uXwt7wEtKX1N9bJn3GHRTPePSHuNZijos+07ro+WBavf9Z+qp8xwwtGpSjxKGd8qQax/ZYDRarUG+3qc9jpfHlcE+l8LNI2TmjRSmMCcNDQvMgFz9VMNiNYbnkrIP3/pgvlz98L2mYsLxzKEZFzdtcG3Jm667i+EacpL5sFF0Ua/kNI+JY1l9irDLJLKRJEyvmJq97K1kjVHe9i7YvplMpzGGhVI3g0spOcerkfmZ1sHUP9aqwQFNy7+eiJwdnni8qM8TxltfzMb3wdMua/hDmwpCjqVOWUkE57fAyUJgqTLVJrpae4BFiibKBDWfEpjF61sNd80VFLyqBAyyGqt+RNfuqpvyDIEdeCsaoRLm04SvwovOhe+ZJMw5m+Fw2zZPa4xRWWmbfJqaKO2IZbjU3XKvwWdzdEJH4DSAogvOvWE9kGp3rZ9g9HHlRretUlX32+blIbOZe0UJBY2VL7we/9r45smsyCVarnMWH+r7QeMkZ3MacsHvLGGTWiWjlOIpn4rAcTEXcIaia4VOLmxlvEAk2hL9iBxX9+cHhhJka6jZLKAIzXmeENz27Um3UfpaTA5+c7oLOn76OLqiA/V3WsCRy7NfbuRy4CtPsdlO8hB1tDsnee/RmBwsH46za16a5nchReTQuVGX/YZaOv9v9chMLMFFzH58S6n0VVtVtYnm1gBMIBSnmgx7jDMUeasMrMkFh1f+UUn3L6ZT7pxWJNxu/0gyrUHyEh+2ZGR52M7oTcxjZaSmRGAVK7m5sAl2o//VlMKOw2DRyELmfcqvqYyePMWpv5PZZt/DVLJSBSXWzj86tV0l+QtLWBiCoc25kDv7T7RoB5eU+DkjPRJCeQU1qU64uJtf/+uAu7ybwjja1MHkT691Yz9xMwXdgFp8xjpsrfq02TSElZMPlomxb4w5j87NILcTIAiZQBHG8qR8OnO795cbtBYfpzTfq3mmkdyu1qU8tTU8im3a86sPsTzAXqhRm9khfOPttnSqj3x6ZP+RYyemEdpn+sSZyjYlcYgaAWogjGPvNvUavhHqpiApnP7RRObDHkdPfVh3vkdYlYvf6MkPdNInxjhr9/3XyZ+DJz/yRvQFkfyaXzF/+gdgETS2UYRfsxPOPz4otwwlkDj23l6S4MDvU68YoMro4wAGfGsI2yGilObgRXxZbVRmqR8HiaKsI1uVNNDKWbR0nmfhwNi7jacbPODaoEM5VJcVdaKGqIPKs/rE6TFHZFhHWvYeSjFPDg40xZm+0nUi0+QVZKBfHCwb7NA1vRJZaIG2g17MFJ0NFra3+4leGGhEGS7QwuI/j4tjKK2A758fkME4Hsa4H5J9zAXlLN88E0F36rWhgqmJAW0KdwODY40MunMoNBV/kkK7sl+6LBwKt0/kRAq4g58gAlwHpnmyInCjNaF0DZQNeEjy6UB9+svT7dYu5Cqb+t+CO1z3PW6MsLAac2TrYcPSi+DT2Ad7XSJSfunUIBGZmgQbFYpC9xACSksdG6QPOR3JHJRpmynDM0DomPsXPhVx5VDSX5q9+Da5VI/RAZSs8xE1/Fw4oVq2oaQsfT9YIulvhgJJLElLVmOa/c/l+Wj1FCSO4Ao0S26NoKY+0Y2rdbaYVmzhsnEiq+ylD63efl39tm8BTe9mRIygnJhi3ww3XpI+VETfXh9PAjPDG5UBgIc6h6BYqC+GRX05+EQKdBkou1tHnynTKsHAUmOGv+KH/grFb67+JuSst9OTnnNj5Q4fgqyPPAoA/quGEVF8PW15+9BRILkVOLqhBbv5k3EtVTzDD9Ab9AkIKQDE579wKjiq3IiXQ15mIGT4SjPfgx1WGT0uUSFjdrYzqpEodDsG5TvMUqQYTlWpGrb9JMrK4lQmSxtuOVbziBJnyJK3HmZBq7UgDcqB1/0GfVuJCrRi190J8VJJXu5EPEvNkKQMAO3kALIOGyf3XOXsMNSx8nKjpLL0MTWwVgXPkVF5u0xTlSx37lLA3yjgbxe1woJlhjHPIu54oalmJHDkIhk6mMpwzO5tYgmxz/kA9lyo3USAj7xp+OaWae+lDDd5zZtYPYD/xmEvtatDLvjq31oS1cKiNymomAmPetnTfz+pa82TZQq8ovjv+4vOs9gukzLMkgqKl6GGvjNYs4sYlmsn9zBJIdO/vZrZTcGWUv7tTef2feQtgwzx5pehIupKtL3Nl9ACMcaN6l5wmRQPP7Tg0wRnIdCKouD1nHeAf5BXHTXZcD/FI28oCO/BJgmnj3yh2IJy/G0cl+oVbM2ybZe1dtU5CV+jHBg2vn6muqSKTiShNf6rDbQ2y7lC5lO4Yp34aKXwJ8uap90tD5tAgbKfHicyQtbVSrMiWCJIaUlgMIMBIXAb8EheNk0PJ9IXPETVgjcSLblzK/NEcYThEZI1GYd2XeEQVCJKljqtC5CbF9+oZ7sZCuDaTqVFdTProlCgbd0XFPoMtQWM+duMCoU3f+l7QX3t2HNgI/33/2mA12Uwm5gGcjTb9vrMZunXKkRGPXqcMUT+rv/lTPvjDruQSGD/r4zyJ2RMF1gfuFZMaZDyXQHru46GcHGf/flhF6IVelud6Z9MUrwoEqwFCV5dV+BBC5+NTAsE25/KNJKc8vGPgTibZIxf4CgbpiG/8/na6/7va2UyiYIznOnwziwKhiNfo0RqCXYvBCUC3S+n4KACqCfrVhHwluJghttefnjGvqzrulhT+Ur/cji6UzlyPt0pZ+1mZkoSmh566Ildq+qfRRsjKFuQmQT6kKFudzc1xvEA7g+MBil0bKhzqHlON/lRftcKeniZyItF/85jBLa4np0wb5ITcvAtp7xF8e6uB14VXukrs4JilazlOX6Pc15EHc+MmxU+dsoTjRs3kClVV38i/v3N/38sazmO+iTpQGeTN1p4NBOK5+JJCvw02oIEUw4by931dVgJhjhCxq8Kjp+zZXRus1CeYywU0QQsmS+0i6t1xHBISLDNs+8bF4TAbQbssY1PHe5Op7AiQNeOO4PJgyfI71U/aOmtOBIVqY+jcYWjRlVgy7CbkR7WXV/qBlP+JjBoQt7ap22rEAv81Z5ryaKVYPHtGe8hOACkbtwUf0l0Nyq6yYiwH2BHwKCXwUMgXnR9gLTQYA1GJQI+eQA37LNG0iapEBtwqdtlZISENdIT+wbLsEvj56SNA8+7UeoVOhMz3iai4iUHUM7o+el+PBxy+uKsxsmEyGfBbMa9IXfN/p7MDS0m2qoFimf3NNowXZLHSVF6YGQsWQwgHNdGvviifF0OErgBRZeTX7GeIlWmimfDXPgEHdRldETIUtjmH/Ipw1pcYNirNS6ze9uGLcTwX9NEAvKOpSmwdqmKCvybG0jOFdyfTPCrgHCycfILhyyoVet8mLTymz7bF/fvR9uMtZtJFotGIqDXnB7TVsnZKRuyka+R5JZmIkhTKscOmgqRSX5v4UNCKnQjrO+SDMyzeLPTsPeIPN30r+ASNyvCBr0G4/LuD6ZaYeGX0ExKoXrVx+t3suFgcFscvR7KXiCy27pmhE1FL2VAS5nm2mmOKnwff6TujK4WO3bRt/oJy5QmRFEAveFohL4b/8uGn3sHTWNKeST18elK5s4gQdZfMkeaWUtaN3N4d/w/WDutY0yZyudgknRJYSV6ydyv5yBGF1AMaO92Ifv6j/Qar4vM34VsDuCz56PRsz/IM43mSdtoDnNdw9XZp44bkAcJf0/GrUjBqE4BTba9EBaxesrns2d/FoGlIFmv15Og7P0F9ZbygFU8r9FogQCYwc62zAC1+c2q3GkpUizX4bdGJMgVx+7gs0u0J3+P7VMI/CnvejHPCrd129c6rgfGqWUEeTHEhFNl5wcmvknoXqxFAKOZYKyjI6/foPSnhzMfWOfTL3fNjRvia4SoQfx26YTlgtvpMKU5rAyAtEL+I7UJur1/toxCB8IeryuRq2C78PAIvlnOjKDjiQml1dZ9DhvkHpwv0O7l6jr5ACJwVrhfhkxGaSkSJja5Cowhi/pf99kJBvQebaCK51SYtenNHPaKTJaSibMCnZH7AlcwEzwrwBCZUpBVrEkNQxF+YRyKPFzw0usp7PnY5j0yo4AoDqZy8t78gPq+jIKhRrA4kLYoI+1NFzM+lCx9MK6MU95uSsmEzEJ7o91fblAs/S0bM+e2vasF8Rv3iF15a6G7tKp7tBQAX5fzt3lCY2M3Qi98E2nmU3l9bF4MSA/xqcDXRReBcnGNI5QyCab6nNrLG6NkmujYWVI83Sh8B4RUiZrRMYNScqVLYy4lqlAmvbGTxWO47seMjhR/a72/BvQFQrlhvRVFmRSa5g/J7PkvWZo8g5VRGP7YwNkSa4tfYNppV/Zw/cB6g+pJchY5WbMYxNz8TqqVCRn5Ai/eufcUoztmEfGsRFXc97bkiM/8igTjzCYB/kyiNHPIsW/p+StIYbb6/PU0uGoLZzrNorRekc/8r7yqqy+D7Tu2uuoopgj6IRgEDh6T00iTka9dBpNwzL2hpqQNOy3fHBKepTxNqXE49eA0HmrWzLvYOC/Dc2svpi/MlprAp9TFY3wXIj36ip5ZLIoH/rVFXNhwI6RORmnKW/iJL4OOiRyu0/Al0Xn7cpQL4H8AxIvUbvAyGnn//Hu1Z6OtltuABOYH5oRYY5gIKWg31c1ocGJBfwPP4D/Cnea5PCx2IVFwZvmCNdc/+BGnCTwtS6+3qrcqKnuzFgjmkvBeezEUO8TOIDNaEH9kvTnvYlRDuao8+EpPv+osH/wXsfrIdhemxo0MgN2tdMihpzBJpu02XTaX+aLSN41yxbpzSWDPWc2yQi2g3B5EXEZa/WIiVDher5WSFoEMcMBzieprykfXzm8AxFHVJlRjGTnZcHQwLvIENbWHxK7zvXIucKSH9SyMzTgMTh8t8tgmW/UFtECD1tb41QQsWB3z6M3dgAm6iS3EabTj4fk9bHBuNC/UrxHU5U4mGOLgcz4McWeAQhggX9N4oMEgeD3hF0LbP5Va/p91hN9lgv+6Cj7Z/M2n4roCKkWW+kIDlvPKAkMR4jfkP7Uy5DCtcoCA+X/XWavvdpJaBDiw5fo+OYl1rYFQSpG0A7FmwXYWwUzSYZlKh8iWCWXLvBp6g6uLyyWArE2C0HPpsCkBQh9DyZIdqux0ks+84dUSQ7zomvJ/kcThDrAjOnX7VzlXgdZbiuoDB6YZKwiAG26zn+r0uHdde0iHvFRokprslzzBmg4bvqWnYUhYq5PettATxGCxbu2xT1GK7rRnS9CPNzeSkDUnvVEDx3jvlM9eowYQieW7wqTia5lu5tUjWr+vK9H1r1E95iIpRygMllGPdtn9osyMSvtK1LTiUzG3gxnbBJ0ZXkSABL0pJu2qq70fDZIFERTeSqXyVsrQ1Yu5Usu3OtPV1x8K4ctjHbpIg3DVYtnpzr6O6NbNoJzkuhuZ02OGKHvuMOebSVwANLW7Os2s9PJSkN4/yjqC95oiVEWfNoT1cMCDbtOMn82toYV0h5mqk2LihR7CqLOkejBbZEguHuUVs2+d6SK/YnBliDw6zHj0kLpin6VTVhbZTNE0X0PW7/719ft9YmemsEOy+E1byUZ5bx9h0MuphJA5F9frZdNooZbkCcNe3DR10IJmFu8BNpZbS8P9ACu5Uwgt9jxgYRxRqqvYvaG/pP8pwgXktQ6n3fHK3fkfVSPY9BMMJgBbz4GirKgbKzZXqadVatOOjpC2QPMaWsDMeCZ/Yb5B23or9Lh0gFUAq0utAkqZW2H7UUv59uOrEEd3+4j0N9VsYj/GGKx+Y3Vxp2ydOiNOMkqwCIap8X51MYpEHp7QrXcUsxlhTUU+78zqj1E6GFTyTc5VYSduVzUe3QzS36mr912z5/ORvxKNzkDyj7bnSWfyLjbW9sYtffLDKExSMEjJ1rIysQUZueEk5QqNi8rZasjvtmizc4X1uaVNAoXOzWTM6AGW8Hhq6S3iVMJrngX/RoNOgF6WsJwD6eKwoQr0Z+0UbIGLb/VnsDhlsZSmXR0BIT+okH219DopfNRiDgY1URgbqNeHPzqFs+FwL27zoVRg/3m9YR6t1d3+PLV7RIEpvpK6qpOurqF4Sy1I+nFK/TQesPjjgFL+7id6k8bY1VwKKsx/lL9LeOvwuT/zM4SCigmprm3YxZd31JZkTmzAK+Za6AXeO5ycPsekfUp8aPOd/bxThx4T+ULlpsoewtNKPj04vd0VvTxzA7VonCQgdocrVaYqS0h3hhxHXpHncYZi2olwdVEaHBjop1HJLxIN5TY2gwcxJ36I0wSes5fDNHKuAwv4/2dzBZfDhVZ/LVv0lxSU7TQHkL/ciSMJTgDh5Ly8h5JKI8Uq3IpU6oKxOBjnXbfFPVL/v1W0LxYnxKfnRpIHeBvuy30AWShIG1JrEKXdxU5ellWMEslm4rENTWh5i934mkjiK1EnYgBWOferqI2UMCdm0QIrqB1ubtJ3qhzPn+nEMECgmlDYrslTDpBIeVwzTz+x8LFhFRQeWbvr27Csjds2ZdNAPJ6Yw7B/z93h7enMiMLUVTeapCqpDxiEGbDojqweFd2QUp1kMFcsFyX2ySJHHEYOA3Rtp220W3Q5QnH/cWr6qbXIkfv7xvPcvtSK5CZ3x91EEnUw8mOEpFdW+BReLaUFxijNtK5dk8HWkg0ah+bNd7POR8S5c2STRbKiUFjUh5bV4SY7yw3R3MGWsz/WUoeOny1c+G9Kp//Qybkvx0Owe2uWxhrvg4sVUYyZEriNtwyPMKs9QtKvpITMNySvVYaLu0jqED52SVIsYGVyRrS6H3zHzi2eJGHiQjq0w9UrDoBfyf0s6mUmHUYtMedPmXoNIdtwT4IyA+0BP/nc1/lPanTjMpgExaNPEOfC8S3Rlht8FN+RXOOlSbjWKFOHX5lClqgW0FaAEfpA/aMI/7nafaiZTWS3L5zTJ8wLeo/Iw+NlD+ZoIceJ6m0EJeDCD0w3Je2ln+qP6NVhK1hUWi6cFySxNNN2yFB3A16C7QLYS1A/J+7t+AWjUBiA0M/6LVkRpLaip3QrW3F/fPHSXghHxP5qab44dJykD4iw4DP2PqnHr2XPr/y3KaLfpqXffPnlXch2znguwhVL8ckXDRhKK/Xbufaijs0ruXluPJ1EM/vxkeEZdmPMBLIp9YeInpXtNGhTdScTjpUfgRVqtYDaMrJGTtIWXgaJKbYlD5qt66f2WI+JkhYrAdDKHbuRnp3JCtdglIHlO12sMBwGqd53SRuKCJfSxveHqWOwVEc/12zHWyZ98W4u2vRFL5QwW8ra/Tv05oOw7EioARxSu0HHP1eN0LiDBKj6dUwh1jHR9FKFCFVMNwt8qvUXO0i+wSJxjA1d3uDbFjZroEYZp8ucrvlZ97JAwIprgVab/wf8Jtg3wiOONkmLmPy7u75C1/7o2e0roGUmlL6PALMYBHqABRyjpqoTFem5nKKASLKvyahNS3W4Pxpxgcc3pvs2Zf9r+RXWvBZvR9NqeTCkTJbtqHoVilhDKC7CJrB8zOmvgAvCjSNG4rBzDcou7hUBX8TucTy/kZGtfmMifhzzaWFYIWwoj7Hs9JK3o6+GMdYQs9RbZXKoHwKMjoAMJifEnA+FaJuqmHzTZU5QcCXVemK/5huvZVbRAV+gSJuj9rCzm+eyK74+nr/e2TC5SuBhPu6NAK0+25uQqbRz+N9JWWvT8gbtXMQyTO3DAKkITNBj5Z90ZedjRRWGJTp+7r6c0EZdWwkw1mUAW/xMONU7wlXWz1EL3cC5F5XbLrcVv2TRvWiqrSEYFHvuEX3nSo2IKawT1rOn8wBTDsepauHqra9GtM32ayisoMIBeVv21JtNhIs6ILlbw5WzGoCe7XZaogALq1dycV3j6Ed3bImszUei4MlatcZdBEHQ0WUHYWpDwGIF9ct5n9KunLawxWaZfOlyy4x6+94jAjKociLgWRYPINf+wWadjk4MBfM2Nforjr/k9sy+F4lBZS9GzLgglFXD7XwJ8yqLmDdGLj8DGMkQbbll1ICjFI8DbDpTQhdJ9B5GsKaidmAoh4dBzy/yBKX8GuyfewTb6dOGm60nM8ZjSr1x5o7hz35BTAeReo6uKTIM0FwODfXJL1iWYgL/2cfCY3Y/P1ZcKgvRB2o0l7PBbzIzhAJa50AqberYdUPAVPHmoGDXLYEGZKlKjIiHfWnElQ23rhoRo2v1K9MfCxqG5dmwRJ6F/Rb+v/Gy0pLXzcoGEnILihITXp0RbA7k0iZr4E/L6b+83RGBGIJjB2uBYl1nac2JNAHAABAAElEQVTJvGa+aXGq6jFLYpeujcvptIjstKFHGPytc9oVtP5UxbljweTSxna+8ex42nmj2zwXFYcYq4XLodpKuajcyKDIgIVoSXOZ8LCP63tnR1r8vf4J/8WNfCQqiHV4BNUxRo0WKbSE1ZcedKzrO2tCgkvW1eZqmk7deLRnz7cqp7P8gGSiiEft+HcsXib7IsDm0ljJ3/uwJbpKxuMtStmPH56tyEGMbX2qnqGplqt+FC83m85K2JjA16QBB+5mFYTGjnlbZ+z2DS/2+EspIvPq4/KvdujDVCA5uCUUFlUl+B4/gLvS6VRGjhvLZGcico4JLyQJgC9djTTiYeZqUCUeSMOFoxIVeEe5oIsAHfKqGnR+VHTJOV0IuYVrbJAbGEGsUEqU4s3aKo5Y7cgvd0cFkyy66a3/leHfFkRYQC5Skfl7SYH4f45UzK1ZV+96SlW1kLjj2rvnhKLsKSWj04XFc+93DRmZJ1ENjfs/KsowWf+S12iX8rpKRA2ypChJcC1fGC/Q2oOeBjA8VUFCkb5GIn9wDh2NokZP8N1UO4QR5G97Z/map1W7TirBYSJuW2yDz1i1VH6DGBDaQJsgUJrs2rGV17M3NUA1gUYvIU/3o7OthWfEN5roQYs6iwzqL4cbnGXHiszLBlLcVllnI/w/gKoz8OmYVtY9iT9vlJRKB3i2+ihvHD3OJoK/UEAre/4nQg09yA4ZsygkmWgMnl2RCmWB8ZfC5LMCzY2ZK0ULfICf1YmEbssc/MsMXhAf0ySGARlI+lK2DOGIBjU+Py8pplJLcTIgwHI3I/2I3sBYbuXglayuqsAGJXl7IH6QZFidDVyPuVS/htD9xhD7RWnCQ+zt7Rt+5lrwSSzbr4SlrQF9rzdqiGhffMnafkqvYop37AXGHIqeml2WUDw3UraWgkt0fOY+9Z0ZAu5i4OnX0K7kZtM7rLyhLsE/XAOdYDUTL4Thuo50QZplxJWD+jkBeQr3G78kd5RPsCMSKdJX+5tApGC38Sjqn5BY25VNdK9X4c1BIBQ1zRUIfKLQSUblL30MzaIaSS55/PE39HuZrSumiQcspdp4fVpYuhD57ff5PvMzqGRzt3j16XLj4N7E7rUgF0iYFOwrzUurtKDopXNolb4qkC2h9ckPFVn5lHMR6+4yvnroa2GJjWIqjDz/mn71Nk+NsKZXhj54iBZIw9VEqc616fpqOv4ht6ZVoqHOTJPEHzzPZDVgKvVruqXtPZVQGab3udbq7qd+jSaJVIHr5NPhTesy1FUY3vqcnUZYj3TRkrn6LNkfbSRQXCXRbJOh6TiWL2kOkrsx5J8CdOtfVEa/6rcTwihKZZ8pevx+5KfB6sujhMO3RZNtGgeMaL4prCArQs6gjCZGwl4bST4SJYqrg1loyRMjdM72nKfw8NKwgyq/DrHh0TgDwOhjVj2f0Np3Ie3V8xG1zLHpnI9iDiEVInRI7v61f9k64DLgMIOnCcw5Uf7vKU5Bkp/zj1bSp7htZd1YH7b1a9hT7iNuLMNl0xSTmx4HtaNuhYL8DJDqQFOLSfA7YwOh2ZaZFsUlpTwWryY+fJG680BX9A4Dbm/pfJURGr357J8TM0mx6I0JB/8IFMu0eXfwDlK4STTfoETU1DZqank6OD57QZgVfHUNs71EF1Dym8iZrvNDeU2Wp7VSkRR6il4KH7LgTzCjcWxKBIRk/FNMnF1sY6jCDBHO1zYIZsuZpX5Mbeu6Wh7yzev3kFpijslISmaz7NziKxNmiqDXEC9ypMViSJvFKOlDCuXn91xkfQZClS06nsafAeK8v7jDuOSqsq2o38IEd+wNGg90HsHBSg1JTEt3w++ia7I0W8FsOt6Wk9yUqgLTuC2S+qP580h2yyfdcM9/H23zw0Jf4ac9F20rBR2Y3WlSiDL+z3Fr70zvn8+/PTIuZfR09lKAtgVFKwIMUwnxcJ7Zl9JJjTEolsRpbx8ZSz2zSMG2CGv41a4kc8sOsqNa6JSV99St5PjWf3V7CrY3u3yBEdnP2aBAKcXYpvrDKaYrsybtM5rm5xKb6vFGpZSM72e9SMCT3HKnRLj2Au0UBuqO+rqSU4flm/XCd5QlhOfeMmoDzn0cyQlH1Wbom0DGT0oK3zozUyl23UqnlNm15pyUlo4dTV8fCfw0dFf2nC/+Ignh4QgVQa98iQe94WFduYVGod/oMfGstSDWrZrZodVpNmcNt6H4aJTK4rEtyWyhhz4WYIeul38txAtFgEzAWBvjdCzYRCBjXrpmDiO5woxZiYG+dThZCY7V1ekKnOGBEJMuBh037LiU/2gQBiAsMihiCt8ZliH4yqEdP7z2YMvMctsNw4BF7+k/qu81os8yU7gxaOhK9OtLlVZPHpdGAmM1chp0vsVHustjFpiuWnRtQRg3TJkiOa5Jb4ZsZ3qrbFeVNFQOWyWiav9ICImkJz5He4broLCfY1sSraaQcFmZZ/aNFtihsHZkcP4xaMtUThJq6jLLcvpIklUa7rAMn+ZczFMa1yKjBuJfcxP0mL2O8D9szkSBc13+rzCpV3ybIYmMyCWnnWTQfYDqoudhBJSCO33Prpyr9wELOTN9NaZtgD4suHJF9DyxsqFfVLnlesj3LvC/h0WRn4Ws0iETn/lQaMf58UUDx8w4hhcFNUSr5VM5tmNSQn5HEZpd9OlwKNWwP32350Z6ui8Shecn3mr/p6HskId841ZAZ54lzXc+wy0NSrYpA9iennB9VVn1uATd/VcSsxmgWSUQxenUzMn+bU7Xa47sILNAvaNEhV9qXQsMNftBs4UzlRZmGkq8aRMTZ79MwccWR/FViCEVJiKb4hkJS9TsUrgf+lWrPSiI+vntBwGFppCU9+f+k76sKvxujb2Fj3xdODdOy7AnKCEKhsY+N48AeKnemyKf+Yh85flQwGh4evN8xAGTKx/gDhPFlQY4+gY7Q4ED0wuTigK+9bzysWIWf00b52qAz/aM8+JoFbTwJkvBS1/r3OwdliNAuTv+LrUPyMgsvv4w2ZwcovvNJPNf7Aqq09HWUBECB4toDufa7TaPAvBKFDAhsGWBCanCPZZBdLh6eubOkw8ODCgNCTTlhwX6i92NNW+vEyAVHmQjlBo9Ma28OGSAcsohGedDP6kGrO9fd/Nc6Lj32z43n1hG30arHDeaUXoCpaDduiwRVMvlTaEwFoNYV/pLETOV2ikXjreslksxl003416lSG7GOqvUklSYfDJRQtMcm3PmNFvqU+VRclyG4e4jLDODSbOXegx6HVOjFtYjCSCBUKagqYPdmvAHaQ8tf/U/PzDmWh4hlP5Yktj34yoJ2hcNck1Aj80oZVx1wkVzW2qHrM2bHOyLfApwJQYaI0X2G1i3aZEieTEHzHKEUvwFLcqvJZi+Z3qbVXdsx0jMRO+qIA+WGEGMLdlJC3ueHbVB7OIE/BPhPFuh55p+tFzBoSsZTd2q2kl7Jrlh6Qp+FtXxRTb6WIvzuRAltABDczJdxNTJW4efBG608sSr3blkuURhpXgf7n9MqA/+pgjLCCoBnuiT5eA59dH8rP4s9jHnjmSzryHw68KiwkeTWCq0GP5m4knfy7fRkJkRNMUoNWgOT3ZV67UzsENIls+qrjc7mc3zbMultmlOisC03pKFxIsDJ0LmznGtIY5nvSJWLVPdTwzg1ITkaFMuHkxMZZJZKF3WsCFoB2O+cucQX7WlO9emUgThBDDrPjVyQqg3sRIEelcRumw3HL6WxCY/+zi7A+Viz5jAbR0pYwvOYdWYOASTwtlIpY/RA3t40SRqI2L3xjjsoio8GIxcobYf6WzxSvkkIlr6NAjL2CL8uozrZTDGE+QVnBTU999iMzwuj1B5+Af/rQ906mFgsj/p253+cUOf+jOmIzqcyuNbrBKURi/n5pJG4WU9/AT4NZ+kHZ0yrrArOhd2HcMKOQus25IX+3WWbZylsWR+ThoC5RJ3XQ8NGUUFtqMqSWEz5IjyTxOAmcsWkAF1r65XZLnYEOaZ9BHe1xt499b8w+MPVKyjr7LkO0QmeS0jWLw0X3JUxCmBz59jgxP264TgFWpeCU3Dh2JCt2iLusiHsK9VLWM0xFm/oTCNBsnnM4DJ8VwiAzaUY28z36fdmef07jmo5H7bHZREjGjR0cmWEElQB4iZS0yKHVoQuJLgFwxQJtJVr7GOSy1XgoNUsZCdzPjIFVtvpZKUpc1eXfJ6ylG9louvtg68IssXjtv4TsZoitbLU4yLH53r4nKOEes7WdvI9d8gLOI2WdCWjARHNLiCghQoox20RoXmLYzYK4psHrdLGJJ3zLh6L9JfMDtA2GIQmbb/5ap32YSl+M5iYA56t2+vsSVTf8HZc00D/XbrxPMjq7+cpJTfWrkRZagJPtmHdLKu6jiV8jLfIQxjU3d9i1Y+hobc7x7yti+UxUqmau2rUYG0EZ7K8q27EGdM6bEqVHfj1ULwVWANxP54GNPUZoQdRn6vGQ6yGpc2I2RgPQLja3yT7s5Z2wHVesY7Wu9jkUBNA7AHSQU/hfsmTDf81ZEa3Za92bFzSsJ4hU0SV/Wc+6MrrOhYmh91dWXVF/wLOKIprJeE7tPOAFFXLpOFnrnhir9g3uNcD+xCZSvME78TccZNmVCE4E+36OPozA/Tn+AehAypNmu3Bhx7VvgHK1Pa5iUiRWcJw44ZHjQCJvOM5Nj8bqQEDxWLFeSPXTW38+FblAunRaKs31lTg8ZXtFuGsHFg8ss1DnCtq2hLE1Q5qtv71EivMYlBBOZMnIhNu4itheLI/FG9uyOXaBhJMJDCfRjdQq9knCJ/h9VFZD5yuLtSCj2iJDyMkHVttghhhHu9RBpzKak5UfI/HhJfxdEHTiAu9desFvXn9dJoWQvpCxAmfW16y6p6LiYRebgTwXwL5aDNB7NieuRHBPaKJdJy4SjZp8knqZLUshdlGjAOrw2DxA07xhdLJdFHFO9/b2j4T6j35ARfJ05xKCXm2zfr6XW74ZDPrVVbRMdldIdngjElDM54bj964F71+ctZDnFYk52AeILhflZT/3O/S5gbnOYVbKSzipfbJzqvshqOPdEUH3H4emJmRZLX12Ys2ShCYGuKBr6KXpRwpRPew53hWAcA5wJbgZso0Mc2A3zPu7R1RwsN0eWXHEoQTWXFsgRJXC2U1sE1S1G9i4Ag1/LW1kAeWoOLu8N3JSnMVFOOwXymcFFTcIM3cq19iasW9XytTHzc0v9H7wE50M8S/yiaZi71beROY3XCZtvr8M4ZmNeSZciVcYt57BLYIzabRGDwQOlYlZErPp9W0x1LiSpU2BIDAKxcAneB5SHd+LeLkdkWzwGvEps+kd0uustlaXkzuNraHMknon8zBaWaBOK/5TXyfypcwi+UjFHokXcTWLdIUJKGTBOufK1ffGNeaOtgjTQUP48hG0QGYOlpnE6vdJ/PrdfT05rmBtO+Kx+WRWAGLulUDfgqMwyEF87V+VWvkMmtLO2CG6zVv16XjBdWf5wGLH7ARn926gY/FPJRbFxifFpJumcUEd6uPhJfiKqcBE83918m42CKZAUrl6t7noWOoKnU/zf1RTbZQ8RHVPB+hCiOTRHmnK6DMSimKCp14EyuDJMO6E1ghHfrnuKoATFBAlOdXv/Z0t1akXyiwaMtuYWhLbDr/poJKJX1g3L7EeCcq5iyGKFJ1HXDex8QiLPomRMsDECalfgRWHZRK+xTbhYhIXMb/9EF+U4g72C6CDs75u62Vaxta0UUI4aKLB7wS/obXdsdAt9xJW4hGm0+1VyZNLQfG9G1Ke1GUssFxVt70cMRtk06+gd+PgsD8/S6Kir4ac1ORTfpCcHz6mbPaO7wjQSZIHmA5g9KRJMq4v93dV9OOoAgP58oo+eYPewcSlfUNTzXFeRaWpWPhqIBgtW2xNe9rJCwkm3CUGr9mgikxSOYcnBQqltvYmgTOEjVNDwBFF9CuFc+1EIbMocy+OiBbzvUNl7XNnbk+YTLrz7+nxqkntX6LXMX6Sp4t4MYKEhJHsUIrK62WQ5WN8L6VtOvYLUKK3oLpytqqiGiheHmDVK12Oe0tyG1dgdXXHu37AQk8WmzvgqTpOoJuYvuRnRi1nfC+IfewTiP39FAo8zGH4HemG82YMNmS2rP0Ykh7/yKgXX96Hun0VJrs3fEwwGZ7oRortC90Al2BLJKo2SWd5LPMV2gp5lD/9DSGg5R5+67Xrt8lQHaeUsNRph7Qk+jcfGnS2V8/lsGYjFgQQsoBKa5YFKym+8whs4ocF9qd4BVmEN/rhYEHhH8L5zo1kU+KvPwxxy2Ge82iuxTRPpc7FaJvOcO2H4ZwLTrGqb+R015Cre67D5oS33mQApfdx7x9yOCUtliO/YMjOEv5hm6iwgDw2uC7I6y0HogDFpB1Pjr5/rRY/yqcj5RjWoVqFBMGq6/4V7s+ci2RbxlafLQy6xlqcAvrKAcPLAXYj6Jn/VW+jg8CLZ4tmk/7Fcg3DzmPjUK0EfWbsviCL30fuSK2/W9Ptw2GOgYSKE3AlIzCQ5gXi8/J2MJYrbi729vS49PIuaPyhqJgQE9VGTff6s9gdw2WsEmuCGShddxosRLYFYlOKOlAWuXSH7KmXE4yYtoobVzq1+phAiilVUeEUwEEU5yUA54qMS49lpeYmHf75iwOhC4glI+WGIBYJeOqpVLe16S1M1KQo8UoL3P/RrbL/f8iQy1R/tz1wGeY0y/ctMocUz1VPWZIYiOHxJT4wnmigmLoMpiGz5zNSmHz0cjgFVg7PBdSotdOI+ibF9zetHZekuJmlA9DtcqO7twdXy6w192fr+mIRK+jPEnVZUMNxCNE2fn/w2bFg+iwcMUcheQ7Y2J7mw0n3DCQCr9nek8QOSVlsgFuGSOEfu4EMleVNP4AM9ugmHoAdT+VWz48gJ38MuN/kjzle7L0rn94H6D9TCKlb0PkiT/Qo39FAOoFt6fJ1jJdbi3mDcxxZ0ZeAIejN5TKPE36u18EFUcFJtJCSgRVcTP7qTRVTSjKyvGHfeJbMaRln7EIZBVCc1V7nhKeoXsxYonV7fL32gZUe+30SoYBhqWA2Nf0tNl/pqe+mf6t2YomM4oR2wtrhK7nZ0M4HhAcnYUCiIPnJ0Cslup5DLbNCOnsUcCg4WIyodiajsn23h6GxUKpu8nz7Vkk4ViBGUAay2LSGBp3AP64TX4LwCIOWP+ADVdX6v4OdmTGMozv+au1MEyXELdH2zYgTevmIzUrkgmKgC/KfHpfH7DswmQImVgnJG4GhdcGwhjy0QhiMjlSswArOqddCEKi82220G9OOOYENyiCFrAibrageoF0uSLZL75w2v+rwLfMFZa6VdVZ7SKgw7uNAyLATKdfIYpjuH9ZCK+kJWhbOB0SAwro0qvWT5YuOOzSuI7jo8olyuM+5RAz4Zv0QxmcwEfGus+pqt+uAdYN+VxxYwl+lLzRMz3re6LNBAJ6QmDDmbneSMJf489AZ9pXYW7QFhsRmAWqlsmLT40DcB7rffOEB3cI35thOKLt8GrD5iLTuPGxTNdu1A3Gy9U82EYAB057YZ45WiQlDQwJfGJ0P9sWX8kKiA0PaQekD96w8CzaQU7ijz7qJh2HY69PFLfDckTWepLUrxE2FljhgdC71LwVUV/ZwR7NFc4LbYDmsC4lrKfNAN3gGJhdaMFWd0mnjEDxQlHcSDcQ2x6UofeXsns0i+/ze3ozLR+vwJzfd+iIeXjSYx65943VKRq3dexERfyge01KTR+wnNN7+hGStWsJ7NqELN6ig63f67cGypSn0Z7tzXXnG9p/122Eb/ANiz5b725bTZaX+l69A8ugCbuZteBQb7ij/uL7xOFyW7kTm7U44BX14EHgMZLLvMB98nDGOttE+J/NUeEuuAqJfR6OPbB7V9+/tb1t4xizIAbEPswKN/WeMxwmHuSr5GZvgEoRzZbmNZK9d1SXzsLNsD+5o1JwQlBgdg/18rYR/OiwqZV264LXtaNt80ORDvE7ZUSZqn/Fykii3+dQ22wiBR5+6eifvmxRVrXyoqC8uCCygG3gg6/gte70zptltuKcq+2wCgZQkrYOnAhiIUTRqs4b388kiUQI6r4LePV4TN7sCfGGm17gDpaFPPXudp7T/dX1HY5dYduPYYGJdUdoGBQdzkJ00jgR/i+uHqsCtlGg13fjMC/lO1PBNmObstQP2OI1K7a/TkhLLouWgcdGSwaU6KzvZD3kXZGls/SSnpYwEL2Ow94dkbAHSuYv7uGy9AdNEdDJNmXz/a97oyCBvnERlYms3OE4DRoiUw7qKjCkishFdrSujKx/mX3wQwDATZqwGUgo34QN2nOQi0UEVJiSFtWA8iHG69LsO8Mnul/BOB1zP6ILn8UWu2Z4ePy/y0qkl2SCnCmIK/8Jf5nwZZmwMilv08r4561vqEEBWoDc17bG9VjG+qkeEko8cI+u1b4XkqjfTCezSDiGr8n/FKlqQbC9daMqB/+3Lc8kLLbb3ElEen5j/JjG672v+fKxWJUgr/O1NgX1xGLRhNX1EdquXuZHH191vPyB8sDtgwY0M4wtVUcPYBRA0Dn4+LohcnVQKdLu3UD54aiM40TeIaywh2PPfL09xhziRWSLBfXJpJpA2TlVMCeuiydkQ6PY0WXMD+WiAXWYVjSwehrDb+1LR6aOeK0Ui2VAhyPi/L5amNzZB8FdoXj6LIaiX6mgmTsTn8jQA9pnkUDlyhYD/hGW750DeO7IUHwDDjMSOgMo5lOIV7/OiWRLTmyswqV4x6elg8z3XQNP4FKoCSH1bujHao1Dega8WHJoZKrQ20DxdOr45AINtZFDrmItwF63u6UWE5xtr/2SamOz76mtaLOvPibhF3UAh2iGway4GWyZvwKa71rWpaLnwTbvtqyb3DRjyTITsV8Rjv6I5XZ0PQ+nt7Ic+GYF1vJ4s+Kcwe5Aj0jRbN/OkPTWA7pbqz2IRzeAWATExY5r6fOOWEjl6ugTE+q3uJom9dlG/DcAnTGxwTDuJunSO3K7DOUL12Kt3HeAn+vbnWLFkpoOeMspw6rMoA5pWXC7Fp2GMhCmzTaF0t56YKsKvzgKiPRmI16uy9oloIEUaysqXoqo/sjI7PqthWswD9YVzFQCoVsWL08BVRjJJVtdRix6GTKk504A458srm9FWinnwddvyAol2uzxrgICiExNumstJgWWRse04ih2xP/SV7CfEorR8k6yJEDzZzdFeyCfpV6evOBkQ9MAnl7sHNzw4Z/YWncL6iVGFnUzM1tgH+zMxlcCVdZzNjetqR384LWuK5W3ynLNzG1JYjgmk7aot2hvqNpr6RhVgcA/JJtqXrDR2jlcyxA7aUjwsyq1uGOxAdLmlDusB/aI3dTaczthb1Jkm6+jN5+97L8H+pFqIYeQdX4CHmJ5tmCtgRExauu2HFh6pYVtW2ZSKsOEZcw/iBXrd1Rpja6G3lXmJubykq2Uwq7rog4m2cqOw1NYtnARBy1mgCUUTTkVqej1so//RMukA7gPVFu/A9npzsofaINrxVfTngLt2hhmpAWWJJ7JB9Ox1YVw86XftpcFrRU/ZTYUouQ/Q6QrKId94yHE5kwBPhB7YBn34DJxiXmWESEtKyZRnNghI90yKSyI0T9RJzNlkEP00jM4Xbhy7RHYNxRCYJaruEbM0vHEpkrthPBo6WaWaPjYirx1nof+8N0UZgCtLyi0mNAB8/r5Te1lJpE+j07DBbqVhCzLizuq3w9zK1MehkEpbmJ+rLzP/if+U3bUSBuEXQKLETb0XYyIzki6cgvUI+WQKm0a3cvM6CzRvRvfOqdcJguvDzFo7xiMPSTbdPs2lSyPKC4HX1tflstP6OVv3snm2xZHitVGz+hIQXcH5RQZOh/t3NdjXpM0rRLVdhyYqlKV9sK4biSCf3H4P3K+0STE0l87VLaV6uko6A82luOTn/ZlFgI/OLDs41or6pPTCbtsRwh1dju8+mIX2EU24zEG7ISL6zDBGTJAOjWUy56uzt+7WtWOhaCjBaOAi+LxzAYyQ6j95xvWh7kpBl/5CTqOa9sl8/yxw9KMIEmh3YIAUSJ9JGQKbpNoS0MwEt7M1JqhxSZegReVryPhC5XRBdXV8HXK1W1jBC93XdsI2txvtcY7kNt4yMVmg5I4sz8Ypq2soklZaH522BJjKXipZwOwMgmWzgsb5BsGxFscbAjN1spChIQPQmVumq5oOQQh4F/joonCGfXE2jB1OJAS8bK5u4+9g1gL7D7u9P8ApGJIlLoPOeAAGR7wU+p97g6ubgog3l2zToCHq9seEQxm5bCMdfN//3FkP149fD813d55tfDg65ly1Eg+iDovapqvRYDV351TagWMdCC29nAd1GdKwIXwEVa/DH7leHYBxC6bSWzhfwlp3uHgKuVxprSoyMwSm1J3N7X/5XJ8EoqkFwRyR1TfHQ4/h2FTzqZk8pi8xwEu2w4aN+NzU3iyCIZ5hg8Xjh2EG999MpYUwwWqZ87mFUsHNKeczbXCV/7oqvMfLDe3MkhOKOeTLSjP5xrnHkyX6BvJhBzWKSVR697wSBxE/8H4oNWB8huOcpHL8k3pt7wwQtZDq7aF74UI4knQTrbDGaeMqdvAPTHPrIkMeOZhPbyFUO01WMZDG0QLp/P1e91LnMwyV8puT3r/eDVRKfSsoQdNW1DRmJzXaSS6weM72Vjo44EJ9MeAOst6J9uUd9rndiBxD818PWFEc1qv33ITgKjSYH+jM5UpBBm/N2vtEcaamoBOCvnwQ9c8d/dzieR66a5v3ql8L2wWcabKfFWR4BHkvHf8Pk7lbWZJiaJKvgWVHTIrM5v9JHIjGy5y+gSht9PI+7olsUMMl97ehA5PWdEzbYuNxhOXX2Yg65lI+l3+5EMgc1JjJA5TuUT9Ph4awTwYGs+5kFjvFF+QkXUkfGpQpfjz30Lb9zGQoGitYAelWw64FtiRlfcTLgzvn+GLEcDfIZZS8gi2EwEXpmR7FKkaTpK9Sbu6JOs/tQ5fBeaq5u3N/zZh5Ajl7nj3JkjGswiC1UIRDYCyQYT1vl5ue9YFNXNx9jj+2yFaUXtqdyd2M2dfKUOK+y9COWwCpzRxCB/jyqpYEMpQRaGtuIEcr+IS/j0Z59tq8UKY8raYkJdwhCO0CSB/Djaiu/z6BJbQ7pKkmSKbtVT8Qn6LLgVQ3k12/Ao6EvrM/HQOERMdP7noCDEU72H/mEGVpdgSafqVRqyV0vTg8VHTyBJ+5JJVnkZ5lZbwRJwtA6n3wuoZJS8RA37XoSUuy/xFff3pZCCN2iAJ6ZQiJ3YURmcsUStgSNAFLMdcOb7y/1IoMObOmG+kdTo2Mdn7zjcnxqVp7N0YIlBnrRC4+nF8WeocdmTwJaTlw1nSCm2haMRIcvhVU/J47DHia+xn7gfNWWQObPsi+wDn1crdUZfY0YOeWZSH0fpzW1hADS8CON0vSvoZfXvnzvLsoweQSFYrgpQO21zCy4MN54dVNp/AhS/7/D5nYolvpIuvn8KCwRrd4hZDXu4vCkC4C8NmNblrqZujh2GVM4Qpbfy0E3wN1xT9G7wPbhVSAlrBVi/RPZ7K3vAfIn+TumEPX7Ay/i2GloLBO8JKriWnSzWUiReSsg+eAIrejJZPNElGrUlogvBibWF39e9uOYaw5Ew15vHPFZffIHj9AYQmLZuwVXWcNzy3+KoxNVqzsSJ5EiVZIYSdDnql0e4HvkUcYy4Y2pt8z6XYUxfN32FvccpssP5hd5lsd/+nO7AiFTW2QTSQ2wSGb+hUD0/RzV7ITJO5Rxf7OmMxoy2BzJv2t2gVIP0kO+caPREhaKC8PavsRe+6VwcdgH0pedNfiz2TYl3TDxI976Ml5RUDo3wP1q8ZX6090RZJPFrzFNTdnamazGcIJraZ9KQWtIa5vY/3nJ3hBXCb4EL9Zb9STF/7CEJM0oPngRVkTa1thfho176qh/GEdFlgJjmwSwvgnpf6B1CBzwmjYPCvyRvv7SwGo3yeMJct2yiiOmZWrGyJdEaTdrsdur6HL84gx2LiaXiQ1vVp9FpOXL5yZW9/YVsM/QFh/F4Rr14xaGqY/Ij9XPNzAz3GzxOUt9CYsw1Luqml+IZ6pxSkJKz+XEWaoNC5/ylpFL7x8c4NpoA1i0/1moyM5Q20PIduvX396+YhGUwat4lcjyq3E8KcglmykdORpWLIV3fOmBs282MDHKsW5S4jB8yu4GmxaFDDKc+MAX5ROuTm4HHbG2jd+/GEmqsLDhLvLRvY1eqahIy/PuHl27Tu+9Rlw8EUl0/7QqDA141+KW4cNMPVqujC7R7qfQdrgo8ldtwtTE5bV/qBgj5nZu1dRodWf+EBQe4dEv9XVi9e86wRUu09a1xIdLmcX+1ZqQ5hlFCyyBmlw3H7XjH0FLE57+bMYe+5X3Mou+w13NGcO/7uAh0Y6dastoUWL0rfPhvvwYp0fk9LxWjvGIHpgoT8TJ1lk5XP6v7Q+5zXtE7Uyph+XNMUeA4E6AVw6Oa1dCAPW4RQD7G0J9p3ZkIIT+q+HufNyNihSp3rSOWZuA15JW76104sUYGttP3rPFs4r8BpkzmKeqVxesU8KcyNqb6wPW+gsP/DCvjyfZBgd49Hytv8bS+Bqea/BWArRvNRlqmwQgwjNG+8P0r0vDNBIFFGmh+YrkV3dh3OHgemMV0hiVb3LdxKPSNmr4iDGS55udGSNSv5z77k9wlTp2BLcupYJY2EybVLEsloHcD2Ip8Vve7qv1nC/JKA/BuzXM1tOTqNKuIQjIxVXN/anZpvWjCKW8FKbhC58PPGAtXunIajckLF3eQZEAdm+wXT7qqyYvSms4Fck6qCe4Pp63JznE9Na0kSA7SIx2f5ZYmlk7JjnoDqf4dOjrIfzgh5tWiysU1dRlg60Qxu1NoeUPfvm6POUo8MpvpooZ9/pitlLr4nalqCP02ia2ZKnsB7qqsofX1/5N/XQO68oj3kke21YIHaB89ZTZuIO50kYRR1zIpEnGCxLQcny0YjrmOHfy5xZl5WT00msYlDrYqxreFNXqN7ouh4NaiiVszgMEdCiAK7wvxvZEAqduMUCdQRAkCvne249h6S12lOWnKiiFllPrCJACH8gudRf7iedN4NnoDMGXmiSnUgFGlpvp/7iIUKVkUmK9uSGFNqIxfSyvDUQ1PC3Bd736RbZ5LLilczY/AA04fUlYpSnBpRXCyElGVdOSPv6nqVLGQgcb62eLnE74SduYjdCYfBMdXQm5AjwszVcmZO8HBRXY/Mw/CGeMp8MRe3d69eDZwMns3rNyJcYdU58vsxg/b4D2JcqAqYcRdm9KV14ru3AE4eKVCksykvrg5ES+nmp0X4olrttwP28aW7V9ZKTRDulEfHKTe0I1xG5+aiaNzwKa2mvJyrpZUUvTUejtyVnvYg8+H5c5kAFf+kOYkLvrLsVyTTvhcoxhwLCrY/I5+rziVjohKV2urzLsIKNEBXXvlUTC/DTYY/2Mb8yuXRYjsCqQlkmZBl5jH/5coWFdjRaBXmjLLx19rp86J+vNtb+Iyzg0GFugqh4n7Ec7K6JVZC6H4SxsCazbN3a0A8vAciq2S01+K4lR1KvVik8gnLWmtno9ahYgR5QDBk3yBN0hbBxgD8D1k4bclZB3rNhxxu6kLjT7prn2TwWxAikpm3vs/fX5gxOuO0Bu9pad7UJCvE6X6j2bNZu/pyX+oKjGgsACdwcGCykz/gpf+/5g6C0Ctiufvr6AIKIqEKCElSogCItIXSWkJQclLh3T3Rbq7u6W76146pDuku7tj3893zsPv/+69zzkbs7N79uzOzs7OzlHLa3+uJ5tJqNIAk4mYRURGDoLCqrHMHWg73wJuWYVUPHN9xuyvEkQsMeq6lIc0gr5bSs82rd9HEuXPvL/9UYAgwlrNde9k4lRgwKa6hPbH/iTwHVTVIv2MZImUmJ0V1U4YSn9whEF+/uMSGsQ+AqW9L5N5IVPy3zZi9frbEXug5hp8+K4LwQ23eVgq7vobOAgB1bdWmYb6BJV8stEC+l5fxmH2UEQMfmwZ1JcK55bhWnYKTtSg8yD3mG84zjt08iwxVh0x6oxvAsX8V8+M8R5KMKqBJkrfsg+XOSaK+baKgJIYKJlhNUcSQV/EaU81+Yx+0FrGKSNGc6eNBibU5Y9ZsQcaWCcMeOckVeeAiUixQtCCyMUszZTlltXJDWvRHPbggZht3vyGHzQ5q7IaYzxj2XlvWLWHGTLCOGsH7n8Uuj7v1Tya7r62qWa7b6RYBkgDVZPBq5GcWgKLYv68EJK0hNPi0L0IUgIsFbf5yfjqMajpcnoRtmhq3lEBuFk5h14cMI/r/qjF0VYm/TQD1+uL1Q0sGSoICwuoMLaQSTV/TsGE/m2QvbQhyXG3R1tAhJKq/CqDSM4hRcsURBDZ18BZOwoGh0gOGZdG6Fi6p2L1DLG3nHqk/Uxpz/1kkLn14d85Nkdt42DJwto+hlk8jwjhUc0g7W5FRXdkvfQUJ8JeyoFO/0fTWYhLF7//E8VVqX5gDHMJTeeauETZuI34H7zmBXICxooup/ZCbdEFzZx1nGVP8dyiO5mvtjwvRHImmIskg2g7TrIq1j1zguRZsjuNgrRwYqSF5F805UwJGq/HwavkEJkcsMDXGAhwgkC1grrOH5RD1bAjjx9x00DhDOqWukfBHAsOyOy1CmKJ7Ub2YniXUvk4RiCDPqgPXeKtb1HLH14XRKheSy82ZadP4dpaxcLI4noiGA/XSaHor8k83OL4ulCRkobntE/S2oRbsZMsI6kpXLtG9VKedDfbMJxdQiQdnZhIUn/ZHtuvr/PImujxIdi5DuBol0EoUQH/XeIGvWHcbJ/+6zVor2TWWkHTko4JyeTrB9Z+xvOwtan5XELuPrEBofMGjYvOH43L5KsLrhFN71OdUejoMSacmKfUN0d2utPXzWvd9IU7TBPtZYXfKryTnShbrkwa9q4Pak3i8LgMU5QMO4+ujkW1Er7frGD+ijDzpXt9+DD7fDVtxtdoFpQvO49MNcLU8/PpC11Lzbqcex+Z0FoI7YsEK8GH2g+mmGKym8S/CmHDB+JolHkh6k13/A+2bISERlPxFWTB0p4La/KX9LDYK8R9rcRjOhX+LwvrQ4qS+n4vtMvcZAUWoRlHX8Gn90ENray0Pn0Kt7swZ4RAzIbNGRJ2MRFi6Gg12gGafE+Vk1SyjHBAIU6R72SkBSSChJ2bEUHOOoy8mAC0SoVF2VPEX5MpPjqnXGpIJb4mye5lfVdwkEDaO4/rs4aQEcbtoob6DHEoEZCJRGBsJQ61Xmg5Rkh4w7Tmqm+THiUPBpd4YAimB9iOOej77zehr5Owl1cldFttwoLU9SekmDUIU4o3G01SytpNgFpH/zIZT0C8bsogUaTvUvpdFRkOEQd45p3a30oTVI7Ssv+vllVHPQZtochUoY+OEBAU9eU/S5XNhCD3C3XqiahXBMO5NxJUhaGwdd0NUAsduYbkfMiGnXZ7bJpML6rOZtsXwVlp4UgfAY1c67c34O3SZrtYT1htckFF8oNHh7TuF42ryPeUGRrpf8/mi5eQX+0QOlOnEvh0BGCqpEKci2yxESxkVUH3SxonWG6nEhEr0ChwNSQp8VgX5YCTkelW1t0/rbSlEQdLzOjIiant+iFSam6KHgJs5H/484owryRfG387cpFf+Wzjc+HiPd+r577JHc4c2zbe3wC7rLZboHwavVYb5YX3g/TndRVdMOdCuj8Yg1oy8xHqpgNhOba7Lx4KqFIJBggsBWtH/UFMWoEGgkqTA/thVemZqcdpISYyKegAVDPi2YQWVhxunTbzIVn/mCnsY5Sz35VZ2k1JK5iFuzWXiD5CsKIa+dEUXxZGgAJTGx+hz5PgXvn+dDdu21EUVbryuP8+y8zWqqAF81pErxr+4aIcMpDA597DN24jMVdgzFBQctuJgmthkSpM9gNbFmxe+NdJtWLObRuyi4P08ZHDt7S/b0WMYlUuT3PGHiYKu1vA1y4eu79Esi7vVR51k/TLlVN4yw/UPk9+K+JEOBFtGSKrpEmbShyAXF52MnV/JaXEwexqxyyPhAfQAImbNdJVsyWNgHD/SMepbdPtX5M+YLs/wHPKoW6or4bhMXJVgKitd2TqD55mpn//QSMlecjTxdUm6LZMv1sc5oB41Jv2oa59LCsuH7JEfcNGgg/7IyaGdSY1HFEpB0qRs7HbJz6UoZfFPntlL4JSfMLJbgFPyHEpKlUkYzSytkLNXkmaHuw+fg3hxRtaK6T/dX5GIaUf5IIs8FjQ/DSKnYhgqvmOF53v8Md+/di8dOVcZZXNLLYKHW4YzAFxwSdDku42tE/uKIX1AsQW4K2tmdg/MW/ceuq/iUw1IBox/7KXZwnVdCowmahLs4PSoGQ7ir5XOXFRkznP9BdLt0crcu64hew2DNOpCP/hZy7vERgSXGqandsLq1K2Ph38pTxxyiOAruiTHNNZvqMC2sKJf+kkuRyyFvGh1dkMvJnugqYsJ5PG1k6J/icPcXuKQuLpNJRRfFmQSdhwPd4p7lkmWqA+pGhTGRSltvIJeOxQs6RLgrTZbLTyLnraq7Q65kSNiC/Y9aA03+CtbJpqx0DCBjYjpfYbC40H8ScSSoOg5Z3mFW1mt0MqqgXV4XpQ1qbV+L38k0LcgrMKvTXlaMu6MWnLNM0StnJNLwq1EDLj+q30T9r5rRXz1QsLqhYAqVcqvFcTLXmpCazXGVN7E+k0THZcz0d17YEA8Vdj5kQlEZtV+sgeI4AT6GT7vnBX4yHzBrVQhfyH5s8E+Q8iM63aAWoS3JfwPpC0TlKPO1IBLQrnJx+XnkIz1yhdS0Z2blhORjNCSDRk4ecRyxOteyVT53D6LIMctebtqcozWZ7Fn2pmMES0FKePuLspkCncFK0H2H72Myeu9Xs6H4cw4MaSEYbN6qe68UdoHn0ndAyzqSbL2UtSxkK8oSOmvqt0JzShpQrl8tlrK7uLU98vHaR8qoz9GlZCSdw3QzDz5U26ZUliL01i69bPWr1bxMt3LgqXylxjL9XFqvV9XyJxc9j9bHMezxB+bdiki+nKJlOCaf5bHUV5exGxVFyA3FgSX+K9Jq2QDfBQX+dnCmAfarDLN5cVjd43HLH/0ujE6tMho/Qb/ASbc8CgsdEPWfPhNPYA+nCFiHmA3t987L6U2O6AtdYeJCFq9znIogq98D0ycMzWH29GzJV04y+7To1yMzR+pob36vpmr10Ks+MEpsPIwX/PCXHrDCiTE4OdglV3rbT01piG7CtEStCqPfE3GpxD+mgRskhxJVSj1onx8c1y+9Zl5Ww+36Ji+C/vl4pRZsYyDulGsHzjFdqWor1c5r3DwSO5vRR7Riv3oaR8hq6U2gjGjbHjpgMzmHz28MamwItKqOfmBxRviGHDX9j4ZZpqF+1+nY/LkYfTo0fTkrt9PTenLvcbG0vzGsFHAUwdruWR2Lxa2K9kTPQqQpkWuVjc5LsoY1Co1ltLr7cq3CPCIG3vvBy6tKfOPCXm8QyLnldMm+0GCdzahD7Tnxt8/5OWBqW6mdPyfqvytcdbXJorx3TIaqVrvdctg909yBkInaOzzcqEgAfIOBqEbzM/Y3Rkcqf5VMmx29GNY0equf3abVqKS2ezttkSQj7BFHcseC6os9Vij9kCNQU/n7icPk7M+w5ArpO3maDq5oU2Sso6UQ9PRG0ucDalXKWEYjdMB42hyYMHWGvy9OaVepSh+8bmOZF+SRpqduOiLtZ1tABvB0DZaOCdOlsCYY0MtZqKp/3Obm+uiEfCykqJAeZ2TMyYwoyM0wJTfs0H4uPIrXyEEA4lD+OBwYd1AG43yMVbbpwDHJ8JUTyAEi6Yh2D76tYi+BtL+sWX44Q+MDx0EM8oUrbbqQL/68qi8La9fiK96u/u+n21h8/yEwDt+LF+GwdJ2PjlHh1OCIbQ1lOhd+Wm0e1kCrY6rwR2tL5L1THZOiViWi+OcptctrV/WFWfrU4qzBRDMp5eyMtX0mBvi1o/OCUjKh7ZGtacdCCQ5o1Qxf2nP/Pwyshl6WM2NpYWwef2F/xb+wyucW+6hoMZxpBMv0MwAoUMu2VtoVNIH7GV8s5hIxZM4xxbE+uOPrNYIlI9BGHOgDoL9UWWguimq8wMk9nj60ecDnnPsQyxLXRdpZSCb/wYkZjtZdaAMBKXJCFb3MDvkj11oRAXarbWzCK2YiRVwLGvxeWJP29g/3CcVGG/pIjOmctvqzFJXghx2Qq9495epdyfMp+vUHSk+/slyx4CS8pFP/inAf7NW/ffB2lc9jbG8iFlmSR90IgDIKh/A8rz1neK8lGmf3p5MkuxBuQkLT62zxMYnjGErHjuC+CA6Tk4+sJFol8Aq24W00CYEX/A00hfR2DGeU98+J+CJuuQeFPY6wVU2HtpBcC+7jauC6v68W/p7r+qHDn6UEhrUmLKRbPd2stKQnlQH8yRIMbsYEgiT3yBvmLu8oF5eqQ09RK5HdlgVRKcIy0t0PetQBscDUHSQk0nBc4e7tTCYPdAL+wHkw4ObZz+M0cPItto01wOVWm539i6zVCVpsPYPmlDZrWCs5k8f/TLB7DTcFRwQbuIhXPDmIUo5Su1ZAXLRnq3OIIayZrgk3PtdYjw3+ivhJF/Jci5nxXqxnGIYm9f/qp42CpzCLP6aCy7CvM50Y+bB5WEXMbRIixwe14XZNflnH/80rvkZnjwegQTVkvTUOYk6dUjOrqRe/ibrP3eZYF9ayt/bJc9dZhqbMNMRjt7Q2Av98simsChhfKuZBPUoCFZPPT9h5n+6yRQZfiU72jhtNlJvyXKJr6bpJixHOQSTNHqKEr7kEtByDTsZBXWM1OhJf39ZJ0FC0vI/mAnfTrXdQXop3J2QMwPeg7wt93XQYu84nEY1NFyZRTvdbLCy5lh9Jqv/8PMPolirilW37i+Dp3z9ZYT5WIWNqXLOQ/pjyhRDnrX4AlaSbECV4NFcizosYAJysaQvNZ1lP5oMMFp3r7iToOafYOiMbkXYCt+2oSKWkZYhkjkjowlKyAanJ6hUwY33LHi8q+tF6H08+CiYOgsj1F/GAdABQExHvD3etWd5lHeWtQBe2UKmJqwv1iw650gpJih0IQipnIIF+Z2a3tELe8im5135/2+0sFzAj9AyOau4ZTOx8S5b7P2QbC7/y3fqkmlggt0uNOSdc3X9OESnZA8ZZdKc1zlYU4PlK78tgcNTKtJhzDcjIoq3hihpoBpfqPcxbaBINsgLfzCElLORSABkX9F0+YxEN6DZKfn/rZuu0aTXwklTMJqOCKQPfoWtqOtg0fEIp4vnSQ5CkD2ILBDNZ5pUl3OVLrOJ2cl6T/YSG6z/Q8R8G0b4g9rZxXnkogowCsF4dLcZIQ53yZFuw3VuiHlovf4jYt5dB2ieiaBtBKffe6/z/Ozn958+48gZDBD1UngeXIoWdWOAfk0hDW13icpXMlKU60thWt0n2bmIEU259Wvo73dyGWWyEgWJC3gl/IYNzc8IATHcVbACJyvHsj4VnaDhXGG8IYL3ILEyAoIVyVKGln7OCtZa7Tj7/ki213nysUFegKmqA5Lw+EEMOpr7rTlMW1lgfAHUZxWwDKz2vqwFMyCQA4GtsDl3aeMEqYjAQEu+iZXei/zhp//SbQjdED0EdEAmi0gXBde/c/uyZAaeZiW+MPpnRsf1VbmUza5Bn9afKgiDFfBuZt/y5gva/VIJGelv1RsjZmt/DmG4o0A0XhS16uRmUaOCud/jL7lmqhQgwx4E74VItxDZ/tWqpmvkZYZ+4tNoQ7QgBj3lstWtRyjRbSGOfcOUTMH6qyRKoDjtl9fXv7t8KuhbOOxJ9d6v/QtNpgYZvrsbnDM7jiCPAFvgqPaWO/TjYH0hMwnyevnXYnP2wVjFDLni/5v+pxMGrfzK1oZfhjIZHiAzFP7ttD4k81fs5rfTuSlYQxYPthD5BPWI+pWfZm9bYm9xXIXIUTySeUvy3gNJ6wYRhYxNJslK5UfXc/FbsdMoHd/MBkMRmgnh7EkLKIOgL05SqBXu/oxGjLNFA4S7mllOgmIf1FFVNRoX4lXg8/9y1U9QysGew4/c5y25uUqVpZRh8MZAFuwUxEyv8KoRN0psWsOG4STitp1DppCaT4wDQKfa/0UtJ5O87jjoktbJORqAQt1VSG9VVR6LrjBqg7VbgvNWG5f4MI8r+Jo6Tp/ADBZULb97ZJLdzGlabQR1RUgJiGA+yL/acwQDDCi7EXZ9BtZGOLSFZAZJLWHKv4lOnhaNv6ysH74JJjsOwlqcXZoOEu2b6YoJJpXnSHAoKrAenSvpF1XrCw7wgv/f+CmZDb8iSNkqyuKTLiz/lV8DkK6r+f8XQCy5c6HXxoqzSt3qeqQYEODurm4KV1iK4YcVdsPCAbdagJTox6rjaJAXB65HR8/jIPIWc8y20WQ4LNbB8xKYYN0erkiKTf9wMIPJXTxP22kOjjIKS13ky5HjtSybcE5r0dwY6tqCwe1B/Ub7shBLKzbRS1BYgr035Ybg1jOBSRREiK0hyT0Eu4ilyzN/VcylNVvWqz9I7Row9zF3w4zhDMc/JDtIVWDaK5zWO78LibbZSjn/Jyj+yU+oQZa63Ad5QvmDeGyPPEX+KajtGwl8owVxpAVAJ0y+EYmagwTb+U19CbKQ4ZUhPEzk5h61/7yS1/eV9pbX6XE55KUwAT8draJ2QkwpKZWA1naIV1OtZj1pT/J8jm/3/6jlLc85VBqbOWOCNWOt3teEVabYR8zxP2slQVRGXqf7VqXFxJ9ULiwysxqJq+vzkQOCM4lfM2g1epX09i4HIYC0j5GaYp0dMw3r+AgFmXBf8ZFI66RGR48poXg6hCeyt8gNXEVvm3s3vS1KEx/0MlXoRPI/eDQCUWtiNfo+FaRD5KqhZfwy0G365o2s88cnah7/NxkEsWV0xPYLTdIe4Yb/cpzWhGBGZuFOpi52f+RxpAs09NXlkKU6I9y6AKdsFW1BCVu2xU2k05jOAy/eAdx5xuCpdHuWuyhMhtiEYxcfbnE446ExC1diieJr5hICQiapuk0D19vKHiCCEV96QtJ1Y/AMi3M82umVOnUJfVCSWjFdYSohTR2GTskd9WMi9boSI2uLSjYT/9AOg9LlAa5gXYHa/mz3A8gHbODNYqkoKhh77U0HwW90Yof5RctX8vwSN+YFOMucc2ROPZCOqRKVhPDKkHGV8EHCRCN+nIpul4LmELhxMGuyJm6a+D9v+sMgYzIqcPTUMOePOxxfsQ92AUbR+Ig1qc6KWazVKsL2ueprfTWTP29gejy+Sp9ZczND5gm9Cqpsx+gz/jwfP7J4cY8x3ih0ouZH4MTLB8j3x6hL7eaA47/0G+h3XUZmy1IHcfuBgwNfUFQZgrUt07wexTDu0dBnfktOnYHT1BEqQuAqdFucuiEHiW+1sy7ru+QuLAdT5Ay3qovFMGunTKM342+xQ96h+NYQ9jGHbFy6XWxErWaLzODDtVTUThW5tf8MU0jlo4+V63hiv0aQ0EWU4UriRPa+JR/3oCiVCT4qSmDzZTe98tyUtKkpwmBo2ZzxvrJzGaWab3PkDN0YI7PWMDHq8OMF9ph/FiwJKbVhb+O4txJeFMLWj8xf6ZmQR+/RQIwMvDUbwEpgBWE4zz0BVxmO5+tPE1BOudPOEHNNs8rCbrtEDiZauz1X1NjwkIBv0otpgpHjEy6mhvIJKI1VfCVSsAMuIaNM7KJPRRCrroM1yX3wpRfBHD5fRhhkgfZpD47LivzJML0KcKMZ4PU+mRQt8E9eSAxzlLzB6NeYjRD3UmRFzNc50oxJrbLUrbdKAO9Z1d3rEgJdremyQwdS67QUQAAQABJREFUhz/67dT89S1j/726xgKPcC3ZWiur/O5sIiHNF+RLtYfASchXtVSKYG/0tRWpgoJZ7bye75xBK5fz7e6pa1XK5dtdXCwd3WOOMkCNIyvQXyMwOuMHzNwlJI2Y+BibjMBuiNoTDMaCRVpBAvfUVekh404fawht9lPGWP5lvT8QfXkVV8gwJmhu1/CRbtAavMPnKdxPxtLYMPitgjR2QVVa5/P2ahWl2vtpsCAsRhJiJJ8hqo/81mJ5KlzbRFtEcxiiAj7Aq6J3MZ2BpeG/YrrGm+ZRDDFrtLgG8GZ4JlXYDljaO33rrkZpB+faV+mhtrJVB8WqJOF5f+l8Xq8jGRxj+7pVB+Q2S0H7sr713x7aGE36Ye76UnLK6fYF6N8E52AL8I0jDtAgwaA+Dususs31BF21olQNcAbFD7q/0GLeXfhF/t9ZCpsC4osJtP2CwMxXwoeSsZGKg5BpHd/ep1LzJ/fJjl8ecfMXpeDcX6OOou4iUTFStp2hSPfFTK2ETkxoRd+Zr6q87coAybrVRx2T3KSuVbyK5p0mE0HPzKW1BgPfFM39h3sU4XPxauLmCHDquvqXtNJtayYpYHNtH7m+KbV8WkLaNB8ebCHgB0bOHTEBtfkhkTqTY+Vqcqftq6KsL8Muaz4+wh33UmX6sxssw0ECcdN2HXzxXTPkhFvFqAy/H3irEntUAKSCDx+j0KU9aGB9oLegglBp1KNAEZ2/w6xmZiNjWVxtyvrXd9qe2LcZoxmR3jTI79cKzV2+8L5yNwHBd3iKsR3/6RMEYqmpmP/xdttAZ0/PxHqS69i3DCbOpRGeuIMtfpUMj8pR8nAuNlDn9J2WhJgYhBqQvlnagQs+Ud3yyuiMPCHHntXBTkJVJhgh/szmceLmifoP0q3BzjziKpAvb+u9zD8BsypLPPDpPATiQO/CDBsjg1O67LW4mhHrrAiSoMy0xP7uwApr6pZwDalkfoDgXo/e5R2xNVL4LZGKUz+bXMcBBEkcZjizcA13yxIrM/3lU74vapR1NqYw+YqP5hDqVBlrDSuFkroqJrAszD2+BXr7ld8Q3ZtX95o0vsvSP8HLAiBKsz2AVi5mxJGC1lRuFUikQ228wtACSdwl3T1zUSKlbScVmguLpXZqGlzPi0nFc4DwZFdNwJS4NR7uE/wnkXnv+OZNWwfxSiQa2Qrm4dHR9MXn+RFhRI2q5u/TxtL/LGPayy5pxVtIt/3z7xSLxpmkGtkqRuRgaSjca4mEuQXCXF2uhvq1mdowTUYKkpy0XDOONS2VAGXOgkb1/Oo4MpWJqOGJSWPYefzgxEzx+n+JZfNDLoApgX241WGrPQtbuSqvr0oZDTYalrkzsEFREaKTGL9cjcuBpyu7c+u3EKHnv4plKKJd66aIywh3WeVfrSvmB5UwiXA/k0GMRAL4m77SEylEsE6+uuWBhx9B4AQftyZsg6YdYXOxXXK23YICJxOTKDbnpFbiOS21BThBOj3yuzwsAhQU7ZS4ykhhnR7ejhjc7LGDFVhZA0gJgAy1qF+noz8iiJ3mn171s29oC1Uqb8z1dCIU35jetFg3PU3Um892INkfzNtFZq5+wIuy5QQUpo4+tk9zEF4ywWIl8khD6pxP6EkWI8S3iWHGfFgK9laVHGRJLdm9qXBOiP3qc/9gJ/YII5x0REPS1wsb12JTz+DFq97sDtDF/b6cR+u7ZDUUDqny4zXHV0BmJiSS3qbZcEWgX+pjjCP3KYz3WJIh0iEN7RlGptFd/7d10R5rTVvm7TtBkPeB+OjeQhrle3lZZTCnf4IabDi+L9JghPSkv3DrYx5t9x6slOkRgz9bfgvvoJE6T2UsKl+nERJmZxWl4ZUXMxjq8R0ZpoGloISWxuYEgiTFEWRPna4LnIVcgln+v+xXsI0xIbLLzFLbc8XwtxFFDuc4posEwp3jsmQbw1QDpTuP1exY3/6yasWyuANRMAiVfITUpvH2CLbqWwTYVfXDeK9C9tuEvmslE01ZmH/grwuaVE5A756zPjMbh49cz9zd/edZ/KYbblpPFIZvzIJFYOrs4qfPR5YlYztkuYqnJKNEmXnLHKcHU+4Ey3JgkhRCnMLwKlkT15BgU4DvzUkLrHF6qi8FhJzsxG15BJDBpUDK5+attPkfFN/pKA2KA8NhiTQmoxx1wDWh+iNV7fXrdu6b9L5a82lOmAgOUwVlZkuhwyd3BcuTzwjU8NqStjtnJeLOqk5y4hGsfur+iro2KHZBPJfhI8L5xsAIGE3Gq9iWwpKTXe5hb3ytCcSpkOVxkW5ZOmBY1K0LtoTrtCDFtNaJBsp6nSlaQzGUZNVUUshzxPpRJn+hnkVBqZndSgV2MHmvtJOAz8O8VwEAjP7KOC65D/gTG9nj+VTppV04FbREAO4Q866cJvhXD2cQ/6ycNY82htYnxUerhiqwNfD9Yky0b7ROWUdJaYN4ze8j0uJTwDh/vBcUHzzGRT+tvXZGWT0/lZ66m/jLkCDfAG5jWe8e78FXyrSXR/g4cKwN6LP84H9D7hLcBf2dUCFdXGuuu26zD6SzzQzry/d8pLTkVehzMaqoaEjdCXdQynRyykgKfKF8XKD0H8jnF0D7rGHxJ/YpFCVlXIbWYilKy/3LSuy48mleusadwewnTOnZ0iM+30g1PiRJak+XJrj0tqVD+oefWUnK1EDMvdn9kzmh7sxGtmpneYYltt8JuVntHvgul0pTqiiPVAtVpRTcaiinH3/ObsTRvWgm5UlbQpLG4fL7HX+7ukd91iV+bX/LylbSRzDHTcdeVr7ZgPyo+M/bEwLzRMOAf9zIVZafxN7+bUmigfodoruSJj0HgH+RMwQrVaY+LmOZ0AdAfllgK+dxfvWQ6YKTI6OfEzG/q52N+GqhOz4Sgww34GL8oA28h65gulCwnr9VHivTBwmM07nk4rf80JMhbQlmYFw1WZWF92VCUys8UNzdGj7qMfeNisNVvOPTMabEnhJK6xtBUwm6Tq5dFc1tXT+38LxUpH6vlFM1CymfYOCYlCkMxleui7TWcsfeevQ40ScAya5YNYQ+faFvsMFV6IKG1hFSEipZ1jjO+J/+2RNGwpZEvdW3Di9XwPQtrJY3Y6I3pe1cZBUg1L9hDfmjpIx0JAMQz07vdBlpXlxBFUQ8BOJ9eBujL4qfXpzmWo71cpzK4NoVfauryeUzLS2ZL8qUzgqWaCcRUCcBzQZAKRN52ybrDT/8mzJEdyL6AmSXW+ofI7iag0uJMvxPg0JI7qJl7UBSaY9c/0Splu+vUGp1Irjxv1B5H0ET8BMxV1ffv1AVws5UEQhu9StUI5zlkqexwX8tTR9ir1//UzcN/W/85d7bDDKgVMvIEuQFAF5DSXeRG+5pl8a+zPHmS/ZoAogH7llGUpcD0khwHStGKWdnxt/PCDZYcU65onh6l12P6drbnQdog0//j/ayWdTBSD6Hibw2mLklHUlTAVq8wQ2+z5EBHNX5B63EB6zOGf1xFeOeDdImWHrSnmuxj+usC+5N13d1V8iqucMOYOqx/89t9CsSQ1YOdlDUeV36yLBWK/mUaz+3rdYQyWaxu40UJeHEa5riv4GWCBMWjpSMNVjtudr3EfaN+BU0MnfgT2rZk1fs6C2J0g45eJQcmnuIjhH6fLRz+z6Gd6kbQieklbDzYG51cNOwLdCd+VpKG724ogAksixYZcNUB+NFEoO4+M/s8eOibG2TfEUv4KgK7M/idH79S2eLnejKlUMZ77iBQPp4lbiI+3h1DxHP3DqmyK0K4z4UYv2Ci+7pLUh4JOoqi6Mr9F1lWkAGM6hT16LA/Jnp8nQD+wxx5mO3vi0TJeEImxlosbzCJxuAvV4vE05xSkRujf9ruIl+lUrUE9LgIFpXR5f4d8QPd4iEFR/62I2MwzNIdJH2Rnr3o1ZY2wlkBr4ZFCOxWP2ZIaEW6h6ZDsKHOoR6CSYZ5iioTRHtgI/droL9yGhi0/xF6Jn/b6JDxY9IexrbbQhnYwDZhzte+J0Jjlb+uj246I4/0HG3SWv4MpFbXtMXOZReGzI4assaDs8TyJZ5dBmKt8Ua8blqDT1mKE2Bw0FMHYu71MlHszeLCgZi1fcAhbmLxTu9aEvSjN/76d/oyHgBddV2iNnHcvjCMBi9NNR68r9AV61qvRg/kraL2F4+R4cE3ZJqu4kYP2i87mIOurELhT788VxEP3um1+kalTBBdAvgIoNeKmA9yCDIibsWmkVUFiv2Hk/8+vIz2eEQPQ8Ir57w3q9i7Nwy0TRTbpNdBZ3GpsUh6gBKjNRaqZyliCJHtfhUzmneuyVE4Z+HQSNsQLAMnIxfjnzLWSvnE7cwFGhVAmKKKTfSnvnWLfK7Pd0V19o+k/ZYTNMtASUwsw6qWci5mot4S+uLBShIeCFfnzeGc5kWeYy/nVtPqk5yF/9zdxMrcbg+AhRYYpBOEeovkOZYKwTThubekkcnBBw2yYN8cWFvZn5KveHIYn19IFijAQC7KjBDz6F6OpwwsMayDw7YpmdjcgHTNwRD6m0WgVIKUq+RI7W+peKnN8gJZUf2FFLydpaEEVIpH3ILSuNBjlPj6wb7iS0ue4eGHaQ84P+SSK3Lve7WvIfrWhPNx0Q+9h5WwdOEQ+4jbfzY+NE7VgmMboih1vm/DfRvM2ZsNJRtlHWwUI1eYGrpPPM9tuGaAVrK7/9MDwUw/H6YtZq+s97cR8EgxPj31VoZuBwKxB+gpS8IkmniIlfcBmXd1OQ5R/kV/JZQ86a+uhKL276MoO6vau+blwg+DB1k07DbslutVxuapcfI7PdvZDP/DzjboDGYvKXAoeysm4TGflx0mif0WVXiGBUE+Q8c7STIUNtOtDx+OpRU0QbEJQ1zuznbz0bMM1GhR/AE1YKylP1GKWWRQPAknoZ+vKRtM24AePO8f4m/MN8pHNVolIAGkmEwKWzXvzXtBZWVhAj6n5XsXw6UHzLQhGtLR4+FnAoZi3tJulNK0xxHPo1Dkn3n97kt6q/YTXzviKhDurjRyYq+exLuJ7+Gr51DtOD0DYnHkrrltNlp9peBIub7muzyAhwgBu5DRKESCkRtyT7WPzk15JF9bcu/Z2yGoHawjG3hZvaOS4OktJVRonKKp29Gd90PB1MTPXwAyKBCvO6tpRftllZiK+3tp9wLp3X2mioF4xEUe5Z7OD/PvIDgkKT7/DYE83hsvFCvmiUCOk1qmCBwzbvaWUvj+I36uYznhJFB99oAKJ7PyE1R06ldLNt6t0l95i3BIhYhxo8yewR9fbS/kYEk5H7k+IR8X9D8zUz8ga2Uk75kdOiBJozg/ZkJGueTuyaH4QwXVV/4jwqqrkGZT9hBEBQLcf3V7cKm/6732SYOkqTgVQmvQq8EbN+2o1XUczLOijA2Ypm2E90v0bVZRXT9HFo1LJS6XGllVF62U8SQsRSIruPO9he3jWLssYvtNCADbUtjfRgERQXGQSbh/P5FBeNrnv+HaUEmy3mzkU6p7fc/N30MM3Itl+Qwf2lD77UPe8iKn5zNVTWXaDGNJc30oGQpfwT1ugtIEXbwNl+xsoWVhYiah7mphsAd9mdbXLPUPe7VEBk4iHdHaD6ovx7K+PcLmo0MB9QZFuHxh8/YyVahQpP1jTrZmlOCEXmcBY0CaH+tKB0dWf4edFZ51oohX62FCskb7Pgdzf2Z2WPQMcrRhR+QkJgV0YYi9QSzTTUw91gz4KRAGyUXkUsu9dNqB0YeADeW/oGbHAI2yUWn0awrSfM3iw3RTQbpp+/yHeFakuuYk1xscbvsiSzi+vVgDpFcOVAVhPu7tNjuf88KteBNuJWt/qKGXQBPRkQ5K7FAnAnQTrE1YO6FfOWY0D3Y11ByaulVGl+XGWZMw97N3SNZp+ncBXYygFHW5DC6J45aXVAMu8cT+PT5lTaPi49bGba64t+sU9KdgKlXlMsnGedRfFncN3190V39/ZUbwlR8H9f2rs02hnrpxYqp4LaO8VnSKVPQmWAsXsHlqP5u7zPii/DTcc6QGVsLkT6zoBLNyh+34A3oyf1d0YJffHIEVAxaX/Icced9reZKs/ML4jpJqJs2EHnoa1sZZJUC2hY6e6jS3dGD6fwkqxNfGoASIraxfG/hOkSAWvHbRY7xTFj2evfdcnvX2CzPVuXgoE4wKHSn05S9U9ghWPTNvvDnvrN2a/qKzKoZjqmV1WP459PK5bfVxGdPVcCyKytqdTCOaGQDVV+bTgg5eNIsZgUVb61bvs2gvxaw8UE0Y6Oe+7kzYi7VOlgEndVun5/0rdVk73GgcAP94YZs9N46hVqCyKi7MEJ4W6smcn/pQSTK5Yg2miESJuRxm41LIYqUe/7mgLYGQyAGAqn5HjNIgTte8kIIT/ARykpScvn/nLXowSDiNF1qufurgpfkPYxNvGDBQlNZG3KTCqJqwxwpj+XDmzs+oVE8mQbIpzlN1QQwhNsxTHxQWNCmiIE+yjZSNP1iUVJ1RqJ6z6ZQ+3q9Jh1cLxL62+mQA5GA/ObCEdbJbUT3Ue9HTaN/l9qahPBLSzcevHOAVyNRbj8PYOsE/+iu5exJ8Bw/7ezqZlIf6I85IFIwM7Qq3/uWOo4/+kmgBhQI0pYg5wO+rFT0n8m3IK/4hUxZgcyNYQ5uRK5OpSvuhi9dkP0V9nrFZNCcvtA6S1Dc38AeCkJ2zXiosRvOy8Ult/wLUGH7+Ny17UQsVJ+96CPpIigbC/m0DBwYx64vXpg6SDSxr9DhmU94EmGxd9BaHZW0oknubjpF9fC5oRGqzo7Mn3Hl/8O5KHmcZy/BQuxb/ghL+gQEt5CFbKWYSHQLzanowN4T4+b/nEUHabTQmfsgfapv2NrHBW5/HdoK7X7NTNeoVrUYhYKfiwAQFjqfBdgYXEukm6nLVSVHBEW01U1h5EXyJeJ3tqF8Pz8O9QyL/3dzLO5qsOTj2PDNg2efSBmOV8PpWTz0JZkBUm9l0+l6e2512Azt6iJpn1gC6E/n3yJPGcuplsIZV6NXg6DnKuEg1vZey7JC5UNiYgR9ueV+83Skn8f/IeB7D3GOOaeLjyRDGhe1W5FhfP53i2AMxwAJmd6d4jptXx8haNgb+0Wb3cLehGB3ZnTkDQWFrrnrh040cqmwPhnndyd6mBMzAQMVRlqbQlclwpsU5uQy4zJpKt4KzIbNlY3QLSDdsl/zWU9o4lUwl1EJGVmhr+pkB38nc5gdm5JRLkdjbe8zvVLS+lnALOGHc52xAwGhB8VEVy6+zeL2SSTSoCkAxFO1pKk3F8lw65jsWrhx3xDHoLntpj7EBr7Nh4INlk9hwJ9TiCpqPL9U50THYKTFaF9cHrrXJt+io4AILF6IRGeNPZNEWgPpvFLZbD0VncHBzxAtnRNYnZoQzA6mIkZ6gngsloYX8RFXsKfiR/xtuYV70+5qKkPrX4sbq7wFtRMpyeNLK1DllufY/U6btT4K+hiRl/iJIgB7hJs6au0f084nlj/EfCPWkzaDzHCB/ccfvPosvdD5ggX8rC7KBo0vwb3U+8NBUfwqdVAsb5wULrpysQDeIncUC5eVI9gA137QpYUv/hnDN6ZarWfsJrTjqj8MHLXKAHVxSWR3HRSyjE7js5J5reoSl/AedMNw91Up+fB/qRM6oQK7B8X+4b6bKCisQYaro+wVVlw5v+A4hoOMLln6Ap8lYCYAjurmxrC2GoRXrANsuz2I1Bz0OQg2pbnXU6yWVvSZGl39SREyHJSSE4Ayh4H7GM8MM+yWuEGcllpmvFHlEXYgW+jIVU4ci1ESf2WF9BaI3YryxHFL5DIHM3tvpfUYftcObtx/69qYIBd9LW12CksmaTlNYRdbdPkGFoLGkNQ7N2xbUkOzmmPQxW26UvkrQ3Xte8Rd4XMZP6d7sz++29ylupVt8OI7asYwKpcTzpaC9SnwBlLDzAQpj1BTWsEqfLK+keZyRLcGY1hsgmm7QAJrpTPtuMkLGPdHsISsns20F7SprC/w5O5Fgrjz8BsQAT0FwFNNKdzZXp1eqEtUj+wsTlfoIdzAOtuRDW4EOgPAz/lNUVZYgSJDfYp5u3zmIhOAT6a45+zyn6TbqB/LNefcLmPhwAZR9u39g0iudYJ0ff8yqHFVtyO99PcOvgPBDNJH9nklviu/aUC5vcgSWoZRufdYDguG2Yjxrl6+X6EHlRW5442OogW4P1UEg5yLrI5t557dFdnfXrE6wZh+MAkqXIza58qU+DQXpqV3m4R/nids3KSgopWhoI60hxvHoCsnMLYey1gL/3l5NJjy/OX/qW0NqI0FSD3ZCusIL88tTG5jOuK1O09gM1HUAKY3+2WF7ff8Vx1Edu99JGj3LMyi15qddxbPJ5YA5PmoNsCPbOWmD/Li1qUagwiS7SKzAXWR1V0SQH6V0pRg41N5LL/In08cF7ouysX13Fi1IFyjwfkFxUSzzBSJdPBa+elhQQNJLymuvrnmb7NfBcXVOWjolOv9c4CKgSjJIYEVKI6w2YApk5CGYyXFIl1jP6SNSs3o131r3/dSzkVSDt7Nw+5JlNYqocjbE2TBQpvOhaiXqrZIUhpDj+L7WrWN6rWaZmagtbqlTNqk23S8U6EU8ifYhOLhZFY1bT957I5XkLBPbTdEVVHujRKeqdMq2Ixpwef93tIGEBdtlGuy3fe7einf1aMsJVS+/thZEevir/GshFWDKpDxaNIDVBgk6RUtnLiI3rCy165E4v3LFHESF/DFI4EszE6rZpEY/JLwoxufU6ZY8V5xdaGNiZTDw4Uz9B8UyNUcVKh/M5+oG023EBZS9nKKawPW9vX8+TT+6S4JLuH6YqM70S/IRM3O5bV2Lav662RbUn9iDlN+M8g4EXoLUBp83CtcK6k7LSPVwb/KDjpnhU9RWMDd6wtummUp7ouOogz3+wlJZ2v5n4bB9s62h+ObdD+yZCNH83vKqv9JXNkX341XTqdgxpZ+mlz+Fv5cExnbFZiuKin3/Cksc/y2YvXaEypYSJnlivkM3+7Ey/8JtMuCDJZCxuR4pnIXWzuFTcYWViZSoGl+YZHUtg4XaHz4E2H4EUExO9b+RVkTcAaRPXXr2eZxmy+4twZsvQqOp09l4ZH64GNX/TJeKvSV77Z7t1aeoYWUkXBU7NcrsdREF2sWWfUVMN78Qo45wrg9kkyCdmjYQTIvsE0aa9ZczvteuwHGwS3/lfEjbmPZs794KGUdvPpPMC63n7eul5iaxhr1YOG/tHl0wUHSeL9ZtR4lx00uR9ZIiowYjDT7+R7R9srX2ESYimyYobyUrcEGD9wysVuXzRQXSGnNCk1otem5CFB2jG+ZRr2Q+QZj0+gWODgihqrFs+ojzsFW96GFq2m3AGHLXSjkcX//Pca+Smou2D3RuP444+AvUvpcSPR257K/1ISLjalLnCLrO1SYVAIaTxP1fEKejg4vnw//kdc9jScU97xKMX2Ps2v4j/Qet4yf6tNXVOauYCueQz5KGCau1iW7csZMDP7hP9vMMuLB1afc4PuraTF7ug6QaYDaqY07lm0jKLgDGlij0S8CzNWiAZGbsCtnH6n29RjOkHomQLigAYNYuMOS3DMmReBtTIT+Q9Jqqv+wbnWJu8lYHOgXz3dxGK6sWcKscgLmv62u9fBgMusOV6IDl0fzGbwQMdqR+Z65LQuh7Pib8YznA6iGLget9onoTAeHNZERvsUhpWyxjwu8djqufC7AelOnU/CmPGlIC7UPMJwKA+N+/LIr+YSreYGLhacvQUmlBouZlSmwSgTuIsvzbe77LNG1Mu6d9WsJcPxThGNiqbbih1Bl3tvWqPFSlAfpwywuSOZW4qCKkO1QE2cooNYEI0BK0QKEwbBEfv5F0QdnVdxMfsP9OSZP4x+Gfz+AeVe5dnBZ7ytHcCuzc2wNwSor/BJys7Fpa6ZQiPUQoCnYNbis4C5ZxzBHYJX20AQjHUJZYNEZsG9zcv7noWUlKZ5pagsoxaVQxrzIj8I06QQO3qcexyaASNXoRgk/iKFvjp1t1hmtie/j3nSQwBWvipP4LBwf20rpfIW+4hMaBbVwDeLVPWdG1woJ0jmIIn9USkaQ4vHiEuQVltSjuTI+cDbH+M4fydRD/I3588T0s1rkVkGrAMl1nktCMiPpyuWenOjJsUSJDXhNQiNBjW7s/d2QWgxP3QtVIa3d/+eU/j2tw3FIxTVJ11MxfOkinN2RfP525QQEiFJtBYCrfosLAXr1TU2i3ZEm2nPAU/6lxaRrK1j757J7DYcPYXrnfYrUR/mPU8y983/hY5heg+MbatsUvvSav5XsY8ALgJZKHXPBVso2RYtBOYks9gDIczAsOLvItw/VAu3K2A4IUSf2XqJEKXbu4higqqB6KE47UZpVXUQQZ48DhOlOQHUSvxqpg3lccN3o/soSUlmfzrSooP1kV2UQy5thpFoE/YEKK5F2jRJPiAvvuOCeP11aY1diBkDXCEF+aXwLcTBkl+wRbEJ/5SfEnyKSm3zLzGLDI2ben07wugSSNRCgUdtahgtELjLuBGmbC5+LrQi/HfK8WjtURM0r4lIEL0gp9rfx8SmVg/vzOVJnnFkjN15F9TN7hn5oI7pLtgf/BZkkKSdtySneXBnWcBAmgs0Bhg3xk9XrstHTds5+B352NHgYDUL4gh+c0hGX/z88J4cbd1IeAeenBK1E62wlBOb3rPrM7qagiC8QBMBnO5endbjOMNtTTAQ13ufKP3tUKUKV/EP412CYEAkvaY2hgzZaCX4vrIAdGsNttgKdXPXgTRG942MuGifwz7ch04El7zxw1+fPKpI/XG7bd8b/9F0LJvGXRPrlAnHtPJRU/VePLcIuW6X2kUYYrBlgbuIrnoiafC31OxexNbMWsWjztGUyRSDJ2eogvfsQuijvLiEroUOpOSuVo5kOjgdV4eEKYOfdzX/ko+lNW/1IYoHMw71l8j/Q3/cY4+fOszU+D5onlPF/CPyjXyRW1/IphfKX4K0+8mWHDe+lEB+uETGj3oLRZ3YJaUHGeXMVx6IAl7XhFObuOlZ+GmZpsRRxfeuVAF+QvoL7s5Dy0WIBR9qRuWPbtOD5mpBwF/FQkh0WLnmGsKbJVeXaB2cbiV7vB2k1pxf0yY8mqlnmcgI3iajLczfge8Cy4QjMPIX0gXYRo17RfPgR/3TEO4URzQEteTqTbb3QkGTx4+O+FiyZkC7skhcAdrVPVfeFlhDI0YcyJL+duOsfaZBSRgrOanQxPXSB49zK4NicCJlzne8sQ/61Gn6HkN/ViYu8ofNzwsavpwltl7ItKCj2kBqYJw2JPCxRzVD9o7Ni4+TNRjeBmek7Vbj1E9UfK9MnVimfcLETqEHSjCW/fFzSI0S0M3NdgQiDP3tfRm1wP/s2N9FE8NlvCPRTX8VmWr9nqUQeKAgrmx02xrOBIwHMUSYHI+Wvnj4CnaKPifmJ06y0Lf2VN5ad11dX5MNdGdw615mqnAAGhCf4I4c8EuLjSv5pk0FUjVcW5nLh24vdlIJ+SFY/IaOLO7xTT/c3D96VqC3Iqur7N5LyDHcr2vjnxk2QoL8v85e6GJqX1rtKY9sAtBYpfSeWDPtIhh22pzC2V4VjP2rxxwPOTcO/Ype4HjVbgk5Mf3NRZB/pwhnle7R5isbMBVpC+r30EjxFTvrHpRlF+GFphRsgXoLb1XENvrMK4oKbcxPcxHY+YyiS+Ac+xve+Qg528+k4BnYji5gUXn0IKG2gv4NJmilqfNFqO16INwuT8grujB0/+8EwPZp/wZPeazG97w++zitX64wNQ6I9C/YFEy/fjzblkv98P+HLtusxuTpeHa+tmukDTqpEK3ebYu2dKT4lvyZiQjJTQEF7Njxbn2SvO1byOvz2X4QdzYTRkykHuIiq6KsfsEAP7VU45t4BBGd04PLvTUvQw+XGpxbdqgCLtpK3tkLbDCUyD0ZdQoj/oZEdu2hAMiWPnBlma8cnwuAO59nNMmobWTGSaiS2Fd75Sip5Tiv0Tvvtuwyurh4IvIt/tOZTW/iF96s0Cr7JxsYLOjXCIjCtz4sIIOSeIFz7wk+YnEJZtyClkqNVCF1KFaAdlnjCIT6utEWaiOtL5hGAlnk6Asm1s3Y9/hgQZPSRO+8wp0GTNs4VXLcC7iGYzEkScwhfX/roLR8/xEoRLiyjePlVImuLXbITI9dkRl+tUIr7O037wjcVxX6X9A+pGfwfIpjl8vI7afTzI0vZ+L8v+0jwTkeSyTKAJbHhRBXg4pOUq7TdiioXqSf9UhbyTc2vGFjapsPqjZJSKlugC82kbVLi7SVsJqsYz8nkfGVv6r8HiHevFhgLptDTOtYIv1oRFSSdE6XAjdnsv+0F001EgpbaqcBrwiTdBOGiZHG/xQE0/AoQzDxsk18PTXziejGtHgoZzCDBrPXPwpwuS4FuVJPn4ne8SFd1Zv+ZfQoRqPMcpy/EGcBLQt9Emn4y9SHr7F/4X3aPbaNNH5lkryitlpiBjBoQoMu61Zk5Z1bDbStjNTPLLIHvFZuSW3uvzATc/m8BjRmrhypgUwasHUBQ4o9Kn3DV4Xgu0vWCbKzQj2hznmy+Ux9p9uLysXK6nCcoMvSh4o1l3vpRX6LZ4dvnR3Cgyizx/53/XCZ6mMpp03NPK7p+Gt8g5rU/sjctHK0ZQazEH/kqlaWjJY1Z3rcrn13k3QrmmrcaUrDFPDmHuURp0tpin4Q1fY936i2w0awfyTAxrpS3dISVeVgRCV6UrODT7hyBStU9hXHwMrhSHACa6XcmA3g41Jey5sO1466GwNiJfO1+71ZetfiYJTiypLWR6DXsRHDi+pZ8Vzk/cSpLhBYmkTlAmvUf4ZHa9ddV/WeNFFNNB3PcT9/N1NrCzs8w/nPdBeq21TvAVsbHeCvyB5p+7NizKc+Cx8WZQ9nkc6lTCxV+egWeLETKUHNzlckwECL+x8F/MRP4SH3RzsW8MR3RsDbkgz0u/+U4V+A2AyA5WnnoTRX1+UJ6+OlbJo0nNV8Gtl50ca3wCNqSixm+MyV3Z6r2HRvfHqOC8pHYta98tEyTQXfcCggmtIZoOrcZzCur7yCnbgYMdSV+hdCh/DxZiG1eyTKMGSA2DAUxTRPdShtxca4v0BBil6KuSu/n6A2+xFBUfl/Ytmg2BlTs7kLTmwRfo7fvvW8IXfI3oFWRaqw8V0oaYv0TMtWwJHAqzkRP3JiGGvOQmdxkrViYbfa65NsUnbYm1z/8s6oC1mIGxw7EfHI/6iMAnRyrrEShy0N5p/W9dPzGzQDAh6HqRbN8xf3G6uaZrc0HzM6OSnVV+gYXiNS7Oc1vmcjNQD/kb3LezC7t7O+E3He6s5x9L1PiIGRVX694BDc4JNbnT5SVlThNUXfZXFcsKGCyzbHDm3nEdot9qquoJXeYkxAo4d1mq/YzxQeLjZl8/jLeTPtc0XKaEcgwrUz+L4vadiMRqq6Upt41EB54MvDkh2BqXc1QecVUdaO0SmUqft/0ud2uLZf8WyQCKvFdPToHXn3OAVqmhBxKE5Gxr1v8696HFyzdwYye0JU+h5TQhv6T1et9iwk5W/pOeYE8gyKTm8uI2FOdGib2eW9b9/BLeYOmA00OfPweoicuwijtBIbXz3uJPUi8eNwAwtRA5F0Q+yA0ENeAX1z0LtlOnqVNIr5GR2/X6wssvWmSMZPrk1lbpCSLW+QmHWWvG10iw9o4V0tIdXP3oVpQqHmFh+mA5p7uqmJRsnY0wjoGOyakuMe+UicRB5Q/1FqaJ+B8BUu71m0V4BKyn3XY7fq7JiVi3kJ9d8BgOYx81vJkVDBagXzKf+/+p+Xgo2SQEybN3DFfBfoMnQNNffL+Th8bs6eX371lxmHIIdssveOTM4xNCvrrXwdgIybQ26JrOxDzJu4gc6sy0xIzaKBvrPQfHJIQ08tb7t8LA0CqdDFElinlwbZKEpQ09w1nrqfAlqIM3K8qUQxK0Vu+0FTMXTHf8x1OH/PyYlKOCd8B5J3/CZbv8Dxr0AkpRuE0srHK+LFikeDAAtoxItiZR2wXE0DzJfXCA9yZ3AW3MJ7FmrC2AsSmK0Hlrhhld/xTKmmSPMc+LNF03BA58J8NM+0+sUPlYHMg3jkebpAgsqSbNlFSMxCobmxYB0VMSKIiO7a/Dxrh2uXPFImCw6QHCc4gOylBvh3k7u/PgULV0fjmli83tzcSmmZoDmM0HjLwZiwJe6cyQdbSbhVTumWIuZ/8WflZvtaiFceUGnJEs8GfzuqXtzD+IkKPk8QOLkMHIHynAW/MEsddP+pjIYK7r0AFAu0VLSxcA+YvFaDU7K7Vjdgbr7vFz/3OKe8BNjyClQvUOuJBH1+1nlYtepYrwN4P5QprSFbaHyV0Ysrw7I3ojzyYyzvb/7XHpSCFPs4cF6ki3hw4CRK6IZhGBccBRayJS6xcW+OGxrEyEN62O6UN6U2/EnHEbYRnFicSGZBB8s2EGXxAnPsAAHqXrqxamCoPPuKLc2Y9Udj9oL7SzhbkKXsG2daZs4ektcrAeqmHuhaSeKIE/8KUflL62ZMwt2ggvXL5BwCfYady2YnQt6wBHQsJ0aNfCw/wavgOU4ZevDGNAO/WWA2g7loeYuYgnj9awZ99YZLvNWwtsRehMk8gpz6u8n3LIS+5pi8P6URXcA5XzX9zhQz/wLkkQh+51Mf3vkWy1FWs3D/IwvxvhRhZLPCyO5arUido3fRXvnd2VvavrHe9gyaDmz3f3U3nW+RaY8RdM8KIRdGqkt2AbBrARthlgjV1erotABMs6TXXp2heCDK6pOTyvL3Paoao86ZkdSEpMM18h2ziNVyKbuRtzm4X64DoCFvX1CDVUKke8975Zi1gjCrhzXpLvmIz7L2iiiTCvQzlyYBwXM+jf/ETXHcYCHwqFEaXv0uSaGYvSYyR89l4zikJ2pePJh13H8GqYURNJLqq+k5SehMJPZX767jds6sX47OVj+W1nacrxI2EO0W4hC+My0+30Skfcpc+EnmLV5/MckXqWstzvBXRjwRyX/P01LY6Ye72Q36l4kP/0o7Vm+WMthzCFy1fPpraJtn9dLYL6x5rIMBeCKj0JybdhQXU9OfchtbR9JrKj1Qm7Sv6KcKyeaOWXZOvBTi1uvyGHCC4q4/WtcN/OtgQYiSHBUfZhD/XoT9nl5Diu5oFvu4R4mk3eacKk7MGGmI7Ecl5hi0rSChtSVpJ/89ZTYMQjdjHl2m0jnlubHCsRnBMO1zPbXYsN/jy6mh9VIOdtkvKE2aPqcWi//eJnyy1gAU+7UwkgTQQ+cao16L1ifZUTTxud33lkotJsBeI+wRLv4S1A0ykNPvS/zmdrCRuSOMfPLXPd8Gnu2oQlMBhRCQp+XMHZ6OCuOWhJDSZojImZCepyeQLQdQkf+yHzOf8UAZwoHo1ookSNtlHJW3Ry8oxAFVlXZnpLZKoVZg4eDOoTDhGuPQ7OWxO9Oq24WlYITy7VpA0vTLy8s+cJCSVuf1Y1rBFl9rQeOda3tUKlMSZtl3wLJgpFWMSbcZGCikskZFNRkzhunV9N5BGpbCGJquFEoPEQng6Tln47xUcPUnAAAkpjN4k5fr3VirdZZb24lHEiTbZF9IgBErfGOLlsw+wKjtS445MeRV9/yjeDGq1xYD5PhG0jO3ExoYESK2ewgs+JJjZUBSgsZlaE1o6DLpsNr/Z45IBGPwHjLo6i9uS7dhadsj1PeaHqJ80fRlkIumntxzG3PiAYmUlcnRBJSgHM81aFfrvOJSGpHCZvsLvVmzK0aG8+6/hoRP9zTIhTZ3xzbXf22T0iV3opf6qQmP4Os95zg+fwqAYThvKwm3MRzas6SZf4CdX3V8ig9Ip5E/TiTWIbnlUCget/d6fdHZ6jbJVq56QRMnfP5ElIU7PkknrS/9vRoyzufTxfbWN9EMt4FzyLgdk5uUj1jB+rYYe3IERGfLMIUjzhR5x+wZe5hZC4Erp+xU2vQGJ5wNHCkwnidiFegKXbrFORj7997WIVEx1dDkEgH8Sl/y+9SrW4WPYMiWuP6SE+Ug0yH9Vpgnf1ISvYyZ+tg7Bu457+h9/EFLX/L5vBlFgk3Ct8skm253Uvgs3nUiTax9Fp5nqxmyA9dWXIsx6xdhW9CVAeDC7QzV5X9i+VIUKmqoj5xZ6zH0i/kggBsaVOwOg8gbW6h/De65+ZCeGsbSGsudzVzYvXKB9wZssf0gVSUVcU6f9KLS/svkdJpWOutPnt4USVugEDYmVBDqR3J/Bct3KVQUeE1dOWfyhf3oKhX2RPu4QMI90U4g+4sc/nq+ch0OfPVDRLw+aLED2ulz9BjCARxkdsk474QHMIOvIHYj2ECMCy/dJNvlUU6R3jbAoqw2h6QxpykKrRFpWOPecjUeVjouDhEmfbeQh7ZyeoiPSINvAiWO7amYaUW0+1pqIHUvG2YltoNLrwSVcaT0jqfE+btWBOqqA1hjQoPgG45dd4hhaSZf+lCLlniB4gRhXpbNlYnMCs6CRNLu//MTD0sMzTKYYO4vH7S0HVEVuZhAjzJqkxqBQNBcS9z3BLfn1AQdLyKOrPhomaY46USk4m5b0T+BhlaMScGWmNyxYQA69xlX107t8gXaea2ftnqG83hO9kz1WPJ/zc71GjTgiLMVG6s0RnSBcQbnLUesH+OFXFFksGzRJYkdAmFmphVFSdOPCb5iOOe21FwhmxYvceG3u3iHw0QWqikZKZaT3548wZDvoICyrff4ELBQZ2cKFA5j0Yhp3BvGNC+ckRD1mAYiwtGqwHrszhraOtIi6GY3wF4bO/zC1l+TJ9zZgp6gIBdFN+gihIdUq0peyA2bDdBBYWcyMs3miBx8xnhaPZji+2b9dQ7p7MI5dtsBVeMQhygKzvx/xF/UZIJSYDJB0p5sf1U6a86coz01C82n6Bhutf1eCxsnN08WqwE2vw0pmr+x/Li7Rl0g8yQJxEDBCDtjpvB0BWV/Jv2zmT8zcA1NxAqkqiczHatTaS/+lXef9RmNrNjKmQ9jFByv/JmjgpDT/O06mYgfw4043AWITIgxzyuTaUW5iaRCP1ixQnaiKWPBb/znqHuzlM/l8A+wgfhu08WE7CrK+/s/pKEOJYp/QXGKbfz5LlEiUGBl0Fsd77kBbhsoikugLEyQgZMhI9Iu6up7Znx/E7a/r1FrjF79qYa5hl0MMnj806v+LZ+tbi54AJvby/A1GILKIetSLQzGjUT9kj5ZevlIWnAZLpri9jQz8gG225i4wsCh6OMuQKLbzE3QUSWDeQs3pBVxB0FKtArlu13FUxr7N3JzyYurU8WRbN6l8VfVrk76HQ+HWkXLf9+58Aty7tPP64EeARIZoYUBR2xmvYm8HfLA9n0Sz+vrqCT90a27SeAyu0dwJOpIbkhK/+sRGv30M4i8r0ADsaz35BWp1KCjfR5l0TuCkht2glXaa8Tq76/aeT8rgio5YNzuKRDE7eJYhi6gCy1JEh91lNLfMi6EH6T0qTV9GwP3BoVRoUMDeTFfVPiC9pT+a2Ldbia+rRjZOy8/M3CHJscRQWwWVgDJIM65jpvo5HWH3afJ3hNFK0Ukq8ekFbMr8HchP+p6i+Kz9q433a0+TJj3/d249Jd7321q6K+ssal+7f6aYOk0IQIKw2fit6noI/ssHabCt6AtFSn9w7HAtQDt3X+++d9UFvWhlccvUGkWNhIQPwVWcRhAxr4qoCf3LWqSWIaINwEqf8ofO3qYIVBZOAGMlMlF3PHeepGrwlWKhEi23+ED7gtU3jVFXWGItSvhFHnlwd885HxkC082qfdMtZPYBQwhzoNSpILFpcv3hkOCaPamB/f0CkYwAeCx3tbbgJG9lnCdZLDUAxejCKbE7UH153+MSk/sEJFt5ff4knLUv5ytv1Iw99iXL6H4Cs3OpmfCZpDUYwiDSRzCp/6NbjBjhDZf4oLwdrfD5AvRSk88aJv9GSR7pyWLMhFL/22FCVrHgfM9YpvwS4JU2weuAJYhW+8YGElBc18rct4Qqz/q7iZ1qAwdvGoDRvtm5FQGgiYiGA5m/v7uaZcGflp/OMFJjcpcrxlB2jxei9cvrtLyrgxK0yy/X6g/wOIw29vFxl+ihsKlUzrlMVff5chBmVfs3DONJSssifILIlhBwbSNYVkoKM+MN3LxXndBlJlVzk//uS9dKrFSAFN3IZHcyks7MMU43FIiEpym/7CaUIlRMGBu/ZCE21jdeiXy50bYPlJ8kWFb/3VNtOI6wJfAa8TO+2UeBVYWmMBVkFVxOoCkgEXyRnDuv6wXJU5ZKkqYV89yTL4HsV1UpQNjv2bR1bDeKIskxSxEdKhhBc+76jS3+oujjo7WWB84YmHLSeTpHbLsagieGl6vTOULbh19S2ysPsC0wxvCLStgyPupfTu7ZfLstyesAFhSY6o0wkDfH6cUH8AyS9FeJxInkzJMJQoSjjHdFX7ygZHzZtMOXXVDaCKq0VYnIG6v4tjv84knXAiA77Ty0MkvgkzonuKYUQIFwChzJNDHzmnF8pVQOmubLT0K4QncXPtwFYzAJcAq0nAq23YF7A/qVhfLWpQ6Qw89/CB7hK94szh3WRowLQy3jQDdrqWiK9YfO+1TJisjoogVtlVxSCfUV8ZOzWQpONmlQNOddsyrhZ4IVsJbq808jtGnk58dqUgtcObOOfuYHf2mz4PzRju3FQjZHuArSU3Vax1CbyaaawXOVM9nRHtjl5v6Invqof4FXMALTzPud+wDaiBJobR9GIRY94Bozzoh3YB/6lem6xvUZrkd+Q5Qqo6MEMrIbMl0YnMxXgZ/NZl+B2RICkN+v62qlNOYgKrmy8aNfuGo5oVzSvVN2iT25VfKPN51RyARp98/h8wM+ay8ArIx85d9kOeRfrrVelM5niJK20Qmd67gOW/tQCLQ9VieVaeGA9mjHI+zdMKGpc8pQdCJsbFsfbi/MQLhEVelY7KOEH4EDso1KvtfGNs7hABujaTKSzaCKZOlfcZ8S2vl7A/3KeVYvafWU1sI1vaTeyOhXugR+3/sqgMoPhdx1CPzjGGwLnlYd1isUpFqnAu+Opa2ZY7qqKbDVuavTE6J1SreiOgFuhl1naj1aKEyFptElit8T/9vvlijr+4XcW8mT3Y0NRG3x09KLboOJXyo9MMa/+SnmgS758I9+ycIDtNJs1PvM4k6uZeD5XBanLHIQd3yTmJNhCRDKze84HPqxWUiyN9IK/gj9bVlAUYTF3FpNGxv5zNoxTEMTV1zImlImZ1ICPbbe5L+EgHUzs5blOnChinBqIW1w+KTnnO++kO6b7aPsWdb4UrxrvdJIH6+2v5DFsghWyZ16mC+gXGv8weGtdfppqZJYMwNSk9/YCNEDWaHo8b/cLhp6iZmGsaGusnmldxFRD6TklqJCA3zpn5WdGb4zqebFAMY8fNuDbfefWb4GrgmcdwEdt6jqJ9SCKcNqA7MFOy4gHvQgLlPUaTZkEQtVF58RRabDKcg70TV54PPF8cu/0gpgC9GDQgjtNotPLLPWwFoag9ImkM+6ue7iA0A1Hk4OKT4FHPNnL4eqF05QFRWngt2xNUKTcamuVtOdcFbwXugHSKaeLxQbSpVNo1NlqbFeEnFFlY05HsFdxVG+FMyD3C/+ovqaX5HfoMLh7EeZjyP47Oc/9K66vbIf4x1nkwU84Qi750vl2A5kk7MyAc04Wf3777kNj6EWvL9rZvtSiLLNQEgYzAjG3ZNvEj9906BRWSbJy2NgC17EcS7lY6Y+N/e5bV+s9HvfPfthPyCuvgpGHwt/3hfKylpH/M5vIJEWnk9xwGN9xT4Ntt9XjeaTex+2SvYxAjfSHx64kKc/oWA7luuU/szkqUcGQyk6KTo0ilXfVDxuM3kYUIlvw/z5CAv4FK8E6ZZLWpkOH3RIYdk8MnAEDRzBe0pggHM/PZ8h4XQGolRu0WJLoE5oKsznWhwZPAaBLuojFHL6vmE++O+RErlgG7teCaMWH+631Cidh5NY4pYFdWFikKXp3Qi5VvqH16VuNc008nrQzZnvKjgft8k94x01UcwO1JJVUOi/m7g5ls9HiRijan0LoyEu/4yEZzdWcAyFQO5kj9LbdlIdAsr6Qjc8Bfj94SdTCo9HvMZ2Yu52QujYHcGciK+rrwsCZV7ID42zt9wS1CbiLRP+14ojs13lT+rrMbG7ew06mpLI0hU6fWhuFCr2Lo9MyFSGTCtPk+pn2RD0PQYE7Htdn2cYahtXgT6uIh0DSOw1z8hiWFNBTOVii0GJlPqA9Nyq2Tv3hwhc8D0YfUnYzy0cpERAIG9/Kv+ysvrIif+CIUFoNLbwGkbgYY8R+LH2lbJAYkdyWTayScNyoW7kYnNgubWFc5nvr/+TyLnMCR1UJBBOxorf2pEOXy15UrYztb+8WBhAVdMneuLy2tHDA0tV/UDdfSPJYbFYbqMuZIUR9v9qCQNJKO93itvFLT71CXeO3QbHgU9pur7mBqjcbVvzKppk/nkdyAjRru3P1B1yRbPQ/QP6VlM6kbUJbIdh4OiLu5R1EueDbMYAR1tShEhyLj/uB+4d/FflXZJ+72EHXsYokxM1hB9ORVuZWXrIgBossDImUBy/yfzw1WVpLiCtiMWtQnLf7kFhqiNRJTW7+mLFRP0tz7HgZJO2Je1TP77cFp8pdyN/GYnDoRVrZP4J2lPfF0TwJ7ZsYdlUfr6w2z9MsT+b0QKb72rPmMGBXk4lYoQeRYQNPFqGoPom+r1MSpXA+AGUnBWJ/yW5oQI8iWaqrwjltFEJirAlRCOIYU7RMx07MAuC3tuN7ES0UuhQ4HPn2CHYyGKWydhn6KqSVTxjznUV1fbhANVsPlfRxLt8LG9nYjgDhYhsyQWMcxF8HOilfxMrFPwT+YyA1VXWapqBf3poH5qCC7hkQLWLuwW9NfSRgQOGp5H/+Q2Njm8Ix0FuU2p1hdygUbuRyPrsO/LDvBRO4CK1atlO0o/VhmHm/wY1edbn8jZlBLouCOFoWOsgYPHH1T9Q1nBf0cXgB+oSx1KRU0MMW6XY/2v3G3OPBb/w+5tBfGUs//ncHfJw8L4snZTHCbYP95nXRhD90q1aAo6VvvLUNr+odwqJG5kKKnmVqQMi8AWbLfeFG1eNnw6md+P+vcpW2IeoZBD0v89djE+25k16IdXTXm186X3sVCLlpBbH/NCGJEaE8gc3NbbhIjhM25Qdhr6vsPOZ8vhIkk4QulbVT2HnGSvAezZ3D6DNlBA1mk0wIEITlCkSNSBNIfq/Bw/Tk/bXzmHr7x8ix8zs9rE+CiEAGocAnAf+eRKRsQm20iP8ZziflKfnthQURRYYy2elVABjE2v/gmKtG8dtTconng3RTRPKKZUFznbXMcx99/pM3E1M63n8LvpzAU1H5StfPqfj4covCQCwjWS7AzKEf5NqXeI+vnrEaH0iM32mN+R3UokhUA1GT2Cj2VDAEqlS1ZPalGqF/0KLwCYGLpNKkDPosm+HnddwkYlUXC8/JpYrf0U98lAk4Y98RAPFt2Prb90NZlChhmf8VSMocOoy0mx22+LwENszl+3JCFj4jcEll6FpyPa3tKMrHI5CSyY8s1+2qHrT9z7tU+jhXNQF5vM40cAytw0XoavL46M0ZVUiOEsSg1lw9sT+wR43W+508TFQdbH4CyYMty8C2JdFWV4nJ4dl7SQqj8QffU+VI2xB9f2iPyRf81Ui9SUtjtuFqJIdwATmxgWTvmwYZ2iUq+MQ/yaVSE2AsNGCd5uUIubPiMzEY8FC486zddrWT3nOK9+sIwpvEXcPlWU68h5zaaH12QwNKzGgqVaDIRZ2L6rL/NL+4T5uSh9GUiE/qHhXukrsa58RsnOLGzUn8BmKvMxO0qyLIhSPNmnkH2Tv67cAAEAASURBVDDFCJ/pNATe3eIniWuL+asBlzYk2cc2O0sqRlExTYxB4gqdlHdNOpiqyjD/Xrhfutk2k+I/DYNNe/slNRTkJX6aPJ8fURX2WFntygoJ0zCmEsSIAIiqnVvkV5WfQ8Kxe1ymuQjkwVXmWgbSmRhC3t6z2PEoKQwW0Yfb3NbTf9W8aSVquxYyzib9SHlO2ijzo7Yp0Y+EajY4oec3biGeyBEEDm3FJe+xhzxHJsqs4xJHhv9Om9TsS0PMrDRMXxKUez1CUekl9g4c+rcoSflyW7V/h78w0UGngSdwVXhdOBK+5exFb78/p8bpmhUTWYE/mMhpJUNiLGGALqDEsossR8405hnLNckUd3EycU3Y81Ghvq9Vr9MhunRTDqIR5Wq6hseQwZFoNIrJsJmiA2Gk9iYI5WDlGNCF4jGVRteIsHs++d3xf337y+xTqKUZhT7e393dLpU/twIX1nZc+bGAwv2E7AY+XqudjK4jXIIvXB+lmGVRyvrlkenwBud62biUGZSFplNaSnzW47mqL6RaVkODx5HfjrNPpQDD7gYzSa9YIg6NsKLmY6+pmFUCXQpiZiLnwZ3cjHQiBWGd5Ma94gQStwvyX/HR6XFwO6Gm7TyPb0NdJKZPJStnhtaGK80Y0CiRuhsMv1IqS79g/587kg1bVrLWYPx3looCO2ylSYGx0R/ic2al3v6nRa5Y2WrKyvCx7T1uBVF5VJShZGZ302bIHzwlazk37Y2S/fklDRLBH/dAGkFotX+cWlBwJnuU94sAgXT/SW229cq/A9njpMO71llZ/23jxU4wyyv/wz2YEoIyn8Yt7NdFiia8VUFIGRe56XcC43R09RE+9/RgkMK+67ubmjfcyuucw5znF1YYDxZnnw0N6AmJhcR6F1uZA+/nLGDWtlMG2P1Cn3NnVPcoMwvOoWJhsPGJuldvGtTys0fEERAVylNVCAn4P/YTQ9zezNLDXcHfJGLp2GgMRgRJfkuyTW4WAoUifvKRjfr8xOieDU1JqZUw5E6ZlZPCePSs6/3XNeMY4obD1hPW4vFGzTbMF+4OU5ScTYuIAoBSVawM6UF1Oq6oMe71VvXLLwOZ/bKMMQSAxtZpF6kjvEcavS0WaA2mpm/SU5HgnhbIIW30owdqGMlxQCtaItiqH+gOflGWUO0qfMlD6RiXJcEKJzD+9Z2zwdblB5ZIgx3yDfEfZAH3lc8+2QDPgf2Q1QWgs3lZQ4Khn/CEsbT3uXbLdB0bROzLSgf/YYCdzyishKA717G54G1mJOfO21yQrAYVtBvjBDpY1zSvtSqSUzKnBD5EH+q9IStp7UNJ3MbylmDJEwUCM5FLzGb+k6yO4/sZSzPvlW5vwGEa2DWNSQ5O+F7ftdLiF4K9HP5utJWeWnvR7z+9wjjO7Fyx2oFRZL/k7/FnQk3UXyOAAoq5zmm1EzwZXbRx5/31WKYWmp1DHFlWd3J/lKGMFoDxLxnVOfPyaFNBc4rfDVeDuNmsIEh5X2bjAj4MkNE5p6BPsd5OWvozb/7z1WCU1glVB6sDGX5juvGTmzupDvuDsYr/A0kgJw8vdPzcM6X4o98RqOXXJ8O/2RXWrr60ULhM83N46v8TTRHHFHziP9OlwsJ5XB36x8V4HS426igdFYPRHZsbBpDKuA0AlCSlz/9H1FkAeFk8fXxJFRUlBAQJaQlBWulO6ZAQkJCQBgnplu4UOCTkQOpoOOLoFOmGozukU/b9fOf5+X/37vc8G7Oz++yzOzs7OzuPPDjRFamfB8b6b0P4KrADJWLiwlvp/JgAudA3V8tHwhmbHkyQb4nkL3/1BcqQ6VBiPlE52IS1ni2bvpfVSKeFQtoFwbTRGbI916/Q0h2cwaUgEPrLQxMMgGyE4hOOPstqQwkt+BaUFMd4z6rG8I3hOkKhzOYQwolYumlfcKmv7JbYj5JZQwoktxt63fOCgzxcR7joJ3DGdLSQGi/08dkxGY5ORS43OFj8wHEDy9EvTnml9qtmmlnMTeCDqScuKgru2SD9pXzqP+VIqhI70JyzwmLCV6oyW5ZttrI1WZdBD14aOnKiys6l7IQXXmCGrIj8Gu6ifeEvz/j+6pTiFTkx7Xrgzd4FMArGTUagUD0XsuqmcGaK0vvWydXGLNz0AL6nOAilcCnL9WA+5dvpv5ogLiP9id5SwJZdIrJjs2Z54b2zGVs103fKaLn8lmfIju3IdAnDQdNzl4qKMnBqgku4j3kohzy4NO6zVVl6+B5Qo7aBwFmLM97Kek4jrWE7gPPAkGGBckH8uXgb91q1oUf6kIa/Cdvgvwkh+5B5Epru66WF4cN2Vz+OrG4tz6mkjWQFSWFDwh5UaiHUQwC1xK6NHyI5UQQxSVVSCSbE+R9lRPDxMXSmGtGWeRl9urUvv72SbxO3tl/xrX9HQgsIFhoiA62eJROqNmuUQT16dMjA6UhlR1KQB2nyxp3v6ggJc2+I6cr8zmB1D0CYmuwuHHITtTOIELLxDp5gTnB+6Z4/s5fH4fX461HdtmhirdZ3lz26aoBqKiulf/yELUMJXmf/8OaBVag4KEmHCIRYPzndm69p7V72sOAFTHupoXzdGEpSZebjiYDwBD1FFIz2+J+LluoLJQb2r4UtVHF5WS8+nKK0z4J1HRMox6qbCEKFFBt2XfC5eAFS9dKeUCZXFVE2nNJSs2IwkMmvLPmhwHkCsSMZch0iIigIcYlSx0vnV+6wH67ZiVyfcthmJjynSqI1NkoaqEIv6epnHWN4BEgmz5pwWkCsP/z3z30x4qNtWno7U1+BHX+WxKW3A2CZd2TYFoiu7DPXi1/PPaxyeQzfog8wG7rR9b/PG4Tr7L/KlPfWD8jb67iVbDWFNwhH68EqYVrPjVxW4O0bojWVMWOBeWKeJxVAFGE5oojEtdTl1TGEBMZOYzxVEa4QYm0OxSTn4pK7qIe2kSsjLdoDyHaK2FaSFGwXA1Ldx2iHWQY/F64J+CU6ZWzugd+2ib1XItEC5KLIKoOyt2ObkpU+OV7rBOTTMJl6z01aIIvTHGAub8rgjqT7U1+2mGIXFJKI3vX/1HSb2vpCYJcLcnDiyjh4prvbqL38qiL7sgg9saIx6lwCM3sh7fE1VKirJmDF+uFD5REeGNbD3DNoL9s2KUmN84Z91dDJQfgD4P6axAV71b58P/9FrN3Myepnm9i9a0tCGtXnd1SZnwqjFeyrXOO5Bsh/w63d8PQDPDgEIOcCnw2OwEtHqJzS6stUK81h0ZfcfvlhPrfGly7AmYxYnOxKkG9givGbC0uUjkOwU9P1qxFsB4UKV7worZlxJO7FdIuAmix4heLq2qH+4GP6AWUNPeNbVmJtj64BhFJqUrbA5DsGfmPHPD210sfFsLr5vyJN866FttRPqVa+XBtJn1JuYu9A2GyqYDMguo4/GTHUzRmZLoab2JLd1fQg2a4W6Cqo4MkXCHM2Ye6DJytPDo1Ik9ik90R2W6h03Fpf9VH10Dm/adtHk58WWb9VBeKKTZGkfNArQswDcZ+B/VYwxi774okBKjjxMXEdbmUac6CHDGKkuHViQhvNIVOVXU09BRWPbdoQk3XVx2oGoaZbuPtMJajIdZrwLQRAxVFzK5Wr08EmeCqs8SvqZdwbTVAYwfu1NmgGP+lgWHwUaXp6mZCGuOMYSuuhsIaH61tjr9zDsamIcZGjgvO93bIQaKkvR4kcukRXYNX4gEUjIfCN3+dCDYTiWX+f5sZfeU43wr84nbDGH8u0MUBKUTIEgm4CIogMpCJN/yUB9CLkjrKkB0sHVpzBMymvFG+OEjsUFmgnERNmwEKeHjTf8lTwJe77B8NlxVLOwP93FWvKXv5E/3ajf/MxX+r7DwDI0oL6Fw+9RYehyr3VS4Z2SohNDLM8/MRgLmHz/KFnVh92XyXVp0IPBUJbczKPqODYMINdzq737G7GiofYHojlf8LR2Nhsk+YOtfoJwepd24vcQiCvHvv+ol7v3FCKDE8wH3Mq4ZhBGuqRPscu93wk6b6uPn1grqdkjy6amYyWYsoaI2HKLebPV3+f84czZvL7e4kouag0vHhYoC8jTNMs9O2FLpyy9Te6aZYJlVOrvqF1bumF+36/CMac11a6jgzeHO5nTE3yyqV6dTyAPwGZ0me85vbSyLC4TP7zRzrBh1AmjDQWFCwAo8J9/yiS6U+4a7qse029I/AWhii/o7x9GxCtLl2BHZB0+/kialx0eRmGfFAqKem5X+Itt8aHIYoUqDnqdoEdNfgCOiYcFLRlrl4uhIDeuuJDZlI/b32mLH8zJX8QcNxqaRXkL3c5FYWf3UMG7GYdsyGUjCQOHAgkONIptskVuYW87/KOYMRV1eBJ5Fkb/BYSNfcTwt92/hRGXhyvgvDJT+CJJDAzObaiTBOuCDF/dLjJskqwM3RhpGOJmC91nIQDLOkPsmfN5qr6xhEhpI2V2a77bJKjj7r4cSQUsbYkbaX3ff3qF8RvnZubZzDwuXwSQubltEXOJ30sVsshJYJSI+d7Pzobt2pi4EvawXKNVPs2usoXIFuGeLaY36+n2yO/+yuo1SUm4bpujiCvsld81feNwIroNWCVTQfrrpDNn590Y+iPjwoErVeWROFCqAXrJWGMhYSjMb8WsFRS+81lls2W06lV1QChRo8C39pNcyDuPXsWvkAQoVMEaYihFdGiWQ9GWNJS6kAQEHMJwcXihWhc8N1kn2AHirqtUYjqOZG4oCy0KwCYZXn+a694scgR5nTM49G4RLKqAOsxIUp4NBpf1gigfenXw4yllLRVqoCz/TvwnLvzznaf94B+aVjL4Hc9a/9jCjTz4Rn8ijPZv+qG9VSEgX8E9eANF9wZ2nZWKQiJO9uTq246DyEwdiBe7nqTbG99aZeg3LLrgUA1bfBhUAEGLgnFsIf2p75ctOusX7KvvT1qAMDG7soEL38hAOGAK+nxXy4la5n0p9+Te4w73kLFohP5jBEv80f4j8FixGpuyANcLmEnJMmJlpMWSVVCNvqtF9Qoow9lrFe2J7YtDvetzTE/mtl7K7AEMTTIGapjCSPLEKIXRIDVwX5xpamAlctG5LB176uHaX/I+rU4EhmwdZOipamkbAmG2ulUwHbf9RdWHYzhCx7zQyvv8Ycbk+pTu/3QUFUU3fUPEVifK6E2yaW+AWbHDOLiLXDTxiIipFt19U2SzJZJxCjlyCyjdGgk1TxCbwg6jWXbYnmb+enCO8LKv41qO5IgmIr+flPKvzFu4fqkFljguDMujo/RzWJQvHjI4UWm/+sSWPqPWBKimaIq3YcD2o0HujPAl4jSGPMXaUsGjGKP6xJDfQx27Q5vEYDSpteihNUIx5qQoR4D+H1JdOYhvaCcBz5GlFCorPayXotHgVeViRiekRbKEenWX7KThYtXkQZfNtUv6RiT3Q7JbABdEGjfwWrMU+bP/DtLyOtbbINxGjPDTIS45LF19GFtMyXI+horxlHNOuFt6N1sBKDx3AXy4tq6medyyhONheg4hRBYEd92bwYZ8ZDjWSZxew7BxjaAxSxAnyaHP97rv3PRRNoElddtVmNUeKd0BXbQBHtI8BN5F9Ki8amFDfexb+Q/uICHNkLb+hol1ue3L4kSf2FJkoP7NDqdywrDUTKn6uCilXiKhfsJ7rl8h2CLfFvfzhj2WKVK/3UFWvOHmj5PGCAq6dwW5gaj6qSXs7K/kRqM7f+QJ98TMS4CJVt6CnYNnyHryq63xHgXh09GWZJcENs0+/3pUX7GUA+DM9C+UuY6z3tJyWe1MVQNvG0kLPmT2VBl0aWm6zgL0+VZlZENLbQsay+8kgLISsLh/a3opt2+ZGU01UrSTEKKrbzeqeZ7MzwRjSpKUkexUGInn08eXGYXVuqWQFvRlPiJ7icI3M+vOcA9iKHCVDXMj4y59kSGeByaU6PY1jW3x2/B37kZqtZTHyW9p3wcu3996Y+sIoaf+5XrMVWhnr5QWwvY2UToJfWjIl8CCku1LDZTfBxyUYJZLNXyby2HTBYCfVpHI3C2r2T7+exjzOWIF52H3K/pFr5h+QvJkAbCH7jeOymAv+a+R1dmvKIqQYCNefnPPpWaEfpC/sJaqS0/wWbK9fN+dmvtdBV+JjCEmIEcjL36WuEujRQ9tJ/jfro9YveRj/A3d6kRGuxzvdpeYcYuQxUfQknuQuagddLblHObXh5ZkdavXIIRRkL7Yy66ABs/V11JlaPVr8A9lEtJFe2LG9qxxIsSGkqk8rGomugnfk9tB+nRRdYXEJ/Dv2svuIJxA7L18RuxwOOuKptzz05bLyLydmKzK7wFxtWaxFf+x52hW0+VKp45FobBcZsu+r6BnZSrh+LSseJKndPmTeubM865IT/5C4y5l5Egj/T9Oln9ERYwM2qvJ7cpNOvrcao4dajaTJ1KJG2IsbF68SSdlBnOFsy81U3eIdA+bMcscgihVPMWL7/lCjW5NuxG5Hnejgm/mFndlIOYrwqHvv/6nRmLQTYcaYzPdvLFcF9HURURBDhnShLnoPLsiqTlR6PgCFv6ESle7Lb0D3q30lKGmP8MRG6Sygwu3+bbVyAsbYMDgbs1m1YzMD3EM6a6fsuhMM+SxFUZikPnp8M7tA/zo4IqFjNTEPPhZjjJPanDgLA/En+FoQUgdzq7+fWtS54j9uK7/+0j+gZbbXvrgpBNUra2ywTKLEfg671YE3SNDjN4alpE6MI8HhTAJKwzsJn+otcRgzk3lBV5ktepKIV/baOdCzz/EoRE03Ul1OcqBtFA4CDtjloXwsW4+G/ouJcayzYXwTmE4IQAqBKxzKOZICMudr8RJO0K8GTc3Fc6REWw1QKDjO1g6NfKqaaQLfzzDUqV1JgW9vVZ3wYou/liZs71EvGJZrEk2CaVmQQqCN6D1/gK8Gpu0A/qYOl8Rs2I5N8QbCmueSAwTjwhjCLhX6bwDpuFWLLOSopSwPRK0InqYgkWAaVL6ZsPU5UEsgmasETgvtMKOwTPshGJPa7O99i+YBiwPpFiEzHXxd5s95WpcYC+00v5hEZLIUmWLRA3l0VDVMpyJmPDOiJHmy2bu9ns8bphruk9VHo0naSJJNN8VWDeT4ZIOOT4RkdnSWgTtocqCBK3h5+Efeus8i68PGMecTxcneTViZhZGj0MvuBIRFJtCWjF8pHjXBMIGZSUAHPm3y7Rdu4jqSMNbX7I10hNx8b1tqs4rcCVRg4oKwUyqXGXVFb2QzFAiQPdaDrAAfZIDNT5u9WgWggSYXsyqzpthkDYYDvKQeIFUnQNaW7SNQh9B4gyhivZ0t6iOGGjW8U/+xb5UBflxfUMzAypINxOwbCRfX4mC/ptxqLBs2jXZQmKalelpz7CPrO7Z3ot1hOhzf+in+wN5e/zEXvvC5F41YMVkrOjpdxgumhVUfPXCTBRQgdaZCWuF7vgXabk6rFo2OQWUVjG4hurDOA8o4u+NSZc5t1fza/vjD9YWrA+qm5JpFWa8qK6FEAFa/CmjeAOJ0VHpKWQK/5SHQ7J6ksfM0cq39cmEVIR5vp3R8IhSCflXCYU4vPDsFXsrLEbuPc5ed3eSTaxFbkjXMU/1Xzi40FaFvKOwbvOHsaVIrtWmunBmEGFbNQ6QgrcVuIkcbCNbgf8tiFwqbaMAmD+G6vPGJGfyv9pCCOVlQKcpRRAW00KIwBH+aKcMf5QveXEqKS8csQCENTHlataKf/AZ0CwyRXmXDE9GhNRUp9lrqIDjYXDzt5V8AKWKlppwa3WsUwxsaPiq8PfEb1rFZey5jVmX8q4szrWCuDFbkhkpKyheqbMHohR/klIyq8G9p7wSHiXt6Zb8q38TDLexVws2bWfQc9/oNzaotu5YIHpiZ6X7oS+ao+z3EqXDsML8V0Wy/TdJRjcnM2BrxfeL1boGQ7fvKOJr7iPc9x6K3ybBkScvSyz1+vsOqdLx7JYuJ0UCgpV7MelIwU0sGawtbgzLuvyuIa/WhslFHKrI100oplC3XXB6RNUlx+YtwQPoLMF4sGSbDwGAEoP4XfmsSyIMf0pyI8KjM7Uz3+4YQT0GABdWgc3nWwIkP6MR9ylm5lOJukyVZegDp1TajAjjys5ntWopJrDlTlZKXzaICgRRggIyBq3lTCSILCY0LnrDagNRM85DClaBYjcoyrIXuv5ml18aU2GHfhdG3BZdbB6EJaFIjYG48/jViQwjOBjrjf943fiH6VvRgsY6H91SSw7iQUDQ+3EF8NQm9R/tU6+5B7Qw6vI9N65YCVkSw9fqhKN5Qcur+lHvp5ualz1DjAlgTPc6oDKBptHZYhI+TsMBTxC7aRMv3vlFUAK05bfMgSveHe+ivYIdoz+dd3EI/1znIRhvEeC2s/3vNE4T8AdQ3OFoOKpsxKyyxafOaiza9id1vZhvFeW5Ujn9HzxiYl+/6ArHR0n8V3fq8Ai5lRlUBPfQXB6X6sLPXvgSOtJ0rpvLoBOjYK1WlxWZpyjvle9DwCNP5MMhoPbDlmuqCgQX7q5UFRw2VkQOpdIWOXsXUJ69KbpXXRjXGMO4vhGAcRSMQ3yAjnFJ/jwXWolw8+LmY3j+ZZlSClg+8GrLhrcd+ORMcViZi0BUVGMss7z+fojer4fhFWmdG0MJ2ba+hF9VUn6CgIDhpbkcmyZRWmT+43mtL9YBdq7rVgcLT9L6yAdVUAzsEZSFXkTnHfT5/xmaCHeHLHtWO1CPK9CogCKc5N82U3goViim2IWvRZ+olLiQgBgbBTG2w2hs2kt0RSa2I8cbllEFu4JKvUVTKGKRXj2U2iw3bcswrztrX3ZGi4ZYs6e0mnmHnoMnYdeN9dng5Z9TvCJm95RVVBJcsyhegAtA3ixBHh7fjwEuD11egZJ53zb9m7ocyZCl66YZbKMG3XUdJe8b4WqNp47/E7CIjAtBNZtXKRQM2zXKGa3Lti4Zq013aTwpDF1Ks5+d2+x3fkZ/tMHCzX5HxlW6mYpjfcNoH5LDc4D8JdWa6i4qX52rr1oraWXoP+4ndSGZBiyuz5bJOtQF8ZOPBEhcSXz4EL/wpXcEaCEoqKHcE3rSnf9VspMQWzOFb71L0r5z4nJ+ECjtil8oRrT93wSkHF7ghZGagEG7Buu5aNVFW0l259/95bP9/U2ybzc4o4Q+yaAErANeIhR2rLke8yeUu09Bv+3io2u5UZBE5gFg/5GU+OC84MlmyHJ08ZzOORpMnttblYR//EgShvA2DTBcXqmGtUhIMOZXVtGzRZVh8i8179bptO/9RX6ZTnkEiPkvsTYe7BTx39W5HhlPY7HL7zboSgsSvISPCPC2f1Fcoc0Jidhux8aSAPa24BNl0SLVaTqtZFeTSdvzsmTdanW0WasZ/3MK7YYO16YISxLCJ+qJPf1A938/tbqcSHDXG4oTXDRTkzVlUBMnIaAdIkbPAT+iKmKmuUKYKxBafqbXFiW1KKX8kLDR8ruKHtPmX3luMoNjEBG6ZJZe17F8bxULDuiv15YvKfbF3F1cor0m+oy0GortZVuf59MZNw30ieS6r3UvlLz7PboARRHMnFZkT4A/YFtvkkeGtKeKQCx+OUKkzToRyDCmPiaamYkNM2iup8gl1UmShA+TYizBtVpDPZWFFBi6vSRdl+SjiBUcg6XDa91UBmgvj/OPaD+yBAitBKbr6YGgV9nUzsvgxZFanW9CsIISHkXRopK1ANk2+p794LWoNBJLJTSd++Jp18V+3gFPq2JBpexxQbSqq4ipLjg2XV7G2qo4fUgOsKB+802IYMA152sZ3BW4G0ID+83/vC9fmmpibMOKgHmYCpgBt8I21Ps0pV+2QV+pL/hvkJKDSxPNIMjpwTYRDre9XfT+xHMbapKi0da+FdIzxZn/I1atsjV8evvi5icQgTxzGLodBNPy0frLSNfIRd9BuKnmEksYlUFplS70lyt8TRz/3zHrW1goUezCK9JX6lgJR24wpIxdj29qKn/aZ5pqiDOknzGUu1qJhR1KO9hoPVoKS+ZTOcr2bkmr3ZrqW2NozRsI7nb7xrUpxmJXu6fdvAl85NQDPWDAzqQOcpSXcOEESoJNOozUFt4kj4FGjvXfJn4qEjFy21LLvE8kz/k1619Op5o0RzyQqbPuHrHEZ4q3KIkE7XsvnFsmeBVe4q5jQIlfln4qTz3ke/nyu8/H+gW2MfsNycHVGLK3TIv9py2usUb7EEcs9QCbWEq3ZyLBv1pDphSAFJ9XsWce0qQRCNw3F2rkaUktMc91+rKno+NBx2mxEgXLxvukpqdt9lnDgLi7X4Kc/L3LEu0DXnTsAshOQ+huzk54lwQMpz5WIy5g3/0JnB7o/iLXlpo5MOoNzFnTbjMNDqT7mTHD/ggj9g9VZCvNxaOr4NJ+GGIaYJtXK/u68OS4K/d16iZdQoe7c1hH73rmhHi+f4sUwLuUGTwJLfoMPslIH39F2T2iHoyq1vJQNXa7muy64kfWQc4CKjVXUYfzU0MbpUUG7AkjXxDGlohMvJs8nHgyT6xvaCD/FI2/LoqcyEbao2DtQZFTNAIECmsLhB8r5U3JrHanNZawZSpZroJSxgvsUSi4CIwrIfYOVZzsZ4n37BoE7tGUiGVilPdcaVZdPK+oIi5LKq+31YJGfxPxFj6fvLhOc5cUyHQFPoMJfUu9ExXF6m8rJmxG2Uwr0N51C5JGGHXhaCuCdaYxYnsrhTArxJvppH/5D7Wijnv3PohlxSPm6HLYJ2YWSMfsJFfqxIntmSzYDvL4ucjlxPTWwvSyXQgzG5vNBdKiTBAxchzYa5kiOwo38oUKFM8FTCAEs/87N7tiPabwrBIBo/MTTVlvl7h710U3RmEyAfnyixC95hJ/zqBd3yH/YYnMumCN9ncifz04i3/nWBkLvYV7tBxKBc3097TfbYK0aUia8r3bXPkZ0uUfPEtVUY7Y1lZf/2PH7QKakA3/pNa4L0oC/mgwntAiqqfBN95Y0Ds5ONy6aF7G2Xsh2RU6qf78jn96G1jCDUz7PR/NbjWIcR99H4CaEhp35fZJ/RZMN/qjeRPx3TokdWVoDCJKUK8fDaXT+dlgZrbISIwBG8vBvHQ7cG6cro76FpIFGf1RgZywEcLyTTwZFd66uPMS8RwGrdcIs1B20TT5ca+skP4pgQkIVUjvgsskRBSNHZe7vrDqTSok98ZUABch4lPwY8xrs5T+wUbZ9ptHTa6fodyxOk8kpldoLF/H9DJYuiCVYPT7q6VRndHTQt6PlDYfz7uGyx89UIo1kgaY4BNVYPp6XdLzqBcMGC7Sz/T6o0ejx7QGHbbaJEf7DWJvTOs62vpFp89838po58yqkV0sN78KhhjhXG7IEKQ5O9Gwan7y1/nBeclWIRfQj+zObchj1OAeC7UFyJkOSfAMQS0aywTd7hiw5A/1Jy1mSNM58niY9IGysqvt2U6NBNvxfpcKvnZxIRqQNh1aa/dfi19yINBIMeegHIz5wyUVIzCBCYb0N+dnSX/Ft+W8cx6295/TSlhwjARUaMVpvE0mnvxVQO/4VBIgKakYarYUn3H0rapEDj6d+As/dTIpVqGJWo+iMM/jCPftMQbxt8ijeRR/AKBsem6AQ2m7LBykt8c8D81jPQHYgFRXAmWCFu0sZHfXvE7C4apowAahYh8nQuTNxiGW3wU0pTj9srVFPzL7Dd6Lx3YyVAA5y6v9A2SKSkskNcwfahBZfFYx26us5czeDZeZjcN4KrIms8qOIoOwPkGSZJxCwfpiptLDQ/8f8vLxq8UhJA6ixXEI3+oNtw+/pxwqyFn1f6idw3tULL4QU3s4JJEQ+DJJcps4ivn/znz5XUplaShsVwE/gy/jIAM9U2ODXsBJDl5c/0tf1Ae5EAfj2ZzMi2+89PVDiXmXRcEvwb8zido+ji1k1zU3kfRPqRsJPFfTsj7dq8M43uCr0wrxAHVYbMh1fV7tlcAwx1sk2KR4YvD6vuITnvIfWAPj+chaVr5aD7Laa/R9ec97UOtMj4cT5Rq8obfD9gAWsW9STaem2WU4i2rgzV3b4eI0IHzNvE7IWIFz+AJGfpspISzGYrP13knURCSMsD2s4Zhn8VXGxMov2qTM2s86TZ2D3DDVt9ikdw6yHEOYccdTSs5DQEzK2rBAH/jU0Oo1z01qJvYKkQHxY/ui/iSL7sfNW4Z04aouhz3ffppUozoYtxC97lrpIwt2UhlelQN1tjZw2hnHYXjAgfJsos+HFvCm9L+ckFt7/My4Wcr6NsuCXjC73lWXhrutOdAi7GJBdnNg9shE11SI5UX4jCs8qSzOHHF89hdO9RS+pf8gvxJgi/UaZeaIbDYwMr6XgvzuF50EHOZmePVuYK9+0jD4yMYtVS/vIpjSfIhTV1XBSi1MIOzrYH9Z79rvUSfcjQTZzOSndjqT0ULWDFfaqGBrdcbbSVmrWn0VkmxhcwQps5WfzAMUJY0QLvjX8Y4xgPd034JO35D93n2CYl/6LeXcW9tshFW3JHfuLgtcBIxFfSl5iV6AsKWp/jchPa4kSVlBaAHSsGs4Cn3HK/gCoCk9pTlYxvKZhVdGysu/wxhIXE36BuqiHZu01GmjnCRJlW1CLPDEACqnPxsDDHt5ikDgiYl2/+h9e2PYNaB+G1oEXxmqbPFDy4VAO+3gU/a2qeiZRUOXaA8mMRO6d3j7kTepd9RltHk/0DCUHel1UmdvFH5YvooxuningUSoyRniBpqoP/PSYkGcFL0705eUwqjWLp8rD7jFrj14nywh1qfOIOr19GWwY39H11lmtVyhvsRfaYqHRserl0dYlfQ6k1JLBmsRjrphKtOnNCDB8wRcm2G9uO2WggGsbVlFTDNItqN/5oMykYqcefvFy4ChOK4Y4FHFhz7wOTX/b4Z2pL36BGe3OJQyJepSn30Um/+L0PNfs66UO5aPuo2IpyEpKnzT3s1WjOUsFHGb0t9jMUDZhKIR5RikcG+ViJvqd9YvSPJxtiR2BHGNykkoXj8DanTYJz6o4WDl56oTf4r4h2aIeiJbfs5/sjxRr7t1adKlNYCa7bv2c3rB8mFdhDNblU4FViMHfZ+xfy0WSyfyn0ND7GFk85kWhp609NE7wnDkUbAbqTonIRtxnTiAwyxvlGYRRz+ZkTG5fgjVl9MqiQ+LAx/Rcvs9+zQZ0/Jo+9MBO6ibtJAsD1CUu6qzf9zWDD6GHpPj8lp3JFyPkpDBJMDmSb58ZUknDTdfdcVs7hX/KbZspb4JUg+3uF9o4a+zlANGfWOhhlQ7ObJ5FQJM/KAwoxOu9AxNL3hCvGDEE52XQbhc4PXNteNMTKdnMqsnEw/cgrGFLvi3AUEEdyv/6tPXefJd8bvXEFD0kRBHiWG/Ju10bhBu0HJ0VNjXY1FFclE6TNn3fsvCNcG+jJcqzu1yXKjY/Kn3pw2JRipmwKcUPTxz6eztzVwsJ1GPCnRdG//DovVTcH3LRmJ23zNM2h4jEff+LMFc1WFGr+APWvIOgnhnyVjcl2gacS7T/K1+sxvWEK8vQb64X2Z1uKZc/CNCM5u/fuBSX02+zedgmow8cDBYfHM7xov/HIbJSm6f8D8EOijraf4i/q4Vw1Xy3dIYbiLmdB3vY9m1/EygKxu7u0jV1HLNBWfP1GKC8xeIkAXjXQbT1iSz8QAIplzSRE+U8tWKMXVeQw/9IMrNztorR+E5N3dMuj2OXxuDjG2R66cWiqckDKfIxVKueygzBY++9K7+hiprnhpLjwrbWJ3LcRJ2J6HC6Uvd65fD5a6OheYq3Y33yxaueznq/4VnLiQaErOpLumRxiEWTT15lA5xEhnnCpPu8YKAr+xh/Ko2G5BRnSQWmWElsi15KjVjpUSZ7wF6D3ymJHZBiRFTkUodNK1zPW1+y1KZmGqgsOnXnACdZmQ0/e/jLP6qr9m0ON6qAm1PKIIHDo5orDMiiMllG7yzTYCBVuqLjJ4xNuzI3H/0On4wNe1esyCr1TnEIdf00eWsw611F8Z6DJo9kdhXc8xBU7HvleRROy6VBNNwCDEbmBaidaw1HPcJ85sqYGWsJqgOrB3f/IH4mj5fQj9pY/Yhj83O2bFkJlAurmdlk8NcLPtt8GqPx0J//kzeeciE2AcsZb8BukGdatBZM8Rr3nVJLQhMyIU3w0PDCNkDBHARIn1YPZe6NpaSB7LZ+4duM2QGyUDje2e/xAY1B2u2LTA8rE+3+SSattcz6ntt4a/uze2ntKiBUYNGpAuSKvuPzuROzNiNuqSdaO/M1FYUiPXH8FUQJwbW0ycdwqzQN/ft2pHZLKhvDWoeRiD7wW0ixyV3LOAdqp81KTIOctPLxXVEybxSKUZwoSza+RmFg7boI/F/ourZ56uujYzr8TbdadCppWhiD8Wi8HCsgTE4CiVrvUn+DIyyyRmIBG9xOf/LoS8LSB52w9kjMnO+YFuio8r1vrbptXdsiSkQuAuakvk3Dd/kXaXmNibfBVbJ+q7p/NZnIIUrNpnF9exlN8AfpMlpz7K8uaRiHE0G148KzOjquW0G3YQv5gwBbUsKIn+/cd++ROdT3obikUFhzR9eQAx/Wp86xQ8Ga7k86CC0N9cDB2XL/g/Woe+jysIZ4t0kqmaBdDDsvB5j3wBbl9ZgWTvB/9OFjnMw5kupB+yLwj30zPLRfKjwgTCYfxKuWOT8O5KGcoXAmkalH6KgbXgtsU5t3mBpunL7ncmYCEVSG+Xr+U4vC+eSgagyC8tJZBhtYazicfUVywjkTxmfNYZ9szkDF6lZdFFrppUSr4SYfWzdYZlg+1XUcw2fUeKLP3twxVuOEujsBRsj259+r0/uwdRLPgqjHzvaQ04IFayU+g7/kl/LpqXkDpcQ4Dmgl1Me0zmLBynSWDwu4vvhBzP35jL6IGfTZAZbdMfAqEuroW+koODPMTbSi4AmpQP3nBwzV6yitIdDU7f0VrP9eUmMeQ9dyBP0JT/9O+hIjmJdfHLwPhE6LOr+jIXeAJhgBX0u5QQ/WUaGwxyI+wKzN08L5BO2jpTOkGkXvGZZv14osRcFh1GMFidBnlUVE6O9tj3uSx/7//QgYiHI/21XaPkhag2ViXwQv1akOGur1imvbAoTkkQLh21v5p0loKEz/C7jPeJoZepbH1U6M1kDvEOwDgc4nRJmofpZPabB/RvfcbQcBFPq2zCX+dmU4i4oR8u9WslI2DNyjPPdo0XEY5L1NQ0imezAtktVeQXBzlET+1aD7+50r7E9tOSjR0RdZC6wZ/bYBY7NB8VVT4ehzz7I/17mC9fZjGUGUWpVVmYchMTdkRFkB/HuAz8GxCxXbNItxxSoWXTL9pRZwzZVstpP6Jpd59uC0m/P3d5zgkVXUFY6rJVT3RD951Cw6RnpHF/fUOytqJYfmjmLbqNOYklJ+J/E3POee15Y9HhjC6hHWLrQ4DEN96cRPLBSfEkwNvPX/3Kje7qIs/u0gJCwrg5Pnd7bO2c0SP1eDrbF+T+hx3aUXrxUK8dpIA56KJAEf8P+IDdt/Ot/bcRp6SB6usOsd04O37UHajWzDkdXO9sgufvid24dF19m6u6/dAdq1eByyQdB42SE+rFxn4EAJFjffcUaTthPoTCYoMVwNpwbVoWm2ZkhRvntbPMc/W3B2w5aZrfI+6HzEEdE6AcwZH/o2bsGfJNQunH0po0/fP2tkn0NKt90UXZriLGpot246UEM+fS67TLd/7iS6I/CwZAbvaehN5fml9YC5M+iIQX79cD2oo1E68g2qSvimC249bSl7jCjZmA4UTvR3QVOvjzL2wWjFKOFFgHGOOnTqPWD5khIt3BXqcChW9tT50/i5B2ZBOUXHjJgKj1YKCeapG5XhGUEs9SJrmSLSYQrOWj+2hiye9vH5EwhpknaJDeqs8P7lems5SzQ2d8yT2kckb2Zq7Kegudl2dnr9c2t5ExgIZMnwqDGJLxR0IqYYwTZqIHSizDiHvAXUcfIw913Xdcm7vld/oUdXxfyQytFeChqWy7h2MMUYcoqqnG0IYUEL1H2IbdTSWuBn7ZpvdZ7nffZw9nOeTDvavLTGVhEo64bpmZbSuAR2cz65Dw9rZUqKzQ8nzvZRtj0B0a1JqXlVd14T/farUZgyNGD3LxPZughjqoiss+1qAMkkdCuyIYP/o+EjIcv5FlDWDt+PUyvdV5rqS1g5nFhH9afMiPagXII6uGUAo+2IS1kgZbMHQhTcnh1uX+3XML/2jFvJAMbymhOv7HNXr4+FcKy+4sa/zwF3xGGBgM6+fybfaqY60QttnzRYWhhDhZFmCMzXZrMWJV42e2Da1oUpL6cnvbaN2tUh4Qa2PwCmUQZvBX+oaDH37OMV++GoovTMiT1baWxu0lvhEvmN4uNHK37gWxO/VyBnH8hSnXYpZxD2XozJ3/K5PKsM8wpWVKifSKYOfu+ONL9VnksyiCMLNAiGFZlmwXF1I5ItX4qn3EbPq4w1XtjLI+5o5Xs+95IZV9iGW7/qQuFsV55X67Mk1L57e+0QYicWahWPd53yGq5Nwf0g9jnNRNysAxEKf6xacLi+Dxf/JdnRD3qy4kqm1h1kWjIGjq7dOZwgTS01/9lJapJtPx4Bv9/V4/nolsmDrdrJY8ARshn1kTpCFjoKBA+zH3VSRkJZbdwMzsysG7xneww8giZ0puD/LQZZaBOVk/D0WNN6N6z2EvQiDjdlQBaM14reeCpcAVS3ESsOukxDR4lGoyaLsCJFSUf/hJrvzcL7SduuYjH5V5hftaw/GupEDEpuxLRajVHeGVAHBPRHiwaFSqTmi6r7sWQp8lVVA74lh84MaF9dXtNI9Z+yP52OPdFpwGFVvShoyNFM09dH3H7qM50mnVqnr9e6Ut1Jc1WXTmRLHkof/nEmWOAjAHuSyjLov49eW3m5+P/5yEKtY0JgkUQPYInnKhyC0uxv9nDHwFfZd2zCj6fpnSW6t1pqsO9B8xN7YiVhm94OOG+Jo/AJptj1Tvobdyb4C1rMdtQE9jta9Rpqg1zE0cE3ZfhqGCUUXDyY5fMQp1rEzZ5sejib7QuXvttx9jHS4YX6UU+/jNMHNTGAaWcNO9Wd2wBhfvKU8M2I+teGIWCFDQjddZDTDUcasig7eec1mED1tGdrcH/1vAQq1LJzehO15VMky9PXDGb6s0/rOHJ5OUdosFYudMD7J1ip8Efcvi3Z41DCPCGbd09yeqiybh/iWCpwFqEx9jOYuIA60WN5b+E9IyJuVPxDorn15XS5ggjaTEZEGHNOuU3D6Midh2H/PP565xibDC5e5Emx9GBQJhFm043/+zkUJ2KFtUymtoLvAREVNIIQ/HnLiqDTfe172M75zh3yZ4tNeO8QmoYk48WgbkMC5d0OH0mJrMPIE1n7ZsDUsKjGlUvgD8qbD8fZeyXos2sROXt1wpMsGfwsUF4l5Cl5PwQaTCeI5q+mLvgNLVgbCt5O9f2pvRvKqaCORrZklH+x67529MvSiDFi5Wuhw+8YJGSN7GT2cVH8f6Ck0ot1qbyN2HqSL9fNaRl2cmNelqqSD1T//x3WGZYxEoRr86EEQOthttR6YGM99ITPJzYCxHMUo9wk9+bsM1wZkok3CyCYGVnVN6WhYr4+y2HLj36dgNG1mOUZxHfqgEZ/stBWR2aBCCaUwqfUbD6DkZqq/1+IwFvh2gw693TQUBzc9Hz0m4qcJH8GPX13Cy4Jkr6cZAushkRKDBe9wjcyTAHKtpnECdCKtOO17m3xDaJPSCoZYu43esMweKJDY2fGOKml3/MZYMCyaHdJm0Y0W5UexAxnA+fbOd8x7w91l09q2A/3b3aHSCiIs5E6D8+jALbyTAErqd4Qn1bIqcOTS4/yIdc9XZILUebGIBgvUVGbiGCG1RMEXw4Do1P1s7gSvUzlQCOHcOrkdwS5WeYlKpDrTsr3dLMtGI0WTApSR78+CLHeERpnUIeFPhLOYYHFYXrY5p5kdowT/xfRVVRlXqpN5TEUMqSCKmiHj/IN5NdXNtXbH7SEeWB8EiNJVvN6dJ2Gu//pA4mUWPbVscvgDNQvKSB1RG7ph8mz73SSqQYwKrt+f++K7VvlRtGkD0Vx9Y5PLteBfNjUfr5IvKaFMPWmUwKR1yAVTQ3z9zj/tcns1t4+0znUagnvpDwELy2n1fzCU2ECY1N4QZTz34XG78bn4mT3Z/lJ6mdpf07prPxTvFBdzeaNu/y6mIbi7ZoKOlPUaSXcuZ/vMrw4WkeaFNNuov65sFt3Qu5stWAjZBTbmiHd30Jk/XC3CFdr6Lm1UYJmvYJ7eumVVn1Ewt9N6RmObNM/KJ0yZhv2y0qVKMiWP5uE1UrAnpavvUmk67xEoNZ6LIbMClxxsYhsHThUj/b9lYV3X3acv7HbRQ86wsBXW26OFKi+YiG8aGwfxcFoFubCiwR7LENF8WgMqsM6jrvtJh/+D6buW4xLuQcqi/YMfbyKIPgFI/Zlr0Vw1pX44rZHNh8iuyMr9OHfB9KQme5uDeOVtJcwzV62kCSMfPjA/owfP6ixymIiYmma98g4eh+hsRyBuKLWK9nPcKKzoywOqod/E/kgvNIKeMPjN7yeY+4VrctRn/Hfdi0v1YclhzvYiL6HB9P/qSWjoyUKNKIf9Kfi6HmpRp9yICctR91ytOxifYdXwiJuMK+FjUCIaRch5jqVZcUUWnlfcgx8g5sn2U1VCtGcoMOLTyL66tChGkGpwM6efSntAnsU9DCvwEw7HUTksA1tvd6ey2fK18D1h1cTPHvBJshbVmgLtc9iVyJTDoh9NO9ETnzssWYS9tAqjkGyz6ppivFL2ZFzoD8nk/htTMcisnMGk+kp6JfPz9cTDKfEGRVmykuIBfH3DJImLOUOnIFb4nEZMPtDr3t2oaO4BIvBrbuJm8RN30WzRhWRSko27g+1qcV5bNQfwnvLtcsW0CdGfqSsi4cu2eLf7zDmRi47ASUHNkGdkVTOi2a1pKVY6U+oYS+oKYW98w+YoE9ni+0iNgu17xURy5l4tYfZLni4fMJ2+VaywI2ZQTvXT1dmWj68B+m+tKaeetejFT+9edO40Xjiw8Vtvfs9qGpOkmu1XJ1UyBRqjuCIi4vP3b9yP0uWFy87YoQakhygNLrKhHdIqf7DwR0/9tNhFzCSRdpq6r6YOvJHo8eMF/mZjW1PLAf9dSOFyp+S61ZlwZWwqjPC1bXpAQJiYyozDIXfZnr4hnpNwvnss8u5tt8UjaW0bAJwmnX85Dyv0yDuFEykC1KZU79Bu5LL6krtpbLZtZaoSoJzO0cvhImAZfnc6c6YwAIOSxSITDvtNJ8O19tUYDY8s01EBbhpAyBnbrdWQLibrvfGXsQZrDmnpMmIEZTAQ8mNJfzDWrdEBORRU8aTvSl2W9l6MuO31fFaA/uYS6x5OJq8kLNAOd91vOxD7um9Yvos/6QIDPnKWtgJmeiGyy9ikXLt2+yX5UHjs1XMdvTR5CRw/OY8obGgQqIQ8M0m3u3Z8e8u2hNbyborLTgpskqtjkmt+c8Fdf/TzrdROXSNWZvciG6Iod6+4Othdku6buUXc4XWFMk8F/9fOXCCxnKBStSym/dBIfWOElM7Ey73RSpEydMa/7xGm4ELbjYr3vDcNm+yt7oBs+8ucMkilnm7xTya8lG147RobCWWLZvDZ5qLJOy9IIxclJwjE/e1UpSVjjKey7oY2svYggzorRxK1gJxmAoAAEBL4xwpqx8N9Bu1vfE8c8aGYqXzz1Ru0RaW0tM9OMcUNM8wgMRIyKoHfaelykQmg+MF27qQQGuOiIuR3dh0oJ/w1Fn2ZDEzAbtQSqqegfrugKcM+phJkBclaVNkjiU4Z9LMlndv42CNpEijWLvp7wZ04JXWxUNqIHR0ApNCz8zMFaetM6I7jugGUb4+aGSfEAZPoaNFqcQfXtQOqjpvDq4+HA9OWuOaxDts7MrrobCn0jGx7rOhp+MazByI2cDESX6cwAVbCzq/RPupyWFYt81x32yfjmheddUcfs7x/Cbzby0+58x4vT0/ej0tn92GPSI8Qx9Ctva6kuLuUTXitKDDO0m6baKqRV7e9WmEXAO7ucigZrY/HOIZdCn7RTnx+umdaX63kgM0s/lhNlpTJV38+cRuynELtTWFJj5gRIxPOyVnIl2eyRxPhvadCe+1gSo71EADPtR4123O6JajlpaJAgqZB4qfby4hZM1DWWFSyibi2tXQigmdC4nfNPoS3ufuzYRUIY1JtibjyHSPQ/V9Y//xbMRSAdKNzYLGeDyQoUkjH+9nCAB4YwiMjJXd0FBemwU2NZQ8nPptz3+Q17Piy9KvPhSq4X4cAQskibawrShE95S7ME7If0T+HOp7KTiVgtd1V/8ishRQi7cpzcHbuor98ibRKDgyTRl5hfqDeYLLNbcMrd32q7Ne4tJpDE6Cixa+ogSygIQYl7B3qq6hajn0d0+MWvbqiqNX59N5BB+C4HTeMykCMAhyUMWsocuWcz9qO1pMWxfOrAbRmEUg1xRTeckFu7L3mPRdFMAt1awGAXm4tUOCLxL6TaYIK+DpXcj46gHH5XxXaPdLdgfN1jyJwUjpbKrzo+d2t8ryYW5ZNUYu3xAf5CJHw3mEz36XLCFC6Ai624JFXXIOaQavYLn8EC9J+ZwNqxFj8MGuoGzvqYfbxTRJHInPGl1p4/BUEBViR+nj0Ol16stALetMFwwP26u+KHoEdGjJchMZgNFQ0clRaIDpWtRtIPR211eV8bhdDiG6ZwGSZYVh5Yd5m4gaVWj2G8FCLdCx0l4745PwKVuYF+MxGdQWSbKaD+Aht0VQyndDDZ2WCpn+tXRdRDfvhPXjwEdJmMOJTxJxdS8X+/oGPi1EsSXwQtEyEIxoroKJZvd4XgX/Ed3HruxUFxAq10/gS95KjlPSi/t3E+CYID5Tva7qpNmpXJDXMgFf3fy74N6sCpp6NpfYY57spcGDB3dZPp0p9kzZqL6dQKuoQcT8CmBjShDmsEhfgAlD7jEFpDfKMCpGT6YrqAd9HeuL9Zy/0Jc9uGbtYg+yvGxaijfn5ioe0o1I2P7fTF2nZgeqHqeuS3TBygXsc0697mI1txUuxLYq/DtWkqJp7cgiHhodS2tPaHrp5+4U9fNGC1FdrjPwikhgJwFxCZ7UHiKWVsdNXvk9qb21gJTDPpVi95DdVJ0ZiRY+hekj7Dn4i5/0Lxa4XqbNQO6Zjm02A70OrBp5B8P3bCaQP1bxVQHZFmOy1czK3EegBCCtX7Yy4CkCs37jLNxJQgEm8PZdFL/Z7d6czXGUinRac5PYk/AfV2f8UnouCf7C726/frQ/wzBDjkU550+hgps58k7l5Pmva6cnZJTZldYSYExbfNGERxDaf7aJbFMaQQap2n2/vyxeAdFqNNMJJVo3VYsdCdhSbkbnLfHPhXhaLciLN+9CBfv2uANYgNHvTDIn79AnsC1+26T7OTLZ4cpATdxf+aJaIAuzha+AqmMj5UH48Z0RsY7ALlvQYvvPhmjM8Q2v/QJjje1YR+5qb2B3oauNboqZjDug71kb0zjbDC1mhGwX1JqAYrsmktrNm7bUPprQfxj3m3F82+MII4HWmCwxgCyzjen2z9oa/4MI7h9D+1a2xvSxd670s7vPjaeCSng37TpUPuXFx6poqlMtZHVLKvORo+Oy87vEqY1ROxXQXtJ0Jyz6Clg/QgH9wIafZrBPHrj9TshKzWTvXDmqj3ZHITu24FYLz//tDDdvqwuFWGmKEQLfewfPYMNlMQoY9ZXcoX0CVCViYWAHYj2f9wq99IN3BhR3WaXKOi6im6qjW7lS14obDddHzMq52RXbardpCuGWc0C4D9ejB272ZsEuhMC6iQrAm/6ivhlevm/tgTMxZrFrLDKOKY3cpKM9BJFRemEUo0aHde3XGBLakOzWSi21WbhKBbAABAAElEQVTaZtU1Hmxkhn0xlRdizSM8OdQrxTg984dE5dvcjBRK2KpR6Jt2lVCKY6tCZ+tkbnvxD7TsT2hvsQ7w0M8NJB7XOXBLeT5REAeS9ZO4r7EhgmcDNh5hHaVW8DsSbl80OHCe9zupZsO5kKE/cj9cWebcdT+bVDmHxD7o4lRFa5CUO+WVTt+TSemkLlq5FogquyPpIwFwRTcYSaIvWTV5HmO3lXeXSfvd5rx8Y1xhfiu+WLS85AFKw8gIoI2JPRzYFIAWarTSq6VqXawR/pr8NvksX5JT2WUUdWhK84jd71kGCWlLGSFxYf7UuoAxQTTQA1k14PmsOmzBqtyHm2G5mTu+gDZdH6MYe7HgEuL0qQwpNAeXoQgiiLQlLOlTrNAV1nFynQz412CvFw1gLfC5pNK7bjwOohAu3Ktr+UA73i+NA7cxzNfvoIX2QGQ+MBhj3IuXlPhMGfac3s9wMTzSoJ9ie43qG6uBaP13HUa7KscFizYsovwtqJzCUlpsqVlCjveCkBp1JB32gEuQzjou7qk7sy4Aa4+ZWiQZL06X0YGgb/SIKgFN9vkbYMmOBKrD8PczWEVclM60XoCrKs68WVbyD8SjdBzQHfwKSArMjOuQnXt5v/QiOuwk/JlUVRYUdGGUp8uYVabfITefYgbkINFXGIZAaHtOoPyxTQjuYrJSUmTOIkAa8FvbmPdvD6piT/Cbmp5OTIVwc/zQa/AtHuNt/uFHBSUmX0vhwfocfF0FNGM1l525rIdhLpgXZd15DdlYn0oVsj4APWRbRKZxWviB7UUVCYSWiUm00klq6h+y/dIneC4br2kBC+nN6ICc7TH74ad+T4qlCD8woqMdw4cGw4+zrC7iWo9gPUP+CXpedW2mued+xhAiLxMaOdy1cm1Jq/tVPUmk0zNG+NPF5G2Mqgu7CwCYRFFqkCc+1aypv3G8fzrPFXalfLLdi9owf9w+LRuosAkL49IPgBMWWqGveps6LLL1B78kwqva7JFkoqKxLkrVt63rRmrvew6l7CBitLSeIJ5KMwhuWwn8yf0raLpeVBNQZZDqY3IiW+vBxtkbrJRT3R7Zm9TreogPz7/3tiFBBqCubhshrH1CqhWKYaXaux9D/k5qaaVUzbVxFMae9VnqfkhLW0AP14mUwm1zygv4cRoNRburFBD2YVtcp16nSk3O1f735EIkkVV83PWE+ljBAGZDHV7VYk/Q5Fad5rlPgpN8QERLaB1Alg6Q5qPFID3b8n483xKUtTi5Wb7fX9v2QbBRUZI2oRPQu07Zec8aMk4gIDG8stJywzS0IOCKsq1hNy2/vET86sMzoUuacHJI3TwZa5FRLC5TyigmT2xO+ZhY9IlT8rRQXDJ3ODej5BH1erY3DwzmMYSBMZnRaIrP/YQFQVmSV777PfT/dtR/i1JlViL95sX++rw9vyP+Wn/hnvGei854v6Xl3waQW58GMLNGejO4ZnTzS/5HbP5nEoAb91axJ3XRaorOMF5+kUHSH0wO818o3w+nNAf736Zy6RYcpcGn7w3LwT1ArzsijdL3Tz/QsSqEBFKA0taW+kluLS/anwjqQLH1oVSLatb8ZAPlkYz7yCMWg44SmuQ+1xnCVd59fEF1vBep3aJVFL8wgqV7A6Y/OV0Hy/PCtLau//49MavVnUkTLn+3VyLtoIK0m9pILuYRpTI8cDNYLxI7Wv4W+Fxkd9JYn7FIk6Chr2qWXd93+aOHYHA1XdtFH7q+KKfl017fZgD4Z0muxHdnwarDIGcQLoyg0ZVzdJkLx78aiZjUMgTdp+pZXzf3r4CvVR7iU+utBI3gkx11lCEdvBJ0O0OudQkGl5Dm22CP0F0E21z7c1ayuyOZJyx+Vd02uB77AwET6AfCu4FHNdopz2btE1gmAsvZc4/3GzQ1kl0nca1b3Q6RdDkduXgm1iOAVuQSaG7/N/1gOrD0nTQAckXfueN+jq8l9x/+7ixFaslRkn0ZoMj15Dgx2c3iUlr/dGUCQvvYDz7yQBi1bOQAyiP4YdyBEZK+l/L3uK+n27SxWAmaQhqathTzP9Lrmrm9Gp+V/P5V6LxvmKaSMvKrwsJQjm1oXBGjggw62XqRc67oz8/1RPFVN7YYnrSnr1/XHqgeUzVO/B3+p3yzTTlGS6jfST7hlLTe2LkfOflGHM+Micm3vvcdrZfmoMJ2XzkT9rIDSsoEGY3GnHBf6SWdfMmnI9zp78U9zK8A656WWVQm4zUxs6mUBz1w2gZmYytbMQfP/0soNQkUuUdlt6HH9BvSdZukZdsqkwXn3vyIvslozeK+djzCwVjWo+FWRR/2H49nCIQRfn9dO9kxUbxw2qVwO7dPn5SCpdVkwA6+dBX+MCBdTnBa1w9KpaOEkGshFeApFEXN7P6HkZr40Axje8wdbJNDAPddHIOjk/SCav9nzvsmO7JMbrLImVC3BS4NmueC7Kkg+WVFVzr3NNExJYyVMOtwy3dtq/oYtNx9uBzw2qya7xUZj1n3RH5pf8DZhxKC7tH4lS/8hVSLkAyscMsGdiSKx8ZBuIGTkyStb5ifQKu3kAUNMBPLS+E2yMcolJ8BsjcRNCW2Qd8ZV23BA2UzeS23RvgYKuCrJWmCfGWkFynuO69fc4ETbz79ODuKFiXWoxmSLhJz+umIJ9bawnU2mn2BYcBS6/TBKnEzfHHRalLRUC7kAKMw++e7WAaQwoa9igweQklKDK4P7RNeH60NomQBioW8AN+LNTyzNL1WxmCdFQLW7PJfVrHcu+Ffymds+q+QLzYhPrX4oupsjCaLCZANRDt16UfOAoWxmYtrFYe3SUPieMO6WRiZ1FlzWDiyAKE7sFZQMjeAt8zcavUmeI8JLyQH/ZR18lwjaxxF8c15HVSiKuehmSZiIlW6zcP2pC3vW3UNcwzPdn7FPTw5aWtRkbrQSxTOjbul7xjFUrwWi9ulAqkitRb/sTSci1ALQ/D7KKiOwsmRVhFiiLvYRRar/9XSeIfeVGSNWQSQkMtM3gT87EE60PE0C9X1UXVvicZsMHbVaHfrL4txCAyXMoFeV34UnOIEBdO69WVRKitSqXSKUveFFYipavWtGK6pivD7XPm/qvG/nVmgWlkR/LqCDcQcRyfjOViu6dkG/sxgarxMWmZ9yKO/F5M6GSCZx/nZEjfsiDXM//HpXB0EIFKib55hB1fIj56GT+o4vzmj1h7xTavYfb+DvtB0GOQoex5lAexkv318IFlfDpD+sBSeSiqF3xZS0/lFk2GLoXMPSFU1pN8ktae9GjrArTQj7kgQqo8mWIZDxoGTwuxV05gNRfg1nJ8qYqWm1fx+VfHPhREGxKLrSCBRDL96FnHltK/BCITtgVwVJ+ocHJmebKrp6rFhz4weTKOKlmju4dRzvutgl8TEQ6B7Ng+A69Y4rcoOGUKA9wQ+vsg20wo1v0W9SN0azjEDqcE8/PUEd2dcHyAbJgc1jhqocIoEu7vr5+zP6E5cUkrgSLMWItR0/204/MYWf9gPme4myf+bzfE2yScIstxBk5FsNSvDBE3GKkJjLY5dRdgkVqNhLTcBlQsGvpp4mh/f7g7Jwf84cAdR71bJba4AgQb4lQWsonnbp9y3btcU4V7SRVedD9dVly4wBdVnSjdE1vrTi+lomW6pPZLmA22ijp81VWHR741EMFYH7pJNVjvIE3zUiWi9g24vgketjIbkRCtANoYWZHkFolwuB6NyopV72W8bjaxtgs/ZC1q3C5DJrLXnM35OXGEGZrY5t+HJBB0QUg2YsZwmqQwjwA7pWPsWZEN8+RekcqgFa6qul7rhXbd+hbgaK8K9zOFyxTvFnMKr1QuSKeNWbtViJXcjwmYrRa9Yk8pMBCB5vy/un3nxh4Za9zFzMfP7iaWBGTDxcQ99YE5fyYa+dyN+GpDg4eA6IpSWJJWpIoM5OeBMBjFDXyfxwx7A2DJyAmYcVGQPGO7x4EAynYaxPE9HbtyAkYQ3buXSj58mwqz+zMVjtpJbL0MOruD7JOh74eW4Vw9Orq2E3PkGa6hCHNIeuyw6oyt6q4HO8pPJisngJy0NB/q+A1cOUz9xPprVU3pp86iTPCIGBBqeINP07qQo4aYfcll3M3XqG8OOcxIcH1x3Fw0DAxMQkHLc5S2MeuISpg9qR3A9U5Mg+B/C7468Kxjo3JlyM8Fqh+Mp/WIiwoUT9fbhp8ZnGwxLIrPX2pxVq2sCvGhqCe7jN2gt6ewuzMFDobVjhq/2uQqGkUsbspkjzVesB/oaVrzEc/v1cBmqkbKTzNo9J3K7EC3jifZKmOZN8Ky8sCTQHdvsPJBbuo2/Enee/Yo7dawswP9BqmANFewb7sztoLVsKs42SSy+QgpOn+1XdOCxfP2tBB2JgQu+fEPU79LiloP1UQZcMlpIfyI23+iYzT6JU48ZRw+zV4JxEnLuyU+CXAcTxxoEt26hJANSlsqjnouLIFQs7XaRXxxn6HDn2Q6mP8hdGMlgLKx3jwtslro44/ya6BGw3/71apZ9JHXzv6ZROnWN4l6BDeYXmVjMUvYvllUzJgHDwjROSJ1ssE/6FZ/xPebCFNEjOHfN1rN7fHYt54996wuafYpo21lCT/RNDYEukzX/49yTiIoWyeT9wWbmp8n08Cl1ZgI9czi71xNC66lmmUYavPHmlpFc6wawmPR0ND0aPmmER1stm/hmf9fkaJKfuqfSMYaT69pGGvLNb/mS0Fp92GQUN816sTXBWW5390mPXaQFqP4UmBDv5GA15IXGloFWyShOINxk6nJbjs+8B5O2GtuxrizAJwR/a/pjPmlDR0VNC5ip3TjS+tuabnbq6KHEWnOkLUIZmkNeKYdW5xUl/8HRk/5uaOqfCm25Vwa48flLBisqYnLye8TcmUnJLLHewkscZpvjlpYkKKz6hK2VsFhn+z60JtEyllPK9ix6OO+iFgCxF4N53jcy/kbPQgLcQZYYLIGZkTnVpkZRLX3/c8KI93cy4DFBzfs8RgH/QkMed4IBBGvKcsHfpwM2IhTvAv0O4aF/XMiv35ea94RhZ9LRwFC3xwcfqLwb5LMIW3eZZpg020x6JQBJu2AJDZgQgrjH9P3AWcaNIR5CCrgts6ZZqCSDpp3c8SUsdXbE2QzTUikLizLrbCtY/N0RNREVLVPe6kWjRBnSN5+zuRiU1kairFKu3mk3ZqnYf+GFm/tYnPhcXmJLKOHYUtbM9ibvsrWXcXwgPzjkxB/CqXD2SNhYgfbkui/cz0Xy4Kf0MX2bxCQN1kP5ersnS8qlPhTIMUb6b+nOpHHEhUhfljfDnwg182hBX3vhc2JZb/iP8mnXMStfVRWcr/Etlziw8k9DjzHioM5K3xN63uVCkFzLhyA8nrSNKYBjJLGryyf/GnfLPJ2tZJXu6qrefdLOMOOQBsRMeO3uaeUUbHB97NcsEfLVtMtdO8YQShOPJhd6g1XzxrXgZGSMEiH8v+tp2B4FK8cPXl9wr4nYYugr07yMG5QxwiTkhEdKPboe9xamURIo80vgwChq5/9NRY2WWHHVuPZTvnIhdelpCogSuC0q7YKgWBFNZ/e1KuGsLOgVz4+Hm6hbH5oYwn/u1WDm2VaJNZV2BQJVibUaH/qx0aFMdJtZuoWplUtA1C1SMf7SoGAWSIN/qn//0dpNis2krJMXjDjmVxVniSlMYhSUhAREboaZ9XpBXLOhWQqEqiVTjO9FtzLAq1AykECMG1sGa9szxIClXa6JnI9lAUS7mDgKuEY9xtU6pgzrD/vrrXRM59rYs0Kh3W7DcOC9wFLe/LbCUVcTNUQou39U6KLyBZ8nK5n+qALtlQMwfXiTO6+zUVmL6ipDwtmVGPod8fFa44fJBY5yZagehv0o4XT2IETvdcVPfbzNF0XB4N3pUpdWbkYolXW5rM2VWfhxb89r1ZpaG3zM7ijnSPHjH16PHPvsplEk6EHCMspNmEv8TOfSxAkwiPvRk6VhmYWegm9hrYvIuv16O+swSGQDCONuTx4CydkuwvQ/l7h5iAPQ7BLxDWnQZihOVYkJVzIP+J930sGzkSGF/y5vwrL0lHcI2BPwQde9BSXjyBMsxE/F8V+PEXamf06JHDrzN4IQiYFRSNgy8ZpWXEHZ35UGAH4Jtk9Rrqko7zjXI4JdwD+1XCK+cX6SXvGW3xdxOIv0Z9p2Sr5nhJGa4dboYhizRF6AbMp11bYLB6sOcLq8fxC1nZtBITBD07i7rzhAYUUt5lOLuT6W7xuVIcBVkjPls3QuvGTTv42fjjWs37/BQHRuaxSgkTZY8whVeV+MD+ReZYrbbohtUAFcmC5yQ4d+1QNlJIeFLnu4+dzuJ70Y9USmEP2RvKIxbWrL7yeaWL9QSXZmG8nTTjYceCBMCF5GEjanRulz3ZkEZP2BrQO0TrgdeiXwhA0DzdX33EXF8k8PHorIhBdpQc25MQX/aHjDRGYgeB3fVcgEpCKNgf1une9/Gru+UmSdSU1S+1qjlO5Yu6DsE/6sYU2teYmKIV1lrWgkm7P8hgbNCKlhyqHxvfLO5/JJBijnVrYJQc4mtDilEAeFD9G+7ZfTtesVqurR6d9aHsmpSpVR5nUI6nxR0iv7J+20/fmHgbLeWqzkRex8Z7GlQlzfdCI7Y2NzwImEyqOGYi/b1mNBdNx16W+lTFQBY0uUQKFv6elN2K7idSyQ/Wb0x25p2KgyxYM+fF8rsZcMlHd954GUVmhV6KHdj1dvpyBH6mfC5svQPkKgBc4U3eHbQKN5DNUo2puoFvBjuHRKdhHBRkhCN/KUTL4QdWWDH7heE6wpVkn811HgmxLMKi98clwv/CnYJpKuyAMH/myPtSWkNfl9JtwO7s+vA1Dsl1ouXQYbLHLw5v8QeUunHTgM1OxISA1xOIuNrS+0NQdKKrjmJB4VV8PX22vySmeMDVGaxCAuUEwwLCr5k4EJFEoEycOp1LPMQAweuStafPK9Cep679Cdj8trgnhL/Bh70cvxbb4QK8FoP/PIT0ygyhw82UswLIPUaJzU0ypNSYGi54D8UtFfoLm60kYWf0/bknjJT57lihOlvZx49QTsx43q6/v213a+q7l6lJ5Zux6A1OS4LB0AsXa0gvw27GUislU2TM+6lf6NmMnhvSNIaqDl4Grl7eZ/bhhUkU0BwqYrYLOCrerfkfEcRnF98QdZ0liFpV6WDJlIsJqX2OI9OuCLG2Q+jO4uWD9zqInFkGAsdkt/PA7D9+nSrdAm6kURW1Qe+iirCffTd6yw9KcYo9qxWjND48XxKgfKw2+PwmQ9rvyhOMWzAIBLGmDNcBE5v2Tff+0y2DGpSL/l20CEmIFcvHb6NHSUsHxAerjZtmG6oRipJ9c126qscc05BNuRtpJHyPmeTjrhmmkJI8PL6/2bETRrgmmqAH0BdZOzDBt3sURPAoCIuf59kmpqdY1CYVSgqvnWPQPSyIuDTdSNC8uzZEHrPPhg4wCFP7BY01miy8f2L4oKtIJBF0SEmKkgSpHB92ytCLKEr/3T/7rk91wUy58gB/ojkHia198t+l9RSnAuicu2+UUApogztityLD5++rH04nFMYtuha7hW+sK2+Wb4Fe/bY+URfgQefzxm98oVbGlBJsksb5QBd9MfZzwrGuukFaB6EKriPv22PpXy1zCq+raeyF9HnSLQDI36We6fgZ8lQWkhDwU0Z6WaL6sVEY8V6PRD6B2g73ZiupazFe1szw0BjuMH1tdI+tdfMBFRUL7lVGc1dt1eyhJ7Cr2QV4bdrxliaouaE9sGMVeO+elpyAOmu77CDd5XqDKXkIsAwm8ht97+/krf5atAs4F9k+x0NljXYNj7alGE6GVXe6fciI9cRbat8C8GUHzteyVtym6nWEvTPeiA0SaSheBIF6/6Wkmzrrc91s63uOlaPcnTRkon6mTj/5eVh4JvKidA/+SGhPG/8AHnp/kuFVkq1FNujJr/RMbOzD3V1T3Tgrs58NyGwbacgXPSPixJFmd1cpmnKYjrqtrF05DFEbPhkw/4DISPW8SnEbgMaer7I7LSeYrX2tO+JL6acbHBcsRU0ueWPXosw7kEU74luOO9VKSVwssL4phoF+jpoNuk5VdXDgT3CvLfck2Yj51dS7MoltkG5FtWZ8SlcjnE7AP045IA20G/p7R9mFLIyFuJvugXNj4oTJsbBHkxXrKdpFpKl2mx4Ilty/nb33fOkOCWofeNvrPLjljk5ZepoGFtSqfn4aD8lov+oczsj+getCB3tUpsQteS/ajkWbQiqMJf6gjDW99qSzRM1WjiLtMLAGvlk8gYWf+9Dm3yGVI2FTK1IC0cvYUufkj+BK6OxDvoPjOIpbt8nPRNMIHmGgY1AUzZmQKJnWOkBN8yX6e3rxShxeHV6/5cBNKmnnHBVjzI+6srfCN4YRvQkn8CG7uvsvILSdKV6WyWU12IeMru82ozrfLJQJ5HB31wVfvaOc5diIpxbiyau0n8d+u0qYsx4Dk0suXmJKqkNhMIFMeUUhpgG7js35MDONEQbn4R/PWkvvgQXKS4y/S49TXJ/6ofE/kP0u+1ts91W9QlHTWwbO4T908eKQnBJgeISDkRR146ht+11N3RWnL866oaDnRCeMSiW6mIq44mm4MIZfR9MXtj7e7itDC8G4Pjxg3J4cOkRvasw9aTYrHleCoryrQ7cuHftNDP6vWYutL8MpcSfJHji4dIlE74RekE3DF7dhlk6hnKqnGL1Hi/TGIfIe4bBDpK4l1OYir9/oOjCyq9tBhjgUlJrtCQy6gzR5ta21c+HKYPAdN+MfWN8JrMixs252WDGk5GVdG/vb/cVzIKXhp/8HR4G6+RHDNIz99aHnoQ05qPRv1pT7Bm1jAxJQf2I+R7wLoPxhzQh/TutIF6NwkMgyNdtDV2joPPAo2FGJl5BJvfr9iuY8nxCspmM3EXutKbnSYBC84rsFHyKWlyT3Ve1l4A11Yp5e/DSl9JG+v45AN99ZeELEwU9yRjf1RiKIoIKkIAD+88Ftsdlsr+MJ5JflgR3c+xCtUfi9MJSl7o3k5zWx/5m9kUIgXSeAY48bpf/w/1zjQEpzK+AwlETULbFm+HPuRmj+IXojkMwTGFl5sNNxdy7ue6daTh/A5bQ4SqE21piKbDxJCKF96hLA/w8B+oKq4VMwUt5T0eE397tV9BAqkKCWDNa8au6p/fJ3tFxC5hLM860sTPJ/3QYT5xquqylj2ZFFx+NSC8uB9ZGk4t1hSb/PPT1GTo9TR0hFtYiFnJzO4nQqzJMnYnlJ3Z+axOXPYJ0tG6W5f8T1+yKhD5iJL4rvVD2dnamliyrfomHU3l9yfN4tesLM9cEQ4EXdE37/hLrgZm7VDaetYBH+px5Lhf5EwHG2hukFT4Mmt3XAb54RW+aKJn9R/Uu8fbwArwKu1XEfG3WxZpebeGUKDaHqCd/0KtZ/5hF28RCa3F1fT3Y8/R7DbE9F/ZK7sH/WGmqSjLvVaIL90YcLPPRwcXP66vS7mfJ7gld87o49lWVUC6wCx1fBB2AJ3QGPs09ato8danw0MgfEDC5VSNcjSk/YJTYvM+qx2ggOJmYfKit+rTQUFebYSlcjGTSyL2XuLnRCKv6WLwUHvdb/hrJ1ibBQFUXebj78coPOdTQEEpqwsSxGQBOpKgCv4CVCXlyXM9dTZir7/5Ry3PwbMDfsX2bmKcxHFX9X8ZLxVgvbsAotPCl0kMURr8FqTDkwIV0jw7/ElinZkqRo2pT+q2PnHdhduND3IYqlIc/x3dbTYT/ODm+C+rCDn8GdvC4x5Hxt5ppYWDhKVXuisE0VAzXHwwXqAh9yd3QhmQNxzwW/6X0FW8JvG3y117YfkU2CjVSQOXPN82sVmwYPHlN2ZwFtPeZfQz1fjjM61jmOYkDxSICn5h+RbYF4NufSUckkwLFd0OPvWAInCbdR6evnlBayHqmkyWtg1apcKS0tD94AZDurSGga1QQVzlcsvN6u+zwjNQ3AAxrkkq+ceQEHd8oEur1QNuw0Fo19wa8hoV23OF7GkI/MHEq1I+TM0tURn3myhDQeXJYkoDGvcXCU3jJxdZc790CTritXzcXwVF0LMz9Vcd/LzGqFVifYo5Irmfz0u+xLe/V1vLaaEncE1bj3ztQtkmaoQYsrdD3fIfsIX3at+9JqaJoAc8wWOI9NmOKF52084zaMgA1e0yFPsVsTALRuO/IipwK5h8fLeOfFu2GsRgByTCFeFZWqfxKU9QlGXWvD/D6ureezt1ovDdtWrgucbv9thdn8GG5FPcfH5lrNL2HQAtLi3EZ4msZgoGyW591gAnrQMbQFmBrEM5YC70Yj9/qT3BiZpIFAG7Jah++L9Sw0tOR9h9TxbWjNMJ+V6RtJ48tuzhanIdC3OB2eCa8A6Z/pZW2KxG8zcJpSaSa1bBBBJJXJQi2WN6OtlX28SER4Vx4z/CfPnwdVRDunfYCATLv1hBrh5+MnW3yUSaZZMrkK12Iflv0JLKPwBqiutuMcv9gFNdoC8DfC1Zzd90moWNyvBpo32miM3hLrVQv0QMcIbVns/RTmcztPQxIOGRg736QfXcMl1DgrAutjUp5skWla38791eXWRpZit8phVfHAKTysBR7/+Hxm0QBEg6q24aO5EZ1cyXO1WYlLANawx9ROktcGi39SZKsc80TjVZvc/67anNQ0K0TbV4NJ7NwlnyFfjiewPnScyptUGC9alEhKd3F4kSi/N3cWmI/s/Rr6K02lrQtp1bPYRjv2QQj4UIaDw8yxeSvT8ILZGkDxWTCtnzgkFqIS7/5vqfaMNfxlu68frjZ7TJI0ydKijnvloUyvuvtByqiKWC0AUs0wIBdSjq9ZnoD2gO/179xMplImI6oXmZpYfYF1B7S8rnXQ13aKNxtxrTufjp8VlH5ZdSoTl7dovWhxaq3UehIeGo0EPT/bTZgTaS7X0UZo8mH03Tc/Z6Ig+xUMKN0VoIrBJPtJltIhJyp/C1coeQcgOMHcZTWu29UaAVxq25r0j6Rol/sbONoKQaMaqbKjRPUASnZaBTNxGB9PA0eyuva4+gJT8zEC63o9Gl/b/bgJX1gp5un6USktGTDcI5Y20G6HBsxQM1UPfMPD+wsUJZsxI/RfEax4wde7dAf57El/xD9smqG+DVnj6HOp8fGecJ15j13fBCKsh+hVSZLSQTcX3kk7zae/Ld/tEgKCkWGD2y5ZZI+hzV9hPZXg50RAZtpzKszyO4QolxLSQDATxErnvfGl3RMt+1VAGvVLJCb45ZZl30zVok4ByZmBKkKV3zqGxB0/Vkh9ny0DSWKRr2idVgci6VdFLpXPOJPRXznJ+0PgxYaqj4dILE3M5adGZIF4MoefkFK0g5obA2KmXlVEpfhDLSxrimhP/CZqValoMfbl1XhX1j5P3jfHKacbFZalJ2/rONIn/9Ar7xv5iK1TN8qq7GFlwm/G34OCX+Ng3huAU9VM3ljt9kLdZZp9/lrsCxsoO4xAx+oM0rtP416vB4fkUVlFC618Vzwvv1MaaayvOPmHooKTNKaLY8qdPWQ9BMQ6CajpUrC0H3Jp0Z0JToxN4IeRhCclO97yv632ZThLuAJinjQY5dJP95HBNP+/n/x9RZAGpVPH9/QcRAAUWRlBClkUZEQukG6e7uRuoiSHd3dzdIX7q7JC/d3b3v5zvn4fd/997nnI3Z2T3n7M7Ozs7Owt7bF7fXGuv5iqOCaMgvPLWKT+mnxEFYtO0DBfS/MhLW9tOq/ePfvaQkQdtcwpjDfPRxxXWbSywTL0v1+cI3vHC1n27UkFFBOoCWKwLTunUOaV9NbMB+fzVEukk+QUP/mAcRhBj1vnPaFQqE+v1dJZi6ZcQV1IvimAG6Xl17Q67a3dqFievwiXo+oyLDIR+Y2vtD7VyyVHWJg+SmPp5Fs8HAqYApm84Cs8rnAZa+cVudEkqEFPaI7/txdFf5simdaCeCnvRHpT7WRfSXmXGiS9LyOKIZjQYvYDbhMwvzbfAoRhcXhoarELz3yU/qE2UOKLx/GlMs3cZVJNFs8vBi+SjKExbc8HZh/oNrZlfY039Jw8//7VXX525mKtWe6cLvmSkF/pf9Aag7UNQ3gPQey6J2RZnPkRDQdjEt3so3Pc+A1EFIybJztTxX9q0D4Rl/toIilTJK0cw1e/S6LIlPiHFEBnXAd3wvGcWsAESKMdn9vF8BrsPHqMr928LCYEJaOx/6OsbXOEkFbLOX5EXxN2eQrPVj2i0jkVzjadR9NTvRi3OvLMUQKoe3mWSvc51JhgCr8BMNP1g+TE/Q6qoIxh5fqAe8V/dJGhLao3VmsSv3yda0aySqCZBoDTE55Lv3C0byTPhFAhKEof5FOqEqD4zxzPh7X1OMq3iRGDyr+63hai6fRh+V/17mBqKaORFX5q8nrQv4MiMNQpAGnW2+tmoTqGzIerJfsqyC1eL66gcO0rNNdrYE2MyLCWik0cPrDaTBL59Wve+vZ4ikP9NGJ9NM9cHkirCBN60e7o6vOv6b/PSMKOQ8mdjf2u3H9sF7QNJ/naEDTKKVul7NqYxppbR9++0K8G/6zJ3twFiRn97kj5UzIjIM/TFYiuARACdjR12OKW/FuFzCQmlEmvil3AvuO6jA4rsUcm4FX016ef/DgNRo20e+UJRhm6bKDjXuwQA9p3EhUg0ANtxN6U4Cke25nBcQK6/NKGKTn3aElY9+tp6TYcz0vJaGwEC0x9QDtWbyUpXhR0xHrgHMEB5UzEj9UBhtf9O0iQ6huLhKtX/lZ3YKwP8DhjM7RJCIHyxBS2efszLU2c8zYsb8iN2uAt4KpaioBk8jxWSuX9Tc5d65GdQNkXtDQpBXvpd4r2lrwdC1v9M06gjSyO0sLxawuLduM3e3ooBGWuI/HhFYLibbcyW4RFzHVrsM0VE9Ee5ecuwhYhddpCHIZf5043opOslb0vegUvZOlB2RH3Uzd5Xrqq+yPcGcjzWYx4l4JirfRa9X+KiPtPJteVxTFxzzILi/W1Jjw1V3KIrNSsD3SiAt05D7bJ8SB09RcNsstyGfUO3RQO1vnF6qG9h15b8fxKe1K/PpAaQZ/0sYE3co/iISds0V6J6uXw/8S7MyA+F2o7Bgtar1UW0MEp4h9MDQBQB8i9OB78txok8BQxLEhKGd8/aH5cshZvV99BZSwFY9DLWsv31wH2Jg4qci5ExL/xr/uUBt98mmYfR/RmLmQooqZ9zYLRtBB02DTq/xx1sBDFfnz9+WYeJdnGl3lu64TqtyLioUmWxQWFYcXKSPhmVkqGlMTMm5K6Q41oPHoYK4JF25WOX01aQdSP+0vBPmBfFE0+N1MB0Cmq5c1TZ4bfjcq0a6Cq62j/DhWazzzk2VrRJzHHU/s7UvCTLDc6NFgEFrQ/MGC8yQ6QDIdxFCPQ1Tn3yIeFvsZs2TKP7pae19rcESLsz+jOxB7FaeVLI5s7cgHTMoCrOHmS/9mgaR4OfUe+92torZ+nb8mGAsqV0+PK5VPbyNMAExTvIu1gCOBh+EoUlhbfwOZshXgFn/VwKLnftri1AyI4PkwhcEy+K5vcurfuZ3+UYjI/lBkfwz9O1MOkAryXJYEX19DHkeyoEZANhjOZEJWHG1asGG8AWue6ZuZD4vtP76Ev/GZD3iP3Vik7k9OuOoHcoND9YzbpuDjkcBfpoRhA/Eka09PUFF0X1PoDqEe54yE6O8XCb/XSIs3pqT0MLXOdLYpgfO1VBdVf96SuV9aEM47g+ft6NPGZvEK8t97KA3nQEuQhByblIeJLelklvgdOEViCd9zunEL0CsBHeN1I8qWqoq5cqoBIxIKiu/zbqPycXlc7Zrj9ErCBwotsPpXAeqbUGiPtWIB1gSckExGSd+XfHK1444d3ZNkIGPpKKEch4dS+8T2eAsReJrcCrwyLS1v2a9V2IhuJtfTOwKDHy2d7NsPsGWqB81TguFHegDLdrDjC2/7U5tdUfYtTE99C4Banzkb4CDQudDQf79nk1zC0MR9FXT0o9gOgLUOK1DrtLLIDqDv3j2JtIhQDWhYMQyJAVVjwI0hDJ6WiYIrX92E3N/6f9ea1UK1jjZEXP5ztqn5EyofUcSAjYonzYyLZCokMugOoLyMFdXvp9tYFLSrGyucmX/Y3eeM1zQk+Iolr2nsMovXFLo81jtMk9otSSF1ztZSzETP2MbXEGaPh19wgTkSMu7aIxxX9VbqgWfR5/PEZ77ughtnT0DyHomo6sq85f3NZfgoGvcLxKZA7IGgQtSq8gBOAQrul4tvIP+9IZ03Yf4SwrHvQXFAGg5mVo9Uzh/O+HTJ2WPI47kmQhdlBUi1h3B/y7pfZubjAmnqfKp8LrYZ3DSgQ/4n6M2gxylwgoDcdtm+irqf7+KLictwPE5Ed75xVtXmSLUdkyLNeqqgQwWYiwmWZTlni5+7Ma2XAfh/8XlGoFlck7ZC2MRn0ciJIjTujEfsYBKOmzWB/5nJdQXhGc1IaO2ErfLKBDcUV0CptS4CHS4pdBFopJBH2ygkzdQ5vIu964VtAEJB7thO0Xu3AGSj/oY3eOTa43f/khU1/Ja8ilDRR/sQy/Bj0ADdWiX2DbZxBDIvVLExl6xn+99giDfUDp/ByXrRhe6LGcvoMQ18pVfXZWNXlmzlO+OgSajNw01PVhtM74BMmmK6+nTRg7ewhh/CIYBhmWHbIx+5J5KKBaLkqIWSKxaqF3Yi0d9DWvo2ZGblJ/yVqfjri/vIobEhzl2i2i//q7aRFxlmaQSqC8/exALYYvFxXrAnqLVhtDi8DU/hOHp9+dHGuigh6b4ncbfKUALCtd7zcngJIeBMdV8RC/V6AvaxTcwu0LPFhqtiRtZoblHuQ2zo+hZ7DOHemkHFMzY/TPjFVmLAEhXbya+8iJWbzU5YfeMbLdLP/QvJDYTbO0KTaalTNiIHSwkbzGP03ttKZdGn+atgB/sTP2T3kx3BbSMlyACwJbA+pWQOm4Sd8u53lAX97Aa+zK67HBfNhG+YLXzGpxtdWZOOZplWVLD36kaQeXaXg4yYyqkDEsGz/5DBDDOpotR1v1IxmCmEew7bGODc3MQ3uO9ZA0WbZUd8iQOQgWpLFMPwmeLMeKv6/nZJTIpIThkpBODk8G6X6ZqS//7eZbLp25i7Yda7qJT87Q94EG23/VD5i8I8Lq7SI6jBX6EwRLZ6M0jExsv3F8HC0lpn/pb0YwrVSQKxnarlGwed/V9WRkkLoISmvnIRyRV36hXu4kfizY9AentxybwFS77BoVnW2YTH5K8hGdOnx2oOf7YJmgoUX7eVANxh8dpUEMY3ZboukE2WROqQz86BCDjRV/sXVCS3gsR38IK63t3MhFAsZQiBM8RmmuhY+8JW3VxO0tj+p0wNKG+FLv8+NsK/c/CFz07qOEv0GfNbhdubmXpXPZiXPgHMSXuyBQusn7B7d5Z2x4aDNqJiGEKCgM5X3aq/tRwtMDXqe0nVapN0vfOPRxIR58gHgvCSNHzGSy0HdCYO40Ttui000T/CVg1mdiFJFuEh/uKUnWClKLRO2OVZdGhHBLKfqu8bkNuE2rhpdkDb8/ImIQ7Pu4d6kfQXT3oPYy+LM5L7zhgadYiiZdtabNqKCB5uaDZ4ybg/zwC/piIyf7SQpStHOb94qS4G/WbLhsEZmslw/vJNpl3UySbk2unFrlwtuVbzGcZqZHM/repHh3w44bxy7anLAsL7vEbqx9vcXehSBOk6i3oX33j8gLM1sqnPC2PjxSPdlVDPjTfX4BqRjF4db+q3l8utgeHTdOUjK1WRpq4NHhRTzsDZxys2NPpIJ64xefvRzxpNHRpW9N6K2SDJruhkGdCuTRqguEGcsSZfjQcJuLDKcSd8ufeCb0WlPP6ftHks61oR01moMA8NYVvowtBJffwmsmV6EtfBeuuRFsWTOeJ2w6Cr1u5c1VUG76oJkDu8U7uDAxsYczxDs7bXISu7JxTk4ePpv0SrLOOcmjo8l9jtlaRj8BXrqod82Wcy1zEJJJjzihd64mCnjXaQo98nz84U1FibsWCtIPrh3bu2ZlBHTtTUCkf4zUitdJPPrHtUlZ2U04ijuaKF4WBmqy3DHTvyTXgFFf7qxHodFv9nsDY3xNOuYp4pqQ+qdL5pbFHW0vGWc8ULtNOMIwOcpKH+XN1Y6fDK8xvl6PxUMtSyB2vGBdiZ7O/MSlmrVmBNTextcBZ+bHk4YMIWfyQpIxMPjXPrUUZ3DdwcJaYbbxf3dzlW9M2XNH1IEQbFd+aZv75m8qwZIk3JWZMTRjPL8z7s7QlSF2ui/7+uqapFyPYIEJyvY6RIm/xcz/rVkyAspAT/VN8VYmRns4UATkGg8X+dDdF9SbBXAN/rvbzlUhlWx17SMQJ1u3zKKFzZB8xVZ4IxxDmhj8Gq4sgzD0o0I9Oi7W6bufoOOXeK3LSJ9rCjY0lv/yqDPDgGLaRQXN5tjs+pOaP6ZkVG3LCGHh1G/uPwudpPPUUzf+STyRm4aF5iUOhWfKiBqCnlaaLbsNXI2KcX1CvmoMT2NI2yXfJpBScmhquHF1igPhAP4U23UHbiU4y8KHJaGBIk+rDAlyzTIN4Q/CMuL1i+Bbv9EkXuBS70DBFK4tyM1qWh1DHjfSXYMu4pgQpfIE8/usyKi70bnTIhzjhrmb+5hWw8CXLgwkWvFVsAGfCxq3SWMLf/w6hQyMxhaj1VBd7CrHQZlpnuKp73s9KFjw7Gd2TeOTqr5w/hoqs/5ChZPcX0Jyvqemg+jS3de65vqnm9+TcxQkZDFLb6ZwF/K9IYn+AePdc7kpFF4P3O19Ak5q8ygDl4N26uEthhRoowhfmFceRqEsbEZNZB8ffSdaSoZjLgyYOrA6hg3eNhLbLex6MmjR6lPMff1EUlVPrJ8ArsiW3fSkKIPUL0lWUXTYIhKMXliKyGzPe5yYgGB8rsu77em3QnptC7l1Kuohj4VfIcQkxe7Cc/Z0MulrPnsavLviSr67WqU7HuYJopZ6H1Dd40YoxR+6teIKaKIYtALMiW/i/doQYDnkWaPOHkrTTZbC+4zODThEfTitAWjPhYvIF+BmWiK3OJbHfANcIvNx0sQ1EQmlRl6bQ65kgty8Ey0L3BuFhGWYq74uFvkbaZMYJKlKKwkrZNtc/thEvwwRgMueyB5pVTLztrZF/vRQJunQE5qtfRKxjJRH4FXTh87f2U19TDGVsta5ivYLwoCxiY0JYZy4QBNhBcUHbE6yaGLBtT+Q7FAISClK6rPQzG0wtyEXuYugtfeE2/RYwgYLe5hctLEf/OCTM+rGTsXZBC7ytvV902xxNxVwIiId2STbnYo5CCwFHZ3HJmlwrfZ82150/5PM9+YDzM6YypAz4iyvmBITJ5TvCyb2I4IYHikOk5MVM65v2H0XAlNGSlmCglFG4mHG7777sX+L42340HzUSZQfRGxqSEJ739WCkrWO8zGVRKmwWlj7yCpafc9OMghMikPBlOV/pjn/B9FRp+oB0WNympW4xQwq+5otE1nAndKtrK7pqFqRw9B+ooVWFlG5AoUot8L83zU5cC34NkSPzV41fd41w5hr6lufl+duvvyQmgehDBOff52lqpaKRqfbdQqtUSrVnXSBF1JVBcKF2mqSS/zSdXa4/P6Hfza2lvAok0vUuTZQjm+b6GLRswuyPl3PfueeHsdaBO6m5c8VYrKSYRJizWoPFwEpuxDMBrOgcb0imKGJDmc6e4Bpg577FzzpiJbXyl/4gobEFXKs4QePtFlryYuaiZ8jS4ALKYGO1/OASlDvJlkB0Usgll9xVecsSQfR/hd3/sV6r/jSJwxKaEZO0DrHbBcg9mJG1WqeV4IzGTjK00SBue7ffkmWWtT8+/iNflUlky6UmQyU7ni13TzSZ5Wpu08Amfg/XDhrwFQR5T2QCjIG+xx7f3XY+VjPFhoOoPx9Y2NwVfBDFDfKLBvz7C1tLRFkaSteKpdya5MmWstjsGsafSZS4qxxRwecba4W42JBvuRtIfTXr09NNS39m39gjzOitmpYMsOCPKFAGhiYMOD6tRS70FyUOMhNLROOJUwYrpPSyjczebo0wTS9ZqWSqzkiXmr6TPqoQWe4/kPSxWlA3rrQT64Upjiqo/YVc8pqIq5Yo8EAHh/z9V943k/w42g679zoBm/4ZfBK5/tY5adL2jBCs/+s3fwNWV7WuxzTIuJ5fXO6ggpcqwI/tsq2j5crVltURmr0WNCeDgkzdtLTqC70j4482WyGVBBer22AhfCyh7RKx2gpZx0rgGx8dJVFCZZcviA3KPkp6LUkauyt2JvOKOTBmEVTjS5ScuNmh7omEhvWS0n0gmTjnlwzmxigC6R9oRTtHd4RS60CQA2r1ZlalBqbpDckTWVfcv1EE4wxvQYX9mF/XoszobdBkzJqInOQUBPr2MHc44OMkAkoGLm4491VrqSbH0zrX7VzEKr66peA5h0ZPlXF36M1mNQQeBUdJO7T1qecifMG8FEGq7ADUdHl4tnFoRAZwXLMPZYeL22xbGtEqSqGpPsy7RgwW5aPf9SX4EMXE0tBYVKk0fmP9xy5DZnFA0lask7eaKVJg8O0rU86weqcAGPBc/gLESj6qEg4lI9HdFlviGgtOJy7hhqOkHdsMjRK1SjF+LM2XjSdUWiKB/wlRuvgJL5FLaT/GVEiQqRPZm70W7O0Qftkk9ONfvkaTgcAX7ICsHygaUYlvnh75VZVRyqfPm/jlRYQEN8XHxdYJligCPCvp3jGgLfq6pEJWWZuQ78o7GK3NeHDuwjIos32RGxwGxNHpQTxDEu5SExNP+AxvCfS1T6Y3JrK+Fdiy/njXr0BOPYRbOUh95Gr0/RY+YIhZvyRVJobbWB1M/tgGKD7ERWAxHX2aECIZnKoWLGm/CDQf9MLvGx8RfSnNo61goJfA6enZcNwUP917dNAWThZREi8M91xg3RXGnaeM20RMk8IFkzrFNqiygVSXOyM1h4G6ek0ZfK9OCrnq+Shggl5KFLrPpAVu7QMGs0CDkUmHlKiBOn/EDaL7MKpbXl3xznYp1cokcXm5XWdxqQlIbO2aUEJpILSF0hzv5ZFV0RUmZ5Jzhubu+c90R+rx4Nef76yMT4Y5wusHFeOkpdakpE4Ow2b50EHQvexZqVopE4HjyqqRvDisST/yrVPsLdb4hLY8AhPemGx8+jJHkGEoj84luUPOlID8KCjfZtZh1E8gSEv5WJsbda0sjjy3NqG6MznI8c5VmSC46OTw2TfprGPeVlwhyy+tmhMqcw+U2f0ZS/hxSXUxw/Bfahzx56NIyXC+LZ0VEWHWkjyHgwDjPlJ2+cpCMRAuIUxLrw6qCk7lwyhxlR7UZvR/xmLICuAV4WoE9gCI+RpRq3WvzTqc8gu9l2UavnZL8ed1jO5sh4yjAgAaUpD3LC/mZ/ThhRHNfhuZiHwSe66WnmHufdxbY8RsiKz78R9RCkeonOH2p3MNTtI+kacr88U/Ysy7cgSsIaVJ7oa1qmKekv1j63SAvk5t1qFePvJvoCpD1pjh7NDar2WxuqigjS6mFvClIrviWBM63YSjzRiMxI/809fZCoLs0KgEVvDm71Seir4G1/2Kk7M3m45xDCjXi9B9ka6v7agbJfskLVKZELO/8Ue941quriZWVha+dKB9y3JH+yK5HiDOUS71W+gZbIIMqooAy6mw+YDMZr587fqzZb7cwyCBVVTh0UrJQp435G7UplVWL0O2BtIRwSXgt21ZKp+4g7ZDabM0rqYViEqzsXHlKOQb7Vm0J8O6+go6W9DYrksVaCcJjxh+KqDTgxZp81sq2d+qYrKeVv5pP6GEVAQIIJM0RbVrrTja3scF/2Be9drax4f9H3+GaD2pT39bR/KdyFxY9UQzo67QigkTFT0iK3wT6UdIDM4pIecwv/8nVzPJONbQCUfVWVmuJrOyP3RwDH3vZ1pEsp/dGL1fNZpQC9Ra4zVr3lSopxRI3Rt2z6D6GnIbWN5kELlOkBFC+QLfLsxEmFiNZzdtve7x+k1CRp16ulC/QuxokHpp5tDTlhcmaxq4knaXMR8WU5CKBcnoaQdvmNigTbiWIv1E/gHEKbgxhHXqm+22HDkd+R4L2/Qd28FIMn0dUIaB7NKRWrss2BS6bTkS4W9VTlA0Jr9fmGRpx1Wft55WER+pAJWyDC0Gzoy+6KdMo9EInG9T4NPWGV05+FLLLlIx2M2M3isRaZENJKj8MOQOcD4T//WFf/K7z/OuDGUbIlcvmiFMGMgiapB8+pXiMt58cCfHTf9G0UkA4hEeGmpb9hhCiwrBkXON2NfzNFzDOYQshi7O71/9dAM/7RJhgqJ6Ss/zrd7Kc2yYZIwEEvpFEgOnHkeVs32CrOmYhtDdJbI91WPlCcXen4pGljxYM0rvBg5LK3TluyoGob6m6P53AJPgyQEbIEa/D4IDyBP+g4IqWk1XRpNu7i7dUo4Unr1pNxTRWUbvwtBJ1CQ9WHt4ezefKSMIytAvXAwRSWq+yjIOf+Hf3oN+sOLG2NZDnkpk3aSsC/3hlUUVg6viq8W6TGRqCvzNYra5MW8D0bc+BbORAdygnAzn6vcF6VtT/Lq+9nbJCLVu4xeMxheMnWMlwhxIjkDkn4Fh9b2TfixdtjCxI1Z8rDcDy2yOFnorpiQPQRBm4IWY6wUEXfNLE9rIFMYtjkJ057ellwpJ4Nzn79PfASdu/u8Zjlbdm6mopHInedPbFOlePFelo+AbeMq3i+G+VJCXYybK8M737zH2MIxNtKcqE8yE+pASETutzeFXwkRAzcnyjrTPZMdj5CCmeQmdK4GNkqY+tzo0SS6+sqR6+JnUL7VfAYEF0ZLfKPWpf78GAaliuOxmAIf/h3xZ4p9m7M+POhWkUuU6SpmSuIkkZ8qDMYLgbjl4ZRsEKlWDf//Hpnj4lB3EsQBpaY7DWYFsSSAdv34/kjI0OK8C+yB8yo2uuwGyZ81hBCHBYf9DWylGmlvplrCEewsqDpIwooi3pJ/1rlNsDaAs/h52Mtf5KMPmfD9gqmCKKC23X5wb1gZGoI3PE4zUDr06Mp+DYdEbLQxz/T2vh5nWNdHE5yhzWQmk8b7oAOz1prdZpFuuUcQYPe4zH+PvwyIx7TGf9Ui+90MtzkkPyo+KUlxDt+CF8JPN8PjyyHSACdzxdtfE5+9ZaEhUn0T/NRXH2/5aT/e96BYskiacylOQiQFSK3nJ3YXVqtfda4vLHZNRdBIO7fTGzraHIVBg74SJ5bcHDFjrdqz4POUdakEzA5H6xNYsFdVKNZzIfO6+jzUqs9Q0R5JjeQMV5PKMUZGUc2uR7kV5h2KJlaQw7qYC/3PV3aXDr27U63YakjLcT53hG1z3EKHBca+78fr+uLlZ60rxieGWQYSsW4/wLbqrEkd60mViZhzqC+UVY04apz6e8KUvoJhBw07DiJFcRl3dPylJIrkG3J7AGEBwrTW34qXMRCtsu891TPNgSKINmUz5lWFMiuBQIV8FohFyRA/HxMKl0wi54ooRTR5pGUjpH/19q0B2Akjv6XEwXIs0MDaB66ycltar0NLZgfP/QxSQEKKrk58RjWlQOJf0f5uhO82ZsWazCRHZG8dAb1Uv4ocX6AmMe4Ps4hqeeqonYeakWrAMnIESaaFirN5Ag4/ltM+wFjMMsVF1tSR3Yh73vzWBCVyQowD5LzPAvyby2Xda6wW5K1sYYstwMMeHj35C1/OJ1U9/csgHwu/LJp6/w8STW7Xge48D7TWF4SDtu/dG3R+pI8tSTLLdsYiYgitdVTr7ArMdeNz3H4hPwlfM6uRcXX4jmBC8nKBgq7cd9Vx1dYAwf+TjG3AN/rdGMl832xvd9wCxmaM1CSWOayHo7Mmgs3LKHtxn2L2SXbmck2+0QgAAQABJREFUtgTBjrMofP8aNDE8quIQCy9EmUSxODptgOrc4rmJrSvTmdMaq3bWF0js5+T6xLu1l1yxMMHxv/qxr319JN85/EPOmQNpmx/NbLVaLJ6/L9nzfja1r2gLAwwp/EGaRFtLSRjN0/hjadb4gsPTWKlAjmKyz/wm7Qb8srJbQgxyK6fnSCnJ9mC3JAJhK4KOuHy9ZyRC0fjL70asMxwAFeItT6I25UkN3AwlufKNuskoPsNIPOgNc8NsSBtySiidFLU0FXgf/rNcqOEph+I+mQyVSLLXraHCSOgM065OJGj87ErE2A4lLNYuOYhEvsT5pJUWaft2xouEz3askELrX7Iwb8SbR5o90BZsZF3Oxf0KbaXJAM4s5r8tSAm0nsiyKDJ+BQS1GoJOouq0e1+Wm/2rEJ6Q+p+SngeYpXZKWskqgzX5BiizCV1uCTK7Lqa1pdvV6prDjdyPhKNSvV51pFVzr4d0+ioOD22GQOfTYSrMvb8KzkxCBglwcO729LNsVkNZv46tCLrU41r981qnw1M8VWIBDB8a3V1n2lbFpW+/COmqzSHxRVF4jy9Kqr+uGsrFiP6Oj3y5fcirj12WxZNxWX0iTNYiu6yeDEQDNHx/BO5NagiyQCc3cRYrKYsIPx9TCFq6HuH4FvohDgvi3B+JKzK+R5VWgg3fBiEU0Qz0moTgSoN5ZSrW9awaKkHXDHnaHO58zFtubgZe7aHvmx1YQAxzV77uFDLtZiVmWX6i/DvhKAUWRt05LWx1GSztfcZ+p9vUI3oEyht5AAH06UFxN3BUUnTpr5vK0wdytXkpquog/wWlI8+jxTBQtWFisHC0SIBBcg16BmnRkoFRGkAlJDYWss5cu+s9nyte0oaVnYqV0CJI51ofkDNSoWG4WPEpjQy6Zu9IuJohBzvut05RLv/0FZLsX1cjrUN1XGx5CAe8Jv6hyBEVNTUrFNHednJu9nUaG83cZQdx2bvx6Y7xOtJzdlAwtsh65kqyt6TMzcLiF3Nqm4mh8Ze6JEnDm6efWNsNWUrTK3c1BfqSnwvGl1HkzTLJP3vOEINXfVIe5uP7XcqJ+JZMSKW3jm/lIaX1jCBwTD7LYLcqDJn019RiTMzNgIl5NUiG46FDsERp+sK5BfvRBMFZhP9we+R+biF92TOdUdZkRGyzMwqxUwK8RPBHrxCTWv9JW1LY41rFDu79h9i/+QVSanheQFurlpiBGFIo2CPoN2zji17Lr2WgZIKw/S54Ygb4reWAkxjYaIhvcEp5IzxBpJ4ltf9tr0iigGzKK+ugoRDGdTTLAW8oIshmknSzTxhkkozLUmTyFteJLodTNkVzhTCXmGJB2DR36lUATcIQCAoQfFbfN3L7ry3baYTaDA04UpTZd7vmJ17C81VCradB+psqEe0yTYVUubIhJsc02cdB6d49CsoGjFY9N6NCiA7OIoHj8XeqQob6T6H3b/vuFcJDkxqi08riTCUp6UrwH1QA0LxZj4eYdbWs90bUHwJzJp9bDPmT7foJY/LhaeJrDPLzT0rbOqNQS4X+JiS6q38ZX8rFgFosacnl6yAQ7nyr8HLynlg21AAylPeLs6ixuERc/EUOZPZPapElBwvOof2hPSUmPhFw/e8FKltq9lzTZLtqfnOIMRugxO5CoFGzInq2wflG4ao+2jxTQDZkUandx8nHFyPD9R9X25n0oR5APrMx7jduIsNJVU4T3H2xteCBugkRRxWnrMvwsCzxP+eSNqqJCtsq/1tFXhnP+LMldfURyua7QLQRkOFzr++Sf4lpI/bzc1MJ93m4PUlcgJwG4r14Giq7hjDdk9Ns8sAbq2DAdejtaKa1PswXO+by31lWtAAijXsQ29PHfGa4deWxxXoyzPzYFFdDyAwdiYmCXZFCn2aZv3GRezulISfb76ocy3YvOdzF+ilKn7dwEExCJTRGFo1rPdZees7H/6m2W13TqamB+MHUcBHyzHXf6rFd1wIS+hW6ixSI87nVuDTYkvDJ680hpUVqD3FsYElKXuB3b+Ol6stEOJsREBm4JnesUC1i6AWAUTLDYDMUD24ooMHphIZAJYu5PUK7uO/8FHD4n7JlK4pey24lisjWMFiySMVtJgJVYr+Ves8sY8j87M/90vhZmX1+moPlYKF+wg+3RzKa9Lwd3EJDlqA7k+zycaUXJmfVyA7p24tBpQZSefMY7A8MR2iQYehzuboKcITA1R+VZ6BYtz+D3KaRrtgZjcJhN6jbhItP1/Fdsw/TMkCNWzwZWfKR9Gb3hdnScat5D+uMJ4Rrki7YNeYkb+9mMPKf1kYYraUepOXOM+E6AM38uoQq7cQRsUebXYtcDPaQs79ULvGyasTtJ2E7BRcDVwVvFzQSWU9JSzxbZ/sAI5dLrzZw2KX9RnnfKH/o0/l6PdBoG5DiVgSR68TwSiFlqjXmPPQFNNAjLHcpUP8JYb4tGSoCWtUElox6jmJDu48/UkpQNa1XUU1eMzJfK0cXbeapb5uIXIMatf8mzNyGGjj39tVbDfr3CUzt4dfxwuQq/XqW9wIHprbj3iBL1ZB6PdA1C0CkUC6fanLeL2qwmQkvYr3vJceqayCfK7V0I9Pso0RBQ5uYVWwyeQB67F1eGaBJiuIwfr+mHZazfTQSshh+oU8ywuf6TaAlDBx688eijsy+fKrqUv4D8wZmxhjeHmKFCGgdKZo7m8BOZZ/4usb86ySM6KLp4kO3NOcXsg2gx7M/X6K5KkjLoe/VUNRO4VHbzT8ZoIAiKyYaifBe7hZvnQFBuXSAQ5kYeq5AABZUXagTr2Q44BH09STw6XHRP7qxwN9FiE4RKjpwP4TuG2gwS+S/99lRJfYIZJyAurx8Bm29oHKxs/gq38Gnfq0iAAmh2a0zQqufa+Z2qW2ThQKSKhPuSg53WBsd9dp4Hlwg83KZH8lYEk76mDTPF6wXEW7pq1d4nQDErOcrDGG3K4JVBXjiJpcgY+2m4F0t/QN/fhdjhm0X40p/LhEC1KpmLqLy88MVaW3xAU5TMdHGexIQKL/0JYczo8N6RAq6265wCLyf4TIvoPkBby8MvrNzcRjpul2qDRpvdMaH+SqxbWWgI8Tedeg2AjUqN+9eUO1G23ss10KXtKiZZLk50cG02zSfsJi73u87bMtw9iUWV6YaSf1nvOJI1Cj4b+BbQkvHgK0tzXc/0W1OA2aJNHVoyRTLTFwMLZH6ax1JAyBghOXnJDCrDHDwBB3fbTQW80f/0QL2BC/1xVq1zHC9imViKQL41bUsk1Z0s/X20WIrbo50DvydVHjlIM3Emump3ArvVYgVGX7vWyL2cD8tkIBqrtRgYAapthaVzMB7yAjFWEWZUy9gZ33Wcb/6h++FRajqbakTTV5J0ZhfLtACilgRc0/sibVOXCTLEjhHfZ3HxsYw9n0pFH1tlwHKIq6J61GV/okj029toftQALOruETZ/PCABkCWCeyCtZEipvx+MG1Yf5xM/RmaB5KpFAlYbUtOLdPRAWR1F5XJKel3J/6tkuQao9twBGRIT/XX3K7oKIMOiu9PsI02VV7gIKevP+KWdhfjmysPEa27v/dVPsv3KrmALjNq9D1UiTlOaG/Qj7AIlwjoiL8LsAfXfWO3sckKAP3oGiPY3fAaCi76y5DfnI4+IGwXSe7LpzeD2qo1l+VtoVLm6+4Dj5xoGJcwaPFBRfGfwhLkheSUTiwBk2pD2MV0UfzJUkG6DV0BCuPU/c3PB4sIA+nLN6FPWhYBHFFUFfm6Ngu2c2/e+q9PnJKzG5p+QP0iN8lwTEF+MvSTX3xMT/PYYE70NH4prTqAuFXpVCsGwRmMEuSY/CM2fUdZFfz8BrRCQ4fy7juZGQRZEHEbUQoH5LSTGUR8oDQ7VxvIeKdxoFiSCGL8LQnMpor5YTffmlZ93iRCXbqCsH4qXJ/2GbvdUAbhEiajNy1BkB7Z8CC6EjH0aS9DGXzUi0JRjRF20L35fnx0nz++Zl6sfrRmNU0Qqg6WeQXmaky0KLYATWfwzm0B/5nR1gUGq2Fhj0Bp/Z8jzpFqyNHS2e2RAIDbIypU+lqkgvBq9KapiuotBJH2U95b6ngdfTu+D1EnaF+y8euw74SuW+X9K3zxgeoyifdpS8AXfAJYzXciLnJtargCrzvD48wkYIX5qx9zn8MS5zaijqfhA776YZ3fe4nJiyo6vpBZm5QJ5fkR/sZzUOckIMPoXftLz0rLT5NYL76wcKT6E/O27C24jo31HXj9O4h+E+5yTo/yfM89ugNj62kJJ+UWqSL2Y6ODvxQD7p4QylhEX+ZehccRRFuN7Iw9CDivhnIQn0OgCR9n82fjhwsb7Drc0YeFMtMQynm+mq+a6y8OyjlAyiqd6IdD94yQEGmIf1iaHpWD9grP/ZZ9o8uZAF4HYKKlE/0Gz3gdRbtLmiUf81mIbN9B5kZ8gvSJq1kdj8E0C+XHJsTRc6z7DVHXaxQV+lMVDsFwOtjJYFhkirn+ZJcBR9j8nv8HZiNzV6oy8be6Zm0hCVauKshsx8wE0YTsNZBw9WiAofr9fTBzdDq2IAO5jqlTxmCl/kMZwtKK5dujV8mRP6WC3fk2rKV880UMH2baIr52Q1Qh4iiNprxwyhbKYdhXEW7WwbNETvZJZr9EBBloAGyP6FJBx7qoPqrxt/xYCFKmd5OzSDkc85zk9R9vvzCCEUFrZ0w4qt+vkaPUPPj1GeQ6qDyf+X3rLe+BCyjZC8nPsmFvKxCwr3Bgf6m120cn6LsMDUSPKlTQ1lO1MflMXbe1tgD96FPoZUNSa5WCfqh2HL20lbr8MPOZ9PsUtjXapCcscE2IhIroj7kdxRp4hwTq4EzQTkWNrjQ38AhKDnUEB8SLwHjyoVG36/gM9azQ6nSc+rRB5C6ZXDh5w4UO93C43/uX2Rwi7Oaeoi/rJfFMzHyav0/j4WR99geKlMJ2UTYgnHEzOrkwd71TqFJW5hQCfz/FS/nHZXpIehf+Gw5+1wATM4axcZsQw216QpLfHKhPsq3oAaLijFKdyT5AeRP6K21Dq5qf/egrn5IGNURFlbNZIWP0v4y80yRtCVnosecYV5hnegaUd+ViErOM6SjD24TjU2BUhJhfpuKMSfHAU4zy1WbwNvdH87lC53Xw8nTF+KglGYHXjvSSZOEIzKN8TE26gfWo4SSVAP/A9aGtC233LWoDemoCLJjbdi4oSi0+yM+jUgoz5foqTq1BKS4BzRnPsPmmN6SZ3jDA9JJdtpkcL1EjpLDRC8LYoo9gaWyGCCXlwFAgH0bg2PX4ih0dvxCqBNuAiZ7N6d3zi1tZdL0xEiqrvME1gN/qF79V3Ai1q39IPmOpdfG1cL2TB9V+SJN2S/a6M4yuOwXts3786oqKg/sUSkicORrybHeBgs1tp4i7Ib/doBtaMucF8T0+097Vm/aMoJjyGjZlBlaK89nQREcDtxiBjzKa4ITvI6LvolWXGSCd5iCnGDHgeWx6IpN0AXG1akvfrYBfhjF0e5UAfvPS8sSz6yq+WE0GKXR3UOVEEyMK9QKIdixLgJo1L/KXihDCue7b/Kv05mMq9xUYmHmKuvRb79OvX3LijK8wzEfwwLjK/vOCUIXF0YMVsCQWKcxDmGsKMc792ERX9AMZ5E5KvMOL6F8XXTFRldv7ZBPkS1ejoF/xDbstj1S3PD58KCOjcgmJ7dIQWknBQo7ORT/lXEDFt7lGZ8Kt1Tv+iZ/+RNBrad92Kl7P2eMky0DUeZ8/Sxl/mzG5Lay+ChjIlsocmqasXe5rJxaaY34DTS3NkZsKIET7jCn9XlMgY17iJNFXtWRgjZuP3lRBRfCriu/rFViVUFai6ODETNcifIN2Aoglc0tEJqMPGY/5m0IPdSIAqNs3pKfhYC7YtcywVEPK5Af9rzOJnKwUO4DGZVwPLsb+t+sW+Sztfcry/txuZo7zYSQW+EzRtC3zHb1DjyeSi4EEt0F1nLl2lbTKeQ/Ql4tElMvOxEhvzQz4c+6VSkAasNn0cmRJoNdm22ql+Ev99lzxXaSyMr+W5OJgwp177sPFq0LJd4lmgQ2I33z+qiRyPlV92InykFVaLAOvVO5UiB7QdzpqJQ9aoWNEYozMgCKxy3ODVP/pcT261MHoA7KsVg5hlsTxNsphNrsnVPZzQUp60EFPRLKb6nucleo72DeTVNbfGKuCML/Pax4uQqWdx38oG7Vvk+eFRlxMerCSZLva+Qo2BtOS6LJ8szn+/ZfIsZm0LzGsMMWgKCrWCleQ99hLW5PjxJVxrmRdIyt1OZCvfzUAHafn9t7HjzHjKH4nnVm2GRVmG6ObhM4k25V7mei9N7EH/MfvBGvuG9NG5Ms92PQ2N7HREfEyUuXD80fYF8xK4vLoNMcBwbdiLVoaKJ/aaiC7fLe5/EJ02sgYJBs6zPWHoWIvH/j/eonpJ71W9Azxw/RUHxPQnRpaBXpDYddVPVye2NiFiMV+84p5u9KiASOwPILOrItV1w7xmIqfNZjyfudJh5EBaweGKgAqS9G+T/V+TC3xTIPf+5+7g1xJkAvFchjGIm00TuFyBpvxbEe3QNQcoko+xVy41deBgZMYNqhASDpYXsAcagPfB8AWZdkM3++Q0GtWZ/g9ExgauNL08Dg+UPJ7PknNDxlZlzHJqwQxgtAMHfZz4xnlgLnLpgdSXEyfQB93qE4p0ID+TBNBc38HG7j9pDwkAFpgiyhZTChN2kfKKRfdvRL+xkr3f7VVVEpJlhcmvehL7Rvtcw6n7c8XJZEL1VXAfxMcygzjRJAgy3b6O/CI8CnDlgljN8KakoaJJaMR9hzaPybXPVWACwF1YSQUo1vutmj2NxjYLT09i+LKv0OmCkN/8IqKkpph5VIMAgS4cF1q2X1YyHwzM5IgYgK3fqmgoExWAiTcXY2LXIejS9X8vZhfhqIhXEFj+gTobV0xPfgwdAB4JOJdV6mQNR9sOuJGZp+ywBDrfAVfuhiDwUaG1imYwHG/Asu4RI3E9iijkHLLtqUTTxgaro+ESbxCygOGAA1IpNgVASWj9BhNcfYllf6u1l+FAkIhlkSumq/+cPE8PPBFJDE/mrG++LLIccTiXV5UVgNJQLOl6SK09Ned3FM0HkG9oMnna0DqlbLGkOBDrE6Sjo5EZeilZfrXnanHt9WTSJ0igNQXCQv87CNifoisVyVYVD7U+DSbvxDwA7DHQZIxI75AQei0SqIlEd+pgz2WPVyh6uOKyUwO0ciZcB/yQda1evSc2/WrblL3i5q9F/FNqFRSngAVIPInR90iHXdlLJnHPaeXOp01r4pZ7X3/0UrL/zKHRXXr7ncfevuENplbmUI58bWEosYqaFPeIOsyS1bedWYGpKx7kCZYcyNq5WX6RcUCge7vI5EkE+8K3cU3VvgFFT+wBUUMEg6QXbABkBHQT99ynXUfRZelUqOUfNkv3eTaNhMnv0afDJZlvip82jXNzgMclGWYmkSPkCGm+FqZJHW8NnV160x0X3VE1+ilf/MzWrt8WZknOg+Ldy8oRwvH2DuwzRgIWK3s4DqGcXAI3ARI/AM+Ph0Qp/3yrzHGkl5eE0f4M5H95cYEv/VjMmsdH4WmQcqmWopnBPf/vU3Cz+rVZID1m3pWRPMJ/SOimjNTKG6ggclkZb/jv23Vz5d7A835pwA274OPpmJD/8KsLUPjKICDhxm8WNlflIi4GZJhn3Ddmd5Rsu2jgDw+1VZfZpcuv3oQlgd5QH+TDvy18JQ0tPJp1tLat799H8OgQRiEftu025kOKQjGj+104JAVCqmUBs831bWbFwecSC7QDpVHfr91iW67gs7HBgTeONw6CfGJT4LsmKEhIlCj726bL++8Z2F5I6wWhEM6Z4DxHFIBcs/ox2o2zYsf1gfs/RB1gNvvlFhURelVtw88LwicMMHMXeIXZ1KB/AUXYoLwJ5apQ3Lxr0r0iYLcZLaWQRtMa2sWFqEmYOONco21KDJlMRzky52MxaosrtjtEOtNfePa7gCDbKprFF0+fEn5jwyRLhh/fUFpR78XsXpISMXGU1RTtUIriNfRWXRgU0pZVd7OYoiK1P3QS6uwLaeAaAKZXiI7Ouz2xMkYzCkYqIQaR/tAYBHsgZBIQP6SsVWnROrLN38gAp2XK6e5b0My8ZNlwkRB0U0P9bGERjVhBbQYQg22EL5h+OZpFFWI1Rq1vKJDzrHUszv1Ib17EgYKSbAnFm4YFRGo467NSEERum0dw0x2x43Hd8lIM8LZu0C8B3dlG5gWiho/VMHChRT8W1/lWcTEfS5lVl7GW6Q4NVO6tglp25N8h1k+wdYFbV/cNWma36wdwkFOTDn2SwHu0zAoDHmb3FFXehIkIusHAMNe6zG99whTTSTMtNASVqYL78v9j6m2KQi+eT4kJExdCQ0KXTDZ4b56Dr+EPOytoSmVIdYy5k6xa9AHrXhuX/pbSXonliBMMYwbKrgMuefW1lEUUic7iNBOAkIoPfFEjcMspt/dAj/H4fIK6uZTCgMC35VRsiOLnwZ6e+9MrK64AV078EXNUHETOPsEwJaxGc9sIqGHtlNGC/saV1fxEFrWZz4Gl1YDCcbm0LI8cawjF2PhZ3rrLyAK9/zvn6D9aFXqQ6U/tycYcW5oumWDg3omUxZI5JjyMCFN2cl0kqKhSaHRkSr/qnpKK0buYFoKJVzkmyeOFU8ZqSXpjn/9i2LPHJhJS7sR77Ey4NjeD7HBHefKyb3Ak6cvkIQvKignKTm25jD1iPmgjYrZC0cLT2dCgpOsD9PQtEYSoZt/+RPL33JrfN1OlWSH5ST5j1Uxo8/CnNPQ+5NPhN591ov9/gJ3F6uTEA/ffa2KmzLZt/7G7fOJVBtWwZhwKKfEf91o3jO3Vla2rrYbWryzYekLwwzYpxaY3xCAoV/aSgIRzWa05lGJAon0UuYN8ZP/dfvmCM0mFgxn1vdRkvpZe3zPClNtPZ8zoRhqS06vJoitCyKn/Y7uDvVvCHMWleEFnEmhjDjkb25uAvPKzGNqSnC1GcrP2TvElOGOiNWql1v+G8WTD/pqVZSEqec5JrzDLvvXs33WDbSZ1ZyvVxod/mMCYUVrGqtzAae5VBuDLSMp8LwuWX8rk1Y4uALdJk2AcxWa0sG03OYqfltPQH/s0noWtwtCiSuut5DcL633XRDR/b9gVx0CexCXkCqF2zEKQHqoyyVWbqa+TLaghOBKTzCnk53oNSfmwm3htgUl0IPVJMBTAB/qDjZH03e6LymmSzglrW3nei+mnljxn1hyOu6L/Qz3/sNtxUJsv/NL56Dl8D/n3It4owMTaRRaSzn9y84ks4OQOShyQQYytvwrg7MdlzGknWvaUfN32AxC45oMrFterriPkG7PMO+/LEjKw6VnVEF0owphREQW83wdQcVw8bOAZPdff6dH0yqy+hmO6I7cIARBMMoyPdT1bIztbtCWfDMt3yml7d3xQdPCsRtD5TDsyLHE4/OXD0Yoi/BnPzc1LAvYCwY6HH3QCR9KQaCD04NrCWgupsa1UYyIcbv6pUA7kb4q8dx+P3edYyjuGuzUCGwOa89ufoyKsq9+qL81akVnKcjsTQtnWB8EQoKrp1t1G0MUJBS0wqmaiMuxFcHubEKvCpPSWCEI040gkteXwnxcojhGtXjwoZek2UVrxI4p0PwP/HaisFyEnl/M3p4SSouAKoVkV7LVIS0FWIDNpr9Po6n0k8ifzkN6e4ExqGwGPpqECS3hDss9NR2M2TYJRwdfTZgXM85X/YeF1Q0H3IyWyxFhJIMBUnZ+7v3tT/CNysKF0A1FT/uvCLNIOAgZTvmFwcsATffCHbv71DYo20IwKSf4YVHBag2tyKYgrnJvxVS60evsqTwqSuo7ulniVruPV0DcG/eaycRidikOaGP/m+py5pM7hQUMyZXuUVZYxJl8T0PAxV34msRHd2DUnh1pw27jsDeK5e9zVHMF1U9BRHJwHy3MPAvy7nUT3maM+Lf8K+JlzwQn4sh30W6oDOijvNaz0KEG+5pjUGJDdfQdA6MsMM+b3kMM8CuF7vrFNhI4WZ6MP62mm+IWH/Avwo7SO4cu3vMkR7BlQKA2TOGxp/TxQ2s9BzjtVJa/3e1IzGmlloLLzi8Harh7W6qJveEX55lx2cyCRoliTOGXzu/awk3sIkSS3Q32HZkJ9dPEBSkPqB6QTL2GGBy+If70TV+i2xw1PB/pfgw35l/lys3qYv+4y6FvNNDJaNLv5cEmktC6EItmnwoTDpqGR354HZ0lU6DETaxv7YLehh/zkStGHnAg37wIANCOGkQn5Q2KdDE8QCrL+G1v2pYSGtyyRKqsMNHXdTwC3j9rbF+hOMTM9iSLqy8RH0LfvBM8WQvLSvpBzLn5cXWsLrrMQaqO6iHrRn4pjIJcNREisZoNGXK3lsgDT1KSmKp6WLc5MFYriFJf+2f1Q9s4/MULfuZHQDTCfEngIA8fXEQ1U+NgFpFOUdQTVP7lChsJmZRY5OLBg8X6QDM7BRE3LeGyuxahWYC5wzYrhTpMZD9a0dVLiQToONI8PTuBgzCpbO3pRcCOmpCy9GYlbFCZQ4J3RJjv8ZeJ+pRWl1/eSw/NqOR3F6X+JYhw3RhoBNHMvz/9zxrVOysEKzYLu7EgKQis6oFpjp/39/hAREFT2MiU9FvYgsb9ENOQ4QJjBkULDz/+78yUxAHf0p1c5/CVvx+mViqIxIDG2PNyIl5IEjTOudbHefu5U2xUMlIry/mbu0jgGxj0hITb9mIZTBY+b6sgicD7mQfZX0FlQtd7HRRTyBLF0a1g+T0OMWfM8YdgRXljPuwPle7cZgHLepacEgh96r6GZAuvy1mkpADhgPk0rt92pOvR9g+NJDqcca2yKINA32I80rEaSMT7La76d19ClIgofetHwSzHH5mfqdyguJ4CnXKBnhT//ogT6RoKzUio/HwuZTLygWE1mHXe58JzjC07w6WmV7Q49ZiVs+EkrRDP2AgckG+Z/KBBgCGV3iCeaS907i4R/NGfRgkGv21Lx9sSlHDbGRkWTmzF+s1NwJT5KohN4JGZrlUdxSuYwweagEHrlP2qPR+whwhraQLjy8b0iN3mScTS0Opm4CunBnweD9M5aX5At/Dr59eP4SGk8SJuCVIT1t91y2mDXYJghFJV+VvqC3XaAFxHV/AHLUZWaqns3cVNqzKNpvEAikmwEH7JXz0tSqxNDR183ykpuoQK4zu54/f9ob5fkrgI8ENfSUiL9pJU0/ijHk1AQmvRJz/v7xWUh7dXYMGW744wv1+qtnCInMU7KQM8bWwmCAAp1ygfEWgnq7qskae2lHE2iTdBwoLgJcBttUD7Y5/lIvm7f9wvh/VmxTQHVdVsenhLdHd9y6rzlXBfcxfbf6CV6rTsMTbVVLgvzWhWQO4gHGb5hDUL6tgK033RMchMvLkU1PZ8wA1dgutqR+TCgey38An7Qkxq+TDkNF2Xd4eVSeFftfVJG685PTbIeYidGovxClPQw2K/WCtNbheWS9HEyxbQmjZuPa1LedxH3E+aIm7mEADP8EDHmX1adsR+coQFbyx5MOHJPjpUS8YfwWuf8K7Dtj2K0OnRN7+UviVy6e0Qi+C9hzL0HUgWPgT0+Rye8W5ecVq9sBRnHInuWfL2MzJiCKCK4jKSVEdc9guep+DutwT/G9IH84mj8clRtC6hgy47NIIy/jRcUfp3M+6LtM+7MHwf3Kj/nUF1aTMGfXH4MsHIw1/Qt/hDi3dNFNkAA9HCGoyBf+D1sHBMgJ5fZkfJfJaj78LwZikfKuD152q6Cnzsuz8qU4De/DrS0s4joMypwEOvkKPxXR+n6jDcE+v8Icne2cNqXSFMyo9xfM3YsrxIvD9HzU5ytwCTVpkxSaez1sx22OKRVAjv7ouydLcb71S/6QYTfDcQE0AkFFBOCpr945ofxriUlwjQDfycQSSeIT1YsStBZ0MPkjA1MXWSQDm9vb9xJjIRsB8wZMW0eb8EepUV/LbnxGrOHkU5XE/LBud6BYUw7cCtnof4sFn6HgDelymz+NfeapmcdBNbG1az8o2WiSvXwtfpq4fChoAGxWL8ZDnHAtzkyphuLntjrhAA80XhZumxWR5LznZ4ZlDc4xyQKWjaJ6Xdf25sJcZBXk02l2SeTwxvCImzOqn89PzeU0U6H3yucCLpbMB7dD/nuwQD49YvU/WN+YnF93lnp3H5ttukpgKWM2Q54/eL8llunyC3oBW0bHZwDnvmCLppX6y41Uc77z+kqTnL/9ZAed8OEUC0wOJlLqUkP+jvhgXoYgknStvhfsr0kKlB9pp9Q6fV6nQ/AQ1ADqJ+ByvYmC2vSDsaWl4VuMw9ZLwSZzlwTrClT5RoB09OolnG9Nfayq+qrKBppMHmuPwdLPJAYKG0D9+OwWjZFPfPbyOBHUMzs8/pq5psUQc0Cd00rQe4mqeEAIGVr9ZeC2tpA+xTuxPZ4GfAjl7yV+aeDMQ5m8mozz6TMfCglk/CTVvu7UwJWHQ6ob7sxgFaV+ePl4RLQy+DYTtJUkljFSe+IHEooJ/ZUSXWGmr6MZ8yq0WkLK1fzdppnHReakS+RHg6/vsdz6fTOuyJQcwCe7A9o4La4ULEsE9gceYKC/DTC3MbGEx0yKFskbRzG/2tj7nci2nsx5IysUkcTUTgvnXDXIVB8G96KQEiXsP7rkqlN0P4+X235T+wiaoJJnRVG2VdT2eKbpYOOb4WKw0DCeVlHsKsZ4SgdcNhuKyKz3u5WACntWv7EnGR9+s0P9/3LnhOISuRW6Ap0HE8ViZqSNq8obUook7zmwPV/EK0ghhZAub2exIbCH/xzY7QSHoPY4tAkN7VD17sB9TlvRGOYzNULSmTB8YBDLZSwkkFr8sFOjYnrJO7kScuwIz8LoABL+HslmnoGqwcn9PT/iE73v8w7deM+xYCt0JSYOVYxbYPADgXXR31cVAOVb2eRiVGEQhx+Ln8aqGpXBP6JL++shAJifBgioMLpALR4Rc2PM8G5wHODSZmWZl7QqZEFbVzuKsprwVQxItX3k+npSMsDgOa9tPaIJnGQcT9qrqqvroHbg75U/2hCMP1teTTASZiDgSx/p9CN92F4wFMHTMu9tinis3isbg0wdylIU9C3awAfaH795RZvznRzfkqhitAqfPaAtQD/N73b2ptgH4ckH6oCI85lH007BRyiGCDyIggQekzUCOio8qVzGSKHb4MC/7gbshe1h4BZn932JiDzQeC8FlBUpRq1tFUQhA6RH4NWhGFhWnJTSbWTLOTExcPz3/8KgOYnPtT6agl68/467vDLDUuFyN/fqIZkqFWPuZOMX2fmxUxuvQcSaSE2S7duCYIAj9W9n9HRU7LFMH1pwurhRkULE9xN/wooZcovFRuy8DKuI+Ji3NEwdTiMugoeRcxCC+dZvFX57K55uEwbi/MNjhxj4RK/y6J4BnwbX/RFx9d7cs8fJWDg/5lrUoT/6AznrVPgYdXgDZRcB8+E0ks2UpB2g0Pc6ZZjlvV/mizrg+cT1ZL7+1K+UlSv0/4F0RrFzmi8nP/tBFmWGx+NW0FvX5lukfqWUguL98nMu8hti6fL64VjpISc8IrKYcrizAWpIzSBLS9pIoSFPcj8yMtfdYgvD3xa2nfud6lJL1Kr22qjGzIveH9U0tICUzdSUVksIJonPt+MvxtIffwjP+yH4Rarhe/KaRbWf4Z2rltCUF04Vif4vveFXXtXslYUWpaLBE1UBa7ha002L6i0qlkR9Q5NQzGDVnWbwiILyAuY3AgcbvRWnaGeENSuWS9ItpsAw6oBTFNn2pHHJ4OPBaTCJxQ+LoreubEJppSbmibPqzMC9SQUY5KftGm8QZ52D2nIv527NyCpKsc5L2ZyWY7vRMTHPRAYlJ5jGrcBLKasqVEfcD02x2TF1KHiW/9Cns2Wkvg+9sm9Jms9k84lmVFnR1vDMUGokH+WEIlrVZsJPx8miLL6uWFy/ofd5Qjsn7Edeo6v2GsKvO9NJ5wSr16AyWUE9p2GDIQo3j31Qht7FoGubiHUAvz6B1cDtWVls2FSsnVAVUd5g3c0mZRBLjPcOuhvUeyZaQo2/6hQqO3U/j/HFE4s3rIkVJrZ1JgqLZFNyuBtgNCxEtBgw+B29Q08AP0eymJhmJvr1H8t67SdTWH0k6Db/ENp9l32+Kyu6nIMzOF2DNBTNFFO+RyxcisOstxnlUa+etMDRk49O8bFTqT2BI1Qm6I2KEByLojkd+QIc0fwVDERKOapkVEaTYqbGkeSU6hCL6rsuGVJVB2TVAGanH/1Zc+Kp22jMCv+uGjiTeokNWlwn5HGBFlkcGD+cFoSXRsPy195wri3wsAN56e0lZVgWvApOBjFfJeWGZweQlhzLpqPiRO3LeLU6KAd4/q2MFipNJO+LGYgCxM98CF6tBNs11N95kKuEw6jUCE3YAQjYf5gU+DIOvZpZWxZn0uc5Drx+G+x+cpys1RR9Dlw6uQtmFz1Ajehx/euCTkx0w5gtgZNOgAKVd8KZcdFg5juiizInHw8/uZWSUIKsvjAdBA0D8BtxTmZCozU4h7z0yLhElriCd99RBz2x3ggka04GBzWhmGviXr2ja7cw97G8ZdMfy8hhPkxcnSviv1x8uNLX1JqspokTCMW2GrIp7AITYAVHRaFebWVtLENn2lcwqNWUpUsAGhraSeWkv1dSMBOJ6uX0DwaJ+GEXapBqR3ifIAbYqsfu2meTaa5wKmVOJl15+/LBSIsMaSZayKehiyNrpLSBh+hnNtKn4X1AMCtQVfJA2DqWvqagZ6e1CJrYKWu88rsq3xvFeOOmbNokxCGK0twbRRzAjRVkEu8M0NFUOxIhUBBe+i4FWCEfyWwVq4B8mJohHCZSrN/3KUFJFRxluGE5oSTNZT0MrZ8qtouKx4tbPX5+4ztiD3TWWPjv6mQhri4XECNxL1r4+1b/ovlexaBqctmKJ2OwmC5wZgtB8Cp/yoKzanBQ2HG3AdBjlBsOYqCDEmeHC/pPd956b0WfgovInMoE2XSp8TBxM60q9YEE6tmRpch7t4uTXQm6DOpbMm0esxRAhs+SIj/dgjvICpbCYbWG404+EsNV0BZUeV3SAXM1++71tWVK7ABVtY/KO2Ggmu2F40jvDReCCUNQywIP6MIfCuL4r7Y4Vi1vALoVjE08dO5DXciP8nplDDIPYDtU36lAA12PJK2nNaxGmhCEBG0GOLCDRQaZKhWFfDP+8QpKowQQWXE1/qhVzYDLL7mBcdTyFqBbiY8W5U+Z67obQYLnvNs9/V2iRtN5ttMY4IqJFwPj5aKpsQj4vvoBUt/hKTL0s+wZJVCFMv3RnWRajkloWplYUT+TqcYEo3Pf8U7p/ANGk7eSHGC5ZBLlbSGr6P2vuwNsPvYV8CmMO1Rzo20ebyHFMXJH65DEDXRghGSSyR95rpxi3zWYvO+BaZYT0a2OHFAksHH3OqpLCyUNPJMtruiu5kkj05db6KLAFoMH6l0rS8OpDbvWC3B2HN9XWDFablBTCKgCj+XYhDl/V9UH4opThcV/FKgdPdxa8VjW4rsS+LV00YVvsplr8oitmzqhbXRid5jjcHLQFg0oszHjTdxeJkVCBHEOEef6FGf1RZO7tsQ9kcWbXe8oA5zsWH6PA52YRYP/g4P07zVIvQPPRd7kO+QiIFhyrykN+zE6EbjySxnlQ3VkAkdpCCYWHT0r0CaB/Lzgg2gHhOgXLhgk/DCoXulki8zzh+pNt2Bmaid1YbMoV1ipTyHzLEMkxAUHwFtFG2cNqYaw1RPjRydohbFJZ6R5mSMMkG30Aphx6347bJqW3GrnJ+pZiFbu63ozIpVPj3O4r05zYdw77pg3B9AiJseQF/ItKiCYDID0kMXRo285ko9EgisLMNkrji7neuTvaJrmjBA/dCYm7jVi2oggwVSrVHKqmB2ubpg35+VC3jkKiGFROtPV+z9hu1C2WQ46OzrQKPK/dfHyAfVIIiOlc5vZ/YPY5BuNs5glGfUE6qlDx/EfJ+xN52odDhS7qNWxfFr9rgTgciFRSn7MEYAEBC136cTkD2oKDnWPW6tHu1FMUyB/hQnSDmlE+XJSlpxf2e90iJ8uGdbuLkAO6g9jTCg3BaDcS+VsRdCexkkohVgYTgQwV+gQ6CiHledGILHLjpC6lGx6azLvgjJLK19rY00/yuKiugYT7ZBZlfAyQWWXB3VpvKlujHHU1pyYs4P7K7W2ah8WDVfCOebOanb91LhLOvYkVjK+rcvhuBqqZyxDBBN0IODViL1PZ2N4/kTLYutsTf+GhgpNwdBf8HvyvyVLU88hXSZb76IJ6rbJuqL9PHFmRewH2DvmM5OO/R09HwyfA5yok8OzNoREAxz/k8bOz9n5FIlzLR4zwPleuDgxY79yUS3r1NOcoPqabeOAJmSwfRXv8wNXICtutZHJgR5aANfLltN7WY0jAhphRxiMVouZQPffKErxJAbdZn9TFCO3ODpP2ojkDS6StwtYsYbocEQlNSBaChBPRhybUWIf8Ony+j8WQ2sR7ox1aBsN1QUqh6H2pEOHgjnceRViXm6ClQapsZaBlK4Dpw7YmM6H9uA1mJbOHE7iqrKYqQ5C2/Vmtlv7KkXkw8wKeqwGw+ORlPPuYFGlhaxgmtJCukjJeZmrVGp/AtMfXy2hSZj6BydQwdTFgGCt7TANW44R9qrGpqKntLSHjYnT53TnkPqBZ/An4PUsK0Jilx61gCBojhncQFATxXhE/BgQj2zGR75l+nY670TvoNVs5EppgvRbe6CLUajZVFAPLp10wlVPPkVIJUAE2ygJVx+liXta+4BPGQF406bn/PrzZEkKnEHi0r27lxhPhULDT0YNpvBdjqF7GdhTGOoh6/RfxuaYL4uaavXDTM5+oG5UoJk5bEtgF/B5ybIEHKExMt+KjpkfABPqIyl7LbbpFVf3Jc4/ltYSiJhVvEcR1Wjo//0n7yqO74XAetyLNooiVJeNmBJdmtI1k1u0qHduZdAUsH7oO+ftHcdkqGZfdtN0Mb9jIMmxA0OFDQX2rb/7GNTcx6VQw7+jXcpFBdfL/0vtNlBAW04MNsNE9QmLh4O7nwAlWKOeUKefvCChFv2wUiirIV6WzBf+Fv5rzzyFmVYEearfWZ3lVHDdx2zMDIWe6RtcERXZINXB2zeOwvl/I9RsU75sc9g0a49gwzGhgZs9aoDC0KwHXCQKVgpWhhe0IpWK/N4rKlrPaQDD1QXHIRH+oGPPwmNZjmp/q/Gxcna+zJslb7TgX6E7mRq7Aio7qUUweRMusAppRHAWQFUFLeBIplDICfJhxygU9c9TSRnqha7eRDk87/rlYLrasJtobPfEasmyUoQprtp4VHjGmBlet/zohv5ILRnfv4pRmGkbGD2xSfcVeNyDcSS+Jj8N7/ptetZYa0gEcgby9mJ9XU/YpJniSemcpt4YL2EiKVtfkEJEic3T9UXTJUSTMjLEkTCgDW6lK8KdHz+T6wCuVY8qgMDecvkysCo7FIO5w3ztIWS5xow29TlpFpl5DLPqFAYzGkD1F6yGVm/HKD709llCSV/zokBAf56lU6ZvadZTggawB/29/vmV9giwBOKlD7JTsoz4JJqFQ1VpzRap/6inqxLAquXl9XVPa/56z8Tw10iHLZvkCYpj/QO+vtcv+3wcfP/DGmKgylsNoHcX5yH5iOLD57az+2ewM/sZoJnQF6kj2XWwk0Jaz4kwu+JpA4zZbqRWpuNVMsGwLC3GbdoTGFuJ/dgT4DdeKoN/sczK0QPAgPEHEDQGa/7rXkkPXMVHCevQ8RW2hJn6UFPjtf5yTvaSQ+Glb55aqDqNWVXsX9huqB2c2AYUFRnMV2W5e7KA4Bf65PeTLu6rO1zAIgZVeLAZBS5e4GHpgCqWNImOcTyVw6LTnklJ+hnhy3qvpl/4CgpFJcHodIbaIQVSZYoV/rXj/RS+YqjUr/poVemuWton7P6RbK3oVhVAcLGirC9fBO3rXIX7QnwlanpSCeZc61kMZ+Ue+nCz9lkBsfC8gt7kDIPB7S0Ci5Rufor3S2XvaAbPxs3bSkxpsXA6EEqTlyRpMHoZYZ3JzIix2t/ZjQhdAu8a2PNPuIlg6nyDuPF6zjB/o79u583yua27231vohl6FclvDXN/4lqKdWTaxRCdKRkAkLI77vH/nfYDvEopVFf/CxF+jFHi/qpAAGPBN0YKr/638+G7JfxyAXqo/q+mQsMGwkmKR6dglqu+N73+P2b8ExaWZyH0yjJOYaZpvd9EBF3BQhrxXrDkwmPFEq1OToFZ+aimI48zuVDKEcyyuhFTKZEFUZmOfESQV8ps1UoWDlMLyXHv2+VZZy/aI/fYd79oEEcUq0ya/42je6p6BOIw8WSeOPFpe9x85E2UBN5KAQbwVkuS/5sfAZ+Fsrha2/+Jv7VWOz6HHxMy7458PM75s1Yt7qkhH4h7SuJAtiIpmvk3c+HCdBGWw//4NN6AYyLJuzdfma5r0Jh2GqP0Z/mrgkzWz77tdKJH8Nu/JGZDn/fCvNNelcEIgLfnVTARRiESF4ihCkNmvpUWzz3GxWBszZs7Xwc6cFweAI8FZwwMmJmLwUPpW+BpegGWVafRuZm+iL5w0tFWZqrLQFbBEVOc4JPRjDpZxmHr1KApiGScDQmhYXcDtF4VyFKJ0qhlqt3pwa0caWY+/fJy5SMO7oFa9iBjAcfMtjK/8GBnXEBmUR4J6O/I/P9raw3yUywTe3MsNdMLSJgW9o2k63YtNx3U5XsdU1oFx9Pkg7zhSjs3RxP28VTtVBy2Z86z74c2oMuOb3/6fNH2lW6TMa0H67+tWPZg2bs0Z5HGP38L2D2LLr56XsR2pyt+uhetKoQfE1ZTtiLxbApT5t7ct8TKaSLD/3h6Jm6RPNVxuezk8Rmprz2XtOxVnYahkUhXmM5qXmjiyivS4/EC96tKJ0oPDIcIE7l+ok8RUxQvolyweD/Mseij1hUgDncisQiQrGVKfIH+gRwd1WxMJcJe3UIK9fPUuFWYFUNHLJNScRdi4dQG+gf2sGiOYM1JbPz9T9JY0uPsM1UTOMOPf9DElWL4KG4JPgURVMLc1hdwcLYqRoU9Mcrb+5E31cMRqK4Fnb6rqbuXiQZx7jWQeWB5XGAoLdKahBwBercNLEJd0VxD4LC4gGiKsq7wTslTWBhZ/VWLLNwKXng0QTC9deeH3sLYzLiOA63UNb72gnUGYL4N753AR2acWqOwtOflcbwfFi4b/DuTot0hy5OamRoamJAFDpo69iKcJ8yILUxeh62Xz1LAgI24jbQr3xMAKB++hOsLB025iwld1dro8Mo0pu7xOM0BAksfRt5UcYz5tlQH3LpC4xaic+Q9PahEf6GvU1m53m/y0GrFphL2oQku0rJ0rxQ9y1psmjm58Lupw4pga62I+6Dpm94zhv5w05mD0U+l2KKcWr5WQxS9Jbe8n+SRLLWNTRL/9jYac3wftu4HQfoXhNiwOEyX1tzXogCmPmi7y7mP/Es8L9VWap2sFxvYJAUYEsZ4cGW6LVhU0ronR9fWN6oGAWaq0lm/DCnLzgy8vnwqWwGU0ArZv5/aeKP8a7oh3rkJTaiUUz7YoNzEX8fee/zzrCpyb4/Ytl6nzLdQIZKgGQCD/6ARc4sZQvdXc/jUObxh8j8w0Fg7NIan6vdq4TZriGzhosIXBzpvBhp4ak8mFwIMBcNMC/7YokX/oNsJHIThdpkSr4IF2NzIGBhBe6RYpj/jQqZe87y6tLvqyDVMzmCKTwOVtyFshGf4IXhGwrHC8AwU4gwbikfPa2LkbnnIvaWMrkKj/P4diULXSMnPoYtN9wA3SbWnI/oPXuqDQpUhh+Fuv+1FpY7I8F1oHPuS5d9tuH+GILkZmv9w1fKX7GkTeWR5IrTSgwhYHci1nDQ3qNjpKq4jQ5OAjoczb6HOF95AC1HLdKmgA/+zPAwHK2GUbTV8j8oWsymGcGsCEcYwqZ5BBbtbrmIQ4TboTvHd/8rFBp4NcNhBDmX7WCkqcJT8n/cxLkCPA5awTM2h4deP/Kr1mu+MBp6NQjBOHHoJyH14y/vrVd1EuvsHsqb0NLh5zWIducUF5rnEHOJbakKaD6/DJoYqdTiMwJn+EEVBDVFQqy+ZGLtbu8pSYtjIj56TDyfA69Vtutkpe3DiPDS2bawQjQbBbENqHRN2JAN4BfCtctkeFr+v8fySd7Q0P8+/NtrkLLPxSorxgIqthggsSTjda/qXYTtdU9aJan4Fd5zvPgv6Kuot2p2yHuWRDq+cV86/VWMl/RquorXouyixjpYJ1FyPAJUogdtLZ9hq75+pc2h7n8LCb7smIp5yMbTu0VqFruaCVWKuDXvvd9ly1KVlD6I00MH5dzsP+qQp/TVGHlcGL4wuktispuEZj7lOahLfOmUKwSfO7pL4FRPuHX5MN8SoLfdqz3IAVT5T98a/xb9fC2yXGR4pXq3wyvgAmwPWKd5MLtyuUWkJo0tPPzLkmGlQhTYQJxk6erRDy6vYZsn/Vvs8rgRi9mm4f/JaGdK0pL2SEg5gxtS660Up9K/kkW5luHSWlljHnRVsLEmwl0lBjHi2BXVDmB/TJN3nLyvlQ2XEaVcc49rsG7YwgUiDTqLHGt5lCLQnl9TVYZfivdoZlqrF8ZPu1R7as4jXRm1rOz0jERy9ljUOMhwrMUmGSMYwVqgjY+XONjlSdps9bqfKPl+1+xZiJTXQDSY2Sr39VwDa8FW4LcT0SXtjHCrbGMLhrV0XILT/lAmWxrqM9Nx1LgsTY/+IbU5gfqbEctuHqbScBl4jcfqF8sdB5w5QhdzRsdksrA+pz1MbnUTNgZwezr3KOF4Ro1KaxbyGHpVb4u4GDChlEB4XS3tvmR25vsNr/EVva3cArh/tqpKPcTaH8R9IS1ArM/LgV809im2roM9p0E3C0JExcLpiPEh82qBs9bttdvIHjba/1yF0LspFQ5XShW5Pk/AMk3jKgmhYcQGMf0w5dainz+JE3Jrzjsy8djgOnoSkfdplKQ8ZgyPcNNcI4V9/m0UtzXuvysizkOMAfWXo81JttiaIYvSK4srTfhqyXr5YELlKXmkaN+v7a+zzKVBO9In/XzGMBqfgzZpk3q+4K2DxOJ4sIwFH15lf1fqGNrKc0eHkQLXEnp64vS9mDe+yUJeXyXPTA2Jk+hgJQD0vrHMyWKJsA/Oc81MipbkmBm5Q2cprtIM/nyh5jioA3MIo8YhBXE3u1IvgyuVG+EfsnvYiDhJn2ogTUIRDru5gC9OmUny7OZxhbj70TMgfTJtFr1Lz1zsClo13/hWkj6cAEFn0BjV8sAkNhO5DiCjIcPrt249l4v4nURuvAnWuHyrRsXlLOZ2NbNuZQlCWaE1m7d+ZmAxbxwdXH3cYlknOG3gA4O6oiIbQv4d9LrlzwxQ2UD/f1pLpFaM99BT7J0t98eFXGYq2kKS50NKUk4yOb/Y+os4LS6lT4cpEgLvVhLi8NFihSXtkAXSnErUMOt0OJOcRa3xZ3i7l4cFm1xd9vFtbgUzff857zc35fd95zIZJKTk5NMZiYTkI+EOxO7tLaGoXAl9+7x4f2uDfwzFtu4WnY1ZtOGBggKCq4P0FUNibLZgGBtnXm5SGmiDrdcF0om1ETIcXRi1npubsMNBUyx4+dWlDLNeBZA3VYqm4VH0ZTst4pbS+3iwzM2hcJpTtpr9rhSdBkdQHn+MKzfk0CfuUIcuwHmSa+gbxr/n88Huu2f08XjkSibai1N0cCIpDzEsFAN1uPm97lPUIN6VuPWcKZUgX41hVD0GiSpuzInI9UegTqmu3ZA6cv99UvPZa0Nuylh4ukrD5q53yCAfxCbE+iZ5E3ov+kAAEAASURBVALhJhAioP5BIO7duQ8B0uD1EG2AXgDJ9UpMJI/pM58pIiz0UG68HJxIxfMWZoL2dzq/9oXuPyFcUdiWIYIAPawf9+ZcPmKuu2TAp5LmvVAMz8h01H/8ZAaCYkTcf6BtC/C7VvhPGLSIOcrFFV26FW/5G29J83WdjyJy3gU44fGsr6g2JoHbX1Sey+AV7sOIDcbxXvrEVZgRuBm3HIy3LruRfUNd6iUFOYLEwG0gVDbGEs7jPQNJN5DguuGNGyr3YD3sqP2AZicEB09f+OKJkIp068EHLc5HcgM4+PjHCG/rQP4Gz1Xjzib/9WKlV/mOQBF44OMPIODKOqwpcbEqPz/43jy31xBUyWs3X9eLSLJ2sOMlfb1VQYj8f9uAWbeD6Vst/IF41VzUYWrEn7PKh04qoAtWgxZmonH/Lm+COh9AplaD7INT7PoTokpreknh8OJCLVCofk6giC4cLHkP+wV1FSu255kDStLOHExq2SjSyRX4j+KUwdyzsdadn03y69KHdvXavqtNskcsh5iO78yVmD8DOnwSVQ7scJeR+lQfIeGXvb3u+SXZuQDtwsZqsQdlx/KqtNBKhwGTqsVxYDr5k93nMqa/6JF5+M/uH176T1WAlwnjxOjnAOcOXw5M2vukuXylN2LDh0En+/uJKilVjSbHpyylojYk4+MjRa+jOxe+Ecath2JFzTbYVz4tDICJw1zHpUo19YN3xqUE7/ZctxuXhDyrzvugdWdAYPnDrYaRgUGc/YovaCdBr1LxR7rM1a216qBoMtSr5KdszO7rX1SQSOsKzciQeRnZjVsqUPs1R0eiGnFziCjpD74M2ZlQj5DEW6ZbFsgPcA1XSlnQB1gLkVFDVVG0XeYmhNmtrQtS86SEmmM1nZDaU1ZFcIPd72xUYAlP3XU/eyvCv9onLcjD0Qk6i5AhEpfWruLt3RYpStnipMPl/WGej0owdCxQYfzOOKZr13Pklc3/zoHHe3azCcZF4eTafReOwhhfSk+EYI7n1sbr3znuQDVM5EqJ17OONNVfW9km+WTVfSy+L5erRjF1uOWHfhghWJL1/ys0LJYPfzznT+jzYz4cM5GVTLjUVHJnqMqwkHeyARcF+iKnqJZuwoGLINc4tzP8IC/xX/KV92cOaa0np7TZtOCOgRhWxw+fgx1pI4Kv9zWL3uVmZ2BqIEVTXxqVBaC35fyVBD52QyH43GSo2eOt1nhgps4Nr1UZ0vE7n/vilAaLCNpTcMFVsmuItk3zUCc9mJsKvsydPnwpaKJiQT0xsmxn0gsjqgp9SrY6NZIH8AKSq+9fkRIU8Ybw+wC0Di1mRAw3DDOE2Mq8bkAPN8Q4CoiNBOeFg2/14iJ3aMApj2ZIR1e+6Leg3khCsfCkvu/hlAA/gs3pt3wt6Nob/aa62/yK/8AgZ5ZoKTugWoLmNinETcrXA5bjh+NkJf/8Iyl16M/vuXvTHzpBPHMaEsZS6KzoKdz5qMZcY5HAY/oh3WIT8t0mNXzG/O9WRItck4SRyDcsOYZLLzUjUcWYqnNj0xCvKYxru56ApMrClt+BJZnrmzvxSChlOQp9QaoWaUYH+pyFPstKXAKkjjO53/dd/5MO65NY7GiaI3YpgS99YVaSnupVmHqLX3UDzzq3e+PPirGy9/omy3Jp5cN+P19QxSAvC5ljDEAov4u6rSUhBBbJq6y70VvXVjECzM9fLvZpBwUJguSBqzVlsdoPv00s/vEJbWHjmDd3xSd5MZ2sxaShCOMEHXfu/P4AmCGwEVx3Il4JDw5lD6WLG1Kdr2MBnbnNLcJwUUwH2irjM27gMQsEr+SovpeBMo+79gMqst9GFkOFLbe7PhKqZZKqGrb91S4IKcgPkYzTTmvOVHxu5reDfFZMVoU2HCIiXECZNJdZumyTMqn5TJ3zdiFhe/hpNL9QdiCRfRjtmfgNzJfsflUZCRqzxNiSy2KQaIYE/JBAz6y7oMHH02s8VmCeMp2BS5kEbsEP8b8ixEai4YwDWsxhlNgULUUrijSXdXaX67D2KuK/tSa0LVhDhtzOOMuG1LxYYsnV6tBttidChvjOp4fBE7gk5LqMV3Mv78yn9fMZMQtAOh9ik3ctVUiI72tDezeJs71jmBxZVbH4s6GeaQAA7loCD6oewI2juIyQPUPGf5/zyF4RIYZJrBUG5jn0ZH+WchTbSCSOUk9pVJT6KOO3ZMP6NLO4NAPw4IYNdxi7Dzi7nWMfNt6LGuGBNNCvsDJgKqKn5h4bSbXyXNVhyrOUDztDqRmXEpf2dRicddC4HGPjeazkVU5Zwh2fmtTK/6miFtWALk8Ja1IV0nCWPv4mwZOg65+q4Sw/+L8+fPdu32qqUaLgUmo9vSlIkKfa87SU/hK5XtEguVpg3FtRbN+5G0XnjAHm/gZdSTQ6LsDNgR5ocTH5VVptSQMSSAfrw1R8npOZXCvx/cQjg5Td5vVlViM39vHjK8r/lti+JmPafE94BvMio80OvoXFfmh+gwkIZv/gEyY+owI9jEIc9pLm+pgZZh300xi9Lp548qojbQP2sdoSgOWfFlZRtYx1wDnwO2HRlKD9FlyPYj6vduBPalABGdevbQ/yChBgrYN04tWj9U7eHyhkPmwJUCJdOMberTfoTwyyz00V6DxwDaglVK7PNW8CxVkL2P3fB/AWWAgoezNFd2aL6pdX8ey8JZam2veObpUHwXZM0NMVrPiua6cI5N88jvDHDwOKBkFgLIRWHV1bSmp/bMdeewv7XobdvGPgAAH2pZttCxgp2EcqFzY5e0LBjnKZnKTy75ui3FXbX+ILdptL1giAyvN+xjOkBpRqWitP6MJpDDCtgmteW4PnptV9QvMN9ZtwA/i+m60UfGN9wYgM2r49QjF8DcLSCRZIRj/supaWDG7FjBsxJdM2nsJtBaJp89EuTDtuivnh/Vh4zLensK/GDZmM3Z1Ey3JrBf1AnOa0vlPbevZc+hKbU6ZKinjPTVoLx/SsH18gnK5BJBPfy0z9Nyv9GBAupQBXNgA3kpEmd18RNV1ZV+7ikmkoqeOeq/3wMDXHJJKT1SpM0Ck0PI9IZzzR0gH9mPUZyQIwz10IhaRL/LOkx97FVy4lUwcGtEi8JGjzV+tkngvDb6GMfmE0QSSCA4UIc+GCVw5VwPJ+smnjoX8JJJvMDLySEYshzPa+EXcZRZmNz+hUxj7SqtbylJtT79o+MvNFqnXk3mOQqeWWXTV1XUMNNVkFj/ltSXs3INFWvJwvrRXVYpzvnq6Hv84389entGBxi4ToPEPtfmKIZ5AyDKVk/zMRfvhN//6v4kqTsAheMwvuPATqMoRaeYwNDKsi3Juk7b6kYDWZ4EXb700vdCKAQxmTq9w85Q39gL7xtQKnWWdOUySNZdhHOc7p3aImq6MOqqSh+hLcwsL+DllCjQl153siXbGjeK43f6NPsu11gD+i+ij8JVW7fnLTf5gbwjir1jV9yGvs6E//BfbWYmE2N/Y7KVhsbHNmjnhI55h/X6D5spk3xMghCO5r21TCs+mL4tRrNgZziBKvilUUL3unoZH0DdiwEUMVbHtyflyLlmmxvPKJ/JJAfxYfEkOBL9FjhXoxNMBNbXZWZlbdyRCSBGIyRHDDI4sR+Zlblb3AlM6BEkxeqaxSv9d9mZov5G0lYoRxZ2xpB9sXFHWMcTrEpyzco6omFxpY0Rc2SePCV3olxrtmHrqUOdKm8oFyQ5QtEdDDgwf2EJLm5VNuLs813z8dUqrCQwhdQTzzhWAvZWUwB3FvLoIWq1dIyrWww2fwhhEHpwFp/yn/+pEStfZeoKIGM1WmW0l6B0SR0aZqCy8K6bbvqUkDCjoW+fJZHrC/K4F7GLSBLKIJyypjtecWF7MSXW7gQxdJ3g/c4eEprCoEAmO1I+nk5RUik7kk8P3cslGw9IvCRdDKWo7RI94U83Eh6hpcx8Yoxb+Lene/cqNw6JEB00ejnQzvGQ4aTnc+IZIcazLuRXgDyDAOCSerDHcindYL6V4GOB7OF7n1jUkv6Zb1IH1GI6gXxWAAGaC25EBEMo38k0If6RJMhzlt88XnEZPSSpTw/UIAH9Rs8kesgCYb/w4M+B1SwywSUvImnMCwUiPGzEMXePVLkBgEbqu0d74J/OqqNQIuGm1Sny3g/tFc69D3tE9Otcy7WJ/Al37HDZYxnOxLH48k2jQaB6rq79xS5WbA14EsuMMJISS06d05ImrLlEK72qRc85vHCO/Es777CQ5iAbTu1leLNBzgF+GU8mFef8Fk7BBxchhTV9pSLpEaQMg+3w/7Z329yfHvsos1ADlnbJhAi9BFMiMIczqpVNHtWOg94Upz0g/tZFmt2PDWj1JuPBmCO6akCwQGfVYQUWdPAgjyr1J26RKkLqZ3Pq4Ao6QaiudG6oDlHh/1VTAIHxX+Hc/H+NsQZTw5iw/yH1UV6MCMPicVoxHPnB1FLC0OPjzZRM/H2Ij7JrGuo9gewzP0FMElFoKKWjKurBhdB/pUDVYx9hndIe1ct6AD4R2R+KVVE1pIdajlwsma06rDuppXKicD+CvG+Wyt/PQgqChG5951lnaFijBoztZaMIb4ciYTngElY7wQS2O+sqUUyXSTr7h9IAyPdTSH/6Q5MCsRso33g6axTov5mfSSwkXN71lj8qNJRthbb50IVaqPiiw3/boB/aqAZ9cYP2mwppbYRTHslMO+JEJqJcDWWQuGeoAfpR3eEvV20ah5OFC9IOJwJfVBzgyR+9Ouo1nvHpdvu1uZ1mRY5BRG6twIn4Yvtbui7u6R/71EzNDn5QNko+4DlmDZilVRSwUQhGtpVEBoevPr/w2L7f6S6bKaaE1nz64Uv+pFHKG8ShOZiRsF0vJ7rpKslhx7prd4/+p8V0LfE7tAytXSEZbokHLYwjwiLj3m8p81DLZEYuFgjxkx6Lw7s6983xXK1AJrp/uV8L1zUdT21b1srAkIExenPtdO+A9ovDEGE6182JeZqfnY/1pJ5PL7xshc+id5257DYE5Cl+sF0qHsq6EOcS58v92DC2xFXEa6kxyP8DZYtwYBv53uetAdv5j271dBupFTDGumpu0XLefzktaBaSP/wnj6sgFwfIEBtCs8/8/RkfehTRuZlj7bDIbAAP7V31XnXclqzFiXfkEYWHr/k05hXCyRv+d3aUDQ2yyPasQTKCwJxM09ZZAuoSY66o82Z7yZ71xPQtRCbgstXTMnCGWwNZlRriM/pL3cf/dekZj0V+AWIJR4oRw88bHBvkiQ084BPXd8P9EXDBWNeuB0NkuM5eeWEjwIybPoN9L3SKeJxBWvD/qxPSyDKZe/GXuGmgdTe2pFY5iEHZ2qXrLOprhHLs6k1kfoL5amx8Wuj2/+4TRA+iWDzCz7TqiX5BiyiVJxQmL3i0KWvo1x2dpXpJUwDrp1KJKYJILobYC0NjzJxz7zavfpYO+jGFO69pWgQ7ucgGDzhE7ONtFM3NwyjqOAStnSUDgWQziJMdoWBYxhLGbjh/PZCQRKaSHvoEawjrEsDfzQW3jWhYz1b/xtpRBBMTUueMHETGYRl2abWhrOr69rBcW7CV8DIHD+79kCzw1iOrOYgBHGwtyNuoEFHJYr3/pK8HX5LlAyt4o0NzXoYa4egvlVcC9UOQ6Pnc6id5Jb+dD6lc368fq7SWtUjDaKsSaa99DOdvOPf81K1FIxl8ShAkICvkW8kJf+xJWN3aVUTYnxybnc6nlKxsPcnbAS0urNBwMeMexk9uJDCH0BjsVUDSxb8fqaxa1AKbS5Kc1q5vAZp3AI7MuCs1gFJ1MTON/9AXC3XyvLPb6GFcpmLVC+Jzoolt1ioK4n7IV7MYAoYA2Iice8TVnIlqeMtURTgtgyESWR1wBolVkmeL7rp8sD+e/s9kFGJe+MKGM6HhsIbNOi+wS5LkLX9dB5AKw4YBtvyvR+UJCbAjvH3Gv2Jc227gU/rGy7DkzW11UYidBJrOewo06rfYH0hNhzb8c/8XHP3ZPamNXeLQ/k/HZyhC+VSarErcj2q1+MsFMgr5D0SaTGENCraFZ2VLvEEHlHwOojIUFPfq2k5j5POKuxmF2Swg8LMd5UACwZFOAE8VJPumLawBKNfPnHqmAbGidBGLbnqpECM95V10oOl24PEdPkV/AA9KbFS9xNVGux2r8LmCY6YCAWU5x4tAkC+IfRdQf18RXG+6hFo377LIRDWI3hZR6Ii82rWZcbVuEcL+EBhXRkO8fpN0RM4/cdv2C5bPNyrj4qnixMq7z6MW5z3moSZhnJwQZpZrZiLK4Ch8Zju0V52FSrWUVaZjjeOBVd0eL14Px4PlJI4r2XPraUQvQM+hzsWeOLoAuc3kAZFXxOdKnWarl2QqIo95/nBAwv496fi6UTkMGq/UpxW7DVAIjytRVeofWZMrJADLLAsjj01mJFrbv3xhgQQtOdBd2TT6wONMVJ7JsUZcJW4h/C9btvW0rYzAm78M7gyq0l/j9FZEhVRm1UWpYB2M0cTSKxOGqJi0xqCJUT3eBhsy1SluHAouHQXSTJXUdFRUW+O48czzwRef3dGZXmfqSPG41CILehKMRx9mZIv7Blk0Z8wnadJ3JQ0O/SrOSs2XIyVoCaJeNvVd8ztKBzWSC8PrEqKV9d0y252e/ZLt5YfmIW0Rnpv6iGLJtI5u4f0fuY6ahPdZQ0flRldOzkMz9mzNFLmlh+Av7eU+zIHJrfk6QHAW+ChDO9hA5wOedaLKB3LJR/i+Kmy1dJIoFh3w3F8E60wirXeALc0JN4RXu+xmOwSqJ05pInducrQgivvsXelRRjdfenE33IFdFTcH6RwMvMY4B+ReSDfYIAGBNl3GLIUMnC/Sz3d0sqjPvngBLlrBgdCxEEdXNflGAesNQAYn1vptezKW1dUOI8XZqxbBQHq/+OFZdQEzQvtNnkXUiX6WNSAjABgil4FCnr27YtRexZKDXh7eLcnI1hDDLt3bhvWRe2Yg2OqR8O1EUD4A93cKTxFE0UpuoVf8OcpOZHe+2WduYkYtYcYJhI5TvV7Llz6jl5/OvnXGRW3zljTuLZ1fIBwLFU9vmYBuSSphXUUAViiXdFj/CxNHLh9vu39eyjJ+j22Z5Ga6RKmPA3AGuzj7oZ9JIzNTX4sGFSy78LZvRxnAo/JlQvfNSH0qANstlGCUWbxrA8UMGgZr6EWJYba1eESYsQpUAOsMDZc4svr7dj22Js9/xrSE/kBSHHsofc2gobQ2MFqieGxfFpo3EXqmotw1mULBVUDZfS1g9iRtRliFJ2CvnAN4bEUbX5rZKxibXSbBVDA9EVu20cM88/AHTER3yjMEKqn2Ceq5MvFdtbyyDtOjAehtvTwkXnywPMdJ+yzqXLTDy8Eh3BV9NHH7e8NqgZYc3HuSMZcVqvwC9ohK/KS6sbe1+sViqLXn1TBACIGgo4AymHLyHoC+wsUbXgefiMXx+CUSQuoo8EkIFT+ftGhtKVmYhNuk6CU/fiUzywUswd9edavFdGOfgZRl1+RHMau7L+F71d/otPjxOsWP3DxkCWUNaP+eVO0mvqJ/TJPWoPTdY5ByoJgdk4EVtua+75WpkUlmzeKmVLRLy5CK0LR3n3zcDbNh8M8a4HMEmRIcUWpwzems7IHX3zLN7LYqLr1aMQsVMFBE4Ym7OzMjyVTz8GRpBUcKK30C61aCYxoATgOJqEe05lUVix02QxWRiVToOFuoNmQcuTwjed2RvWwJpbrK1HHzKrI8bbqufvnzReKFPA//YcBJUJXefqEFxmzzcs3S5AEnJnt3ifxn5o7+3Tmm7y33fVSS1k7vPaT8i5k54U7N0/7Xqqbsbf48awtECj+SE20Cm0p/t7E9BP+9uvyF/SFI4QJQ+U2LyeHqJmZ2GcUIp5iU7uzyX3qf8yZJ1s53Uzk38IDX/ba6mmXZIcuSwTFWyHEP6S1BjXJKtYTRxKPEhYlbI7r1WGz4rJwsG+GeqwFrkD7oFUKDswyBNdIhIxMmT/W0evgUqtodjOLGIYyYuzSZhJPJPgJOTg2rC30lXsMpbhoiyex/zIInYQZEOdHMM9G0m3S13YoLk85EjpMytWuSkNNkJZd7yyXmYIDwhO/6KRpRYgHugujc752ivebfjKbjB3G8hMgyHbhHzbMn267GyAfzKQay0uPFSg6qdmsG3jgWFppENfh4Zg+KML2A7I8loPUi6PDrXRQv38FlYzT+IZDs4BUcWsIK6z0vqCk4JgXdVV24AKQmYwAkzcBpDKOt0/1Q8a9UV9JCzFan8ZVrkszx9c/6C3KFTNz71p8ONW5iWoOYCEV9FgXewXwGhkWCk2xif8o8nub31HDiJkrnVHP9jYSRoaJWG6C4LdBEc08+RQ3rZtT3PTd0sBt0hGNUsRNyXCfgPVwHG2xFTyXdhy9LEpQT+E7HjQ5RjkousMRWi6fyaTblibqA99kcT+Fa/jFkz1PH2N3SAsOsa05FTzWAlWivQUfIJc/xYaWgGYF/xCFL88PBSdpyn6bj1GJ4PWJsYxmgwwSTQ2MuDwloQ5nViwuH5CWxJJIDfJFgOlrw9UDr3KdzxD74wEZ77XiK1cofp2cCdpaVpiW4f4KzSRyfIMgVr5uBic8KR4HZeR2Rgm9K80kruEPBmzSwz/A6NrUcUwJ68yGLI+iAt7o2l2SffgDPgzkpP43XS1mfUCUIYrmsjveTf4v4uVbaIs9GPSt/puj+L7rHep2vE8gWlASHX6C92giC9Gt0Kp5V9GiRc/9RmbuVLWn5TSwy35ZwWC+/Xs7tgX8YXtsRipBLUBn4XvFrusuI+utFHBLlLm8vg2K9vYsAeAx9QUEkvwqz6G8eak7kwginiqokSsH/9ld/n551zC/grLeJePiDh25E8m1gR+6G5WYOboQhc1R9ku42K6iykGVYiwnvt58Aao2dNFmN+lq0ScQTlteX0iZJWXSNME/6V7TmRdeZmUBOpvdRfd3u04T5yA4NTbU+8JMtMDZtZOfg2MVQMzpMf5Unde0/YPKH0X957yw/uK/dvhhPIc0ny+jBHXdiB0BeQ37Fb0UOWYtkZTnhkRM5N9rJBLFv7zJMsXX2rUny7cuwb0z3j67C/0Ei+H7Qdrvwo69EjU+4JaXLe6DFNhFfk98heqa/HFpg2dR4bbh+4VbhQz8EE9n7hmbqMWsbI5qphc1+2+kav5GAXvSvaGS6ULg+pKJBp6Z59WVo79jGDF2BgH6wEb+sYGJytKtfqWXMWLy3isuxVhD/0DMERaBX0xT7WjkzuOpSu+Mm1rbHfjhx/MIk6+lIiixNH/0YwdLXJHvk3yucAj/utunE1P5iCrXtGKnrIbejeIIbpKDiF1nZ/0GdONu6tr3Easm6xajRK1q1pDwx3QwtBDAL7B6fcVdTmIvKKUSYuqkvIZsUsgJqETwJtNT4njzDhyL8SDpBS2ZW8OrlO8n7PSv6SpSOQq9cUzypc9SORawz2fkV4puMnV4SC/x3AWk0ASGAUzlBFH+2mb36lMtsMkOBt9x8eJl4wov8+XPXCbJWbqSzSLDULQIWSAQ9s1bzIGzihyxne5NFvoXWkUkZPdrNY5W1zw0X5J5IFNkisP0pLrO6yX55RAwGeyki9vpC22KoP9Dy9zDE+jTLz+MvG1Oh22ElTjpwEkm5oQY3rVCuBihONLw9qWcH4+RkiY47DpbOR/RA9xrjfrq/Ik9zzkZ/e7sy+vT7NAwEMCFJshL7cSPNjYFaBPw8Wvd5QvQAc7B7YAWim1ju806giRtHBVfrWHnqMyjyGlVQVdpDxXRUomAuHfxsZOabnzeY+H3v1/LpOP8aOCBmwefKYzp1ukLq7R1El/+f4dS+Ovo3DWIZgsvkGr02FEgEsJJF4S0R57s68QFSuREAXL8YEkw7eZkRyGgrRERv4vbR9ZiZM9YqzWtNguf7nKDQMx+NAbTFERNNkyQfC/BjVWEPI1Vs6vWW+xe9qBeNq4Y+HRApjuj/ZXkdBpXOjA+cQEbHV+BHH/9dnqMck81HmM2jBXWGCQNCpEKhK+yqu6YGP47KDjmlz2XYddu5r+yIQ3z6rqXA9bBP0qEo1qMAixhmEIP8blMr+fsb6iOrbJtL2AnvvCiWgLu2FLse6B6ukxHvqRLTWAlptg5rsYCqUw1ziIg/Wnghgodt7huRdbLO0HryyVP1grJYnDdSKX4r/m15Subo5WnE1iEzs8laaZ0Mu3nZoewYtMCRz9FfUpeiEOuD9DI6Qhcbu3Kvob36UJxws9kR8gmo2B0LxBhD98Xe8tyMnJo2nYnAMAAzyqTgDaf2CR3PrHn8p225QH64e6AWC/EzmBOVxPXMQy7bOrasVQ+FyvTqXCYpSzBmUDzre+4q7AROpQq5PSVhvxXxvc6RTEBUnZAgQWMcxfKr2caK1pVhITrZNdCZ39oWXD9+unhtPOKvMSMesgPz4GoJR79g1arGPH36BCMNtiN37ylnc29ARUtmOPW8Q0G2NkfoF0617u0C+GUwWawz4uEQzHnBgKkDl6X33/5UT6jSIGRflp/nGsaZIyX+ern+Ie7NcYQlIpfp3hAmOp+Ap09GzZdDrJGseYT4Zsg5+01EAhcO75sEqsueBWScLaNLEfkpZnnEzX1gZsged3o6dzs6PfJW/4bJYhYcaxN+mG2RpTAJ81c8+WMOnzWMH/IPfsNdQGTH5ZVaKh0aNu0wp2xK1EBY14ffO3kgLHBwFP1cLdYT1u1TZBlSCALoZRAG7e3SKQyL382GvfkxDQwe6PYiEkDf3g7ycKR5trTAEylWT4Jb7O4Zv/DKWFCYaLEeB5FcrBpwhjFyhtWK8bgKu0STV8m+o+rM3mCB+3WQh2DiOZg23Fkh34byYnLMK2J+t+DIaybLMLPG86CRpBm25X9WkTCv1kY4cpkGmwpqORY7Nhw00sel71FESsCsV1j9C8EbTgy+kR+BYc4YOrP8PQwCNkuPT/2HwvY2wBHfHID/7sUHJp/+O+QSjcnHui5prSV86TttMunkn/RIdUhijk7M45iqhg6gleOyfWMAhn1saapMT/VO5OLqD7K9fBDpcS+BKZZTwQNLUcsr7V5XwY/FRDKT56XC3bUEg5h2pe0+muyE4IT77tHlwCx16N1GKqloACj/W3dglX4UmWCoGf7rRYhcNgop3ZaFbfN4lKk+hbii5dar/qbysKoxzZrM+qcvI5JU6sbSAU/nbobf/4MJoBWyDqwNtECWSswNLvoHzVs3O1KqP16/+qoZBgkteR4r8RN8N/U56/T0k3CaqSvxnTTRgsOB+n+LHHzxBcd8Ac72u/shegjKYBEl+82WnkfR/rwBemqvb+0Ezlx6W61ZXpi9ErXlAg5zNfOOWKGcZ8fJufPiSeDwsL5qoOn5BWnX0uMSOSfzOJA4h5IsHeHJQWIHT90S2+sZK1LuF2gf133HBFdSnt66kDqkz9d4BOhfcHL6mJtjnskmbRLBtiWsrWczx6ZYSeX/D8tYbWM1HiDy7rfxS7GVlCsBqVImMWgzKihFFDE4r0GFkLa+zxVb/Dy3v1Vw5IOyneMX8+Rr41Z5AaKlod1Nl4V7jZKHd37X6d+ecml1uofXXUKhNZdqwCaDtwBWMLGtJQr4YicPgG6ti2RXq17s+iqILrgxNqXTA68pPuLvzCTqRgwXvRM/1E3DhtiyIKXlRJtI231dvZd6NsmrjP1yl3Meuv7hTvSC4NgFWFgP3OWMw/5q89UO5Po08r6gYjXZ7y2gGATNVO437ix/X2DcqanUUIhcX+t6ru2t9/+ySfKFvS4awrJ2LlhjemylKT9iVgurC28+fz8KFMD1bmtFId8SppcpPZcv1IddiaGnkWO2T8a5jp5NFz+GUzG8pgfrkk1ODau0iJCoAYa/OVfH5YkZtRQMMLeqL1o6qPG7LB+MsKiklM2ysa/6Bg927JndEC878sg4K2jXCFGVLejmNDxAXbzKc+la8nE+AxGpN8BOlb/tLc/8p/+6M8MBfk4xv9uyEVxwt3IoyLfC3sKRblER/goHT1/KCrih99+24B14l3evv2zlmmLTr6+j0RgJOYQSBAyJZPWlUSoLPnYbKbHTc/2Y5BrCZxc0RPzXX/Ntwka1Gu3RehwvKnYcttvmHouo5jyT5UOnzXxI0vqnL5AACbh7G7oGbvj7/pTm9QEaFtgUqXMHGH5pt4V0URy0FsrhZLnFWq1QcFWZHqzfzKmUz8UmvDYJ/gNuiiYZDSPgX0H1n4uSniLdB3pcufTcHTMbYmQdpPvRz6GvAarEKYM/DrqTaxXR/c7QqaJWwoVdhWpVaZEV1aQpvs9xrO7yjmKGy0w+x0dvM1phmei1odmZ1oTUF+Z94rKgdfiq76HPjm9LkEAquXLkowW8SQx03MyQXaDQd39TiZPv3R/OW/J4eQwLCB4YTCfyjk61okQC19iiz1wwO9A2lDMJLs4EScFyR9RbG0TVG8s0e7xOSvyn4JyELtXVPNQN4szM9PMmScL/OsnmIUxX0FPkgU6F5bJOj2zsFkutNAtWjgFyV7ulYkYAIfZamVnC9xZb+8CcBT2w98408WRo0V+p5mklELuRYt3gYs+LWB/uWBsRKy3uTN0amsVjZvsUCLjuemvCEHGEiQvUzlD0uL/53yy7Nv6KREPuEHPbPvA8nFxu7HUstBPUuhna42rFgqa4iVXU2yXJxjsNBRrUTAw+rs18Cn9FETOQUIgtTtevy4awoimBWNGJIFO8aVvRW1OaJfVqX4gQMzmQwk6biG0yCx6OSNubblJ2c1tXsKv3z7yR6sL2SVeLsKisrFBYWeCVSBzxea/OfNvtAJxSkfvDfX67Cr38n3tJi8Nnmi+tMrudJHcbHavljn6xwdczbRDlCEZNelxkaOZkMtbDqDaEO8RoHHPt57grG2oLxfd5KsVQDaND+bNUnCcwNR2rulNYXQmwd+LtV3mEFSpuWqol1lPGTgSzpyEaLN9/mQhAC7dVJJpv2rWoI2q2tK7Oef0SFl2KzhxAIwlbt+6bflrAiHwLv0dJEWJMFgfHYQ2pThdQhCA3AkxxoMb4i9T8OVV26OLgN1eczo3dGd5TP6kiFXTXJK2l+/TopMItk7YTWVHDWRRaUPVAROFykoxWbqgtELOUOM/hslHx7J7eRKpG73jmzwrKAvituCu2iZillg0mlyvKAd0GRkD3XVk77FGtscHWysrbaD1ZnLV1U4levjxvK8MR1Y7Hdd9hPDuism+xgSRTZ8bKzce3mCqeC8TVyW5A/wGesEFa3WIObaCt2eGUiH6IXmhvvv1MypIX+BJPk3++7J5FtfbuvjTPFT+RqU5vsPtOpE+T8GxW/EUKaZLahgO6GFkOUYKlxZa42IEkiCziljjNYuA60fLzTN/AinQ/CsZSGXgJAtCpNl+Yi7MW4gjIeC93WJr4yWWrk4DEGOD3MOe7t+9NXSoxBSWgNUOo3jHK0Lstl47ge2EYR4y5RQL5X0fRql3OT93ZfE8xM/i7ePukVFVISGshm1oS+dhBzT+ClefERzb10tQmk/rW+hgRPbiobmb2VQdWLRRea6GsoXv6uyDcGCPIKXtdlg4CFwURF+RRZiEsvH+kY3dkoFGAmViCKCXvQvMlt5OvCT5A+3RKNd6FX9knI8J0aO1ufiI9naryGnv2F70ouMNzU4g/Tbaj5OHUCK8yMV5QFtYaadVbl7Ld2Um69aDlP7nvdTi5l8XoPfycosLc3ltWu0wBlPhAJXgd0P+IL/rN3YDrxX3clPzafIjYOPCHyX0tfZI5Qs7z7bsYKMa/lZrql8t/18xKv61MV1c2OIZJ81fp13sp4tTg/PfLBtnmDliJ1rnuX4E/JL779PScRZsQWYRQT2Nb+aw6VybfxkSjrLfiJjnvrr/VAVrwWATbgBR5g1TC5XljjQ2TWkiUMVvr+f3nXKfFvlMn4jPVEl3b3MLKltIiOu8UE79dRtWK7+2F+gAZp2FwRLpo80DWtIRDjydT2lG0BKrqweptLK+afRGzbYl+abvFa2EgJ3w3/VVT+qQM8spSs99luGmMd08LgdrKxKkusJEGP0aJRyd63vA8jMKWV/6iViy7ZI8PIp/4x7PgXP/BhRqNL01UI9vbZ8haHkJYT8VbPsZtphyTRhsl9tccGXHyXA1JXOFSp7oAp+UikioHiDILyQPBt7+Kox0BXvq47es/73wQcEovaCQYfJ9oOKTQMClQmli+8gTIfuGvwqPnzb1GmdU6A8yn5FzNS9VcIu1hmRsuDoabzOwjRubnGaXRgAaaFolVhdOyHcxxqomrpw5bQ/Rky5YypVQwbz8rTgUIgmfPzU3ohaNFMFgLsQz+5ogRIznkhIOewr55dVaGo6Ubx8zABdV17cThRqDnNP48OJwNJ0n36xuGVbosRb/JiknSxN8d0pQxcmhc14wP5ckVLrUrys/rD5xPyjspl9GfML4iQ6RmUbrpUl359Sw5ERxm9Vvjqa1UL5BnUvKGDcQrjCf/pHOWzIx3gBCnOoQv5AygcTxS+C1eBeqw4MjSBjJPmcAd8QNXlgHpgaBCswnJXxhf5qHvluzrugVJJWs1e6z6nSKowYWy/hoaOw5keY+4TrazTgdbiXi5R5nRTvZtG9iGC0Nwv0ZOdaD9h/ZZUAP862Scpf3KfJ0oGIk92gyQs3oi/dUju6em9J3C/GTCFfcLmGO9YQRs2Q62ehEJNZuMUD0GyNt08x3QDgT0OnOLv3LAIbhKFTPmXiJI3SfEvZfmkjqsacu9+5iDaSvccip9gLBgH31fXz23ku0BxubSB3QfySrWhNzKavWX0Gy07StgoJy8K+35zCIvE8BWD0rgjEQdHqki1sZ0grkdmsSOQ4YROoJv7rSLXggW2234r4b1GjT6L2f0hgsSgyc4qhl+YgzN/4VqE1MbHB6Tx+y3D24eGYNe6zZVsdOiTcgph/9A8cAfLpS0eFFzBevp9p1Q7GV1QydWYqNJOT1H41tbYEt6XS/2rA2tg1YloNnKKfX/O9jpSBMFXgDb8SvuJI0174HtoMtxHtn2F+Syd4EJzkGD+nuMx0nJuhEawxesRAVYDPkZ8pud6Qee4BqHgK1nDSO3RpmTBwRNhYWQMMpMJd1PDzHAID15GfoITMfbVOvmEam985DZuMNzjh1oXZxTSu8X/0v9hDFqslWE2BVmZOcKeLaRwNNnhby6v0Jntm840s1HigwdvGq4ZcYW2cMGx+djVRBmVRb2fuLGpFfntNZY7sqSvTIGZfzcelU1H5LiLX2C3I2mZaTB2Roji4IIBzxtkkrkcmH+4eTuPr0MsOnJGwCqyHmMSWGl7965D2twGzJxWrOZxlWM3O3EW+n+tSZ45xJxiceHXMqsAyrPqZPb7iZWoiU443lc1MHsgy9B18k0EmzbtinVQngkbhvpXfR0dRDIsJGwN/MlQcwvyYHxh0+OAZSW0ROzjIobhg/WhV2saWXLYVfMAK2GpoDWZEJN+/xag5fJKm/rLkwhreCDb7WGnq89xeuNdzdvcPpIeKnel7slLo6HsKcsUIiDADtVYt30C29HvaFydLKXHRu2aXJ/zU5lPESxJjQ120+rG7SHV/2HSFrO3FbLl8gnbpL8Jho/85VxuZFfidwtXgaK/J7UBK8wMl2rJDj4GE5xC778smZdh8buwkmQKYW1dFiPzDLbPTM9x3pffukLD5iWruR8by56gSlKTPmcfmD3dquPveNYIqYnsVYvYgO69J8um1oNrd3Rfzj74FX3z/3ieG2tWMpoOjwbXR1rKROclY6g9TcLCDzqln+7cMQlaOBlOjYn/l4Cj3Z26KFo8J93ZEZZAgyaAh7GiGc37QE50AcJ1FalVB/NpVS8OCQ93hVDTIKV/94EIg1SI04+f4/rL6ADnJ3pr/Mflp/+nXhq9kgJYr813IsT4+GDs4o2GVpC3kvmHcL3mrGS6NI4EQ/y/uN1lhWnFu20qChilaAFsEDPkTT7LKhEY4FVCxsZfbCWrsaenZpYA/VRGi9nYF0RdPxBEyR1GVEqlAOiGj5Vq3tHQ7NQDOTHOyqFSRcTVv3G/NBBdMTQbC8FU9BBtqRI7xUMZSxP4XTzaOCsFQ8EIjQ8VJ0Fz3s2FPF6j9AfRIxFX/d4w9GegO9pwJrHvZvIPpVVeoGmQFIuW37a/tom2g0EXvNm6pSP8tsgEZTfHtB8H80ql1P2ZR9YXhx15cawVkCISKooKLri7OU4U122ceXDnwMsCsLs9CiOTIOoI9PeMNfDTL9HjxBO5NWoUb6GKU/5+1+N4V+E3UQreZEh61Sblh7WQpH/jY50Sihhifhq4l16+GPR2jzOKe6EZ7Bl96Y4Ypl0518nGiI1XTQ1LeWJaJCGIr+8s/8xqLrOpxTCBLpab1DVnj7WAK/X5ZPhj16oFA3hZGyGmgRnK113q+HfNVqkV+XO0Pg33HgKDZK7MD1ydBqGa0nTyOIdvk3zZtLC5CbmEJt3Y06otgKkUKTiUYhCL8NF0UFOl2CeqQQTBeOcQhip+uyUunB5Dhbz/paAlMPWsps4VXLXfE5lHakKEtQAlRNIZlvb+oCZEnlA7kJCPW5UfEpp3i8up3yjf5L5Oh/PWsTk/9DA6ZUO0yMkO+gGDdTdqsjmpJxX4cUg1M/XE9QgtJ+xLjOb/r4FDjIXO9Wmsj1xPj6bPkGBWUZNdpRsae58GaPqCK6OWsRTWfJPXJkaZCkj54k+TU+KLnUql+9j0/5DfVwTY9npoOM9ae7bJR3NulbQX9KL3j8/2NrYvcqg4VwyUzYwdmOYfdcdoOzIpDmHbNRd2iAUHHp2ZOpAEuYAVb7VccBPCCakALgJ01+ae6shFHkZMFvRv15Ic+gVbg7pyOzdq/slZguIAI2RfR3MpUYNuubpAjM4S5gE2sPh0zVLhRkQTPDaiRXHTdJaNb7qkEP5FVpS/LykeErZRdt15SZgnGXdU9wa56Qjt91XuK1WKYPgL27/xfJ1VIfz7m8pZDG4Tj6aQ37XPwqZfOABGDoZQApyur4Z34R+hMKD8M+oRKDXKpFpgV7uE+IbVnX0eB6z+0mC3TRDz/035+rWo7iB/yrdUuHbfSMQ+75/PPXniEmAQU9qGqMAnzJyXnCxhyHL7+LXX27nSgffbRfaEa/GJS1kOi3nhi48QpH6FCPvVvU6gQAnY/fiAW9i9+E6XDPpQmy/tcqmr0XtXJLcnie3b65QYaqGn89rJPSC/51hUvnBBPbz7XQMbBqFtXJ8nKgsesI8z4iUHUpK/JrkaL/PctdrIv5hWf1cdUBVE0m0y7BUMEmeQUXe/M9zaZn1AFxJK81tbIR9c1Grr19CQ3pjhwkjmPax/xxffDFjo1t/JCoSOCrRvt2/WwR9BeNfWnBfS3XyYI5phvd/sms73K4ft89uUMAPFCnH+tMZtIAgCq6Y4rx8oXmcUDCc5LLKj0stoOeLytoARMZRlhl4KkCsEqRMcjEKROJE3t4TNmqeB/2TcAXzdkGL2soPNKYGTleJqTfsnr0DBmGee53M/xBAcp1a05COLJTUO9waw0kItiq4iGYP/3r+V45XbYS+vlNmLRD4nvm7BHUu/en7OMwY3nKq4TGLOxxLZE8gvHJ6a35yeeKl5xGeFr/Ab5PYcNpigExsbSMs7yLUz3U8qRh0EMgs0y3xogwuqzQ35HEcgiMm5RrrqtOf+ohYIPr3CxPfZkXKI0ub27+RS3kuJmdbrPfIQvYXrpkeEeBaLm1Uv8JEjAxA1ZWuUwnqC6V0eOOhA+xNDutKuz7c4mIqv6jXwGrrzQ0wG+sxL1Xp/2EInJmgJ9QN66tHODzC4j34YVW/G/LjC8ZWEtgD4Z10j1sW/QtujAOkNjM6RNrfe51EeGct8+yjKFmMA5V/NlK9sweecJn145GdRAUdCqaxfbqKR3v5gXOhBmu1ost5XWnEMcmHshUSAgmltXFNJ6fhw7cAuOJYUuROFRzDYlpAlTGWJZSi6wujb8wz7pBiwQz8GbUy7/6JOcUId6QBQB3aBts/Av2oUqFunMEFYidHt1JLj7UT0esc5yCZx6nq3vU65hd8d+f+2pCRMMaXux43TGmiyL0Jh+IBVCdptAJ9oyE7EhGErF7NQLXjr3NfmE8WA1DQgAaiSFagu5oKIwTdfWlylU9jaisvq379Nfb3n3M1/4a3YnqNHoP1FVTrHExMoFSwXipiYzLPl0yAZ/LlLKk+fmQtVpjLMvjiNRCZwq6Q+NSJSzsQwMkV9Tzcful97szs86wQ/PqZrYg+t4IdVYi15JEPAVRYCmWs0dcxS5iToRkYpYPwHtpaAMYnhb8F74qNxVbh8BoU/fL/9i1Lathke0khDhkm82hQKVyiMB9Xoac1dKFyF+7Dp+uZTw8g+WTPVI5Ulea8iCMmHXtIqGzUrjZMZjjC3QrkqnrQB6L35/Ikj591WxRicUzlyEPvaDW87479YmAXvwXws6+V/YS7Fe+mjEV43Fc4NfpGT6UloMbReXBHcKxchEG42vCV1nKym/6DuEtjEtlM8bCOM+Qcb4rD+q1YOmutnP38tCa47U2bMxlVe93qWJxZVAAX3S3dlYQnXOyLCbcOMoEmoBIWoiX8PW6BMgIRb4Tp/MlY38AIgzg0U1lfhJpMczJl9VnrR7sUfpTuAJcf7aL4ruf5qLHN8jLsAg7oRby+jWGn6nYD9QimF5I6gMTETxYCCc9Mdv/VOOIykViRsfshGU0kIvVNQBW7i/AxDPleay4KRa9siqkXQWAG47b5u/kAgIPnOLMDjtOQpy6KYoyFFm8m+5vvyOF3cw9IBbpb6IlDYTUOx3M1iBD0Pwt9E2UC5uPNgQu9OogXYwFkIM/+Igcf/fYZjVpUY8HtNQ3CLJPpZ6eM5T5rif9VxWJdJo0obyN+WXbrmOxslCVqWjoaPOpi7vcz1LRx4VfqCipbmuU9Xw7pcNXJlNpn0BVA6+UuKCh2wYGMBggJuynf5KdrSp1NvKwgBImFFAe6VopSy+w03mfpygtEq0owfpNaa7QHw86bZyUEt+JX34t0FOVX9WU3HB5UU5T+oKCuZ1uSRXcj39uHCT+xAbW8AhV9GXfMw39nMQQw7mmG4+7T4La8kgLBwZ8gnrwalBsEsFcpf2FX7nFTEfnvKpp4kaCLk9ukOrpgLRpay5tEBKO6ecCGYhciwqHhjEIjiUolxUgq5yXzf9TBYm3MjFyXuq4Xl9uobq1laBHiHFoL8sgZTeBiDaLOSa5HXfCGVwnsGVVAj6MUi1xLCkA6ZxKy6d3NNz7VALUWbp0+L+uvKVVkp3fU96YeS5V9MtFlHzdD4yMB66Ft7/r1qhHRhQgkpG06yYPUI8jX3p8Np7Cde6urXzkWCvBFQifSi/EJgcMATRR6xG7jZUSm0qxwleCMTsKXQsK565i5aqaaCvrRcMaihFZiKsPBGZelEQ5r9kxXdNseg964ngCxHIK3RyTBjCF6GLehb3cK5qWvs4Q1Ski1f1oThTQnTV7TsT+rYdSi2rhyyh7RffWfcVaXoLk4VlqDD5kvcY9FzKDe7sI1nekg2dVSpEpyaWY37YIasAdIVcJhPOgzogE5kAvmZ8XY/RHCUqxtXdxVEoTA4xFQxguI1VEowyupXesdvz+SsmcjmHXtdT8zVx8d9sDJplg/hw6JsoE6/uXAhTF1MOPdLzCshFtNUn30x/Pxoo3EG3jV7KN7MwP/ybIruY6MuqSZUGNt3IdvxkeEL8lMP/EMhMGnz2CkYpPOX5fG+TdvOkOIak1/IZJyYh4aXvnzbQyba95C+ASQUXkL8YxwwtlwLJW6YjyzW/7bJ09VQ3f+8G1O+Hm1/aLov5i4hhGENXsiUDQSO2nAqGyUL3JnCytXDyj5neQjoA8J+qmIH3x7bYEzCuV14dVnagUnS9d09VxL+NCvzxJPUc/OD8DGh/DdIMZHIi8HhGKfzhx1zfFDouhe0YnkN3JjrZtIZfdJlx/zzvY+DaD4oK4JsArbq5ZQXQ7TsucI7b1O2lXfGM9Tm/NP8U+p9yLZjGy2HEk1WE11U1wtkmbJ8OTxjgHRS1nRYLDiPLCOb9UmnrE16P8RsEcs35FT7Ppa+GZSQRtzop5RzDhR/0/joBXQK2Gx/JFrgOiJnIMXgDjJ/1L0lTf5g7hWJiw55/TXI9IrjdsFtSu/4Lv9B0spoQHKwo6vTWksREVBH6abvoWrG9G8tPDLvfg8bZudWyKPI6SVX/cj/dPmkQEC4rBT07QCAvHUuBs1/C1Y20fAryg9GqCR/J9+P9C7fuwWjlJ2NZFrj6Y7r4vNAdEWJDaC9MzTF+47pOkOD2EBrBOmgB0m1/88fk3xW9xlW556fhhSJvqO2Grm5l94JZX0uZnqBYRk/YhnrqKKvJW8q+CkfQIf/kee79J01hkwN9w2RUyUFmtsMigq9RWnX0haOtbfhGChIy51BPVcYfsI6BZh3MZUZ+lGz+giivakNzbSzaCxS6daW1kL4GZfF1wu0ria3kdB+5J9G2eUNJaOd+7qJYGvB82iZFnNbD3EfIG4nvlfYxa+RkSLlxy9UsnszGEXsoHVDlx2n7p3JWNB5eUWVL0hKUfZXHCFImYSFu7duV44aReEbeneZjytWdVP0yqFAIw1ZYYUuTti479JegpadII6TlkRAAHvnynNYhlTDg3xehzQ4GR0y4onnxzKV2kpOCqEytloJUTXmDvkUVo8WCfleCUnAPYMaKuwv5/N3d3ESoAr1lmegkbLi7hPu4BzaFV9Yi3Tc3v68B0VtMR9SRGaC4bYTLx3rrGtKrzn7ffdOw6VE+lnBtjMNEUA7W1B1BHKVdOlOxleLSbCfi7EIddbRaVJRUpZLTmaBxIqZjimAuhVcWCv98/Tb4tWLzWYEq9H//zJ75JJhRvTA9DD8Evqm5LiIXmOHSwPlBbVWOa0zd1mzkmJFSBbuHJHI+3u/Sc6lhlsSBcdv//MjPuwadi7NXh9CDzNP4afdQb2rg0u4TsQLIJW5D8GmAoY3qulVXSaEZAHr09yG6iM2XFZB8MtegWG8PYV3gsChNOkIalzKLWHZtfal+WnrbBw6OtZppftCIBpHCmrEvFe4neo809hU0qyiyfTRLB18XxCgtb0PoHdtlT60QnzL3876rBmn+gh4aR7ZgyN3F2hJJshaRD3gVaQWl/4q6JAkeHu+JYwRFm/DQf0M5ShcRdh/r/V3E73/NxgcdzdLtEi3bSaC4EvQrKtjzPTvDhUjriNqrH7j9mBmwL6bPHJ+hD3GVM4iYAGnQNpt+ISgzP86HVZ7GlremLEM0DlILBm49jUrih3HjY1MOL2IwjI7RK4iyLUMBhHqKxLIH44ZZDoIRRNx56uLrKCVcpXRULcCVxaasUtLhxAmekcd8+j6i5r3bRHKzdiFNKe0NTOl/BhiC661FpYOE1ewMi0bqGH5w5lk7IhhcRujFd9m+3ZJiU1A334ZZRrttKW/+Rm5mW8J2jLFcCDAp1m+sqsDaHmOKCVYL0F9cJKRcMdR9bkaaDQESsoGKVpuOUpi2atng9Qn3FSYPVw9d1kWCVjBosFtB3yOQPq2vQ5c7zWP+1FnSTr0FTK5cFRRU2vWVxjFlxVvib2tHWDbmNnM9E7yyoKmEdww/VgVMhL8w5fXF7JCUgIjkw+SYIAZhhgJpHfiAkP+U8ScuMbll2fMRcCQCzqvXBdOv2I+KxV12Owl310Up/B2ji8vyypVQxNNecSwvyRUZfV59Pt8EnGXqw5M8gx0EiIauyky0sDCE7TsH7/V4tF8hpCUGWbRNCiy++W5CeooXBDwJNg/MPrnMLnZnZpf3h+kluhRuGrd0+BcoLBetF6AzrwO3QeomMcqPHem7n2NRdIKFF61kwJiVAQY2aXm/0sFtFEKZQ7Skr6ZjAABAAElEQVTn6KybbN4H5Pmwv5QsNjVPcYimLejrpMqSE/m8tI6k7oLbh3hAm6k2Y7gVWI1VxrfdrmTQlUHThjHljtYX+xYglbJcj1dpHJWXz9tuCKERQR25s9U97XiLaIazwKnLJJflJki76+By7x1mTAw53roohvUCTooosZAsZ6z5nuEjSxrf+aRNnjJE8f/cDeNUTiVmue/LbMHr6caga61zQxsOassvrhdJsBGnFnUd6MnZjBJj/cSAeEJJ8cOCg/WEQbDUk6t8+k9Bs3CfwyzVAWzfUVEnk5L6u/u5CErK3K4p905FsOcASRRstgysBRhX7vlKv7m6ichSO76fe7rpH9tUijD3Ks5tSkG9sIIwfT5yb7XGZ/YEMSIN+OZ4zECN1R/Gd1lot4eMSgPI/sJwKIPpDyrkskFp4s77/NkkCZOgMasi/FjYQtlgPBzWIlCQ9Rl85zSS/3fX/iRDAh9jqs+KmTA1dTgEznVH6b5Gz9XI9lRIRlgcfuLB9th0u6BsRLW5R6MM+QVV671RQvvuh68dQUbHaZh1wWL6hEtSnHW1+Uk4uoabVolcqEW/FfB8+vIpFUVYpCYNXIQrOMXgWH6yGj/iFn2oPQ/KuUFSGc0YtJ/j6yta2O8rhtcytoWyxif7bWcYF6rgrV6PFEafyIVxmkJUfhsI1YwmCUxfYEJGJ5oMnJVMNPs7R2ND74ZCnJqGL4RatbSh/s51Yn+rCaUp1d7X3CbVJ4apSyCS0+3y/X8nOrXQZNLl5+NcyophJEdfuGkvlwxLfKpoi+RyLDQFCwv2Aa+yiRm6VlVgxOuF5De5fBg8gop9c0GzT4z7Qaqin+w5Z2p9ym0npubihfSHBy9RIWBlK3D5SPYwr/lykYmGBOZMDJrLNXFUARgbGp0Pof0A1uYU1TLgT7ybTw0gKHZh0byub/r39eVi+QrtHF5WpfRqCtw88Z5MNzFa1MA0GPs19FzYTA0UnwKwnzVrst1VhSvmg+gcl13ZwQqNhbj+Ep0hoh/4cZU/JOoyYFcvwFOAAca7BduqjUSbiz/IpIyRo3/1nRi9M81T7H0+47eFAgC7zguosbpoGFKuW5m/da744rRE2BGam8SkZvmETpKSfV3p27gBDEA3lbvDMdVLaaZIDCUq0p+gfXBqMHHPeOV/T7/LGXS76fd+3PcC8Icz187AeZfGCdgaZBqQgxeu5syH/lQc5p/yTzZ0Znb7TRm2pHtP+ylOU7G2IqeyZtdbLO+/O7jddMdsldKSAgvBitZBbP7rPYe44oRSRU7xM5k5r1t9q/mj8zSFptNo/pJhBAD+j2q+IxpeYJsDJav6yeQ8IdkF9xYGcYs0RjocWLee49a55PB1AasMlkTIHZ6gPer+kj6NjBdkGRroeErkfX3boyKtuJUA80wBphGAntmOXXZvG0UrwBPM1pS6EfL73clrigaWf63kAsp5WSIEiYpXLIJdmV4KAS0napKl9TBz0fUEIlf+nUc2ElOeUZSzhexwElabsYVDUklK4nvuJq2fprrEgmKDBu8gKt0szLgRimEbdeZDiDARwCegXJu3B7OHIwHppY28APdLx+kPWrO4TY181jfCJB5wwOdyjyPiNOvOBwePqo8MIhy1J9TDC063z7VFRrY7BlmMy55XX/t5LSCkJWYw/YeI95SAOb3fLGsMyk1BCqnVTMASnIzljnQwXcWm/sVJLEMx37+S9s0CWVhw3235sQEZGNagTvXK9vxBUMMMg2BErpC6Myn+zBKMAyTIPJEevWswpZ6zuqomwU839aOLh3mFqLJWJaXvIFJzuKmLSbvMALByH5H3c6GV0QaPPe5ELGS6a9HBqhpogBEGjjS54ZRissKisX42wLaPFXGRlXdmHDFpQxJAYnz0fVngWQo5qMP17rNVmzr3f3vMP2rxoXgQ5P8dXvVzQPuCCpJWUdEieXKHuRaqeSCskaUu11/CuneuXmmzeCkl0+BvGqP+B6T211OU3Tf86QDfmbe5kKjJUq3sPt63y+r7BR07Au7NJSFz72HGZK2MaGoUVn4f9Q2XspjPV8tLEXaSxh7RHLwmq6CqKqsWTB3/UcpTf+cWKCoXt32wSG77UCdXzzqfyRosAwuhRgwVQupXNea9TDBpWgnC/B9/YUgD1HhdmUcGKWg8l3Xjt4jbv9yZA9D7583p6RnuDqty5XfSNb85+x9FEc+IEWRaevWCthzL+p9mPx0W/dF5LVjazxHI1wCXUmFMRcoZkwuvTRpiHNbxyppBJkJauWlISHGZlcDcSR6NLDWVa0L3VUravsYf/JDvh9H2GUjhKWfxYUAuG7UoiptA5BiKKtgoNXWKhffZlW7JcMVW3N5c5obAoZtaMDjyjlzrjrdDcGWF6c/3GBcbTmqKBb5yCjeqL6YkE9PZd4rZQhEFd2YbAyReK16vjM8gcwXGGr1QnkLPrlTd/eznLJbj+nKZIQSlydOVyHOa0/4WsJyh0Z2RFOUuOzWAma0/IRrkLRNcA70i3pNUJ1i1PdMaylw7V4svESW/8woiwoGAxEYqt29HkvlU3Sl+1eXLLy4xvPlh38qIiW+fKlInZ+12d1szTexveJO2PrvXTJ5MJJ/qnHYtmkuJ9BnHD2LEJbgGK41ESBrx38kqtyaQsfsqR/09iBiGlVbAHD3qVk7QF5bHTYZL7xfeZQo5Dbp/F96XBjeOz4wOTU0mqbL6H6roXmS6QhdH0J+BRXlriAEmGb9nCxy/5XgAxOn6hflMBBcY3ISMOm3JJSxlegDnojZk8D9Fzoa8pKtdgZzOtlmPWMqzWGrSHEqyzsZ+rdpMADpj6pX3X/kzfX0431637cL1z8scqbTfZDJLQxUe/P0Fqid4kY0kQTqg4mrpUtJDSPgms5PvWr+r6ZeBKqVyrFeindbutzaHea89A2wWlZaDqB/4Op19oeMZrU0AvK/EoqDvQlIk7JLkmQFk9qjsot7z9/9rzy/1pEMri04KGQViaX/ILzjL/oSMZPrRxct8e0azD0fg93maxXfJIbS6oSwCuRrudw//CG3TGnoDJGenZhkvBm3KUpsQ0ToiTtzP6knZNFKwnaWaadC5ZIm5qWhberE+ShatRjbQJ7LWxCuEk6nrbSJEMn3JD7KR6DryuJHRrsQtNck7kgLT3b1kZhHNj6fl/bNUbu4HSp4/bluxaJRjlGDWeD6QSg0Vy2YqRlngvdN+VpyuNdBz1qBxWK+ePMxMQSK3Qv/tG+zSVRKNpIMoFjBow4DQ88sA6IGXxjJgQxL5JqURIB8yieZaTzFK5l2E5hYcqZ//zOXr4qL4Vx+reciPr2tqz4mDAVXZwdfLrahKWxGCnqiRB5qiclxSZlrqunHSx9HH8BSmKUu4rZpKlW9sN5buOBuaDdWjjrD/0gW10DBDJJopfy/vKQ9heveM29ZG9VzamlUkVcNVh8zE821XP4B21xvDuaOWxoCbtVsOKBxinNtJpyR6OmuRbe46XTlngDfIYv0k/IgCCTOfobnVVHFak6GY5hlkBYX5wC+Vph6Epkod2rlp2yX6XDnr69dWgsD4X7RMq4V/k9rupEeLTCkStIP4CaLznypEUgaTh5qfixSE7cQ4xvGnzBICBR1TEiNh/WUCq/GpH7HLv20sYbaOfDGXI+02GWXyz2Ir2Ofh8xUxq9pO+7bJk611xxs8FZ6vGKVGY6Unhd5ThY/PdyTymk0n5Nlhm5DowO5mbu1hsnKlWYyjGe7uKYtncVYuZwdzqSEA++f7aScC+l2WkEcV4zHVUHhgkhL6LxneBmo4a6D0YKLAEuTDuYNhiSC79ROtb03jiC7OagHlg0vvndo7DZ5GTasVFz6L3heU9M6ZTC9x00zibghXUcje7xkJ+ayQpOrYEKuH+y3O16RO8POOXtY8A2FwXXKJYAfBbVu89QxQqEKaUN2R1iOVN2Ap/tSN9YMFnbZ5Vk5UOYkFxYNp8z4EwSwD3X45tB+/HMwGiwFdJ2SMRjDMNnWv83Vyi2AYu3JhgK8eIG1j+hO0tpdWQZCNWYFg7q6dYlBXxXUIqbb6fwt9smKBAWWjed3FQT7n9wl9mW3+y0hhYBGEetzRgfF8BTrVIgFWh39kKUnWjmYd1qi6WqXdcLGYeFPiICjjVc7PkS90Cr21Z6LW1Yv6h0yrpJ96/cdpMdd/jRI4pRwPrcqUyjL5mW37I/9OLcjCUc6cUe2depyLP8x9+A2z2vr7fkrEN5ZDfcMK4Spev4pmGr+FsCLKAKyY6yhI+JaxSUmawO9LRq/7eouvc/wP+HRmy0G5UkoUcal7DbPpQkRDF35SnJLdI+5o6mJ1VgsCYISK8w0XGm7mHeOFs01QxSYyto/VYWjjr7QBzoyiLz9qO92Q5ZE0wXoAHjnEUdgFM5/LkEIYLGA6QZ0yEEal+Ivf9QXvck1jIKsso/TtqoGeeQgHQq0kwlX7CZJpj7ru+C3YiFjDvOo/OW9Nsx3YW8QzBBDp6/R77BfxvtyhTUKFqTVdLqBIzgNABLLDcdXt5v48Flemt+5AfzkKN8NtyS5Vm3td0fj1YcBL/0WM0smuySyfFqonNltiHBRkE9Wrh1C+s4EL2uu+Kx0oK7VQDb54Szlv0GG2Am2jHxF8Ykj6F/JoLMdWSlc+0YP1ZEghzjdWiZU3wo/frWfUeusrPMhLywI/WnTzk3K2MyTcOEpCTQLS4l7Nf2Rc29Cj9j3Z8ZWF+/F81K4Lh0Y85rs0Q2iAui1l4FYXxPYtZPoK0/Q7uhghpbBspZnf+tpf4s2prvoAj+E/olRZ2sCQoGIIwhCuzNq0yUZS+s4klci/dDOu+ShicdpTClmPhyG/m8L6SyOPuRR2zXDhuM68eOdo+B2ISm1NDy0y1i/KnP0DEuMKj5ZjHQVpGJiAfg1YzgShaVU1SJD9W4P5QsHwEOhYPZUOfSgAvW5WOO9+JU0bS16hM3ZvptyoB3vrU96EzWTINC/DS6XjhUkGy5rVFbySvgK8y9bK2DvQH/4Y7+yPOYxFmvWXVDMVLKWODQF6RRFJr66z4DBE7gEFq+nia9ak4Sh2IHO7SlfWIX7uj3Q2/LxAphF3ZwS3noj41uuchUXIjBe7PGAbWWdPSFNPcDhWYUmqc6P5wRNEcc3HBEsvs4gjtywhgXd500//UF/xjBtvUhZYWB5ty9JvletpmDFNUV/JRt7O5HSRdraDCjhEk/38El/uRX5CK6NH7hLdy49YnhP8IkM1dEr57hwrlpoY8yC/xQj3qkH+WBHfNpepxhAdmiJIDz08MEQ/DdVeGfkh5jMMZjG7mW+QQSyVWKgCLhkfz14hqWsFKJYHPAd/7WhGy7AYtDY0QMx87n97sSWEh8R2DN1aYEMCWxl+PRgy6jgwzHIQs7AtnHp40OOW+BRD/Px7PjFwvBSD/sI1m/qjy1uVapYwM6axVEN+e7Wby30zY8pqeCKzoav4Q5laXAI2N0mpx6L2tqw0YJLPySwaCXhMCD622o4MiL/XYGpP4yXThLg+hwrE8SG4zJ0gx/yKF77XnIzaI6wy5Zrt/o9uRFR9br1pai6l/WSbudoxL74iFXoFzoc+IArzv18CwM2aQS4z7xKUEjM/98+FCyYixhF/Kw37RIVAx/lN9ZipNwzTPLakO2HF81Ml+H/MWVQuV/DqLcn3THYuqCEKFca2XQtpTdJvncSG2Z5a+YuYxtqdg8GTTBQ2trhTZURb2wT9ikUvronxBR4qS4KQRgeUtL5IqCMWARHa8xgg+c7Hee3CI0kZmcTnhQpWmTjoBN1L17JwxZMn3YPxfo2+xL5KPmKHw4EFaDevLKznLFI4HAHVG+5brzUUjde95z/thGRo+/dS6QOUscRSThluVRvjWjb77MIPKyba2t0Vbw7YbyqHDHP2xO75CFajP5ZZC8TkG5tA1L1B6cZQuQE5DEpNwVbTugr4pnf90OW2qnzix2hVK9CmMoJdjQ1gfmfqQBkFdVTTAlfylgILfc3VmwSrynXqxGVHaa+eslXDiSqLjhiXlPxSW8+ka+SAayUNCmZi49Fwo/O6yYy0QRYEg9KQIdhAQDu1oVDOpSsbGQJRiL+6XCCQpSSiiBdm/EP7um8xT/hX7teGIpN275UARUcuPrxEUG5eb03B7d2bsi6tVfMAOrMbUQ1kXF5UE0UY4OeuaOuibc7Q482xDR94NLnomXYUf+I5hEnfJtP9QWkFt/LffG3Y/DRlIR35ZvPdFO3i0p8ltTrG7eaR3Sy5+yjan2MwuALH+LJ4+xjtvD6RPCbs4i6DqCAaxxXKWFLG4BybyjPPY31bZ1ESWUl1wrPpfYLz2JQ0IA5LhpdKIm9QnSCww6Q0QAmc/ztaUez2Y2YbHvxRCFxdKqjPRbYjPgOSZ2LzSo0WjhlPWce9SIgxMDCIOcG6YAyzUXrN6r7B7E5ODOS2H01eu56kQnwdla1Dvq+zkohhlNxJ64bj1ba2MG7zk4ttj0hkoO991eZnZhGc2Mk92TX2JjsfduejMuNtbrd/TQPS5NkP+WLPVK4ecRbKajso4kPfutXhC9PcrRSC4cOXxhElI7SKMBVcTX9Qrvet7sT3e7MaAk8AdYBVY8m/Lz6eatMVUJD/BWx4GyhediIf9TPfGX8DgjTpQQb5BPdaSmChLftz9K2l/sIXgXoAlspeiPTHHuOFJBLwUqifCBe3ivyMGB6WpSogYHx8r356g/b3TaFHs4WvExEoUH3JQN86dAh4ar9n21gESIjuY/jBrR6ZLrZQnIRySyG+g5++7JThZX1afb/EUaPBRREMDnnsfITkCs3yMdP0GdfJGlcPl/tBYBcBBANEeKsj9PQrM+JLxs/cWWuIJ/nL2FRQ7zWkCA9Ajgv8uI9SH5CXq8VrCWIrt1RmyEV7R2sw+BZkUWmouKxcD9c4qZ8Onz6Wi1jXVBkeZoKHUhRMrQeA0BdTHJMtrlkJNjPkEXbmgf4nq1tpbUnQ6INW7x1YofIFJ7IHPnL0Ti3Wr3Ofb7Ao0VNpgnrO8CN4Q7ss0EkS5u7YGYhhKvZ3fK4sATjolpjvtaQYgp1YmzgGobn3g9pZfrtw2ORx/3AmA2nStGW/BIqPGJEmmGWTigm29vNBtsH3EsKhlZskFh3lE5dxBd7bjIRugBSzReCybqNxlq9ICRd1b4ViFLkXpr6/02KHqYVXqOo/birGBMsqPVNinz9zOthXR7d9x5JHTpXp4HaABD78iyr+YvF/EgSxRfrCPJNCS8lswLQHcpJ9NeT4y+2YThifjG36e+dYFIyKkDpH7vr2sTIDBcoCeQXC8HYctZFJ3cnwhyJ2WT/8iZms+DjCbYy9jJI/9mrso1XFZAGYpliNham1jA5kXUl/Lkm8zJnhyNm7w/tsu8X/AAEPC8sNJw5Bqq705enPxHZ2UKx+ZkBG9IXCQbN8C895lrTF/FjMZZUdGfXrmXBGjxxY6i+1nmwpag/zuNUpXfr7ELWlfcw6s9vwBOJTdJXhHdyQFj7mRS0wXsIeBVFi4rL+eJB1CF3MnItKuCDwoYXE2Vqg/Xmqr9T9nsmp9c1ZQdy3CwyYIPzUL5ros731t3h4W2lwfWOC2g0cfDdekXIC1mLIFcUTod3HHTX1hHAyAlUjJOYgM6qrkeS7RjdIK+TzwAqhkzEahCApHUarVO/TQpCMcNO2aiX+Dk1gNwQksGNWw0b7wRJ0IVuvzmXksaWWSvufe4da+ogIymTHC/6injBo3L46JAnX1Mo5TV14Ea6FuusV8rpa6TUktytvOqvVBbmy41N9hYYiLZ+XPDBEgD3PGNgrV7VAScp/+t1KlAGI3AOl5u/CV0Y6Kg5K67wv4f8go4ocpEd3aLE5tz3fBaIs7OPQN5kSBpQ2VVpBKGypzsXhLRNEOsj8OwT7oe6UtoKxTJzcTgkRh0bcNmAuW3ooZ2VeiFIgDZ6M4QuWV/lQP4LyKKUwrpsakJkgXbNQWQpm+YnED/3x5919VNsX4aJAUhEz5wuxwXCHGXc5w8iP3DvJNymowviHCUCNxrgNBLAwCku7rVvWmCW9uc4QHkwrVkimzvJ0FBzKeHaVj1mua/BWgLoLd4c+pxlIaWvo21rcApQzXmNXT5/tz2ogJaY4By23F6pZeONYnJhpvFAAeOjYvF85vKg2Xw08XCMkGhZFxExcbhKLkjDlCAoUfJsYBCCJIONv6erDdFmJGD9poLZesBwZWrA8+0NEzn3/uCn1dGEBhoRSqENBC1LL3HRdiUrN6LdHX3oBflFFuLzPsHrHRa1pjN8kf/S9O4aEDNxRofMtqljNcvkJA7V3hqP2lgPcQJMJEH8C9lgAyjVJW3buR9hyYgrMt6+WOZerGjTdCFjrqzlFg02Zrs8pIJlw4isL7K+CMsDg12ZkT4dqmT5Qxsa31Ay5i4nVCNPdqxAgFoWKnA9wGbd8P5m3cIB8Q+2MmiyUcokD0uUmI/AME2rCml6uwdlOCqDbJz3tqjcRc5yEiqNtNOOFajj0i0677i8W4/si9PbGogIfPBdFN9n1d8owfTFu3+zgTJun0474Bh/rwJxHs4SPMi7OC2maIwDa6qcuVtdHl4aVkO9xGcwqRts0cmkghlvnpjIgojqj0Hnx8aDvBMRELs9zu4ayBSmbNea+kKHSPakCdJufp5HnAenI6akv/5ttVw7GmQm5KkMGy+eT9D4mfLhUAdh9gp39gM1lw79ULCGsT53JU8ZdL6cwTl0kSJBAxrESwdFl1fimY0FGiHeZLL0BTkmemPkrFPlRd0ZHGKCpO/zFCegZFK7qUBDzWQ6p43f0o6PvAsXQWQF5nPij7XyO8eiMNmNDsav9+AlWbJl34vrz3SHN7LH88wNzpUPh5vNc+UAYxo9iUl++EuybSg8FjMshJZK0Sikz3q+LwvOwXXKr0V4jr9ysyyhdvSUdidpCGGFWdYIi6wxjNJS7+2vIyJfrhY+4xZD9J4K0/Np7xLCk3m9nyAwRhPyMIC0EXnInl6duch2Wss0aU/11H5OqVRlkpPPFSGWUk6uui6sPfLbjnAWoKVqlPVzhrjyn17Khuem3X/0NMSSHwoaf3yC+S7JQIchv6cRBPdtLIVCL34l2zWi0QDnW/9wDr5ybWfiJ1dH6ux5UITabD/M3yR3B6C+FP8YSCtcUAV5N5WoXKRAFTpO4ToUt2nRMGDHTnimZqeRE0E2Oi7wJYFlxXsDXiF8s7ccs73bmV0oj4LV5l8XdFB2/5A4fCuXgdrGhFXM0mT9dMrKHc1ow+Nwz2ZI2h5pG7pekO/qMYNzFdUrbI7rI1ZT3k5HvBVsy3A+NmzCuv+JIdEGyHtG7WOhdpRLpgsch2JdsOej5dVWdoAIM040PyJtd+dy1flJLoiW30VUVgYAHbou8un7FgmgREhgGQ3LUDUUjjz0dm5gAzCKv7cJMHQTuZguJcYCYj6/7VT5YbBdggci5YrC5ur15AqNPm2+sVXWzzqHy4mjyrBmzHl6hX2ElCEwO+mnRXiv1JQwkfVIhx3lEEe7uNT9zAbsV3qqj/B9TZwHgZfH8/xUECQWkQVpQSkI6JBREuru7ESWlpUPprjtAmqNTDg6kW7o5UiSku/b/es9zfH//vfs8zz67s7P77LM7Ozs7OytjY6SiM0m0+VQb93BcV0jkfldIHrX4VSFqXHYYEOzpOfortvIQcesw3ePS8x7NOZzYCrWzaqjo7eG9TzMkFIo6O5f1umzS1P5u4t3RymGyFRsVgd5gTvESbCwTKRfp1tyTzx5sPq81uAcsu2/zlW6jWUCRygJwRmhoLqTZwxCwy587QsySOaOOEEQUbuZJtntmtio72ojnNOpc9y1K29YzaMrek8Vi5JzaxhhY4rEtMhe/6uNLIksWovyuD5TqIvsGaSNlH+k9nqqg4hJ3qiUUWMtlGD85t6r9/m5ab/Q+3jmb1WtzOP07BL20QZdUtP98laJ3wKCewSPQyoYNDK2ic4M++JVs4iYDXMRGBspr/kAOA+W70khsqqtI3MzzTCdwDbb+Vcw1aYk8SwUjgJ9LWFL3glqAy2m26XksRkiA2ldl6cbkjPcIyztHdpU/V+LjO7FCYpNIV2LJq34koqgfaC0uBq/9WgMGQ9oYVmlAFALkR8oGl9SH/QhDMtVXP/8FYlxJC9/N3iw2mznaE+XaksW6wQjeM8QrzhpRUAEzGdMSubf9dXDwOYeFF79s1YPyPkGsRtcknqOlx0qkYklpRQOMVS5yOiYBoWxDbqVQYmcw0ByTAKUUz7huFdfJM+uiXnf16I+A10c6YmtkCA/myOzNwHOY4ybib5m9sR0BFyRedtdfyKQCwqOKhIqzEYdtN67o49EEYGpMp4omuFPenivGWjXk+QcKAdGuytMPDGKWKgFf9tvyc9LrxEIEJVGhfsn1Z4ufAvdvN3RIS2kV6PgUSauykNoSwgzyahp5VQOMkROSI8LbYwYCLYRP8M/lygKSrlERP4vxRtreUaw16TIglJsQpJ9EVzgeZSaGVfBXdVyzLsR8OTOPP3ZgVxQ92idYlDx0rRRoWGVu1p16G7Pc15jcnaxiaGj3c3uti+m/+u1kf0IyUkwVjxGyIR6aqVLrUrXvy8AaCQDWRbRJjFY8lxKe4lOPMDifbPv52j3MiIWs74PtpZ8fuZQ4hGiN0vmK6YSNbyv3roVvvU1A/qeerlMShlhkagL1w7tV/lf30raeRkXvc5/+6V8mFEJf/xVpudvKCOBxBVnEpFSd70ytSORue2dB8ftlypcu9wKBQ90IYHDmKOFL+vR6XEqHDFyjMEY2tAwD68DrUC+MTldxLu+GGfCdJ31/gaUt4XzE9V62t2MCC7jTdxekQl4TwxKWyB1M7zhD3ATvJMlls+zHWAyZrAqrxoGVuOiBBrq/0quAsYkohDRlzGNAvUoxUyn1jMXALd8+oww0NAYz80laiO2OPAopLVx2/0p+07QygAjvcV068xAn3G9CMwgfriV99gyYhMjggg87ljo8gcJMzBLIYJiafeaPMakrqeVNptNWv4J/xYxY7rzfFmpnLC+MONOnmd+mUH5fj/Yrt/h1NkVQyIB0b31ad3Cl8khs8mQlFhvkIlQg+yloq0RxYKgnLInw9tAuvZ5+UW43GEZoqeu/WtF45/grw6k+t/1qhCxSfvMMYFqgeKwyB7iIBWD676r3d29nQsc0PesZBt8Wn50Gws6FbBPMSM+kzgpwH8mJrGnQ8YieIOrg68f9sT83nQoR4yEEkrWm77im56dviusxCexNEpt/6abxM8xjs8vGLKr7GZVhLpy0HecXs0yJv2eC1zKmm0KYbVKwhVM2isz3NS75OXPRaKRJ+kW8kckYafc7eWUrmUwV+pZ7AnNFQchE3ZAf/NmUfYPY9u0iLof+14vCVpEEC1yzrr/xpwqKK5N0XW4ZFHI7J7XAhK8vjha1H57Pd8vv7g/JJhXs7VEmuBDNPUSQcd+5tx8B6iYxBruFhx7Qt08s0CobOrfB2aB9welifWfDgHI8/7z3XebedQ9G10ZMVYP9xrTVDnh72iSELGPvgsHG9Xm0+5MjNX7anYwC36srkdljMZC46H7KmlnT9tombzXmJhb6JNSMG4DkPyS/blksQncj6mGEVf7sZhQYNFFOORJ6Swd32/LUDe75/YMfIOOaukzP+Tqt4BQrpQYRCgaWUwWr0BLoiD4vMn9uemF/+xHMCHJA2e+HsVsdJdXpMuFvIMLn/HIOVTkBP3Nnyr1eCMjBn8fHh1canNlePA/f8q6w/e//I2Hmt4NFkjDue3kzQBE85NJ3f9T1XUcE89XI2daJBIpj8MDavvRffam4604F2tGo2L12U6ugVBNXpoDAy9sxwXrNpEpuPjXwPufG9Bmz4br570cEsrjgtq8U0BPTWwOsrVHuknwQBbsOXYAv49f9pGXNhX+zYJEArJx9yfipmrH8mOzJllCymhdMfqetPQDxLkJhq6RxaDIR2C+AKbMKuYg+YHhicfFCkgqo37PHPgA9GIn30+I62ENJw3VZAuWA6o5l9QLYwWhNYG2WaMubBukHbHJPV8II4f5SOiK3a5J/OJ5huf2wS47pfPmgNEQDdMsetAHG3P5lPvUq+axw4tqNQbEAcQloqzHws/gjNgP6J3JVkRFp5WUK4YYgexA+AnSX7LGNRuokvdCDWPKBqeVsWKNIYnmVze3wb6kHuTvja6A/pERdtQlOi6gD9F60IKC36SDxqsxc+6RMUcT0Oyx8PF+CqWZZxmRksDnn+jqraiImLyRRW/5P/V/Dffb6Ldy0ZOCL/SHIkx+tB+SLmXPQeEFhdeVDkjmRUhY+oC2wM8wHIJfT4MQBT026gD0KdVSiHLr/KiOR/V2kns3KlH2D7IonZBSq1qVAWbyhLCUs8Cv6+F8mYEE2nuYoK5RaZwPTBzjvqORloXJdemngrsfsHZqUySE3MIn1fnHw7rPlfJuVJGv8jxuHkctC/uk6oH1sOhyrM8tOc1V9By6CpeAhyiTQBSJw2YYGtiI8zsZ1ovj+SBEC58btOARsc6F6H9Qh0JPrUaXrqgL+3HWC2bhadKepahxktn3VFtwsj/s+GQNCVl6lQjMMfVjDuzRJHQSeRXXN7pWaxMpOMxncVLkG3PIuBI1x/EneZ/vSxzbes5l9UPWN/mhkVwiWipVcCw+O3YzICJiGwhJo3Vbmul0zwoSWv3Bx+lgMGmBjEp+Yp9FccFxpUYzpgXQxnm+5MjbBINhIsIEEKq8FGLQE/RAiZIj1WNTCIDX4dXBUCUHYDwYEV99nLshU62P5CSYyXeDFFyDB2DGdh7mFrHty6Z1JV/6zQvfyzoroAUP3jQKoEq5sHn/YX/lAr/rbhLh0FGppZy3jlKIe7IbdJw0kcPht/AZ+imyhNKsyyKVy3lAf68HKkHSKiviTxf21WG/jGKxqEidSRtJ5ymu7WcazYMWo4vjPvBnpfwHp2wHncgmwnHyAzO7zm/aURfgBx+7IdFDvpmd2W0RuaJDfldYsgiKvEkqzGSuPcE5m+v8z5gotgzKox5rnt3KG1jmOVbFVTIH6kLhwdVIZke0cDXvFbSEc6SgNUI4g6BdLeJdoLdmhIUdl8XOWdNhptFOl8yb3ozUE8wLt7m/d7z9rwX75MtD1f8nHoguLZAzBDojc3C5HWcGFBGzjgQZUhYXnCvY2OqL1A9Lca/FMSmP1gs0QA33lf7XcIxDdti+6NIZyqxNz9vpAPKdULBzfa6cxpCdns1F0VpX20gZRu7nCrR1Dyj9U1yN0jMGCywq+MBEBGozhpyOW0Ifw0U8SFmd2RiK1J9XA+2qsXmelUAoL0+amx3qwVIcVCp/XhJBW9TXUPUFSFBubb6I/UZn6/CX8lj94ty1sHr9vWEjFkYKB922DS8AaQ8gKh9nI+EaJrZ6/+DEP/nO8soD3M17JBQnpbBqFoh62Qxld+48U2/7XAIYCodjgrzzZWR2fXBswpwkSOCO3TGlccJw1sRju8180vRCFHxPhl041JDifj+bD+tO4lNDV93+iMdXPp8Ps+2dqnQxfpq4Lf1P6nwBoThaCWSc+u23wp0El7G9H6oIEVvqTy/Pl22cKshlmbXazgIDCyXE9o2SBGnUqJfaZ8lg5Tc/vhAL0SK0uFf+4MlWg+qNwfSFNsCqfolV1XGGpDDq+spbWQHpUIs3N0fU2P5uP3jIPtiWDjIIdXpYy3o07//W49E0a+I5EIXQx3/sIxsyz4/G/N23X9oYd+CkBpx1IZbYUSXdO+NzstH3jXnJd6goYBR1DHlUmuk/wuSpsHYQ5EwpVXNFz4Y/giEIB5ymor8+VOCsGGoIkbvVTeB6Y62MEKCiOLhsS4K/Yqs+mK6CtilS8vM3HX0SfKHgsChNcWDhNOUDkkOUoK4G1AdfgiLSH3OwZgfaabFk9lyTYkgDXXIX5AOtdRQ1HCCIGxrYA4SP/pgQsFs15I0EULnQZZiEOA/itgViK/Hh3zWH0oRTg2/2wLlvTfL4UUsjcbIhqmvyZz2fw+09yOyrBYifnEgwmsHhOlRdppljTg8w2fgjqR3LInmDnEwVO6fsLSx8uG1G+/RHdpEPapFWFGEykWLr9v0NrVwMlrKFWyS5hF2HQ0UEUci0CqKZfQVX4dL8EVhX8/JNNYB+BMBTUvC8W7+yISNVnc2V7nlb//zk7PUqMGuhkIxuQ7U7yWLgt3Pd5ZTjyqN9TNV4/Aq6l0xlbRp942j/iepQZbR+a3aXVAjMy1aeuLnSqMuZyqnOEPDaj/7YJgeV50a5Xfrey0R7srrA/fYv2bih9QGO8Df8GGQGI/UlGVttvrEGkjQeU6V4QEWpBps4jbEmgJm5HOyGZv+Lcu+eGhsuriVpYoItYv6BwN+jaORTi5t/hG97yVS7THapbkZRaGzXldtPsfZVnZrKCF6c4CxlcrqD6ecPi9R2EZpCMAYAtAVd5osNhFpT/1UgujKI/ifeY3BW5h9JFjYtTHHNIPYWAhQqx0lnHJ7RERqFu4Ksct1qZqM3f4UpshOt9tr5qvseA/aFMYtWqRF3u9hk3tw1WpdDyVnZijkzUe8My30EQ7Mykbl2bmRksjmiifiGdBgxLvirUlw3wKzuOU9FllViKJeCildgr4+XvhF6Sae3TmKw+xBgKmUigeTa82F2S5Vbm7DzlKomb8ATrnZH0ZiuMZGnz/Ar1dwHR+zXiJUm/iDrj+WWfzgrE3WCyaloMSYObREgotvT+EH6vptD7+kw/mBSR7pYPHTOgkSXTWfEBI6GVV86R43JZqGGF58JCHU235PUWUcMx/iXX2SxXj1HCNboARPGkD1K4ODd6u4YF2S0mhh/HxMs4CkZmbG8dgS2oHlx/RSPX5JYK4Yy6htnApky5lBSR+Y/3Ed8YPSpmy03sMDGn7a7dgbCHtqvuK6m9iqojH0OaHLsU/Iu3hzfZg1UUwzoKdMOI0lAh19od/qyEaV0mCQL80Q5ReP8yrEexakUM2WeyY2jJs5O07xmoZ/TwvffyafUn19+v+66EEvM3Ii9h05HToG9CAVITva+Fjy/Aj577OfNr+ZPw/+Z+uuLrUmmtNVMGte+Zh+Ciz8or8hcfgaSLsWW58ggSdCO8qyLjFXZJdcdtsWsTu0ahpSlFo8XZRp7O4QxtLfzU2VLMcxEGdt2n5P4Gg1XM+45c8Q953bTIJ1nwWW9jRpDdPM2zdrkAdVhXTEjd/Z+m7fkycE7d+Auj2gvkIUEjn33fjDud9cpXS83T0PyaZRLaxNPhvtNHWqDVScQphqiO+tgLxaYQ9ySnGMumKzqYS2LM6yFxDoWxu3VMc2heSW/1d6Djt32a5hNHJQLKoXKFizJzD8Cs3syvjrwWXwcOesKrY6SvjrsrwMkCDeFyixVhRHlt2xEYxia/3VGxi9UBX6Yq6cZrXF5HzXDz6TAwKHN/OA6DH6J7YAFXw/o2/+9gRDQadeLym1vvIrEvpc4Ytd99Y7MyU9Wl6vjGxDdR+F8qlpiOoMIVxIQuFNLgd1hzRtZTEuBwWEB/kkZUvoDptRaWsQ6+XHTSx1CiB6DYanvpfPPG4QQcFJ8c6Z8/l32ddgn2LHGIiBY91DZlt++Yr/ORdr4u6hVULVhWlGk6fA85sWxAW9TLyq1Mgd2YiiZ/GxQsQPjN6y0KOd5tvk4JEECKswoe26D+h7XaqK9JhtkN0Ov+ewpVrGESYr8yrIKU+NbmbDH17ppofUJuvInTaVKWNfLKmnj+6F0go9QJ3De5iO3qo49LoWgoWHPDw+Vd3vfrK0SsA58/Nh+NgZ0BHmWA47JrrpQho0JT9hIDggArRGcvy63WVvgpOkxJnCgfeRo9ZjNjRh6WO13Le6zQSj+DxvyBcIJngbSzCGBORN3La0dQk4moZA1fprZl9hfQTYP4XdzeSyXhnxGVcJzFsMp0lhxN3xqwGK8J3fyiYuclyVzG6OD3r3tryeAMg6FpenW+LO7s6OpfkCghM+KeURBq1YGrSMxrFXQPhGWq7QNiZFcpoYpIYDCrq+1eXKb77GHiqXKyXtIszXtEU22Y5T3sxIpE3NaiO5HAlR0eVCgRkxGtkp5/3Aq7aseOdFT0OXFEUUW7m0gNKYAcKP5AKdyxm2Jk0gdwKfalo0rh7NFJg93slgniDonW+NJIJEtQNfjt9GHx6fC9E1ZgoniNRdczTHf+T+j5XWAERtBRmkdhs2tDVi0ALOwyW+V3RvO93mxhG8Pq6UT0py0l8KXODiV6osHNZE53xj+ALdossWRbNQc2wDfVUn0f2sIiaefu7/H1E41xrqQJxlgSFm/+VDl1kd1wO4GyA1pNetnHhCrGhWv4urq1CE//4StGYIuiGt/yBUYf2OP5sRIoR5OEtGhgCZXcFXvZ4RWCu5fCJDknE63PwfYxGVq8z7Uz0peLEb3dcK2eVFU3Rjtd6XUR2n5nNkUQGuWGcX/Dj0lB1oLPmHEVhm2lB9B9n1zzEUoofvn3EdfwxhCayRhvQ2PAFqtFZAjq2EGiR3Zf1WeYzEvAgp/9gJCYKGOt54FxXO6cH9FI+6DcqRX+staJUVk9+6Fari1SJiqvvLq4Um9X+dGGV1kvYeSnE1gpghMpeOCUMgJWY1nS0Fo0AbPrSCnFQA/O/5LQsXaA1nkOfQAODWmmV2r2SmwBOXRUHk4BLMSRdKM/+871rJozOAYpwCWIP5cjjvLzyr0WkFLwn6sq1AJ/IX4Hnon7mUljlaZodmulftFcMwBnwOxeYpy56Pffdt+fE4ZNSF4LP+X7js3rZ6ebEDpbgaa0ZuvCrk2+rl3FKhPaFxGy+6AMJoomuXuJ7rRzm6oof/uofYL5xzGtCwfN6QIjdS89MLvjb7QYBSQnSGqnIjwf6m+no0/ZOT8iTK5pYsHy4zMwV83dZVJhn3WxBrRVBKYJdTSOFGkNhHbCBn5+50gwNggKSqER7HK6RSRApBoREVRwRu+6jThOb+qVIwhQH6FEqbSoyYZ+/MU10TyCLpwETMd9cQZeuhduoRFpPrxcpcFmytKQqKissyxU7h/o4RQ/vWgEI5287i83pZosrxEYFR9ESHvWuU9hLlQ/hA2UgIli0Hv0KKYr7lbj2P3oCyK5ls6fr8NaHONs4MJQnxLeGS5UJAodKXevOs99/w7is20NLSLYHMf8qyf60D1gsSvYZ3TJIs8j0eMFXzWOqr1Nu0sqGzHVURnsbIKPv7M1GWVsUnxLMxKWPpTrf/5WzKvjTafnsc1S4pGQhqvUdmjzjJsbhIjfzxl9j4F4edgfPpLbdoXO/G1HUC0WkeS5W6gBCPmnMoU/jZB1Xcj8vGrhGSUx87nhcEGRHg1WWKiOJnFplujNGpO7M0+vFbb6yuQ8fDtzG8sPYWK+nRRQpnkaBG6z6gEZ6MwmNzShFqCYGwe0y4x/arkrzM+JH5/nNUzh/AUUzEhpMyF7hQPwlArIwlOg7LQbsgEQxIfwi3ddGdoSx9V0Ry2mLT0KqQiyOpkdhEXTwUJAXUhJCiyHEIOTbVJcTIbAS9x/NER+9vLYSKWtCjoqzeO37RAwjBIonJMYX/smfkfTSxAdP8HYcLhyI8vrRBnA84/OpjN8jxAuu8Kvke6z47QT5FCugivy5E92BRUD4dQxdHXC3Jk6WoM+yChAvdUyOC6TfiaqCcNy9SCEMehLWMvAzbUbBSomeDbxdKSuw1CEHSGNCwKaeZduWgCr64NNSVUcSNidpmwvSgyEK9jNP2xAXGl4m5r+xf8BKz0OkEjs776oqapz2nz0K4FnG3Ms49NyjNUiSllmEWNs2u5g++9IsTdK/kYaQXgNlRiCiYzepqvDzBF+rQBzgdd9ZIzahM9bP0irZN3vbTrMHYGIbJP5z/+Dyf4ULJ+qxgNXjJsgotzh6j/fDkJAqggTEPi9pfZFQxidTXVgbd7Az7h/Dq5i3EI1DanYPsH7sXNMBMFshgVgmTVFGFgK6FClQNRPk30lo4O4pco1jWW9R7tZLvj+fu0rnsfRwMu/rTFTQNJcF8jOZo/0KGcWn43k/K7HtibThmNIjebh5dYAT9IYxmSAhBm6mW6lT9XxHsfl3hP81EL+7WF/6B2MPK7bZIzf7m5GKtVCBCGrXb2titllYci2XqC98Ly2gjpV1zRagKdZyFLbsLNnMncZy0gc7s9/g8Tb+hv11I/Ip4vKKJm7bpP7HafSs/O+7arEHxC2o2s60DBkrXYZ7DUECF3H2PX3q1xMDblmxkC7qQQHa6YGtM3CPwMDSqE/jCmRhHLih2718f+cQ0RRzZ26HYvGQhr6rhoM9N+Wg9V2qkDmuTUZWhYGgIi5jznc3aeeJMklwoVVKaG4KJcedGdZ1w9x099uvKGIRHFIxNCV+F8HIa5LD8cgYxPCzmmPJHd6Vl+Txosd5bGFRgKa8E8a2wGglSECdy6j3kq9tFkc2VhKxtP3tHxZpPvdt1tbDFAWfa/4TqeE1doapSQQfkObN04pL0nO1Fvke5jb7AzgfWbPK9VodCZSUZbfzQaI2AblxCWhIYWzC5wsKk/wfb9VlO2nd/5bGk0w7WOFCVpFDjS75qRjBnP2f99CeB4+mWCMtBkCSK61s/2SzrwjCsvAUVmc5T6Lts+kVMdtsuZcS5wH6+bVfN+mdARo9NYlBQE/abtqeM5AL5AjzNTnV6sCeRi+14J3BDrC/TjMtSwBazXbTW/QJnSwhM4lH03tTij9fu6QQxQDHAGV6SAPz8UJgblqE6hELPJJNLkOJcaGu/lQSE3OayKFZr5zn7jgT1wWekDsAqBYKtk6ls1+kwfXXOJrentjyR3y/aQgMSNS9GhD99QirbDQ9ib7Z6e1un9xulJ+sv/kqAD4fxQb/kz8Cw3btoPcZF6ayce8ygRBOGqEpDXcSqxyMDVtKNTLsXjxcYyf/PoscEL7gxVSIX6UN23bcIHe8iWk74q0FbFnPLEAiaHWj1ASOyPlPVxFX5dPi+MF6/4Hf0h3CuVxPOy8FtSWuZEusMi6T3srXGime0y3/A+5lWYIwuSnTG++zblViQ6sVaEQlFNAmRTJhPELHUn7RrCZ+G3SeLSCzmzvvVbB5/gxL+5MgpPwQzNfHPyr8gAhYeosNLIYyAetmsxemxBCFzTzjd2lWMjZISbUWNMxDMRQjv8E71w6QACyBMDnB8c0AuZbGdYT4ucOW+WeZ+ZL1l173l9uS18LNcxVFQk4/49issip0cGeSa5/e/T5e7OippzmjFz5OXqf6Pq/sGetIDUbHpTRZ2XuQMm5vHNlJUxyc6mzXvJoawvsxC73DILNIxd24Ov62XxYH5SoC5oMG/N+PtcRLKq5E5/cZ3xXnjQvAzf7JAqyVU+SHrUDEYQpQPl7jd9YP9O5S3qDj5639JdLmHSQ6ZWhQmceNoeJ9jm98JttNqOAyvPRAzcx2mHWHL4zwqQUB7lIYihD4xK1urvSwjUTPRXVyPIRCoiEeB5paXwec1m/ZamZ8VJOGIhuBFd70a//k6f8gb5v048Ubep4Hyk9rhfQ3Ym96xtSvZZWezjch4OIZwsn1++oEGj0mCS0kP9z5yaCIfY3AD3ycR8qP5+X6g7B1yVE1BlJ3HXZioGQyT3hpzGUplgmjxEkvRV9R9FNNbiFT/8lmqx295x8SGH8kABEOVeIqZ45CmOqgTpgfXlV5Sv7f0EeAMhDaUTBYgoDnNVK9n3LM3MkNQr8p7Xdm9KldDilTd390xDBqdO+EZh02bd/vsB/y6STR+1dZXbABAinEIHK3zizTI/gX6gnBsJ/2Oxgh/4iJ6BNqhZZ2fid62PFbyxXFZshbCP8SLPbVnfZfaZgQqBDga/+QF/z/CcE/eL+2mlxC8kgyDAAmTOVpiGX2m2Yi1aFqYss5rkeJ2bXd8OH4E0YA2P2QglxmuvfUMhVdHzxI0zgj5hGRk5X6VseUWLKrLGJgVYu2GY90t7PQp69iioZ2ymS80K86ccCM+3VY5bCEopDr/CBbAkErmBwm6tp/vFNfm8wY3h/vtky00XXHEbayuRWGY/qFfcO67xb5flXlxuIxenLG+U3xxwFY4dNuHY4/+oOGoXu8ddEIPYRhlBhYTnkPONNK6oNRmKIbN8++iulom2hCjaZmGJZxUvQBzcY2kDDSN5HjKWjtDRWVrgOs6gRquBdVjiE7erFPL83OaEXSMAUhsUmOodiSvG9y0miJkA3z/DfJ/yS9t1qgZarq3WAtVx4FhaZErLQ5sY28g0m1chWsV6AoydqW1T1r3yvfMJp7oyub2Tpti6e3f4+4+wNyAZJ3Fu2OjeARF9u8IngX5teqeneHCQ/0R93akJraimgtdB8xAwEdlwkrcIu3g/ghgStI7U+DN85NUkkEwymUipHul9qHJMMqqUpL/BYazKaWKKft1dXp42Y3zXzJ3fg3/HRsCagsMWOcI20XwUgMrjgDjHr68/qMPLsh1hXYpEPv7IOnNJ9Np/i+wFiy+om9SPb1FQgXfooV3xL4Wih8DBSPrSsavOcJT0GT9cT9j96afjglnaAhwqJo3JYrqhNIRmdDywsxZo1H3FQxWINF1l8C+HHQgX9wsREUcUpspMvIInv4H/oKZuZg/FGSQ3haktHqkK250JPY1j/+MYhUZwW7jOdTRMoRqHQ6Jv30f6ra92nadGu+3XWnxms7I2iGZav9FYEII/0H7oPIMXt0vqeNFdZ/Lzkst8/hE7qTLbKuDSNCVO4VBzl4S2oS0PmBtw7TQibN5hMn3ahASSkjxGxtx/40xNFyhWaT384k8+tEIv7k+kKEPodsqcI37bNUMOex7gky4u4Fs38tdZ2WGjeNZ2l/gHMb7q4NPqgtuwaXem+y1hyrs/UvocK6M6nkz5brwWcZjIbYEI2MqF7oL1G/sOWxF1VKK6UPiHO5vs/ICS2HSjuRSf4NHeMvp2M72IQgeI7bBLQF3X0TrW/ldUmIyEh5FCFbFYFxk9jI6ufyJK4YHuT4tda2Y9cbKW1GxlRQdHiLhFjiE1hS6kCcxG6pISfCgVqocTV/pcfDn4bl6LuDgz2ZgksjG0hhkOkreCk5N4SJu+ZlE8LLw6GEDqKPwCe5oUEJvTSkilCXzg4b18m9ODDNx0hZRHqHRqui2+2ejiHauKdcgyB6A4Ug8KoQdfjf2/vU209KbzfyAQ6FIkaEjg/Kc3LL/IuXJyOFMSZwphF0CkEufkzou9s9MPyYXIa0gOYK2UTfCgPX/E7IbFVXUQ65ZecCrAqkzI2hQeFSLvme8ei8Mp6lM2B8wYUMNoAtSWqfKZwibKLD0ueQvc7fHhrp1rKM6r/kxEHxU074AeU8hhbbyxlAL0GPy6LzDeYa7C9hX0KiEf93jwvBGU5y4M7BiVZgSVrvNgT55rDrz55Q9nQMhTo5581D3wxyi24+k92+ZcNgnVummCQJ0LcDGQM4cJlkM0mCK3qk79NCqPZoailw42VoKrkXkUV7p6WYPwSOcmlRwLEgq1XbexEvUXQn6fmetS1WM6nAi6cp+JEVJKygz/cSQfEn4U+KS8JIcyMsdLxyyTzTm75b0Oe03xiwGo2XVsLEqxhjHwcHZ2DmJ4ZOqnlWJp+0Ei2wafjA5hToD/djwQnWDpAe5SEMVHVp2EEVLhaKe3wNoTAghdGRoIAuAzcTRRAUlp3RjxdzFfsm1l6Bf2J6R8dtZglgvHlxWwfajnLnaygwUY4omTQeL8o0kxTXtwUJoR4BvlXnJ+SIExww9u/skXF1EFZiBVkYrt13FHZnuxSOWYbIf4w9KdM832qdACxoQp04y79qyUgW/ZFtr/eMgcHnSn5eb/nF3+zs7LGMnLH1b8IvfDLEO5rWxWKbcjj277ZH22PK4qmOvD3/5xoZgZSxeWdSuooDneZY42J/0w7DEfhaSpjRxJRtWfKOu8yKwAAQABJREFUxrgZD+gtKP53aB3su/lxpd5beuO/crdqrbCCdA01nYWLSq/x92q/XEQyLDPbci5JPNp5Uv/bZwOKq4sRI2knK8SofC/faQSPoI3EYNV7P+oeAYwApf0Qn8d0PYI3pxUSG3XQDK/PIvnL/WhUqib4MZdStSEtM+ZTeFr4q2V1t06SijkS/g2iL4Gjvdh+ZcNlPVpqkIprZdeEgV605tw0RhzvIqKPii3SeNrm7+BDA5EMoEZ94irRJYFo3wEAqaHL3BiBWBdn6upnLRbnojpWOtqh+0sNFu9un/0douvWaEbOI+QTo4rIc9l9ghvgF+/WnRgBE6vKhSL/+ZUCh+iCxHNrOhR7GLYfUNomyMPT21ZyXycnifhfLPE4fMFVVb8Ceq9pz2B4boCfgGzClHa+0SDSBGgWlb5QGO0AtwZo/izALj750ja8KnRQzb0NkUZxzFDz0goxfap/CbqDqbbC40fSGI9H+OatAhFVmois3RgaaklvyxQpWREVbv6obowj9cuO1x8PN/qiDUvKMGdFclq3RYICXr4oYnMCmRfhzi5/7m8ZaSzNFD7fdNKOszSMdDfgvKImKnQjuRyWFQSEMVDbXLWxrH6nGp8M0uLxEUFE6iIEp/XCMC86I+FDAn7xG9UpdKpA4/0GdDgK0o+oaQr0Kg9lG2eR3XzmixAgA3FPN+t+qDaLkewlroY5n5O/RLpI8jGijGSusmtyzS/YRS8g2wSp3b0aQbXk8+9oOA1esBxaeNbo3lYyvUMfUS+0bCHGKixFncf9KFH5L8LvZ8MjDnEGaB7HRlL4sQ972UiaDCHU0g/E4E6/RidQifUvY+5/mD3QDr9Lpa2Gf8LQ0VVti/iYgimqRM/diNUuLM+EH8nzD0Jp2ZFA5EKMjfUFnifAtGzbajbgSVO1MqvjNzQL9b2OkQQCmww/Lu1mvYe5gEL7cUmCRwUTN0J6EYt7SzzenfVPlZTw90n84ox6onyAVjQjFVAxFQemk0Ckw5ogfbsOkxa+QiHEL8H+d1pET83bQ1K8aid4wBrr8twlegy+qzKdvFK8KIFNn+UzCOfarsY+A9E9jCnouVzqRURR+8kk4L2L4aOzIUgsN8F6jUOA3DiGDPq6uIz1zfsuFmyWjmL222DI+euRkb2IY8JDhagr4IRMDLrtE9GjO50NfdsWA4lIklKRq6pCGLSEo6Tb+C3Vow48mHV8gdqnuavMmbcgJsM8Cs90dl9CxB2as/cPH8okQ7nF0qxmLOM2SiXmdMjSAfkKueO0HdNzQDX1DukSkgDdnqDaixU8HsDrxbdYnrfHK+RcZd47xIJe+jenIVyHogokjRW4S/Iy8Et+51Xont7w2ijkSimQh2XMg4iiCCFTMTuNrDWzkr5EQyOwkdSMtEZaJSqrA9W4ZKieBSTytrtyYJeL57I3/f5twJ4BblvvUDHRdlvlbD+V06+AXcC5sN5V41Y4zGskUlEEoOsnqA7HQcdAfpOWoV1bttraG67CEvUDc6tYVWIno/rtaQC/OOxTVl/4JtBPN9J+BuIrQdeWFPQJnJAxtQRELVrPFanorngasocjK9ElAhsxS/xDSEcnZqMaaV7yQ8SnB9kyPidDhkfWQOA5Acc37Cn5QB+6uWwjvtZXeQmYBPjpRPNc2PybOy9Mv1WNiKWMPL828W+Guc6ofpc1fP5CupSP5uBNBP6tWjGBcLGxo9+ho0g7/J/u+8xBzu+tutbVjKgFAxGJVCSmeywJQz9/kvyl9hQYsvQ/mJi8gw3Q1CdgF//xY1IGJrKURgWcbsnN+CjUQjt7/c24xJ1X9Cn/LR8MqcuXWtsFA3/3ZRxQM8PeAnPh0z4VBmcn/rzSxjf1DjZDq/Eiat4VVFmQMrmYUx+xSKORSn2HqtapOXdTMftLHxUorBnwv7aU6MQI9ldCCR/BwlbzwEtgfrT6LvvCsA3TGVy+MAjYjbPwKVDK8m7WPVAoH2bb2hKEEtkUruO+12cg/cFw3m6suBAeWF+/ra0HLSop8jI80O5/VWvRiIMpOBJlVVKR/nz6sc4t3zviQ/8w2odPB5hm/57i/tzixrI1dB6t2ZfGKRna8v5gvs3U3wRX8Cz7a6QQ1jnIUOi1fBNPONnXt0H3S/yOmuClkw9PY6VH/6myDkcFnf704dF7ZnlDYl7ppouw5VSM9iNLLlQmWMduHYBL2YvpchqiJO3n323ni6Ihi6wf5dRFPqwEw6kcA8LAYAFju9+fTO0QhnRqbintA+n33/mZezmXVjPn2/SsbWiWH5HJTqvFJ4AcH0tz5Y5DpfUBt0Lgrug3vYY9Ut4QPY2VhRhY/Zdhon+ZqGyEpYEyDrK6wr44RRyaQ8VhH6RQ4QjqgQj5sB9Z5aTfzRvRV97Ciz2KfHpvDpAzAMCIw+R0JOC/TpDKX0mFh8GG0TI2vr/1i+v3X9HMIi8JAF6vSzhLjIzQLC76+jCYEpn3R5+AKCaNi/9dpw0iPmWV/R/+iMbEsjhMWXg3KEcyUPePYvmyKeepWpC54McUTMoTGaxafFhYEPFqzXmsO6qWyEYVwSr/8ivxUMJKND6xthxZo+Dl6JHClJVle/91JXi5ldLxjpwHqB2QgRvGkWa86eS7MAvCh24s7FClgZ/o6bDU8IVPdiy/l++Hbrq+Q7VriJ+8h8i4mnMoDDbO6qKirkrCf6vFurE6Jpn+fAsCttQApptQ6cOu3T0eC/Fbwo+XlsE9wF/qiea/jGuakos3CRnuAJGMzAFqXVdy2KSeGZ7NuXdmkTwKBGbdCK9FwR+Nh0N9/bWvWlIBbnl/rm2qZESHBFk6mZrxsfec9w9RyunARBCV1xUZBXFfLno1oWv8D7h9zI8m0pGBo9hMF30pKMVMQR0W0ELOy0QJ7Bo2hJlFjZgluaO4O5uUWadVL23iH7KbXNUPn7b9dwOZKrQxDBQPkbqyp6yjPVEWsWjIllgB2S+TLCymq1QAhWhX3mOt1ZDI0qm7PEQ/73pD4qO58+NL+sl0yGXUKzRUOcvmWwDK9Sp22cFNIOwsA+vdEfO5ybHaaoQidVHRAcMeTXfvto0eaQNYBU1wgtd1vUa0BU2oMAXoFKOfTicwNZ2eV3NKwsDQEQBBBdSKLmuuS8YCJqZyW14zamGqgQ+BJROOwopiiPSRerR/nyCNfLhJ17T2zjGfxp5eJcRW4GUwt2S7CwGMixTkcDFBgZ1HnrqYBJc503keSvR6wfW0pEopnuN77/Jxct1UqW8anmkR78O5LzsUed6lcsterOWBlXS0mM76uExAUnsXJ4AfWWv+jKL+2W/ILXgRq3vowdJSJNht56AB9g3KiJoI3SGH5SD6zrc6caJwtIRQRRqY8FjW7FKp2kxCRz1WlhmswMuEz+9PoofNXEZW6y6A2BAGGWyg+TECMYzRawVy5qnVM0SvE0+p+DGXeInoaLDUSsZX8YunyCKbducIPJdKbP8ZufYWtIJ9oRGwg4NaIoQfbyGuUjL/8kvm7Vr1wL0aV8LuWtJ+7zYfWKENH6BI3dTlb6RWJmS0BgiLvgxtpxOzH8v4kmXjs9S2WeRSQsMNT2YWY0oiW4zlrzbLBwxEACSur24peT5lE/PffLHjLjTjTe/21Fqkecdp6X8Gc+DcPkVTP4hPL9f3lW8OBUtWevVe5PmatvClcMLpr2fAN7A3i1rF7lL0NEF5WbRVNHOB5n1vHJZCM2qOGxPkEd2aYWl1oSkEN5VJvp2aBL13QjH5wXTaFdykuRu+pCuBtiOj8X0CICgYFwTzLtVglz9UJ+58WLHn8sBRsQqyswsWmWACEvvGhsEvt6mC+Dvblb3kFoL1/DmQpDlbZPSFqq3RW3W1HHNbmnfU7tMX9Mnk/pOWCpkSFEftOQbpGka7JkACP1GpIkTMP8ZTg5/aINyMr7RSfqUTdv23FX9sxJXCbFBl8SsACZoYiWgcNyKBz8NsQEmgXzoS4QfBV5LKThQSJfI9kn7LqLTVL0okuqkQpbAuTLvzMdPqqYoFL7tDvLHZ5Q1KfXuzNLfkGt1GQyCz5KgkxtqeCIyZ7Tr8qYw4PRXMHeTVg7nXlSQ10t2qbsd/dQu2dSqCJBE37IYE9e0C2SzTLM9CfqFJFh+qWQ9LgoLEDbQr73fd326F30JZ3/dFZiZe1J7+2jS5QVhUGVmhMog7UaAXp29D3Uv/rhskf7KY/kCapSLCHYeLiVj1eVXNpuC2lonPOIGvg9s+pKdLf3IWdXMLQb7r155Qy58Qy2OTBGlHEIL0qwAEnBnNiNqikvgU+/0+iJcPfwCocRVK6yamqQ011Veqbp9A4zpqJhZUj2trfvfFZWxgZgoNWCzY4cP9U3oFOkDRWUrNRWw6PXGQxjpyDVxxu/Vy7DlqLC/rY4tMXewV+HcQAFmCjMtUQa07asmdZeURgh/1Lm3fe64je/+DxkAuulznzXP5kCt6Mmd2aVT2UC2r2tGDvhKsFi4f54X+wMxpgYhmyjtNSwd8wGmi2nmf9jC2gjtiaZRd8ySXZIcZ2zz5OF+gVwY2dv4EoR3uexUb4P7eJQpCVb1T+cWtQWMFKpcEH3NFe/zYaYK27i+CDZOuLb83/G5i/q9Yyu3K0oHrL1Mh/wJ0vwgAFh2seYSVVFttzmLschFOUZeNSEYq2borVoUopDDDagl9CaRz2yxku0QPMJaclG68z31F3/fZYin2IJIGnqE+8/wvPXdrlpB3rolh9GkLwQ0x2Jy+QveWj3+tMqhLQ+J608OmWfC6PIqxshbhvurlZT0/GTJuADfesiHzt0saxwIXEZs28naIZ2pgGNlT0ZnFnOJrTKlrknefB+G7eRdkN4vFih9kQm/kbphLhnp/y8Xs4fyvKMQi/8TjYI3GjyBV9fqzXG6XYP4HjwD+nb7yxkfGoLEu8jaWP3ML2A1fBWZvVCD1FlOWMVk4SLpAH+IpkJlihJaejl3fpYYJsm0+O+9ks4E3wfbqm5KR+GmVoSt/R7uwF6VftjdkCXogjBnMKLoOJ7lG6RYz46pDgi67fuB7UvvlFZXa/7sb8TQ2k0YrH1fWLU7whWUo81W1Wmt6cc+Mg39DWoQHzNdI9+0ZX7riBNsr9G+S4paS/n9YXbOF278bC7gOueEu1YrBo/f66PdfSPm1KQMSlkWDMKfvlSYJHG0pprpz/SfNT7kvGR3c5uAUZCYkpO9mkwDSSLSK40J9f3Lwj7x6Ast5BbviFkms7gMU5b9Orw9TWmFHFF7Wu8YKNzORQmLO/d3RlznC53qSwCIrdzQUAaICvvVp79q4P5KMsASPrtPMkmn0dxlppINPWpKiu/zmA/1BXMKVek1ImGTFHnE4JKyN6B1upVR+DrirFf7z3+z1e5J0Hw6bsFUxtMYgs2f0vOlBqforwuTCVOqDK/Xe8nTKSjDmeC1FAdZJb1Ae/3Q92+us3gwPwqgR9W6z/cOPSxM7PwAgl9XYKXN7doqe1ilhEy2i9toL4wn2O/svKmjWBA5m1dhiIhctT2g0sHzFfEyzErsmhBxn/aHz2dQJEDlpSrrRrPgL8GmzyvfgKSxNLTYd58AXTOaoC2CVgwuOhvVPNzGZhKHIpojqRMVXthoXEPInsPNAUqeqJB4Il9+i5MOz+V0t38TQBTjj+TEMKoPUMnYMgdbiIC4BNqVIZ0eZMmDbe1m12Q69CpuGsypl3xO+541DaHhG+bDd6ucGoGZT7Q0kT+0uIDU6rJzfrWxRYrSkWcr37MFLOkDP/I+iW/m4CBvD2MOr93sCRPPqRMBKqygNDVqqR7mhBb0RQqjy/PaR3qUBO6SYxgpv7kjCmR/uE1f6plGQwaEsGk3c23eCuBjwWV+kySYxuawV9iMy23GicF1yXdXNtjc2URA5+hd9uFt8UShW3CA0lJg55v2ZKEVbs3RnVt0I2tZyi4StYXEh6uvkFz5+P2JK68n3vtul2wehnI9NSJ3BzzhIbDl+bQQzCqHujzxsnydNUh/jVwKtazyWh/4b3IZq8yW7GZcGqOE4XMZ6cG01yCgONREU/KnZEdJOzsbR6jIBYpboPh8pNFcYZCdxZ2pRact8mC3XOfKPhwTEmLGND6DXd18tbpHRv1wGqr4i03rfG8hWyDLoAT7aa9ZkEEkYp1RG/c0tArG5yYZDQTdzw+NOgIWgex2LrUhYPN+ppoG5jrs0VhFwmmslWEZJj/ZSr8vpoU8Eswk+zyB0YWBHzDSyaEtWkDSam1UZwvjfUpUPUJoxSo8CUyifkOt4A+hpYcxv6a/9bYE0A+T7klYPWjCL6SEkrkxqJlACnMVv9wn8j0shz3Mjbvm5C0zdemtZN+FjqEFqd6qxAFnNp/uigbSyoXEC5K2/wpJz58j564RBsodgKFku8TV7mzZhuJ/R/RFpma5z1JcSoDp7IjXX00wrfeUYbFdQcYK+wP0VwAbFXVPrGzGUiUmXNKGwWCAudfhxl/spuhQQxrIj/m/WiwM4RJm4VppszBrIocu/83RbCZPDdczPYwqfnDni1sK2HdYCqka2B6w35MLb0dCTNBECC98wZce4vvXm5/FPcJJjsUZo3tFATv7FnJaOlLKyqcMoAfpIe0f97TCDm4uzvbQqW+fQCUYxsWM8+m4Jv4ZYhuELXkDG+HyntdeeUS1lXvmtO107gem9g9v0bCZugIA8CJJFBE3gO6IZTXmZ3j7OAEz0rMZvrw0v8WWQmNZPEO6pcntNruPpVjv+AXk5QtH/mVVmpYHepH0KsqFP0dxWVI4o/u8wqv3RDBl2RBjS07c6/8QYSp60yz2mUrjXbjydZwHLZkt4MmyLkKnYDvYpMK4WgngD9+cvpqduULIMj9tiaSxW2w7iImMf8mwgpXQfncQGwC7YZ3Nr/Hf9LN2HJCD7N3fFAWTXisuyIFPEfLTKs4hV6XMEtUXIWfr6tgcwri0ZLjNMSDFdXPESw5KLvfXSi83AkmnpYwb/13udt+jgTyz+h3XLs6PeukLILjYjxkCc5V8wYJOws0yCIX7TAsRjVQafR/W3xyekAIFJHIr9kLexiLt8h/hIy4lTl+f2sN0gbVOUM/Yk4V2dog2qF7Za0AYQTZoVdLl2bQPjwTzjmCSEQxmFppFA8Jbw1TvDSs8Pvrdi3Efaowh70sJA+m/yib6vSABRbV1zDU1FH5ss69SfULsvCYb5Jv4Ztq2p4yMSDQeTXO53xULmQjo2QrkBdzse1nWSsFpSqzFpLKypH3IZ70aXjmcFOc62skhMMWIVTzl/rNV9xbVKe1E34I6yzT9AgUo+1jdFiQpAIoq7wW0R/dNygdpgYlqIH4Rxtz+4WIGXEQBcY3gGX11qZqPg6sZCbWNE8rEmaJFyG0Lk3qQ9aMvXLWATo3eD6yvPDEvlCNF1BQ2HF8b1hqEMIeQ5wVn4EaSSAdj5Al6ebwuMteDWUtvQlwa5gPoKlVzAVJAGSrrkTwLGS2XK0jK1oMWyXIDdkM8CAQkxpNA8IaoG5EMGX6yXPAM4sJkIWtXZNqfVgxUI/YR3HpJ9LxyjAnAMNY1ZTjo1b49gXJMMKim+A9XfdUP3pvFQLIcQopnvI0T7gmHalcRloOuLiihSw3HgYPE1q+ympxp+DvPDdBbhitQLAICfLkmqWOzK1t6CpXwptbZEIYHEFMChF6KTis9nRm2lECotCkZE9m0Uko5m3sNAfSRhd3xpm/XB1ZWEyTtt0E0P9nnsQ+I8jNr/grS6SHvwyPF9dIrKU3TpV+h9Z427QB0o0ugK5Rrm731moPekbqQYS2reowHxyUlICtc9bk2iph8y7Z2s1qBUVGqnNjxpGNh7sI5cCARP+pvFGE5oEjJG/YO+4m7ljqyxAXO99ojGNa3SYBUys5M03Tb5zZ1WeFeT+WSwCbnEz9MLLSRBEeC0rYdhBh7ovlKd+yfdQWJuaKvMAX8wtY9hDBrV+RVCycvriKNcGF1SBUdd/JXizyXnICbxZ0gb5EHp4E7te4hZi3ciIj8bEnmpQjtsuwoBSHmbCArXMdaq+w25T7QneEwWCxqCnGmqOfVIw7j7bZLgPRNLUhzEcg2N0u6V5KX+h50FEgeaHv/zvv7OFtue0SMVCC7YJ26PXNhqPwq5RKjiAyyD7Re1uWCgLfqw3sUkmrFIgAP/btkFCIRhxlBszJFzII9XpBhD9AB+73rCjl0LZ3rk0r3RrovXfxtKEheCCxGHyaQZti3ean/bJA1bJuvgDhMgkr76Xz50bUAxtgBKEfuJD/BfYwfm7IENEEmXdq5h/IoRjvjt5Zig1//vKkep+s0Tn1gxee28jNQSifNWq676pZDp3Abus5bLtgo9AHEW9ctMI8yksHCA5qi0fX5zbE2WEEss8OtHWPAQ2BlGtqzTaT1E3Hb+d9JTEd+/8NmbE2J6ALOVGw894UqGWEFUfndSE1ufYyC6I6/usKZ1l3k588GPlewxLbmoWWEh7WpCXq9FmPGUfq80HXQBrgGPw6UH8C3Pb20wJ6PWiKKmEKPe3A1DxPs0AOHXZ+WWZ/IDrJrszIJ/1U2UO/9lGVwLpv7yFkbPBy/8w1+OmGx7hVSn2M722VquWEdTzZGoJKR4j2+f0ffnic4nnHCjG9NYrGD8/spib1m0VHq/pcH9mLqLlI+2hVL5+dELC6Iq9JiDB22rqoDaWdYzyKWXZrowD18ZLKJGlGVkJ/Yar2hVqymCLdu7HuUZKkspuUJQFZ3JpYafmuxPmWggPRsoQllCo/C0inSwivAYUny66H8d/GqUEjJxaNgbcvnomh2pW+lgwJZqKxnp76vFameGdih9hy3c0xw9dp4ncsOmzP/c2D4nLbfttlFLNl0iDYiDJNxkyaT0HRr7cqeHwhLJ8UivrGpKPsn8gGoEfakt3zV9a7Xu9EdvphNTStqv6C8f+WTNIfhux+ig2km/BUUGuSk+npZyAutAlKqE6gES+PEU5SE3pyR0KxPTiTVqDb0I7ohwmAY3lqnSDoZ4uIV0eWRhbKWVC6j4TPjkmi45TRnnSaLFgvSgCDYIKNje5k9XaI3eCnMAZ4/7KkvT+WWV5yjWvqp5ogqgEnHugoDNq+D1ljLtVYND58gQG6FTxL8KTm+qotCV69NmknbIpg+UWkKBHtrk6qt1hzejF8i5aC12zORzEe/SGmpsh7hh2Gaiv65ixjENLfru91TwK0w6SSG9eLnM/nQmbnRB14QRggnCd59dhZUbpEgZujrC8gG0y+3ocj5KIEQROvmJxSjN9ytj0TB8zfgBsK5WRF8sTnLbBrAzkXvjCy6HFUwf9MUv/aJc4iGhLw6BC+64Lrhg7Oz5ufwJZnAxn688FC+HAs9cKL01muycznCur1uTD3LieMN6LDXKYlVjLz6hs3ht1aAMiznmC4tE4+GMeGORB5Xwc1gfGMu9evRllO5Wd64TiePWId6zelB8xk2+T84183tNUMZ+ZPJAx2M6zaFBNiY1o92NTl9zdirODUSUojtL7WAI7/ezv6oGWi7QejxuLAviBss9pTIcK8aw2nm8HPC18qUmz7CheuJ/GwA4Ol4Dng/Ha+9HvoOo5fb/LgfmcDAS+DcakKNSLAmSQhZ34tMQMYYl04m3EhvRn1Tep+8qER0dAAXGDdIIuqWksb70l0xCioxyGM9GEFc7pjZskOBx2luGe3PY01lPAG4zOnV/n77rO94xg7oM1Jf9+GHXPvoZ1YQf6gGTS/1Fu+VYcKnlP/tBKz48H7HUKifvynMHFD0Z/ntm1lExCtCrj5K8QQ/BjzB7Qv39MhttLDg40G59ToGITBlIwCXLa0Bd17qnCD61dr8Dxn5rZmaigbIH7/VhcE64kJWznP7zM2pq+BfPyCWMOhqJIaYyVXli6qkwGgO/BWTXmRzmq1fhUD8M57sPkJEucm6IPMV09cqZshBhkaaz0J+4bIInZLwuzbWaxnE8SuWHL9Suk81fann0TXg1zq3K4l+tFvBpf/w6tz4qAaOhlUMLuUl9WhbHSgqEiGQ+zyPMh8dr6de3/cYWgQdbLcBWuZxLj7csb/ZNkPmSWUulOOHit3TDavuVtxcfRko+BrxDZVZZyFiFdxxXhvfbYAqv0F+IcMeLRBdAbY4POQ4cS2crMMLhO65NxnYqN2ITuOsEla8kxqWZXE44cXZaV6MoQShB26XPFWKrKb0sXy5w7MzJBf+klIxPVMjbTYVp+ikh/N4rsZDL0MfCWZYfLKrvV1pP9PDRRMnumS+Z6TXg+B/uSGpSvYwWA79vkIq5hZ9OBdSZKgUU3plBRRNJHN/XfXWJjRxzAvAUWowLuueo9e210L2QOlFav81/TX5MXveuZzVKiG1uTIufrbRofQW3p12RBYUoDf9aBbqFz5/ox5TRp4CLE/zF3JLJVIU4ht1ZKUx+xG33RLlc0HYBdGdiynzjcPH2oJFQTgmdSFsDnSQpMs6i5+oJGkvd9H58zH6EAlOfBLh9KLW1U3WSCjQkqHmX2ISFisDFDV6ldoxJss/9osemPLGqqs9wmF5cRNQAR30pQ/1YINuvY1vNKYy1mctaaZ2LrJ4sLduuAh2FJvnY0e4n9XpcYyvPOv9shzZIYY2UGhoImHDUrcM8Ak5EyV5L4neWmaG4JCwaLPEnYAdwR9MyXBr14uE5oKuThir8nC5Ke8XND1WS3KOss9oIs4kIm8PDPwNS+FtXh1tGZbvWV1wwjpThtXpyHTKOgYEoMHFL81IYIZz2KDPGEXr1pF39FPhXv+4f7ZE4B6U7k0Car6SoOjERRPsE4981RLQx2wlTbviJk0LOfF5ahUgVuQ+hpKe5b+bHl+GRUGKKIBvCYYzwH9V3gdZaFN7mapZtir4gw7e+QiasNcc87M79KPXBDZy9kVzL+cRx2p3oLP/9yzkWdJvrLVZ8rgj/MIRjzVy9pHm1BU5iyI9hfutrx5uVB5iDtHyXzbUMI/CNWU8u8pnKgpMuMnCzop54kCMNw0duGv48I5AKfhHgq6+KmkfALuXdVhfF+h5zlCoTuxAGcHCnJvnGGml+PPfQgbsCYfCpZLgN0/uE+yXB9RPKqXnxR6UnksxJel8pEyik8RTe2uhEv+g2hI40weEy325MEha++BRWAGSmj/AehbOKYrXYBRSc8O2msbSxVprjETPV6T59pxU+KwC36cfc3WeiOF19/s1HbTCfuiZHPViBoERXQ/hwB6KeoNI9XF4+mUW+UxUTwwjh43T24Qlr8NhAcbd8qa43qKs8kon/z03FN8xY+xqM5TQNcnDfZqFWwje5JlFFQjwDAbZvF7SiV+Rwh0HE74PNVVYtpcdWVKrDMNNPzRLgNjBFfcSShvaiFn0h9glzi2Kp9CUZRBqNwBc7UX0C8EwRA6SoyKjsMvDw8ZQD4uDVahKJkzr6KZHN/GxwydkWZlfp5oI8S9lN+oTk9+gyrmO860LED+ot5AyCEBZ9z4dV/blikQobUfHtBH1sIBiIOfqjcS/YssMt1Zgb/3JlbkqhUCx7Bt2C0yF4JAV2M/5VRALjLxU9wnd9SufAu/S56imEX1+l8vUqczGf+LA48tmc3SeVjOT7ytLKGQHEfVOtBRLshTD2q9IlRJvwR5mZlGbNXIX42QlpXUEPnGVV9DgeiUe2Z0SahIeGaZkZ7HtvHYlS3MzEgSZcauJUMH4Ht+nKI6Z2Z3C/SqFH7X6rMA1NiZbrfgzZPK9iNgu+1q6G9YeUZLolDbHjIP8BDCSGtiVaEheWP7bYSKaEcjaENXMI3Lan8FML/myB5Q0EDkguNQjKz/X1aymQgYyR7gPYp1zvRjLejJeiiT+ydXgjuPcNlmCVD/WjcuRQ0tJ+a+ydaNxPv68YfipGnmOZfvc9NqcI2KczkQQyLxA4VzMXYf5eCXRQPOFPCnzWlPtGP2mBb4aQRDooB6dr7VKJlIRBv8AR0wlEdMT5ATb7sgjDxESxtEGKKLGWdDNGkI49x/Kk1GXOMC5WiIQSynhGTN7IHGdeWE76mKZ2JrGqOwFHFbjVvnW0FcOXvzUd4LZ2fs+1GpJhHbV4t2SGJf+bJ7TdC/i9BSOpGB6O9AVRfKmlck9HyFB2xcqP2SquNmoIxW3WYl/Jo90quOGiqMEX7RNiw/FR/8s8xShYK4I50JA5yDIXvVjywFTHA2nxP0gl1urMGO2eisJGn+piL06R/tomtE2iCRVyrcV2g7D2q4ukCzKNu7i73AUf62ujmeCpiFGKn2Wxw/L+xgqVGH+BfySu6SuWA6hlRf3acRtNl3ng4X9gOcoJ3Benu7/4wV6pzkV36QxDZEGe0mlnrcuRPfgcfoAZm1bVRZULkJW2DYLv4odCaG6pYIQm1EWnfCnP4O8jqG22t7IcMsCvSGUWSv6b+JY5rrSELRmDB+4KJ5XItZSOn6kU3Iyp5/B9awBljtJKklCSJUcCf4FpCExhOsnOswO0qVRSmVoI3MBQ7jKMYo7QaTyaGpdBbBMSuU7SDalEs2beT8hlMUb6Smo4crZvf4eiakf6q4Xl6TqJ3G+67l9XLHNZUx1WuPIYaNQAg0mD6stCpUl1UsEoQUhyy9iqAjBmwSIqfBaDFy9zpxwZ14A9gX+jRyV12fqdrLUaqA0C+msJsAe1PzNYIHtIWDZFgNSwBCsn7nsYdr6GBdntiGAGypR8S3+dGTo58Q9Adf8jsjeIBwtciHjOCg6ygBTsprw+f0LS/GZeFdlQnjwNbwDJBcNSBQmTRen+sIdgkn3JGwQiGbHtUAWb8cOdH/dphUWgVoYSCBLtgXmtORXNP+v1qR9zx57V+GA0h1u0Lin8uhmN3ZfRfP81QvPG5u7+5X1NadzepWJybH0wJCgZLUqp7BeVL91Dg5qCiOAWvAFbecEVqXADtDsVU8FFRoWgntRZXmajE3QVxDl34cy5CoaIx4r7LNp3mqDOeNu9XbRDcw9z0SJt34rtT1VK/tEALcr9WzXYg/zwazbIzqYkeK+ZemRQuMNqgq2LKR4DJuzxiYJ+6MNP++lZIGtL552Diz2Fqbyw8sQ6uDYBRb2cfNoWeYEAJDpm+5dGvnu3uLQxRPH9Y+kglX6y/g1QHlZduDN0Mf9eQ8AfLDGMo+YyKjoSLEwyopyKPhGa6can13T6EnkSN7OCYyQktGtYTT80cXU6lutU2nqwSlbVzctL7BHXBVs9tg2Ap24ujZJADmlkZFPsns8OxePTBvNJcQIRF4O92rC3fvK8ZsQIpz77AuHVhl5u12ynAYyFXy+SBM2BX6Sgvf2XrHGlVLXMPreHXMLvRTVBJR0eiaY+XXYsScSOwHC8eZdfhwPApqUW1ZClAoTqUk7km+wGTnrq5gCHTEzqytvvOdS7iOhEI0oSgs7DJ8TdDGvMk9VNKWXvvv8jhTBSSaVdvnKlhGOolttGEPgzb6rslcCWC2cFXjEWVrs8Wubc+U4DW2SKcAsVV75XX64Fy2IJRU1AKHrbjUtqatKxcestMhIea6CRFJGwo2hLWuUGNZKRFr2qVGZ0/Lye6n0mFo4vvz2P1q6tVIw1vnsu/HNv+FCSynHd5D4/p4fgV/ZY4MWEECDot13U3ogK1vXYAQPQLhE5EG7kyuNO99HXa+UbF9JYz1obrNiexiaYphAr6tdtr8+ixRL/IR++EHOCmXv06RcBToJqPk0q5QXj3EOqOMKxbBJ9QkINuKr/WlxWUINAB9dPWkyqO0ha/3+3T/XgnjV7xIQN4P1VLbJDUNtBNuA9e/2qhQOB4I+FOk4KjdrW0KQW76kSu9Hv/Ne7KA8zD/XweybfxSPVm/Pc0yDdSDgmWA3mcZXU4yJHUhnaDAhLXsBvm8xDzVsnsp9G07y6Gt2fIs+oRtpMU/NRwtr56HGa+ZF8R+Ub/HOXJOuyHr9/rjCxiaRc57e9GcLTyv3Bqct+eZY9yf3eiX7Wj9LKBiTPIc0eGFisKg3hzj2KsB+3yvJ/382n/5nFgTYqj38IjeebseLIA8I3GvaMuz2ZMeNOMnzHWRskTqu+GtswoZnsmOjVbqqP85sA3Z37OyekpO1dXAa1iUHIKC3pRpWDVQ4B5UWHYveq4CiB6XTf7g0McxcrH/EbJY9zIw41a+MiV81CriTd582piDktkLZShR0TANeBQ9g0OeXTvVHLv31lcawYpe23ECImr73Mplu/cn8h/0JCM9VooVUOnV/nWrmaljsCk9s7tgORoGd8U7PLiGmt9n0Xq8iRvokQ6a+ipJAM0nTppy7VT33trenuYvj/fonV4z+UCb+v+XAylHlpFMlaGWlQPsQYp80NMqynKYKubYdt8xTlqtHNYA5FBAmpusuC/zNO5qGO4VPSnun6c19fISZYEwmJ4BHZpfRaPOHjl+WUaXRB73Xs7n8tPXlzSSmlhPg5LV2ka3V79mzLXeInjGT9/CLct0h6bxAFLr5EJESE5/cL6A3IFjiYe3NhIqwXHzjc/LJYfmXknbA5u31662FwY4Ce7fmjoqn80y62mrYccws3aDOmwPDuus7FVC3YKZbflHWXweN/Ibj1K7jEg7q9uGu7FKk+v7w97A6m/grHRQo2QaykOWhu+WBj2CI9w8cu/m0W5UDi749+81ZFEePRlpB3jJp+dcyfkIozYBLAb4muLh9CTfurBfv2wL8pedS+EJ/MzPEZaFjSFVKh4M3/10BH6Jyfe+hfBKcXayKNLHXCG+FW0jZ5Y/keE3/F9z+XXIrRbr/4Fv0f20bMt+hJtBeEml3+jh01DATugoCci0VV5hjjb58j1MV54z9pKsuBflY4RG2wIGtf0ojwrZYy3u81nsIsR1HVXg1RZdIdlB8aTVzFXoP2rano6ZARIuq2YeqIZyQCsHEyqbgknx91Rqnu+DQHuDOXKh0lQ9SH/4EW4+6oHsU0j0gvAOHhOvrVNq4Dgh31Pn8d1CylKNXc8ToGZJXbySe/c7waI+bOXu7l3URUPOmdKy4i7g4a541uVZaoJCzm3JGk4KuOykTH5PSOzroXjdPtqm1I/R97s7YwaHf3MPcsbmGutqxn0YIQHVoqme5ynRdYc2lcgN18qULJM67/lknNXvJWqxbgD0zEnLiMQ35EZ9voqIg/okwHYfg9xW3W7JjadRdu99a+C7phmZU4KEyvhAsk4dYkvJ1C9ofoISu/f/SWExhi2s33Gd8yTenBkjfnOi8ifKJ/HO+dAJnqPeFGUPXX2sIrh6EifSl3qA8X199l+Zho+vj/VJ45zPaqCVM+EYDk0KbRQppVsijTvvomv56py5wcitCCKzGN8Jyyx8AioUPtLbciQLEVee9lH+cOY86bxz5iZ106EVXjR8zuBZWXCBrqkFegHyKj3+JLpNOgsUFNGZ1kKRmg3lvGysIU0B8fzjxM0BSbL0ceHMaMWKOTwhhzs7T0T9uVsk0AzPw0s5trxw5JSEhbhZW8OjgoGGmbexe7rCh2PSWG7aGpniQW8gvt+ZnXn+kKYh1QuUDMTFA232f49MILdNnM/TV9tt1ViVLKgglU9fb0Z4d1HWeM5x1FjY2mNaMX5a2B++JmqyjYCCp+31oiS3w6PkWPjJCN50ofeas0A3l3XNCqkPnEcO5uiiHAAZmYvP4Z7XKp+/bV3jOmQwuuaGr+s4s/mwWaPj7XM9OUDfCyyrkRQTTYctXQ/N23fIrBGe2fZuRW3muDcQTkOGqRO1Ivi/uLaeqQakgN9AQzdEt3vey1O25XZ0ivPmKdYLfRJkWtN7G0Fbwow8ODU6nv2gPII7TDPC2I4QTf+iIFWM+ttpQV5tK2SUwF0bYeZVyksFRq7GX9tszFO7AQAH3pCfptbIhs+rsq2ybgyhFAHhvyw33s9uVkWS+qBaNENUmGEs1oqqIZeRjdQpE6TKIZ/QPBI5NMAQYQCAfWpFKu/YTpaDK6kp6j6fL8+Q1udS9JuVMa9481KgTw7NCZLDR6dNe3TVleGNFwO5/2Bo+MSGv/Ck4RtlIi+Cvu9jT2H78jdSA1+RxO/xBpg/Lfk8hcHQBRB0H3I0BSkrPnLUSi4/eAy+tvZImE2L9hKGhlWqQ9pELQb0fpWvP3KNBWKQy3aTESv0t70YLMrueTpyKpJq3373Za6v42zYJw+9rwRwbnfr0SvjUBs4Kxz4VYvex0/Z4yLOgGFQtkPEkoV3UKQyfqQaoIDSYsxiDJ+UJmNoXHRdZ/zBW+v4X/OZzvmbw/I7ja1SJEAyNMUagtSyLKQMM/dNXcRrtOp08WmeryuUednY8w+5mmlVgrAIIp2c53LsuTZBIqCP/3pGPYSBBzvh9s2mGEbtcUtxnD7Z9ALFcmgPfWJkIfQuWEjFRQ4Gj3eJIlZ3vVMDwr7CvQyr+gU5AoHl1Fk8DXHa8jlfzS3pIJtHLnhd3eNVlPVk/QriqPOC4temzNc+J/Tzpa6JZiWJxUN5fQSpEShO9XcC5+gxgDGEtwNVcaUvZRMuX7gqpVaF6G5M14ZOpeKwucWyVYhjDOBSlVwaHHi2pTxFFtG3rDTnrijvzGOP2nJlLjfNVbmGzwRzp8od2Jlrm0t3C0zm/wHNOLlDvGxd+vh6Jg2B15Y0iQnk/fSDv71PTSovS3L1BYUNpzJ6nzrGghClcxl/68Xm+8IVYhaexniKAcvtybT3ncckXyHMYx7fERWABqOtI8yci7+gS7iYlKhIRbiV2TvusojcStEMsqVoO9IwBovycqORsM/IpRzYH+NCAACYvzRsmIbU12VvVZ88bTKyI+r8VM62KQMWhVBG1XdT7kUk5/Kj6GZcRA+l9jEdN6nt/TRLtXj0rmcMpltml0JPnAiKdnYYJxSX0X+P7uxD7hkkF9d4I+gQCcEUUhcpig2gegnk2nUP6elekJjPM2Wa1DOCNfcZm94DOoVz0Aer4S2zYIhBYNR4t5C03bISzdN2NbYoQMfQQomwDQPF9/8Nc0uztUsscSR7GwSVbTfNMV3ObrY3r3Zx2JTJiboKmczxUPJ0jU1OUZm0k+APtaavPy1P7lMB8OY6FnPsWZapbA/xSNkBUj/NbSKrvcGB+3QfWUJXwT/D3t+3DQU1vK6u4e2q3lM5wMn6sUL5So7eiPNTar0ypb4ze5BybWFGYnBR2ml5d6i1E46ApuG8Mlc055tRSfUucdQFRgYcXE5mU2TXszl4wp5SKNbtI3en1mhjy2yrxwqNS/4KTudKF0Gnju0sWdbLvAp7nx9DA3gAZYao2S4MhNhWYBN4v8Ny1oBVornMxirgIqvL0tlOiUtVnPvjLMr3ykRHQZVAAzXl96+JWOJxjp92x054ZYKq2302YPV/4kDECU8OfJYMTEtvBdyjMDE7nPoiz2DbAVGqYMU7WtpyBjHEvHpStp0xvbM0u7tn9kNpSaCK+rNin/l9DblzaalVPF+Bad4nOn8wvetAqk68t6hDJmv6quuBEy0Uc1wKReksqh7IJB6/wnemUWj9gkAWU65Q9nZZalpOAQxjAanFSu5C9vGarCEDdugUjjRmk49w2+W429/OW2D6EHa2mnPn2rSEbW60N9AStJ1DeHDbaSKczCLy1neMC8fLB5QoE0jkbo5cLHDUcFR4i+GfnS7ezp39xHyMijXHFdFgnFr53d1uNPm29WgMhtobIT/zuhpgSPlc4CBwXSCFkN8weZZimVDsmoozs/nK6zr9JjRi07IVFE9dgZFNqU3zgNNw4G2294I7Dc3T4JEs0OkiEVZpr8g4tbPeNK/+/ZXY2GoVQvwKRsxd486djqsnrwC+evCuAfGIs2rsRQHXyVnd03AGPSYQtQKN5Fk4oJMg0emA9wi+Zy1sRjGAWScaL5R6FetlYA4wdPJC5bRnjrMlZ3kn3YhrqnTuMi/rzIs3TH5dEF726psQinVYYYVh5W+hIKCEVUI83ZrkQfWu9T6Ovj9Ymf+4yIsHlgZesP7hOH+M82tmzz0e0CIb0OsR9XcudVf52IFFL9d/bXRbM5e8cliC0P7IDyOy9rn2DMT6PsJlAcMp1UXGkr9ois65rM2/7rmfU2VmAivzCIyQ53v11JXvgBPt6lhCxzDLWx6+pK2akM0OV+wpQeMUgVp9YFwEpbp4WZk0j3CKn3/yZNHe1e7iW5FSH1lDV1iPsNLkIroAn1JMGzKyYQaO0JJmj+sllmBNzS2c5J1+oXoBhpHv9aWzLl74ogT0D/eapgSFIEITW3IcuG+eQlgiOh6IrO1VkXwQgry/0G9qMdj6kH4uY3pMdN0ZFTwQjsfKy3PRh2zTKLacryYhE7NoOITt2j3XpFgWZc/xkruLfWkYgsAQ18AtnPzgKAcOaj0UDn70049xNcUhMtURKck0N/f3OT8PIJl7pYPkZkSUXYunnu4rxCgZpd/cmyGij91TN+Q0AotYhnW7yV7RF+seQJnL48ZekaYuo32IF7ZJafGmMGlJhiioyPh3Z0rz60czj+gM2wekB9B0OarL29aCL6j5GtCbHaSpVTtuGdzxmJiJkTkVbThdDis20Ug3nZ7/3QJ0N8pMqgGiwp6utqGUYFvNOF95ZLjP8oh6Ah5Mha9XEQxpWmoGkb1WJ72gn5w4X4R4uCLoloV+ROvVJXLqOZJ8lzgHFwfi3f9okKq13yshtHxDjqxE5Dph0+xBeVrq/yQcPbcFgYI+vYgby1QLbuxxo8oe7SEsh0+Q+Uqg2Pv/jK3ZWCuU4i7yNJPV4rqaqEyCt3GfyfxmPsK6Qlv7OE7dTqiNq3qbe4Q2L4EiUxOazkjcUh9Vofzca1OFZQNeRGE+uM9Je6/NvKBmYqh+aJJavNAKpU56Hr8a4wXvgkTcI5tQwVKb0C1/xcGSPt8bep27fyNkkUZfX7FXlZ8f2kr7tFMQoUMR/qXIPN3lPn54A2lKztLMr4pPvPKK2dfvTE3kEz+ejKjeMcLEtoZXo/eKc4E3baTpeKOuFtaVoHrRhwRLiEQrYg8oVuiCmv2Sp2nrVJrREFywqTBSeaD3pptV9Z0wlBis5lK4Y8gjD6A9fgMl4eGxN6WeX7IzaU6OPhPl6etcXxQEr0q7vB3O2MgrNtvr2l4n94ZiCWhSpgnspehJrmjk2tj+dYBkm49gZsOIsH3S2Ey6UFWH3onv2mVnKsiTiGiXkoLIHZpameIZU237NaTQHa7EPSARiKZ4MCYENyAn9KWwmZwdvMmMa0+nI7bdMF8t5EnRbhno8sihwtWKgbIa3D4HUGkEclFRWQJU4ThXbNf2VAibOXoMQUlfaoyK5VWzvYLz0v9bcZ2LA6wbpDY19+Gdo7F4raur82UbSSeGYzgJpw0v+Vxleoc+gDqXsdIwxm5va83CrvgZXDTktyJilSk+NAvgysOj9171nBIPV+sIBmEGSkWA5/NqlbMogS9yJLQi2Czpc5AMJoxZ//mc1cWOvpGTccYRAmfTfepI+/WUKZdWA1pTkX946h/96K65onD6SDIyfOx3WtaZzusur52oTsfz4AVhxkZSXHdWTbHqOFXz822yapIob5bOVUFFBxk9MtK9eaG2GcuYNtPhRj01Vmi4Z5ARI5s4fdWspA0q74f0ydBYBWxff3R1ARVEBpkUYQJQwkFFla6ZLuRjpFGulupNmlu0FCYOlGWlhqly7pznk/33Mffv93dp97Z86cOTP33okzZ86cgUXeHcex4+85CKTvWYPLaF6ajl8N1ygnKNPNUX/o9n/uxvZHp2B+FEnKO4fjrrf+m6VDO8bAEnGJSzhKhyiMVdKv6EgyxcPzadkuTzAERd/+mJPXq4VEPGorgXsID0Z5sjKvk7m/wFkByVGPktgXOktaii8BCMCX/n5xemMgrjTolU1LirlXZY0VcfUUg4nzzxMarVrINVSVefDfZvnPRQiXs9uSjctN8GLh5PfTApSgX3m6brGVc9KG4brlhFH4GKoqMiqmfqymBGfGXDpOeOEjWOKsmjfC2amwSp+T/JWNglo9zeiwgwYz5NLVN4hPMHCx2gdVxFqQAZPTZJTGVqWBJL/EHu7b1GXRiVpsUoHha8aJ6F19TRHXr/LwDTPo8obpeDarEUHMjt3MbkM4dtOThTaTvCjoCn5cNRPsnDUDdW8DXMt9fBkhsek8+cpveQkMdbOZj2vZRE6ls+d0XS8xqBZSmP/ZfNKxlmcw3Au8IyjaR6RxU8qCMoD0y+eIBg9Cax3jaye7d7e8G8jXKkmtbiROgGoTW7EmZ2U77sHe8ieTuu58y10ZRqA49eq35HgRwrk1k4cuwNzyJ1gF4pO4BbfBWGtxbAejUA1Byi7UwCULbu4F9/b8dKCLsANrCa1e4lMeZNdZSxiuFHGbtdAl8P9cG3whQB4B4/KUMAkAD5N22zG2ywn8CO6F29vB6KURgEZNobYI06e7QltW5rNhHClLhdejiDXmNsqt60eFeZMl9VzJ2JXZM+dVH0Yquftsa+Hb5DuiHpX4BYczkOCIds5o6wh+pgW6+Re+TU3ftGsbDgxc8hZnjKxQcqTxutmEbpGhkeAGwLcDcJiIiuHo1VzLPkIebVsCeCVT4WR3Ks+mWab7Eon8rqrqWvs+8ulXKVckUkajIvMf2TFE4cWKf3VTvFCeI/3w9II1ngDzHawc2Iv0y/LkVHf9xQ9UBOH+vJ3cYWnJKxueAd4928uyvzniU6fzh+jtMNaQ3Rr8RX9lIN3wrbiWGKzffYJKy5FOXjgfylkp3bocii/bghLwx7dS5DF+bUokwpsIYWXvhb4Os7VU5UwJAoSUWt94wYHXQv6ZJK5jXpoTHTsDNDmoRiE2ysJNb4aLzYIPDSYWQT7ha7qYkkYa3zL66o06XTOWpK8cJ6E5EZTw6EV3fdBeSXegwHra3ywgBcRoHH7bxSVcQzOHmSD1nWv7l13biUxaR9vcWSWy3LlyJvIMP0Ufo/xNMVZ4ep+P4T5BxcEZ78cbtdIZZA+T+FZGgJGFnUXLGRGQbCXgKZVc5Vrofp/2JkGQUwZLugXgfn6L/d97FQ8yryvgvQ0BwYS+6Xznrn72xF+B23fr1f8ZJlcUsB0nesOIxPC0nAlrnXfZNC6CkH1+aey0ZEOO82maQ10yqbnsOfnxfySOK+M8cLl+YjT8xGMSfsPG/KCYWr4KrQVgjAyBB8iMZZlM9YUDIvR4Ffx/4rVEhm7+p2jbva0va0JQbCrIsnkFIUBqclt4xLU8819HXvmSaip76Ci0cfk+daXqXips+VpGC4vXseRZjMChHKm3M4Ahnjj+eIFZ8VJ2liU3xKpavuDZr27MDqeN/wj6f7pzblJJlQTtfXJvbymYjOnehvhg4OzLQkV+/3Hje2LDvpPFfSX08RvbXcg0XtnI4lqa+v0RELa34h5U9dN6GFzzKr2NQc+XBFR3IJvZCizrjE+Dw4CEJhwWAqRb7a4fG+uqZrZ+Zf5QKUEwYFyp4T9abpJof3Tm0ti3rr9JsjG2lM6YrS8SJHDqw07R8OTEZ+ivl4WUyUj/5FsZC8joGwzjwwhkx7PwZLXxvoJr2lNbSYKU9kr2NtO2ne6yetND8miiiW/4d22YKRa2Im1rdvc7pnhps3YTtU+WRE7UdUkR3DTbJ+0eplQW4WhMtK6dlk12bGw91AQyru0SymcnpGkdjvx4myuEaSWTFufv/kQz34IGbwTf001+be7o6vcVp6uxUvZ4lcSiqAvcWzAPzOa7FVimrkkpRgTLrZYFzV0wgIrkV9RP2c+ydk+NOW9Zxh+xLqCuZ24bENokLWv4RkqTcyZErCiNNszP/VetHRYiiDwALrpUm3W0215fU28Z+f6599/07bPT3YB3uq+mpqSdtV5MsgaGp69rUznmYrH73xzeXvw6ZLrnxywrWKn5qf+StI1rTTxbtCynN+UfL31LqfnlF+XZc/CZQ2mCKjCVwdIP6yMIdu90Rs23OzEsulmAKb6uPQcTL+2wEhHTZIzg0+GKyrqRVjh39IRj/6HnhqvVtStKz9ZN8d1YjJwCwr19DvoAAEAASURBVD6Wi69tQDj/bXyBS6PZPcAIEBfcaZ53VssfPwdNdV1JphwqeqAf9pNGNLlccw0m78D/tI/l63ZULytWQ5mFX/bx/tdTFP5BmoWL8VyquTQ6lIkyOtLulS3lPGLu2cSyTknFWFV6thTDdA4fOJ/R+8G7v2vmBRHW8Nmna4OqdHucm/fVtMNSbd73nD7jub/Lm0eJZ7jymBnM7QsIItrIz3ZG6ylshYJrAZixbzmvRWVmbQmtknT6ADghDazd3/13xWa6sDX8qYOJaY1wJ+k44eDOgtfdsJVAy4jasbjG9wIdOUUdnhinE2g1IUoWA8fpS7bm8CKDG1H5ZhMvAubuqNv+McGA+lSpYS9Ucq2KEN3cX4bFhGWz5SGPKOo3HyPlRmGsQPIvErAfuv3IwFQl/7L1vFe5gZztIDMfHDo70dS6kePNT2tRf/qtA5U70xZ4nz8tNRLrJY1FRs7tgltRoIsPDxWzCkH+kwL8Xi9l5Xwuwy5waeLC7/pBG1xsfaCafjZjk0/8kg1MxLGAIlNjKfDakS8M7SgYSmczL74wX4e1XREOngCvzg2xQKnFqNEy6sSRdFFMxrtvhzY6i5avN6Gr3Ulc3oU1xZhmMn91qYF0mYAeQyL/t/oiuZ1nrRH6JB/5eE/7G+jzNcrIGi30JRUcy7LSOjPFS8ECNY9YoCZh2r7WliotXXy39hGCsOKIDtsjJYNuYanvlzVusEiSFW1Ym4FcWkP2P8KxapcMrifsvpRGbpBrnbpckMoR57utLSFOL0z+Y0JEYKObbeJEWXW0Ivw1aoUUJXnysuODkh/RHnNUY54IGR+9zn1awkW9vjqkgXk94n6IQyifEhTxFxr5I0OgknkUenN0EvBEQco4fykLVH2mX7XZ8uenWB/KXceKdzg4tUBEpZsFmsa3EVH+J0R/H5iK44uTyM13fI302xTqmGWkF945I4pH90K6/BwhFSPIzmcDooFZlCM+8IOgyD+p74tuuPiR/lB2gxS2GRQiE5rBYZ5KjCTjZFRaYgvxy+H/ucQNlZvvUhdYjIkxGlGEa/xCW1eY+K4n6kYDZY872Uh54JrwC+ZsWJ8RINTKWkqSIQzKKE/Ppf7MRdUGmp0vzx4Wi7x4aRAznXRKBQSOUwuMQTpu2WxvARurKAAF1IlrODp4y3lczWj3jC67PrDDBprk99UeSUdq0RoZdfYBgftPtjaDN/PfpwlF0agA/4eIoPgyX/eI+kSqHkdS2jBF0YjVz0dy+dq7M98TftsfoYLpacaxDoaa36Rv1gaWdQsAw60wSwdULazdcjGRHoL9rgxd6Px+sxcWECDud95CBPfO0tnF/c3vfBC5F29TflFW0jgiE0yuhCgJ7zbusgKX3cpIplLhcqdjtPJidvuqaZIvbY0psyagd6ravvr9ejdLw1ePb2tEZNnAl2AKrgTqsjPz0zyTPB77NpmUVSpTZzS4f9LMliI7vFaQyAZ31FDxYF+qYBJtxvQuNjrYcQN0LC41d2HdzES8QTKIIZIy9gH/bVrmPUrrJEKUCCT7XroUiVVHXuL9TQ62+IEQTtLSAUFlZW6j8sSKJ0JxzadPWwSwZgscH0nHUvE2QJnFr5fv9rWv2TtA0RiBYiGRD6VhnIqpx5eCsAqsmKWraHd8HYYg3ghdC/dTXJq8EYRZ8qR+BV9mZcdJtidCzaEijFwbMX6/dipOVCVDW9105x14MPNbt3goxE4LFECX07/K95Sn+W2Y/3iZC7rSG5azL9uMFRRkRKyPpQFt2N0P7v4854alcEeqMjj56YUJBbR0RT6iptcX0OP0BHuvtziE2zvHrPW5WNNETIN7jhb5XtUI9/j1HgmfTS7W48V6bGkHg93FtMtX0Xk66140ROHeiHfwUjuhHHmG21kE+eHXEnI0uWsxDyuMPa1AlK2z7wPXpQJw/jieHHzGF1DcQ6JFsiugGWVuUwPbLZNqmKsaarkUYGaAB3d6Ki0djgQpmY7T46Pd4ZOx1OHenkZb+QeUG4NkSO4nfHqMTSTkUw9UehGJr8Uil3Gb1oLUABoApvM5D+923CYI74LIKa8SEL9UC6ALsLy1SjGTIQbQKz8vDmJPIspgicWfWczhjVkVZBBYxJ0Hd25OMXlIC1esjIX/6W76KhxhdDZiovi4UQTjqWPLPTNc/MhFplQ/Em1pAEf04GKuN5Va0HfhKNhVrGZjlNDko1zMEB6RzPJBpcrMb9TEBErGW6G9atN38C7+2TBqrKVSaVQqEzd9IjFCId92mWAAL+WkBIrWf0jtrQy4plLGzguXonhwRCxvcT/gURqVzEhooS6+y1dAEv/tC/Gh0voOe3dSl/2TZWuU/jT9NjmoGTFhYZC5SB+vHK3L8kce+RP36dmBJMEoM+8ZN/dMK3Sc/K98VXCH6yo+LNs1v2voOibDd05L8o3xI33i+DNhS+oTmkkXztizXNORzSJ4/JDpfDILpVGzN6i4ZeO6cHQSkFuzuLZt5NMHva6y2CWRFamZMtUh3I1D3+ReTFEkbEAM++55Ej24nmCYgPwuYD+3r+zcCsuUj4J0vDCsre2VMsR0Mw5FpBtxnm/oGv1+KzVr8KRYEJqhKk5LhkyQr8GX4dcKGq6XNrEHsVe1Y3Nb2UsuCeHd2Lf76DP6TRVH+iZyV5FzqMeHubIVu1cyx6gRxNBE9AXzvM2k+KFiJn9a74+jDoJoHy0k87uk1kfqEBTKeHNLdspA3EohnHsqa8P1ezBoLzsINiLMlbYLkWz0QFh9uLJd51FL0XJBTjQZX9Ul0MkigZ1UHuqx6DUY5q7lZ8R6Kph6pfNAW7dCGn69rWhN4g9wbcsGcQipHvjKc2k0G2ituMXSDJUbHZAXBi/fXoluJS67Na95ChQq8xjeJOriYPNxoSJjixzkwfQbwd5KlrL5gi0fX6G/RShC3YOwLKyohBCsyv2fB1w2DFX4zIrHZxA0DPORBNZYtoY4tY2OZxIGQWtg7Q8FAa2futN2Rkr5nesxRdcKquZM/Cv6WSw4KEg7hQDMIon/bQKxBHh+QXz4tK2pqsDQ1H72iyis4bLY1ouYnZx0hzYV4O1LGHFR5N2CAXpOn1essM1HgLa4imRp21jl8/G2nETwXa/62+e/kzrLZWlLukI1XunwLTtFjF3QnIUaKu0c7j2BQ8a9muPKZdcbuI9UJGF8Jj9uCefahhGl/wiu3LgW2GitS4kwsdGPOxRRodoO18cM+BkronS/NfsB/s5FvqckuEvReCA4rdGgUWjkud/GKJmyZgASDjpi8mjCBVMBMTw9JO0jfC2Y6sIDvMj7LLDtDciv/BvzhFQAOjFRSMXVikIAhkdMvMEJnsC/ozTypr2MhBVk8RmLLZkZoW/6P6kHe7TTxWY1pVj/CNK5LG7+xZi0BOirYvJxb8rPMSy5CZFRmsgIUdUdjx5F7Vv/slrMLaFfq9MbZaV2waXRfmMa4gYxUvlXC5HBxaYUmeszsG+XMrzSBezhpdY7zzcihA2hLVDyi6fRt2NC0ic5iQBlh/K6oI05PrcN7odMS0mGSEcR049BzGWcfFeNNnBQKI6+yl0bvRcsR7npy8rM2pRdyJGs6Doz1EL38/KeQZebCi7cJSHna5SD3Ij/4feQr49m8Ag4X6dEOpoCGjSxzTauXc/sco2RjAdGhOFUr6N5RVlUws94IxcmpkrHmeCkWYPTw7Cv2piXxby//kVfsHz0mXZgNLusQ20f5mM+1ROEjtuUsx975WIZBXFRfIqf/dmJ8t+ZhkZpGfR3lD/OhXH/Te8rNBomNK9asY9b683ReS8b6Phi3gI7OmKBYA8O+9B8vlGZesxd1Hwbzh0DrEaAYSrx7/64FT6eIOE+JjxcteBLOvFazBRtcaoT6vnvQwNTZny6j9G4r6FTv/rUUbw+c2/feIlS+QeXEpipjUS2tPCMaD0Bf509xs+xr2PLx+9UEasHh7da8Qd3so6PNVYGXHM3ueciCYqEXJpN5fqOIr4siPZpgKIrRwc8v0/yhD6yiqbukJAZaV/h/OLgybuB9J9PI50KsLNLVClHxpuFao47vAtZ4M52RJywwPbW6lHAFNpO+eSPuu1dpD9fFOnBMoLI9HBbgzhRBZvnhS8Op/sYSYkMIXQt+62EDIy9f8sYqYRJSrh8+GzG+MPvBZgypvI9SyPQipDRsjI0Z9RG5Lo8Ci35+QKUh0GfFPw/SgR7mFAorWFA9TZzipRZoEOx6x5riwV+E6IVL/Qo9lSCVYFn1Z2DMfj9itKLhWa5aJHwYRz0Au7uSmVBQeacWUxegELPjgLRZf+MOU0elnsM/r5zvR+BQNliDbAvW8pFBBmbkDIv7LE2t9KrD2JJem5R8pB9VLHGyrhhfD9DnyyphVy1P2FloDXmiS8YKWZ4kO/SY+BeDVgJRDV2c3BxehWYjB7qWN7ysha5gImvYH53fy1mQA1seuwyOjeT8C7lKYTDNaUNp53GNE+oMmBIW4cy9EoGm5LWH7vunxejR2BOXWkaccjbYBuH8c2R0XHWh1v2KLbl1IzeFNesspMVS+romCHSkrp72NdV/sackSI4R0cFAsTYgT00t+wORQ5YOlbVVcGlItsI6Us7s4F5kK4Q7ENSnYGAwxi4K2BEey/YWGMRUeZy2Eai+/g7gd7NVXyMfOwleI/Uwz00nJqkRwLQ0mYOoellkBo8JQ3Gn082qIFIKHqFL688ZTpGNnk7GfYGsU846MI0bREXslde1oY/cYcXtLZe6q/SsQ3mXzfl3sy/BXt6Bg6WCvIy2leM3yvuVl+2uk9QrF1st92aTfBWLLev//WpmrkZ7evTGHEX0Wk6DqNoSnKL/A/pfKleK75QmFwLRPvuYjcfWHmYbsYYXObA0khc9i4FY6hxr2iUSgIPohv5TPHnJrGPmxALmW5rE591XaUgZpeP+NzXeB4QmvnuJx360qlGsv/EJfreWswZ0TgyC/YAQcqXMCohmxYsMSpmLmFlgjFujJJOlAe1WOoRDxHtH5RwHQ+/nxfYZCHDl39i2vR841/HAzk4nAtNv11XvXOjw7VRFKhISROu/Fj0BksCNU4VHeOrPzCiXKKDaaeZLzVLwDM5fI809jYDVShAeYlrr5IxhROe9V7o55lsrGHRXDVUXx4/glFmoix5nLgNHCmiViNdemf8PAJ17JW9D7xFazqvllJDD4i6M/2VILYtv+RXwhEokw+Vrj+uuqs27MazegggWe8nHMlsLkPMWaW4zs+ovsvnCaq0lLLq3QZurS+puKs/YfmpPi0GsgJy0qfPTWmNSrQbdhyf2nBwApCa6ocQjNQqIooGc5Yw7LRWtKxgTybHGL3ibQnIlb+TTAMte46P89fq+pf3Ry4D1Q0wLkWPVg4En7dxaMcC7VOFZd7B7TCeloRM4185sDBJc3fRrsZ2qfTg9C7pwWewmvfA1Yu9o7y0O9A/r3L/gsW0gM6hKxK6cZCJK8YMiWiZUOPvA5fUFFKWqhgmJ1CS60w+lgQ2TdcTkYNy9JB8MieLEbXebEm4NNNFRpComWxHgXVas7IBlmNywr6ZzXq074565m8/z6ao9fY1+Uaw/XwIJSRpci6P4etb+FYjspwBmFUqi67w4hEkYbPApb6/ZCH8uZDh6PR2Lh7REroAO9AGmYCcBW81Uxk1/ujpmf7Kr5bkqHR2A9+MpHlF4m7sLQdRCMoqLqBXZrUULftqEyTjYSm+IbnwVp+KApPLKyC4nf8Cpfm4GyMFzHoOOfA7Ln32TmNS5PajMo/E2JjSRSjS3CuuQJDiP83O2n1mAbcAgrZsWDCn4U43/H6pwOS9hV6kBVaETXXL/IF4bvjPIPRDosPKv3BVjjHM/oa7lwTrycC0gFJK76hn4FfSh6PHl13Z7OeL0YrPrbDdTkWVug+LYjTxuooYyi9as3oj0iI7wf+GSB4JXncC2J2dL5tVEPOjl/ajzMOcTCgJ/Ra/TT6MWcH7PRW253SFMuH7neVFtQxgcRgCkZG9cfD7CMLSKqhcpDil23Ts4b0nj+oJ3xJI9/j+r3omjDmlN4CkJAksoOGQKcIXMS4k9Od7lqOaUt0mb9PLB+MfImju6/pjwbuksHB5+IY5st/yBYvQJ5u6RpCzhjpD0LXKensIDVtDA+h9sOr+1SAVdUdRfDskA2YYIbuW7uF9hDfnNtFVLrmfYCFhX9NrZn26Da/NFrjP2aM2In0zQc658kqEQFBJ9Zt83W7jO+RXPPvQ+bVlFNlO/SRVg1YCZ2DPgK+R1myN+LELI9sJuIZ43lYlFyvdIxJ9ychb6AbwE5BBPqDjaXG8abpHM2YpXUGdaMCZQ/AXlSSGz9Ym7w8qxf/cVVSy7/MFb1AGMJfLYoJ9LEKC6E+dq7y9asYD9idSDfdLcT+Y599ocGpY4LoPQIa75YtkVElAaIyuy7ZqOFEVGi79/YaLIC/Yh4B+59By1TPBLEd3IJe/cTljmAG44PK7t2L9EbK/S7ADEo17YEusytTzr8gNVKlkZf66aMhsd7ggZfP/z9WjQQyVlEeuQLWbpNtzdYiLUJY+wUP6idFw1XHOlAvU/38C6+cyLKlqUqg3y07k+/TzF7RYVl6J3isWcOT4UZJBe9065PaStORCegXVsUTtvaSXuMcWiP/Gaq1yE7G+jqWKS7wXjQbUX+0TqagY+LsZ3P4xTf6QDpLguLMTKclEagPZPUOxAHWGYj7zpdwAwnL49kuFU9uO0zEl9VZRRLTMSUuz6uLHj+V55LiOYAVNN/nfwirYYTwPxBvTwxsSF/63Bzf/51uWsCLPssw9WQ6PTDSDKFv1t2W0Viq9hTlA9V0BN01FN9GHMSMLPDyvxDLi4WfqbfBXWY3xp7ZaG1HHiMGENUpork+u/Cbf/oIN1vTKx6JgOfPfveayMzXUWNycDJrMvlTI94tWVlzMYURGlD+9zPWYT9IjqbJaLr0/xmnJMJgc3o8ZMmAJnm7F1nEdqK/U+w98YH6yxJfuKg//gVEfVDpxs/RB/YbYIO3D8/3XnPIwm8GncZlRmYEN+ou+KNUp39OXrkQ6uR/daOyefokvTUCMcyfBFGl2DPobWzqLvbKFm+I1fZjlZwnHRXKcHio51vECOSvlbMbtZymkG3xNOPubMlO9JB8mW9lAIdt1rja05WiRYjbNb+zFrthqDhoZuCIrZUeZ8Z0PFX4kPJhOdBH0bs5tjw9KP180K2Ot1npJoXRz33MnTzXhId/pgiUEZnm/AFRZjtoKrFBEpnhzM2ZuNm0NosSX5atqwe3/W9OKU12SJkt31F/9NS6T1k8yrNvl6z2nyVb/yLBvKm+9z8RMM6EO8KH/Kpk8wRPmBHJSEwlYiRX1bltR46LdJsyBhv9Xm4A1PKhGJ+0/MYlcjHNQ4Wo0wG8QfRcjnYX0n1lq9HkbE8c/386QDLkGVw0/9C2NbxR53r6EJj/O/zmOCYOpxBJn0WidoZ/QHwm91HcnMIrNX6t9gKJ1AyGn+Jxe9A4oySFmc7P37fK907u0WiD5Hf2qebdSgrvLN7PCUA86K6Hb8fx1RpZCVw2ilY9SRjia4nyyUDTbs//LtRwvf7aUrvjbuuB2GSmhCVe3+Z3W4v9OYZi3jgI9I+oc04EfE54bIqTDXYnNLd8Kfq00vpSKPCkTBBUXip5tsdO7u+SOVXnGC2Udzqgjz+6GsBtAVf9bH/ehgHSc7lVpPJUhulu9I1OKscTE5XikpKdIK/wVdrAao7j4RL+vsQnK8eUX1zN3Oli8U/Do/ENP9OV2t4mXRjD5Mle+TaSZQyEuI1/9GagDhY8KZnJXtJemt4X5Y16jd+TrKFMRyu4rhAE9jKiulUlu/5MIw6K0zaRxNKe+3ZZsRPorByiwnz2XdxXpw38NkIwO0Wy4pJfYsFGE+7piP82mxQFV9GtdUF1ce9y9HCR5iYhpwJceh1B0ye/npgn8xuHNW9PQZ5i0TRDp/3JjMYKZRoCNsubfRpSLBmDXp322QtXTvsDK1mZCIaSDKKW4NYuNhmFDyJ+kaxGkIetJefZ1j25LJ1AMkKkG2bpZC9/2hAzhicquxirmH32FQFgSMVE/Se2eJhhmDpmucKff4MMKxWWr5cMyjBMQR6UxsOvFLXwjprkPwUJBA56JqPQtDSu4uO2DEHHBB7HJME1yOHV64V+ra4slNZB1amo/9xp4T6+mDX0N5fJz680DuBATo4Vl8+7jnjWoy59OdvE1AVBxKsCF6f02ZXSoF44HIVmCp/YUohYwoKvx3oe34BtbIjUKyljZAsied4EGquhp6Jpt3jWS8ywQbbih7KV1BsEZWnzGaJDsXbghUZakjwRwtDk53uwX3d1qHkUJXbtIg2LZoe5/9DC3qAa4rIY7mVnUqLbwdY6x5qgSvOvmfUOXTMlsT9FVVtfci0blA3MIltVmakxrfPDNn0iJjhaeWSkXB9ns8TGXjDa6zHWPDPtJ2tsFiZ+i/S5bsuD7q7+Pg5p8Ls2QYR92F/2AwT/HrzLPpw1iwUNEH8/W9lsmvMZ1M3BNEqNcin1qkzn30FMFKSHdKH+fMvsdsi+x1CeUVgOOuJgfCSxnP1V2zbAbEqFHSugrvlb0N/3899lsQeyLpj7pe2Orr/dHX47+b3c2VXmcDK2oVs5DsyGVJFi47nG4iA4TW7s99o8mWpBhuWBLvt4jFjHGS8OhKvF7bWckeb5nStPnVH15XiumpC4ZglMKAwIqW0b35yNuefkSCRcFR9mQ4SN/5QE3qpY9QCBN1WafNeQB8LTK0y+fIsVQfBjOjVo2VOs5AW3C//bIyXcWRhWpwWHMqbfQ5LBIHVK/lZ03KWz+z2WGqOpeI/eWizVZ+cgEjKjO4vdTCt77ygO13GI+ZEWdNpTVeG0SgEiv3yFRTlR03qGRvC7pm/bxGzo+b5ZCxBXvYsAbZgJYgW6x2zgJnMiC+NKeOCl9W3YxKMb3BL9vJtewvHNl79Eze6Y6HrFobkrXngb4DbWLdonU+IQliDWRvrGHTBCVYlUAQxBqZfpn15T5QuZg/PVj7lRVy0Jx461UKtwzNSUG+PFT1cTomTL4FjXVEWxQbE94P0PVJdOmuZJysDjUWVX19CtghV3Eo940RazBneAgQstZohZpabm43XzyyVQRbV4RbbnXlE4hp0UxaLWcBGtWCv9qqeSwxJwUqEtWElRVyakM+33cpu5aWqDcAStB09W0VQPaVITxk7cWIdYUcZkm80Y1b6Maf/q97oVTPuoukj8pQd5r7B3bozXpsUwHXcSYYF0XO67DwQnnd8fynE+CFog1AESusnIiLdxNilqtRUbiqhooGnJsoMlFfmE3a1mBKbzyPG0yjpWcbibg02y6wmCt5QnYD2AB14/vTqgjW+Rlepot9T7cEjNt+tAqQj83rnUiIUOxp/a6F3PN1sACNS5oKbVB/SqxA+hsZvvNoCVZ6V6cAtlfuzrSubVhdAmjNEWOJO4Jd9ap6HFoLEokPOAwnOtVDslLYB8OCVhP+3LbKDInnCcUFv0WQtfWAffXNtMnl5B4BC2SVjQBeTvLc3LJ4TbfkZcqAPF3/Wqmi0FeAPfEPjVQor35tnIU5EtVuBaSKx20dGJ04ZLshfoCL/cBlJOtBdTL4/o/6JIvEO7CJwRq9uplmlmtgPWjYJs3oU5ROQ+epGsC5a/V2kX9uh2RQWlaGPcZG3nPDeoz0BZEHAomPgFSUOZuKD8Yg4Y5K7rcKIneAhqoBO3pxXonhQKSyfRq0/KaLLZeY9a9ZSH0c1trjKx5gK4/sSp+l0t01TXctgauM92L3EKNt/YqiM8rf3rWaET0AwWW4gmoJqp8JBNdJK8d7NhcO9o09LzbxpE7BGkrcIJKaE63YVz6cjc1dljJpAwRmqn7jTfLfW1jA2Ovy3vFEtT94Q+Gnr/xqzdSEdS+q1EBloiCGHbBkJhsKIIO8OyAl5WsKirKcp1DhbziX4VK8N00ibJJ8TZDNC4Dq7aiclrLs/DGRNX1I6YlWneAFHJxFHuAESUnX58H1RxPrhLitgH2EoJSHUxvYAiA71fwltC/tpwqskfhv1CkAMLXS5c/41c8mbzS/gyknpv6zbl+SrNDV/g2Mo1M1LgAexyiHcMtbklINU1pAgLul/6spuU80suIBfZq4LzpbuMzSgFks3FU4JlFR4gbGkGQhjJfgbNINRDoZYEB2XCJ8H3YZJwQ3S5pus6bo5mNZDGyb1a0Obrr5TJeJDoZYqdtwiVm7Z/bPtvuwr4CUfqzoN7WRbZUGBge0zJGGR46mLekGDxYyeyF0ff5oOh2EMH7BMnQXhLERKONCc5lsEBhY1uJ5y0R5pLAx/tVj5c/IYBCtCreWX5/86ZFsgZkRLi8jhH+1OCVwsUAWuJG9EuMCrrlJvO8/tPtiDZulIFcQxBbg1S0Z96PnSvwizRUs5QyvXilvaazbqaxEZwec6c7kuDgrjwqECLhKura+H8itFu2sFZCLwv1fJYtxJ72iFYU9FeC5tPqfATfmyX2nhPMfAo4dYeyIiT9Pl98GKzL5eTXZK7wF8Joh8FAhI46vkrtNJth8Bczicue0b4nOz5KocpdgUWVeWvAqKVk/uvzLg35xTIBQknb+i56vAmV6svk2mf3gnGopY8MR502wwJKIAS7hK4Er/lENYPv9YFjdMqQh8kwiEdqElc0SMAIsu5oNpex2j1GRT5AEqJKux++1beVo6GDyFeGZQmoy97UxZew8v7d1ETaJlbncpNwYTFD3txBVhvsXOvbNP/WrZn7NYAf1XTR2OCaELLG0jgr23gsDRoyZFEAmQcJD2/N+VQTz0vwWQAKjVqsHQ7JUJ89gZyqLjDmH4aJRbkrDfbwpVECSw3EWjd3UQnslryzd7MmsYLlVWvV9GQRH3qyr3ezxnw7lJx6aNySpdJaJGl3MdFJaPN6HzFPgIDoMSY53UUe1c4FdZVLVy6Hl1nVVXCVr7ahOAo7v/qDWwizKcWQxRKtnvJc6WrnlmGiWyimOhc+NoiG+B1l0MJy+ZjtEsfcgIwWSA9R3CAYaTy7PELFHAIQeOUfwjzV6gujqre5ii7mNNO1LRMrq992tvOQli2TXMIfxpvkmOUOwUYDVj+0UgyfYYSpBtyjNkjJJTMFPM8qB1nMAtjNCgBad9V93Fl1D2qrwbLeOe7L+FJTp6zKBuryqRe1ZMG8o4lo83N8qwvrmdNLIZMJYRi+O8iBTiJK2MkkNj+q9RgY86vbQ0nKy2Lu8WobTi3SlzkvOj4uXX0foKf6rVkudStgh1ylREACYTGe3U2FKEcKbdjB5b/AZbvqnQVHzGGfPD5WA3TmWxvJjqSZjaM8/p3zzCN33xLjj2s1rZ5PI48cc1dr1Wbe0Y0dGlLJUdTffdo9doNZ5eO8CxeFxoSVLm+YytE8sGNEk98+V5a0Zz3S9nMcyoJ9A9GrFU25R53XC7DCCGdk5fJwg7ZNWejOPevcgLk+3PVdl1Yn1C6/K0b3qb+hBs0oQb7U3o4ax5RuNTpn0lXD39b9Q0uu427lwz4cr9g3PGWKLTFo3Sk/Udc/YyuNGpdGlsn6N1darain3GYkpeYP6HzKTSyqjcef2zS8iu14DfcNe94UkTlUEEBXZiAwsmvC89dGnBRO8Ijbh/HkH7RXUmREOjYCoqoyCTmyuBZGnnFa5WZG7XwBhg1kabAKXhzZDOuDG/LBX2KVf6gE9JMKVPBHzprSKpVxQee7LzfANhQWJ6qckXjbkyt0rchOAnuTG1U4QPo+ZY7L6yP9qgKsYsNgITHKNLBkEKOXsTBaSOuDl2nYaq7oZq7g/XewFe4QsqtAzUfYJBtTSCXr24YFFSIw6cPQKpPSY+kXRNHX3W/p/vSTF2Ej4POQTZlIYspDYyWIFS+zH2ZmfCCIIzfINkV2X0INTfzePBHh14GNojr5L9IxW0+BgDOxNt19Q8l5jQ01XoUqIoN1eTV2OLy1ANuhftRPOrUissIXAKuQFBdLG+DHJN592O6iOCc+6G987H/isYmYkh/gV/QPU1YXbeRcu6i/VNk3zqAj/NKEbYJBAfgkjEdyY4QzFtPKlOtmm5wbdkvPa6y6Jqiiek0hGFGsBLqJf1AWtLozruIKCQZ21/8G1NID2IFnGQUptw8VVmqWTNx705SkrbuMfwXaqkn71alsgstvNW8iTe+gS0rSCcGtY1l8FsDvLJ8N2bh13efiLZ7mL/1pIC6WqN/2KqN8eEhniQIEmzatz9XOQ79G/B5u7W7u3fDE7akgbqirtVh3FOGQ4C09I+7yK/qAl8vsSOypiqNXSKp2VPYTew+cgymWzGwuG1W8b14wHQ5M1nW/6TxLzOYc6u2+CJ8tNlPqORPRHVHLmpdQn4jC6E9Dhu90qI8p/tDCLrut8HhPFPN2MNQlfZZZZluY8wKLr7kydexD7B8CkzbBu5DJaELJYshpRLfWEVtIs2Wmegz7WWy/7O7ro6kND5XobgUe6UdbhXLbYwTZ6nvNIGlN3vbWX3gd1FNR0q+Cbn6zi0D4Aptx8/mC/efEMrsWH5CE+rfsLeInYm9qCa9ovk9hvQeJ3JspXC7i1/vXf2tCzVMsueF3DCb2gAn3RRz3rD4JyHijZnQ874mgC9CX8c93PDnhI8KooLNG6p1dYS2hl0uquB/zIn+CC06pdoZzOx7QOpEcWAjcYO824/njusUDxmAMS9pXdAx6EQhUpX0d1tjeYnNg2EnFTswPl1bl4Uu+CIhVdNFIos0ghQDNWTSfxw6njbv9E/Vkr4F1wUotDUGJC/JTWfmb5Eci8MveY7lA/RQpMG6Hmzms+A/TCHz4BsSuuqyGkclQXNAovwvwdepIWo0Kc8Vc0Su15qZt+Iv9bvgvXyOnXiEshDTg8Proq8prJuxdNAC5t29/dZCHJh1kcEkihnGdKwNLoBZJj7UDAXD3zHrAzWGp+hJw5dYLISjGnNARx0wgA0gxXpLsw5ox7rdoYu4CHR/5C9/S6fo5CCuxSRvHH008heGIehkP2cZ37gIMd33CTJWoIY+/QNzwiFi5IPHmry2wQgJQA7Zu4Y+O5pkm0HSwR46I1J+H3afBUJHeJlGXBvjKuSXH+t3D0yeJr9NbAzcEWR27qwn1kh1G+3f6UnpyNPcIBrnBxTDFYPVT1g9+Nt1aBNPn0Ado7PNNiNSpYRF/seZLW/gQPRrUKE/doyRPlB4KCWRWBq3z4j1F7qro4uxtBOYUFCrB4p6d2sH4ZufECoOI+vx4DXK/5DP91to687qAaPfpJfB+t6FzgJtZQCbbXLOz26zebDyzDvJh3T+lUlgU0ZEjlMhP2spsScL7+0HVo966Yx3quGgpHGLLDJngnltCBCu5laSgn/xElc/NiG+ypac2yd3glxaQdBwe0Z386xtbq/Hv1UCOXUipzVXaYDdTYIT36a2RQiQ/NuoMfHTfMpHq28a1NltBwW92r7yoc+yrHKvqyw50B3KLxmdb/VuVaWk2PWXD8hfdXmRq1Nsn2u9PTBErTYttOBK8Isu0CKAHzJuiAF3MSGmLikBcXcoMGHOSgRj+yKZI1vV2KebGbzx0x1/aAL/7owogfEvzyjdQTdUcUyT5wEzCU3JJEq34oYMFoBf9LiHmbOnxrCA5V/p/GTiIcW4jQ7jvWlAhrVoJGO0+kDXH3PJPfbvDXXgAuAF6MaK/4VWoV0OzTt/q0b9u2St6HCw9IpEJHZEAnNpbxo/M77KruIfyI5eR/it9Y3bLQRiP/S4YdGApfbstnm+ibdNSW2/mz0xD9p/PbDHdK95WuZnC4c7AKGRQyFdufUEt3cGoQIPrUfPM1sLsbmuQNYJazJd4Ndqd+7kmmZCtfnaDms+sNxXHV2Q2M9CPXJ3nUfH/RUur2nf9jh51GoN7/tLIakZbQsPgQle9k4WMnaeQhP9OzPZQrD7DChWZT8sXDZO+oz/fVHtry2manNKP/5UjJzOmuw18Bv32IkuIWbNa6PH9owAVbe2JORS13iMbndTBODd3PyvGbeoA7shk5I4Q1/uDvVrN9jci0ShrLfMf4L31q54x+q7tLGrhK8xpFFtgVgPO6i3P6l+XADK7td1UGZWE5QRGskWBP21g9liHl2qtVDo6oCfycakRjsHVXY1fV2CEecv8Qsofch0aWnpSNUT5czyBPSlek6EbG7McW54j0rtjKft+ZCvSWNwrK0MGw80mtV6Vc9MC3uZnIxIBTWvfPemq+bDxGK3ehTJTEykQ7FGx2bCgFYOL8KfjfeEc9EDOLUrLNzs8jOiFphQa42/GItVzsPU2TXKGKeWjcACLXmibjz0/19zExrrnEkz071QqHgDjVyPlEGEEv57+3S00lRXWHRBFiv90O7GO3tHvbX9eAfo6nrBvAZm+smGhDXjjtHgj/DPV6ST35aZFfMBUk9GF9oYbwNC6UPGVGm4W3t6fH++T4ISMvxK4RSNoqe5lXSF0gTDRnNO/OA+cwBcGxGMh6tjGuXsO8em+YeoHsLk+4S1qn/oIuaV41dSGTQkeDzV3f/snxVRtJSJ8aJalI0LiA3X9FwHQs8mJKZJ73g4hu8ijQ7pm6xAE4G9GYmDiYnBJ7IrYiMYDcLYWq6qp1vsdJZi6p9IkXZw5LMFjJpPCGe8P9eDxhuBPlwPtWhi0tCC9lSiBthBLkUnrDzwTSGvws/JnbePYpKZZ9QXsJKBH/76R3Oyn2+q9TvDaXLipxJXhSGVNOidDcjBU3xc5n+Yb2fXWCNzQXY3yGxEefeUndND+WzgRRn1ujLHSuJNTB+oYZ6bj125WYi5rGzgaRcvhgEgnKxrUR//AFLp18JrcSl3q+eQ1uKUeE4neRR4iDgdCB1fgM2H14ce5jlwxrW3d70sy6yMrQW2JifJJhrlZP2mglVOKrXaTnU/XnsFKoatiWHHX0CFJbkj1ugrVMKN1VaIsFjaL5vjaDV+n13rS0PG00Tc+L6MtsHKWGO61aTolvlmQeFzBbr7XhbDD8rbzLro34mJbM5DQa23wxhWXRFZzP9L773aC5DugwNhUifn9QG34VAQuXOKCs2Oe8ZFmmfLh3anKK8fzA9XujAEHuxYIFa5Kl/cZ6D1SaNLhhwzxlR/bBtZRSWM5Orn7/rP9hYm/ockSqSLxR59hrfKHAjDTb8ElHRDZ9UG2rlVHNyasHhAtA0h37hOVplFEbXBgACcI92s6oO9+5dNYq7dV+eTCAiNYjCBxb7YBfgHPaGQVuc1GxJb4YiVjBsMH+60KeHItU0sGPxbf9QdIVqTCiXOzij6pId5Dfrsw+Z4sHfy8f4QqNfDQyObz9ZCyN66FoR6o5osnnxZK+MyP6y8KV8cO5/r2jqqPAhvlwjzCr4g7PR3UoDDf0oOdDKrdQyEUAMz/937dKelBaE5VM8C8v78OMVdM5+An3m1n+w4fYG2a8X+dbNu20xL0V7P9vUsLTmudwrmk62YFS3KvNVCTjwx/UsXvwDzyLXAQSmx3XciQdbMZ2rsxPhBRCxrG744vQKdj6L5cHVeXSZ21aO96CmjrdIwPbE3hlDfuO7pqOfguKYFNAoAzHoigBBu5UH9Ypw94/ZqGFqMxCFnQE/nmpKQJ/6DmUbenovh4ygL7xWEn/OvjCDMzCTxFsDvJzB6WtnFQy/0LQCGCT6To3FWLnJIxUamDUiCSVRtPjdns/NdFXLJaV8V92D7571JI4CvECLNBZFqu2CwroJvw+M/u2oUTyGjqAP7nNEG5MjPMDBVS4D43ddEWgc6JqV4GqxKkNyUsdOLg6QPcGcidHxht28jKY/IJ5bS2ed5MtPmhNhXU9HCaYaZ2l0YwKV6o1/fcXsyG4f4y4zCxZU2fKRK/UDEFJt1StzkBIe70JXJz6CmQM/iyTSBx4luJIc3tH8r04E+NeeHUlRvc/9zqV8Gi9cnNJpTMKxAATfO9S0DIBuAWqUS1KkPqFoEUKPVrrqGMCgXH1iVw8bLP3nfM3V84Vab3V0x4z6Nue7LgfuEx7uDGFvNd13Lf6K59fnWwmz0zIHKVAYnPQHeX2cEoGNAqG08DtmxatNeTzF3Jguss3+dVDvgOOO0T8dlNj6YTk9q8+3w8BJ0u6f32PT5guOxJ80AsPROJKruPEkGk2XWUvRpg5hUA2jKF/9Ij2KaNftxvwGt3NACRi/y/v0x98k93w6SBEX/ymN+DTT12WkjHIR7W/2QChPQPGuZgdPNhu2QsyByazS7RaXkx0Uw/pcm/Xy3kNdn4Qgjkaout6lEnsLK9a0L7bxnq07iWyv4gQlmpNb8tAZEtbovQ3Ye+M/w3Pn5uGmx6Tv/8xpcK0tMJLPjAW/5mTsNCJIgCu0RM6jfcCKGEyQ4er1YlEKXA34Vhh9c27+CDYCtM7mCKG9LoEI6eIMV07nDSTDL5qW4FFnWq28Lz0UA7dKJ6VeG01Z6WPyI7k1EtdbU9sdJCBEZyiBeCRN2d3ogIAssrllB0H0WBYM7K+T7WxQ45lvdxOww8MZUI6IgpBiRffZAI45FRSW5T5OV3Sjde/6MBBBjvJWcEPkjn8oQFKBVNe9FyOdgtylIJV6lzin+fJa2hIqpAI9MDVGd2gnFErwThVs5zboA+ZwXf9AMSfcjvmnYnz+mUgB0jGx/45uVYQx/iG3T0f43JRBLktKR74BfaNJ4FedySISh8VfK3r1zQxsgjzyJAoTJB63ut35CfmHv95Ue5EJ3YcaLhgl0YCfHUIvibT7oMmZVvGpYNTKrJaQL8vwhumuG4WnFB/EjQt7mMZPZ56T8CxqWLomsx39KMJSDNiXk0rytQq9OQlmbvfRCVCej9+6Q36w7K+pfvhD8H5mZAkknHUabpp+7ctz9U+YGfvIIKHM83aADlnwr3B3wHC+l6zlPjKisZHCcVAnfS95/MMgLAehYGFSplsTSQQMmKsxoya40BdZ44um9L/1T7h/lpy6pOBluy8tGt6/g9Lz8CmvuSRfqNaRdqi1nwFiqjt2GfWsZfkM8oC62lILCq7sfdrvcMDkk2/4DEYsFDsQkLKuT65iJUVT7+99rdn5lkCjAEhiIeWypsjWnI5DRPAjGpdE2VpCVdDy22wkagK4VhaCKlA+b1CffFAch/D+FTqwOkv3MWCGHaawec5utgNRCmgw8U1CY/+c/CadWx94hUBfvv01NN4X9ZdzAic8c8Jpcsq0TTv7aVuNgO87OEa6pdundnUgUr+oOUXSg5UtnYYZ3Vp9+8EWTPb3ZHom0oUaX+kb78qax7f2U8qGupJDJYxOTmH6LFdi+rlmF9IdUUuSJ2pdIyxobcTfGTVX0drP7R60G0tmsqPdBYor/XyoGHvQi3dVMi68BgsNF6mvT5J5Pvfl263PCJijCOjuVrWMtlVrz12HG61g0v9glReLrMAFTeEGHafgYc42cxsElI4GJ3QKlHtOmcm/rPbsrfO5XPuMuXi9S3IWvL3Dfa7FNNuRhQ8Un+8L8wBvCXPdhXnZpdd0I/t/u+9lQXDilXm6E9PX0lEhY64HtH0hOtoC3DlSEwjFF3UXLjb5C1zqxXfhVkKnEdgifG55u/FCdzf7AOcZCibQd/OrMMvS5inXYDU6dlGTAIoqIsli57Gr+lTqjEKrs6VxQZa5r/zaMAqYyMhSEwaYZVshPJaOMXONOLQDumq5KQIEBPheex6j38eXOWYI1SIYsO5ROOEG2I/1dNManWHiKU2u946ndHrzEvwtePjFjA/GjeGsDduUvGQXzpEyciO+YlfrKqSrTmMeAcVSGkrv2dGIQXlPKKJRxzTaN3f/Mfy6f3Dr/ZRkE1Oik3KOGK5J24jeoZ+7ghBo+jvK8DdsXKxPzCZOEf09A+wa4bJbklTDbHZNOx5C983XV13KrL6ikAimYk1xaJhdpFmAu0WsqoB7mpyWxXq4oLjh9a47nvok6IuN/pCA06w2a17jnx71knULb0NLSKffTmhpSp1X5Ea5X89N8T9tdem1AbEEEGq2vkfuqBGDPX92U65RByrf2Y1GsoeQHJrpcLmBhfdtfFtDJ6EJMtGuDzm1o87L7SP11BaDQFjmBD/xeidw5qY0iVZISfPMlmoW3pXCk3l778fD4U8RVozZUeog+3V35c7mDjCyaWNcb6AgfZ/S1sQz0mz6w8m1mAlkQVl8MaIMozAJrw2pZ0uaNXXnjs725UNx6utNLB+Qy5bhT0uv3CtN+6KdTLV4zd5cJgRtN9zcJ/9xSzo6SEBoJ++/w3l/guc6JrEzofrR2Vprzo5x2ESDmVjULrzGB/uOct1geikfoDSB7fbO1htTxGspMiM4B1g2QCy78kTckWDfyryVC3iYNfEAscn/hX0ZtAbpCZ1OsfvzypW1LPBkcosSEsCdfx3Xv2NEJCkof5tJXYj8zHyNzWnZpAk0jvriIjk+N4L+16NqebzsvUlIEY8RtMPosJlIe+JXBxbGeb8UOXc54BxpA5KR73YLYTRsLIBRwZ3UiCNk1fLFn39KwcwhSlR/bR2CCzLtETqJD6/9sn38TtipSJmVoK5lPG/I6UcooPG5LzfV9/7zR6I9xXWHLWJlpL5yMrfJv17yEKPUFhS5ryWNyfbacFbDGUtqzk/XM9rvxBJfmItR5RF0SW+JYE/tiWaVCahVJud2/T1wG83zkcu34Z3ruNsOVIByY79JRKsmUQPUJvsTTC0tjHnWeP+IqLQTZr+8oo6tfnmA/yXelqQy4ahT151Y1wriXFUBIF+O3Svaj7ZG5AxRSPtXoC9JbHHBuo5w07FyBCR3nJUazRTVeI34MSkonXVSSxmTuF1mx2S+gWcueCOydZrtCTXmZF4uUg6HYQ8f5G/MGQJk77eLaPA1eb67cbdXf0siSM1fe7mq/snGt2KX+N/OA33/IG7Rhppq9Qdrso9EL83fYKX+anlRDl1QO0z8qkgH4nnxXhPQO27kK9hOh6MMCdiF/hGN3vNd+CSoNBGK3NuU3DAayOd6A6AA3R8LO4nYxvG08wvITQirJQFmUJjVrKKEjzL41vpEoxpEgPRyanYrkn/3YOIQeAVM8oCzQPWXSAhlaXpahOxyshIJv7Fe5UNnLYRMaB07x1KOX/1IU25hXSVr0CYOw948NgORwLDHR4QnM90cB73xgA7djTjA5St6UYsJoRL6ltHJpMLtF+/SGr7So8KKZqcs1eFP2psrcGA15w0Ew3uqUeTBEUc9ni65dToONtjY5/AkUIAaXjwOhImZ09NDJTwt4i9G4KS+JWpPhJyqKjiWK8g4O7axQ3kjw/r7i9yPAPf5+G6HcJ1rfSwS7MW2BxKjP5tlHe5/w/6Yru9rmP+755WXxUPFBcJZ8VQQT+0QNkWz7BMnZ6dfmsKlx8bPRJDgivow9XHziIlz2DL4zmGCo62Rh0LRca2B9DD/YSBwRWBh9TFPjdJVQPiw9yYWdI4L7oxYoM3qZ673UgwC2RqNfcvAdO0YYOzakvhPCVxR9uyFHIxGmyXVl0KH+DxXNqxuesILr8B+ge4B05GfuxP11WhXBTw66Suv2HpM1ogHYhaoWjTK+u3lWgt27o0UDZk5yNRtRHC2a30jx6u25v116R5zf5KDXyh1SoYHEA60xj3b+hHosYwHw9blVaq4l1wlfbTFv4MDSsiCHOPrl8tS6sknZIL585nYJE2bWOFWRV8SkGuDDAbXYjNqZQ3GTmI243orrfVLwZK8zou08eg/qeq5isiAaNQSspgNgfRojFedJKwsUscaG+EYzlL3HXKAtA+ncDP8MAnlNNpayfdnp/gXueVpQNZdqEAEsfoRUV/77PlNtNO4AYLfa3xLCA0LYGy1YsKUwixVZthRpevzPIrBVN80sPVJdPNN65q5UeleOl7/hYi3BSFdQ0jG+CO8Ox0SYzEPsEaeUvOs+ElermDBg5/7yGLbjFLW6F2x0gCXO761oS/ik52sBbLY7uilhFuYrqzeKGZnbkT4iRtQw3XBO/WI0Hp4gK0vFFcO2vhcmwmvqh7X4OXZfkPE04FIZbDqHWb3NDyiA6PIcEtFmOzKObNPd8tF80x4+gj4IOv9Rda6AWWTvrls0dw3+k8TZHGjsCuF4FzaEERBirVx6aiprplLNiMznQ/v6sX7It1WZqXi3bEexgTnI6r3QMtaaJxecq5wd8rh4KJS6IfOEv3OCeJ6BtRtgwIsrar3vvsc+f+dincFJyUaQIFp+ewh0zda0nKE+xl9sVRWJIgbdwLhPewuPgRBn+pYyrzDX+cSvG3d3Ip8Dcy2wm8I824w0EScFmR/TPHlEZTrGS8KlizuC5342etDUeM1MEE6nCiz9QlqP91vOx1gmVQhwCVi4Ls56dTFszqUwNJRxsEurq3QDxMXINdBKV7acigH4P3T3ygXfy+jydaoj4U1aH5MyG0zZaD5U4ODOH4Ymx4jvXI6Y8PVsb/5qILD77KYng8myq+SVnD0dpMjJc60oPmSKuFB3WatrY9iRKrKp7grezuI5pPQi5tRT2ddAEWWs8pCMskIJWQrr0Sqxfm3vdQx9nl3oBgB3maLmCUQ0Wgl7yC8NLrLhgxbXg5zQKgLwVeMQ0w92vPaIBoC/99HeMUn5B57KpgVSTghzEJ9IP1tRGNTijMFV+MRdMaeNwGYaXIUSNmZDGNu093D0cv0hsLz2FbbmmK2tcGB+e77RyLDUl2G9nHV3mNisOWvJtOnZTYijKJitXjDOCT3GIFdyvyfxH8EZCGAWj1rjuK8vC17jVpVsDhoTJTEe3OoQEDl2s0DKKLXTqe0//iJQRpwtt176Zr4NDaLTPS/uc+CuVl3xa7UXI870VnFcXfSqw/bqA+PLnVyPRRnYaOB6sl3Z5Nkbg/sWzmI1amGPQeQacRVq2wo73g89awC4825Q3TEYICs3Jc12z5qpfZJ/cz+yEUB3fT0iGBniWlIAvZfu135iXV2J/1xdiBbpucyVgkYZLNWrBdnd4asiwsJK7rEmlAShmUrRAyiLLu8Ws3EqpN5pcy1iuDsZjgAB7i0ZSYWHZ9srTAPQFpCf0LtuDmdNhR/RMsEb6uzJh+Yo6zLtb3+SZukMrbDL6bGx8jJgAQrTN53tuYDEnBoIDicif0khr8e2V+Yb5jwpdiEyhvoIZW9Ggx4uk8+ngJ5WxSvd/bxD5pS9AJwLp7+xo5Okq6Yf0Z/foEuRu24HSjFJgGuiBNKNwhBM17EK1q6piHkbslotPPKqFtg0CGemHPevgCx7N6V+z3W7HyQjPtiBtl89Oh0omt6XjausDd4zc48YAwydmgL/Qi8gAsy6X70IdrsOA3KFHrvVGov6waFuziNT2yJ11vtX3iGXNkXE99FTTuCe/igqH7FIWXIhXlfem29BOd9wqiciKsGysDP263z+aYJWt8tEKG3sjupUjKu6xPiOU/iz1l4Uk3is9TKXNruoIggO02Z0mQnxiy8u9ZLDAREMNbaEtBnyoC/dpENTU6Ga9CKvi1bRYqGl/bpHaLSXT5P5b5HIMZkh3YEFxI9XRpbNVZ98ur8yIuZy7OutpXPxZ2mEtF6ur3XIBPKqX2icQtGiE/03CO5pZE/9lYxWPQddwx0eN83noyk3lNwoeMpoI/n4kVhhJ7TpJtixOGh9IxyrdWmYwiLZ/MKThlcCs00MQWta1r+yJ9fTM5p4v4d7Mb5bulOgFx9/xjGLkjrFPTG0inZJuw2gC8f30rGsjhasP4g/+mwsKdNnSPxVUakb4ttokVYB7bk3xi5+G+8RqH4QbEJvBNDE+gMRiIPRRfMpAYYG+CbQOvvOhHlN92Pnxflks4r+hX8E9niAClo3PcPu+AgaQrF5LJd/xEQMICni1eb013b8V8isJjE7cAiBRAlc/B81dZuO52rb6vI9PyQ9Wk31WjTMbVYHmWRq3+5n7NEcVRrY5OkI0jwhuIObBMNQCG033AABAAElEQVR75zLe4f8TtqSJIjbKPjauCEdwp7bVgJUwEBNBghcLBth5I/2qZznBYTRTvmw3t+yVDCcI+hhIAfMSylBSi0WwEWI93V+ludoetzHcYvPTjPEw1B0CT9wuy/wE+Q1jqWAQEOd6DVnEAady6qEOI9ltJxPv5ihBIVvyr2TdxUkXzq54hmxpMWE8Jx7iwuf1+rP+xt8eHaDnL6fWcuu7WAGcSyg1z12HPHfiP7iWCtbRtd6d2EiT2/oSvmWVsujX6hX5p7BmMM8YdqYm27o5zbEaD6mNIigKwM1YNRjSzrbcuvadltQSKHAsM587hjcL5YW0f86EsQi6dKJcJIevOM7QkKIkPimEbwb4m8eILC7yciTJsIOKPTDMT++85DpzBiB84kKjg5W6y3Ccbant33Shti9V364pLbmG+1rXST9FIhwjw5evzntO52OvEYKfx6Tmf64/fiMcytVnpZ+/RICHl95suKSouL/9mZ4b4be+d4e3wKyc1moW2nUXIai/d4wymk4PfLvWwr9GG2FRw2rf89E7gCiDzi1NvtaFtolon27BFbL0xGmEg2XooXANvJuE71dxsxgpHRGTRVKvtIiAWRF4zUzgqT9TgOLjGvCDb8ohNAC3BZOLxWIG3+yh/MvY+8EzlZCaQjyRu8A6CzbzqV30k4SPkPYZz0Zv+o5VglVveQ4IV9oY1I8KinIJhbYFloB+lz+9j2DrLTHdIRHniEASxQfuuDhqEWhqVy4nfUK6mwk98Zqu6wfRik7VCbTcSsN0vcNweQArBjkNJrv/LD3R5Z+ZTADYPVt+4bazvE7tPPCVvUTvwoVNnVgKwgSpB3B2Fcf7+R+qA9AaOpysfzC5hGTqEmfRuXUok+DWZOQuBnE3J7mGJqHr794pqmox3ce8W6yMo0ylkVLNfg+0CNL+GEjFmah8LnNdU6DWy/UW0Q78liolfQ/y/rQjEKnI7dGF515DQ9QQWS8Ny19j9Z5Ul1opFoEZ6f7DU0l7AmfAnOsJ9Cm5EtJMxRB7uN0zeQ9jbJMH5qqyMj1jiBSPyldIxEth3XDG1nOZmHL09VkPWypLuc73FLEO/kxnwm37a345ONhnNg8A4pd3EIyUxatOFpFGWGDgJrylBIrT1F+t4KmD0YVjvqf5V3HcUupki5DsUQvhenyVudp9vEyu/+uFDivaVRrOV/spvaDumKIP4vHZMUFInwXE3fZ8RTcoXsPXzMhWeH70/7DywJzxZ8NEcKgRxw8v5dNNlKc9OJKecz2T1z9ddFVL9gEqjSyKppvkX1+A+f9musSFg+iBTgGc+T1DMJ2C6qNLeMNtzMwCHfISMzMbKOXD7NheL6M18lc6AmJnV1zOVeci7u4r07zX/OtlvLOUKvKVESovedvFvpfSnvCPunGrou8aY8T8gYGSuPwBXkYtH+RkebwkFaMYHSkfVhSsJ41/h75msrJtm8XApqf7g9HQeRnOFf2AGV7wtN6HwSwwxKWC/xGJl000G7PWa0WmE2DSaol3kn3JJ7sCMHvY5mr1VA8fKjlI9xVUpkcj9NVUQ5Okt6FngMBnLK6wlVWmW7/Fd4Q2XMeKQ8rpUSvrw9/O+qHgqD6uF4DZ0C42mC4tkeYd0hYZgpQPdtxEsBm6ucGhHNeDHAfkjlv9WBLJVfQ7dlz9kYVTqh5W+5UrvBVujNpSOb6dXDrlTfthdpfEAFLe/RjV8UBfU8+jXl0NajM31yejSyWWYe4I1yNSNDME+3/QFZYdWP+JOI8QIW7zn1ugNinpIQM1zINSJa33iqfaRo9n6Nqnx9+UaMK497+BselrrxeGua6ak6IxB/KFysAPdmCNzwMd5typGPhnoJlEs9QpxUQnWlkBxV0/6bHitbJTmudZii8NtAUB5wPdcd8i083AfQpLj+KPHbwI3TUYF4AWWizhL7Pcc4LsZ0RehxmfKUOVEvin7nf4YMNOjYHNn8UiWkibH/yaSceTq9zzqHb6fmTZVMmEcUVdh2jCEi/Q+qSvehVcyv+ZgImZeE+pqnh+sZj78Z1UA8KArNWsjnOMSpLz2fBXkha5u2d6gfjvg8M2qNV1vdaK4TghnVy9vZF8gDQuF3y5iiKqvvUnjf89hm+aVgVxtfF/bFH6Ao0NppWk2fhyy+6tasloAkrNxyNZ+jAb51MBqxlE8AQS/rvPh/UvkshE/7nn3+ubqrkkfdLmlMZgDwg4bQRst+iZXxm0LUDa/lcGBfHd4OSu7xdGZPIDdlEPGJGQJu3jIo3u+6HSE6DffVt754jfSbC4Sf/m0Gd0wTf8fTTVgi9z+lNi0VrXaQPf4w1R2PUjvhn84rMSGy7cZGzO31eCD6wG4168UGt55FpXPeHGx2Ko8pUZMqa64+dUoHVQSXpAR9PIPigbyEPO/XQUfqct8fOWl0IBYBHwKxIuP+7KOjuf+SPmIQvjUuFSUL0OX4YZgFwluz4sKCLtnx7k9E7l4Rstud7cuf3mZzVSSL3qa6skgynrTK5ZNHnBtwuh5fXUXA21Aq8WyccIPZMAKbhdQlir6OIGERwpmu+Vhmi2yU6td8pfeET7Q2SGa7nalcbI2R6aT2B3yWazN4mZjEnjEUMnrTFLRdrIhXSKCw7UffFycEPK/CZjW322IiHsLF1U3QqKdZcZ0oWunNQJZfpO5XRIXcppsoAbbVehaAry8XBeX/0v79BnCTQPOyHtKvQAZVTx42pW3Xq4+S2g4BPW/MC3u5lpjWuy8JLIM7q23+efhXTitbcpVDL3SUmSR7/ny9c3FdecYwiytTyDCv5eElSl9DwohapZNsFna+hj5uyUVQxozPT76G/aynqADuyQHV97GvEhQmDBf4J8OGpDLRfjLi2VPJaYn4Gdx1MRf5ktLQTcrp6gvQj0N/5BeIz6x13vF8CGK5Ug/B2QwEs6Ku4ZE2ZfZ54tQQDSyGAZ+x4QovdirqtnUHsb00Om66c/3PRXwgCHNYeKnLaNpHuBGWdiFUb7+mIij1XiLDlweDDGmYriqCdAe7TftAVKygXmTLdHTy2EFi4ffpZlTL/Dw8OLfkh3c6U2vTJCZ1bh8ZlK2FjSDUxJIJ/RqSJ9cptdM4wjd7mUlqhXNg5dJKtZLnIygHURrKqZPuIZkE7QiYjMRGm0MTNy0YnBkbPCueCdp65UiEZZMtcx+4S0bf/xLRvQ8Yk/Mx4bfzyFtRdhiftDphZ3QCWXCEK3I7lKGdpQWDXVucyGbddEk3zVRFV8162AOt9AMaGZUhkyQ8zhy5Lx+A+my8QWr+dT3+HdKnrTtCy37TWNHq3moYZj4zkRN0aO1eTrjeuW86LvVUVtgDH3GpU4SjFdl5lUrqh2PCk7XvhbjZGEIf7UyvOHf/gBjAOX5g9Egj3ipVLUF9pxtCyHjKF/dJUH3nxoo9MwDeRJz71lD/MlMYu+k5JzZH8lEhv+P3e2IVnr8d9AqhE6CtciWfBOs9IVtHyfFinkLP9OfjgzUuwlzVfybGdYseRfE6Bi3nyGuVkRaw6jt0N9o8jr5gfuF8Y+XfjXwQ6PNciY00DX4ft2klDFqatIHcPOfkkGHbChjaNK8jqwzBKFvoIyJy4GVqaZqLGWthezEi3y5erJyXpY31A6f+aglhMsmmDc73LfODuAEdPXTg0fY64y1wHaLHLMdqr9YqXTdMNlm7zkwggd8SmpWHqhUzjpFcPbODrNUSIRqyjU6vooRjyVAkaCpTSkqELHE5QMbzkpWzAtVlcTRkyeL3yMEC7M0USW3fD4wwJski7qZseqUKrmjOyKW3BZTEP5xq52YbDiAizHWjckcKxOlWDDEQxd0oJ+yEyDcTmvUcFX06x+iZBo9fT2I5TVJrVyFOhSqjk/tnV72sNTUDK4js0Ym2bg5ciAfcwSlPvsxjDJHR7jtX8ECvGxKFBWyz+iaw3NZSsZ3+bQbLBMDdAnmM2nDkaPhekJI9h2R6fhycnvM0pfOWIqkmW+EMRTdeWqrMrajgz/4Vq9DADTWc8mqqflxIeSktpyVQ64Bgc/t5utejQbMS+WojH9d9qLV+gtV/cBxJMGhGi2B+iFT2IvMyWyLX12XIfgFqzlPxnp5zIuAHrHvcqhmAW3+yuIos90Ley68Me+w2U/PKNg/vCW8eKrTjK+fyub9zj0dh3VNq1tdLDHccdHuuzroMB8CsfgVyVXdYqUWC30BsRn+JGHW52QUh3t7GzvZBLWHUEk/H0TnxnxSHDKBPdbExmhnqBQImKDkTM91dvlf/Fu00kI9s6mE6SaLiwsMm0258xk4r9fskiIfNSA8GqcuVhGexTwzWsU4FE7EhvR7R3pMNPwxYp+4l/8TCQ1n7V9kn5yVopPn745883SwUWL6HqYnB8t+axkNFsrRHEfdSDACSYmVKGbJJYrVoJ7z2wZ+h2YPdKnLm7KSFcUpf1GDDIR1DK/f+TXxXY2+B6mZt02l/jcA4mXl/gvnxt36twPhm85uU1BJzFKFGB8zjBi78G/gR8Sq2F24/L6yg/T/IhZd1bpG7mNb+u1s5LI0jOuNPXlpoRacoq4quERaxsSwtqbS6qYo91fF7sDZyqFi5n/XtbuSw0rOCSkGHu016HKzEz2l5CMyZJTOZh+2NbH+UEC5YKO2bjgsyDav9dEu3cC534pmBMDuuvq8JgPA6r7/KGHyRPDF/8D74PTC0hrd6rGddtsVcpvP19KO28tUkjadkLoc8OLa5Bl/hXVrYD8T37tpNtt4VSb6w/e3N4ObfA1+uzd/NgC/oN4RgheGhpX/7aVQ+Pf3gODzbuwQvLQ4Vz5mPuVrs+zEWDzltuwxCe7g+wsxV8AGgILnvKzWmrzg5l1AkZTi+u4IHLAiPfN4xIoht9GH0O5fNngAajZqNMvOXu3SAmmS/gheAO8JCx9vfwJPDm6Lw0LxO3ZqnBKFgETfWLmr0QUt07jIj2cEHUQBq8iC6VbzNfsQvRjH+mjI5ADb/WzuxOmFRouXIrMmjA5t+4IYHZ5FWfPtVb+sZ2/Z9X5HmPiaDq6VrNa5IE5REwmTOZz/vAGlw8NWww0jxDsPEkPurMR+HtJvaAVYYj1dBjaxXI4obTXGyEL+tcyilEO0q1kJtfUIL7DcutrwaQHSvIpZ0TOVmGsQCk77rkcpMAMEbt5K2CPjIh3lDE6MSXh/G8rX9jNuNcYuXyR2SidIs753WhbDxzxcp8FiKUVsPyo3u2hCDD3nCwrGX1WoUgNKEpkl0u0ksJO8Gw3+91wsDR4yjUmSanAy7Xcqm37xIMj7QiR344gbbGPoHfH6IzwcvnPTxGw0yNX+Ekf/Iki6CGtOVEAZiQvlhGZRxv/1yC/gUg9d+6R3p1M9oqjNrrF7M6KJS4jRAHy3n/ApIwwrGjhHmsNX1/x9yqz2DBYqZBw0DkGq1cRBMHkd5ypHusFeTRpUPmY56t+Lc8iv/WHyjy8FyHm2GsjXZ0UeGcHq7XUq0fjiNa/eIsB0vTibETWuTV7ATrbDN0zJIASTBWoAdfzwhW5OkLYJXinU2r08uEOfKuHi4Xv0k/lnkmvF2OLtjSj4h6kGzLh0kpXOrJtsJUUgNJS+fzte2/zJAq8DM6rjTZK6i93VjQ0OpMjjboxoBAq6SIRyZdxLhWi8ZcQqUrWBIOS5A04X2Hi2lWfZZq8jHSIluGLKDLqe+jMXYDDoQ7+b5/z7oHlNf4AMDrfW78PMxcbwAB756cmvcfE+cJSf3FhHJt6gHibbH/6DIkUnalf9peyRMeE1/EFB+Bhs7R6HzrQRQD1dkb4mW/rLsNPEjzK4JKP1EssZXkmYRByaGG1Vg9FmhOWSlJr7TBhXK8FdJAN57byNVVIwuRqW5kD//AxcLvjxcYHkUdW1BoJVxQrJUpBtW3Zwq9CIAnyI6ZtjK34N6RXF+HeiUdo7WokCIwMKy8gxDOnvdilNwd+rp3BRJa7QPqNErVPR41EM8NPUAuYaVjBU+qtwb6xLJFdiHSSN9qp2YkqHW6AOVT9qpy68mNbfKMsEpCMAWltB7Yi88hmeHZSgCPZEssFlC63qEgLCQK4TwhsBrUso+14OuSciuWnCZyEEOmPlG+NdPc7mNw6HdVn9GZ/IN01A8900RkdDR4VSYnokYsqWcywhwz/M6ozp2It3sZunoe5zFjbvV5SfiVw+R6ad6C6yuPWJYLdD6oWHejkCvWELjjgamBJaMZDz3OGghBrAoeVtLhnxfEU6rrSXuMm7adj/j7/Q+1CnUaMkDST3+RmpT/yJo+f32gAUOlv7JhNUniHpSJn8/NdgYavpRawGT6kEHS0wvDjQZanpYXU/R4fLu2g+HRqjheLyGmLxKn3iFFpnV8z1gSWa1Dn/Ob0an/gHwE5stRv0VgdYLFPFY29/u92N4hBd4X7wRnPQ6G9O0FzVKdzmF2NyhyC3CaYVjdSBTTpcgTpFpDlYh8LThWGpVR6QybmhQytokmp4iw1FbYvp/qYOG9ZIuZZkQ+IEWFdit0Tmmzp8lR0U8NHFiQJBRu4hO/POXqDpZASKDLo45+hXzzD6AN+unNcRs8zO1WE2z7oru+idQW5ot/GJpSIHl+Ch88myxAzNVaiKn+VXvOdQT7ZI6u2vxk+4OA/UGXw37Ss4ytskTlQh+ZQdcUWCiGy8jHRf9rwBVVq65eCaSGQR3F3j/gfY/IhmUqwCbZ5tWvV2CLvBH11kUAzfFuQjV4Pohts+ivsIxRCUwfD+kUwqihpkWQeHLK5mEdirHMJutWqDivwn19y586kH3zXqRqklAgqx9BgGb/ASXV7LoBVGnfn+2p7ZWi+gyotLmar5cgl9K8jZDFg+GxRIosv5isnJYqGzWYO635sVL7KPIdeqaOSFZZGYrdr+KwHSU8JqjMhPAiZ66Thxu+oboGa4xQb2liEGYDRwXKdlU4ov/hDFFTeidxcv9+4Q/CE2z+vjOCYbX2bj/ZadCrVGYCMY4e0c08k9+X3KFWL1ztshH6hBirAdvRLivRdQ1f8RAzIs0F0VXTMfmn3dfaar6l32wggo1TFYmv1R+lgE8T9uwPUEV7bV0BhQVr+rKU2X25wGOKUAkOMs1syjy5Jq7bMrpnnXBAiLHgJdT6xzmf2m99TMfpL0c+vqldDzZdVs/+59anxooX9oV8y7JLlHFwQWu67bkXxfzbkJQyGQbFEjUTu9YSCbn06s15SAPxqvBfWoPVAjwnu/IbLMliHBsfImTdt23NY7w32IYuABhsGxEpYciFAwj2En1M3lhT2qcQJ73guqHQcrXO0NAACzrxEYGGg8ZMzIP2juAL8/Bi6Gvge3sfCAb5myXeYs2Kr4V/lVJ0vMPRvDOrC6qmmwN3Thh8psBeyD5SZY0uySVF7qcvSs6eZp/sCFIGKzz1Ld3fRoLc5xfP/UXUWcF4V398fFBElFCSVFlQEpEQFBFZAuhEQEWlBurs7lu7cpTula1e6W7q7kW7meX/O/fL7v57Z/d47cebM3Htnzpw558zMV1uwoDsnGI2OuL/gGVeBIwW6JWZBJOgPhlnOttGVVGlbNwvqMokgjVb0FEh7VoV+8W9GaMY5upmfN2UhnrtaYRKBiemb8SyDP7qUA/n8+lGjQcopCVq+Bh7llumP4P96aVFfKQZHEqTSonjsbTRBxpCqg7DM+sgPHc8MuYoeIzCXDM1A6vCtlUHVOhRJjvkfqxC/786zAE85pR8trYLrjpW/vsai0MhvxqZJpNxPvNMnQkoT2ORiTl3IamlvHSJyzZ0q66pLA4wTqtDPRm31hC1d/cnk/o59XuM0DAyylY9jAl/7CWcqKCdZB9nOYfBXDRTc997HJSM1KqPeer5RWH8yGypjn0mfK94ZwaOmQnQ8+lmwdIJIWq/lE5fVEeHhCGibuZNwFt/sCr1m482FN769Fd9eI/lZZtqaJfnuQQ4B5eIHFVnjnj+BW4an+RZdY6MnApgGfXaHPrGpaNNcxh59famy8iM9oqd2i6KA6SU0LNj/zAArdnDTA1Un4bhsgsDtpm2dhqeasmf4eL13ac/gG4WYG2IbnQ//gbkBmhr49RQ3Ic9Ab1+pMLJeaHkVPHDS0L1fVdXQYRtqBNF7PSogJXFBD0vHvOpznyAbwd2KvBbRQVJGwjLYYA4tL036gPFs+Gu7DvNlVXOIlCbwr35qsm2+2U53cJOwyvVl2Xk5IB/ipyiyl7Z4d6FPD0X47pCST/yoGPifGn7/qsenbF3CZpRE7S+qIv2s4/vKIVnrOmofnMhF/83Ed/xc4hOehvC+m/iIETD3Z2+WqmMu51ozGVTm5lZdSNIAlUtUdqZkDbW8v0WwI4oeBgrzyB+otruwhpQ6k1UaRl8QWll/TIM9T4+okoA7PWWYYUH87M6wFM0Cc/jqpWHKQPQtJe9p3k7ZgzmRi1AtVC46EIveZdfAr9Ui89mv+UR9LCdCUVuaaDVvQoXKEtecuyHYqGsW0999QTc7QwYXs6gki0Juaz/xqQF+xNPCEGLe7x6PQBoGyeQgXEb3wLWW6SRZNLtXoSYyUCGbST8/HVXq6l8J/g1rMKWX4vlbIMCMfJ1VJtwMZp9DITB+wkYJx0ltzeXDoM5kWiaix//YeCGrCB3OU8MEVQKeqmW4uKR0j4GKcKnfU5j9r87A/w2GqyIj01rx/b7NN1aNgx2JuVxdcOrlbNWuRHVV7hL17CrBIBNyy9xz7S28+hSz8tp0XiCHYIF+V6BRY/3DSrbKi0EwoWw027v3ylFe8Xe6wufce0eTwPZXO9wC1+bC/viQh/7mnZQq64FMAfFMCgx/0ccrRPl2Fd256ycnVmE5FQO74D9opyC/sn8yfs00wVw+7RJkkbN0CxxQ1wIhhNvNPo9pfPbiGh137PVZ+vLCTBdm5fz5xV5JmLWK2qiShGOqAs8R7ExpBf5nxvzYlmpPsUtctbZI+cPtZXxb66aBQUAP+d/7pEWPSFqPAJOuTXLZnEAMq+pv5Eieh4Jb9RjNRpDfPz1pnrxco+H2VRO0CB8KdsMHbth5hWNeIfQ7SgRu7vwl9AFKjtDluWSacltBoAhtNIZiw9oDvmuxiVJ8X93mBXYTvyvuHBcTWqeaPfID3hiuIg3fcMCs7dDa8K9pHqsNbrddGwVyRua2MCn9LIpWPN/lzPwVvWqy39HOd6kZ2hjENoAWWQtQfvnJa3zglwlfcDYsdj8qjbhETIfeOtc1PlMzwTbdyxzv+nYDgTXNLfJe2UeFACdS4T1+TEeCkdpSbyIdMxkZH9gbpO1aPpCvCpZD91c+0l9c8wk/a11/gPQ2V6+ynQNykTCS3rVkvvvsEKBuqpwpZ9GYV4rhcz8LbNx+9q9WhyReGWBvCtFcSws3M6feV/QB8aXjTMKvnir/RFWcIw6I7yvxVh4CbBKRHYamsF958rEbzwbmRwtvcefJtwG+r+CFJsiAP7MH2aWtH/WQt8BbxJ+EHJGZoZmbSmpFSP8PezT9/duOFoecP43FUcxQkUL+F1g28wpGBn8sFKxLilyOi7rutwL/xafo7lJCQ6dtk9kaoYfi8f8k9mo/tZ9n+JAEw8+TAfL22uywz4J9wRklfaZWfqiMKjBMKG+U4Kmn26J8rUPmj+Eqoc7AUolMxx9nNbGbd3RdOYRx/KkyqvGL5Mw151oCIlhV3S2+8LMZ/ciUeEGOoxNJvGI5lIcO00HqZ1VvqS2s9s1nwYyTRGfISfwcvK9Ehv26w1MzcNMMWCzPHR3iKCOJIh0KIgAzCrFImxDjxOy6TPt4/qtaye1CVkpPN/NgS3w3g9HzjKQOtAGbVMQtg05u+RvVCjcF6c5WdDjSu2wHUo9nnAHK7Om+SWqQMoUuTkIYBsGxuFNZQelRECMPNGmXFP32cBj3vdtmDVx7WgEJDMoNFcA9MxkXO/o93pKCmbfS87aN4GrFqfb4o0OI8cfibU45SJywBIM2E/DczyoQ2rFnfdRGXn9NvzF85BL/YpZvoWaNUPM05OgwAudMnZRJP9ik+Tp/JKgxXM2mwk8+tkUXjZXK51q3WQMrcxB9AaoLmZqKpmCiVjl7nQ3iHj1IVMSF76IdIplEZHwkm+TNN3zffQWskHmHGI32aFLzpeahbONOcStPnvd7lvm8fDFER2eg6X39znot505XofxCt9Ss0XiDwLvXDkV+UVx0F0crndNAHpfm0WBM43eS6qQ6tlpfE4oCs3StBMxTIazuqs2dmFtZYKpK/4TUwd27OMDkEy/aotYF5qqYuuCnPYKxgL5F7IzfwHPYf7IWWXQeVWJvcm4f1Q52Tipu5PyYitLvhC/9h8zgEsAlA3lJr3VoCi0CWu4iaUISSUHGAvBmyiTK+kpg3IVjUyjRTqfsK9CR/FKfNTPc90Mnlb9j8y3TkLWepp1HpPFadvEb0Qpl+e2kqDmltLpo4UTn1FTsfOc1/fw8k2vk592l15qtfbAU6CNs3tU+KkDAl+7agiyXLTuDZD48yCdUxwrwsBJeu0qPqvCma9orl8lsfwPWRd0wlNPuHJ8nka8/MfMENxdNbyeePsz9ABMFMdmjwr8jJEchtgHU9ySfqeWypz4UILNnsk3XSID5q2mwumRwu67J5HGAAnfjsrnAEKGRSxLcMHu6tpjC8kBfx7xVQgQgTWcrV1f/aztufIyLBK8tMzEivo9so4LEtJ/oMgQBmRBC3YnAOF93KgRr4thOVRr7GDxAPEHYc+koLuaPckstkm92Gw8N51yobhsHx/YujlIb+0pVlFEJl2yuH4gcK5Lmx/UcQbQ7yX7DpRUuz080Rzz+IyizGoie/LNMXGhjf7seLYfsVHpeLpI54eVnzg3j/E6VFEyZuMmmLn6QpjkA60KK+29oIqqNq1Gj2a8BAqubku2wOASFloX5hMVdaBx7PuD5Nfcp7m58WpUCuoSySNzmyt91wzTCpYccB8VLt9Nf4t+2bEYpvLyv4xM0Ife/httSVz913HJCaaXpKzdNQAx8rxNodgaX09amyj166HVnVF2dXsL8swgl7QsIkQzGahxUfp8njovM6OfNjgR88KfBEWKCgMcW5mVJ0vP0eJYgB0L+Q6FJoZbDMbuN+Am4wKA0zcxGmY//EBJoQ9P5m0rz3aT5u2abeRtj1zaQd4BjjwwwH9cTQD6P0GAv9zFCcZk0WgF2NFw6F/4XY0nV1U/9x6q8qlXFfybSZrpd19Gs+iR9GGSaieYnZa2ZkDLDT6UcEg/4VOOR4rM/CQR0LghYtLGLhNtu60KMkrZ/ZmBaXlpWjymxjmotFyZ7iY+Dj+9crrWoOhFhTd9kiVw6Avgc2F0oKyu88CfuHPU1WazrBlcNligHWChRGd61ReZ6lS7K919osVaQXRoCE6+iBjOKlHWJ5QlYX7wjhIEsyt2PYYYogUwhLg5M+BybRaQRBPNCfsrdPqYvr2aLv6GNkr5k6h5QqplJjU/AAKCrGBrcSYZZFmxu/UWBQcX9sPde+aQL6lztsdJXQNrdpAVkxioOeIrjMhLCrqAz2nfCJlxjVkl7U/Xo05N9Kb6TBrqFVmEhPdBiKqIzmi4NRtysaSnIPdl9arK6/bIVsqqGFjsTuOXSQ9D62DO52WRtIJlAza9jPPOpAi4iyKIu36SlHpP/6Y+DrXC2MZqoNEUuOiXAhQLIKd9o5im9bW9hFXZHUa7GTOOyjyuT9LLcIBRyRUx2OV0f6DHqOZS0slA3O1uaBu6RFSyjVmWmaalUmZdy/ydQieODp2fGkjCV7BY78Z6MVl/t30aw/XwNY81Tw/sq3J2s0ZBR1QVMtBe8Z33TloabqThzpSba1D8X0+62J82kYn5u1CNxetErqaZmO9qtDb4zWOC5MTFdnIYNPw3NPTqTWztStXTxFjWZyF5ifLDulRSHK1KHC3LVNgfW4em1Wbmm+udPj+shxLsrAneFDx2S7U4MxSWXcb0LZ0TiUZBBVRYcI4IEBx/WE/vBm8HNJaw4d+6Cq1/a6Wnf1eMyN0iodF/oWvDtd7ibJ8Vs2LvgQskmDNngG0qSwTq5Yt3QbGk15RlZk61AysTJGGAgtQaaaym9z6onoV22d+p31UkOQz6OKFwjn72GmfspMKAwRBpIXs49bi5isM+HvKWr5mCVumKnxXh/A3tbEVIdQBnaf1J5+BEMTm7s6qM+VOmKxo1JYDTOV2541rghiwzPrLn8CvO3wQ4WyqzteYTHyOkXWnDbzx8YHZ5cTRexl+lA3siiZKwfU0hlwirz4u6bgoy5dEpxiqwtc3F41ApWId8wt07zMIO1x2hLLoI/sctUK3ESK5jLh+ZRCR/62k0qC624D7GQ/tM8eq1ZCRC7sbuugf+vWycI8O5vtOGpF+sD51DSqgBCL9Cm6HojDwIxfpCzo7LxlvQZzV2TBIMwgdLTrBx8U5UPmJ0COc7GXxLMkGi5srFcc7JhKPZ9Q9fqyK9uVtGP1UBuMk7AP+91J45LJITbSyYNtN6NbG6zPZVL3wg5pn74VouNSu9vqh8vgyDAHBFhBuBVfS8VCdzeh3C/zMLSm9hmdTSx323wFz6qYvPXPARx1U0Ibw8jDBYnMwo2OOASVEkSmNF+QnId33BVu+lLJNfZQOv3lQSMh6zquynCfXZNs0F/qTUUvP1we3ghhf4yBFj/FRius1WOHUgUCGzV8TAi3iSo4+YXKdr907KqKwN3YHugj1jElP1tNTe79SkRSBg0cWkA0eJSZqnrWYqQlARG8OAy9HEe26aH4IhSilS9msXCow3PZRXRPDbfjTEDbSqHAqKraKuH0ms04XjPG6KNymlmDqrZxiBITB3JFNLwQKRH+/cNSjZDPjym0UHles3rtkCz7uNZXYCti4YHI0Aj/o5gbRO5rEA2Qu7p/07vGkD9GCfLMvkUu2e7Af7OuS9iNXHrgb8SbFeo8kJEUAJ3XI5PYAEeAxs8i8beTLUqFR3/gdZmYKOS/Jr7t5NPnUhcJyt6Vmyi5TNE73juj4gGvcTEgOHPJm0gV/PXcmg1s0dkn9tdvU0LZOim3F8S7zveaQSPQv8PnJonI1wThtgUg6ncDB65Yj5klFkYf/TiXNUBApnMUIlbqUsT9HRMMWe6m7AHKvx/7uaz6/owf9va36ar3Sn1MQbv5McSqAK0tp+ecNwK3uOJeRX7adKDfEYB5eKdMiZ+w9KTK6LAuYlrsVJiFTxyIgkBjhf0Ud8mDWGsd/l6X1o9GcI20j9l2HQUFa+yBC63WRJ9HK2HMQSBxxK1fpXBpH2kGDErnemh+ovBNgw8Bwllx8ggLaZF4ya3XaPiAlxc4X+XuG6YQ0+2lSuDvmInTUl0Dvf4rF4ARZAcoSz+QlPbpoETE1ME444W0wokcCYvBz6r9edkRF6kQU2DtnYQBvYGIhGuswspbq0ydqu91aTcvKiGHxckYsGkvRCqpfhU7l7P8kbMUj+N/agZBKtt9QHrlIsfK2qpVg0ud0TJgl2KuRfPdFVmSwjdtH6NynUH2n3U260nESfYEN+CJ8XJoRjAnSX25+3uj+pBKpnaxSDxPrPtXqBIqTy0AOSqeooD6XVFsdnNcNHqXCsSwynwK+6Bhn3+SBdxMxyFpGC20gs1sjtWXxLxdqNe1oNVhW1jEBbeARFrnz/DMrZdT5NFyPAU4E1kl9vJeCi57s/Uicl37a4cUghj/7o/8zHVxrmLxhrEUmAQG/BiY75fhe835EJBGZpoz2Lww77kO1ihcehDg+y893/F042ZrwhcYJUGgodHQRKSjaYvV+mLtRIBloFHCb4iaV3/kNoC7CnKLVDWLhDXYn20vxbuD+zRV6/TtlyaFtMCILsHjhxb2b2+GtU5K66W6vmEU8CVIVWi/TbZWJWUd7HQcNSERn4RKz1UIF0PXrM0bitM9jnAzahlFjBafHHGx6itiUTsgrSukReEy69fuZar7OVtcXp3RdGmTHCzW5GMd+7hCKhex4EmSXmyWY/eVUn24/Wn4LVlkA4jtEHjDtIU4IHlK6XvxIqhZnntfq7o8Uilla9pySp5dADo6ALJgTwtcByzs7ZVN2r/MD+4SpICOVxzSIrrIiyGqcp5WBlIEedN+O/D/bZLGHZZCzxqj0PxPDu1C8n8sTLUNJOsHPrQq0BM6Na/pMndb8+FxQa4HOoXT9gVg+ycdK1UsMWCQbkbKEjGskuLzBt7NBER3GcAibm2evEwe+xeoWf2l58UWmi0VDU9C714KI8aU2v/+mEzRpZGtmxodm/t8tLHOM46v8LxkympQJ8gaITSUBPVWEINiB8us5EHqkQNGxDvwittXyOIy/zy+zFn3tbAcrFgmym9wGSxDWOnhZmI5NO0lJ7OXhPhQAhGWRAVV+yyu1LfIoVRcgBNCVQ2v5rB0vDsTIjq+rh54/mf6wqG/VwPBSA0H9o7bOSbHkS0oxJT/OPlOyYyrxumkRIDQ/bLrn9Jubzr5s5imsks2HQNs8cFdeaa1j+MRYFPNQ8nqAHPxbeDf2xTHMtdUBMpMxhqrEJp4BT4xKhYEyFKJ/7Ft+g/O5CbCrbBVs1ZdDaGv9Xz8oApHAnkWzWE/XQSxkOKZ5Dqu34tWH56ZP5yp1fsPfEzatraJfyJW7H1Z/pYc3+4I1FRvuh/iEyFR+nmZmAM/nfgZ7Y4rUKV/C9uufs67uMcSA9hngdYGaA38OOkZQWTmIHE7/g0YdQMfS8Y+X5i2pYQdQFREp1b7oZLQ+tLF+xLqc7SrE6QgLW3cGFwhNjtlj/6L4aNpot57xiqmmCxpHsB2TGgrn50z8BbDhaEXJ343WNCpMA7tE3ahNzH9EJmevRJDvKpUN3eo4qZFj81V/9gSkGXlrDJA9ceJYaNlHpzhc8pzUxjBSQv2CFUmXC9+spjNcXDIYG6aMF/RE3PQcM4mNtkDACHobyAZSuLHeis3uSA4lg2Wv/rWb7LKkCPaOXbpOZQ0PHu6lzGPS38OKMmi5d3rB3Gk2hfnLcHdwq/Ul+zUJcvR2gWPBxR11BM226F2uHVFkWIO+Dgtxd0j6GcGywofpuhkbbIUJsY3G7qXdGRSMmsxFoP2DwVkJDqATgGW+EAfRRDfVy68BuSdxOzmRw58DNuaU/lh0d5El9YJLm13/6EwZuFhrW5fO93bfhjms0lCEmQ5sbET9Ab5qwb04o0YOZpEqhtWTG6yDqVRwntCqIubjsTZZZJi0nJ95X5o8E3wNENZc7uj94l/pY67JwY/krjrL7l2EcCDcvhZv6tRtjfPa/ywUt/eoibGXTL/9siwaH7ZMGOfzfOYghNbLXZZd/k0TMzpOFid2zqW03GzIZjKhcTVg986xBpsAb6kYxnibq0Q5us4S6uIPvfcC6qIX/WJrTEn3bBHG94MuL7Wwr3graJREia8kiNc16iDgzDuBP3uFyU7yYzcFdjUndXpQ3vJeUNXggCswlxTRAmAII523f/wU7C1Bci7HeURU0Lv2TAZZCdrNziLh2DidT2R3rDf3vaBrNcDUQrAbV3Fsocdus+D6BKYvAWrfsKfRE35B2/YzUwKkGFfOpL/Hb6qSL8qTNctDjWZDos5pZitxSTfaYcJPSA6MnivZd/M1cb9OC6MYqN5F6OmQ8Rt9WFVzVnz4ul8QNBkx6zUvP9Zm7eCByrMH/4SqB+AXagvs3P+D9QkPeOxdMA6e91fhEbBOxDQP8BkcvZpGceFSe+X1NJBAGvEsi4lDFMCyEV9ywkeiVkbmxzwymaVU0DeQ3GQCzYo5Q46WpfcUMaChg2O2DZd84zwMQD0bXxREYH54uI+LM6Tu9NRfAGSodqR1jOMWqS1nBhSTXgtJcVgGGRyGNTIM2vQ3votF35tQ+Y3BX6l8iVLzV/+pa94OOzMZ7H3ugGx97GpLwmxcW/XR2AAzLyoqFV8T4CcdCc6c9cBLX4iXKV337LmPxuC9Ar6ltii74nMwAMGARSGQ83hG4ONABa1g2p5VOS77Qn60H8vFncwgU69xDxzOi03/w1yl66yL/aleugEZr/j98XRNLzwiRlWmrikhhWRLH2qlixHAOqsmJPW6aHTOYw2jpm3VusxoWnhH9r6Htrqlarst6JtvLb6KtNJcKO2lleA44O15ajRs0DyCBqv1fLmOBoTHqGJQhig8XuemwxGa6QMpzSIw2Tz/so+TcXD7aVNi5FFTbOM0T1VqrqZOWXUu84+My0FdlhKAUrrE5b/KhD6hAP/DW9Wy2K6MMWoN/im5l5NVNqIvUnbsytuMr3a4uGS9kNx6TDsNeqOWGqHkbkGX84leMTMaBD5ltK9kUgAMeHAsBC3G7IR0KMXsFOPa7wRpjIFCqu5JL/yxVkUDgLlhUT03Q8Q668ZFzGDNQStdXrckp2Wv7jq4Um6EshmuLb0LyESkciMYhgFjW3KaQpM79tbj+d6CiTWQvGaYWS9P/Ega4hr0ErjdTN+kAEUrkPTiYKysWoBBRKpiFo44x3p+/+D09D3sN5xTA7ASIGCxEHzsd2WIxXkHPEWRkYxxGM714E/TEHgM1l9eDZILlTVd2Rs32dvexQZn34n+kivs6/UBHalWkp80tZvzyjzd12P56XxT8EZnS/KidKoRx6wDAuV1AXsoJSXm4aOejRrP0vrHf33g+w20WJ+yYwHnI5y7q7fOf2qsQNO3bSxciPn36WTvnFbl5XGKQ9iPlXOkfnPj8inHxN2eMGzo2LGfJVUvn/52iDDsmo//06GW023pya+II9hPNDsv8RFB8RHEUCWUFfOEWSZJweZqpunVzPY4vQGeCPlCHec0sNCgr2ZTB/S1E66+UvStMjzT7DX/264UdMJfsLT8CJ3XttdWQCRa6Z/K6eea56muFNHVDDJ7p0C7RSFdZJbD8MfFb8rl0eJJVnfRSomBMChQmjuUp5qapKQPNmajXJ60OO+n6nwT/r2wiEqXhr8BOHJKd8ac3nx2ez4NjL1YfiWUEZw330uhBut1OtPIDP/YThQFXgz2lrR8nLNLMyPONPSd4plblEnwhdLVtxu7oHiZw7BXPQSqBEWawfcy3lueP5LHxOojSM+y5gvVj/c1/TUKocGxVUHlmGKzMk370bho8H3N0kZAYX4LRX05iksN7KHxzR4e5PAk+tPgtc42boA1voiMjbFSB3q5TpeMwN/4rnlUQBFVPooHQY2XXMwoZkx6SfNZNWXSEUwwfzAMl6COwYfS8d3EhHXJjef46IBiKD/ItYW9QQTY3tuKojhoHs88siSwvSuTKeVvpMytbQ9PlTVo4c0btjNh8lHHonCa1cTJUoLZs2kQENaVw3/H7FkIRiys46xss/q3y4f1paGo0tJr31lLI1C+YkOXzk4iL+UrtnpntnuAs/md3Wxz+1LTOca3tuhhg1H5m1tujSdxWwIrFCV3RVyXxmPmNclIhucwQdy4oDfF2oWqfFa5CB+cM72ja/ox2CXA7Rz3gl4NiT/KZ4hfxvBPdOkqy8uUWu80NCCAve4nMDE86zevW5IGzR2k+CGV1TLi8NTdNepexOtg4yf+FvqX+xhrjvmRCOVBo5Ht8whCugK2lU6D2iO/Myl/q8iFDq3gHmOFG3NVEriAqrahFlI4+29dvNsxzCq+29DgN1L6mrfw5mKzB23VDJSvB3IHnzbWUJhqjvVDja79NzASlEAL7M1LuhdV+aqOGyoCKngHA72a+jRXFpKyppLYy0aefk3+BXXjnuy/Spiz9sQzvVqjotAEcDeN6I1rFMgRFrFiEDQJxlwqa850HJ12fLSl0YApmLQWT6uEmmZdYROV3dLyuxYkZKUBUyBRsn1FUknDhHDjXkB75egRZCrk9ld1gWnyEhgJiHRdS/u0oyJP9hYuXkf5KvH4xJnymEUU817XC7RWl89IzGnw5iQTSOeTKv0w39AgUUr300UWGA1Va+vEg8stK58AbBjJpkmhbzsJ6FTcdIwq1PTfQUKQGQBygBQlzFUkSC2N/uSD1OQaHc4x0CGZBBxZLeL7eBSX0QprNOlVABdrHKCcUn47dAFTJHWmab60/xM4CR+lrln5cXU+IMTDC/QjbyTRbCsf3sHNwcI0oP1gi+4O3jXiQs7FyjV6oh3Vc6lRe0CCyDjmnMFDI3IN44rvJa2K5/EEiLaBh+AhEaaxD5+IIoR53XCXIclpVJGRF2kKcPtr8kfq34sboIxTy3gmHwzlq8jP0k8/+ML8oWJRLeGEy/lP7Fazr1GY/gFVnVdikTbjBgxxRcj0WCoo9hdRFUj6ZQ1hAtHOXnTVwIjBEiyIHtb91jE3odgU7w98abUepvP9EvPpi1pzaIlgpbaBdXPQq5q+zUu6wVyTio8D2iDGOQnIu4pkb08TBYlTAg0niL1MRKqn2N4s4Wpd/aUG98NGN/erXo3fOBraj9MI+wX9mHWb7bPHU5ot/ZPJHltboLJ+4ztAlAbw1Kdu6H9f55lJ9+AMUy0nfJ8fhLpSMsauHhFfpjw5iP4aVZ2MIvogvgtdVa5FnmFzR+bgB67qS8ZDE42rX8X8Jy2dqjfb6kZki0dr8JeUSsL610ORH7LcIwSWUoyXDr2q8qajzFlbMEPQUv4UwdQS40SAyD2YGQOQYU5j1lPm+QyrXQBEZ4ULKu99VbAsirlBvs9jTWyqU7aJLZjasLT3tOZniWlYthljDlDM1CIs6gVg1dbssu7gQYG/2G/eJHnd+5N+Cz4gdsQgjIBJPQGbKzRYpFhnO9yISLz5/E0fAGKpatoi0xQN5Sg03VgQndNVNKHFb2b+8D8NiAfN3mFRg647VnR+2VSAxSIWFxvKReX7EwjDpVoOeJ2+P59Bx9lV2OmxqmfHjDuKwXH6Bm4NKlhMHRqXYICbZTvohK6CVoiadv+H4lACdDEncoc+BuGU7HAgZ0cEH0citsGlk3+EhrOAa95y7kQRBVvVv048tcsHWKXxlrxpAAVVBYf2nCH+h4qzG+HoxFTSUynX7+KwO9iBTStw3M9se9gS/iSzQl+R1io/nNnSBu+SXbDhzwz6QdRPbZEUqj5+jPzm61OxHlY2fzESqaIuprkRwi5k1IpeD/XFQbs5AByDcuhLiiKZpQh7FUD1gWkzF+yAg53k/JYnpe1/VfVmb+0Y3DpjvKQvrKoQ2MTzpG1PZCJmdTPaP6k2OJhNx5oSbI6x2xGc9ofp3MStp16IQIck+kbEb8kW1IACbDlu4Bif58+MlvmUvVghgdQi41oeswH/X+aR89HSsN99s/ANCDLheltnyQfbXa613ZcjHN2uxx2/9Pmf6X33GDrndUKsKF/V3vBrs4E6md+9jdM4NO8knO8bowyEzMqohTYnMfqJgb/Pxro5bep/ayHYUYwyffko03xojf0IFr2G5jz5uHXwNYxtnKSQnNJ/6qp0nAo3Xe55LLrGY9QpOCD+smzFGvpEF9yecEhubbCo03+VJA+OFjssaWxRtLTi7qWzTwZ5aAkvEZmXxFmKF0GSiABrfhuZlRMUw72vR2fT4V/a3/9LfL5n+9uIeasaqRQkk/6RIwROIXz0+q4tu+/JOa5R+PCvBinzCJzL4zhYFM+qHKhhGK5V2d6e7ZbCmumj0TPZ0KZVtsMibh9GWjxGDpsMdJwP5zkSghMN5wcUbupxSiuxcVx/unrwO8tDukpAJTGP1Jh71YBJlWSTx4avgDLmh7rRJ7F4sNYl+ceZu05sDZrrgqhr/qHyrnC3zqHwnggD6xycJsF94KNTJid9wVPC6Nm/PGMokNPHQRhrGDcH2011hExGskhmXnRb2/v5orAMJGWh9NFSDvjLO+Vo+MNHJWVauoYBG5ywEtYKSzKC6WAmmWXU8xphMX32OM7C99CElhoQ1ga0rl3eXL42K45BIOb/f4Vmeohc9TjSDD2qDZ0dqLIKT/b+67lJM4rBzItqgfWDmNm7p63yNm2FYTUjfcqNg957YEKJEe+cAmKnk0FDh5kMUnqUq8aqZDS/EgJprmi4xh/JK4gEUT2dLzYUHjByymOi3o/XfyEX+cOZWtFJT5gZv7SrDN2Ec4TB65ij1oGKwAhSQEjsFiqDYaUezXl5QJL1P9wDkfgeC0LAeIrKQeqgqEUIqqRlw5sAY2vyK+MYJ+4lOOG9q3BluKE0Mz4+pTo0NRx/8BBY0IAbG2mG3/62vBfqZMZsUr0mNP/xYG91y9s2bzHLOm/Of+hK9c7SbNqOnnFYrsuqX9eJJ+86kd5lHmeqFg8Kuu4IcmarMEV/tNOd+G8UP7EhYQzEoq9m1LNzZYILTxOE1PFfv/HBGllUWKTiXyoxPJSLGplo/rDGzF5UHMWthPzGp5txDV4ANF61+mr8amaENSpScqpS+JwI2mlNwyHNo1gPuP/o2szuwjTlguk3VyN+OzbfKfFpppz43adecqP6YF7XnidrJguMKll+Zw0QxVc1RR/1r8ON3CCiOds0CGBIfsNJaJjQ5EhWekEUw8pjNUp5iEpCqzEzVJBiVMr5zLFK3SaUirKOLUTGINtx+fBl9RQfrF9/Mwh0yqVi2D/rdu7meqhNjL21LhIzCXGqaBoh5p5ixiNwVNetGpbMB5R4OuHFnUdVk54W+MZJiTmKIT4X+UEmPrqOKK0sRRGz3C6PmIV/6HdGZtge1oaM2fqUlfK0dpLu2v4pmFgKy1f9Hfap/5X9+r0gqOFGQxRyBR0jmd8AiTBzDnLCQlUOQT9eg8zcjqt8Zqp4ot+Il4epdEQxPa6rDXNHUiNWY9oy9PIzrjK702SZidKORDWGF4MEYdIgb/ewEU2e/eF0Iss1nfAaXstXjpRIV9NxMgpOYVWk/fbFIiGkxBhp5H/olGGdoOPbK9mCOmD9n51IoMP2fhf9CInoksf5vpddbGEl1MwVSMASsm7x5X2CfakYAMBWiz3OooLsw+3lrfbcqUPyonnBZBQjlZuDIBmOjLL2Y5k0jDrz5q7qEPz/hz+HWALG6hmCHI+tRoBsxi9sp7WEL5gumd292a1d+UYbNT7uHvjSOQVQwF0UKZUud4B22DUH/6Csd6HpSRzk7Zx8fyg9cnI66VNC9DRm1CJ0pNEXg9vgr9ry8Wk2y23yaa9t3+x+UmEp+Ess9eUhd3wjUPODyftRzjLOIADkPWc2eKUtZky2jKZVCAn/qZUNB05BlMo3vRwxcI0COy/e3wft54rxQukr7EC9YLCw1i/oeLCnxJNmrHR6rAp+cxiKxIO8uyrdbuFcKpDND+JS/VmQhC83Bf+PrlCd16X1LCxQ3C1jNAayHbXtJ+Exj/JQ0Sn5FOaQPkdlqifD187hljY0XiG+VexdcMVCC7YkZJr0ADYGGNmeOoCmd9imBhaUEGYlOM8zxAjLHhAW6rTWio6UXsuQcbuTL/DU04Tvus40LSbB/r3gENHmjaLiMD3k3bh464SXydRUyycdK+8grMiwG6vhwvG2JGedu48/mIHBQAF9dDugwNSYsk/jN6CBOvOh9hut7IWJyrB07C6jYkTa+kI5znaZkjQwrNld0jWSNsbMipPFc5W9pQcLQenXym0+W2/BK8MlavkzGcJAWcV3UtNJYPlCuvvFreK1dB68az8HQIdnfPtSghsv+7vvyZNdD9msn2umaxpQyfIWQdImd1aWmQBL7wUcvVzLUPK9O3XIYa0dPhgwL9s4bgio1ixymrH6gLvpUKh+peUH2NXFDoa75SRsbLP8gS4c/15rYetTqJKeircKUwS71EcZBGv/yRuxgWZf0B4+5U0stCPWMRNYceH6Ro7uBTX6bscLSjeVVRPd3DnjNVu7cNXHfnL62xk2p8TMhUaLfEhmWbXxLl1J9f8XkyrjE0WE0nnKOlmZeaqRG2HFYRgZkFiUIL8Ps4sX75W+OoZ0mquTF4gxf8jMnPb75w65tkukraPImt65ccwtUeEqLagGg+vNxR4S6c/2tMu1QIxj49VYj9MPHCG0RbBF73Y21LHBfXvT57hbDBHLasfCTLyUCzZuMdhQAAQABJREFUVENTtSARGE12lNjlaHtBfM4ep0wf4M6fWkaUyY3NPiUwrQ2KtBQu5CsXxGibY/Qcs2YrNgtb5LnDJzP759rwH0OO323ZGJ3aH9Hsi3J4P7ZpNAGdnTAaK4zpMFGqAR8N2+1vxHzMJ3iOH/IfpXzhX8qIS0xFYxePIaLLXp0KRJJJAtbzbulEHI3EutwSeJtDT/Zss9NlZavhpNThY1gzDRA3TgcYCBbwDkjfSmA/miGZYutqI5cvV8v86twmB0rja89tTtRMxx5nAVjBbzDiYY5cWY2i0Ro2qh5zZr2Pn4kcOi4lcSk7xeIfbWRyz7BlFDLmU1QHx+bx0bCUAr6vgr+7LbT7LIn1hr7ugut19JxBpYo8dFfrSeI/2aXfpQokUh+9bnOntJcLyYbvaDLxtOBTjiPyMR91DhFaNd/1U5QGnZXW5+FD7Yx9An8nkp+F8Aul7/YsDVxFZZiRMJKnWpziCfQ32zBtceUv1IfJr8/u+CrgSsVlZunMGdBVraa2sarZcrHfaDvZVlybBYISoXISblEvAfPAALF4Ot6q4nw3xr6FOjIRFe2Hdn6ElI0DVI0Zor9BjtuCZuXseRMsWMY131nSGskh//J36LntGYRguqDiXc5BpYsC1ocgj2bCQNVUv6NBK8I7ApOQpe2ZQIEayWUhrQBCZ8srUsxWvnMsjP0tAOfE27MlievEwfp5CVmwxUc14uBu1yVRvIGf+h2rVneWe4k3lXRg58wM2wp+ydePyiPA8fpcxcaZibSajrL2R5BrTj3mZTRG/OD8dhBRv2DPQo8SVzx6z01tIWmPgkV3DT/0kr3IlRtpVxqpKzDjdxur21K+FjxEjsXFeICFhhi8uUIeVQ+RAR8pZVff+SD4amzu7lMhOyzMFChzAHUiJiMNmVxqFoS49/Nl6qb4Ri1sdVtFWvvZUmYHM+ox3XB7lxvYkqli5EBevDLsWXO8h+5ql9FtMpraPG7mW7t+Ej6HqdPnvtDU8cK0Gk+rtwKXzW5RBBP4ZHuvsixxAG2b49dpWCa+GWO2BYmw+16JgfEbA4fMkoEK8JbNBS/J9xygLadcasbX0weDlET60Po+gIyBp1cHm63cuDlC8/FRAucUwavuyjmKGJm1JUCJqGoPs4D6AL6ZViCmuojknnR93+eIvQcjJ+Xn9yUX4S/MreF9XnQ4Wmd9Tb/q2N9KKvkCfsOH3/JVXiFi6Y591Qkfq+jUYJ7TtAANeSPPIhxqoPDhymSosWQ7h5//NvD6auNxMWk+TYyN8XlJ+IFUMLlTVZSrJ5fZbh+agTKnqchPfnOuGQN3GnYmt6uBfXrRVrCbuIEMljSUXmgcEAqsoVZ/NhoGUzr6iU+ChZBf1aW5quGjBL/WsSWZnppXtsUGMsNyamDPX3JAXkZk/AWg3oIffrWPz4V0ABYIcDlmnj7iI/iYYhd4GWYbZ5lJB5t7kJ70arNRLNBn9WnsPawjkpY6HsisKW8v/ZOe4ZfQrOCMl7Z/Ac8CH3b72Z5k+tAfJyWR3kFiPvP5PZJdyhF1YlYHP77vdxYKsI/Wxub+SuGm9GADUbT+D2K0eMmvCVbviFt9K7Nszpu1vFoWgQfpUZiuvxKdxxgGzuBVhO83WmLB0Dpyez5fL4vvPlIzkNECEJMfyGefGqKFvujqHgFODk9tAYSmg0FxMzXPnOCGwLOZ9EHmFJ0dg87qgtLcuBKGATX8S4Zb3Bp/oTt8aTzUp1ODQ3GHwVylMyUhHYx3CUPVcjAEP61fWUY5GKl+4QjYUn7aVNOW2ru3HUBI6rBfIItNzU9e26jQ9F+rzF5w2UImpq4LCX1BNHytfz0l+OpTlQ0RztIcb7+zvegCtmCwldnY/i1yuEhgPIKgIjtzv6/ORqiNyLHmIsFhsntYoaP3V5cZvm9wF0DXPaq0Mts2egEO9b5SGnDEkyEyFjcWcg5cSOHp9KZ4hXFIkk7Ii5IzjVrNW4c3jJ+WjIDB3gXzy0ocWBpAIOgeWH235HYYRWkvWtcouWZHjULJi97BI8QIpWUL//sfTX+TYoIAsQICOJhHELxMrJlIwAbpcQ1muSKlcs3cq7JgRwT7Et2xMeI4L9rXXw/9+UZpN8wE5Ct5ca2xTInOn0blFHDnFWNlfs+Y3hhOTq1Se/59HwvWyq9/bPbHTm08mFBc6knBpGQWAszkxqcVgnU0AcKupEZKJVSx5T7ul+sxNquim1X1XkrYy2mKvvsut1pImjdxZZPyrFCqUbBsB6SGGlAxQXpjt2GJ8kMF0mfg1ByWazVk9MCNId+rvrdsiyGxCH4GTXp7oCpZ48996bDSUjm2F4NI4XGJDoIoQvGVdH9SILyCS/Kdd2lSV63h/b+VS8ORbvjLaxYw4ebvChlCSwB/KPQkMNx1y5+c5YnXUHE3C7iPJR/q8nUVv/3SFmi3/xE92XJmG3gNS36zrG8rww/DlOaxTQZBPu7NLkNtYCX+r0yV63VcLtcp1KUS9+xQnPq+jfH5JQuAaeEuCend9XltpggvLW3IXDzK9BewXwe2jwn95K6+RQekrC0KKs3Sg1vI61/7gcffJoQB8m5b/1UliX+03JNW9osBcllMDbmFCtHwq4JLsl7YpysoG1LNa9Aj8zHluneuS7AMgRQKKjP+NqEqwLG8RjZCXMMz7sAsZiXfkdwkGGwNfj6PrRHCd0SEKEAsqLKkNi/9NVSRZSDm/1+bVA6T5IAgP13F7l9FlWBZppkN4lfS8Ej0Xyswg/DXhw69EGwoAtF87cNkLQZHI5z8iugMiYytg8XoIPyRSnS4+9UkIc/md/b+ef4+6W1Rm7RmHwtTwMTIiLZv1GjZ82T/304M75u9FwDNAl0O2zLuEo4ez0/Fnyxqt9e3XK/hhZbtKx0Iaj+BFQgERc77lfbd0sqiQZViXIP8L9O4R1PFlW2IEqk6npasCwweHbn6QajIahNmqzUfr8G2WL8+c1/Nsf4QlBBiY5UVGdf839pI0sVAw9EkB1f4SNPKU2QHX6WljDckycIl9eO/0B042TGYAkQpzwFN2xUyVZuhaJOr2RmtXTjypHrBXFjrb6Qv7sVz7CQrgYHJXNmigRdsdb6LYdolFcLI6a5Ww/NXyJhH4FSkoY8JGbJqrI7HLfgH7ozW9mpH56EMYn5xpJKu9RImmDcYy+n42gaz9n0yz3e3H8BEzGWYimD+PyfMF73t6kzaFyWM8ehwo2T7ENfPe3cYynwzFjzbAGywVDdaxsJz8gMVh4eXx038OeHxRKCSOqUqNlTrJamU4gp+xuYcrvFwJisNTi4O2DpN1wqRxrAvEPZ42bOiDjl5gyl6ogF3I4OmO8VSYwpqBL/+Pwp7/PcpUDU4x9elAdV8EsnoiHkL3XnBC8AGxUsbnI8tu0JRwdfMCnSqMGl9+Nm3hzIvkHe02W6t1QGHrlV5V8ldYJoKUBKg8wiAPvI5YT3LKARSkV3T3fepfvA3rrId+YccWkd8/E+EuuUjqKiMsv4dNRcR9OuVhGIWgweOq+OEjwGykRgeeyomP/MWYYs786KWYsb1I0tf9rnnMo9+M+EaiFQ8ogxdv0ZfdSiSgZ/OaSubVYJS+GX7eaK6qWwTFtIxNNZP7xiBT+46AsLvQ5Z1+YMMFYBNoIw4l0ZXvuYsC/m4FbTYnCciua+icNqlZL1WoutARhSGiRV5WPkPYfoek7ekigqufH95+DE8FvK5O5ifpdhwZe4fNYzvaGj2VAzHE9z2iO6NFm0IliyUqQRVug7IJpW9jw8eS7szh56xiPT/QszaCEa6E6/NGpzw0VJreLOC6/oXdzzSGRvooF23fUcNnP7Tiyzsm20muIL5ny0CgPwxxylvqM1/RumozqD9chd42IBaGE5SaCwyViDbQOWyZzfNW+G4b8WmWo7hVoYbAp2PAO8GuID3u/hMPnzHiYHkSRDWZPaiuyZeLo2EDvgj2LbmI6GfprJUUFcuAw1Ghkr+Dq9XgD59vU2B56E1Voud70ukwZNzJQD8rxwjTBm/trT2KBwJPiYQgz4eFg/PdwIrXv7QNBl7T4b3y1FO8vLz/nle1ymzBi+VnLINFNEhD2NEY2FBNrYFOmlHDBkFA2CzLUzSAhrDz3wUWgdnu5sLbv5393uKafjev/eUFntacS5uH/FkJ1RNYf1ZkZDtl1oGZk/u0yz2nbfAKqZiXLoluE9e0btwg6IlvaHVDFMIx0YzYIGrC0Nl8FTX/Jo+6A+i7gpsMm9JQjjG0u/dfwsLwiVox0Ds2stTT4TjPrFKWQ3EMdXpQ13guTJpp6/gW/xiCITjpj/5Mzk+QRUlVzkl0gzCyKXZxUd7TWerj76ZsSg4JY0cpJYZ4b+MCLMMa9SANHkgWjt3/MHVOpj/MYFZyzGNtiT1xnYs09ndtwwDynAxJ4YsA9s4UmlOExM4hJNdw5SEG2iVbQJrVlD6e5SnJSye6uSxDiWD6kAiqM/+GjJw103P7vN1w/Q/KfxByj9yTMwnJDf9zlRJ/LCUViLhfy4secVELahZTt3v9SsvNof/uHYqQt//TR06noUwtPbJXM5WfscFVEIHBAbgRJiTChO3UiUCctBDvrp8t3WRQ7iqwQx1IKdzkqTUCQ34VsVs4P8yWPAm+deXeU0IOFBdAx4CwF0CXquJcnP4k1sM2rgPiVy0VDDwrbz70CNh5GkjuUq46dt+kA+IXkwOB0UQM7XDD6fpDLY1E+k1AuW3NEHaCV9YMFtgF6aSkIpubhRfRhoNPlZVO5oNVOje37O6+8nNfkCEawc8+WipuOfSC3qeFQg2V66jevu/9Ahaz2y/VI1KtoKt/Id8Wfz24oSpNPTTsYpez9hbGsrLJNGl59RloqxIYkmsRuM4x8jSXxyopuH3D9GrSL1gVyq+Bf5WEZkzxMRwCGC2TbaI/5VmApBi9aWPCK85AtBtwuxG8/w8SeZjaghSB53TUuIoX0CJwgC8VaQuTDsRmvihSKl3Qrrf6W39iHoaJ07sIjMuBuL6/fapEeCVm/8UVn48+Xd2t9Xx2OgRuD/PFJ+vhPcL8gyWismKsB1FkPvY1FJnaf7VbR8ma/Bxlf2WKGxEbIDbCHCyYBf2XOO6dsxE5v3Kju6+gm78uKDTbhDH34rvUxbkEBfFyTEq4nhfIUO2uHjdENrf321VtV9l8lZ9IIIZR+Nr7upAL7C3yMTKWXe/jz+PMgqwn4PvF2l7MvjqpQOUdqVartMwvZooVWSbkVUo8xdfkvysGJeRxWKxjGkLKO74LLoxkVvE8qLvUZmo+sa/kPU9CJ19j1d6UXgT+Mf3mITo0fg/oUg4qcGX+vrZB/n42QTO4HLb7o2aG2UVOgRbGLTABE6LnJ0qQNVJsfoXcwi2bpqaZ5+sKAcfCW+vNH8vji1i1ILeAJrb6MP+p1F/FRhiUQPL+eQPBKs6QX5p8Ne3peFzlkGIYft1SO5q6Wkz/KiiXG04vAB73rskQCj+RdASw93K4bOP8c1bGjZlYSp6xO7hitqJl9HIJARi4fDChtlKEtmRM8MUQ+bzzfgbokBtGGJ78HR6UDomKe6jbshwsk7kW1hTRTyV1NrADEZIkLcNVes2yEpqEawhUU7YPNfwJzfovBZ00pPZVGKHdhhQBjmD0fWvIsXciNX+ZRtSaq/zxyA1gLRk7ADoPBn+8p9PsZ0+AO5MnLnjEsM0mYm/s+btxSIWuu8Pka/0jWC0hTFjEyWzFpKJQwRrZur4OjXCGQZ6GPtx9y0eqww5jRA4HSa8h1DKRvt82wO1AqDfQFSkGsVLMYCu6wjvYoTmxe48YgyX8cuaXDGRXDI9jR7uYxiBocqJecZuJoHnVWfnDg4XEP839tpDZISbcoGqu6z7o2+gA0xOJj+tETyNPMt0wdzvGDf+XykQQ5dIXYhjUsaMejeMjvj0S357aq02XLHc34rdRVOT1h+YtHoQauelJin28dYryyOG6M8Np2+8ShZQX2d6wvywGSopKnh04l+UJrcoNJd/375YNh0DeYik4J+7Wz4Ba595SbCwUY4oMqPfporcocd21w3VZZBH8k1BChB3SRdiLvP01sAeM6GxqIRsMwZMT1l+/R+aZGz4oZzzdX4ws6NP8AfOfQT1MDGij4r7zJdCtvTRGEtK/s2U8SWqqNSY2A5L3iP+eRZnILtJi33xtK98/+Y+OigDJiA9s7eXgmPjunKa3E+CCLk2V2Csvt6tsjf9x1UbiypwOcLVYazxRfLy6wHBvNDkg39C6kruwNCgGIjE7m2vgZepmbKmVtIyKYpwNLgey0f8gq8K0UJ8OaJssNfDoYTMEGSD+h2pFDhbN1eKxdJ4GO25Tfzc5XANH9rS+NFYNxcWkZ/WFEEM8wINO98duvQjgPh6+3LjpyVOS9ZjR9kFlHsy/+MnW6FcMkkHIIdO/qRFHSnJFexMK6QoqJ/TPpQO0Lbq/RUpYJliFBqd+pJ51Y32pVEeP/M0l2F4W/kBiWQgbs5u/eT9CLpT1hctuEUBOkpx2q7bBX8r150FGmpsKqAmosCbinz3nq46gmiJPDh4DEhWD8vTJRmWSWZ1GVFeHHeTaAB4jBLfy9amqJBlnKrs7N+SdGAlqR8o4ZpFuEdFDEdJ+qLWJyDpcbFto7jTp1TOWa3k36/lR3AiPP4W5ydvqCUdI9lMJ+5vnTxqQiXFmKTruvl8k2pI4dssZEwKwoF9/E8RCg0W184o4q8XxnTRN63e9WMCRxjSMsHKdvxPnYB5Tscy3TU3j9i0UquK5Zpp1P8HT8O3fKKO8dCkgsWEAmB/jXe4DtKOWOfVfOfIqg9h6UPMeDs/EACCCB9vICOffc2uyADmTGRd1bq4ys5EWldX12741B4GGmcuO/Q0qr3bm0UwW5Eo+NREFFAo4Y2uKbDgJeq8b5JAMa3wGz3jLsrfTuQaR7kRsxD0oWVu6OI8m1LbatKTba4BwkX6TMtkLnGYUqpHEcF0ChvO7hxQ0vBPm16qEo+0Cr4jvr+Oo5clAnIArFgjv77jcxOGKS+MyHV/ZzKeDgqdeW3MIL3y2EzX4Lk/WtGNoiyxn4LOqeyYIE0tSANm8ES5z9zgIk1DlEtRNhd0v0Ty+XhV7mr/nereGZXrDL+II9Ku2t5h4gFzY8iOKrqnz2UVA+BzUol6xaWxMn1xkCdthEcVcBg6+OLPuZdBo2j9wO8+3F9wmrPMf0+a3h+AvOYm12EvzJ8aj3/IBPKdJaqYL/TNJN210FDd+Nch+66+6ellcn6Nxqz5WJIsm3YJLVO8E8SAqE9fXj+j33NZN/o0L8f+qMF6u7+wdWcuOHLmc2ZVYEtTJqt2ihgfPZGNlsgdMzgY+Kx/2NeVOqZEZMGRjMhK3fOPuyQ68oph+6rq5xd+z/iiBWk0YWbNfwaKy+CNJKpvIEBBhDDpmJOV8Ol1FrkKxGI76MDbASAuQtfGOQtSG1u3nwj2YeXpyNe2fSazsD2TM0s1VN+X+8GX/HZwkse+XbifEsYCZnZA62r2jqq/sPOjazwcXjkDga/U/FyNIJpre0vX5RxzqephRO1R6BYkoSeect2pwRVNdoQOOzEqD8Vg9VNlPSHgcpW18hjHVhYmJv2d7h/XNx0is9CRAiqhVLmS/lHOFMSGsubOWrL/fxo8dEjSMe3ZBxISJ8izaX/vSQpnV2BDrxCXrkAo+9rBwp2rnJC57VNtt4Gtyu9FIrgVx7Qwlc0cCGVVXDQXK8F3azV8T9F9ktnSdoj7DILL2EnHQp0sKybMSeGCXg/3W+7rBB1X74N0vhq9CwD+vxxiN0KjM/u2z0vcr64EKjY277bjMoE7SjDSNY3hM/2hPDhRZBTuun5GcFb9c4r1vXpJ9aSGGBEwsjrUCRg5bv8l5T6Kc2ziEGRIycE7HIqeMmYYDA1U4QTySVa37bnBFEG5WMfV1TdN4c7h56tYt3Qv1+qtwNq8mBJrdfujfAAVgWCKqVdmvJ1QAOP0kUWJhQeFJiNJlzn4v/GFzgfWUwRiYFXB9wZorq69AOYB1JJ+G73Zf9A6Of5NRBbnnW2jGD5vCKE8OCs68AYFmT8yoMSnIZLJ+zAiUZIG8NbA09V57dRSE+/J8C7VXtO7hyJgyCbFfL7U0Iw4/hxCVpyqtjg9l0a+/fCuft2n/t5VUQ8ac9sbNi++kkA8NQq8nzahj1Om4NeiqNqf+duHzDt/ZOhuZYNh7OE7ZU1Bcncyc6M1LYM+TuZpqKYVTWvhjn7v5wLEyh+NsTgO1rpCSAWu5Qnjgs3kQRZJIiQ4lB9tdJRWXckR2Ywrt9w7/LZsgmFHk1Q+qtjPnZTK31D0kYwOQ7IpjTEgh27bJprqEQnsJk2LaIdyZGcF0UmrDVTsQyj2/ioaRPuIsCewdDD+uFwFyqLDP6jqJyGDSKi8SfeZ6r8tiW34zRDCEU+bDuQV7B4SsASKUqVw8T40JH1kjpX8/BBWSTRTvKUB1LbCBd/wMJ6FdBI+gMYbOznCL/nbHa4zH7Jdd62vllj40gb5SnPbftywAupa5VcuulEPbj80BLGVjOByOv5ZZstFbleqbLadNbmv1asX1Gp41WXI+lK07GMPxgj4Dk82/X69jTpFTkBX3KAUcKkBuUopGXhdxUfpVcfxl9giz83gA9XQ0/Alub1LzvG+ybtEmCZ7qgl4jyUXU0UyH4l2OlVPw/+DNFbV3Wy6UI7kBOJqcsuoTfgMHg2HXnDpYb5bEBX1R1mV5Js0WLhcX078dsI6ysB+1bRJ5In4o+0ZMUhayZSQiRguU9sMvs5lIV38vi8ejafWzGmnXyNx5vumvGel+fsrv0apF3YbCi80n/LTpjfXff9Jrtw8TcKXWsWZpHynk3HccSAwO+XS7Op/k57Tll/d1JPRjnexQVv1GoaIjkGUKKI5/Ct4AvderTQoQc8kN3hShvgGrgigDUOvJ00248bcs+9Lyyi3JvOHnH53s/qnwoXO3OfI6Uyug0XfYoTYszcKWXEGR/feKT8zkwp29ff6moLWBq6MKzAprUo/JVzE2bZ4xG/QEnmKAIZ+IPe2TvK+R0J8fs8IrOaN8o4ncRVC0PQfV0TsDJL8AoxM04jsKAMcnSkoCFnWhT96/SZzYA0jvBrAzmJMsRcpQwT+GzU7cPXjz+gaOIwH+pOX9VsHxj65C0WRmwWvETQsaD/TEBk8IRvfYQOe/6U+krZh2dphkMEJxxSjOrzAw5zMTkSMWwd2CWv7G4ZsLGuszPPQPxt5rRJNZq1pCVgZt7C624XYxcWqQ7/KK1oJjyR88PHdLQ9e/2N6YoCIUMwV33un/9Zm97I8wuiklhdDg09VCVzWJ/k0v+YLNPctnos2q3LGRvpbh/nqwZ8rALjlJSsTYtyejf7jxScLp3VDrvnKetyXnyu+HnASKuDnPzwVpkGGg/muYj7iehrJ80jgNAgRFVfTZE11pWoum3q29go5antDmRXKSdAwguVbaBVjhhHDPK7KJbHB460YrQGH/4jgomeLFzTuLHze1u+oHHFU3XsHoOkJOH+yu6oFPDVdLVZXbgtf76Fb8jT7pxasilq5XlCqgVqkNnhry4prvv9pP63URJnPG2LMvwfsSQ3MzXZw01oz+L2WTdCkf7FKFVlrqJb7mmnJccwlOgldZfsYYW3608+GBLqltaKql8m1JMHir1o+lbHK79eYu1gZrtluwwwhJNNftXEupJVtAnzag/7vhyeI/TPQ+tLsYT2y2sp3odXPntatrefWrhB6ovpT5IvQY4Dmb02CBXyPIa4ykxyrEShp7rQuBsufskyQNx7NT1tyux8MnEs+GpI70Nl4q4luQPGd9CB30GQHWYeSHjAmgo40pPJRHC60Nga0SkjnzzUJfJbmRy/oJhhNXqpBtm5rGj422CVc8JxWvOsPPUsouzK11InnpYnAJdaW7bhrPW8U8T98CwOyBpUxaRu4ZPbrnh8fED3gti9JyxnXw+wSlc/ehGbPA3poFQI9a5GqYD9RdJlnthBamJw/jeNSAKdFqD+L4I8kMNA3SqksyonL0VbMjdmRc34sJPZ8cn/mH//7/MKU1/pEYJPNlqU/fa8M+eHaLGN8t1mfCrY0dZqOfNNLvB451/R0S67T8a7aLtNzvYRilqT9Vm+P1jhWsixi1lFhVoeHfTso9TexrGi3u/t8uwlGwYjSImtaYRRo6+n5cO32aYtq3jSOtfdleQE1DI3t+MjuDkEAJgP9kV6ox15PNp+MWlGQ8KlPlGJYB18EAxBGCsQeEJ2LC4+sk7xJ4m8BAZFww4LkYKGG1r3agLqQUja5DPlsJS14HleihAKAkjPrBDetWuY5AuFx3x+nyE8Kfwy/lx87rS3sajLS318ia5xqqqM28+GpRwP2rvZzeTjBLKiVEJqF0GW07iM6MRYuiOskSNAexYX+UG5G8LGt+wDMg94W86n1CH7joiZTuyrxQQLMHFjbpmV6VrsN/p3CpEgd5Pycdv4U8pkDacjNf/gZWyfMIAVfqIOaiHTbthinYlKagHcnKaJcu+DYENv/tfIFolZWZyHD4d0cgBejPLmhTRLLMCiD2OipP1nmxZvfj/yzdpW91f1UzkESM3RBveo6z5+D6BgZAdC0stP+RfSLq60ikNFle6X8DLBpVqlVfLdYJiy3QxaCfiODOe6V9kCwgjAvyEvE7yYcJIZW7S9PScE1jn96kLE1Yx2kKSQ0J8p3o8vwelj2/qAnilp4tcnwiS3oS7AuMYUwHrBAMDFiGr5LGQlxeSSv/In9CoQvuP6DddtHL57m3o+nGF/+PUE0+MRslfzYPdpGzXbWxOLe595K5/uImZPLygBcwDLwCrmzcxjZ3PyyFrBSVNrA6u632LBq/8E05k8nOFngRNO8gN6os5nwxN9ftpklLd5Lctg3QjGgUpGRftc4WLUifuzDQRVPGOUmE9yce7ic2smrHbxOoUdi7w7EzXwDXYhXkqll2uidJaNidS1qax+ic/rkHf/iPCUDCxmdAxFBTb5XXEldjN4lcqOPkOEJqS1MTYiVPW9JO6Awpizxd4YBWVnPjQiHyeeWFCYRIrREUjvuUm3sk6gwUPnxoVcrMkiCvfH5JqUvjsTh+uEVFj3rnvOp6Tf93JTYmtHdUSzgwfJrn0+IsLb2B2cbjmxcZzTsInRPHQoPACFuXLWkB+I862GsnApDrXDgK8vwxejCav+a60wb2RkJi1wBCa60FcVXvv4Mv/mV8fVWzczF3P0LIIQpXaSvRuQOf97K0MnEbEthYL2vKAWC9hfthZLY6acceyopMjtfcdBdRUGg5nJ9Rv/0GWCPbimuD3rX3ZMhdG6Rka/ucGJEgwy+5CWUtqX8DmvkeW+q69Eauk7V6MvKS0g3WBndbSLWGcMIXEktYR5K7A9SJcu0Q9sCcMpkiWAJNYxYEj6rnuPGmA5OXJke7k/BjSyjq2mm6mMJ9CiPZp8uelYQy7ZirHoAV8JImfZxl2grCuvp/TZvaKwuE2mLOjKT2kbiMGH3W5gJ35TXR7iMcXxpiEqrUpLktG7hM/1d3vUOo1ceVPqlrmQpgEcL912Ye1EzZHCqxNraQ/6sGqb+3+Eqy6P0fs+b2MFbqOzD/OMXiMKSUVjwybSeGj+fHzeaNyP723AqMAfFZ19h7SuLA1eD9gefn8v9CLOOBo/KMQ+PHrrhe8mrDR3kyFXKtJPQp7VIlXvmz07VvQt5LiPmTKWjnbRDg98YptNoHxpJI4f9Q9i+EfTfKuqX2yeKmomSTVAhLTitA1nF6OqXvrSwopipJHm7V6W2VUHh4AsdL/8EOUazvCY8Byh8SUiuorrjTmK5KFmTjDVUOHrX7Pb+g1A/Nn6a+6fffDk5nBoOiOlnsdD7B8+JqrdUPYhUDDY7ZpkIZIHTNzYd98Nq+llTBL68v+VBdCGCDWx+u+Ht1P/8MfOnVmmMgRYoA4hVwsIyyMEeKryVlWIbctnr3OIeRWgJN2szTT6UMsi1MFJwe20YumTohCWbbUKoyofTQk8wCj6n26syy+n/xtU8mk7oratfg9gCQXi7P7JzVyjhqetiLLQG5bYoihfvYXCK3zyf7Ac/qRa8QgYo6F5K22JA2dSwxB6bW2LTxM1als3wlKoX5mVZSedDsl0wQAZH2/pPgyAP8mBSoF30xa/fFII6hoUcfRcikN4im882CFWLwl8BrdWJ2nPkl3ix9lz50/3TQm9qbrpgIU8OZV261D/sLJW1ZgUfed6C3ivuKjOK4CmFR9JgxFoLkZgO4txF/7KmtUT7Lju0Ee5xkldrdY6cfa3ZAZ5g0yxUYdHrFTGE1fwMjbyDUQAm3ORb7dWALvHFpFrONgdFwtqHXjJjDWjeWwrkT6pQYp9/UlzJ7tiu+OFuI4/EplyznipVLmdVDgqk4u616OMOP5CS/DmiszMRaOVG1s3ta/hPeAfIg1/rSmMjZxddW395Wn4c81KJhheKsWaWdcq3TNvdf9ETqkZFLoovLLmNpF787NWIc6aq8W0Jy4bcfgjNirA2htFpOZzjiLsM39duPNHzVMqeO9ZklSDOWegQU19DPN+3wkqJfvQ/E+jACRtTk0cD9N4OR1sqI2KEzKcfXx3Pis5lPv/ZsCftnqL/BPgIKqKBsV8g43OseCXrYE7g67VK6CLIHIyJ2w03qR0VNQWZ4KqZruR3DETlIbNBwbridWHy3GQS0FkH5v17e97eUhVNiRcsTpwoIFw4BnEflihYHuu40QS/zZUocWZL4LIau8XgtDL3/fSytjI30fuQ4yrV7tjTTenuL+jLTAplqMzAssQfzKJnPz+GBUXPXFQ+P5qvG5YakFlFNJDUpLZTVMV94b5pt9uGSMPpfNWHdKu8PlSzZNk13dO7QN8FJb+tNJ3xSod97odyGKeSgMzGpiOBz386jF00crSm6beSdpPMp3xOmtRdvnUjJLUCZ0Ms5sx8uI/6HIWhHbvgAdOAoyTgbrl0iyq+ErIsNWSkEEO2oyYt32DpZ3KZXWdiel3qvhaj7zMBjrods60ONd2eyvFUxgJ+9KZm3PieBfsZqCRVeTKGvM81UkMm8zN3oE23Zn+SsyoXd0gKG22liTOuocp9eUkkmfFG7kvRjI5IiPSqaiKFOYbmS0rVv9hk4cXTQ2C8X3YV9KkcJUAUVpF9bAj/2ZuBuj54t3do6MLJsBFyvHU5Ky6ej/IV059+8dXDIC4wGrcMrKEIjIu4deIt9d3P9xt+9LosvO6vktD9y+HSHftLxYtqJoGYyd1P+AeI9U31mNIa+u2Js/l7l3h9isxAtwj3xUtunRY8ZjlbCEO7H6LkPsWCWnFOG2/4qQlkR/iwMZyvxOha308YCj+m1vf8v2MqIcDRUiO0FVlOqe4cnMAuuqE1+JeCsUTGDndjX3cxMfZYXIWB/eMKX8D3u7DV9b/Wv0pfXNHLX6aG6TUEyfJnmpEdyxG65KoJfAGXUG91uc3QWNAoFAixuM0RmCrayeJqo/ifWkRTV6uO+rf0P4hr5ca4kif9GeIGONnHBS2xFgQ0sbQPLLrZKChg25o64qXPVVAR/yg37wbupmPA4/c/6QdRAvEX/Lvt8Z3LJqqcPgntHM7WjiGv/O3joiIc83RCh30pbBY/Fr5BWJYr96c6zcpq7xPeBNnBDIRu/fh/63dNMZ3Wocp1qXRA5ngHLe8AEDXfTc9Sbpqp3EaY3oWP+C44aV/+xfSzfcCPh92kk6l1798Hibz4PsPpaz5N8Eq4powkrXMP5p7DK9l7+wLlBlGjxf9exHOFmTVwP19Mu1N67ApEdVXumvxwv+jC44xfx0RS8QuXgOYy3RhLVJs+PjqwkoSTOkLwXWFCw9YZo+csPkcpcgYrnqTkKy5MgULp42u+5zpo/IggyqdJkVGoV8tc9i6e1EztkOTlbM0bZnBmKp2dbsxHOOr+mgqJTLlSwuWavQFqL2qIzZTyMwolOOP7nITFI7QzHGakyYNPID1d3Xx/tnL80GtJYMlwufpylFdxkG0RgPDdNvOCI08kCD1LRfAcSyRsLnZf1pH2JlJbXy9TjKHRVk39v8Ui4KsVRLVknYlvdI7UztF+cj0BqZVm8COqiZARfKOVBtzpyVI7kw4d5W1L7CfkR3lpC/C8N/seiejizpxHRhWmT/Y/VwifS8eAcg+ZGI/BhFNp+XXx474uwXXNJKIKg8ee8VuVkyYv6D8YaCxgoViaBdPjkuwfAHQxnnMlZ24D/yGQr8tqBV8DCG42sWoIxIL1FX+QlrfErjgnhI5/u8QPw9DzgX9y5r5i2tOatfO4SpZC2cCKNWFruh1+w94alolviV0M1nx8VVePVr3W93hZgmlm4s/ZB63c8As0FZbX5dG4cNv2llp81zIyXHAHdXJuaWdN5gEgn9rrzdQNrKp7LdSPzyCAYkaRRwGrAEPTXNWoKbNOqvfnLf/4K0urKHwByHBkcjpvosrhBy9LW04I2ZjfmC+c0ej+mTb+AnoZz8os8bsrGGIOZoLPpnSzvpQ1vUOYZZhocCkMZ3hlmHYVu7b1bZ/n0DjbR0lhmr2op1ybXFxu8yPHE+POOHJBcpADRJUUnb6EhnXHa5Nw+sZDfA1mh90FbZi1U50wYsy2gFU0WgIvsYKScR3dkA0a0iCLcIs6IEvRTTTAx1KJgU5WzwQSfruJlDjeT+z3km3kMctDXglnuA9Q9mZkVeRW5eoGVdEKoW4KFAGcRVzu0SFu6fnx19ceaCRflD6eZ4/kkY0FS6rLFyYNpNub2yfPs3AxLI1i+cXSVbZ/CXZtsscYM9FBlbvEe1SQlEg//td2WEOlZqgWWj+oquijG1kJbfZ9n6KtW5DOj/pVKNR33ymg/qJu8j4MRmXuKuSkrh+gvWzbmD4npcGW9xZnE1kmXxzajkuyNjiah/Uws2yzAGi8Kudvzs3pyh5MLrsBps0M2Tqztjv7fijZ9WNgo73RZ34hiKyN8Y4ph/VIyx7CottZJpJ63Z1hER5/3zd48WdPI9PCfQYhsgz6HDEeAH/E6ISbvNNq70vv1fofaIifsUs7im1uvg1/SaZRuJ9WV2a8HoIvDb9QweZBbz7M7P2JnAdBepdU24TxAXutL6i0mKXCszXf71x3qfUgRqKWwkjmRgiQu8/WoBNlJi183d+EWr95urRt6NNe+Zkh1rW2ukLd/Hke3klks/ry0vtRkn3d3EO0/zIF8f38JFq4JkTmIof51Nc7iE2RkwUrq8uXA6C3RGAmviLXlNYK8UBPaQhNh5e5kwD47WSnVn0/gXwT7BNDhJs6xGKIvCtU/EWlRugzEF83mlnIhWBWkYF1EIRYFtZYhFFh5FubW/vsq/Eu+5CIKnhgOCZK8AHAa5SpXfgu2t+otuEjeZIy3po+gK1wiaKg/lcpWtz/AQbF7uy/VM1kUIDFh8B20Ve0wjrELMKik9bGiwgZ3/Efv925R1Jt6kh3jJBLawOZYPG/bXcmNjPT/R/t6YQFuqQX2WgdRN7NeJaPgi02+jad3iqmqvBKe7MkXmHciJCNoRL83qhisjmk5+RL5PKXAyLYC7NzGWmGcgIe7RtvQHejIzeYx+AMI8zTDvff+wX8hAcstnhMLCjYhEvJaQQVsvFwkIhkWLbs6s/KjUaKHyaQXxkchQxpRU0zngoM+76Qha2m/mKPrjU4scBnsyanfE5GRX9uR/ujVrdP+0GwwV0ZsRvsLylkfoP6BpDnG4myE/dRXk4koh/o0NTAthB+I+Q+QoBnuXw0je0+FgwD3Y/QzRza6zwMLElR3DMXrksSDtB3/Naxr9yDI0GuD/Za5JZOJHYc90GmDKah+xfAFS/vTDiOFGpgkFGVq7OYTNgSjSIqXDXz179ipO+8Ri1PJA7Ho1mFgMdNge0BcCjX2MtYnRF9EJ90D341T+k2H+MDGSKrDXVJsYQIWpf/jKYj12FqFagWMFhMcLvVHFIUQwtZumGoQwR/EiWbi9eP23lJzuJDVqCTVfK5a/FZsblGs6CUgprMFgv/kg1JLFk/85uptpv4djlfgOZYe3F92E2ySgUu86bFGhUGVs0abhNccZALoIYt/cT49CTDgh0GVCHyMyrpqCuf4KDgC5iZuKS73QLhSVCQtvIQqddu0KCSDpjr1Kt2K0ZzfeHm57OAwcv6RDYfgXPd0SpP9Fk7198YijEh1v3+GCRPG6tddECW+x5XcjENfWhQUxaVWZXe7z+igtgiv7QvmVXxOo9ZcC2Z+/vSZcRtKIzVNkJB/tYknQFUEaYW7nBhQBKYkaq2GYRJlKzCcFwAtFoSTdyqzdYoIFkN1zbQA80GkY2tF+ABn3d/V4LYSRxZKOIHYBJVwB+JVYMM8wTUfJOKm8yHM0dlYCgGC90/fGBlcQeOMR2YClnq+vjVLuTdSZBFAcwQ1tDXS/LlPL+5psiyiW8XMcuQg+zZHeGog7smwLErQRRFjGtL0C2a6s+Df6vPzPdx8dyzV6FM7i86IPMIYbDLvB13maQjwYsT1MkW4n46/BIfagSy/xJrBRmTf1gUOTd9DwT5mP8MqTjDTDewvGpcN0gjFbYCKz89WoaIvgJHHi2bhAfEvVCJzwQKzU7q8zBk73VRCtfD1HOJxP1ZEtnugOSnF1TUCWrN7SERqCoqesj6QzFk+TKwib/C8HSwmcvV348TS6dO5xcNOnWtqArf7Ef9rgjW+pjOrDbDl7Ri7IrPGZBK0EWuBBRHfc5i0qzWzf557vSKJnjObv51V/iO7q7XFqWXv4rmnnbSCDlYCqX3nxrITd+VmijX02BZls0ieXKG40eGRF4tuKNi+qa93ekf/yXkw9djHtdc9JMU4fdrs+ha0QCJeTmK2KRKcTuLqoZx/NkJzbmfl2FdPZ+uFViaM4FVbl00VLvoFr4hbK6imMfr9hJJ/0wYJQFdhQjOhqcBGCtLImoSK5puoG8wEyA2m+UOZqNu8iS1efXhMtPWP1JLPI6YHvhMSB+YxmhNBH1iFZegOO5L3c7m0oXzIcRA8vb4O0p6Xpk1YJtnZ3SoeCiLztpO42Kb5lvwROpS77B9RR3JnWVTKNat41DbMzrLlqLeHKeqg0H8UIsxW6rpBsYHzCxtVx6oqUnwfb40RFT0jcqSrb1lVhlNlBy4uGlpKDgQcuEnIDwOad7dnEF0X791I12uLzwPENYzVg0eeFS6Ehztobl/DtF+zBLvHm/lISSI7GB9y3UPP+0Hwh++3O73KlMtjeTkX6g2PdRbfqsaZgZegWGftIjassAqpp0E0/6gWj4htrhPdNbqGtCaFEP/H1NnAahV8fz9xQBBQARpBUREEAUEpJVQQRrp9BKS0t3d3Q1XujukL93dJZfuzkvu+/nOefi9/733OWdjNs45u7OzM7Ozqc0OjxVp4OpMeH4GiEkYJosxM4zPqWkzIzyDvOxkU6uMNUGcz1PwDVna+NPXK1nm4Ni0QUqaKzgX86BPYGNk5ZeEfKNLEsy5yKN7VQMQGTWTqnrOQ/w4UCCCSOM1lozwsaA+zDUwRoNgLoKJVQ4YIElwH59QoQuB1mrE5CCDXUmvIU5K76k96IIsAlN1WkrCOQZcAesSQhwUJ56ZFJE1X6osf2RlZhROWPJrIQFZAY73B5PGiPLfbsbHTEFKqf5WqbtpOWRupjjU+PMxyo8eDqsV0wnsIt31NU3FhqBsYBdLpBsJzIgcy/2hT9jPiiZ3l5c9tXRDN0GPR+HfMoO4J5tV9jwR1XEmy9tLBahyXFJ+U+WReCZTE2jDrtrAQeK6ZF1gCwH01L1MKwCYf1y3swimO5WD9wF6NcFO+Kf+4OzjzD9OWw2FlelVZOQfXg36Cmqxwg0sTsaXPrvPq/xoop0k6ldQvIEIZlnXwC96RmGoS2etJkxXUlxwef9nXzfbLcWcFp2XAN8gdi/Mt6NVswkKtsHzbcHrIpvmzUr+fabYVS9cEdMxiXDFip8qSQmy3G+LeKsgur4hx5n3RtQP4peDsZfnjs9ui/+LVbEbZENBRF0wDMVAO3i5CPSwC7+Ojk77H+9z00N14b3ssUYTWPEf3dnqqMMc4TdXMr5OB5YxnZC2ujQSuI23Ch8HWfxC5C2lSol3cBSlxFBb/JNox3j/1jCrRpiQ6qZWtOPvnuM/2xbN7K2vNnajXVJsrqTW6MeEhkB9PiORN/Nz6w8/Lqus8B7PkhipNcF9B9YQBl3PgHsCcQh/7ray1tDisZoOt1guIWaGYcG7XcVSZTxsBLQwYgoMXbZNLxHD62jWt34Zbctk0ejSqQk49ZoMFbSBYlMookZb9Bh+sDSoMG1WmZGkNLWpuLa5qAd6WYPmhiSLSf8a9obaZn+po3J4DD0vjqkqj5EXjC0fPW2s7cSN1Lwpl3tyfG2TkfboeVDPK9kjsVOnZ28X+29bAGXtg+KdqMMxq4MVb2GFB4eABs0PHkkAneNzYZDzoa5ZA0WZ0XYaPQ+mqggzvdsc7wTAZqcqWYCQ0w+xNDAWU6Lr9C/UFN4ucxVW6RnZbU4feG01xVLsCqYzBuz8Tf9ooL5Eu0CAVAH/hD69fWtUFoIPddxaDpoj145fPRR10IAX4Ds31PwT/BLem7yyoGY31GUJLy3tz8b/uOUPssk6FSLiL1/4Ux+3CiuDOu5BE3GqNN1h8GXsEji0Q4XizfHk1iAoHjXJ3N8tuJ12O7EsCjJOw9JiMouasM61mOCYOVGkUAtYCO/0lfgq1kzK++C4ViL0YXd2T1HeFCTbR1tX0RV1blfb/T5CjKrX/kXqA4oiVzJdWMtfLmnE7iRi2SHaj5y3+MTsefGxQWYt3Zw81rKTy5TNnlrfijExgnV25cD+ySUeVcnw0OiLbvKEGWyUHy5uYifIbVISiV0qgN5isvzPtdRswzAxYv1RfxsyDuQOFsFi1Dp/rp7lAhFDJruZqzZn/QVs8h752/iO4VuYNyBm9grGKm862N9LNf/oHbhEfU31KR7rotY3lgEw8Kpww0yZAYQxpQIZDMrUQZcJoN7q8tTy2S4GaPgEoSIa8jsYEXtRrn/hkpwn7qK4FjSrMH5cvzWFULb57SHeCH7uNl0HTXjemTPpA2AtWXIwxxbUV59OJaWHQYEmJIDOpC6s+7giyRjGRUfAJFZIhfl037kFryyAyC+elCeBpCNxz9jvawOhCXz8x5Iyg+ZuQZK8CWW+hV4eqBU2HtjOtB7X6NxTd/SkqUhR7BPiP9SGH8oL6xrdys3NWTfPwkHDquSGMC1Ofq5QfqCNKXhryU4fMSmVdsm7dPSMVzcV489EZriLR3VEKqM0r5BKBLVxYwRA6laHaXHx4uf+Er3ynA4K6LJ/py11AQ7VBgXG1L2J3ZX5WMcMFaZaQOI6tIOrjRZzXpByjIrc2ZMHwWara2lzDk2dGnHVny760QG8uH79xVck02PC+r9SgivllR6FRRteHW+NG/9QIQBMRaejUS5mbXUe0RWXxz4Ff4vPixaqkyQUiSmzT0gLw7IWU02SGt1yZd2s5CWbfE7POew/fr959LzSs3/SLDtLJepd9+PuaeKXFIcZPZEsf8KVosefcrMqQpFxdBcLFr0F9B/oWTZPig9T5pSEq0t/UmX8gT181iUygdJ9mJ/wt/pDRFk2RkVGHcUrjs91OuHNP0LmjGKQzY5OKSndARwbBPKah2Nd0KzIPBbr2GOWUjJzM4k6c1lAujC1/R+H6UyJBX70aesFAJ1gWQllxpWcDdIXHhi61j5iHIITCuCEv/bKfpWV8czbflcFmcTfR8JyxQ6gDCRQn2iZcZow/fbj8zAFUVO8ThfiszVxPlxCyqrWKmzSYlPMmpg+pu+ViZ292tFtbjPRvMp/MvIGF+Av1x5VkMgmptYoWw3PGaUNe9xay7xX3MWG4NMAwfSYlvslaWi6n+CyZ2ArKVtEI7j00SsYLj5BfFdO2lar3WBjpt6AaEyMCi6fQyWwhksarPFhS9Gcnqfr+ThTSsbGS+ocLoXMG6iNVdH7ASMrMVVkdqQK7rvE+J/xc38q9l7HB+JiiESTLf5nCHrOuaHVRSolO0eUH3uZxYRskOC266taYW1rKkxKU7CYuAFALj6roZhI878oj0Zh3LRgZ5NYQ0MeYX8ayfvwTR6JNwLV6LXuUhfMFGcRrNwzrVjh6zxlXR58BAyvHPO7dluqKlp9cZw4X/h6jVT/sQVquxmWTp6PfI6xfv8sex7Oi4gjnqGglufMwf2Yga0KooJHcWmJ59sDxOfmXYhbgSgwpi18iNTy1jW89N+S/qf9WMbc/q984Q9WDWKmhm3SYzIkkoAm3aeEuCgxnLAqNOgOy3ZlXKXWV1wceISqJbQhtB8oMnAD/PwaTN2RX0T62/SKIDJWvcP4LKASKtNvQAHYGVcUERFduXZHwl64s9QHR/xa20azUTxKB8hAvau+7ER8PzTbdOX7268vsdWv+pTBsF5hKx8PM1ywx5otfHc2+kF7ZUfxSwBIO1dThcFzZpcAvvPsiKfoNoyWCZZdl506ksXFvOQTL+RJLHoe0WP8z3kYe4TV/VkYG+Ky5BDi95/9BQtok94/lewXaFrhaWAXO3fppcX7PHz+Ws8hVk0fNpT/e7ZD3QMNsOx7kD2A44qBAb2v3vTFlS79e/4f4qbLnFLnnnaoX15Z8WthFmj9pZ9u+jQ3IqVVT+Xd4/dlnkl3wtv5lo0ginSkwV1LU4PgOF/gjQ147r+oZNO76lFGu+bQLdSyVemJPtZbZ9SmhieV/6TFV08QStcoTVIPBEv05/gn+Gij2ftRlY+Q66p3aSl3D9HN+eEIgUX3s5PqEvCu5qcuHrExbZ/ffasSm+cVfMKFAwtCqZr6CgUzBiNYHWmMl7BZGD04rfo6FSCGz38HGAe6K0VQTi38Ln1S7vuf+T/UN8YF26lVpxLVsV5o4Cx8Fr3wXqyEkV8vlLM7Mc0CRFmYG9x+0zRZDZHcZ5YJ/m8hPGH5mEsgmHGgXz+uvUDRCvApUovxnM7O2/3mz08yjAr2T4LaGwrkIL/f6VGN6qoZfLW+MIT4mKo0rXGMKurE0VQ+RkI79qdsRhbAB1WNKQw0LQElwsk4jR74TuABdszQdbnlsfFO2TqtzTAEmlNsVDtkUSLlL4X2D2LUUVAQtNxS3RT/oaROCGPr2WGE5cG7qTw/9wHSW2GxJsvyz2QIwNxJrhDc68jv73yoFXvrZmkQNP1+YKA0ide49cMC43hRvC6Wc4CdzEQeVj4hyyu/TPXjElCRC/uIc+Bc831oKJwGrQi1vOL2iQlWy6OxSa4LZNzrFnztWP1p1TPCL0uFJ/gOwtzPhLH8r18RiZsKLRW4HH44aLp6V7Wg5UTRBD4+01xh0+e6rd3hLoY60ic/2lTCulMVyEnX5FsbVu/CFqkE3kw1AqIVhPUHBwpEnCx1VYQM03kyKVkqVe59K4RZXDJGvxx9i6b2PqILO8/PJUUwkUBykGhyIwiSvx2jxMkSeKBg+dX3glCUrrlv23dmzaMlfSZTRP6ZBErg7QnmlgSGs/AR1HTKOqELlQd7m/zbb3+Kj+1dpH97YkPp0LzELTVgU4uSZfmuqhbSIdOToewHSKpVDk6NqCAP2Em1iNOd/5kiyOCkWZaCcRIYw7jbRBAv/T19Vnm5XuZpUDgJIvImIo5FIjoi4NtC36YCxTFLaTNugmAit1LFRJJHmd7dioGHiGni/qsXEFagQLndbdzP8ll1h6QcQugZbGDLSiyOHoULmQPt2JOVhUVw2eD6HuGWogAbZ9foebYR+mShSYL9DysIdFDGrlPyhIutCUk1gLwQiKFHAsDORAp4WuAALRZuDmcErV7k6vPguNu2Ews4wdp4SmKy4wJfWZxAGG+B0VR8aoVuuUHeJaMrrAUkV3CFEuqKWAv1WppUxtJGmdwDLhEAZjeEReU3CgQRdHxcFCWnXwu1qAdBBNPMnskAAEAASURBVKx+xhpDGzmSiXfVyFq3NUh/IA02qAVwYAf/z2SATzSx8g7JD8zEj41VSv9TuJqsSov5lEcLJP9pR+Np86IhzdbS6x60+FS53rnJsYJB794SI5uK6pmZ/TF0CcN8outhQRXui1emFlEt0FoDtKBVplJOVnubJ1Ca2MGTHKOU930+SNWK+J5/SNR5t6kkahmrdc4UxVW76nuyPAu57sFcuKLbuxjWJpNJAzWDx/xG5H1tSYJAXzpCWdL4mre42Xy83BL2KdpJJenAZ6ahonCXN9+5cVtzDV8KS4qjjjAP1A0gsNUkVjihqsYq3wgpsSmJYoj/V4wdAUqrkzCMsnkxhhD1gp/e5yeWHEsDvozRK/AAVvkGh9sVI4a+XhDyjVVY+ZFgETzhpxtQSG40igtfDnZEuEWJpT7EqnaeXon3XckAM3m4LflngbXm5L1CDClaO+uO026trrrr36yAhRMS+ktxT55wAxQaaWC+W2drwaqtcH6vEuXgh4tlZgJUrFXvlFfuOjTXF7+skim13UFdV1Cv/ItCtLCf5zpCeAXG5m0qCDKF5DdBc4K2ogCGQFU61j/Nh14msoVIpkBdRbk0Ka7lhu4M59vyBqw21jBZlbgCkqr8c/lc5rUjSUsIDtSuczfxJRiy3leXnatTrW4bVkFYiHm4OafKloktABFAVvJjKlRCNsyE64e0FlWCGw9A7qx+4CQKjTBpxMJRd0FybSbChFR2ldHb3f2R7kpFF/+DW7VC2XrOY23k901pryYKk+KOSX0T2lABmUiE1bRpMV6CdKDEuq8CIO1u1zPnOrenoZs6gSg4qcYnJwVLDVK030tWhpxf3ujdlqfsTLQ6dQXORWESBpyVjTQ8TMDhGMVhVk67kQ9MvpXsXYLK9L3+AcA0MgFzydhkytiX6ybbywnwKL+WkNnEvIsF04U3FSsv7IJ6QRKrp+otqmo5p78f+B0H/n23QU3BGbVxpZZ8CmaUUOmZ/OlnmtyAeOfuJetX2A9aMwJtUIWDC/t6YT8sh8TKtIIylzhtmw0Hb+LqHAkP1/0sJgzGaYIcJ4orb08f/tcNxi9zcv3UzqWozmwwpJwAaX3qYIXK5PS3vldffn8OsmbFzxElG9Cgxbp+v5HqmiHVPPdR7ZHzYACCZk2TEHpm6jdKE4/J7Ro7DurMTL7aEn44bz54aM1CdfRkSHe+EiPEH4mRiXDdXEMg8mRHxHXZwgT69+PQrtuqZSDdSpkOHcDu7IYWLnt1vdGTyLyi+Wf6nqBBdVK3f/d0eBqjrKbifRm0wIFYwkilYF3cggUwqbsxjZXfLubFnijrgJJM3fGXurjrxQtrai6vduinIoqXJiv9EJgtQUFKUkq0zq2cazC7fwTBvp8T2Z0sHbOQtCaMC4QrQJFodmRjSQS5kcDMxijvCrbHfa5kArHExTUjGYEAFYKghMhzOmFCSNtzJCbnbKL2G+vjY9FsyvB8QGshxWcVs7pcIdYNxE3kBwZ92dydm3ha3rb1tF0lDUqDO2ADsGl6lc0GAVETsLq2UVVrzRu9YdQ1p5McHK2cb4Q12Gp/3eVilDDc+6N8yTwpbqzcHQT9asTN98hKFBRfEaXI626eS2VrqEfkU6T0kuXjkumErhcA2r2ujdIgQ1IzIC8onb5AwkH/mkdhlSN12r0MTKCYfPx21QiXa5GuRGKM42d8Xfmpb9OOCtwm7+CCxqhqo6sa41N0xJ6Rh/ypZnDRIGjQLxyJnV6tYcQ4SKAaxvoJIziWQSo5E7sYiDLj1KTAB+OLDXPKk4OIp+uE/05g0auPP5dqAx2tpc95T0hEc5d/1UVXXDpfcNwkTFxXtpBdPtL1M0uu5tv0fpKZ1fY+Ie8ZMPM+hfuSjUVfqJ+5zjDgIVh8tb5kygPx3GO4Hpb35sYvDqrw4xPuczf4bgqamWqNLbnfg1sMip49rII+3jPYZCLNQjlzl2AgJC5YmuAaqVODiUjDOhMR/Q6xixsTcHDDsooRmYqUSGtXOHRIMiv6QQkYScDqCHTn6ruc30gbjggRFWh/BRQo/l0qtZLlwbrP9sAjyO2v9GCdp7Ne4g5QnHQQN/jzRNc8Q4SrF/nrEXWi7g8q1N0FEOQ9rpJ9Cq14jgUZrV5RVnKjHTO+L9Kp0BqZijkV2OpRwqQTXJYa5gw/bjSB1tqrhm/dudOQf5Ad5ggYTv6glnkyAo1A4XgjdUUJatkEKy0I0++2PFFNO/nPN5Nwip8O8Zq1ya/ZIKza6h13RU8z3zV7DR8SBJEQnpIgBc7bv+b7Qt+YsE2bN46PQ5qQaIzoxvRVjAC9YwrhAq/vL4IPgoyBqEacgQzqMhb5oJWtYrb4hajJqkz6/e3kXGl3w0hi+Kel4KE9QQaS/q6hVTWRyjCfQ+zyt+Kh5TgfN40/elU+IgYWUEYB/hsR0gZIEiADpSvHrbK8leW/+eTYbcTBSysA/IhNQdH7tL+WTjNUabzmzDIoWE1D39z0DhqLBLbKXgP7ywZaqSeqfoqNLD91l6gBkxfIZBXt6AXqqwVZbYcqtaCbBAZf1EZfZ50mfXYDpIAZA53MFwVPqqI1zOqV5bFlpb88x7yWacFS4t2mnfUvEuezdUykmy/9qa4mDyU5AzTAXIuAJiB6Zz8uV6VFs6SB3s3ZGYSVbroY8r/YL3sM/2iRyGqlLSmRPm8lZtfJKFwetGUs37sD88Ec7ElZVi7BeyYVBl5hgnXdLHFYWQyRdEMXCY0ll6qgTS9ub7aGyuU61jHlbWUnWetsOkA3Lvfxptr83rGtySr511ktPlj/8oUkzXLiot1UGflK8N2GUDEqsflhs0DijO/diRC0dDaUalv47eDY+83gKakObcMKiiMHvgVV0vquNVsJPDHYSxBKPrzQxCOPCKiWVO7Uf25FZy3tNb5kFIYUifgwYCh4IXPT7VMJPJPWvIlgXN0VO5bdyoFdMSWSP/5f/ugSkAY9lY64yYdDagaBHf7qGMr8znPuWuDqcVOR5yYW4pbl67e5LEhMcSOI1uG7pWYcxaPiLFlDaCpqRtNgWOHE9sX8F3Qk2/i/m7i8uUCVwFc4Lfaq/8FNvtoz3M9fTjTUNsVgTqUrELmwRxvHytUihfh+ny9xv+VU5tAqHgrPr32jCn5RmbY+ZexI8e0zzgJVXOJMuqrDhwNQhgXIgNh8ebWhdo8ADV0+4EyTGPkAFiqhc4qJb4opE2D+kd4KO7e+vlLA/3cbryL7uDQHeDlNFWBUqMkTpMmlNAW1AtEQbG2bjQdNV+xKoo+QzgwuKIyeEWEZqLWceRR/mAXEBkJP5iKuVISRVCyGVW5ijJ7wsBZtZ5f6TucFgig3b1AWzGXau8N//LUynIDaOWXMMPIMeebzZdFLYFzipiH7Kk5JFxRoLTSy51jDBRN3JJeSm9xLH+Y3LfU1/BZQ1XGpHjGooIe63XqUxV89kX42ulxuYRRthdpmkPLjn0tsZJEY/6pAqGAfFNgVC5KT8X6J+m5LqGKQ6VwYSZCMON7hDmF0uWJTE0lP1TVY8R2hNCFoIo7pmB4+DdnjvNrHUPzT0oqyRERkrqx+dZKZ38h+GaEsJC5n/IrFxrMMVLJBMe2aTsdRC4H1ssDdcAWL/6si0h5CJ45RK1wxJ8l4FHiFEaf8bDXhGyTVKxW0JVQjNL4b2h/sqjrpX3x4dYg7AMFImcBICACr+yrNUArohbE6uHpC+7Qeimc9c63ykvtOV3+5W0hnnKDc6GOgsHawBFhy+ctjzEaoPcXngSrnqsUAaUiMDGEQZRqVQv1FJaotwr7slXMu67SQvpjis8Mo3FXDP18CGaQGHoN8eUH8wo3/LYJ6nHsMtmobkjYNUEFujzUQ/dr/TDIJOv5S9Mo4Ra936Qr7b6dgaErucLeUFGf40UcGSrAH9P51gpOKggXtPwwEepwgsJEcac7+rSYENQByX8Wgrgr4JXmQJH8CFdDL+O1Wxi1F/wrbGm5pgkcq9WP/bRY0lIqKwIOQMfdEI8mNn+eHpz6tkQ6SpJqpPiMEnDQanwNXRdpBHc+bqqDJIlwtl2H2q+zwf4ZRyJihfCQDO8ctUsZpagZbImVS4I3bP+3B4fl+W65T7rcT2qrPv8Hv7hX+pjrdILPwLAOCIobDF1rljsnrvwqDF0WB6Qx8+a4C4tqKcRGD60ErwRQhjcZjb1YDdiRrQ9MFtUmOL2NQ1Xz+m5RuiGkXi9ouio2mxLWDtYpoANrJrxolfywHo7EoRnR7vF9psrGZFxxwBTfyfXGUz5zL2+sAdBN/NzszeyyzsAbX55pKde7k1bAA9mt9FroYoB9IntCOYEPbcvRkId4vZLUra7ir23ToEmVA/wZI/cuk5+6pePtFWTwHpzTTPqwzcQyOdD+Lz9lOaAqhivWIc7Yf5y0Rddx707gtAYoOmdrUeVVuAb9xg0uJx3QxiYkpv5vYJ+ZgU/QReGj3tp7NKGEaqOgagbKtAFTq7waJJ+SYSKuTcgiLhr2sNQQmwQ7gk/qM8QCa84sfvFbAQao7mx0TagnbpHdNozRFihHhO3fXvJP1ntVRUtWYS/+bpIL+9C9z+pLyVMbziKecZYiZ4ErcdgUewUqxFtW0BLAbIHuJosqP0u6bp1hlelmkiNemnf6CrmQ1JGcAwnB0sYYT9xu/5hCLZeE8yJ4FST9kQsK1we18loBvpUJyWJeC8wT/XCU8r8KFqUB4rEJ61hPFkMwq4QgvEILdo3gL/t863dckhXgRKNNErwfaCOyxwfurn3O4F2uHHviv8+6BNFguLkkNZfENVv83hZviwWMsc1k+wmwDB0mlqepSkQjmzoJ5+krr/vOhGoym8ATPmhKX6/Kdvmbd3REJpLXaVWV0cLHncwve0Qt6iDFCuJm+fys/YrvRTkTvl5a2nuCPvdsH9PQ+H1zokp/QE+EsRDAoAwuIrivKkCv84CI/Ep9Sr1XKC+pP912LZv70QNVVOTh3/BK1qg1kzZw2uBeGPGwkrxTmP/NDXDcNort7mGrQymBqYM2CsUdzswhB3CH0RH7CXk0pp78n7KA4/rJf6zDFp56uLkbIKspsd5e2M2DweVkuJwEx1L9wfPIdmAWcc5quoD/2jYkK1tWyr3UGHKjSfPm2pYJqfbd2/qyWtaqoo6XhmfFFMKtteyYLhhZb5fwYfDBZRWxYTHPXq72tIJBCV4S0PxDXogcs1RSoFs6mo7HZdZhPUQKh0OrMTfy+RupdF9DqOWpUANou/sM7M+dgWDbIArXDaINsLt1jKNNmFhUAaa1aKfEpg3lYBxsMfuk9BjRLM5IK0R5/sIawtAgxEAcNATdCn5MPLROzVz72VyuLHEP52vNFIuDY/c6QX44PBIlgcQU+5YrSRX0Y5MZcplA+WCsZ2JMDg5NVqZvcmUklcEqVg+5oy4CVXozcP8TMkiK31Pf2aydFiQy+KUtPkeE4HnqLNt1gLo3yaJC9P62FlaqA1GLN8mo1xkXToEFZIVxgqZXyzX5Cg/iPJgAYO/p8ShAy7qD//KGkKe+0tm5lh7CUOYBN7BxRN9Q7Kyb+F2SCq7ta+kTZ1quQD2pmPsA9Udz73eMTlM7yJlYjqiCv736WOXyNiqUPwzVz7iUqXUG4Xv9pQjridGS7j2deWx9B0pRc7rtIo50Edo2x3W5FRas4+6+sMIEI8hdUaeJoEUz+1csB6DABX+4FrDMs54ByG/twFnhNDTyCa0HEDeNV5jQ62bKVUKmrNyuozqUdr7BP9kf5VeU0n8jZFma8ZwPpIGGm5rWiwU1UewMINhBu8RtKMbTrFoIQZlY1Fr9lj4JRe93NzEE+XgDiibyucAlSvg6DtMBgOHv2rJ6/j1MDnws6saIJtRSrac9sKflmn8aqhIHZT46V/QkzoJjzod7iSfzLC1ImeHmAnCrch9lVmeyFqCnE2odTe59J2m1JVfXRdvmVM5X+BP04iB8jvZWXlIduUhiQjApz/7rphD4DmBILEzXNjTny/QvygjpU8gq0VXxHJsSsULVI0Ib7Dpm+sax/66qXluW4L3+WPqsDjBodfkeTUKxaeNnUCzNqGT8Y/jOG64AElLRVQIAdFNIu8eAUKpiNhBnbfEo6w3/DkGouNPPGZAbufxcLKKJXcS5xeMnVAoWSHxT51BVorLufkTeUxUdycKZOAJV4qeL/chPkbFOT3V/36QZAGh1cYXX8Y+1fp6NecAx3srQ0vxm3XCcvbBfUfmnlBAiRGjIFzIt6EWT5lvW3i63VIxn1g/xTFjjVbDwBx0UaARmaHiBQmA1yQbkdQoOw7QU/3CrQpHIz0WKf3UYxmPhmkoKj3PeT7OWqOJWZ2b96KrmswqMs7geHYAp0sMTXQCci3ltFIvFLIzxF1WCjQW7xJjc6YA4y7Dm8I5vMyCLUpgwKCpoVqsYQrsgtt23/Yb+qPAslCfh9i1xXOiCesY4AqwEm0SQ3Jzt0XFnvuq03jHW5UWxgmbL9krboUzKnqJVg6fmsJTfbe6FSjbVexJsLQO6Htj4KPKGvfR5Ng3JqTlc7GZ1IN2x9sJw0WvWhYvyY2X6EDa2MJc+VIUJNZs1g9GB/lZS2/BbZjlqDPruCrQBpJsOgapU2+cK0ZYNBf3F3i0hSOuWO31mPFdoh7FWIDdjcLx1CPhFS/uvVLBw6x3XD8JO9sWuUdKo2sKpgyGBY6keZ0rT+/AC1J2LB7KqmNh+MyjS7oHhiUZL5lIcB6Ra1nK3BbEWQ1Oq539pegex6Fh1o9BMCsjUIIEyPz4T/4qLra8WR7XRAr/Db7pNlqKVKXnQN5KXdIHlcxXJGGZL+UuPQakkT3I4SKW3ocitKwI09REF3R/DCSgIF9Zfzoz9lZhVx5i3x09ozlpFiNtitRrUGhAlEqiM+bIB/gwaf7B6BFmwRVGIsOyEd6F6HAF8Ebvhk33I+H4632ptHuqcmw3vebSoV0PBFKRs+jFRq8nK9MQli4lo9NISj8YZMhOnzN6Qa13een8J76/8XK7dWh7CSzGu17otS+ubOsDi/Fj/Lv5iE7iMFZcM/BBVOWdTmq/T93kdB6To3gu+Q/Zs+ZAVoDkBEdvAnC13AnMNt/zKNy8H4Jm2uq332UjKOeDbIL+e4Dp9w7M48Jk7crd/RZ/12ggknHbskA/2+P1bDDiJ1psHowpYXlRU4991UyZW7uTkW48JNkk07egyU+Qi3KIWT4UzoCdI71KzlX0dWnlAZfnwLGKKABeWw32vrH/tWAFRVxSaBZsiaQo2kRTnORBYe7//4AYJ6BBHzbeZWcSttcVz8AQY9XtgODpbiQXGSv76CiUAI6myDlotjWA7VXzfEoq5e3/upd/1UUyTTy3G/qPgXf2lVJ1vIIN7BUtLq5/tWUYDI46skTypTsM3v6hF91/KtcvGFlaTLKbAxikXNdA1WwZtY6mPQnEGaXOvsP/2XUEWnFn8n8NWNRiVbRKoMIchEYQ7lSmJa36f9gH9RMhlLBNPxPEBAi+sm210iC6uNuNcjaoU2Du/y58tEY7/V3Fj+bfze0hvXCx3HvJMOOJpL8ONH73JqaeHiJ1kt8iknDN/vgb1dlgfgXro/xV/SdgacK1/RCvrX7FeI9FYsizUKzOU1QuvbouTmyv22MFSiWVG0JkZQQBOoAFxiEGzQ86wEUgIlztFMQsTslGEPmn1XgbIw2MnSyP+640uF9YqC2XRNN4IilN/yA6bXWrd3pSs+4rzA4Lh6X+OMlAmkIaF8+p/bwYcV/soCR8cSZqUHpef+a+4HfgHb+XIGTm/x8TcoRQjU52ce7yosf4Aliit4c6SlzBuBqnpjX4leyX/9FTD6iQez4uyloIMx0s+PQfCpv/l6hKkskWCZwTWIAPAy3HAH/I8sBt1eJsHSwTYrHbZH+q9Su739jwS1ZwifJlRAGaAEwcfcrbzZLtw9eShyTCdq4KbbVe0Y2KOZauHvQh8i8e+jt488fLAKXi1tKj87xDUF3TkO6XFZwm1t0fc33z2uigi/Kob0x/L+oczPdcmIAq0f8dHQZSgT47L1MlUdRHp96ctitS5OKsS5y/YHkQFRLJ0lMTljvP1FBajd3B/qHhscQ8zM5hZPjHaL6fihJ+Q7iaGBd+DKgWBReQRlPU6BvTB8bRWRsglaO5n3G8D0p+nXABTb9TkMSA78hGK8Y7QA8q1KwPX+xY98qOIOPyKiVAOQC4MJRzlFfFf/0eJTPhrC235NLIOEDDf1RJqBdIuUMpF2a9M2FxUVHAZDLzCjnAbHtvV8pA5i0yGA8Hq5Gm7x7/08F98Afn+6pY6GanxdOcNlNTqWBv2/6UNbPOQoEv4Yl58e7fK/3FLMla+5LhmvVHNQYVeJhjIG+NkAt3k2Z64oZWCUz9OJD46xcRzLKoqaElqoV0gyQpGt/ifShwvu+8xgRpkCJ9jVZD1HGdsvLNjimKr4i/Af9972uWrdwjdV2+f7RbHdbT2z1baA67XkEnQzgvFfaceWb4968xb3I7MQhrP9j7QzcKfyioTnQ8gBHNN/Ns/8i7n2kP7bZ/8mDRbA/m79aT4cGEQf1XWD2IoXZDs4TCGIXT5TOFE6ZMDPaOxWsVTeDTKavk9wPa05SuafBSZsljxBvi47pXpdk5iN/uNKj/KgL5OHwREoWKfzMdi24SJ2JJPxfKQs3fzfmSgCAlYqb3jkVGbBzLx7trSuvpNK3JYLAxC3BBVoYdC4OZeTvtbp78WF09AC27TVDjN8vE+VdJ8rGtEHLU7DiFcgMkexNRCNDbSEB023EG5wwWdbhW3CepLMXwbmmgpSKT0FNVc+8pVVVNNW/uWfsqWHy2KlccG1a/yCK/iFo0GWysfW5jHucey+lso7Qd18jhW6GP0IKxygZ1mxtSyLb1TVTMwPdalz/Nh2cFM41Zz7RVun3nwkPsB6kD/vDuea7x7u86ztkB+Gv4I+0TQq3aQHxPVhiV+G2ATaVrSKiBs/K34xTagZKNKmNECG4kkw9ywF6L/ldP9HzdP6dqihHH8pd0yCjICMbnRHSBUG2W4oSFClwd1186gUEdRbLFlGVwEEy/CWfTNRWwcV87nLVz9AfYknfKT2Ibz6cKxvyNBtSda6y0XvdjYNxOOAyzzYj7yZsuwoJ8EMcoYerIP4LZsSYlWdFWwYsryZUGsQFLiWNg39dvw8/qQGXq3qTT1La7pBAmMZ/gt6daxSiBQy6cSPahq8KOhQavBdMZ/YQGl+Q6SsDoFZZRo2G1Gt7Vgel8MNHS0y6ef2XfyMGgH7XWh++bCFSPrQHFqjp+c9twGHm68UIWnznyKBRxlu6VuJG9zU9y8N7DW6CLfUykY13FyduT6bOhGBBut9XJYGWzZaUMcL4FL6EUX2gGlwX/pvSiiLpjSo1GwDF1/jrRChVaZu6kUCyKirn91M5hLUv+VcjGdsq9Dshv/2gFR4mqHU3UXjq5Zf201ZIIAvw9P6CF2T1pPc8oJDBYxjnFXmFtZLxddbr67QaI36b/6LWJDgka6r2MtoMsAt6Wgyi97H9vnYB2BkRybKq0QfXxUVR8a1eCMZNH4T1uxLt51Lkdrf8L6ADNJu4CICtyxCZqii+657ZHT7T9u2/ZQ8gbCj6DU/epbf8bcyD043Hx2FeK7RLZWZeqxgVu6My4sZqzJVVgb6Q4LtbuBKMN0+HTKXm+7XgFNnQeDqPWcv0jVyJWnoZ1atFOQoK9SOi8avh0oBLAX6pyhfxVS8xEHErbMki0CrF2eZSJE/jS8WmU6eARtvHn5M0mTGzJ/STiGZ9R/cl7wS/HSA8rpAXPEfTc+j6QW3RR0u1fwzyixojBDdjTI2dWhTgCToGdgh94hPtAAIiPTomlAz+hUfSQPRT/r93ApVY9n7MXo+pbU5/NSnKNJutwb4mZ14suculvSaVYWL1or1DWNvQB7LB7vqp2/XXPrXd0PQXx+Y9YuXAbbIld7m696n7OuE7vDzbzqJiboG356gyoTxuTPqM+x1scNVdBiEzpE9ei/aXUx/9Wmw3t+f7lzS6ur4kD6hcfQR2O+aYZ7ZfQsRthmeTBE/olJjjl3cxX1M1qbjqIN/sD63C/RuFQ7eh6UavH9ONyzq70zWgnE2U7Er1rSSb3rcT6pxWgU5NxpCadcu8tANnykGupbiunOFF/H8De/WGrxZafl/KsLi0oCPtYaBFuMOsU1szNUilo/an5phMafmotIDC4eBV7TmIPpdkN9/1rk3QHlJU/I4I0PwjQreD53kYlsocpAfDZFBSlfup6cpXdvotfIx31uHtXbYwsBq0xqbKJdSwtLDs7pYqNVs//qFSMFrZqBOWYSoeRvaaKtJ9TXl/0OBd3/tREJ0xGN7tOvt25WA4MqqSxuSqWMsr7MjedvddIDtISXzMCgdI2j5Dk70TiKuNHlWixvdL3M8rrcNiEs/qn4ppUwoCzLYguWF3rFcUt1XMvH45rlF5hWBrOgRJJHaR77MT9n2UxOGmam1hN6h8ykrKf+0LVyW8QvFj1otK3+DUJL/i84MQZorUJTfJgLwXaV+7NGsBO09uUId/O7ZdtSRzFht91FV31XvxKzfx1c+ANGxgW4QqgMWlh5jo/utkjibc10XMK7mBnGwsnLwL2V/1RXw5SCLwLDBLlV+4l0B7awtUUThuvdWwSqQj96ey0nBCjQ204CrIZjTxNySh42WKQ1S7O3RzCZrQ7D+2dYslq+BXzqR51Rpx01xtj8TZfZvsu/aeh9ESjXpTSnWBDWQljE2C9LXmfdUeUq7VJDAKKWcZMAEzVtjDTAgxSQ+asbZ2zEPqI6iQcIz0xqL0qbrQm6m4HIsgtrAqtPvPmk6SerVCdyb6qrrZX28yqwBzlQIgabE43bFo9gpOkEOzFYUP+yW+hezHE2pBBUwD+Xc7T/wsiuMUhHz0JZmFiUBV4jshIK3SYY9pvn1xmpAAqr3JwdDPL2rW9Gd2VqyWb6XwMXfTckdfdIUgyw1HxDfpUspf9yNcOiZRLMfZC1mLV5NrNUyeQoApttw0T9odu10fxXM/8w1YiHdU3sJHYrp7vAlyIHqmS6yF8U4tSg9M0FLlKyXtUbXn6Qw9R9yoWcdi0ylE3f3efmi5nRr30k9d/pt0HkoI5FDDsB6K7UtBd79apygs7sCU6VjTZDJ15zjTfwn1Awre3lfIbZTLiwVFJ+ArhHE/NbOo67gYr17Q84zf5QnGr3P7etQApwUUzzloANjXo20Vv5FSsHAUNXTUMaoeH4Mw45nqUJzxPVgZnOIF1BgB0L/VQ4t9EvTnfEje3fG+mtx27nkI5QbF7SfydbdiQY1tMhax6xB8cWEarMJqA1g137WWmSQifC0IVuOU2XtsAApjuSGHLMmfcLtuaXymccLSgEVSAEP/eqe+S2YVfo8sICWdpruCv0WCYnpWmSVcQWtQmiOlqdDpLA00PQFIok/5tv3lDZN05SB0hlRAFZjLcDtKKT+Y512qXV1nUmzSFT6LniB1NxZ/tF89PjK41N1I3xCZGzMLrB4VZ2i+TfnXNo5isDsAQ+eW3H9JFwSFYVbshuWb6oSfOqJ/sxri7JdHfBhVQZmEimvkUpzEa3us/a6BG5dUZg6oq5pp56wS/9TGReLxtSzAmcSrWCW8AU0QVrc2k2+YiLSWJnBqq4Oxw+GS1xYsfVXIDIgAag2ulYXs8zyNEBdB5/xxP/+EjpYTwH7XJfHlWfGhPUFO0Ogil+hyfTp892ZGQFpTFCqhODHDg168P8JM3iGEAEik26huWr/Kj3pXQLQm9rARoZ2KkGeDdJI5QuquzONVbJtLlV3nH+PxOQCcJsQSMjWoD8Gu53wZd+3DJMiI/LHsyL53x487lOptB/gmjZzqz4EqNVf4qu63g/vFa6sh2CJaLS7CuC7nHCLToM1eF/KZ8cuRybhLiPD75zOb7FkLf6vux2lQNuvbMfHC4HA0QOnmKtETvFSGIRBecR+4uedDt4qBBp7xqZBnNnuADf771ksxh3MXNxGs9hRzueLWcX3n1Vtr+J6+QjSXcTnalARJl8rp0JuehkMrcFSZlQ99mn/xZttTlpQ5VzjQwpbsrZVMw7Hkl90y6qE6GjV98N6vWtdY+i6O7JHaC5P+MkOOdidR1F378L3OCQDXdV8OInnbv7vkXZs4NRVGN9Um7gcBRhXHv70ASl6VBTYNl/mfd+tun8F0oOUDhrZ8LskzMmBiJtvrhYg00zDulZbyYPSr4GpKhP9V2sV6978Qbxs5JtoHn+CYGMrVSuZQRY7NqtPszpgRlqM2vAbb0uI+G150NN3Kme939uIfsW7uaKgVY20ZKGV0p0xPxhTm3UUH7xgAyli8pTGvRWdoGdUgKN+dZsamkq8QA/1aSFKcZGWDSG3AEZFIx9BNabmeJKuylBWqWowCw18o4iL8A+qKEtNk9o4FOHGAPhiNEmLtTcxK6q6I99/TyCu33B38brPL79KC8ws2/MrvKNIYSK3+65cHZxNaihI/Dn6+FY6iQbLJm6jtXmpierP+MLfn6shoCJoAbdcYEGclB7A7FFI0dzcfMCyWBw/zCGmOaJ0yrfGB/zUY+rm/Je46uMFue9ZGUQdkyeC31R5fK3uDFojgA4uGQ56bfTCdDuUueL2HxJA2HTAf5O9J9HuUFL8+nf8uNugdxhqgpETK+CpWNoKL4FiP63YYqtAbwbB+SY6O9Y/LKv3qXegJ+Vz64I/E78UEi0ZjX0ykBJbmhnsiuxLKaGgOO5QIiYQi9Se53mEK89ndp06RXUHdC+2UAEJJ8kX6ZLrvhHR8GWsUlk5fCkGx0WgpVC7fS48oHS81crLELV0CtrUcxSDcvQxkJMyDRekHKSeNN9UejwNWMPxLPzcqCN7JtEIjQ72Rszm8iswAD/e99rVybcVnwIVXLU//MMJ8tfSiyiIgnJLt881fuZrbyOc1RYBIP0rsAZ8PspnhG9xkfKgKdaDE3CNAfDZsRIsipezKaTZYMPJ2ytFCUZ6DLI+vcO3fuaXMaKyrVJdC6z24BA9ya5MNNxUG3HVB80dLm1P2kaMYm0kJReoX9zzT3fDIMXOxTCjy4Q6Z7QgMbzCyP2UNHwwI3f9uBGf4XdnNvhVKyStxioPqOLtLzxSZZcEwiFVUdWGoog5it+udrkl0+spnzGBWKp8PXtPguNBxF3hAjUCed2SCkwefdwCRkdL1+R3Ck28FVxN6gsBDRFKUmlxCHVfUpnrnUFbR1rmzX7/OdexYQCgxYA6M6flAGPksLLJmw1ZjklY3AWFe/k1ieBzXx3s6q3cxGgpklAUJpxGkUM4t2GXf0qHww1VBPihJLcYaNK2fmojQ+yvmT5RWRBGJOmWizV5rh/cd0mBRK5AM9CWb8DsqPe4DIhG/c0MTPnEfs98tNTkKEUyTBiY0IL0UoR51zb/ooWaXieMDYwrtNfeYh73LG/aGkOiVVjd70ukrjvdJkCkKqYRQh+zOUQ3qAL1WlWDy7QVwTxiE3g++SzCLhCOlPqh681V7zn6gtGgf+fKO+yJdvuMPbyqVEKaTat91581q6GBQdyniodqVFPXFDeBDE/pzuy4YBmMoVvkhiRRgPwGod3EuXpzCZVRYf3y5EKdwyB3ggX1beUkeJAS5mGI0olwd/9STbaHlxERJTFi0Bz/eYkmY7QglGumwU/KPEaW3E6I0JXcr/OT+Q5WnorGubvDivth2q7j3NwvYalkxPD3H5P03Bor79UTUHrgvsjiytX0NeuhjlKDqC781o7RwlPO2qQs02TPkpAT34BXMdnsPQhimj4mnpW9kvINtNbKqGZ259k2z9+ppAhSEZ+AgmTe6kVidGX4VKXOJIkPvcKX/A3xQL/yHAlgjXv6gkLnwBITuF+9DR5dyHLLmKV80WjMHuRqsx6ci8iXScCmgciGDRsXthwiu/OPkdeww5zWfMIHqgeRVG2f+vtjxM+1J8sVktT6Gb8rGYTQg2nsSaQt0aYqvx8aw26QMcUZE/+0hin0EzEIZo+6Dq7C+Cr+ygD416FnNMFsV5UlB3+UZR2ukubc3RfASzNUppXIPdpbsyaxKPR0J5haPybaXsJgP+mL22wPPQKiDPLoKnv0f006LqaTTBtw8ak6lq3mix+aTZ8NQ5shKZo7YqqrFrn8ZELUVCogy7convUgjt4mE7y+fSGtIcJyKFvhvjVIsfOSIN9cwht1fc4VGyO/KJRBOeiQf+gkWZtteTsArkiJjORvLXTLKOjuf6MTjF4vJnG6tc6Ef7FYOn5Avsnt97pRzaWjsrSvCsSVYksTNdNd6Mr0KqZ5ebfpYDO3ZkcZX31pT3qwEuQO2rsgQy1fJZUi1g8NLfp7ALKT30tktb2UgvtxJ8In/V/4O4ggvSM+FWIFRRqf2GK4XEPiGAO1kXCEzFHvtPuCuqUapAl8tcxoByWkc/5HaB1zdivKFP4zp0J0qCqALxLQSsUPPeTfCk+FxT/SVRGc1QcBbS64QcntYEoBu32IAgeOfW6EdUfVkt/8SvKLq7pIJLMV0oGhDvuVvx1ARMtMYn52dPQz2tM/27aYCFZgv/nVCwxPVCvzMi6Ako1Dr2L5Rm/9ZmQYUMwkEHK7Jcd9rIqylAEET7XQA8Q7J4vMOHDakoPk/2HjfNvOTtQMfj11aowxvvuNdpH2vk1JQK2rpmYAIwZE3UjpwoArNM5+0RcJQwlCicCAW64JMuYFalX2IJ9w0aaBkVMd9BrxyXThHwRwH0QyntSUdDRWAnJK+2EHGmI7YTKjfiaT2KdQ/Wy+k/aRiMLfpP06KianyIj2WuajZTwU3sEO0Q5B0T9pE0cArpjpvN5kbKxTdqi8VEwOo13Kgg3z9nTPQVMCTG92E27yVHDJH7F6j9dFuA9WDF+xD8hSeWWOyBy3nH78QPgYfm2p6wji/BIjZwkvOwDL8o3T6WlNfGomQmWZyKW98//+3d7dSt9WE4U/NYwUxuuRCCsbOFBwf/R2t7j5k7XrZwom/8SAS2eMuXVU/Rutkzy98TSe5CcNsUZx9Ex/PV3l3+vsr5+0uszcGaX1euxr3YnT6gc1GIxTklGKD9QDKTiRdBj+bDJ5Wc5HigGZP60Qq0/8Gyo3u1Erpz2jOBZIZ1kMUQH6W0YuPY012OJS8iHM9K9UUpiFbCi55G79svL0Lh/ZMhtYXXnlZg75yvt8gTBXYUxjwT1L4MvVEjvZ/zGA+nEVc0pGoSz14rriX4eys97qjZpjfCsK1QPUJdz70QDKhhUgi6R7oFCIN2/lXbwZYS9CgDFhKg3Gr+DAouu3c4PIgXWPhmFdnysKsnvpr364Oizmyn7UzVxnrvS+EjC2kkOiq5lylHNfl0oh+e8uplK+i99kGnLLM7Fgg/cAQEFZ+FwW5bezF9eyiUmOGwR1RMzbUsFerwrQd6xEdGxJ706ppILCFLf1Wv6afpzGZiuxE8YIBdIVOyvjyQwcaMKUoDL1V3EYnI4FkGgMbDAAf53zMMddVwah/LArvA7FV5B9uE2Ob/5tMX8MrVVppbgjomtqjTq+i+5sU75AmzOR1cUjJj+9LpoYdj7vt35u+ZkunKdRyipuJoIg/I9iih3ezc7kLGRnA+VpEosgM0/h26zp/BFYdbN/0Uxrx7lhfnYrNWhXbRkqFrCLIX0fxXFR0bKcN3YW3HewpQiko62Uvm1hJFeQFTzRO1hA2KP1iBwZEM3zw5dXxA3rUFkHoQ1WoAHtK2u3EcRsyCCvXqxmm3Gq799GigqKCCj5fmKk1iOui6+bBkSxnjVlKQHhbFSqaF+Wt6diVNZ1v7utnfY6SSGYOW71uyQZaBnS6P3WQ8FVBkvTPy7fVSpqEQZLz0Nh+/OQ1QBf429ZNAodVVuNKtzD6ZQ46o17ufwUnt/tkfEgj1F+1Om/htD6zz6gahfzS1ipr+qzx5VSE/opou8CcosidnZdaApd2r+dxaYCEIgR+yRWVqdbA/TVcqdT9FGZvBDpNmXWzVc4ogdPpcqe+7pf9qOR105Q33yyQmcg6z32VHCqz3/1nt3PaHQRMS2InS/GfjuOo6OESfDaoK6YylzK6951DQySCY79AXzSfhflpexUd4ZwBER2MaH1yaVpnFgHIfK136oq2J5bguJR7/iZTBF8xXSFLMlnExJn7+zAICg0SoTUdbedPd7dD45QYCcDZ4xU5MuGypEcio0z3XVy0b81gOAsR8vId6EJ0pdQsdh3DqJbH+IuhpjKThws+BFEHERWaZq1ej+vxW4BooJAmbXpCuGAg514K36ZKPX9ifKhqb7IF2G4jBQEuzNsRxg1PfS/FpQBVMS9Vg2Hpz8+1Cy28Jw+S+j8JMvkV81W4/yLFj712W/w2mtUlF6fwr7tC1dxAcA5Np4nJELJOgvLyTfZkybwiW3Mrem+ERzVUCbyQICnhwH523T3yQ8bjYIh5Gtt9v0HcK9o64R07GExrhXn+7j8VHbYTr1nmtCo92GB4mnQgm3XacdcCYE3FXWjmuzqBIaWOAFai2VsXZ9lh54KhmgNtbexWg4FcG1v5XOKfU8XXGx+IlBIdLFWpLQcPscYRg5mp5IYiG9BX7ovhDWaWJiFV4EW4B0POcgR5Wr/bunMafcwqAGiZtiT34ks5au3idSrm0qATk52fuYGuIXrbdvUWbfjXWRwr+x7HgxGX+h1tyLebQPbVwkAptdUCTP1fXnJbmvBv0Pt+Zr3/OyEKuGPdVJczHvs8U21YRRBMp1eBbFqOWySc/xWnr0YeyDlqSogXLzW2lcli/3ipd/2zUei2ar8lvydapBPJ8yxz2tTV6GuQmAdGTSpZtJjd7PTxhbrY8JU+NxlY8kDT/q3AluuuOailMU31HNBBqMWaWUmWWnqC0+oiHSYJAlVg4sxTOC2fPmPsUfUT4/n8Qibo0RnCJGkGlqePnM9g6QAvVRwY61FrYHsP33QForGKgjWDJhwfz+ICD3+FJUioUYNYzAoxAxWaagoCbo+DaRfXVppeXhX8y1bAUEJo6yTfJu6yqgnHRIDT2JBjR75krO+14mOLSz0obLauH0bYTuAnC8s/WBiW9oQdnvnQPXZa0DvYacyuRItpi/3yUa5VA8hSqYpRnTmun2+9eS/08MZKct2XCJ3oUOw1hb2eqVqEZH2OaEOPvzOSEjF+Ze6xIeua80dC1bN7FY7A3t+o+S9iE4e9j4kmKeAN9BojKlGrqtKY8nXWS/HJaNQlwq+qR3K5d3nSFZ46WduqgQ5t4jFr2pyLX63piBElHI25op1ATerhctoue9SiUv+QLlxDQtBSUayAsGrTDRdYvXmQQ6yVVPWGRkxYvO+lZ7g5+hM8Uy0weOq/QNU7yEdu+iG3f+F1dAD/+dYf/QCDd4HQ4dy6wGNS6XLSd/re0kvcZFmgAcEYqlg8lIxoZjALopw6OyoRvcqPAiDHx7/RZptV1MSarmE1KU7d8XTjx8rkWzsNvwVr68v7C80GBQDJ0ySisfqwhp/LtmfYOOnMDoUYf9CKvUtqBlihxEY2D24AwkJ/5ynE2QfTdiWqx06aND/RCagXaYMaYWdgxSb80FNsSuPqlwqOw8Oy8ZB5qTXvSEgzJi4fYfxtd6NZKvPF35VZhEB9f9h8v6IPBEszdvAS2HpORMhLINfiqN1RA7ZoZNsGYvYoskVdyCYJ9OhH4U0RY9GZG0/rWIV23UBLRfS+xHwFijk8H8EwmBz/suyrkYhwcu93Zof0mM6wQtsQZReyF9qPusy2aQHHafMCp+2xOb22jbFDka6OLTQI9r96UOZ/pp95tULd2EXig1WnJQKEHC6r755xwGFxMlfoKIlO3aXahqdo3cSuH3P/Zas/rvnXaER2Ki+Qb3eP2+qJgAj8tyNQqOUGcFQQRdyPfWD+KrwqEDBrMzkvTHEpxr3J8coMT0/IDx4Ka21OhYTwqI1L19Bi7Jp/PUlIrJhrJ2lD6zXKonUwMT7P/ODHpZ7Jd5mOWXU0kFSfvkqqgSaE576S+1SMw5EUMffiNhwGW9Ik8gqainILW5sC9uR5VyHFXqe3FjjoKyiQVtSs2oPK4VhNhVL33utvCoHt8XnKxX44kgx1SrWDc8rxv+Kc6wdxIdevm2OrBwVM5An66TCC7U2VZX5HsmScohaTvr3+eDTRL+GEuJ05BdH/ffTOUShj61uNtJhbH8cY+rSQWvBigSqW7WdA2NUZHjwvvnjlTBznVYSr8ANeUrcqbJBOwsGWa5NReG1quvAMMaB9GDTzveNRbZYD1nko9R9q/M7Lojz4J3w0C5NHeQTTboBgJJ3W4+651AcjSawYDPoTdDX4Feov9RVccE2HHlYTnCrVjatgWIA0MS/k4ls9aVvPkwtThZDaRDCBuLuu653tErsCWKwHVREQ0OqN/hXcxRHqSHg4A72aIeUAjTQok6QuJMDnrqjTPXOzc0bgYSqtvLyR4fFuddWyBgENhH+5njKTEYPBj8fDz2lJTOVdwcYiRJzHJl2PMwnyazSOOLQWLVCXoSYaL7TwowJkZ1viiIyNr+zAK8MIyKLRSlauMPHaWzYzcqCNd5ppQqFvXmpnM66Ae08ViFfgnBf+MfgFnvsXEa1XV+zRv0apmdif/pnI6MBrZjd1/8EOLwC3vCWW+YR42usUJxsfPgphq93kT7tuYAoAfE3oz7Q3wrgjMSDy720uuykUlB0Boc/CTmRJtgJcJ4Zf0dlt553FXot01bVaylOibUxi399Ee8NEqFMBINb6hZP91cSYivStBUqLuyoeHv2M5oG9vskdOFmH9B1sdtd8+DQ4dDT98k4aVIewUX5NTO64jkxKbD42YTlDRKoj5fLUgdfoG131+N+cuDD/NUt+mSUzqjVpgqznLfWmqb6moRUycJJ6MuKtLhxYTTJbQk4Czxx5Dhp9krxjCK66fhx3O6Tui5FoccWgtX9V6zHAmTEs+dMwKa/B4SnMnJGCdKOHSICqdP3ooamxQczODcmJnPWXD7GShO0D6DxnY2qXKliNdHBwtQD2Mt54h7v+QSGEcOClGemQ9yITSwqFxdLbLHbH8MIJWxUz17W53ojZ0i1s2xYKUZ1yAZFs5yYs8G6dZY/Orcji8iv3bqDoNxtlQEVFo+5FGlcq4eEVH7z+ERCDeT2P6xlZHDeENNYDgTnHZjnrHVTgdvBfHx1hoI2+YWoCuWMr0LWi+9rxQObk2fLZMSAVZHpGIgYwCxWGPppreFT6PO02fiT9KV8012+2zfGge7eQiUK2NwnZjonld4Se4+fMWQpgoluGTTEIv8qyhbw2YHf4sD36uDK7GZUmVfM976gYs766h9Z9P8vVFsY5EA8fGZDk7el1HtWSozbIplP/Yeam5decLfIW3Qo6jd6RAzbqRBWM/gr1SuKIQyQgEaZWmeEENfHyJp3dCKSrR7rHpktd+tfdSBLLPtYlGFr6fBF8vXk59f+wEXfEUfXMPkU3aDhlJcg9qDiHegLaf1fW5LFnykHxMnQU7UD5ZMbSYELqoo5xRdpDxzhvfx47XRFStpajnkqAVPVEg3X0E5B1Mfdld+bs9Amww3Fy6x8gIYuf65wHjR6e4jlAEBLyZX8v9uv+nFQZ2pdR2ugz1lrhtKJuWkGLJkzlOAqPNL1sB9QC2gEcO1keohdjJL/Zr5UWGUUAaIJo3MMtNksCAXy8Z8ppXb19FPutyMFBl8qSNlvgcINXP3LKK5ZnYkAA/CM3t4W2+CgcJfduqqwZNwK+qp/WAsbKE4q1C7aoqxXGOV2hAvX8WfAA+1OQ+0sKMDyrqVSyrC/3SXK2c23K3OxYnPt3oEBgoIESiUrsqFqM5bV3jCro225iv55ahKYwqw50j22R+ErDVlMvm4iKRFHs6ITyvopOCiH5yZWWVZDbFUJxjIg4lw0Id7BW94AeQ5AW78vh0BP+gHNDvglVVZfIzSDuSyoz6bOaAK8mI5RhWDAv7Q4vZSuq/tVWpSxxP/sDpZXpZYxyBzyBvjkrI5+lUtKYpfP3Gge8bkfNA22li0UC+80Ocs05lj35evO/uG4KE3l7nwR1CQqCpdAWLk/jkWFWuaPrFCzhCKJ4Y2yj+bjUL0tdbA3SXOZb/0YUJEC5DYh8KadEdBTMvWr3Og//cwts++THiRY1zht+qRvyzx3yWOUJU2qXfaRBb/cijK7rof2+McN7R0GE3dCFXecvYLTx+DBegFO7MTGZlNgD6EY2iBvLsxHCwNnDtReBmvGQNv3Z4K8FMTAd2DlaFYWED2INt8mHFxvP9oCrMAyI+bdQ11aiwG9SiKj4R7NR+3N14EDQgTVHfZfLB2lskUD+Uqx/YzBwLjXdrDPjWd+xP6CK4SsgjZIY5p8ReHbxJw6eaJf1oYlP3tp5NQmLVYMFeBnULk76FZ1f0Lix6/9Q7CT1v9xDXpzW0Hj7PpzAfO5Y0/gbU+BxUdpq1guktiNdfskjPD6OkdHl1zDnJI1XpBxrPEOevanqwyZ5POOFAr/JjQt4wWzDWIcG+y1Ur53uZhE5s/vM2Uj6gzxEh1ttGpPHwtLCkrVI26IvUVLfF973Y/IQks7I5IO/WI7ZCR3wiKOytx/kpP76I0iCWr7qiKe8zz3a8Hn/sUEadjMs3rtYlQfeqVzSDxmnDAhXk2pWtC+qdaLBSDy67abSFezrB1CHuCwDX5n/61Ef6qS+D2LkfOmpSdiPo3Ad/tGNBgD9ANtiYcE3EuWHukfu8FGz7uZg27cIuMRszQCB+3OfnXl+Ln8juV3kTpKi2f53UrfsKZU6a8HRKOaKm5/Yb2K7StmJZ2yAxuJzOon/P3wQHGvpng87vahEtffA6a9AH9zTN7cxa6DstglCRDFjUFu+uetKVLXDBzm0fA4lWcOLY6WCAsPfwxS4l3MkI44amAOY1J//A/Es2cs35zwCWqf6tDvdl0F9sxlLHJc0G1F/et+VdIl336hz79HNDbUpaHSVjs5TU/jG4o263Xi+yCGQb07KMtNvvyh/0L0hq8HY2S6v0ky3Q9WIwNxJ/FdTKiEB7t8zwcpW0UV7mt0FAv5FeGq/GLIhsA8jw3T12xBzoKoUIwrHC0ZTq9npOnTEg6bqGjFK4gnli7y3azJfU0DU4nmgxjjfFah3zyW5JW+w51Ozp1JsVBSURE1F1PIdP+UBSaUogrw+cYIna+f7dvFoFR1HCV8BNpvfjq/KTmoAL0caAM1wH3AhDiEby27KCz4SVnZk7nxNIdTKjfMpS0qQkvvBOFFuBtXK0M87x5s2ITGdsJRpOrfFatigHDrBB/EjkwDOfKLskOCmkUhvEcLz1aMDxsfI5Ov0sbnuqilVF+/5zHZKjDvA9oIQm1QTm2DmLEce7m+xpcqciDcBQo2IkSWVMvp2D+rVVVCCeVhgcM0WHCyozvk7BikHSHlHJy+RD310nGUL3Gb6mEwEC71eL7f3DSSjhXf0G/mICOkxh8pICIW6EumJk4UsIwH4/0E6rHuYnjq+3xkkRnj7WMHjSA17Ad5/5H8BpcTVut8ea6qqY3ks4a803ggCK56ye1h4lASgCKhVEoJaR5YixXEQ1zIjVX4tSzYuVEbgji1TyDt4VTRh2cpSzYXpnaDB+gp8IEiDTQ3j7VaPoiDpXov8QB9KgC5xCrlPh4GohX4sAnLY6UM+R5eVGbBOZ1uf84IK0BK/guLdcCXQ3V0Vkub5WOBvuioJmuZzAhVSb5JdOU0zSo80+Wfye+8SLDcAsb1MR3FAUgujlBwTiTlg9xsdU/Z7nUuHyyBacoaFEVuEKUREFYD/jjgyy6ZtpXLaosStjFvJXITqQsgB7+GJen+CVRgVSbRX5h6Cy8hZ67hmue/Yn09Tvs2pSJPuivAV0jdksGv5zYnjv/XqPoS6P9u1zg0azPTtKxBbL06fq4QBZ/0kF4vXJkxue/YLgEJAWCvqjClmJHajkRyMRKzAABAAElEQVQFpbsoRW6CQyTjG2GkH514FGIZD05L1a+Xc2fy2TnGJ5+iOV7bzg5YccYVq3MpKLcq6xNV0Va797Q2026aGH7QIRFmAbgrVgOUYa/cRr9w76WxIulDLsrv+4/VEPOU8ZbXl6MfnCB4hWm8Nm15Q9oV332d2SyDPS6bUslJZ27JoiLe49dJVl/hDi7AT2QGxYdqCPRUYN/N6ytb/tqAPI1rXf/HEJuyMsWG9l3qlz58sOaebx7uI0OLZfeg6uCgkAknMom3L7kQ9NpfX4Dme7ccbsUjSH/FQSOwCujb1KhIrnvAJ/KkHu0aPZatmcWd5qJ09tgfFz/OJ5u42ndKrofYBdByuKyF1A3QdqCCZVJuAWq1X9AWWBwFDne3bWioBdDmoGXtBeB9S/cm1EzODoA2kun1wPXWbWm0ZBfgQ0hyPSkOXJ0OeKv/T4UAVKT2BBd/Jpl5qA71I01j7fyrpl/7KVoIrTYq5aIdoFawIyPJYV8GlhO4BgTZD5lxY8rhPZEtaUIyzM2O/svGkUvo5MBedq3iEakHivQnv4Yx/07zp7zVOQmg9vzuUXnGb4x+S+UzibAcCAEjkE/dT0fxodPJlwghuv08kZ6N8VGDa1bP3tLAUYx/cIjnnE1WaVpL8+0JE8nFeQJwr6dV8N8/Y8lYWcE/BMT/FwrgoOneIOm7w4vF5VEJaYLVsMIRwAKtMmEOmF/Zj23kAYGUNJJIxFdyxXyHO9oAfRX/OZbxLwNzIu73nGAxFXMcxgOoC2pZmScG7ARMkbmeE4mRE6GSwF/7wALBdW6kBXRJKLFLoHDJoVsYpM1NyOp2/4lCdL4T5tw2drM4V3/t2rcYXk0fhAaPYcjDx7SGFMv3zxZhsKcsEP3RwI69uluY9oENkVAb1+VaCrRyWWBaHcUVhXuQCjj9ZXU9NrTVHr4aFm/lBhsfyuy+t5W4SoFsTfn99GQGhKDRtzlUt6Ci7FcP1sWNe0rTy/wLXBXvGv4yBBkZZ7ccQWLx+AbH+Y28I6ClBhmo1u6RPGwSK8xHW1YRXXeE75qOQhbR/tv+14aCVCXLuHSn7OhML47NoSD6jfEJsx+ObZqgCn2RxRWB7a7t8iAUWYd7n2lHTeL/i/JIEiJ8oa9aQI8K+ShaBFlLXle1Niwu4dxUFWQg8FCldHkTtSCF0o570r7MK9z1cNGRoBdi71Hw90C1OnasNzC/tffn/vk8vXroc9YoImp4LtZ0iNCP+rHbPpH2Pyval+4XWx37yhC63bQNlmntfhvAAf1XtbuGbiDQElD+t/oC9fTpoTU4E60EJjnbboOWWwDgKRpGFP/lZVcoFgH8f/k+049XZalOXyydSMWF93Q1rijJoNlFvN+55h2lzcQItzwadRI/uOlZfOsXWjlL3/dTlFcByUo29Fz+RLdUZYjz54fu4UPhdxd8mzkC+k9pHbsxRx10ESRMgnhPRbxr3xlWkWhK37xYlL+WSQUYe1339P9DAhLhU8R8Y8n8GqzEZK0M85CWw/90urbK7RFqg60qCY9iN5ZhUoOag7zmmvNJytyCatBHNKedMmfSbkVY5UuM9NHow7IzZFSupUuvlor0O3NBVb6gKQ3wTJ0Pk+ONaoTr1VxAiL3zSlwc60n8q/4sS3c2MRvWROg/8julM/cGrkK2J1am31zYItr8srqP4PMI9ZstP4WCbyLAio1J2KikyQQPpWx/jllIp/b4rc9uSQqnpM9YjIzQUpXQSkN6Fl01DTovcUxUFBcb0M5ZHdXJUIHxIhAqGg2FpC0z/Yq6OBF0qtHElbPU67Lg+zYAFIt3pf/mkVGCIjkw00rtxc18hB2XAqeDAgM3xegIygk408thzJAjrRg0g+gUl6ItHFOoYmniFis+xx/SGMkZZKWVVcvve89a9xSKTwAQfVX9KJRp3kO9HcpdMmmVGA0BTYhU9l0gLsyqge82cVWh2q+k/jREbF9nfXCgT9yFNuPYOdo97VPJpSlhAwvJjRF+4QarxQ39VpH4uZ3QXYEzhd8xsYjekH6nDMD+GjBD75k1wa/m68mVB+JXV+0a5Fh0f36bggV8kgEYEfqwDqRyN4HRVSC8vzR7UKQ7CEBZ5sHbnRDY4Yi0N11+7b4kRSBSaTBXxhUlIH7ocG0zno2nun9aGB4EUGmecw14lv0wDRKQ8rvr+Y1HagdnkQET1THrAcEOnx03IMH8thPW9EnKO4hLVaZkcPIQX12d/TLFUMmWJ+OY/Ox8KKXi3ClmVd6/smllGdXJX0dzLzbhfSzmP+ihbNeKf04YBvIp8A6+iybacyNaStkPPdL8Pp+KuuNTCSyGj9XH2qIvdfau2ZxKBRWaYknLgXAsvldJvvh8XlNq+ZjoIFXlm2hB6B09Wo98rpd17xsa0EU1sZ6n1wnkJbeCd0eJeNpBHUsx4r55IsofYoaRCAlvk6YYDYs46wuCWs3J24G87lOrg2LIdM6KIykuvFBMJrS8AcrTCoVH37bGxdTZPgVRy50KeMdUWsI59M9QmyzSSNwN4L4iNMHlXu0vEMBVgYsY+Fw4+xDtq7Mb8qkUmRUIzyWoxilElOcy8b/CCFtJVDqXJTt5at/pbR+l4NgVTLe6pd6mZEM3ExSwAqE6uvhH+YJgDN18Tz3WfOamKgr1ERJGkPzmF4jICYUUpb1m0tGjgKsVFfN7B+E/lGwp/zwTQFPB8NA43nuqSM5IKIF//Tz/e1/WVG1c65hYszYteMrYUdXPzZZqiYrD5UR20Rg6IsyPOxsfaokMPFbP4KWgQt1RZJRCH8A4Mj6Wcvld6C190DAkXfmcCNuc/S+sx8rOjbSwGbv3uy+i8ODm/QGOD2Fg6oQq8aMYbqpKnSNw85ie9UhWnZKK4EdocYroiY3rqBGgUt38Dwd1BcaYSSwaRTmGMkLHWNrEVPZ91HN8kb90rvoPEmT5BH8euuIyF9Oq1srKXFDgPl3t/+W3MGjhnKUbHYmPXnpotXgJ8qudqzXrIpZUmCAk/TKlPdVyN4kdhvrWjYNjggkh5ZD7sZer7ia8ApG+fOIw0CHjw2KoyOl9zKstybxCUE388AqiA2zPH5Pr+FUIbENkkscvE5yvq0bw/ClSFvlvOppnyh38qNif6CwTMERgEl5wRLWwDcWBASIxOTMxnwXmofVQACwLdloOqMiBajPLVtyk7/na8sZpopL91DXws9crhl3BF4uwz8Y+0iZTAmKSEu+gGpCu/15NGfkpNC+RlfkAEkm9/GKaBJ3f+YElGcAqsS4dbj0vKgx/BAyD6Endwrju0yu+pKzvZV9hjygJ3Xh7AmWxhnCKH3NmBZ8RrWHY5qYe6UaV1wakYKPg4rTFNMOlyDwepOLDER/Ns4wUsEKymAt44EtjFCNoSIyvWsgcVqcAKGZCJftuz/30eor5oAtfoPYrNblbPKWIRIaIl/cJQzI1d1AFcQ021ODeVLY/dbqm1hoQZjUFyBesw00NFtnKUxeYrMA7x+LzfqBDYSXN+r6qmHOSkGjWxi3BbvAG4DVaYCxoH8QjVMLYWScOnRWV4ZUKtJPNW/LuwrRrXuEG09IkYjiNaKfqGj5nR2ZZfHkVYuIamN7f3vH2jhWhKDdyDld1S5y0Vyzl3ZRIsMUStEGZHoREZPYWzOVuBn1IzYByCgI9lT8QXGlAx0IeM9U2TFrBdogZPcpaMVhRsKMecSUzBOoA3Un7jKEky2rO7WFawZvy9zGl/xR06YtLbbQd/2UG+riKIZVMiZTP5vKXV3xnSA4l8Y6aCRcgJVcP9ssK/Chz0KPWWyWuaRHWJzoEjqXJf0h/gHjkI4GGn4S/5JgZzIdSC1QFXEa5VSwE8Lb9HgwXJQ2kwBGpff+k8Gg4PMqgXfLyrJjti6ykR2llZfFKkyfnFG5d8LTnSdYSA6ZLuUhjyJVOm85g1qNpxVeEBg3k7j/7rbX9g0RQ2D3o9daa/FZcMgMfov2bfKjwzL7ENMb7dD2Y2Oh0TwM2KLcwRU5CCVCOz88GDvJ/kR27wvJUYKXHndUS6I95d4ee0vV3SfnedDTe3m0dx/PW9Pte+tIF3PyRxS9+KcQT0hHhLlMBn7Zdfn5GpcDcalx07DuPFT+mY1q/ozhGvlX2uwZVvYrXZdB+HrkqgcW1zN/if6SDrXP6KqzTTHlNeQaeRKVXXXwFMyl1dnKwjrq8v326hLO84ir0jzaX9SyqoKw+XaYg8OzOZnRgGA9EtVFvqmDWErIT3F/DhQtISfyfT8WQ445EfAPrSp7dr1xoKb77HeKbYX95D4B4ZTANxuHTKzA5eITxXf3wGpYTJeE3LoKc+/3mxplDcldfwn2SfxsZzYjuJ8yI5wmkVjmcHyWb8mNsf+Bc8knoGg3S809SJ0+/oUVU4Kb4qqoBF08ZQ4+nsWnaOO25ZmrL+4rxje00YD65eRjA81eYnJEdTWRaUgMgzXXQD+5ih8zos9ChSc9TBiQR3ZLR/Jpv6UyE5GixQnn8eVQNu6m975QbSXqGMUcSk/Ob+0WIQldhOOED3KQgyCGegFtMSu7CGSR8JTHXcfn40IV72opZoZ91MYXQL6B/W9rR9c70BS3+dEG7saYtAGBIDZGPUEwhkuhXdrJPaT+obrk2L2Ahzj0/tTxLXGuBat61SGzBCRf2Chx2QTt/8U8lumd9sNYSgnu7tiiUseURkPQRWfq4o7zn4uTzYWVNie9jvPcN+ZqNRJsHAGPP4VvLewL5nMBxSJJrbEt8rod64L3fXTyUMwG5zKRW944quvdlVUFJCjbugmWIVJDp6g2dcfd5k5oGn/Afknf7BsOl8oszNu6qezHY9nF8HjtS9H578sO5RJKezArZB4GHRu0gZ5vQ0XN4syxkMqhRX6kiDkleUXmU8T6/wlDBzfy/52WmSBWvNQlVqOC1OrMSJY8jbYIMYoXhXDXNm4dclqRkEKibKp7NWHzz+PX07QYqkp9qMBcC3CdJi4vgC9SgUZNtkyhbswTLkgbIOPx05ycuUZxdfvn5w1hxQHAUnYtUSL4GFeJQ2zYoC4hJheqeMS6I+EX8lGlwz7dYP1x1VGhJ5Re8InD35wX8NawRPlJTxEcILLEfQZKf/BXkgYrOxkkm8d/ZK/R1v+Lh/hVljmzjJDowiOm4ILSTThgSjYzCB7ZBVFX41VOOSB7jhw6DRcbnxupAn4B1q8OhcUOK8smT/jVShVDd2iHrWnFvn579rTQ+qcs9ioT/x9RZAHhxM38/BVqeUooVd9dSpFAKFCtuRVrcneLu7u7uVtxdCneluHvxw4q7e97Pd/bo/83dbzeZTGSzyWRmMskG3POiEO1FKLFbyZpJksPpaWBjJmsx6BNI+4DNVuq59PvK2NAKk30eQqo0sL6+/m2xggoQpPfBjexB3j/ix00e6BP3AZRUMczelXzC3W9nK6NkgvDjxEDcKN9mOduNGV2YDyuCV4krQXggv/waa2KrCgM8enb9Cj4hASSKcM6waNrsjU8xNjzDX+wkrJhDte3TKiT4EcZPJDPm2ynYSZUsx/XuctcOdhEHgw5gX62EvsxbX/lYCu96GItbJtIMQ3+kkQBKl7frCbsn0QhA8+uzenn0yV6m8CiA2WAO+Bvf/Crn4Qld23F8T7WpguUNlFNXsVE3fd2D3YkoHdQUSMDo9xtGOpbqVgIhGdSb6RWfsogI5SeOvxQDXF1unf0L9l+UQxRVlmwHflcloi0eLgl4y8dMxJAPS47oS8Gf+c6/MSV23qMhdh6S8J+DtclGv6uoJeFGpKhFzGrFMhi6cNvi0/1CJQqnrn7HauZSqCqqjXUBncrXgrWbX/Sxz6bAND4U55tM1VWWNjAFh8oxPLTAoFM7TVQPCKSYABqjsqUwrki+0evorukNxsWdeBUcAp5eB0kwkvfJTl1uKIMTfVBRK9CdHihRzsYrcbNTt/XPnqWXhWw8mDz3tTh/XLzAMBfRgMU5hMmF3N2sJBYnjF7Nt9XvGHYV8b2dHgcerIvA/E/MLkEhQIzHyn82dlhc5SyKf8F6b2+8J3hqnHL7PyZ0KWBaOy26TZ8R+TentBVH6JrdLCzRjal/exfy73HdxCOqmf7vILXCs0w9T5LrmAaesNLRndgRhTriKBB8CWtVmLI7qgHkSe+zNJaoahZI4B22VT5SyoSPvLSDa/tIEsHhSsGLRzz5BPMJSxNuFeV2vFIFDV65EMFHwYX5UokpgyXaMai+Thy+1LMKsZJLt8t0qjFMnmJhpQZZOtbmYFiEcmOsDB6J8T0hh/K8tNt0efMIjpsxR0+wFR9c2H+bx0VUn9jjXdPeKhZbhf4wqGtHbogWuWYznoaP2q19aIqonbCKTv8eLmbrT7+rmRiiYsJkaofipOYaHHGqp0G7MMGVnwPBfowMNSZVGSCwh/01ZL5OG6ma1rHUJaAd7qmW/rtqkhj7WDTsvF9YgHyLE52xfgKuODAQhtqtAInAAF1ZueQcKArL15Bx5wtaqTo4qQEYiyVBAvkpqe0Z9j/EVAKsDJr5cvLJDVTlqZQfySp7YiLVfNIcjOcEuw/y00Vjag4M3O8YnC0Sy2bDwrmO/aW7F2nxW5+FhZsLMOfWgABk/0FLztbuZMyHWTQojtexOlmvEgGAQZVDs83BFYvyD/IvcgBhpy/X2K7iYT+uMXPzOzaJ1AdMwcItpUNSE7fF7IZQVqGGaTdyd55BmQnxg/+W2CV+ROxgB2VrZGKJy9mo00rD6i+Ly4A/kIZ3Z2U/bsJQeu8w/1Hx/3Nrl9kKQvizkmn0aTVm7WMx/TlqO5jH7XQyMMuyIXG/y/u5bPF2sd//Epjqk6f4YY33MkxYYbZrw2alJDpfsFgw4kh+3tYcNoOslT11Muy5dDIWdYicrIIOGMcLNwSFkG7IDj/kCjCa5HTNbyQlyBcjWJba9yWqAEIf+LFS8s62qEWjmTfymZbFz3wocOMmjehx5l15LXAsMGtdzAQpuL1OF0N05Ym0I0R+5DedW2tc+c8BxM4CevjoxcbRyg/at8/Y6o46tbiZ/00zq1Iy5JnjGHfDc1kvdEMetBK6e3KViDGo332nhtgq9BNyrBN0mAFfTVGam1yghFOmjoVkDiDAkTv+bR8+ko5/NgcU8ZClhBj8t8aDCphRycQnVzaKJt8wfCD4YaWfqVFaiwj0EkewSMkKBqclu7HMGsysJIfGmqmkEu2H+uytQScNXJ9hhwC+xUi3ZYlp/v3ccbFsIfgaxe4opMXoiGZtSrbDGVZJgkQu4iVqDqmRUw2sut/6HNS/p6336YMcDFfxVl/J7LO0nsNNSwN/afhLIVL0OblVvBRgqZlZU5GPcpOTpoZLqlrEdQZaf9H8IELDBvE6q9szSPas6u0cFPZMyPIJyRXjVgtAwgAoc1OG89QDdjaNMDD9A8UOLVYo7DXBYa43sP8RPO6b/SmwU2c5IR8nDxB8hhZAi3QzQpGL5pCEUYJtQyX/qPg9YcmF8Jz353GunI6r8iHlXNt7xsUsYdhC6HBuPIM+erDd6sIMEq6lo47Q4Q1P0r1BbS8ykacMXQXWt7KIewfGoqsozk7/fNPddNgTzFRAGXLex8i0WkYa0AlVBeWbkS9gVrOUZoL087wPhFU7OiQ8H0tJdD2dR/e2TPdPYe7024lXQwXY759coTPzXg5rkw4Dj9SMIK5fSKzPlsWaHf4GO0O3YVsgupRlBNJj21Eeh5Dk/JoSmGTDO12ZCK3hEZRN+A8dwxg4e3v39t2+vSonMqNX7jlYvXUM4DP/9EM7n3gvp/AbN6GZ1hKdU0ZrjI2FEshkUy5rQ/9HbnrsQL9+Giu7E4xjp6sdrMfLO72510TK8LNCq45ieXfpSj2FKpAzeJxks24Qm8tn7S02I40BG54CBKdU2u360ixrobVWk4cWosN9R5gWxsBGKiTml6MAPnVb516KkmeoTo/txcKDHr6sJg+KtUcn3KlVGq2N91M+7ZlPMxAJc2DF5/APGwVWqvSALEv9HKO3Uegn/ZtGk0ECi5s0v/FqcEj/OVf3pRiOswJQzhCpJI9Pk0BF2Qv9z9BtBDYXXdV4hiQ53tB6SG7D3ObJ1XiIgxG0cl7+JQnO+WOhSnAw0QHfvwWeqijMv5ARPZ+CRDnUJNi0i5j7I8P+F6H+EXAvZNeS+fMpiMXO+QLBQ0mitoXEMD/oFF8JV8hP+qWOH0gt7bGtmhqS2R9TPJ7rwRoHZLEIrFVxsELNGHsaWXf/B4wNvKOZLl0UobOvPUUDbS/tHi7fs6Pb57nr+jBSovjq8AgcICIlx6ItsTTVKcUafuYC6UJKUdx5n3om466laK2/OvagpjB/CbIj7AGiJCI69HgA7EYXvI9x73t34ycUvBMiBr/ajBmzHk6803GZFrmxS/UGGUVtuaboTkspH/3T6PZ9L/t25cy/iQZaXCM8+ICzy2JosU/7tw0XbGucGjYOTpSHQbBObz0ySOIn/+DK0zRk1zgroO4kk1ujjCpF9NlWmaly9bhbDvoYcdEYuBsvFf+WE7e1ISVUTQjuqF5jdMe35Cs7tlzLvr3tmFap6k8inD4yXeb1Zv79UPpNhXJWwZPhb5Mp4m42kQud/suRDaieTj3bldpk9+PIrIeTDPRRGr/x6XgKW5taxWacnqBTzY25wzs2Gp6M7lUHoHxBJ3BSJGxnMrXCYLv4Vls34jes4fX9nNTgqrQhf2/fSDCvO8piABpxNAEL3/KZEZZ3KPW0f63lTasyNB7if4XQGeW93Y9D64gvNz/f6QMrIgL7DX+dsAwzHtIahy0pNvenO9M0RGeIrLWNp5PJi7VrEcU4cLAK3FIu9vlKhQaSMSdD9nHjZeQKlWN7DsJitZrgMJtpvNnBDn3R6b5XuqCKfssIOxmPYBKbQ79EmaWMceSo1PEUXCnAq0bsIZJBuKJs8ea7mvlqWKefypQLSbirzXPnfI7CQkCbwbWzGx5JxcGbVfEpmksPus0tXrqK8hNJhD9rpvBrSX6CBflLrjVd7GdV0D40qhyM67Iyx0rKqBsUD/hIHrwHwDCkw74epMQ+X6Sn82f2Aa7S4b7/sxV0Olj8k00gEpvbvoLkLcy8RJ/FIYccXLY1OW5ZBYUCQO5Q7lbCPzx2NEjcNMHFgAkMBXST3BXjKQ3OZdBULjMXoMX43jXH+6cvD8kAcbtvydBxeSF6FP9fIVrHFbVG+wSUud6QRRAmIjkW0QkJjxeyaUWLj9ouNeAvvDpvxdwTrSyZwQD9QsK43Gokr+hX/XCWKxZh9qjWR+nYFzpLi6H7aDpfJ6g29qnb1FBqii3D3qKMlKca8JO4SE+3YRLr9CXebEGgOss2Y6wtknRLjfdN5i2EddRzkITLraMR9SkEeoCTmslc8JAJvrbtATapudlww099s+aXg60U0201wx+PHNP/dUlpWPBQdpCLTzkchVtbtY4QE9H33a3duUwTUjol8JGmT3K7w3SIHSC4LnpVWyWmT04ZDFP8ha93TYsb5maWxvpWBo+Bkxoptbyv+A2KD6+Di+3mj/DFZ7DKuMvqIkZX9vk3T0WyT6ITLATL2cnnycUT1jgSX9pXfVeWh8KprvZ+g2mfk2aD04yBxoH3rT6jy7/KEFK53p9OlUO2NEFD/ejPLZftX6SUym90qmQyMXpnVVBXmxtR+WpLn9BXVLaIBuypjxDoFXTejzmsnlCta1UUPP2HqHpr6syAZvwEl34bfl8KDeIGK4G+EXNaHw2sr8BoHbeRUIvpcj+/x+jVtOySQRAGjgOMPETRf+sY1g0ZlE1Cw23N4ap4yskM8rrA/Hb5vC0tMrZdq02Bgo/3cQ7ZJkzh1IjNhzjbw5/0LY9AInNF/8+G3ogtPan0RRtuwVM8ka5rvzL1WQZwkdmklSEuQr7EmufTQ2g0Dtx7Hq2PwZc8UKwro17NUKusc2nwpfqJ/tPdvKhlOgCh1zzgQ1IdTE7HVnI+pGEHmUCBidWjKR9dxzXuqFuFT19cEdDWW1IKzJIMGsXheMdJpeAnNpv3k6XjkuCqj78CdaZm7d5SJCuBy36ZPUZKaGF/sRc2O27QG50JbOXptlUHoHB/b0OgknN1PQuzc+AOoSe3hIe0ra6RKcgk6Iw6vS189WMaqgm+ctwmX5mgUEM7ABPGu0ztsx6DK9GpyJMWkhcMusSxlpg/NsQGE1lK4vigcZr1+yph0U7XrEj7yNLOK/jhphLfLqs43mi1OH7R6UluzqetbiNJjyKcE2jTFFC64Lns6jZ0foknUUx/i55iD8dbwehdsZulszeDWKV5h591daUOuho51fTJ2gtlEobnGDH4Zd00/o5n/QZ6510YiLhE49EKyOM+DitDY+G5oe50EmCH1GbQoFhzPKjOm1GeF6RICYCcYiE2T0H9in9vKynuaTcp3KRKQb80dY+8tERRfYLDSn6VXDzCQ8CQEjlia7nyP+GryRFJbGF47qcsgyu+rD2jRENjrQTwlMFERAkUAQEMvkeOq+t8x3+pUY6XJqcB/lxlkohBEsMwdx4oU1qzzOzJGYlWmZOTZfzId9J1rIuUmUVr+t6Vv3H74rBOXcQ/GKUFtvpkjwxK+ZtL+0rFUQEmV6aBy+iz7aZd4TFWpHYsnh6vgd2uhi3Gm9zrmuorhpaj6asA9BC6MbR061bwE/MhGJAiIjzmhMayhptzimMBRvlVU3zkrxKxQVnJOC5UTGDRH/3C2wfX8TkhGP/Rn01RgtR1r+l1ywnTz8/w2FfNqSW2M4Tur7Dk7vkthtdmuOTneqH/92e7tN1M7XYLE9EoBh/VIpetZZtJA+/KL0zVX/thzJ1hMM+fHPh1/DOTeqsbyi7I8wp3PgrG2gHmGRDA0vA4X0npZY5sKpTeIK9SqLkwy7EQRd+RzL9gSdBeC4SUGvaeccComasDWSTWQZ5roQcBOFzaBtRqSPzx9H0nQAN8hOJ8plirIGe0oD+gsh+CgK4v1dly8ZsCIM2tiGy63Y7PJuR3P5ZSCI3/Pl0D52bIniBf+BpARm3Y0Bislfeq5vUdQmqh2qnRWtJf6E0up+rHS6cnClnKugd14gp1PR+vz5h+Bfb6PK56vdzYcIPhib7PvEdXF9h4XpYZSoleGFEgNirgMSzHcZBV7U+mCZpBt1BGWqPpb5y7/A+z51KdmeBLbGLJT+srmwq4mK//sq1InVyFLhQJ4wFXIQ+nVSfQDWd96rSkHwVW8jHD3TP8/nnf+Psos7TJBYOQk7w1jlgWjsNqayIPyWxKsKXENV4gLkgPn3G/p7/xtywDqxmIyxySiRi5pG2MOaNpxq1r+QtPWnWrhMYTvvSG3z7JfAzEPf9e4r0pR/WNFHbnkjgRTZ2W6SpzYASqQgeqGXTyE4MUKdRv7eeqZ/UFlNYSixbNlf2sO9sJQH1VVnGTaaqmMY21u8lrRFGDagQ08RNaIpXC7zNE5Idrg5kaAO4UIkxPGZ4oMEcFxNTFt5AQM/ma3xUCfDP+D59DZPBn5DcNgmSl6iy3710Da5aFRAQ13C/eftRfCgWtCLVA+7XbODagvFJymiiFCn94S3BlONf2+2orB/3LEfnof650MSQPYQUxMxg2LVBwHWPzhFLHaTA320wi45te2OVlhtTfFV3F88F0jPphar+XjlOuGiNYB3kH2YHzdtHNDaf8sMO+ye9WQLdOkrVV2K0zjIWhJ/CabQc9NrxaxJ0URo+AC52BV9MyS/VJXGwViwvBlvczH4ex89KvemHrIPiIe+HnpxY3tx8f+3pHNAD5QAiWifPsKK4Dc/yAdoF53kQO07ctmXfXDQuB/tvIHOhnD7z91mfaq2I21sXKVy2jhsA+7gULhbga6N7YtPey5I8EEBSL0wwaWC6ZTn8/AtkS12HVRK8yLQMfwUWlu8a/ZHD8xJOFW4EoEb8Cuh+44K/RHX3vBWGC0ZluoU1gPp7mS/cQs6M+MbCE/1eNocrMpOvuFFhcfXkpfAHqt9KoaxHMPQk2VPxvsEqZGQJBjTLoWWSw4X9HZBeVz+R/LgOycv0gyfGljY/oRLa+MYxd88Visc4GW4eDsxUP8d772fH1shcr1aH5CecT1xVOVY5ZQkY1DHObxh+29me6yB8Uj24LZskfXU5nZKtX6wtr/Gv3xFaCEd2HoNLvDN/Ux+dvKmKTUHrbLzkX9yT28Inc4G765rk56qEaqdKBj+uZLG44ncwnagUDdjm2dk1+ipNqLS+h0ejE4vR1C9ntfKmgkvrFZZRFMR+mgN8lVdaIOkUiSfMbF4A7SpI3bwjhz1nRGvFmCrY6L1W7ooDpEX3rU+6RWcZbXVUQnrPWn/LcSSE+8i1dj8UvtZC2dboR6husQ75OrQ2Fm7WHs6zi2FfqXPq8+YlkinPtI81iKQv3mZYCV7MUlytciSDpvg26WmtPim60XfrnnlqbO/XSnxlFhyx8l1yO7ePA7YnuWzXRGAbwVRXywYdE1VbRlugHd+dBhP1GFpko5Nyt37dSknaJNw+W+RKrTorjdwFqYhrFoL3RwmwjQs4AYAhT015TPiOhoN+yJUDwcQqYQgS9WjYiiJpJ8oZa6mAhgs4C9Sk/S+mvZ1V0ZYZ0zmOZTMO2jNXJe/7OMUvGCas92TR1wwJ8LWiBFsGmQjyyqfQJXEqyIEWsFk/rchNfpKqEQORT8P61l/2xtuSin2MOmQ0PsMGP7QgGWCzhGzaRK2yLKx4g5nRSS035BKjDih/rr7h3/m6H/3AQt2ohTqdfkdRezM2Hwj/8XzKO8Qu2sa6BVvnGsCn8Hb3UwMfK6898tFWWppGCV8QmVOXaNC6WCjP2+Hm/cZKSis76BX1Bkm4djTWdryy3wK9FMuChzu7gMWApcsC6gz9CkU7b+gCKJcYKX/szwCEQwjUVCBGatnDJodkwDhqsewC1Kc3i4Cf7hbWGbxkrO8w4aw1FdoNkHKmGHBXKdAy5S0ac39CnPRjwm/E5mpJxQk6jkNL/taq47NYqLBNnd20jT1NF6WvgH0L9zZjPMYTnEocBxnblpg/kXv4V3ZcC9CkpD6wCfvUVxOwoBPLM9pMGco9V8+s/Ofr8qj5hpzVJqdG0ZkGP55cUjCvU3H28SEeDsepKDHA9U4OufwPCucu6aGW5rja9PBH/As/vL0V2Bdv+3BcapBR88ZDL976ApbZ0ErZR3zeV1qlSLAZFXVd/OrpfsbZVsM5FqRgvcjwSy45Vt8PynqT77+Y+WMI09iKTIaawPjvpW85FAq2dqNxyDY1BRECb47jV09GynvlQOBoA9C8F6INDVSe4rOwALtSwM+t0XLutQkdLfWrwzCPGRQDA1dUTDzsbKj+EoRy384Ay+zVfyozmiAri8V5xS/h10v3cZgnR3Ex/wY6zWNHOR2DN7ZyVW48jo5evJD6JcLbx3dajdX9UIRb74KlKxF/Bt3/4cNyzHAmPMEWN5hRQjUrpuKrOU7xb+MFGt2ALTZcCaZ5GoFnAppv0r+VIv54eISx+A7Yqpf1DW7oFYI6nLVGIBj6XqMWfbc/IUlamPizrw0n7oYn3SmaVklLwe3qR/MM0zVuBQV5DFpr2SOP9YjNqzul0ZqLPYrJ5hRwNU9ctMVlwK70whGpulBSPG7FMlABPSV2eMM7imVxCD4I0KeXPp4k/9h6avVPloV39W6jGA2m3GzUK6gQnUpW8xjfB9i5aWfaqgdbqDq95CVnNu8WngWO/BPW92SilISdlU5v7L+ywpDaTLJ+SossoiNem3osH31UORPgB1HH2qW19zckSqlGIfjo9fGKfGhjtB3HwAFGVGhOcOKfS6eOx1sYvaBtqaFG8fEq6Dg6LjcN1Sk+fhscuQJMvxCEZK2fBQ9p1CUMTMoC/jMnhq1knD6JZnwq04SqsYoGNvhadETdN+i90z6m5REb+e+a//Zv06rTYYOaRBFMEHZ6ytEvErDlOKMHtAxyuLlfeZXijw3Hp6RD+VcUlYoHJRCCnwvniQI6pA2eYtrujgFGqMybL9r370n88b0v+10OCzH2Mkb7OmKy1z7utLB0lcwnF+HOe7IK5HFprWfmmCckw2xhXtpDIj+Uf7DhiYwrSrUFOfYqYSfAdEsvB/5S83+0iDmhPu0KynpPGfVUToflzgfZeV7hFYz+Hj2K7OrGLaZzxOL8AnopptWL14491A+eSp4Q1bCOAb7WbqBoppn7BC+AkTRn+yf3W0CdWB9AuIb8Qg7n3z0D2adsajBVSTXK+t2yvHFdMMDRDSF1YFw3HO84VeUkBoWTJqGQ+EEM/BGk6iv9hMZSjnn/yp2qIoI38nxil5wQQCMyDlo3oYjUlu5hW65TUu/oG3+aSoRwFyxfp5fPnMKzPQbOH0zh+p/fy4wztwXOtUqkNTqpWyOiB3Mh5bmwBUAr0AePScEhZe+gryMYWAHRMHdTVSFDEHWcvAmKyNacneIO/pTS0HxP4XDEbo5tQYrGrupsBHcYx/TBpkGL0hDsKSTEjbS0FoGf+SpglWJ8Al+Fo6j3/fNMlSABqhuCD5COHh8BDgMA87pY0NVaLyQlALWCR7cOWzzThoVDFtrTAv3byfB41c7KDYOg4VB97HmyluXljhcp2Ym7jJHRv5s0ZRL3BT9m2vLCWNE48wbLKBuVkEYhzzSS2cJKhWxo92FZkG+13oyZpxhOqcPtt2OvHbE4Y5IfKpJEy1owDhBFlga6s2xMM/gwieHcDGIf8htVflFDsW2UEJKmvt/ZpXrm8LshD18oYkI96HKiAldhiFtBFtKOioh8QCrB6YDwK9YVE/F0SiPbBSmDG98f/RMAL6PgoO/tI+mJmxjAbVd15U2VIBSbTmrs9anHpIGTFALHG+M5glluvEcrTHLwVbjb1RkAFmIrqQNe/LjdkgB+0n6gWzOoclnpe375+7cfNBdQLeY+aD+uEf5jlVIy0P4vPy2f5YxI7iMkpqXJ85IdkNYtKRK5PhQJ3FZqnnqHTu+/YZ5Fg2lXPmL9xCzHvLD29nSpOkEffNMrMAfCuQy03lxbn287YpMDW7L3H8cLkfh1m4mxdStH5DyUKmgGV1qBUrnS2vH3wa4YpP8H03U8uJwIrzS+R24h2DXaVD/VhvhJb1WfBuVCsu9sHuYk70biuflTE/ncWCdCTb8p+5MXwLUt+ikQJt6mVWD1YrdHYga0PkqH//cs3CNVM5TZszvrWrykHviu65DK34spA15aB7vqsmEaZcqDqhK/NR4lT/YgKeq6vrQq5VZDS18wtIK4vTJQEQi16/Et3WJyXhUtX6AtAmYT4z0ozB8cXmZUp49lW7CbltzpK3RUebeeiKKO1+SjhCw6jkSWRO6hO82S58u125nCiFWgHdbBRPZXZXfZkPdeI6YsUizBO4GcuORxwGuReC9f7xWJ82JUA4f3jCMJijcVu+Dq2DZp1NCry1bdfq30HmTQr5Yc7WwWKVWsn9gbUvRqXRUx8rFLRBMV9n0x+tjKLX8XoQkOnzpvzD2W9FaV6BmowRZlvd2jurDx1WXnu6OJkAGg6jkSHuQfVIDrcQzMGG4yWsUvdhC9juyRjzVBX4HiLpxWLCGl3OxpB+pZxCczITXloHOsEIo0Il871RuR7yCcq3Y24Ojn8DOV9zm+BROg6eAKmlbc0Jhcj3rfrA3mmjJRE+Dbf3VaO+cUuJgA47bh6V+8D8BE28fkbGjaocP6+wvHXzR7PfCauU8canNI5Lp19GxE1WVrI6RQSF8J9CFw7WHC8S9ScmYgb579dwkqJe8r8WvthsMS+3qWqqXS1jfg4N3vujy73CLFHe/wwtBpYgIsowJ/8YLda8dCkliPfyeQem2g+vP0ECtaGuYkWxyGT98Mq2w5uSSwAghKX6xysOfL1CoYaAgcJHedoAeZbYXnELqtN49XbWJP96xFT+1QIeJFdW4DzJBGSFtw7YHNvKH1zKcItpETCXxMq3zaGFEn+fZ2/Eug8aLRUDDhezi+3OG+BFeTjTnaH8wIlY4GTUAAmJ4StVTF5R1PSaR3rx9UmcdXeuqsEOVFnZQgFkHAdmzzeU1bY/512oScPzgfBzJ4yGm74C3RVSMngbKnHJHqEv51I6YvKEGcDCnFz6bl/px6sackOAFsWTmsJHfCVmlxFMG70mgD8XVcl4TNJ2GrQu+Q/Wqbjc3nMlZ7JzeAVayXU4aVIRxSrv10DCCSHJMxhYbwUMc2C4ykLSpqBgX18b3RnnUOrR6FtK4H3THnmrqsMByJLKxTGzzx0rBfG3To3nIftBZyRYd+P63DywPXJ37AoUVMNhZYmzSH3RrMPBBgG3M22IgCQkfIqpmVV9Q5Xh4sI6hhTfGOg0loYPbQgBrSBn5FfQkfftjqj5DMWewmgkgzP6FUHqr10rXHX8DXaw8JLl3QKBnpzhv9gQx1c9Epel+FsxDBA9rjB1pGhhETDtbHpK5k5d1S/eeyTh2r+T0MEsx7jbGdPew1Bsf37kAkiMrFJlF1JBY0Sd4zDfYwWCv8w4T2cKwZ/mBEMhPUYQg0/fBGTHfybYbRN5Iuc0We289TIuG6Zs4/UP2QbdUdY/IKFqDpo1a0ewWGSot7sCLSRYR9s0FxVDoqACllx8ZXuDjoM2bvMY8O7u12gu5OO4X/6pJn/UFQIIaDK6IuMB6ios83oKSkUo0WAm5B9t29XC8VgyNKQ28R22L3eWSGeJ5ptVfEXaeiLl7W6btnYVQl0CguMsbkN6Al5KHsAxl9U4+o+Ny3fHkNIzfUFLzFsDsM/yOcxys/6J7KxmWPNfmjxgzjnENja+xI52Cy9ocn9HhNgV34nmZaJM2gpyGp5VQ0i3+IjvJkyQCWIsyS3+VF033EWKpxD0k7pg3Ob2Ywq1NZ+V+aLjAAAT1Nqa05LNKRVl9ZhI8xVX6HkPlDEuEL63aNS5ehZAJYHFnfGymOWSX64HtrzEdqAnco6Vy98T16wd4fKlOfx2HVLROGN6cBmzufT9sjSEvBtPlNl+BqKrtLZw5LjvW8fmISLS6ZXFUSGSNFB3P5QQHIQC4IFFruTzVllATDu/quiZhLGi0dPfU9dSTjNYQhjx8UXU6GaJ+G5oBBpLDa4ZGjnx6JqsPFmuep0+lH4XLe25wzFJecwbIqbHURPfOOPV1eEzkyIyn2rLNXQYjADgZgQyMovLRoUvW3mIUt5/U97nAfR6bf2IuzRX/jaoTZQ0RBnJROWBIwkUOAIG3r6yMtcQqqCXrXUgwfoIUQiFsz0o0+Og1V434V9RHRBptn7cfCB+wUqZR77P5OOIAOb6kSPExFup2izSNWJl1aELlHcUBiq4XY+jpuYUyj2cxntZPzTWH6J0fvsdP/7v0Y2IRpCqdf1kAXhpX+g+bM+2WCVxsya8T7EHRjLqOmT1HVJirHzEjAnwlyDldoXecNt0NoiiO3f+CWbVRDuCj9m0lzc3hYRYJAuSH+5F1bj1tzP+ofG/ANaFlsECerox5wbIgyrKUH1nEvu9hzzWFkW5dsHz/xGuLhM2sC9S9b2I+ikdsQC0HUbZK3tqpKH8pkcv4BwdSwBi/aZJuIb4o/3jLpIsVY9Jkbh3ld//u07IQfODioI1ygGhKY/EYi4Ot9U6uFZbmHjp26UKbtcVpEFKLRcS+UnHeUt9fAY0u6sYStSrBj7EwGWi7UBstaa4Zk4QK3lRlizuxLGwbiBNTSzK27IsuK6S9llaZfpiIptjBPiGl32bUtYfm6d/17dOLt/M6CK2zHShSxsL6I8kFhTkAgLrahrViK/bRwheEoTQyXAli/+CepuBArkRLIxzjEZUF9zHzjyyFR+gNA/D7RqwEVsJm1rsJGJWijf8DPi+gA93V4MC8VdsogZfVJl5fGChWmI+kaViFi7lSO28U1X7nzijR8bk3W+KCOkEOnkKPLXQxeTQ9uFdempG6c9vQnht+BmdMymPFyQzr/S+r8CqdzaSKaQFfU7mYkEYwQXGvPOQLbU8xAC8cUTOD0l5sI8ATfmJHOIxkxbAdnEXV9OJqd97XLNfM7SNm/TvW4Q8U1dN4co1q/9RHSqaYUcwc3NorUk5ecb/eX7HYNDhwIv2alYP/kss5b7fAOHvfaHNORvJLOb2xStJNp7GdSlNoK4m0POPnHvtmwDUSGD3YJsQhJUrykiNBrLwJ5QHDfpG4AnACwwVmdlWcYjiLejm+ZalUmqafWSRuuWaQpX+5FH1vxLgZnArSZ8ZRyu7H1+XeGxGab22SVPwzF+UCzhbmcc7JsHs0XymS4e3/bd7PvSZv53ImuIhaeLWUYMSnDaKktY6dLwwk+J2LU4fIhgIwWRZvIe5vqu9ifVPOmfg2n4aoaESqeZ+1QlaeGCqCIMLBlAQHoE4GDjUtLvnA+4YACYtlQONew1HPBTGh8Omo1b7uNnUP8kh1B9ETaVZEfYyq+IexdeaRYxiUbBnFgHWbHJ2pXatrgDX/9TYYYj8mGZcWPc48bf9B2jaYjKyshiufNfmiWAUM47Ws14c9EOHuKdCv6QqDOaj8aqANwcu+64wNlS4iFfAILleKBErlb6TxVTWkP0c+EsnjMNu9lmi3JF3a3jQK3yIJEhAB5x5/+div/WhajS18hexZdpRll3bd8KaDn6yu6D3U+WIewuZqKVme1oPSjC6rbJmRUhW2HhNm0sfr0+nrDOA8dpyh2HkGMWUkS9yY4XpT9u+3uP4FOQjQCpMAZursruuWWaB8VAeb5IWo/7Riuyi8E6+/1IVMVINsWgACMpi4ZidvzGw/iz8dtsVkyWQmdv0Wq3fIxnUBFQZS2oLUBd2+hsSx79GKTjwv3K/tWzaXqcyf7Rj1p8gSRl2uGvXMd8T2OA76+ncGtGQEMh+rOY74dZ9lnh58nVnE3QfnIxjSuxuI1H+HvHTGwh+tFsZYIFEtMsc9tT6iDicdFhuLwID5spzM7VsRamV5DFlh/b6wWydbOMBqmVgxJrCG9TDouaz+nUylV5+8URZjDyIB0/+3F7fjkPGxOXuINgfIMUnDwjnsYBtiUpJW3NABkSTbDPhqAsbj70pX91OnzFE3RcB+WdJzijNXpZ5sOMsPRN6Re/ip9WzUHogppovP8WtoRj1PwsCO40fY9ItcqxqROLPGe1GUaoF/yiAQ1D90xnu+zmHEoKxxvMCP5xsR70yxIFODEEey+l1YOFb++V6RugfL7AHmjQt6v83N+LC8AviOmD77SvHwMIPivLhxwez4swJKx8eYuBFjWBMMSbuQztJSwfkglQf7Vgf+Q8lap/aATiA+pBufY+e+vGz5wNmOQwbml1xkKQcQds1o5Q7CuF+R/pkynF8XCGIyt+53cHJE5d+SJVSe2WbgFOa1KS+D9Ev62qQMsmNY4JHxkGgdEijooIqEq8qAsAL48iDd3BlYVRkIKwGtFAnvCry7z4JaRNWypMrmtgR5rz/hLdbR6gZVTMecnL3PktcYVjbn4+RKGJ0LvZDGK3m8APdGPRi3BXVyHA58/3YsVelAbRNEoT3fmvqBue0JfIppldNAilamxAKbVZd12YyBd73dmw0M/pzloy+uq+vm1CTWMVfRpj2pQmPztF3U8Mp/nC6hKPoRhk5U+OEOSA/+Eu5DA0sF34TUUB/c4+uoaHghcbS3FjlPacDSvbjWjtMNK+ypR5lIOcrH9Fi2ZaciZK8tTBIS96+HpwKcJgtXqV8vMVu9RRyL0o4LMz77ChMKLC4c61cLsbKZrj6G4u3YkvvrEMd1z+OdA6WKRBfmy3dsCZSzZDDiOFwHKHm84qm/JT8tsgvI/oqjyRFpjk5W3DL4t8aLdkebMU3ms5sKPADjDUccAZAtpnoQRw52AO54O5RTRn+BgQIvtENFMKbHZ0uiVoby+td4kLyvZZmxhfKeqFWS41kFd2OSi3lKG1d5AxrG6fsRYtm9NHrsrWqh+s6chvz3USZD7WVNGZ/qzUvUCgxrRtkXaukjZsgELb6Dlu/ULgvo93Pktt+DGz3VL3KwpDtDkfROU7Ubjw50HZe3XNJLBcBOeTcU/J4SrwZOteuSN9hLXCFw0F9wpJXrAEgGQsdbQTI8lxfdodbq4QSSP53hrXD6S9Er8WuPf+8kUApSCGNsmJNtzbr4re5WiP+daPEyuzxNs+S4iwGD8C7O5fHE2MooJMcSHEDihTBhQS4STtvWAm4QZku3aky8rHw3o0MwSSTgX03kfgdUGcVwkT3bJ79EiSPp69yD70l/louV6kCLsET+9yZlVVcnPC8fPB7lh20SoUQpi6HuZ9+AIEEqN/cf4K56aSRTn0YAuQbNn3kFwTzltU30s12w6nmqeacPlBpfqDosPg65+BvZjE+iaLwWiswGPXNHOxzYkwUrJ8qit+OmOFJHpixNV0Su/oNPFlY8HKiVKciP7fpmjL4FmY6x20kCVdm+G5TrmDDhtwAmNNcFLbkp+/PQhrJDr8wf0+eRiaHf8RJZwi7WizRqWlkPDf26sxi6qTMnaqOxsDblUmCxMEGkpLwQDZURAy7JLCdVReapm8Vpy7ySRo5r+32WUQ5P4OUe1pFgJVZILJHWIZJuNkDv8C+W/eU838aHY71GrdEFbyHTBcoqGf+7cTds9W3kg7DKsKfGUOrkaRGXos0fkLKnIYE5IbBk1gmk9I3+Tp+yz4W/dglzIUi0DKjYzbONhGvQ3Up3AUF9Etoqg95bcxixt+GRrc5ZirQ3C0AEkOsAMn9XpvEPKFrwoNswntKfRpK0RoG1nqmFgkqqAc/JxdSoCqpYVqqYoelVZHuhPNf1WwUyZtiiBKZWUKKHJXRvd7+vMriykhguTqSCxEqRA3JPzkY7//JInlaMZh1AlfEA6u4WLDUuyms0KCa29U9Jr0MgYMkA3ffZEEdL7Uxgp3RiI+EpfWbHvvB7nrWqSILH4ncUpLz0Ap1buPz8q+gZx+ZwfNAJoa5TIwpPAOWKim+ucRIjlAfoS4FtqkoAG4fhGum1cM3WgG11uzhfoMH/fYQkwOgxzluU73u80bZMi5xWtoUpIc4LLF9sqcdY/EeJ58etLPe3SMHkA7HgY5vpU2dT+bqZVA51MeN414uRY0bAw+KTtZxwqzbDPZXWuywrAPs8lyzn2ApBiD/FC9gPwEPiBOwhGwDxYFfdf3ZQycJDyS1a+KMArS/Mm1d+E89vNp1oQSxdTHe1+BWXd9DAepYmPUiIA/Yg9BQWwIyy69y/rg5BvDIVl9qo5GSjXgv4IPUVNiqzrkRES3HlI01rvcxwPYybxEDfv7EYh/a2U887YTz8DNTA7qpoCzX96eU1/5ulOhICGRTBe8EVtmqU/4958E7GSrbB3DT2eKuPd/AG0ZajbdCM5Co3sbWla9h+rr4LIJi7TQHey7CcLWbt+UvfVBB8XKYpavTMtHsGVw1gi+E65feN062tiV4sHwg5sr8BcmRgsEaoJa6nwsixycpPtfl5UToeJ6tUfNey2AcKUJqviF9iiadHDthumah869491s0/PBrDi+FuLvorfolIP1wQ/Ma0Osgszq9wcIP6hJt3vurosPnZ4TZvaW/lgurYfh4DO0SitnJOo4Ka4BmMZK/yCtnhBH/S5U0zFXU6ERj5HG91VMlIqGmCF5qpBhUJGgKGUV2pOLPMvogNyadWPs49L6yB+IuKkMTQUCTvfNvsYKsdbBN9/BokX32Y3LJqbmkYBA5DeCX/44oq4y3XCuelmVwhA2LjYpjK05gg+Ixi9Vx+AMgBn1F5WzjkMwB2csKhc4qQeaadEF2NTKMMhYo9iCl3LZ9xPUjwikFx71DOTL97ip7Rk0V4gQop0jF156/hJoxW64QfkIskiYynqcCpimvXVVHJ8yEScAWVY58G6DfcFRO9WrNKm38xzsl2FZup1vKmDuUNuQ+ik1J9a2E1eqEWkfEQHG4ySfyIsz6uay3Nt5muXKX+15mm7albBYolGoAP+wQzmYGHG8J3IqUhKQigAAQABJREFUy0+ej/qE19ReoliXY7YViB+qq8Evfb5Q/Jskt5tjdNrreuSLICCDNVMGCjhewrwLfzF3Q5C2u1LneUurLG80QMoOyW0HJMvUWdFXKyatjE/usvGLbPS/kuvXMiuL94IuDYaQIvrcUf3PNcxP8PV2AX2SBMEOMvRRsxT+3myf4Gef9gDzXfX1JI+h3dboIRSPagz9Xan2shomg0miV5xlY43qfjhTb5TYX5931ZZnKvUlppMMT5nDOj+e3TXTSJNKANzNNGOgMj/RbY9/4jaZXS0R7/dOEZ+hzlb/dW76KI5VzzekLY+3hYLBM3F3frY9M4w2a2NYaY/0VRLCenKuxaqL2XzoBJmcBsOVksyXAaoAH6ZplXw2sZ7NUaW7wmxB3w2/rKyBBw6lucr6Z6DsdOiaNwSe6Fy2DfK8IgMZE9o8I+8ukOdNZ1s4EYn6gMGrXxxKhLr9UD66CTyTED8qrpLUQFr+79wIEP89fW+zO8E/GHM0IQ7nlRAnMsiNeiNsvMLrqnyGd3JOLo+HGrnBpwYSFrh2sK+dEAbVNyB1mlXMRbwO5YDhuBIgJoS/8ZffMuAwSbPXGH5cBh2Q/jgBC0u0VsqQNcyyz7hVhn3FCMvIaYzDHFMA7FrH3tfgRcwxyPWFsMY8Vq4TalNexj9mttowHCO80Xzq5n52RQ6wifu0xzW/cJEESEoR0aWfqExILs4ls34tLwR4vqqSWLGYPdXhmqCFNgQsgcXIqpKRumgcTrb25+popUBpPzmpy+y4bq5/aQNrOm09DlzuwtiwwJTsQ8aDiZVd1CVtaYHzHKtr0St+7cMCC1SFcvXhDz4e9++OZEmZXXHnkYvsjbVYcFrVk7Nr1kN6M7elHkPBRKmdkhOYSeAY4wGcO5/Qbc+WK1MPPgo0Uc/e31JzJjY2umW2Ez53Rb0uBSWCxKCAcQIJmU0bfM09jDfefEqlbKEqQYQ6qPazzg4P/zirCbYQoFyAeEX4IppimyqFFD9ylQEYrvbvq6cOV0gt2dLuENVqh12aKSeCZbt+l5XU5ZGCJO9OSBH9s5c/V5U82wlfxhEZEQmcKSEZK50h1fV69pGeIZEqBvkKCwrkClEYnY1kU7XnmnKH+K1nQoPYpx/sjV5ScRnNdEJwnQ7gu/yh91zHf90AcjLE5Q2Ey+V/Opc4H9EydKp8h3q4LuMryXJl4BPmUno9jsNaN0zj3pUj6x6yMymaTzfdml5x/L6FRBzOw5PYuwZS8zW73LjXw9z53jZVZiVfpXDJddaIqj0OyDeV1tEnckv2VMM1hqtWrwqFMNEXpvkQy5xMjg0RPwLOlu0tquDxUbdaCnzfavLcOK9xA7+oStZaQgoVFcLd1fbnkqQek0gVsf+mUBjzllkpiaIoWUIsIiJu1hcCHSsDDSq+wSopXdU8d7Wp1I/uC3QBSFe+DcpDe06q5GLmq+u2leapVTRZ6E/bUk7vFRJu90MWnM3iQAA3OisvZq0tFbgxo/3+oc71b65ELUYI+6ukxVyjW12pVlLLani/+0D/ce7q6Vvhp8K4fbynwij3mXVkk7uiKhjddXQ5iwbKg1EDM7HYDIrYYbBD1TInwhSGqrTrTAuOQHpA1lckryA3i6f6gDfrHLn83vf5LliqfTCmtJQ/Up0mXMdjWkuGMqQ0MOUEkBvkN1944t/Dzr7LtpvwYmqnDR7bwcOrUfdDfp1W53pbhTTZyVTOtdlJeBcp6BSy4ld+/C5zm6kaSleE44Q9qBIRrlV/pg/JIygrrldzSXN/0MKJgnKttBOFcyDvyaaM8S14RBbcEaoyccBY3weLXJJyhuxChDjZFi3wJP+Jy6EYEHhijQWdqSrVYY5iqawU2dThZzu0df9Unh4zM9SFMJRHSYM4Dvj5Du9MB4/PXRVD+FWcBQ8Cg18IvnGYVYmChNoXKf4fJu+Sv63Ziyj+z8iKJIEF29ewb6kI6k9PkQ3lRv/OdUgmkzbBUKuWoi6TQ8wmbROgruLMLIqmE475UUQtQQYX1fVJ/xAj3mPKR79A+xASJAOG7OHoVkN2ZBxPqDe/KUxXfYjYdIhAdZSiZbUuhivg7+adJY/LyLxT1/J/9zfhe1qiot+xKOYHxk5wRe3EsTnBB8X95AJi3ri4kVmPaPu0EkaPQzrLgcmOmXGFAnoyFF4sNh/VkofmY7pKh9H6RATBhFI14mymoKnkpLDtHnjtKhaEc3HgF3BcKkFlBpKxAQYb1E+ifw5TaWwpCNDwhuLr5jZ9iKWK5TuRTyLxPtWJYJWO3M5iJqX67QcA0HXTaXDv7YsGqaA+SbD2gAx+rigWJFiEM0tikAFQQ8FNFvqivM5S9yFmclJfM/waSwLMFwzw5rkyvgYvmqSRgq0olpogDY/Te07o52UQ9rkF6DRH+t5vMa+qogyqC4W0uaSCRFG5YnJyav07wMymiCYNGAtlN+J/7fhki0SNFyorHQDUT2TeoHZzfIDYZC+PmXTQz9EMNr0SrANunvnfzGjkBLxI6lyblhSWkL1YwoPZW8VXRvMJ5Fe5Axbo+Iv4G2f+rGxpJwp669+TGsqG66NZHbzUWwiESgAof1EKfIuUmQjueJQ4PuNTYQ/QXGb1VPxITnm3UB1bpERuPKR03Vd//u8zZiO0REhDfafi2ztumS+QGM+eSj254uY21tzHWmZtUqhicsV92a+gWX/6yyV9m7z1s/PNBIOrRLCmbpvTww3YtFnYdLsekiNzSXnaYyz08Ou+iAX/WbK+2xiktPXt8BHuWqgu5SWY55z7p3YVzqVv3RHitchcOMwYqrRSJwskO+6H533XDXm9AwKiMHZwhSegrR96tw6RoIx/XB0GRXV5IARGziU0t5tNew8/t1LPa0ll0ia0b9Ccuax13ixSo7ZxHxQtb0kX+qnFCT+FfXzJfG1JN6EG3P+lck8kZO4xuXTGhjToPJiMnlbW/J2GGXePeayxmBp/PF3NCodYbrAF8M8gzuOUT2SupDiD1sj9yyx4UQtC9vkAjN8XgqBP1wEg/a759maKK8wkNuO3eUwdfAIweQmdyQIfELDCfKGK/UDZo4q16M3g4KwEUpTC5gMWbMGqcGN21yBfTsqFfy/t6oqVm82P8dXk4T9ho1WgRigICXxFvTq1DO28C2NdjVJRg6iCFWB6gduDh2bZmL80wQdnxP6VkzTpPjWH8vIXXmfLrbs/vWtBpyOaJpWz2KCOS+THHWk8m9mChvhc2fG1vJ7rhaHt7voMSSIfc7L/vYsxG4oW1L2ETprvD65h8v7L7xMHi0R3R9PxnD99mTHor8l7WDSYAR7BrZFQhaqOTK76VhdItBlKkSulVXIth98UVYZqP6JQVEHIR7aKaJkbzLOkTNrOqzB0CA50YQJOfZWFvIr0TUWhA8iO9IaqMqBLQPyou8QEy0bCGKJ1kgj/ZZoNX2Nbii0EVmgXFWT1iRPIru5ud0xIBa3EOum88OiKW7KLeXTT3WO0R255Up9iR7jqWf3M8BnmeoxRvsg3swWzWrhY08tdcK1e9ssgLOE59ucs4o5LKYCgV2VwbZFPM/kf5R2n5Qd6vzJp46dOQC1sGH2jzg+AOtSFOLodlGhiiSxKjRMSXgudTimD7XNJWOIx6H4NP8OqGmxBisequdxuu84wA/JPRAXaPEGTN1FZww+CE+vBd3j99Zp4ultW72BZhfKA6wjdCqiIR2Eync/viz4hyieuOGx4YP404uo/7ZSFVeL6Jp7Z6iWkphwHhmWSADIa1kP8FXp3dTMxvf2Vpq4lUnSmgqEXh3FGoVo0/HGR1HivxJ0yGPk5l6ySJv1PT4zO2foAOGaMAMo3/vy//6DKBXRNVUKgDc7LazGbDj5xtnZEXTvkvx/3qUVLLIbrPv7INW6D5MM+KyumfkCEMVljYWj9morSDSuva1LPjy+CcVU8Fr/LyDgBzRuD/SDnRSqpNXqhHbBZqubv+blBpPgbIX4o4/Bgyiru1w1MQpQffaVXQFvUw+QgC0JHB5lD6+f4z2gDstwE+FGEqbryqygcpa1TYCnbD7i7jNsYdsph+2JNsE8VECoqp9rtyWGY9B8A2pSAKTcGujKblD+e8H1oqp5Z0p/rneYfHy02GHQhrt24JCN9DfwdIikjdysFo3tubVheYD1rAboNHNc7PiN9KB4xEJJh5TDhoKsEzIegeytCIbvxeDv7MPrnCERvxqWV77Ad8Ixe/KVAuNn8Yis7t/nhslgtjjAUd2pXKCDwpUPrEO5Vj2hqhbIHWFEdOUlfd5zze19FG9IeZRF0o0kPpVzKRok02rt7ch7BzwMslRPlG3/xW6UZIlilRP2e2Q4IJorgSyNgk4rzXFdD1Cdb6zJusuhJSpKgSB7fj1UjGBarX4UudF0YjkUv4PKAfOb/l062KH73D8d6aVm9iqCuPHRtPKtqftHxo73J5Sczj8hS1VgoVkuDzKwjbXV1xc8u9ROxuybpxZNs/fpeFo+MQUiov9IXBfN3rB+wFIJ40T0EMK62Vh/N0S98rL9Jmb6RwmYqZc/xhLpUDrY0DCzXuSO86Ih2pr6A/9Z6myvUez9F+kWJhG79TQfAJ8CWrzXwvGAQO4NHv2EnDWWHvH//rrcvdiyGP/0BOlul0ZnZPoTER+DrmGQRfMJI8gOeQs+tCi02+g0ENxz1FVc2odvMJOqOX/Cl+h/53qYEOrhWMg/yFqw8XtKs2MUIzMTkf/DkvTSOkBvT92XrPEKBfvzgiJ76K8TFhSswV7603TQ8sXSqoA6b8xcDVfEXZigd5jjcpFGFWIlOMkfeC/JHDGtLlYf0lK1U8LkOuqsS6YAqYuC1w/UEPO8yPsZYaYFymKpdDGvwyMG0pCQBBlFun8wAlPwF0qAVQWCMkAREAei+Xem3/yiyohRc3qmUo99GxWyveMV4UmLTm95Nlkj5mZTbkBsod/+dwhWfrDspNF+bGcIR+1paEkp/EIEojUohnOwZCJ6GvFMRbuIW4LGDs6HAGTZWh+DTZVv5bEWTMvBlm/sBYuD3kEVVk0dgQukG/TnQY71Y8o2/DW3niy/WfEJ+BYwuHZKmPHqwRnJBcHPhHt1GClCeKhhsu6w7noVDidilswQR6KeNNlPH1w0CtEmyXJEjUTq+A8vQEtdbDrvOp9yV1YZ6XLpBx91bQQRqrZsC4+ZE9r/9dAQQEGaacDgnytDv3CoeBsT3pgTqX1VpYlHIJ5eWLNzOXwn+a7uUbkVFkyXDj6DW2CRgHvEzF3RKuNajuIi+6yroGQZRSby9/WZbeUbIujjckh+QPQQuol2DcygSlAa/v8Ss8C4p0adBTNXBnumkqypFCpFj3EusACe2DZcTRrVc2HTXH3aMRQrJwfqI5vm0u7VrnsL2D0TzXxQP/xpDeHa5fCm1anCYwOFSlzll4dfvmJzGuZQvJF77bCfdv4fviJyFNbd0UOnWPucutmeYqNUYXoNd5a9VLf6Zstx3K30jBDMCYT/plntJFw2MbAAInSusZ/jJT96NQLC73304+bpBjP9wEdOZWk1Ys1I7DSJL6Nx3/gGTCBC5Ohp5hd3SUZ8DSt2wZqA8MKNcMIb1vxagvWfHALzAN3SF3XgybXn+9XZKVTYp7gQoyrGGFsVwynyXSLmbTWeBAvUThWihpj4rKhW45YO4h/ns9FMixjLarPhLzDOns5ZF5cToW0bMVuttPkESfaOFNd+MVOZBkEX2eUe7ziHrqCjXghdJXjcn+sy9fUlS41xhsyvbwWkq4N1zJ7P/h0fsKSjIIzI15uCU1dtPV3GSBOi/uG/n0RVs0ZH+6Iu2SyRgeq2elJZPrtqXXEgzYaSuRSPc0q455dEIOu7vvp6NCnXfNpsdKMpd1ClDogB/K7HvBBfD9n1c31zZEo/KxUQpLP0v+d9swEQH5onAWDiJSuf6mj23Dhtff6CPjNUNPfyCORK8vV8EhQNiSa7a7lrL6TCkJ0JeJSiuBruoBURFHHW9GS9A+FhzHnb4ZUEcLOYvXXxrqYgIs5yYIhDpf1eJ1sGRKn/WAf7msusALByFjl/hkmuxyxCZfO6+t5hW0NljvaDeNp4+IYNUVolQmO1cfIP0X1kMHAM7D3sy71VNlS/4hAnCdB5fZI9Kp+90o8uwPsU2nZ+GToYqaV610gGb5fq68YTfZQUsxfWKr9kLJ25NH6W/bOsoatnKyoQPEXFAIbwEI8N0KpxqOf45qCBo8Mj3OY9+ya3JBy0Pvov2nm1wqIgfRU4iBPqZIcp/sL41PL6CmqhgpXJN8nuKdVKcKuBuLRYuC0AsBvdFm9BMMYQ1X5+kUMjy12hbhHQf+EeZ+a4WCoPtrE4Qck+ktfZ3eqFv9yWEx67w0N68XWVvFoL2YUFl2krrNmTKVOn2xcKHRDPEHU/Geiz6cL9upJaizjEf8+HLnN8jpy5CwDETI65kfUvZkyxYB2rDcsp31EVAptyCD6HNwOKxjNS8amLtv/cxPj6p5qoJ4QmPswRmihZYgyq7ljLCRXc6XU15C0nXE1zLoy1WeM55X1Xd0l18db8k9xwCuopZ6GryFVtlW9aU+r4BZGa+FnI7VBlp3UPMpTCD2HBfdEStU53dts1qw/eX0UaxS5mLovk5PtPhi8QiEEKglKvPbbO4C1dwdaSA3Cz2VXfvlZJrrYv3uVqgn0uLOj6n47Ojb8nARI9mfs9ovPZsDFSeyUV+goDjFiXU3q8VIhE4928O32QmZdCExo0AXeb/V5BAOzdHTVPIlToOHks5dq4W8fnncEGnhKPa7mFun1UqDHOKkTeHIomdpojIWBdwi8CiKAel2JPFCcd+XHn6ENjc4upxTsZI/zkdHVZ+1eS3EmVIMyxaA/fXBeZo/GOlC+AO3bB2W8aMeEWGlyzrQK/ZWrST5Y8jP9CyxTXVlYzQDty9Zq/AeRCaYqCC5saohY7Rb+R68ztZCGXRSjwRWqkE/pu5WVLcPWXbmY3s8JTFxuqQUX+9D8rjdCAKXBYhpiBy1yr87a4xYl1M1wJ5swRHsQZ8ALdRQpVgMUTMG6zAJT81jypvGrbXwdciMX6Io4VY5ao9DgzZ1cufa/0imSAkzO8mbiC2DuxSv/FE4KeK5sRv/qhNw3CuQ4UbZMMVr0xB7F6arp8XtWJN/zzTB0VdE+WRFS4vnt5VU/13n5BdgT6K+LBSWMrNvpzxZXrljHFh5CXULyXgHyr8JPQz9V4tMzGuimSnV0Gp4mHTPzPTz+m/aUFNMxtXFGfKxcEuQH0fxdA7VKRIzKqW432EMuzEeEOQIbnSDYismLS8DjmuP2U29bNZrYYYsDeTHtQzE7Ec13IPM4AqPyginy6W7iH2we3poM/owtkExW2w4wBL4KOlhaV+sd4djwOBv8eIhLz1k01vTctGB0KlmAtF/FeY/HDH7cRk+AgDzFJvok0UGMOsjU2a/FWOaC0Ar4U2san5rERT6IQAbF/58+Bw+dK7JFcxJdZ5FtoebCnYMswj1fJfp0sCBDKvrRqRFMWPHsc1Ctfv0ZR1uHQVFeROgXZms9mQp9FfSdnRmKhA1FCS0p5f73+PjeLSb+kyOlaFLIgry10Oo8EZ2P+br4jZtmnk8N9YsEDHrSBODJkS2Dn95f8OTpDPH3dSIQp210NDSaElECSLb9hdmsZwC+sxMsMHOD7ZeFsruA1YYVN+bDBd7D/ikSAYZnuG3JBE7FLBMvHKr+oQQf/RnP3lFEI7gkckLRu8HiuLx2719/6fFy59Z4WsE8Aq1btvst8uYAJnQumxqocZdHQZoxYRnOPdh+HFj3JjTuDj+rK9P0oTd/i3sV83mTp/EMq2G2b/ChUYukWYymC+TJN8ovv+yqspUmqpICIypXVzfgwj0BKmZ6Oghf3kykEcoQ7scoyqEKL71jkA3K3LYnQK5QLTxSAqo9IAb3yCM08oHRukIS5aUn/sbHs0DLb/X0/yXHM35AtOT5aJL0qR6lh7S8mzWXlcONHVPi33s0iKjErVgAuxLAKDnpVdfOfYdARG+P1JLFVG2h7MQKv2ciKsWgz3CyQY186uzIw7wLgAksKblBHtIBEKORuFJKGDgQbTLevIkA4a3NLqEqxnqF5aUWtWN46Pm/m/WSEHa453QbIqsLb5hzwb8z7fw6A4td/fnimZkamurTAaIVGSTwfD51Ja4y/7enjaOeOD/FXDWt+Pmna5N5Wl98NoYpcBgzDm0FHX9BQbjpgtP3RLyukl5Lfzs/BiTbP8zMUtduwdOcQ8dsaFdf0yfFeWWLarpHpEjnocaICTMele2JwgzHs7iQ0vIeY79T1zZopqFLwQ9tsV/V71nrrBoRysOfwdqycj4HGAm1THVJH/Kjvi0LJl32YY2fdTEQHgoDXC+aDrMrnGfU/cXeprp3Zwb2Y2L2YQHC0RyaAArmCR43bCAyv4Sx4jBb7yERmRJivCx23V0LuogYZCnIz4wxVWeVi4YbWE1eRdsSnCGB2P5mKVUKE5tsqjzZqLI4YoUtgL/eJ1w/3gIwVsIAMNGiNKE16wPgfpU6WOetbAyoITIcZynDQL5nDbiS8yKMhDPdsheWgrFbKp//4Q2o4jpPlRWTjI7zvV5cCMi0E+DZ+/m3r+0PBDFrs8OWugJxkoHM20Rtixuuq68rjhjiDLkm+p6BOfnBJxnCd11AaUBogm6oLOiIrvdl5hGTtNPJQAD69llbb66tPIylGKa2790WT9j22lqngvS2GfYr0XPCMA4IF5zVfTlSp42VdcnTbKPdyWTelSf0tIkhYiRfJggylTzybE9MiMJbdkISejOlpA7Z7+hu5SMcmuS6lxieFQxogvZ/PTmstPO4WDRY+o9cp5QrzJWVRoIYKoy36vhJgXepp6CyNCPJtcUUZzYEuL/RQgHftVkBBdguNQq7gvfyMnpfl7lR6m9QZf/K7b1cc2DRke3oAu9FwCHioDHFMdlt3mLTuBtBC+196oLHUZAYB/aPIXeAa5s/A3bWs8G/XHMIH1RDikj5k/3eJrdL8nMFzaCPsa8JlFciOqrbGvcGcqPlMgWydHTEjtpybB4LzKl0AqHa10hvy09EnH+VBVB4hiW8+r+10Jwobb2VVfI6V96aP0pjpDeDvo8Hkv7nxFlXmK5OWES6CibzZuEfpZVZvwy6r1/Gd7kA3CmDodc619YXuiWB77svkM1MyvBGXJpiD3oJIu4r21D42SvixxwEBv65Nb655BrsIHiiHyoNE2XNv6TVtmg/AMzqNWduK+1REZkKvqYUqN6Hn7jHij8Wc/W+R/adTY563XYQwMRNUqMkQNL9bKUeB/gYAduVtivgqRKABzNc+nUPHPX5iJtB3geEhx9TQmwFqnuh1g6VvPMr+3P3oFqJ980UeOV95vKDnAcvh2nqx3lQObLHA7Jurqc34n0ydccvJYipXxbtvGlFEgHJx+l394S6v9pZ0qjOmKwba7jxaQaToK5E/pbXOwC8PH+SLBjkx1NVOXXc6FuLPwguJQhDyNKGxLdJL+d22KWPeb9BXWmXEb/rx79iZ3FlLBk8zj9kb1S3vQM/ffzCdbR4Y/8V+wIt+L798EOeUHAibUEM4/mYwELWwSF7WsopB+qnYDfphFWO3p+ghX4ZHAoU1vt2RBR8kk8hsbj0jFgWk8dZai4VmsAAuvZXeaN/IrKoxSAE4C7X5IAxKmSSRnLDu0hNi1TmrBlMJSrVXS/xw1ZqF9um9UVaCPi7VHRr3qhm4wIel0jNwZ6QuVbIhgzC85dYL7CBqSkrNwEqbA/NDm/jH64rhtvuchX8DXpJdfmtrT4PAm3OclA2uO5Dg/4K7LpPlbA0kYQf7+6xFYju+TVTXDan1AIYmFoFHULSGqAhvDE8U8qRZHiHlpEbN1/To4Y0ld4zaXz+FncUjsjdrm1OGV/lnp8NRqDsrmqAq1SxsMsiquuC5kfy2pDjYygUE40TGj7yqbZtW8iqWp43/cfcbXkR8pL+NRCO1EtJtN6oLDmkOEuGyYSIK/scjNHWoIIsU0YzUS7+XIGdrYPLHKt6lHzEDFgRDXb39+MFQ5GL5BBSe0ycyXMqDhxSyugq0pIUn0MFQE3d8MDVFluppur7/w4jKWIq1nnFbi98wM1oYhfEYSxPt3FYYEbzZdyJqxzNUfgSiPLFe5n2Y6IGR14jpImximKg2O/XlX1Sgg23GZAuGHuvG9IH55mZSVVhfBni2c4m+E+A3zJbi8gm28B/zKn7ZYd8XIfTNhlvNleMT/+ZzZv8faZhgpq6UeyrxWJnyHRwPeTPYCytEPnT6BfAv57zRMYUxa/JiPDGqEl4rQggmPe5EajWi8YFdoLqvK0uEuZV09Nu9xFBjaoR+BDCCb9gS1D/IcEVAd0LuUoI2lYp44wew0EVgyuuA2e27/z6/qt3M4+F1P6q487OW3oh8g5ZeZvW3baUsCUI7aTTl9wDz+e4P5idXLoamoE5zOLTX/AhR3TMxbmwcfuhtum3lNQeHOEzimHcYqxzdY1OkMw/VfO3dKuf4KF9FqXowiKivDMs/nqO5QQ5fuThNu41EWWP20V1Wf8i5h20GwniSlnvlfMaCmb3rrM/8vvmoHh4o6hw1CaIjHEA4BMYw77ZSyOIvgejNHY1jjqcpkBDKw9PUf2T7B+j/7m8ikr052gj21YrTMivGxBXRppMtHfjqNb8cx/2NK5S5UOdfopc+wMeBR26USmJQ2I1kx+t4CkLcBLqoXPNGUrLyai7ibx/2kW+xSyDXmPuqrYYV92CoYWDBe6pVbbpmlCLD6wN+5kTtWaNZfhlR8B0l63kVXX+jGarB6+r6ccg1+sNKtD8EwHJ/JAuSEs8Usj88UOYTfjhbi95vSNwNmGXOveaKtvi75qpXcg61ovOkiZLEinsH0MQAxK5CM5MP8loCdXAjIHx333EodL7o5xp1k7kO7EUUUeGuT5QgzytJWH1W3o+mpC73vpM07I5XBDtbsc7vkqbNzEqCeYICyG+YeHNdXLjXkEmhj0OadvlIv0eNyoOxnIiymbBcQzTN+7r/drqwQj7/yf0ElinxZzi9PKRKbXnAmU7nD7PVeO/mLJf7UftdDReFWWu1IeVLEbSQSo72+8xZJU9AE5LtZIzG/T7JLytsgrrphZIWTGxEYetQB8EjKKtWDTDhwh1vWoJxQoFOkQ+dsCC5QFbkzl16IxjdTm9PRtEh/l3cwB+Lr/nWt0f3JPmGcTnPZpN1pVjWA9kUzboVpGn3TJoa7cqjriYNwa0fg2RC9XrTWmlZBPRKOVUi1mtUkE0X9nyH0Q4uHXCxr6mHJwivO0+JqMKCNtMTHoJGi0bdP6CHVU5qH7uXfkMhI9oGhXjZtNVjuInEu8a9N+QqdKmhVXc50d1Sqejbm5ycvOQluim7dyPfJ3goS61ZtHaSCt7MzSdPo2eT7GK9zLItVLFHAXoeo5r3ScvG39krPDw8mNxATr1yy8v4fASQyuirT5xPPQYorkJiZHlf4OnPQfh8HR0bCuzQcGcXn1m2/jE9rwa15CFSqD1WF4LtjiqCKzi38m724FpiLT+JpvT/UGVeveiCF0xb3YK8QfR17IP/qRx26aP4FloojxcNcjPpg/JNkiyI4EzU+mys2s0Z2LWDKtWJfIUD+7zqDsYixop6ZUg9pP9tVt/EGVtRuYh5tXX+ieRMpbjAYXVnS3lr0UpD4TLiktmSWniVYMSqQ9w9mgOCbtPHQaPAUr1ydrTGIL11KBfB6OJVxnTqupdKICLfEV65u3Ad3ttBXLQbI30TZ+tO7FREK7aIXoOetradeREyp2YpGrqHyltcWLeGhkRJDlCM4iR7J3+1iYAul9dBLD94xkBdbKj0x/w2kCZzQlQbWGjW9cln2FZ+qJiraw+wxWijavg3+14CgLDbCoYAR9IspWxkyI83sCMVrLT2xr1XkzqoWcPCNm7jucZkiNYh709GiFEAZwFhJVwDAAPddQRRCGa0mVLCzqMymSc199LWdpYvdCfNBXAW/tOBNsy1ghwRhZHa5Vvy692TZXTvUDART/qyGz3OR0LqTbmoh1N0uewGdK5nbUvDILzCcftzNsJfaWZtEKLTmqm/4O7Nee1qq6TKjQrt8yz1EQZ7tMYuoiQv5fzTjK8Uh8oxG7Bn8VXTgJY3+RF38VaBA3YVRb3ahRkL64l48GJCWlvTBoCf9FM0G738DYw/Wrh+Jt9f5vK2IibsYd0MVOrS+e/du33IgZnzV6CuEUfkF4Jrc7s1C7Wbbuv1EtL2Kvkq0HmdAKXiD2RIG5PQs9p+FVZQm+De9hOoVRdHYm+3Rv1223doXQg1N2ydgDa5vTKPzK+xhPr7QVGk56NJS3hQIWIMJnOYlqfcGgxWPxjR2TSsLsmefKuXjEhTe2Q/aEEeP62b7PKfBwjWtx8Wlmckl1zYuRItk+0wJj+h2kP5/YF4NX7UFLxIVQGs9IoNsWBRl+funj9H8IFxFzQ88bqTuEknsVktsdx26GMcrmYWznc36hu/zHg2MdUErQawlviTu/D1v2EJWnraOYWpLrxfHtbN+71GU9tXL9+Sqc5XAqWBbR/Gw8JTcz9fOtCADlawnVj5cWhXTFoISHC0lCRBTHNaRl8EamCsKOfZDH8q8WJ+Cq3XqVHemG5+uzeMVW9SlyBNmFhnIcmNA2NdLVImSSt9hLvqYPiC8kG4TbjJtupuw4zNFnyTwMORJSHzUTul1kzVHP0ddVZG+XEVpfbQns2X6aYgN+s7z6WgJV7wRWKmF18AieB4GmYvKaYlKrnwj2/2QNIjVeGsCqh9+hDcYnJZEO1ayK0B720xVgCwUtAlcEDkMcnVYnMVeWqvW2v6KVuszy2N7D25RqY+rVJcY/dPZKuChNxDSb4fr/iP76BPK/iuVYC3Cz1Vw6+FSx8GWiPvW1mJ6zV0lYeKJ3wiYJWdLKG/VL3/QziBGLne/lcGRbDl9qw8OAzy1XIM1vh3jdYdNA4Q16bzuiz53hx8YsiRV1iwJffYJJgFtUlpzhP2axkZtZaiKC94BgRg0/4iPA9EwjDN7tNXa4l9VcuSqtVg0MyS0RO6/7gmTst+GFwYLmEv4yEzrX3IfYUZiMzhIutlGv2ChMpfjPRGpQ+dxTR7mYbLjD3fPaJVjgY3N94wQWfubI75C+RWKFyIVtPs7GAB2uEAojL2E7QmPE6CioUiI7ep3pC/sN1QvKWb8agatDC3qTSM2h3X6BZYWMqgcx6gScAVX8N/+QlnZMl74V7jd/GemNAGqYmpp/JpXlw7kqDI/MHFd9rdKEPPVr+PaMw1qXG5gH+ZnKIczaoPAjKCw4pu/IUZHX/+mWUN5Klv5CsqbwQ8xGu3aDUV7w4ZIYh8S++eAAzcNzS7uUUrXXnPiq9+UqNaNROieb2sepLeU4YJn5Or/w7/TpgYwmQ/+wfiG7sF6ho8XGW2Mx3bG1iCDJ0NBaAdQ2BpGmynM5Wag2ctdXsOBO+RaWaw5qzBuLKFIpniZ2lr7466iGwKEhS5960nYVrjPNX4M1Km+VmGUtG7iVT4GIumskbVkGtEIzgL8n3ThRzvKDeeXwiB0/Mdo4M4qMr2itIGR62gRUNGbAObceg40t2gth0HAwLnc710FnfqhPdSmfb2igZuZLz8+Ip3LcPe7AlPx/AJqBRgOCRy9lY483VU1IhKZZfpDPBSH1UNdEurKXlPTS2BdAuarCn5TLcPkYnVRoJp93/LX85pCw/wTeKcTRFp/EtewStNQMcN3G9zWt9LE27zlz22eKzz9h4/T8yl8/Q0+yfqoaDt8NRELGfiyyoCaVRVtfdwPeKZNfFC5b2cd0vl03bW0Pu4X3/3N61s8v1Z25dwJil3JPdr3pCut1HeyLKa4QX5HCYTv/LMBIaPhIkkYn9ZL1cDKAl4xoSSRLgq50XW4IO43llHnxT6APueXQPp2uulL8phGmDmZDofTftu1Eod0WNmsxOlrJbPzW9teKYZ8HgWKwhLsE2icOsC/9uzsIqix8LPR0sT/cszyOIXm/K9xK1Sbe07f+1l2GG8vpt0Pa9UnRkuFuX79w1b6TJyLz7sG9ZmUtupHG3kLzbTT3PkCvk8okGB57wuqy56Pyu1A/iPE6E0Xl7tq1rf3oan5Iqo0oXI/9AbaH5GV7iLfARkH593Rf89iQcrBUvqhTJlCRvx3lbYEgt0cqqh0fmnOGxSMHYAvuREVRlRphKSu0HN21DPU5PeytQa+n/fZHvdhJo2Eo6VI71YwJjVjXjEgUAgCx5oT9auyOHTNqLY+08pHdHxIcXryi55sVzh3manb3OyGDJMiKLN1hlNPgeLa1jmVyxgnYb9w02QZg/ouyEKae11+YtBR/64UxXT+IUpfFrPVi/X/er6GGoKAbX9jFl4K45CczRd0ar4SWLXXLz7N2D2kmSSsW7po9wqZVgpOGFsMoGx2bV6EZliW0jCkwxuLclgUmKOCwO/WNN9bfzruorTYKmFkpsKFP8IU1BHAMMgmWLw3LEI536moG6z2EPwTtlLMKLvjMco27P+7X1ZXGyo+WQ65aEJhOobGhP/steadBi40yPYeIoDq1ZFjPPEw4Y7K4WtlpusRwrDnRnPYiO3Sq5grqutyXYKS6Yyr8BZQeELFcJii4YdgItb4b6L3+7uXj90l2XUwZrErZ8OUML1Z63RC2/7/Lbhp5Uc5fbWYNhqSb5b89kWPl7x7ZEnttxQGfMbKmXaPd4D2qVgzANLWGQWdwS+i9qmkmzTPYn6ERSBhKvW1gapkFV8G+YKBe0H4wUH5xwC8GOZznoItN1HDx53B1yMTBYo5zmVdUIhV160yhaipufa1ZY3WGnR292HjZYBDyr/QFEYreoffGka1/N8T2cwvytmOyCLIYwHuxE/GIWFK+QZ1T4WSIKymFdgYo+UQvyerpZ/DVeVgi8hiR1d3dIK/iHQq6+6KioAdcTPK+uXkv3YQgClmR2gNbsRdSZFkck63gvW5205Q3+R+6EkZ3vDhFZ3lYScKw82NBBc8rPSHhyH3unnzlwryXIQgcOTm1r3ULkmffhu6Wra3ASFOYn9R40X3alDDfFzbahHaHwPCXrJ9HhD4JQD0tn5lNDBUdICH9av7Lnta/1clziELbKyeU52WYlte0B1S/mMKQSst8mSViKvtQhZo0/BbmTw3cJ3W6TXrAaAA/4+oswD0svb6+CxSEERCGgkRpQVBaaVbBElppEMahEsj3R2X7i7pS166u7u7Q2Dv53ueH/939/72bGdn8ezZzs7OzjbLlT60uxtylbzVqPn1CiQAHlbU3ff8kVNtshTiWDvJ9oF1U5wg6dqhj3xLGf7rhtwhImqM+B5bGo+ENt2Hu2uV5H/lC53X6vMtO97akkiqqnvVngFAa0/aGkXsdFqcOuyXX/KfTVU8DrRjPGmO4yd29d/yFZNnRe5GGdr7sd/rMKnxU7TSLMTlKDfMskb9VOWwPPzHL1QkRcAkZ6JCEFRUhqu4kD9/G+DVxj9Ee/av+ZosVKIU3czXUlT+4XaCCH72QR2SIAXscrac7W/fcS9TSF2/y2kaeyibs8u7FAgyFGiXCcbdLpheJDckdRt9XmSXoRbTe+Y+YYVMcyksHrXBf01HndK1W5Wi/FtIRHhrDhUpgaVKhhmloNxIgulS/TWvcgMa+6WNC65+Y8GyQECAzK/jR17KzoGx0+i/RMigdDbFtQc5G3pZU8iSyiASSPfkQQBt0oF+7Z9XQBmMZxQ6ICeRqRxw2Wxl1/kvXeoC2G3SkbK1ECRYwaUO9Tds4C/MHxhxtfVt2oeN03xFVBdfSUE29bm0jOrDrSAx6Ck/Am1dhvlCDJ9uXwRo+LkaEFvlIcXqEM1CNpgp6Hmwmx5nb3kZaRnw28Iy3uYuIg0Mu9+0KR/Rd0cnf/gHy0OpsdwgFRalbEdU7g0IBiFwr8us0UFbpYhkXHgVYSIKxobNoEtS7IYsnwxhX+46JULLGuakOYXOUjNWGvTBEbFd6SDFNTnBiIM9nN9+fmeJMqdvxq44ZdhSJjUQIa7nqFZ1XtjsLCyBiBboFJOdbnBkY1/yNfI3krz3rIaiKWNLXQoowtOFS4xwkHgeDRhS6clacFz358oCvJj4Z27i8TP/IFaNgiZkJxZxFf0Fj2K8Mc5o08YyGHRL+5zGLiOYhNJcOPL4J2IcRGnviE9JY+wMl2UvaygqAWqq2OMDBmDwhWNPOhH/hNKgj35TyvfS+0sq70ype7GJQlEIWCZww5+/5jipQv4UwXhJbPll9vdPZJuAlaIZlCY6rme8nAAfQwRbozHhw3yCHQJNzKi2Wn3Ui8P+EZV9FSbcklm4CB6aRh8sQO0F9oToX8JS/kNfis75xp2Um9K0j6JUHnJVoUq9guWMKLCfFioAEti+X6ImboAY3ykSXVfrzDoNHQYaiYzrXBI5ir8oHDugjXq2qZambj7bIr+MHml1r8sA6rvsfH4lM7zbXpoMbOu0n3ho78gstTuZxEofNgoOmw8J0XkdTznzX1xRPytCkJJQ3SGHwGyTFQBy+h2SmaoW7lnl4jYcLSYB+ABvVEngP6nwxCKNZdSiN4LTHDvAlrJcAYrApDH5BGGd4YNwvEeaga4Ljs4gJj8oHcH72lSxGxB8JJMQThh0JiRQjrxeUCPZV+KTwsTaF5IiEab5yo5dwRZxFZI//TN70VNCDoggDqp+riusxBb5A9EsKtfyXTK1reAUF86Fg3ErOLm/RQWxg+JfceM/Q8BMW+CUAA6QEUyxlZIekjtx3YcJKYqymoqIrfcf7A3YJtUXkEaq/byCmby7toFeyWIh6tFFKpaQAaI5d1HkudNyLGbTbDNaYKO/W1byNumUn12NgEZ+idi3GRalj/SFpZeh/E+qvUjHx9//haPbNejR5iW6sBzhsBiJZrYxzxww0VNcv5BFTSe9s8EIM1YJSIwJU3EweChRypvk/HH8CtJaaOH8LDhtB8v/yWtptjHnjFgjoYCz0sfWZWRtnqFrcQM58bmUaM9J3qOLsdw4UDEDlrjvGczm6PgPFgAECllVrMj+NcyL+mVPHY0YIfoxQkjJ0lSFGbNy3ZfGVbUtp6AS/udaxKbVWBrSGDuT3aRaNQEINh9bwm5FZDcAl6lo4KPVNbKbMZIJbRU4O33xsoS+N6blJO/W9P7BVTZEqj4sQdvEL8lFAUIT8mvQkSkEJUV17hueUfjVBnUL3Fiy4mH4QvHIflwFrCMN6XfAfkb+wZdEFLxE8fdAmJ4xf1YmZfh1s2g4xu2KK42V/VRiC7fIPS0JbNVPQjpgSZMkpqolKKeqK75A9sYTllxKk9mxI22gEl5h0AEKxRwJNsVYRgx6jVkeYxSOIKTNAJDv8t/5LKEl/ciEJXsQfzRB16euyzEht7ajW752yXnvatbiLCFQVFer3JVHjF6lC3C+OXfMDRdbtFxh36BpCI0LGAI7wBD0Nr6AUtNwd2FFLmqHTluM5tyUT670Bl/IwAizh9khM5PgmDPb1kEgtGOJ9qGyKi2G32+qAfArfkynfJvxhXBYSTVWuOdMPEIF73hegNBvtz88BqeMIfMtfOpbLeXl9+lw7EDHC9bYYG3Box/JSHcFkzbSErt30zjA/EtDAvXFmX0k+jQxGQjrXpy0hYshWc7yt24XoxvtIxrbNsmj9njvEn6LV4VTCey/ZEaE8OTNEfNx9IKE0EIMwXHUjBi+mcShm65XaDbc/tamXlF1Yg14qcSjHpZrJs17pc+0QKOLtOlj1ZFgHZOAXzmWP7VmpWyL+h0PVsIPzJy8VqXrJRwJujrKQXgTfkEJQo4AbEBXyLCUju6F8NnagsmsJzB66ioyBm04IUKw9iXooEDJp93sUA/j0Ajn9t+YDRwZFtXC9u5bXH8b7qpCRFgz+7WBFHecvo1KAkMrqye/ZjhGhjMrFXwGD4nhS4jHG8/2ELQdCdjD8WmSs+Gsxdm62rX0QOMD0nS1G/QOiNYqoKzt0XOnZPE9l4bv8w/Ra5sGwifCSms36Oh0m6cZN1Pb/aYL6ms968OEZiKuLhI/KsdOMS0Ey+UuBaNKgqIOOaJhSYZ8o2mdOq0VKk1/ToFzfya86l8UBgIvShODBtp9fXr04Ld3i1xDSb0sK+hyB5SIBHh/GNTKzpUpPVnVe8Ltru/ewaO5k71Je5NQP+h/PFtIB/Aq3qgNlal01V1W1q2PAsLblVEkl3NdTkzdNQm/VBEUdwM/SMcgPDn+d1GEAhRpoA/j2cvluc6DWtikM5UUrUBKar9QQaXz6B6YOkrn+MJdPF8OmEg9KsOAmvw3zYUxO6OJY9QAzDSH+QmJsFRHStK5yKnVKJZSy6+WjLS8+ud2MXcvu6aknS+19YlCQWmIKFGR0pjtj6URXAa/6o8jGw1yIIBqdq6PKSJzgLXrF4frVUKjoutpX3/O94pGu3wNKky/9IuJeyzY2fdLEOjXbfINCuAuNcAOzWeXm3+mnj2rgSEEogElUIIezNAVyhaJ0ooU+Pla+5GKaMubj7PH5i+GMeJTAu2FnimyjzP+dzX9LEBtl0lKt3qm3P7OW3tgBSlzseGXMEmz4W7WCvQmFMDx28FM2SLVWFt/IMQmZCwf8Njub0dvM0bhSKAGAEdfWglLpmx649gFMteLpSAmr6rkHL7lEHMYzGb4ivEYBZTD8DiNfsVzTYybW7lJbNWZ1NKx0ySJv8AAJYqqTQYZvGZ4WjedFZR+wih8wtYiJK6u7mgZBuSnq/GtUhlaYPG4pk0Nchh6+7g+RWX5aCXE3bUHFWe4OmFKO53vXcpmQ0qA29/g4nhgRJKMBsZUwHytTtARLegOC8+aiZEV9FIcvWyUcHmiU2aFGPslF+rUFaOm83DeF8dka0ofzT09hhxyL7/Sir95aaWY48CH+We94i+i8wRR7bQpcVzIS9vp0V+UQmp/c/xUtHBgcNR1NiubqIqio//WbZPjvWhYGewsHOjto+OJiN+KWwpxa25d2ETM07RuTYpPrRL/qqjBeryx22l876vhFb6PIhR/rvzI66/5mnYcP1iVwVWtYmAKdMa9BN6Guorg77TDH/haWg2jF8tdxQZmVvA9O56CkA5aW6KltYh+MgXen9fAFIOtJfC1voB6842h2sVQhZGNN2FEw/AN67hE5fGzoLdV6V2MDeeH14U17gxwVoz50nAQwH+nVh0lnr6X61xeL3FZs8JHai67aehu0kP/YY71/sHCNaAojszXlpr2b9hZDUHqCuTDGAoH1srgbhIAWhv4RADNW8/2t36LPsRVC7bApKt85ifnkHa4+12mJfSlJNFqvE3itmDxZWShZNBMCW5WMrHoYGfSn2bAJptIZOIl5cIUF/sIC3pWier3TkxBUC44rwosZd5HEnOEkO06HzLWpH/d4CYDUSU4L7GCRWr1Pw1MFgYGCKaUVkPkaEsvx+rtm82wbniEgDQ0ce/+Ci08NTiH/L/GIwmEf7XVNO1BF5kAcNNW887RjvrIy8fOgxrnlv/t+szfc1eQV3OVmCijnY7VeOzHdE3ud67pFcxZSEUK9T7nTQ5hGP4C/numcAUdQ0vObC6EFw38yR/mBrqWcwhnZuPGEs2Pvi1643/J+6Gbl0iihngAPzIeaG+00P4tSy7vuV3BVizqNrYW/jCH0Lun6MqPVjCydg7mNvjiA0AlT5IjoXHQtC5N0Nk48r63BJWWBFZSwTfbRijTWdD6D4lkVwrpbta4wlb0Zoo53IRisBXd8Cxa7YvNI3bGaq7dbUoRL5dSOcndbmyDO+Abj90wY1R1MqkpWQtBNWTN1yEuPBOlAFda4y+MJ1YNt0RuPD9YHiBISBaNINcThtLNzKhNOu5HjU7JIb2ileNSgMZ/TjriqP1y2Y3EYq1mM793Lfe/C5YIfUU1ThL9bpFbQLWAWU8ZKIqsFLvvJlG3YOOL5SwNT2b9T/3enx6MR/NBWEweCyZ+6oIhJPdnFm+My5LXL5wKKRAvBxO2cetgnc3Ma/XVe0P7MUtpdpctqzdJRPF4m3wo87nde0i4lSZ/2zMID99NmxoHM62cyjZvW4UYg+r3fCSV7iqmoKFE/Mep38/HViiySy9UtnAelBaNYvMy1F9GqTiNOxWADL4UboFGtvctQAGi/3nEVzgfr3+XQX8LcMf2s1l0u3ln7VBUF6h4GDDD33XkPhyGZcAnr2FQTctYtVOGyYb1ZcvlXZ/2jdV0bB+mE3RH+Hblg+iRF4IYyGRQS3bh5uPIEUQ/HHT5lnQ/F0fXWwQGAf54pgL2VUoph606YPx0LoujfhIqhaYLLZdI9u/+buvH/mnhstzxnuD8ILRPNQ9uD2M0m+pWQU1UZIuqwQFc0I9PFMcShQ53kbtL5Rv++seohFWyQvg/flRE9KqVZD4hq/sB+Si/PPxaTZMjrQRGgicG44cgaA3bV/sa0r+++D/APiX8UVGf456f4m9C0PB+rJm8HBUYA7TwSxqIXWQ2sj9KKfnhdAU4NG7BY45lEz1ewIqlDDFYIyRAzfRe/KhFbZnuFTkGuUo3MGR8l5XSELRIWXxzxunoXRS/OT8B2wTJif/G9BrYdSdwJrqaZrygOWyi+4p6XEFE0mOHLR+5zlUtqj4j/22628PiM+pmqPw/FpoJTLmcwIVom6XpBiE0RYw5THDm9Zw9Ue0eS9dm8o/ShdisJUFCEQG77T+bbrPoFW+h9o/eBKWD05fbfpbO/Yo8uD8b81k6aRhrkDAjhSihxIPe1eCenVry/xLUwdzC8/0hxoytJkwHiUkK9i6/TE3JTym7orq/UVXOr0mdVq/lVWHYNEg3Fbgsq3alMAAWIaX8wkxphPGv5p1AguaAq6Gfm06IJ3Gn1LeJQ3vYZJF8CskLcyA7nwoPzvJPGx+xNMgGH6giEOteTCA75Px57VsLONt3GMyTduBq0lKrUdd13rHMMwlgfepe53UQI6Ev3JBmZDT+zmLOiKxOjwUl5p04JAKafhdAtPRPukNrBcH8ZxA8Uf2/P/F4CKzOc4B0XRaI6JLf+rwPM+pAFKn/3MC2+12VDvTSjeQbXOE5XmckoGv3t2WFdURbU82DCpzFokx54alNtvQK0FcqOML7bLObhQq2C3Yjg1K2Swstki/cYBqHp78MPGWUoB3YiyMWsEUSTfzjeq7tpLyUT9aZ7hvYwZpaE3YpAmBhRLQKff3hT0iB3LM3VuYilmY1IokRdXuM/9UuEZkgMRVlff2WLLwDuui/aqN1kQtAXe1DiYK1E1jfIqbe5m9tizgNq7cAJRD3LJ9SIBZ2px03fZyurss9NuYDES3x/f7z37XDM0vEoWv9522Mr34Y1/JuJ7v8fazU9CfrU6GDzxXABiaVxhdMk6CtP76y8ibLx7M8wxGvmfDQCUrmodlFzDI8sH9hbGHNdPsCm2wF0eElnxNOVSRh+QuyJDFeV/87g/JZFtKGq6gqPuZR0KvhMuU9XzgAI4ZieITpnIkOBFc9EJYLv1Be+FnNg6gCuGJzlcoy8SQBdLGfede5KZAoxPC/B5HQFJRAXabUmeu6d/EzaX644Tfd165tm8vAn8w/Ci8+6SQRIssIcfQYkmfdVxcpYf8pbhvtgzftgmxmgWJ8lQhnreV1L37OVEvKG3xj2vleZlscSMIpMTldt0GSamdRopHaBOcWNek376GS0QtBuhgVj3lfc01Ac6gujlvv5rNm/oBWxJ3FY8OUV4b8NnF64l/crYXX/oOpsQTrJ/brnMF3WrSlfwuf/x/8HV5VJ7G94wHf3BRt+JtV3zQo7d9FUe/sEMK0JVZyzZmJCnJXiTsRShRLknxmU+e188pSpC3zZZ5rKdoKQP1/3ldS6TKMhsQ/xLrEhSfaTUI4Kgl+7WkOj0HPmoGQKeYpUMjhvYmiUsk4tAJEoTvRsNBfSTQzBgxqkoyHLA91mTWW5aIAAEAASURBVMciPvg+x71nv6kVK7uOfkx6XwsmR+QQu7fpOjJUMlCMzEC/zh0HsCLK4ozCpKw8McJPwbtIYJcf+bexZl0SCgnYFa19J0pyggzNf/UlUKE+uthYrhGCFmlooViPDUm+vO6GaonQLy1D9HcqymcwrNFyrPBoDH3P0sO3rK0Et9TQO83cV+qXXH4d2DQzANUVFRkeSqOKJjcwoX1UmNLvE7bkZakudaWTzHA7o5Ytl0B0rTbhBS0glY93pZGP+b9IAuLZmnVtM/8UMqYA1wFbtZVUMrPHj7U2VG/Zvx2AjGXeXDBJNIsuUgmCIjCx/E2qs4xHItsCLeeLPIv5LXF4TbusixFNiWLSj0eHShfiMLb/hLSUmdLy3s8T26BAMJ/3ny6ECXcVnSZwyvcyNKnHudg+JyJrf/spKAXL6WpMaRxAg61V/ZHsaZdA03mOaetP12zTleK7wXg9Zdmu+88+XNP63j9AYIyE9yfd2Hn8sxtfS5JoZ4mv2wG96WYzOIlTJLXPBhb1lGN7ZNHIbL4Vcyz6xE9qBmbgsQm1j/H+dX+H0Tvujpz1ZV53Lsy8ZLG2JQ6jI6XbwPEXfG6928DB3l/oFsM+QcCGkI1STMz3Z5pt7vYWDDx7tPq5RRt8FX3wCxZow+u8R0JhaGLWinyxKJJvAsf4jYm1laYeI/sQVoHfOB2xhEDzg4/7K5d0UbFAhN8e6pfnBpSFeRgpI5HPjKObn0LoUbaMLvfjUbRZSwAN1Za7bOWoYDM6DWwLMx0pPyg1pVcpml9wdLPVw/einQTD6C8JhFBB+ozI09/4pwUlNFt3+2+AiFxVmFtpD6BRitSlgYqhBEXb9lmsDTa5cEa+dG2AgPx+LsLW8QNyGxbnFZirpGnGclMQy6iY9AQaLe6X/5enTBbyGrIi2RgyoIRyQ9csBCagTRjTs+FQpzCll4GxmrxqE9DeRPqIsA5QSst0dvG57maWKtqUfR4sYHFtfNKa8fRQOd8c8gP/IzcqE67FoilD8WHwXJxbIwtO8ZNqejI/0KmDUj6d8EQyiVC5JM3YuQ2PEU+q30wOVkYxFxEKHj1vFd/N5/oPuiEW1YgDc/EnnAB3abjqghu53cA5QdTdesBhSRpPqhEBVNlBz+Zx4sZ9wqIJ2quTH8cMkSU0yHLLMa1xfoSoUCY4ZopRHlevj+zdet5gKDmusBF1SKw7rjJCrajTj9B4kFums1zc7rs09t/UPhMfaYmLa2A4PWUdCl89EyCtA/MjYXtjSnnk07sYBIbZ3nufhp2OqTRm5ppJYp0sWPXttNZpOAJJVQ5gZ1HyqA0e++9vvJWaxUmSm3WcKcPi0X51UDSfeZvmbmuLB4y5ogaFz++/ymVLvn4PxDwxS+INLGCRUKYKKzY9foH4rzkINXyapqGYYNluJvdltWCFbJHuXrRlsET9cQx3v/xM7PgJKeAo92rpybSXXeleIyxxXa9I9EOS8siseDNJ97rAUq/XmPaH73D1DGB7T175H2YpOi4Us+zXCIGv/Oa6FUTZBrJHnXwCz6TlqFx2QMv8/EL0Qzfaox+0nRiNtG48QWPYSEuVjvcfcfhadOKHPvpqXwWuSokZs8UjHS6+4TEei1lInYpyTP6IKhKiMxyGieUHWfma4ckwMgp3VHSZlhY/hIAYIY2FSXAVuDSMdmclJdj9kZIU0sBukMgTNlx8Zho2fkMstkQFEheFYGidzcEK8/+khCv0FfgebEflJ96UbRHqYDwr33rlR/39kILiVUkY7V2HTW9eh2k3SDMJrUvcLbR7nvh/1i9M0W1AqnLbUKnSOMe0YfWAoJgK31BQ9jX2OkVUc7Ea4rbT90Egsak3FYhxdyPs4ATFS043uMrzb1hnsi5P4+yUOvxpKMly1Qla76OWr6Yyv5JVY6ESNU5iHSy2nCratOh70CRZ+F8gbwGFMMA1UHTQPwM6cutaWkC1KMX4RIUJV1rPUaq62cs8CqTp/8xWO5rnXP/RlhDYHid1vY4m90EJ0L7gYITiIQ4EsHQ7B++Efb/vSzZzo2rpTGArhaKkRbK38oi/2xfQTbd6a/EFlkyLEIJ7wnhNw4JlEHyXEyPUKQryOVi7njDm4yIYiELfFin6vKed/eKdFhk+GpZZ4xvfb02YDuRxrODALEaQUk/S0eCrze8IdFciss3qlrgvriP/5O3KMsBr3w6Nckuxxf/cSZ7Y1zLJqLTsZEa6e2lPyhF6ly/RlrBF220kvv8sAY1hIhqGLkhAQ073QNjsX5Hglih0mtBqCYCUAgSmxhGt4fb8Mdl7AHM3BuH7JolcLGVqN0lHJZ6URtIh+Oldr8+jX/ExJ89KSBjjL/+SGpGKl46pnQ+N/Z4FEkwTfpI6zOcOB5zLWcnWdOoT3nHqflj95BVc2DRqgtFv0CC1DTPXbuuBR/9Jcb408KDqISgCca3tQEmDGPGCYMufpXrX6fpDl9IvpV6FcWmijUlChWRI+jiMCnVuGlXte1QCpeqO8dgLg4037VlWMaGKPsSRHrjfmzuuFl//k4uVhBiuui+jIO0EeJbTxQT1rtZd8RI2OLSepM2AgjAsLfsywrdcnLaPezSAuIwJ2ExtuXV8PeEdWFUo/h2gdUdrAMekXs9mp1yqFWbn+qvueiIyqYyCpHnRLTHECOxOmWAa1HaCBcDzfnkJ3NB/mXuIOKK7h6VttvtspE7pIAr/Sdzkx6o15NFzQqWUCoPak2TTLXnqm8KpNpaI1eTk32zwdcKhFYo/wFb3fYE/lZzeJgDrlGD+3NIoFr23ZrJ9EINlsr2zoL3ophVkIhTlF4tIgWRblPIQwoOkQKIRqORi15RNnE2SSpn50Pe6hGMrXM3q7Say3EvmytKMexM8G2lNZIyW3gloKoQitljPHZaANCD6JukYLN3RODhtJoZnlm8xRxnbzb08C83w+/dLLWaRlQLIE5T4q5Z94iN8vbA44HVyqxydC70btSUwZVz5aLL52RTricEWOFi+5zSag/J699tiVkJFj39Nhdb258LX1kpX6bAOSFLsEojFyoPjXMHhykMG/dd+7koeITNa0SLJ+bzB4QiX09N4vSYkSijklm0AgZksAMaKMlzPrzm+TwP4FS5TJY6oL28+zxRb8QKirzDsIKvV6bzqwORpcyfb57icYc3S3BopbbKb6Frk8bvfgVYKzBtZsWU0I98VTIyEniOnf3QX8Jcxc4/QmZaA6pVGxOZrD51nIoWsbsC9x2zn8/VEwSyDZDax4cQv4u2UxUzfU+ZnZ3zUHfJexPLpRjKF6DjED1ukIzgZhMvaKZhjkWz1v+IvhYPX4oOMqdXnpv3MlLLDOh97Tfk4R5RggoXKS3tFu4GmfnOpIlMMGpb28yKZj8NtUQ1wGCd7VA706SXxipiCq7sd2UwT6WwFnrhfOwqKoGa0DkJFHHqUAmacUVo/EqvkLOpA2vHX/eXWLWZ+a1M74EyReiPoosOzUiVkSJaIEyFzrTLySn39N3U9O2iWt6Fdt4h5k+dbnNWRBzHluI+3ERTcj2QipmRU/wX4tHK7JbNlB7reOIB92J2hsHUAxf7bFEp9wcq4sxvziuP9stQN8SZseWp/ss88rQJY8my7cixFNZd6FClTwDk+vLv7LxTMEs25oCArsyq2RMvFmO8BZ6aADh1jv3O9w+k/vDWVZonuvgFmMdRx5Jseg7mIjobDMCmwr0YwsFoqeHzErmxEESoXA9axY5ABj3ex/93MtDDY/leI0L4a57cIzXVU7Eo4SnyiVAu7zlA8qTKlMSU/SvGrT6GQgTCwxGp+H1Ba5uKT8CguHxwb63r/QqxjXpbbdmile8YgaUH+YCImNSG89bdSmdaVvYRP30woztX8fbvCm7xDZ6MLaiM5wtx3NZe2+U6JzfFfNNUTYrdruhwy3B9d7rSizDR1eiDkXD8lbQT9TLYw2ICJA86DAVdgnmrTpRFwHMkciZB+m9awIxhNtFT5aKOfOhHCzyYRrUxCE4zjGKG8XqmMX3e7uotHCl+iHarr74cVFd6qQXhM+iRho2Y2mK+WH/Yax2pgGFlim8HnL47/cQHDjHouJuwv9+gplODEDpcTGRqTL+Rs6ISD2SmJYQS5/CQdW15uxleWMSFSKpB0Tw0EjSE39BIPmBI2U76Q4osim/Whc9/MMzlLKD0eZWgm9PeqJ9PROKS6GqD+Fjxq4U/DvgZpT9ZxZ06MtWkh3THPRFSUkEQz/yfwN7io+FnAbeNP08J/egPfZDkC6unym/7DM1giPtAy3VUvcRR90wyNezR0CpjeL4X6JKwv7ZgVOV5MT3L/CwtOnPGytbkOtrVTB8uxmq+XVlQoyrSSc+3APD4Zs4+NuUVzdMCMPUZGxlAaP/PxbwLuHIUGojobBKcD21ePcULh0p/2FV0MO/dBXlKAiGoSu0EZsaRmTdFoE6G20eKgdj5KbiuFyTZv8nPiAP6CSm4OSns/kcxPoKo9gWbWOH8jmb9ynyC/pSLQTTdNv0vfW3KKfNA7F2PocXwGYY3l8B06kxpESDaJJPAdjQe/0oTVquKYD2F+WSP7ElPGRsy3LliotoHFEScapulgYd+/inDY/qnYbcgiyDhYxo7dZ1KSJrryO6vyflCRzy60iSmw9J9mlh7EWAt/gqsfw2Mpf/l0ISopIcP/4z2AMZ/HGYCcVfeuYIRpr7JTmnUhyBe2sY9xWGH0KX9iPkLCiV+Vzgn6eKAZDBMFxjr+wAJGp4tXMiptinuVht/LSiG//QmXDq1WTPcr6RGEs9f3DqwQcdr6qhMaPmRiq/j9+DltW4TGY1dWCqvtnD++vvRve8IG1JI2NvOIcZ/v8LVaopzGFw6a7XS6t3srMY5Epu5MSA1EKWPEXNuTTpDOXx+zwvvw9+VjgFBh7MSH8b3e+npj5RXj4m9cHX0YT9IFfJZzbP3ZKCCmqPtgsJ7b2n5HebXXER5FbctBv13jJXWtzffk+DWdOXd1bjNVykW01H3u1yUG4N4sNiefknB76W4cDeV6iFfUhkMTGp0SkEF3AXMQTE9ts1qsqzQCCnh1qBX57tyZ9WmuX+2E/vuaIVlaPtzZiHNohN6KJGeGu5L1WONQfUryPX9kvZ3TdFY44SasA62uMGUQLR3WziFcVZKY7g1tVAw58n8DUx7XNxs7CgVGD2kzjQT+hiWyuoPgat9CLMBdDCF64lpFnapv6acVi8RmGCYTGupo9BO0Kd/CEvlHVwe1LKKWhtEGE/9bXzkZOlRExW8J572MJ5WmwnFyk3/avCvvskWcHtxDl3o7WCefWrKilOdu3QqinVQC+v9cUQ+lxrrlj9pYyFYdbSgLNsjsc7XHtEaDUnn9+fa7a4oSScRDn5zoZ1v+hyIE5arO4i7cue3pe/iCixQVjPPSc1PiNm5f86cYPNyNOgIY+LQ/WR5S3GhCbmukdZ9K2FT9ooIDGc4ivR5NST1kpi/LNUxj9e5/wd3qvXmD8jTyUN1YotLGzm+XpAth1CaWq1NvUoIOW1SrJcSzwLodqMpgosSXjW5EsL3gQ6Ks/to0oQXGJ+vwLO3UlyozpWTZMyPbFL7GxeRMnRHT2OykyhF1Qos3SKt5xj4D7H7xQ0LcAr6EzJNxHdQ1lfxOvSAORvx6TTfRv333PnEVoNEIChxg3QhjXMDZXzYmAG8uojdCuStNIHeeZ8xVpkFQS98EpkCfUAMh5pu80Dk/6dmCkf75/O46HShcNHQ+wBvi9Sz5Yv4evUuJB+ZRK54jEB7Hc2GCR/9S8B5tLP85OPOCWsDwzxO8sbwaMHM9zg4rhN0KIhoFvS6AnSSQFRc0YnEH33qCkvG76Py7lz4zd/e/6qBFcF+ZwD2XJkblKVcVohrNXjNy2zgJueyeuID+q/+iVSEMFIMR8WjJiJ7TldNpV0VCaRRUPZM9IRMsQhUcKpA/CDWxK7KlG4a/+12OFmq3Daey4n8ZwD+E6VceQjASISSyMDtACjl78KxciOC/c+1DKKgpz6VYcP11JQ2zxFyOHdeFfH8i8jxqBHPiLBbMlgrsi+ub9NTs7WN8QRT2b5vkBJ9LrQbWqLJEhkcVnc7mP180g5lvU9+FcEhBsFWbsNX8CPYXNRE2J4tqvICASqsLDvF3L6EHSNM3PxgQM5oC29OVqDZYNJcC1r6b0AXBduNCrv1Xa3EPjCDhQRBXdi9D3p9NCbpT6LZCq7Z8RPiwhEJY8Qo1Z9cvq9wApW2kp2utx7+PY4XkXDYVRWmm8q8UEINcQRsOXIWOOCbwha+JiOqUSUabnD5n2cOapH9mnBbguH5szoPEHEsjUwKly1kqdlZvdJtp+asIMN0FwE0btWxmux1UguWU5cnWb9zqYf5m81+psj5krhbgY86ETFcWG84iyxqVafqx8amCZJncN7+0/x6cAt1FprOWwpin+dhXwRhcOK6AH1MSfC04gtUWIjh/Y7Sdb4gEZqMbGYPxZK2lF52OyYJZcqwUxLnum1OKrK10IJxehgUjDVnopDXEbS67isdcgh9OhtXCGI5Pfa0EwqmviDLGrprrAOLMd3zUi7oaBakBaOAM122blxNDNSOb+9b3XDfDVYf4QArRcUmrDCPIEk6boC1d3mPBirmBD6s0AFxHdn917ulgM2gxX5TPogDIqXKQab+jBJ7CrrFmF7EBHme3gRHdZYOnTgahTGHH4K2+ZkNNt/stRm5Z7RH/kU4BVBsK9nSjReyX/NlgHO+a3Z2FvjDh+jNG6jS/kY3ywZrEA4fOgX3mBx/bvIEvSNAZemS+NJd1IqpC/0mrXuOQkN1CpSHLJYvU5q2dmLOsJqIOzjLv3iKPUAPT2HTeq4wW5LXfbpk92Wph7qImMjXeowYxQpNdAaf/rw6srpYAk5ypFpEJDdVPXCSt+7QACPRUWaWLa6jZ8Pbf4phvi5qgz1UoZoI6/UZzKpGAdYjC7OhQK2lIrNau5oDKgaOcmDQ8ZgVQp5KdYyGVmvpCjHgHS4JwOpvNGANxs1v5qArs479BZGkenNzqellxy6NxLa4RrltHpclMJC4+v2XPkeAkO/MKAgora38men0wO+7FuXgBfdBYFsQAB1naTudxx5pZEnVdObuMwrd88H47LgTgrd8zaJ0l5VfEBPkC/e3jMbnqoHNmX75Zso5K75p5ZgeVStKoM0P0KklAgdnJ0bGJ1/g6BxmE0tcGQBmZH5hCPu+1JNyfjzhWVJj+2mKsApJuuEE/4SR4tKbkuA7mPNpmNa2p4JWNSD2Yogr6QYSU9zaUlhrcEZIFFvOEv3mDpv6PamILJwDskqj4cyOJzQv5/EprgNh8yizx6/QdiSNMKqIGtkxlS2ZqGt49LOtGViRFZqqYHqfdmbVNvrjdlzcDmLbFuQTKror0aR6cV3dnnjoPhd9BJa1oWPNB1WwCOthAkarrTC1X8I2PEDyGrLea0pDMBSj4tiWC2EvYQaT0VK270PnWwpvOxMPbgIswmV1kTJhugj1VE8WVImf1AC08pRQaaT7CaBymtPqwLFn21Tip8LbEe70vaJFJuglPxB55wzm/inGrehiyRcI4JthVqazKi3MFig+EXjAbGY7elmDtr6PjcZwXgP6uPV0KUxPFvF9m1ZHCKV+lrQ5ekA54MLggV/rDXquwlqapJsTyBDOivFvoU6Zu9kKzKSXflbwOzPk4kxbITlVopFVLE5tWgY15lPOue1AlI+RQqLK4n53zVVffUbkMqIe554l3ZNfEVNZbmgr6ITWoaPeRscIgFA4wyyCvGcGZ75GKDkJixUZeew2GuaAAGuoxYcksuELxaeGaHVtkXgTl1Rq4BUiNnGi/7jnUpExvkr7pGuElymAx0X+rr12ggMa+wfomOzaItWxXH2lek+LQ7ZypAxV9pcD0qt0ZtRyEyHkNmdiz4rIUmg1+vhNwS3k6mHNQCdixvinh7ekVyoRf5b1dvuYzjRVivpBAau5r/yK9rdV/LqRN72S3ry4UmW78GOvFC643p+5iIX1zY5djqWpANfmaoh43swsCnlt4XJyLt93+7gvTmCY0Gg3BFk6/sJpODJQkUCkomn7QL6KEqDaQ8b6EO33oIws1hABP+BhOz+Xc/EpyntIqO2aqLsmbQBBMgB+AoDRInnKWmcGL7sogpNHprpluQCBN3CdQDDSVVDtdp/rI68wU4zHl5dYSSBSEDRPfv04fX6d3BqVl+Q+DLGN2rl6pG+v0osDMseMij+9pgjdUN5/MCKJc0BAhWPAe17V4c1Jo9uW13Ug9UnztNRRRbPeMBlL6uO7A005kiyjmX0fLVYfKng0y7SlQhvU1/eI0wVocsWbn+k6Bd+EWLNochvZduZ9O7OQfn3MzB/oPZjLq+jbzV9l9bKA8etEWwOdPFAuWpTQPu/38M18zJ2/6F14tq1szKFtHgRiqUWBb0HMHRpsSV4SF+A1GUolK+xoM9i7F2Cz8F4wSmbTKahp2PGr/O191sAFnx9a1dWRM/x64Jat0du0Bzyr4xRUjXhYXY3tTPwbmjkKxWKtUpmHTcOoSZxs+inkOb7S94DDhl7msA3Wb9v5RC6hfHpDTEQW+MvgcFX2pWaiFu3sgrUGPKx0BeRdhdQZw6kKVMOYs7xk2cmImakoqGfLFbE1Se6bH3qOU9HuEhp7SfMd8oA8QGeh8F4VVhLcav9RAmZl3UssufqqNWQ2gfqCzzLb+6QbaNPcM9wUW4rMaYfiDHpc+OTlweMyIm3vZM/yKJvHr8B/Jqj2/3HZGm9sd4QvG94hjtUin8vi8v/rMCQrDrcmfF1D/c/oay/G3/6Cw9rUJjaaHzqKS/wKfzBzTS2qfRENF+xDXf/Br4epL8dTSDevfvbS3crDg7xWgcVTL6W/+I0paTKOXG6Xm++w5Y0V+SQlkdJTUyUgmxsvKgnaK3x+27yT1rmDca0GKplAB5QwM0qbryjJlAsk/4jXj/tQOFiIE/T7X6vvv5rnAdgkbLPfiDQwYNqDiG89Y6EvufGEBZ3gBmfyyOBTpG6U17D2Lg1QXAgNI1tpjdHewmn2FJ9w90GkgeCfx2wlz9a9POwAWYRqBru1Upt/LN4OAVsLaqayKjHpx3zIwdfjXEiESeQEgppbHnMtvKX/GF44f3K+mDPPTyDkf4gEVut2zenHOiBrx7omoR2GHR10S1X7TuYiUmImU+BPgruuAnvmJRf316EkKNPNzsy/9m86nDGpvVRmCr8hoBlMA9L6/E+lcHesyAP4Ehca8+8Mi9nbBCATcJ6jJJBzHYz6b/7i26/1mXQkb2fylKcyzLAzeeIh/MNkyk3KEAWuCTzxIpGYQmbiYNoCb5jHNSzUhPcYgP1HF8n2a3CgMq45pyZcJpowoKJ1oiG6toL7em3Kih2dDkZS+TLOvm4jCYE5H/djv37oMYUuoFAYlCheWIKpG5pQ3FKD6AJrn7j2V61FSByuULDgZSpPh0TQ5qDDHcKPanpa2sUdsB3NK6SjYwAnFDHJpqjc4PYTx50TuHMoP77wBYhHhyEycEQFws3s2lxAAqLt46LFE+1KEGw/3dhrh+P5NFvP8NCYvmLfMaXU1UtLq2YEPrENyRI6iw4KptVyuO4Kb8Olfs3YCeNIZAi/+2S7xRPFuECq9U/shQkUc97MlrG03E4EsBl/Urqq6L2tuCmzsapQzHkbKd23/pygJXnhC/0rjjHbS4vXhS2Yqmm/2DdxdzTm+eG5BK+7kqDo3ioL39zE6PpUCPGZ5dSpRhwEssC7jcq8TdNKCbAkRiNO8lc5jVNPnsHVPqWAqoT04nve7s5/JzlZYnIOiv5+4s98T/txy1qvheOI/La+F0SBiVJbUpv2okGik8kp1QtAqfmr2OzXhx7i/oKzmEOYmnWppPQlSTAGaKGQaa1b0Axb2NhomHEMa/+sli99OcGEyCVYZGK0XcboDIgudRQqrDlvVxZJfT/AW7yNIDDUGNwKO0v9XYPWyh51pKTSqoj7T+Cmpsigeba2hJgLP/b/bOy1TsrbQf/CVElpoEmVSuuukfFrc3mKx2WcJBjvHZ8PQwpATtZlSm3B8KgGJz7ARCI1Y5MdfzPcMH8iytQI3Wr2sje6iLrkTdY5/rbboHxppfa3rmU0e4N9eqOynXFeMP1h/66F3VgJwZSwwJMLmLHHdL6YziL9iHKk6EJhS2LBJUxc178R0VVa/vvRfFfbxpcltBhRoCCFwWrrlBee8qrbBp25S16Q4AemAIYS3vb5DCE7blquWT64hf60tETjGoismA3+wyWIwQk3MRQtXsEL1eBkc35xU7onBOTzo0qyzl/G75wjPL4i2jmlLDt+teiievxCE+4vu7DCU21ArzOnQ7e6kPe6ZXl4mzik/PFj9mTbEz2t34/fzeXZaWlhlfYy4vSrOpwDRvvZnZvhbDUQZVtmtD5VDZQse1NJxbSJxg3LZOtb+21byOFfhaPnkBeRj3WRkcLWVCtcJFaKeymi7+/QOj65+wRgrNHWxx3/6wG1sydit/SdBVRlzjJO2yPoXNyLrvIVv7JY48d1FNghOG+QhM+jhJZxyV+IR3vqECeb97qFANwJNuvZf6dmFjDVTLXYii0ZSIVJDFwi2gylB/qlynXH0XS/c3ZkV01eZgq0k0z5A9opnYVVPqFdjf1shfRTLnBCfo5FaMOP+xXftbaSQx25AdVUnicJQyjutxA+8DgoMlb3M/DafTrZ5fccv+2sr3WqVmJ3SdTgkAiV958pRemvDga47jYtuGNwJVHi/kizvT0C3VyEkWEgRVQ7WYSW92YI7+HYMGdzepXfzUxQuWQDCFhws4o2HWqfE9XvlmwCGEFJCiG7Bcs3bbIqOF0I5hhuIpdQKRqstVRsus2PlmHpOerwjIGO2x55gVAcSiekSZlTS4v+Lo7w1LLPc/bZS+W58JNOzUfhbw8TpxAdfebXl/I/E/nqPnA3dqyJPV+AWuwp7ZgeGsnaroQpSNpAhBY5ynDyElbdn9uscCYBAO6d88SfHttiGT2eRskE4uPipKqyPxRaBGikmF7mrac4QLIx57YDUNEIv725FkEk+1n/xEkmge17Ej0v05mlJf+/mGtvdcodz6Br4hFddlSIJDZWWMkKOWgFH5F/nGMRurBCvmEqFGN/fSog6xQgUftYrI6BVsMvxK8Avoy6HBbxJS9P+aUgk1901rS8w4610K9wpnXJ1yDSM0iL60Wy+fk5I4SQUcf45LeqjXVRX6vOUOZVLdjrldvJ6CjWF6D5bizLQDBgzy471bKddRDse+NufA1EmBNJ/T1BiZiTVU/Ll1BVJShoj2ksAOW50ElR3cBfANroTbGUTiDER8bvhWhaH42Q2HUnzsOmgfBi0ULR3+JicqgSLwhdHGFcrPt5kMQyL7npu7RybokGaog4GubwbdpOj3FWECESDdtF3bVusYPUySOhyDpQarPx/HC2B3tXT7LRAXQKhSiUJRiCqIsBOsJvsmyqz1fBwz/zdZZSJjYDInhfR1kvdv6WwFdf/DvY7Z8Sz3oeTeIcTs1TwgkiZTga0jyC+ETNRWco+oPcQ0NKMQQJuaD4+EkKJicZvPuxvh/m3kFamcjV1K01rgCcsplA0gwlm2z6mxqCPH3KDwSaOUqxN0Igdu5WH2n4pzXDmfmMxlCxGn+Qo9fs5jOojf/F7VpcXzmNTwhktcUl3+BVSfIRkv6XyPeIZPtYMfsZHFPKjSjJJ1UlCPr/mw9Lj+Kg8JE45juWhpzPVXt0ViEfmgSxXUfxM9oFYqfdKNYxp9cuWnAk31hfIZNPyK9CRV0Jl+NSD4sNGuQzJfIwk/iu4DE2hw/ZrNmjhnM1V0ledxsEMTFix9AKLggcx65mwGx5y6TWXsCtygJenG7jT8PTBfcUoiLvFk2PZaXOtFiCFpsv4L77SC6T2JfaChmKh7skYyG4BoDGsTEHGyRi177qrsS7UtRMw9EExm8AXptzapck3wSdeXTqg18Zpj91B9AkYpsvrLq3dzLj9XWNgpJ2UluJ/8Vesn0Gnj9L1fKwxf2G/dSco9ETALQFLpqcckBvoyVCEqeW7z+CIEUobiU+nMGcbGirIbJ5kai0jje4nDeonKDLfacteTVYoq1nQv0Pu9Rm8MZUuRtlwgbdszuXZ5rMZ6u/Ri+HV5qRb6WZAE4SmU8tRjPlZ48r2kGL/le6VW6eKlLJSLZ0ca+Z4gK6PJQ2CUBZGdW3uQ7u9lhmt5Rm0qg0t3i9SEGkWfBrHxC8KkpHsZXoxXfLUIiikmJEGYlEPpoM2aJtpt+c8r7OGOAb2JbvNXZVrmBJQk0W2czFJVaN0DODiRoL3iBO8rf+yPSONb37TpTDAGRPINzju4izIP61LA38hjCJIEjAIrCBm6HHS755gC1DwKjvFV+fQGjJZs/tkIlYmH3ejOtdJF1swlxBLCSzxv3/rX77ViqLgdwOqpFEJr/6ZHLxesQXn34ohmVqBT/yfrj9VWU8AnnpAaP7xJZmBHWMlTM3uOmMHIQ1DoWFgDBaa/Nn8tu6u7ZIw+CmfO4+gwKALmDpIzSEWbkumZY/Bbag3mMZ75INreeXf4RtwLMhRGduNYBavn4n/RdnWVgDJXtxOTXBHO8/XZSExWinayloW+VvsDBYP+RELtbs5DjUoGo8fwPvs1m/SMApoJiHxcLdZfiTEyWkNiDYuFke6mEpyoU8x0l8VU5OI+xIy1yrTAUb6PwTthMWJG9xn0xz9oGtgmDSEx5xI1TcbkZgTV0zAMNrTj/lReWqZScdMfjnMmqyiXETHvBkBSP/R/M+m11DuB8KkMcK4CGJn9lJxSEglwWWm+ZiFRNDmqQzzmgKpkfO2YnFlXVJaAotufa6L4xK1d2n7rA+aKV6LbnxY4E7ESTLq5l34ggTmC6HsgFI9AUz679K56/UkPKrxX/q4u98gh6djKZ3vjMrYLcUdfIEbOvYlMfBbv3xP0woywr4HIY8droMt35uHdZVukAYI6sGm7fWpTdnn2D7btYIt4TexsFwqx5G1e2FabAQje9gqDua7r4Iwmv83erHXNbV3K4BYEybUlfxVctJxS5j9dZrlI9pYIn56JR3ChLAhVt9cI8R5FQWey596wkrAWk4pExazVWZKck45Mm2c/CgPEOmOQE5sp44B1B8sgqYG9bc8pW+8CkDGLrJ7ka2g4mHoWbMUI3GmcLY8bFYKvhAFRp4AWJp2AAzqU7f2nVlZDjSkTHuVoVZTFJBdBNSFwUidoJZegP8CnEjI4yS//sykL5ZCdAYuM5phLMpKCCZhVnCLZVX/oWjLiEaxDcz4s5hBonOQc7WvtdGE2fuPklYOQy9rDDQFjTC963h/a6JLbSUcj52AGV0zfwGqXNki/zCFElMIfhJhYuchiVJEFMupItymSckwtNs2u5vuCs068VcG/H4MC190ITxh2I70B3yMB/Izzh8b632KnCFV6c3f+KlDhaKdFe5K9VsNlZ6adW1NOnDelB/TAVWgoE3hcSirYxqJds94pvgsv62QWE3a++LepDDGHVdXsKKo9nbBmvStvtIfWGXRFYFYknxyYtMheWY/hqbW9u+6VUFo3BzAl20nC5c/Cz/iO83ED8f2SWNi6zi3K9UZZy+CwP8zEbE+TwmYuBXrA37MplvnR0T8G709YQkAGMMV5dMcs2E9d4FtQT38fqs3pTqX0Xy6sEDFnqGsdTkH7jYTpHGrO7vxpTw1XUTEsEbPHkCwCiphc4ztaumM2mh1b2SIvusLTBWelrFlGkczck3qH+lcVJ62i0GxZ9EW/pZjL9fVuFPh8EUSpFrz2zwWwnTHj0dLDoQRIxufkYrZoPxQEPx+UzfRErqHBUM11M8ldUay0tfEHb9DuGZOA/5xdwTvMS0W8doF8bWNW9j++HLFtdBbj/6dJSHidNOQIZdA38JGZUNx394NoSoKlfrqtA6VpBmrSGzNdLWYic9Iz4B1dX+6Ye+6zGfqcoGQZJ/oPJzhlXyzre/w6o0wCLpljDRRFBhS6mi96yQqfoARCe2qxpKOCLuuMFXeMvgYf7RHexOgiczgoC5ML+TTiZnVEelsomHZXL++gIFZr939Gq7qkcKnu+A9SO0aYQz0aDTJ95VvlzpUuJNQJP6A5lJ0nT/zgoogk61wQPuYRVFJBZFg8Ly3kdEjK5RrD5i//AyEOrWd4jeFxkKU+mbxpWFKKVVH2ZLR2cKEsgMHcyvYJ+Z0O2qx535InlouzSelfU/xEbel+Ar3yvTf5AKNUuB2KUkjiKud+yN09Xc2vyq1iwjAD/1ofdv7rPYmQHUJ1AKwWNX/YGRTnqvfRyaJd64tt2j5V3USEWE0v15h9y8/4yku8d+pO5VLUNBj0skKmaywPiTkd1NF+6wd4mGfC0y8lhWeQ0uC+fXID4n9rEnomqpofswcpQDLbaQSZ3oODvZfMP0Zz2J2+VYOnugi6zAxovrdvfKe3RmwEV0ZpwcpIrnEvBScmuOT5DAa/y4R8+EBwaf6ixEtaDVvfB1rN+IYrqIqpzWuIH51aGvdnof1Thy/QooWIO17ObQt0LJh/BbKS5grAiJ90bkd7mX3mfqjxW1J/UJzCO43HDfQfbvPsGVlUIrrTKHBnYcKb52GWLa+z3iBGfBEJcWQddW9PkviFUQWorkx/fMhK1dx8tqmXhUAA++FuRUH/X3f5/vCzU/ZmvxFnbGCkuwxPpeuYlQhz7jomnXOf4e7jC6qLaaYNpOyV8p5u4gBVo74jcs+LFn5kUxMwW5BNbz49n/sxd4LzmfUCJKZ/n3X3ykbbMpE7eSyD1//maqr+jmijaGnzbIRYzAgFSkMO5+P4KAIOoMWYaLatziyGLhfcRSrKJt1eVzP9kNsDadPJN9DmrWb+Pl6ItCwRh60Ju4PYNZ/dtSlSHfiZ7BYXT4Xjp1Vv9lUNxHLT69KcaBaXGfcw42mGMysmj+B1dse202jMvQteXCQ0gGfNYJBfqIfP8ggbonoeN1gQyqRyqAPc41pvl5FGsM1iHkVFdQFeLkU+wulk/dDbYhpKpQ2vN2/7vN6R6wcFktZhSOXDNP6tvIkYx2KLRdX4R1l0h0OR4Af+BA9NZnG/txH7cujjR1YwRVhClD8BTeXHr3PjhBLaXcmYoyPYdr4fRjyRrl9dQdtGaSXlLmGykIZHYa1NDhHjEgRSGgmMUgziW5sOI4hqktz5SeunACL2rCqnnN8h4VrY+IaaUC3LWM+/zgBcVPnMvUYytCKe56mriDeF0cOBDrp+lAo6mz6XedHJmMcs1SxmK/SaZaodWnFHdMvD3XrXJjcvvp9MF2u1Jm01nr6E4GyUHI+/hIV17Ve40/e9rv2f+mfXSAMSBclrexiyQutCMDEwosIKKHPdEF4NzOJaUL/OrrgSFyWcUa5XBRjGBrNKrA0T2HNATEr2uk7bvh2RbBKRi43AlyoQlxu+vJtE6mSDJYNAut0Stel1sRkFcn3KvSyG85tgbDp6b4uQjyAcJoqZohazvAbxNU27+cZMuKxlLRmydYkfItjuN0PSYJBLLviNFomjFYXBeqB/0+ea+yYf0H6s03djgAIjhbDfVnoSPY5hkKJ11ZZb01XysL3H3Ayqi6TP8tidCsVTsZ97w6pWI8gTNu7XxdE0SyMB/yY77R1WbPAj0AwXBj82vqyLyaG0CywrwWE4vYv8z0DDAe+R7UwrEoZLNy8G+mQ6CVyl8OKcK3yppPIaaHPXsMN5RPAu/BB15ANSY4w8b8KNK9DOf9pPuV9MZW6nV6qjg7Kkmod+h9B8mORnGpzVG/5kWPxi+r6QmrcBaTSWRS9JytfMI5yiqbxeCUXjqEqRbT6TVk7qPqjAIdb+Urq3v0YQvwvc32sCoYXYIdSoGxXe9r3MsD6P+Dybvv8riXKQxuc6fRoLOA/0g+KtKpdL859Eeea1aEv6T3u+XUfkegVP6utSrX4CQShtx/aUxkFildy9PEttzP/EAYkJS9DiZJ9qWMC/sRdlgXUU2f9mJZMqse7SNIAXgVeQWjuz85tLwSftik6G0f9vI0W2z9LUF4IJMTgCeLJy1o+Ux6WD/0rMDfdpstU0FQ7qV1LsOy0L/OKY2KZ9OhSbv+goM5IUKxtteIjCsuE9+/0l/z++GkFZEwYYOyCkDqojXVn40gUGu0RxcJE8pykG5NkIisTh4/KihxmvA6tKfE7A+R9NKy1wLeUF79Pc1xwimCVXj/8b/jEzbRkV/SZJNwKDNTlHBN8Sh3mdkz1u0pedW5D8btM6b0OVzLzwmZc5kxzQdFCBpaLNjhPANRmV09BVH7YZmrMRD+Y5RlwGPb97DI08XksrM9kPK0WlMjHymhKVr1VupuztHjxbpH/j+42gXHPspiKJiXCiolFLDOGwss1gXeRYpMOXymrPeWmEJmEWjYcqtwWF49yWwIAaBfE96M7SIaqwZ6xpUbQCySym+cv6P5KsRy9mZhXz6HUeYxBh3p2SARTuuSM/Gu1V1lRXPp7r7FxJXt8zRdZ87iBfG6DaZyqDvAU0WOG2BRuRzWIbI3tBPaPzgwFv2jewk2C/SBv12BQ4xTZN6y3nPZLtgY0S3JO/p/G68fHSoCTgapwpNs8RhemQE192AluqM8wy3hTZYCYVwT8N3//DfoCuJEQ+HI3C23zd9qXLerXPiXnm35aHx5wjOFgdFnvSu8qmONnbiMAlYHAl6OeMGptQ/U0Tx6XtjkcocaiJRxAzYg8sCp1ytlqvNVm6xVrfwX3d+EH/zx+UpeT4VSsWf63LbhmyouCaK9PmQxXWx8gK8IMSUDdrLfPJM9Rphex+2unrSKkGoLVRHGP/hp5LC3rBoCjWmwsocwLPDj5Yt3pSsXfawdeDUIuKralDP6rzF3MS1wmvoovjfIo2FXTtx9zkQ0KbGoZzbspbYQla10YdBRzG0L40L09CLWMR7yP/KU17jEdr1rAuCudfUrvIC5I5mw7kb8mm0EJ6KTkyBfx0TSkaOlEp5gtlcyvmqO3NqaeQFGP05P6Da5W4InpGDwgYBxsgCISX4oH88ne4J7hp2ibWBR1G9Ynn0zNNvId27U6/kZwTpTkV1fp6lsxq+HEnpUkKYjtb3IlmyVDEuCzD3cpctIZ0YvRhN5JAIT5/9lPpBhx9zKG33Y9iNyUB+Uei/qNAMv4LXmuOGd8j085pH0K0E140d9OJTCLkp9B/yfLaWX2R3sYg7tjP1LMGPRL0JDGXSB8YUdt3RGb7zPP05r6AH97dCzXtec//jz8pilKY5/zmafIB10EE3O2WyXWuaF/XHr6Yf6YOXIIzBqiOzTIVtJEbUdy8n1+xpYVq9ws9+AkGPmoCUrkwj8x5dMDTr1HZwWm/EJF5QtVsak+4+9NjSSLW+ZkassLEwlOs/Je961mK2DCKDnuTFb0alSr//Bf5c9vDr82nMd3itPPf9eneOVWVQeX98Ujc9UNi8tmb/mf84MS+EOXJ2eQyGC/joSS4dwFghAr0bw0TMqoofqZpWk9TUsOM0gxBAVtHlgA006/7BPxATq2CEVhOn8PDVvXBrd8g7/vfZ1lslyp9ncllZL/ElqxEBYoqR9+wWddCztmn3a90vtWCAAm80tqTf2GLTr+anBCzsLh0Tu1/PO1XllMF5EqfKkVb/ZRi7gIN+4JkO/4YiVWn8WvF0QTcgQBnU/mB4MF4FWF6CYyZ/idpXN9JaZXtyiCO7PrKCmbr7O07HTmLXHdpb+0ce+W9c/7sLl/TNBK0F5/LIuSYdwOrlxiw+4EnCjACrLuGtYDtMxoydAW+BlJSMP3sFJxmHK4QpFMe+A7wG4IxjTKqXjuRau5V1Den7o2aRG8AtLM/YudOFNqeXEMwJK+bDv8vlIN1HnjIZCe78uq+PUVgZ6Qg8mv1WhrhKskoDdjOC1/Uw9T/Q0cHA+x0X/2CppSF0DkL8lpmDjWxLWd0Q2TlURvV4c1Xg+6Qasx50RVb76LR20U8FULu2P64nShZlqbKyA3ZX3H08YnNMEYsLKq6o7Sc36pkmlCVv8ofYoeb+zWWt6NkjX+imeDCxpirAIaJDhHTftErJrD6pd8uTBQMnePuvMSeg+3aBCaVyLP//2uURYzhnTiuEvPCe8AR0DD01VO5xSE0Q0/gYsnB258tBgukN2LfPtVIvrRe6FymwxBSEnu4PnrCk0lu3pDzl4HCAjVXcS9MJJghJtMAw6JVPgEfF/bLnRy6S9AEzfHCoxe5QOc50EYeV9Yp4qnTz4KkXgoQWiqcLrinbIHsVgLDQRDQbx3fuRZ303nOCqbGG9T8pS2ht82FdwKRWE7mWvjzCN1XHlwKym9HF8/1A8QIVakh7+12EJD1ewenT8GEuLAOx1MixdXi66TiFyMbepwxQaEQwpF5RH8S+kQfTt1pgT8GsBBzUJSFcjnb70D6ebu0xKlYEyAfOBlA3MuDzfQHcC2y08Fjq8QshhApSt9w7B8BphPe/f95QNBoB18ZarNf4cQy6WfDtomX6EEMrnySkqY6qaYqlrO0KWFZTqstK6pAkN0WQVHcz+xUFohV82PcnhSt6OMIjLyDx94KpeCrFzPFxwe71KPkYbODUW8MJsxnwYwbqnffWkDWb8NEKVBii9f1qQ/Sn0gt3BYQomuQ/w7Txcx1sxonJ2iUIZug7kXoYFCtavrKtw+jUXPkaJ+5wvNYT0Ws4jfBjkw2Qkdz4kd88EPGXPV/vEvDsMKqg62yE95bAVhzh9gLYDUruJ3rhQx4cECo+b+RJ7JOji1erCPuhnUgi43GOGcmz+VQBAqQmq+tvV4lDcV4dxuLUWkk+hMH0Lr+/AqEfcZL/QqOw6l3o/s1b0IZg4a5njFP2j22ioFt3wJ1iDvaScdVzpKzuh6tOyH1evtAbdgJPidqTpBoR8fhDh9+oXP01vZq0z2g6zllaAf73IOLoECTxR/w6R0cmisoBPB04mVEEk8KN8QKRvr78wmwC48tNZNSEV+dwJdeXUmyBVYQj1jX4Cp9LrGbIM+HGTOQMGEoHpwcrI+YR7DPa47kj6gvT2H5gCtoawqkRyhS9CJeW8euX0bWCbW1jAEXs3Weify+YzO9Oo9CiFhxJrw3v8YACnq/JazUigP5JkMLfV+a6ygGbq6xU56RQfU372A5yPtxajs4NLSTzfaiVpg/hrEzPO8PEnt8C4/vcKubNRMvS8T2Ud+JJoFxD2ZAQz7eO8LkCZw/DCk90hcNxHSX9XiXWjSMePHj5OrEfs8OaXPRgpL/Z3Sh6uPZRCSCMDP/JUE35tUck/QzCUaoN0K0OzCV2ZAJK5riVBiEU+h/QbkCC3svFYftlsiQkWm/4Uep4+ZT3c/dsRb4GGPl/4I/IE/WpGUaAJVmRCzF0u4RGosi5nm80aKFs9H7tZsOJeqVjonLFU8SgypNu0RECMSa1D7HVG+SsOowM/eL+oHcnlXmZFnO08GKWGkNahaay43gPD1TKs+1ZS6ACzV35/WTQgqrOaREkROzHamjNTZZMUxXWAKze2W5S1hNuzAwSfRokhzWsVOyoR0bAxnX6yCOy1OC3iCygpZWNF1RGEBueC4UOVzmaEahJWUYF5nwWu3lWT8DEDqFUvJcBcNGK0AfP8Mpmah4Vg/TvsQ4CtxAecC9WIhHd1MUF6F+zoXGvlVz0JbSo74/R33e3qydCtY8VjCyUL5hRVPdZVgn5Xucj22BWsdS5FMJqclWSDJbWwGMY68rBfiVORQLcv1J7/UCuQjyOCkcekN6AVCdjdad50BWFTEJaUTGs6Ti5bSbRe7wAGjOjo1x0KEANVS1EM/8VjIXtS+rndzCbQwt1k/T54LTKr2/FSaJ0xTi2D+9xHnt7pvoN/SRx3oqigJ2xi4039TVCXdA9/QMyjaaIXNtddBGhgDDxrAG97o7gs6nanWWHRTWhPvK19EYazbLIB+ozfbpXUgngEeI23g0CEYgLvBbD5omuGtxrROEcSzqQQ4YH0rLbAHiuA+Hjt7MUEnVvuH+z9bChfJidvvqsCnlvc/1KNew3XSZtlaviYCv8TJF/l/v/DDjSwHepd/K111r3xVc25R0suYp+pj3fbx4MpsBAADQuYqP4eG7RU+5p/LQhYHYR34VXAtC8Ve5adtsPuaqAUO5AL1L9pd4UP4xO5ngZkvu3yAZubxZukF/J7D+3uBFYmTL8VoU5olYMw7n2yyEI75RfV55J00DN/HiiFDM89YR1zf5yHF2pnfPXzwqFxwstC0I2r3133bpyAWGxwdfamHKdz573WMXG7bHKe6p0S83+8+jHIuKrWKdsuYp6rhymXZ01IgYdubvaKbmDSUaZrGwAnx6zeNlePoHPOSzq9gHDENJhzUjZD8zwyHhoBViI0oliEgHYVZ1I/ccAOAaCO42f0ONSFzS1sJR6SKh5nIg1qb8p96J71ArImC/vNvT0jyGcPF80XR4Zq0qV6PiShmq2H+epIpgcU/B/UFWTTra44zDMU93sI3Oo3WMoQNENy6LruhAQaiWhZ0rvhtjFJMjmoBDJmvx8Hi/yTBFHFQ0HW8ByNflAWWqg38LkwXW9vkPMc2bVzvCwZJo94zBPAx5abWxmNbEEtOxj8Nm6NoeCJh9D1i0DGVz+Wrh2r81lyqg74DndPms3cJMuFBcUtpAV79z9OZrt9ASytwnuZ5P2EIsJm3aiEvQOACBrMnw/PDVUUdbfdagkYLr/ZM7X1+IGdpB6v24VjPT7fOkn8pTZEhf0D6LIGNfG8uzEXSsE0lXAAzXfsrC7HTTdGbgQCjvvKAwvUd0n971CL4mrnR3SyVbqTAmsEmHqJkLHwqKr+1/ghfvJoYa/5ViaOCqXll0hEOZvw1OVhYdptVlSrgaEH4dcaqoXOSvlar2kx9nfNnU0A8bljdCudvP2aDWPQFu7GyEGffs3yh2I+ZrGj5rWj7NjwT2WfTSLvdrrc4QfuJ57evBBDlih86wzLE474hFSjAW1/6zMvTKoUVdOJclumyEk4Lw1STeLKpiK/KG1y1K+Ll3AOhWwkMUafH+SGboJKu8B84n0rmS380jP4TkZ4qOWQOU3Ok8PU3+QiFFLOofu+2L7IGuQPUX37EPhV8ykgG+wADit84heY9kB4Qjjk1BgS0r91qu11hv5IOJYF4FXmDvoHEGuNYj2zhW36r8MNBcX6SG242yXZjKDibQHD9+Vp89ezUuzWCIMFd28dfoVmyekU4K1CWS64OPFQE34nGqeP6xnwMkbYFGQm3bJU71io0pvtJVwqmANjumDom00bHHX5XDMGqA9Z/ayXVqhPLThhSVuKf+vkv3FgbN3/Bn+K0EBUw0lcaCNo7aSFaGcrTC+N3Y4gVs11LSSCRi5YbOrCMWVk7OOcRm+v5jp2s6KgFrBaC5StbFIB/EdW1I3DSE1G/t+G2MtPm0VuFDeyB4LeNbNge4uXa10PET9zrUf4/91KUyADNuLZFCdq5I0ngmuUJTGGc/B+Rz82n9RXEsZVr6qUZ3oUdGa2QLweo5SN41uoh9Mf/zBfMrdmAnP6NRPrbdO2BQPqJ2gS63X7cukIGw9LxK/8ISTiv+f1hVebWDPFx2gjGOeFt/+okNSGG9Gn5fxdEOmlDFOe4P1BGWz+lecpWBiXnwng0M2pzZEZ/dhRGbNE50YplZ+LlgxJxrIgW1AUEunYAy59tXLX66C6BY8uYQtc5eKVS+IT66k/lZ+gK9HrQ5pc4RTsIT/nkL8Fsb4mBFLxKsrZa0qOFtuuigKqJsRhIAyoqiN2DuYIkZD6Fa72RHE/JfcgI0p7xra/4A0UfnraBUqwJyXIpJAj9mIFDLN+b5b5iHL1WLwGey5JPmUkQHycecps7vkDVxxkLaM5k1bNTZ7Q1lKawYWFlYZRYJRKiokMIqwWrEvgorsxQ22TqroqW2ntmMrCyuoEroV9XxOfOhNSgnP76AABAAElEQVSAZa/ZpPI7es4EPrYbJ5gxdqd1W4yUqf9gC+C9xExUkJKpG+sQvYIWmImT7zDalNSZx2+0fx5aPnjm699DP/KYJi+BCd1vvOrJgYyUspLezPX/JxSGLualHobJNqYw37SBpjuY1U/ojUrTVn80T+vKdJb0bZTkU+j1mb5D1ate91FyW5mvRbE4S5iOxvPRRkwF4x/Q/hNUvVi8NgZr2A4YkiLrcAqU/Zag9ll+qIuzTJFn+F0KZNad7oAQAVpqXcIsM8rOc1IitKe2PPhnoofNO62RJlCZMZnrmczNsjvtk5xnm92X6+wLPfqp3P2GpLJTY55WRxR/SS3sTMilgtS4tmWaS+f8MLc92/cTheLdmx8263GMeCamLg5/Wz3Q7QawTbpj/cQWKQn71RvtItgKGx2fq1na9ZsEnN76pA+EVNo9lpzvHaaTH3qO1Yg4utNwaR3yCpjvZb0eiQW7qUr0jRZDTdDk+9qmvlPl5lSZtQxkuF5RAYP9qvmX3e0xiun7X81pT1Skd4JaO3hVPv4m7QE4Aa1wVZZzuGImiDc3fqzdqabka180XaK027WRaSYZcNPq+WGf2+nftRx61mvJs5X/8YNfJJ2Y+xlZ7FKS0mfZ97dKiWEB5xEkVUpzsKWEF3JZpnSjFdRU4LfQHk2OS0hkfj6IIlu5KdynxDYH/ELDwnqLpi5uPf+P+pI+qLAw83lu5gSoq8YsCkqjTKWj/808l33NXwx8oknErEwCIGbEOUUjO4cdIbst1JmWHSRLaNgqoYrnkrGJKg9a79xqv+mOL4pPJH/BJNY6krFmIfyk5Vfm8yk/O+eHLjdZehBdb6W2z6CgnG9J1QieCmeq2DTn3RDEwXPtuoEJSjVS6QgVNr9DnlSllQgE2Ke77s8tsQkhnvXv1+WgDv74oVLW94l3LMhjbiR6EFEsuzeMvPkyKUU7r9LF7qy1JwZWQPxXavpaw9j3uOe6C4KsVxJNkDHc9nmRHGrNimzX+eYXbalpur7depYG3dhTwXJakLbq4lXsx6xG2RTMhGcJLYtrSIrb+WeLx7o9sYyrhnD6KumZhezw2cZ9RHL3hmvbT6kKU/26ZM1UUORM02EeL/pYo3KR/NOnjI0LSWy2wgbAEV4QI8l4enwXY2RW04Uc6xoeZpqLauCg+L5idPVGhvbWf1kZaMy299FdyqbqJU0IUuJmpkU6izAbZY+d1Zp1AaFWKODz62nv9nKUj5PFiW3cBwzFXhft6akX1MDrf/MqdakpmomiJ83hGnxVK7pAzZQI89RxALvG14IDQ3WTsxlmT3Db+cxHIirVoSyZpfQCr8xKFZVlpnLQHRrGNMzMeQIozYipnEBWSHiYHIolf085mJoWMi9WBl87A3z9PiOeQnfHvhpggVsXinGzClFMVdOhk1hH1gD8uTNrUCnbKbxhOB/9onMfEGYm3pfSsUBd8EOfwgBLKAfmD91NtMYgrH4ycB6c4ROwKNQGlq4K4JsaP9ra1lENQ7t9y79QLMkK6QuWTn/TGrXGLRVz+NKF0FN7qw8O+df9ja1U2qlUJszPsoKtIQJAZ35iN1UP3/422+TPuAq+BvVihuTGuLeIa0Xgp8SCPdvXmADXCtE/hIvF63xYGeVifL7AdOlDGOmcFlfbvNwmZfjM9R5GgZKJt/yrp2Zgs3lhotBJ9KdC440ZnHsuZU2ZEkzrgtlX8K0EWyRRl8bZDvaCGRbS7ZTQYg6F0AC/jElj4dPuFnNJ72pO8aV68nz41HC0qRXTUevsikOTtoE+h04dWgoAc7yqvo9jye+z/lY0n2Tu177hPBod4Ss5o6riv8JD7uzb8OoGxppjDrZaWipwqCkkTEHOpZwu8gEOI7yRZ852Tf9X0fd2zLAZ6G7/ZqkO/CYslsUG75Vd7guEyIP69Ix8ITGjaaTmB5SFKmbqsyhoLpMkRJ1cnsHsc+HnVTWacfHauKGl93QLKpcRpOazO6fYlyCjpBsf8pfaDdG+2Q01/ZyWBoXbXu9ZLmkBSk/GgJ4sXgk3OOKIeimXOvQt7jCpbaMvRXBH0wMaD+9U715ozWYNYNaArvjnz/Qhy2kU+XGyS8Czeg4YgZmch9EGGFhLj6awVNzbUfI/PispWjFckBVlpvyZzT68t8ZWIKZe4jjL91ACsvu7U+36AuGpP1xl4S4UHkR15Y62GpufS3CCl3/E2A0aiiEJ9RzVAOsn8RdUK9nVuxASdlbUm9u4aPBRFmubSUDH08EVtys/Ef5+4TwF0A/zVuuY6ITjVNPDuHdLNFf4eygdKwnztEH+ZnzHKh49ErKM+FyDt454xEDwXJsgg4by56NYRdB+6YNb+w4ta5NW7FVFsrpYXycVu88rE/E7Pzu7HzyFyb54F+QcfzAiMHueirXc5IcQ2OnTfdOaLiNDHErT4OUSypAyrWsCkHocdrOq7+teqZBJdT3s6qPZLrHInzp9yNTS89SENvBBborcmfNpdGHNSYX9qhQzVJ/rkbbsYUgPPI+2MZ6aUJSbkvU8WBB3NisIT4Yp/Ac3WOrmGqSDCKFrhQiqCZFtkhGkbyItzDUOo7yYHl3ma84UdQdH4j2QHtx4qycFdUuOZfqi8omb3iMAQgF+pClEyREfjZAbXxRXuS0scTodT5WfQJ2X4MPsTmJN6BiC2ZA22F9AKt8Fgb8EIpiKKyaJJDKDQiWBhRZ3OgtFAlcpWBavFWzyfbuxQEvMNbVMWbPqVITtoNzh1y94a3ENSRWNX0VFY37D8hVkd8l/zEpHdwmSvF8CdfRgfo32lxjUmWuJNPiAccPUuRZ1Y5WEyah3gt019r6yA4fSkIYVawsNgFzGczdUVn9mnt/6kV6EYeNfuKJV0yjDEeE7qZn+peuzFWxJ+GaTFWIG7l9MnvAIzDve5cVR+KFOfNAoz0y2/2vNqTdUKvqDvgozQf/nBL+4WWKl9VyqiOnDid4P/EO2b+MKPoVtPPGHzolhEai8r5QGSTglgBASwiqlbBMkyPGmJJFVANGURPzMayVqbe87vUbELImtGduTIii05P9ndSqFvGTOryKwCxVnxf8RdRYAXhZPH19EBQxQASUkJKQFEQRpBKRLGqSklFY67wQkpDsOOLpBuuFopCSk647u7tz3853nx//du9/zbMzG8zy7s7Mzs7OY7FYZNjJU7rRKdoA1G9RoQGKPoZa9LObdCFd1K3AQ11nPHabs3eCxBaw7pF67/PcTEtk+HHDV/fRw/9LypprMQkDwejZVpkrESJIubiO1GJfYH3zKoHpJqikGlZBnsSVFcYajjziOH4TZg6We0Ee8NC1FcG0g9+B4Oq8z+ELoY+cw3xDlV5af2L0uGZxVc2iCSjQlQUG1+X1McAQNZCTQT/5y++eEyoFFeZ1NLbb2zy2BIu5496pkEooxF5QPSRGUjQgKX1rhtb2B8Y3v1GL4bUT3tIPEVEocZBJggCFBpo2hoqTVMg4/YQFZkUM1LuVWa11CFxF+CSpzkwtklz7b8jcRjeuJPw/DXVsWa8sHuUNJKiwoE75G4MRJhHknhyJRFj4g27vrYyorz1mfZ8+q+kpoCMPpvuWO4WEiMff1POeMWqBYPbMLTVmiEIJyOh90rg/kTmnlDSOSqQ8yU8BxBIHWS6rP3pg90NSlfFGaHbmv4/KtzzUmifRPP4JFoxWaK4zVtmlsFKUMXhjWwnFP34bovcPUQq6ebXy3AfDOL9dXMHiNoPNluf2TB3UklCvFOgyK77wdQqyKrOms1uY/oIS7pvqi2J2ocaB9ii9h5lxq/82AoTcR7y41HqWJCOmXWhlLXbjKYXxaKwSv6biKbrBqLHKRj9bGDkJfW9ilAsm9MBtCQIVvRKbCh1zc/oAbX/Z41LJTUuUdBj0mdwgDIMX8T70T8HqUmQ+lJx+dAhU1gsupnH4Pa9u7b8OSu0ozPlAISjGf5NIs5RXqY+xFPHnEaW4DLn23vQgfafpxfuVU5u2Rfv2dS80UpRy3WbdrPc93//l110jZndxDzAhI86yjWID6CY20c3vrzbGm1bxH+ebHq1UnMZPETFXWxzRXn1IYnZZRTbEU+B2rPm7xTMWoDpJgSG5LCwBUs6h/f3/2deArYgVmF4NLxEA3CWy48wI7cjM80IsYUAzXvL5CEv97iEQDTKylrJZCV9vTnJgcdwWXjx94hpfFhdhFYPSD3Dfplbpzq1c/48mKE/H0G3KfZDo5YdvnoFQk/x/jurQaho/n83dqcUnRgA9vRwIRkNxPEqhuKly/o6Y4dQJz2UZa1+cNKIELt7Kuy4TKbiSI/KqWZVCjLixbkA+Qd00V1Dd6m5hERktpjmKjDj0cYub3eOgwhflVa6XQT0yFoK+8q4Bv86iLlCU/V2F5gJ4pdC9NYXY5EVyDJKgUE651ZZTwFomaAznKzd9XRFNJW4+oMYUhGC1/AietZt/yU8h7ei6R+r994PPvrPvtXQzujxqJ0SJ3Z0yWNhnpOqeUDRQgepbLcdds34oiRH1JwA9hHfGRPxLTREC46EABrn8DFgo8OosvpCqdZRgsZAn0inj8cuS+SfR8vAVzhSum3KN8cFBd45oumqWraNtJN1HFEIQk07rqwq9UtI91Fc9HFnoQxE1210DmPzUWTEkBay49vGKQjofCtfSVYy0A7VaUtSqzLKGSRuAHJ7ECTiAgucuRCkMvbFC5zPjobqjPS2I6mGWBO5ODABEzuc7mFwxcQTgdgFHD19yp9CGKMVdYs/RXHTgJDCXawD1s79NPfMhHVw1MRxgIbofc4HtLdZvj+9MlsOWNc23ACkFJXxo5hR/Tbc30SuPB5C4dbIMJShXvfV+c+haIYP9btPl2B/I7+U9hLbr56dVQ1cyc0vg2gmbAKOtQfvBXNdntLwJ2mD0NGezBlfPwjjuuCmPkY9Z+jfjaYhOdD63DbboREMwb6NbVZGLGa6bd74GQE/DWYpzLJiKbersW1rbSB3p0BqQ9n6icwi0hyceIlinGivu8u8Fs+hC8WGOaiqaoBnatksOEdkUU2fC8Hze1kyWjJqfWIp6Cxalm80F1KwRGXp8RAUXu+r5Ce3dvCKuY000gSM6DkSwnerkvpZXgK9w0iZoiT9ZUWf9E/fiS4np3PbT3q2W8EywYmD08iuX/b8seqIhvZo9KasKFVedX8T7JzxgT6SM4OdR6WwUeuz74iKnJf9hRr8A1G5tNCK0x/oNbTG7wN97j68GQbmNBZgeyZxvBdQR2xwgtxBuHX6hwPaR0veP15BmSvxdNC/LKMt+lCTrnJ5JEopjlmJQrElAbfcYvqDcd362M1FdxUvQ+VgVKjN1LsU66lKxRsRoGkXIIAmqJIARjblfOwiBoXh4wDNjX0iU5ocQjrozotxkCnUF7m6LhW07ZeoPi4jcRG+GWL9mPCIC/OJ7Mv+oJt51tdDVlPOJATuXDWSW6BD6XmHvTBay4WtUNpnYYuGZ25/w2YcMuQBYbLc1kmeSkf4qahlj8f3fbjoY1JWgq+IF6pKvptregIWECfilYt2LLmEEpMpWVthtFpeTdydGeC8A0RImT03r6hyJ/MzUS4sHI613DxgL0b60kQjlGcS/v017Av5Y9sJd8WdFXvspUVg6PBMN0uguppBnkc1f3+VtljtKWzb52WhVwN5OVwgCTfV3JZxXWb5Md8lmG+UqIwi0IH1jQlZ9x9mMUDd9/I3omgU2xuujfvdMU7H5NHeaWhRla4kLoGyTIMYdAhcIsMTbVZwWGmoKrpOzKar8zFkLdJr08x9yEdYEc2SWLV1wSQMZ6N14QqzywUGHwJQb5jNi17JcJqiQy+kIlLiPrIMzjmAMpcSTSQSI0UENuEcEFK5TnmyAGLy3tys+axFV/bM5NKg7Saqjv1KKPrgN9tubDKDdt3Hd+Ybf2gk5HXHqR9KE8BPnOOXsziMQFVzHBHv1kKpC/JOcX+kJIFRirSS/7na3wHVK9VQQJyLURmdb6ZS+l70rMWYt920F3WTL9nVZ8oCT3Qk/+U+F9+OlFy3+nlAt+ouqJq171RBIbiCkQk6Cx0JOJbdpZiZoyca+PXZ7YtiiBuUwppgtA8sYOprPO2QmPAH+uOAkEXAWoDvUy3jp85rPl/mcpmlK1JfpItuAU4joMbPo6MXLW4k3yVdcFRy3lETDR4cxwiSJcsufteohGSyXlA7U99X5mtCZ+6CrTfPgJtpEGBv/h8Ba42XpgP9/1FTXUblBKFfGF3gzrr81Wwh0AtbfO7/zWfLp8ZCoy+NQwjslAq+6zBO49o3kk6BtUJ88bjq9Ww8f7nesoxbinrt4/bn06X3CR7/+Pj+0KwABYXhwpNpPcPJ3nyxeJ5MGHr+3nC8Uwm1YhZhM/12ajb8Dc9/kNAvf+Zt4N3DjhMTqWVpZTaMrRjnqsQMZOJP8FIdvTMLHxWIX/kRLVJ7AGMbmYsbqP1WYrU1kfy7ENMgyCzzKjgtBlgsRTtV7/rMLYNdXar6l3H+8HfcES8S1Sq8sL/t8GliWTq3DUDCHXHhAUwUyAY7nThmsEZhzc+lhB6Upv658FgeyCmtnSAo4jIJGUePfls7aKfv2mNVHhDMeKvvxFRkN/WBRKNKVbaFfjXnNDx8RXz5k6UFAmWVp29wbzeUquaC6KPUp5+CY8ohrQvobdtMrAs1Om+UMpgfmBgZV5NSBt200nQthsyAnTyy+XhB7QcI+IIFz0iW7iJrJoJ+D+FMxz7RI5SobuhL603SXTVT2ObtZMHte0pYLrdMHFWKra1bcT3tzhZxGaz9geysTNJPe9gXRfx7C2kYYt25F0NGqpfsjd9mmyRZRpdQC0R5Cr+N3/SsXjtNcxc/AIAJUQoNTM/a7cqwoysqU2oFT9fR1b8JYHlqkvm47BLd02c5xy5i+VByscU3BsfjCfa/wJbcDpmVyjSVwwiEKWYVpp40/lPv6UPcIMrQlAaZKVESZ5pZSrp+oLAaB1j6BLxSRmXwAN4RdGFMulM3nRiyMoN4sTXck4zLCoxehCWo5N2k8gKPfHjovEXfb1ra8gdLbi/iLulcxn2Ld5XZbgc3aCth8HbQQlPArsTtR4P/ZVB3+0HTzhviq3gNnv0vnjT+aQbE5wkNe2RSxYhs1UXv5Tmgk+kmubatMyn6jgNeIP8EGCHtRMUP/vqj0OFPQVaQlAYcwQL3ascggH6IsosYuW3OZuxbjiJRXbCKZtYdt/y6Q0zR8+IOgNAdDUpj6MDH/FKw5gp+VE9nDzn1dA4bGmAFSUaEiuR3n88aycY0wnw0+9qUiN2sYo9gwocPsb5t/VIHHwQb1Rat72H++QvzcYdXIllXA0hksK9BZ+9JFPte7OawT5VFHLf7smLdXJ94J4VKlb11pZdIaOWZsfw0ghxA+c46dd/U37a+DS3xMQCVex0mMeC2b2LfPJE2Mhss0NPLI7IOwoN4ToA/Bh7KMbFeGOHYWaU1oa2S/q7h/efa1tAM+2KpIH2n1JyeDquvPgnM3wnUZNscYO7Qs5zXq66raTte2wZebLeCba7n/P5021wJnZYAz0qC6anTfGRytjB4iiIp8Uc+XjqVxmWRjKnMSL94afCK5n/rtInuC5S9hGGE0rUKPSkLnNjP6f0uIiKpXLhEEmiFFskeXR25iID0knD3BbrZ90zoCIgikRzRVz81f7MvqRsruMxRXPcmYG1/l+ySI9t1UNbvkJfkbXFZoSgtVHwM3tBw9sSWvXd6NlVNnVfZ7ORplIg3964f5nrcx4If6DSisvqcgUvjzjGmcAaPVeGGWmQdCvOE/sOAld/cfvuKzTfg20jT4n/PVqLjWrcQl0796Qt09USUp+b3enwWjV/TIPxW3C+7XrHHc6tnex3XcczJSEWChNF+kOQtZwEI+CZHeuBBLEGtDsB8QHDOQA2ONAitaRlxYCA+4xid96N5QXQqbTMByzaaunDOjmAqoprJZw7ovLfi+thyUqeSXZk9wURunJKErpZ90ZyGy856tVwTZO5nKQh5Hmoo+02+EY27kQiU3eMZYZ/UervPDDYKbTKzz5tSqkPG67qvl1eSPlUxCDt5CAtb5DHkFgvMXpEu1G7t0U8zuJc3zcwmkQ+q7MpSxZ2XemhvldzFNYKWaJKq7OO6Cg4xp2RDIw34VS9D6V1QEABSIDQsXh2Wp5BQX2DrZcLMMYFGZ+qrJYsQToiapwRINMUPKt0TmIELEff3C2kZdWko1E8cMHItGHT4Av2so8q89jRezmiGTzoMHNrCUjQkUo1tcAEanDW9n4NvuezxSDi0M5l8SC/pFZdQoRSBwk/Nagws0YyWwxizJTfqcl3WY+4+BGYuzWi0/kJp1hzW5SmEV+dITpFZKLBDMjpW42VItDn+8bvMhlXJ9b4lwJ/TL2fNupPiGM+69cYEfQcvpKmuL2VbjslqiJoRZnn3ssoZ0oRRQDVKWRv0ffRpziNqoOGBG5Y1yIgeRdb8DngkDtL+2+BoKKmfUPb4MTCYr5rGOW6kWZcUgMsiZNQPrwXwugrOFSEmtOyfVjGbOsd1zG9lPFKzLkGgf2FVQOaGQS8e0+DpJcjhuETtAl/dsLlI6rKWZfkFt2KuG7QihZypvLRPFQP1mwwE3d5gf94JqtnmLb7HvZ9odjJZFVrYWZW9GqyBvg76zMKplV0oBbE9ji2TyovuHqZSw4iL0xTzWOlLKFKqEhpySxWL5swAz/KmI/keVv7F/HKHrhK+7u6/v+8yEfvlg6PXKYfzmQkwV8gybHZY1OBTfcoPYs+7UivBt7FL5IFB2PTKpmy98C+vCL51Y1ShybRTzlNp6q8s9Iz9WYcYHUehZx7NGJZ8Ym4WNY9przajAtC5lFPPVp9P1pdC04ayoBHkOEPC4O7Bni/ynDRQkD+MnJryt2Ps51QlIG8VmaTV11uiih3zZeBCIlkhWsxnR0kc1JtZ9j2elteOCRtSF3QfglpPUGEDTa/a99owzAsjeBy9zT5HOz7igC5zJkYYdWn8YnIVpcKnL0R0jV05pwKYMEa2alRDRXahIlTuN28F/ZqCbYnVCXMV3p/8wdoccopFPTrCBpQS0hSehjO7x+eZWr4Sld/QfLIOahhwf/6FtXzEFKXzCIxmyXeo31LgpUhCzcrByQE5F+B5OsCmAt8wME8VzH6s3eAXNiK1JcvQVorsI/dgze8B/0VQWvlLPKVibI3Xgfu69ZS0n8MTGKTkUpO3YT3ONfcwX6se+mOdgKzyN+PyOveS017R1+u/jlOKFSJWPB0bPoxgNq/HRdIWjtP+fwRf+uIQBV05kpQ3uJrLU0yq/OpohfvjVzwgHMuIQzKxR6ALAyRH/PZVUVv0kKOmBkGqJzmsoEqY/Pdix3WGBBgfLIvdLOfUX3PU72EgVZPbxUkK6AO2BJEDxEJRIi5N4f8d9MoVxptYM9cMrAFRyNT+8WZa+xwbBxLwjUPv0olb1yRiTWuN0nBg+FpHtRfqrnF+56WWAalZcmK6/OfweuXgRu3nGFKHMGIrCfNF3c8k26BmoFwTlMRLWUloI/thToEOmidYgvHMrtb+wJfKrkapj8N479qBtrHLIrWk4vjyHHquuqS8r8IV2NBH4CvRQIdC4eHBVwJ9b7OrbWWBvaZ1QEb9yt/ssStCFUmD1OjyjYLMCt9kd+8R8s9qWFAi0nkWXbmpZGwfL+3nDyO50UrrZIxADbpWw8QnH4+TyXlpbt/QUZp/0mC6ex1ytS2xxVR0Pl8LvvNHe+1/ExHY64H/5kuvoAkeLnKiyXkqNcA2XBYYpG4Ho1MKrvnOfxM0LFvBe8BUUuXA7dG8GAlRuhNZ1q4bfN3TQ7WhTAOwLjdZKeAo6wbx5LGgp4CihmVG2BKCiHsZ3v0fRyJ3nfQQxCCY4Dcl9kTBxFOmOQyXeNQFMBUZk1hSHb/Qb+yF0pVo+FQR+fUfxGWh6orPnqCxhSlNdLGffpAJavQnWa9VhSmHLY7HqQdeVM22aUYIbPn4cmhJq1ExbJNoojqBha3FGz2xCV1wE6FlPJ3/jchwxAILDltPvGYCEYL+KBIStRWkGLbD9k4OSQ0AV1meiMCShnpb1A9HrucpK1pBRLiwb1S/lCJiKiVC67nPz+HY3OHvYrCyI+aLGmkG9T7h/0WasKV/L0IJNVfsGnJikqs5CGg6f50U9BxJTTmkJkwlV+1gxc46lLyfPL98quvzbKpqjgZmNwlwVG0KGFnVJ0TKU04kAfvNhnA1C+fRfaS0xw+oqSupiCJuzTI/7BH1KGR239e2XhfxOmxiKBygmrvchvMAbEH31ewBYqWgnhKvBLekvAR9lmEcks4ubWGkxuYib47k3Zm4uThepXHYi6xIx2zl/fYc9Hwpm5pn+Ezp/A5NYyRnozEfGE0p68ZFOVltGmp3TRMHzdAz41eJn5SfF2lecS2s0Lgc81u7qOcxkKE+WqJQq3+ut7gQasvuHsI3dlX8smSR36grtMhb18RvDmYytVx9TJwy6bTRkmyHyZfY/MIE1RHSTcgyXnlg+1XfG02b2fjdjfMQ+I0KseXj/2sNCi5qww37qHfEHJ1g7NOeaIm4egk8jzvkH/NFcIC++D9niJXaSYSNpqgY4z4/qwDwO9agYitLPeNFIzu71CfL48pCnnBx5wQ9Fx/RoEAMTaT+mtp59sVqnASmHzMHjuoeiXL74DIJr9Gtr+tdwnb2GaXb1883YAApxPpgEo5K4Gh1qDX2U6HYpuEEnOMfJkHEbRt+U9FzIXMlRMYKguvV4O1HI3/ZmCa6VToQ50Q5EgaOXyZ/bQhVie4pjErIKtL0VlgCMgyoTCbC/sZO6vSsk+zsTnIeMLc/y1pZaDLlHAfZtlVWUmI0a9NVIJHWQmA6UwIvZgy4IbI8AE/WsZ1la9j174yYOE77v0TV+m1MkwRCq+Gz1RLoKvVQ8xYGyt1ElS8uNrflaZrvl3y3aD+rkgyVjkNNPNBcvGpf47XP7NCkfKSGHNv0B1yxb3CKCvmvjtzaBsH2XSGxGnb75KOaiAyiojFhlrSbxqsLb37rua+bEeZLMt05yrkhQuUKMeC0mlkwCK7Hm+Px4HJoVermIUiaFOlYppMroxsTXyixx4SiN8xqC6xOqQPVmq7XYr4EuaMUvkApFs4o6NtlmBtr4rXajXOTZsmu2lP1Ssz6jXkUE+dlvY7kwTTQcz1U+j6Fk65iJtpWHu/JfsbQUuHUufKTPC3xhf0nHERO9n6FS4pQfLr7LU+FNagmKitIydKkRsO5hpW4MZAlSlJwZDyLERuS6XIClvrHaIv2UiJHAYv4SSEMfoVBHB2CuZPkvbI9mJ4Wxz/DWxY4SHCbNpbSLrW7VAH+Wc63JgIpMIe7m1+2vCA5HQx0TphPRDYFewhOvswg+jiKlcqoNLW60RNvhpoDisnSBBgTyzupX8ikju/KdPb1oqvZGLncUAPBA0hQnVkrG9KI/Ks/uSCaARurrF6AYL8d7PpCEyCQCVNHIj13VEpOk9WyzZib2J5MWtdLEaoFOtzAMEjrw6hMZ9md/0cDzYMS6MOkl27dsBVYnguNkljVMhrVD/wWUmgohnu7UTxxpWGSh0Voutg2lVCwAc8fxv8T/tl9VZuZb3Ip/dFK/1s/O/tDbaKEQOYoo5HbAbtCbq6bPx0aedciOzWAMYr48pLHWfBbS3LCyXB+GceMZOJtfuU+I/5qfn/o53NtNPXu4ehTmXDUtv/v225x6+wPYkiZlY2cdWi6QYB2rt7b8P5xnvEVW3IZeRNLDsZyQnxojONug/7BnhfvP/VdGdhPZcmsNdRgFdcp7OL3MiMtjnTn9K5U2k/w8UjxYyEw8HxbIttOVF8IagiDTwoI5GAkb3lJh1923UYZe8oPCxWBdBeLp9vRLAtmNF6ajqEQgYVgv7TyDQLT5RaFYiTuJb8l4I4W2i6pI6ElFFSB6WvlE8fKfusp5K6crj9ePP5P3CGCYqcfzCAWDUIy7958qmFa6K8QeK9aSJaGFGtXZrLQU7WMYRUyAs+rQZJMXitTJZOhibJR5uNEwQx85iSFYNUQIZ8clgP5fnA4Go5/ePYvW6ZY/bZ/gtKIETeZQdRx91Llq+a2T5w8XVY+kF7Ah2vhCZw94jUfvLvVJ7pUigMS1lLobphiqDTXzNpPaUHk664AUWmeEfW0I4l4RPP9CSVJOlpng/Mb49ijTOmTKwftOb4O0x21kRgkYEn4PrxCCfMuzwdzta8lmDdrtTGf75MItFHqwO9Iva7r/zb+NJBrnoe6dIIOYU7M891VSR6mBqeEh9pyGxqOuFIrLIxo0YwkUbuAjIyoADT4LEL23oCKWLsUYfvGGoEc50ZLP6dpH56yAw7g+qnxUz9kRWDAIQXE1X4j6joIq2CnuFiXMjDDS+uL9zgTcC2RvncehR/4yBXngLbksE4INqkKWFiZ2tse5gbmO5utZ5fJEw1KGGoiraKSh2MXhOFaoalpkMj/EE3l/bl/ZM+9qiO3OdGBxgHoID/o5NsC4BfHbJAoWWMSBnmyc/88+rCvAfojnmzCc7zKt64psy2BEg9481sn8iWv1+p87Wy6s6l/qvKbMZYpgieLupNbgvx5WCcoASgZUe9XCwC75P+S1u7pZrGvnOtND9wIO/b4K/nu1x10LtBhcDqiO/W6bg92U3vBBBbM2iVD0K+zA0/LRhtOzi9j5OFggkXEPfvzW312FAQnzY6FwOvxVf16Oa3SWR07zDH2s/Pq7cJ0qHqnmLJwhiSNcUsEihziwGbE4MkqAtbNstt8N+S2gEWZPqb2n1QDAEXvhMX1hRKvCqzmLvAE7HD50I/xTFeTTvoLJBGH3AX8UFllpGD+mkZ/yZKUjjDilgTudPmmSJV5dt61D0cjb4rW8Z5b+Yxf9giPvYV1UWvw8RffBsl2VHo2qgeMTJYkFatmMfCcaZtGF8OSIHEc6vnC9MmiXVEdIffBr9qo3v8Jp4yPexWJZQyRLs8pbW3E74O7yyaURcU7mMx156zzwB7QTxNdf+udh5bGppoSz2D0paz+YWMuDMRKolxUbfCYgouvnI+qpEk+sL3W4EK18wUUCJd0Wq0ZgFEcX73ZlzuI2U3W+0a/8V7W2pVisTEt+Tt7mCOFmLFB08121uS/FUVZxJtYxM2XS/zslngPP1weF/Xwjk0ZrlNd6slESXXYzfWsLd3BKYGYtm//XtVqR9SbK6b2MAoXzdNsKmKqECLXc6Q7+vUdrW+q/sizxCWZZSc2vtnyWWovU7t7bl9jVZ3kWc4drn1BRmW7qYwpLAIA91MNdjkM+SQGYw1bEvHfxEw1Bu9O5CRSS1nklCExRe1IzzO94o5Glvrlt2pNYW2B7rhVb7H8LU8EnyxWdKxz3lx/diRaHFt9Ejxv6spgS5sJ3SyKNUUahSCH/kY0+6MWIE6h+u0xzyWjn3d5E2YANvpJ+I+4HXpHNchGHzpGJGMGUVkyNHZpUmzm0V5mY9kPYrjq0Qcz53R85vtpAufdR4LBX/cuKKLYvFc7b/lgubklw5jOBvAhTJt3cGXVGsyatagR//k2f4dIt/PQqu6EASSvC740etZpbnKY9ZOf5BguU+Bi8ZAg0Vxjz6p1bqcHSZ5UW1Zaf/Iycwc/CfmVqoNvTksZqW4p9B0kH8BwGtpu6rPbGb/epfTzkfjfeASh/wTAC8eN1Qoz0NJ2iff6DlVDqWs2Usun46uwETBWA89R3BoxlA1Vpx1kHwYyCj/OQF8gQA3JdbtEUMHswXf88PG5DEV0+82172Gqi/4zedPzlY26/Shs5MGuDPfu/C/6GKhSyOcUhvqWj5DtjIfEgqyKsCu4KFmbgWjlRA7sd7LNHz7GANsIsN3cRBY/fmwhYM0a0hl/BHH1V/x0Gf372/najoTdBKvFsmC6mxCRR9qnpoIssjSjYOHpyCRo3PuQEQw/AifGWgIy1Jtri0bAcMwCpBMQWUjZ6GRABXcmYMIk9Lr6YdBt/4VJdXE/+VhMt6TqvHbaCpFTAeQMVl2Z/GXQ6PWmYwBw+7gRERhHNKemwr/MCqs5K7DfKJysIIBj/OCTLXXO0rXofXQ6iIcMYE0X0UxudD3B9xKqiXstMwQQDo19G55TQufa6gEOSbFYi6qti0rrvy6H8618/Yv/q7WB0BpHo0vi6G4PGf18GVzCNMVxJgyA8ADOqtDWII7RTwvWH+yvm+sRnOe2wjnkoAdAT1LUeZg4DNnYhog/xv8/oBfQ1H6xFtxB3yR3OK3xPUsJHxBi1zUcFdb+Wt6fuM9J3i8YBdPAyKjthjMwUMgQ/6CPbJM39ss4wYHdJb4b+3lmv0uMDqBV0nOGWHcaYHkImcRiFFw6l+OkqqR433fNWvyVuyzEZ4cq/av2MltQCYeWV1oVE7r9FI8jI1Ze16MYOaHDRczxn8MEdXN7M0pmBCXi3jf2BE8EAiKsLppib+P2MyQDKIFwIZNVdFyhVzF7dSUEnxxCFtiuzyf6S0HYrf+uWVSa/V6lP3ih76DEkjXI7ew6lykwSS9dwABHMTXd5ymQErYzwWIPKkyKQ1XVrfWKbSR1E0Oyr1ANV8atM7BqZmY6u9oi/8F/LD6fPUjoP87rpbDIb0MMsaA8WYd66wbwBdeT1XWpLpO3HQU33G8vtX+G1MSbntFZSlNFazWlaTzX5DNXZ8lqVwhz/Fc59fPWYkwWXRKnymFEIQoBQy88sFAo4KhWVEtDrH7y0ALRYUpXUGgnYBQ8NmKTw6J/clwZigeWWQU2053FLJYlG4Kh9zjfbzTyiX8vR72Ecd6yM/Vhmnahtntupr8RZaUBM1TJVqzjyfP+aNaqbtBfLbFCDvy2PjzuNBPyeWFxLsDnCnLuzr5mdFn4fVAIeRJP7lQAEQCCFubuOmspw6gNhZ5UmPNAhCuSGWcOj/hev+LLRP4zofGfyotv60kTJum/6Y9lVwIBsXpdow3gAWSEJQD203DmVQCISHo3BwqXxZLROMuGJiLEnhboKi/awNlkwVBmfmMkUuKAKDgx/pKjgpmdTjVoqfQ6KIEEjxhxUUOhGFyYLFlCt7p/ob/+Ujb5syRGErqs9ewZx45Vs85xPs2WUGd6fQcxX9+/11bVlLg0yhDVgzKW7gc218aM/a7eJbqpJSLjMLqLCzqhPadVk78wjaT32b8TJ72mj5F1Ple+x/t7IfCcbBpNC9ouZOnSOy1f1DNzSA44q5mUNXv/duKJJqNqjOXkRmIhBlsnptj/yfI3MDAlrr1MCYkcoq7bJ2Wf9BwMO5yWa/yaISJJDjxAOSf6VwfaXO/MporbUK7APuFdXWTcMpkBJ9P9KWcvN91moazFNg2TFuXjM41l/dRQTQ/9rC+fV6iM0kMw4QxxR7+rsElzuQdkJ42pU9Z4owH/svDmi0SoLclmsiCOje9ArgVk1yMf19s7OuSgL/RJ9V7kN+u+UpOgQQe9u6/PzFOUVCtxOw1xau4EDSGmD+T/SZXoQeUsn7aJ5GGF5ni+fumMPDf3m8ou6xpCONoW/lmwxB3reWKctQ3/uYn93tsZ+qOR/XnRXhjafpksvfz2ddISHEh9BaZ1C9YYufuzCHnpfsEKRLP2sA8ZZxsTJoBeRyWTg+44ITSvZvNypIRafiAiHy67s6lQBBoJqjP/IbgcoKZ4bKOu7/fseiVYBazcR69GTgFTT9Vjc7vz0ljwiCkrMuNyKwQKvlmlZ6jLZIFDNmu9z3Kl/rCvJPnv2bZ9oIMZ2hH2QzzO/WjzHClM3NHxC/6PGOEUL0NfSW8/vOL+LLRmWYT/iQ7xlkEyJtbg05wKJGqoxBq1jnKMhi3+du8ytXBdmyGvfwd3iuKS2rM3YONo3m/wUP97rb//BqzzZfy5BXJ8tQ4/MG5Pk3P2i1lJ+/hiU4k4oVpP7iY/dU4Iku+rAip9A+7cune3CN+t6ZSuR9zBSC5f2ZD/2ArrOI2I58kDkRcbzO8EgkuZUZFMhBMWRPT9J17qUZE0Z2ScEwaHx3ZCbAIDGY5Q5/eN3NqQdsw/WYMOauBO5IswLocqIzFTMmSNJAzP7z4LdjaxcoapsYoDAjiunozIQ3Q0Uy0iqmbfSJhpgy+owo3vyWPihY+9YCd68a1a4b4SOyIISf65erC5miRHDcWhII7+lB/ipKcEzzaU7IE3dJgozcobVVup6Nz2Z+NWjUKMglM6CgKPbVf3zPf/MeVOYvAVeNqYBjh6wuyxQ8rnmhRk6TA9eO68ZJMDEiFFwGCdD32Aq8n/DLn5eC19JX42PlbIXWlTpYhgsENcmcqszblQ8asxjX97XMvgoj76h2R080wV8JzgHX7idzqbnyVomYL73KXO0JR8WCaMtDJLMkCUiabGlZ8KZP1BrF/KnlFYuOUaR/VtYgCHXM22iO+3ULuRHtpk3KPfdCqSpvoTHfkY76D1ozpY+6AT2faALG5eetBj7bfOKXLCObDkapjN5NKzogbr49y2PtruZDDYLUfunGk+kCPYIbOgi8qH2eTZ11rsaBu+PcbHKTcGb7A55Z7TTt5wmxdbSiuzf7yP9IW1Kqc1I7ZfB3l9DJE0DnmgVVRoBx+5Zvl4s8G5oRVKcewh1L7NJ1cPMwjXD9jb3O4h3I8rUUEPj08JYXuaEXBYvrfIK1+gG+lRzfjaLDSoEphV0Cp4GHVMNa2mGfH/VEVNb7jFKosGTnnyX2I2tx/jNICkdu3oPz516bwoaiPgEJEf0NOqH9CWqw+orj54T6eSoZFz6ykDiWHNoORRNtO/dfnU9tl1hcUou6k1ippKOQDoalA1qAAvkrcPFjzZFgK72BU6ZprwRw5CMWBCRRJJi5HIUX0lCVewqEpuXSbLib1w/PsJZcdvLDmVTy4ETQYznyD/3gBBIk2Pck/IwNSLMDnobAl8QkavkR77sKL1AZceek2y2HfzW/zfzEZVtD46Zq3wkZ7+kOU1t+KTJpT7w/tH9781o/+q2i3ZTwqxLP6QEt4rllDfzsk+u7z11LxyRxMasEEvkX+kxdqK8XmLZmwE4kE72UMnysLzbq9icrLWbGcLxMBZoIOdMWKFA5eFJNdb0zvj9XeXAF7HpWGpf78WqJrbbaUzJMd0pg82QIw746C3UUTz/MDUDvLhT+YCP0ojs4fFogzBytjAelEbC/9SD5VYwwLTOTdOkVdRbZoMxxoNXCU/R0JRuPZsreIoJQakrAgOd+GyM5nu3G/k9x5ZHKRNHX3HOMph50zYoiKTRdIquiflAVA/BmPsb3dejERSooiGbZX4jAIKkWbRWLps1epXVPCd/ANTAKVFVoEgn2HYDs9VmruIXAIa/5nueX7yszi2e7sclJ48sUUUG4j7yMuBKZUCHL5XvExSfvHUvB9xeehrNbBiT0cZQXC/kioCzg9UHQXqd/6u2j9sEduqODy5xWUY6BrFPPBToPtvwXX7GX4NDQvXAzVEEJ5IEcOLJ5Gasm9ja68key9Gai3ZjA9+URRaYcUn5+N3iZyHJSOPdjRUb/ekK4xNAeftR03lCIF11a47CJpbGGvEbWWHwTWM7fqJQBzMhv+YdFXcLsRIoeCEaAcdPc+1vhKQZmtWUOsn4lNkuBxhqHSgtA29IWuMZcY9ySzHRKuXkvXbjWhGKWg8UDN3AfdnJjSTqJ6pDf0k6Wft+kqTFlRNBWthetZ1NT7Cp/XWVz/dEFVOSrJBCl3F3a9Xx1AYFJgI+wUzUyQ29wgFg/AGLCuPhf2oyxjzlbhikX+os11dxfvzOZJkLApuLsFuJRH9xTKYxXpEgSKJbIA4lo7UED4oZ/78O259sCIadW0E1miFgPJAcgQ/W/ajY8jK0v2/BuckqW0a4PE5TJpQsp8xW1Pcp1oxmFu1cgYltAqdWKj/8z5+DjfHfkOITmQ5gecueytu3pP6PziZdib8VfifWIk4Eop19Rxnx629XoG9dhvEKc5ZP9wiY2avczHGku28Z0BVUs11lJFmVXK81sD3zuK5wUOpyv44Ft32sEqxDamOGOWS/IYo3ZxhO4qXX7upjEFEPHsv6uUmaYcVq4/5WirALVwQOhMj1cyOr7fKv0fY/zEXzkOsBp3gsVD/AvrsWRz/yo9dp4IEsaK/U46WTEqw2Ps00NhWgAeJWh5YNwb2UjYJSMVMplRuLHNBJRVAZjAqdi/4BXWpel/9PAsvdlNYufKX82iQi9SdjvhZUADcFsKQCbPqE835MWpyUpfvRMLUifByCK/jw25HgZMJSNLqiIx/aa9I1Kks7M8Woj60ArQLZN8USgECSaTuMYVo6iRqWyHS1JFkmi9WYPTvVvJ9AfAwNd3VRjmC6wVFKzDaA6rOSlfuKKZ9oZWp9oZn6eZfBweFp0jjj3D5DTnwTZE/yX64D9XHBEjz7YeKC8myU0U0Q9X/Q/bu3/cC+r8XCtEoDgRTzN7r3I9Wm3IjvLKHO63ZZvE78o5RwCxzyeYnCJo7hwDGA+l2D968n4Hw6vpCdV7AS/L9Vll131rSAfvZrGwXYqMJszT2jAfyvR3p6aSNClNgOfzc+8ezEwWsnT2SqbpHD/5/qcn2p1/Hs21R5z4h2VMyS2jCzEdlmKqH4xNWIwBs8q6rIU8dhx29RnmIKGBUmwfbhp3w0BIyR1Uz+nFR2MsWsRlP1uAFL4SWaQgaD5iSHKaYa/PSfYiHIKKGbIMnximKwTHTgINA8pNVjF2BQeFPOYzNp1ZnJwpeES6KJWBVc+pWReszFwlIToZLZMjPdGNNXfvQQuHTAG3TybiZR7gokzF9rAZ2jB+2bGg0AlL2/TAPlc6aiAsf45a6kMb8SDdr79AUC+lFQLe7yIMFhD0g/vLg/4R5yN9Igo/WmH8xlt/2PALaEwSAUnwjRuKYkFXVEQNjg50e9NXZZ8ZTVTKKzNxBXwMHowjIqH9XErsMRuBiliqnb21KlNf4tzc3coi6o6JQaXWjJUS/laRHeWKFTE4XgKHTOEztAKXKIamFv82yX3PmNd61YXgdtNLLOcK8wv2WMESypSagvcnjJ3lM4bwSNImXOOH7/NrPwLD5NNrO1Yfhp4GsppqNmggv/jl3xKcp57Rltcd8c0HdTmN4kfXM9j3kWtAfWbY7EYEISw+OK4pC5nQgQ9FLewI2jOZnyFlrpCNcEmjCY4DhV9/vf+xDIt+W9jHpYbCB8Ho4/rjOplXbaxKEHrVLUKali7vucYlZAgEinLXTeM45gLFOrMTyt8M2aR1vhqh/YyT/oEvCm9CF34uwZJAqkmenKk8r1xaP25a4l0vuEi9P4rW7Tgcbp8z6WVhQg0VaycWSN4oSW6AsacjchyhmwXUkKOfazYRaBnHIkhyy0s+EGZNqUgmlpyH7Whgbx/AUjVi872xkUHngH+wX1LVBAYliqglXfxnOPHfCvXju2LyMrULx0YlbEJ6GqDdi72XCCSV0L6ejV+oEFZqit9Tqm+QjxW+K7ZtbvqclP9HYaRKIKPDlf2v1c/j786XEaV9tyYUsE76xzBohF4l8knGaKacAMb6b4pWL+8uVqC9FUguT5RwNUa/i4NAXSTfZDorUF2smbCOMkYktbxldfYJ1P39bWrQom3A6P5NHv0PWezpFQBrX+4SfpsVepqwghXgw7qIHRlMghwbDt4TZCZTc1mW7xX5VnK0GtYMH9DESpFmE3A2UftMa46WCKN6/4Fr+rSfIPwjy/B5t8hg94q1yEN7iVTZH7NyUSQGEukIevm129P4pJRxbQRCIScatLHth7NPbypcmUPSnKu/Y53zxCRF+q2LnG9gvhwFSyUz0LvJH4CIDe/ZAWXGqqzhJexFJRRFijUJgBxQ2KBLOSXMzMW3ELT4ANZcDP2HQB59GlHBgPg4SbTQOErt+K1prgB1ysfw/TMDbIGo4sH5UvtahOcn7D/1XgsrYB53SajLu2kOQY9/eD0QFF+Pv8wmyw3690sjlTDizJIg3btMo80AE2jo6CCO6H4VonYSRQAkTTduWr6aioilPOKCEmElfSuoLATmEFio8VGwL4aXEGR7tk76VEi/NX3vLjMfXqPL9ehnXKPh5e2OM0tgZTV5SzLW3tnVtC1x8R9BJj25jE75vQVeTsNJPdS5Ca+m/UvQho15ibsJKW9i84JxFXwcCw//jsljPQp05UC0E1S649b491a8Z7uM1FJh57BzdKrO56ysgd8SbnExKjcrcd7gLEIv8f1qp76OvtT3XjWZVkFE9Kx2I3vCMMR2L+rjrrwwh+pDh6hTLIO99vrpVEh+LlBtXJY+Q18TznOM0kQr4xW4BedU8YR4C9+N2XCVIfVxc5l1BT9IFqVrk1dlcETK4PlFfSIdUHXba0ATCMMvaTRGJeJDglOoOxyt/zCL52CiVM+bl3LTJ+AZQbyq0+mh64fudwD3hcjAyrUKkhIbhT3M3P51mpbJIs2DHxI9t5QOUVXSqmQl6YXYwbxSZwoyESNT3C9N0j+xaVmKpk/3qj0lgravgP3dRSvmqKNvy+PT1lo9vP5zMhY0gJciZbteLPAo8M+MiI0eflMKTV1NkdoXrPNW0ZeJ+YrkMl+XcLj4O0J8sjBQNvWWJFZNDPxPevpJnrRasG2JpJ6alzv5wKG28QvOMsWa+1oeGguCrn94MKZIf8HYOZqWiBX8TUuaxdLRRK+sQP+evopKmKJ/zDhp9IZI6C3XRUiEfzjO9TmqRTb682jai00xZdsq53NE7pB/pL4tywHbEPvt67/aYQYumnJGhOq3G7u6CzuoTK0Jr6PbVkTZ/1Aftmv1FTVhJl8ww0Q0R5F2mpQx2lRfxDm2qUeqEih3Dd3122rmXryb40FQNfHbEBhd3HWX+f8lQXaGnPXvxo93H/COvHmvdVXcpHpdt14lMYIehTq04RgAYpcxz3rRZbMVrpFcAkSEBgwabYI1CqIPLJYNb5fv51lwy/NOd3YNmQnIpHPTW/K4FZcIHUzX0RYeZOTQRYlDfKSfDbjwebDJbyCYSpiAJXBhyaGqAnTRdnk9Ar2SKy/uvquQAcOhoP1fIHYv2t3VTtb9jGpnRYrohrTF+57/+PKYOOZiqHbQtTlj1EKrC/ljMYb5wgLHwZdHsVjDR/Rx2I2rfOt6xAGKHB4Fj2UGKOu1vemhm1zT5R/TtJrCPh/F9srHd/IMhS1a6/BU/36Ptrh7lLJ0i8LJeK7higK/1YVhhqtgsE3D/N5+0i719Gn7o7lATGj728DpV556k+ChMPJiAgPKl3vA6IeN6eMP1Jx+mJ8LqfqU9m+DUd/zfWPr1bm0dYrxqW70D7xcSXhrvNzkzIjTVPIMnA7yCuQ9tFR/MGbYfXGzrS19JZR1sJtKD3sxqKJCSZfbVEbxMuGgetOrnJztg2OAUuP9r8Hi51qfbGVkkcLcvgwUJagYlV1hN9sVK91whbIMs5bKbXzgHXAM6025DAmmp8LgIY4fqhjYgurrbx1NPP6KLvBySuMabZK/teSrbGFSVyYygCV4KW+lusP8BUJ6J/LNJZaWjSGtQETtBIODRb8YKuLSi++jLkS05IjwL8aHGOuajG3Xz37SiUt03AdEcmhwPRIfh/dWpJ4HEmjQHHvac6o65M9z6r8Bq8k5D+s7Kbh09vHFbEk9v3CSiRorR3bUqCzK7CONRiur8QcJfgS/5/IAkZBLOJdsFqQTbMon0So1dyHYLtOfDGmz/09f0TR3ISRtQSgB6swLhGVpCB4m4yYP7IKd7qk7R8OBIHRWH/7jBVtNe8hfAtA9xtmO5SBsLVD1310kSZ0Z//4qDBV8iDZCOQ50ubQGSJJV0RLg7CV0mopd85s8uJ+OKFN0lVBx+wY5FmqsfVokxLCxBFUsTpBiR11hjnG+L3zszH7zWfdWFRLMlj5LJdrqD2CREM/OmcqvDfNlpaPrOYzFqHL9yExIasHyHeBIfSEqk4MHM3zGdbiweW1Qpb49zVTCn+y+fHeVgAAQABJREFUFmD2VVL9B3ze3vVzPeV5wQFsYcQBfldlvarbHFqNASp9sn2WUkA8jAFLr/rW24Hg7HVz5yESxrMf0nVP7sbR4UCjo0g+5GNHoLNn1qNR0SCGvlhdVlwmUvrWYQRzW/7ptcBl756Ffk3HQ6+73ERN4FV4mWXb7ZYzT5dp+hAKXN0g+F9K/9I+FL/8qova3hKe5RazL+xcjIoE7DOmEN6Ce+fxaSKuZPIfHPT3mhxzqUh8qRegZ60t4Cfl6JofWk8hJ/f1G7nv9zW2gWnQle+srYn/c6aJX5oCstBg367cuYaHEPZO7dGPyTSu4LOxprgmcPiRRTSoH1gAhuexde39qFaAPPUxURaJsJ/7KJ8K6L347igWXG3SE192q1JlBMCxHx1fQn60lUn729qTvo3zFG/TWXdlqIc/uFc9icjAjw9gaLPHl/3K+SX7pxAklmtkyFewU06mDIgDIpffh4DNpITzfscrUzypxKJ3eIodAe67pySX8mD7a4EuAFtCrJQ7Lop3p/EwcvHPUylIruBqXcvYweZBpakVYVZvZf9Aa+VsqjU2FpW2gBnlD362pT74CkSgraWre7AdvsKQ83pA3K0CfmnWEzsD9fHRyQYSyySltB/04ZCugBs1HFmkDVrB+KXKGsLcKre6IN/uEzcNgDskB4PX+8s7MAAgteCoLCDnB2AftiaNgKWCK7SWgDL9opDVZHVtIJoFHSaCh50TYkiG0XjndjCruBEl3LTSH0othYyucrlDYqZ0MuS348l2lYUB8z9J26R03B4xre+zRgybwSK6qV/+vS+iz1xNDPIexsDyYyN8JBKwrI2YelUulH4jqOzEF1zYLhWpXwM9obpNT4KtRZ7ikmnFonGmkRZk9YMOGKC2lFlUKJpuswMZI4TePzAX1MKM/uRCy4p5aHD6rQoEOvM7P3uMe4e7RoVV7aWX6yflILCxnWKILv8m6ZkfBLtMBl404rQtx6qlv5xm86D2/ZID4tn1yef2IqZozHrKZ8yhUoSZzULNY4XA7yC6jHb8A6TnFdNCHURu9mJBoQLwXOKioQgz/JXyFmHK7q5hQcp37SxGF7lPrFKzfqHamxD1u+K3nwRNT/b1WP9Rcg9TupXPRLh6ZYvxgj3CuV04+EtFUtriDRx7NDEm9JOrj3r9ddvgE6aEJoMmwY3tR5NYUnYiR0c1WmX6BrpIaliNm0gFsaq/okGm7PlY7e44V2pnMRZH/LmpPGyLndIe6IZhMmEAgAouXUAhaPy5H3PcX1aTOHsjSvyey4GMAD3QWvJ4oLWZzrdY+jkJyuyP3/Vv/aHjcVAvz1NYC7oLG1y03gcxf5/gWvuT2QFsCVsf5RcZC/my26E2oS1gpvdGM4Y06MV4q6N8VvR5ZrSQIyp45BmoONCTHsE8uwox1KVFfAfxNM7nSjVFhBDzPn9JkwpehLGKKnQRvgTz2tPRZs+c0/qgTMowhEjmWc0JTjn1zy+8jppxxJLgkKe26KVKKuMnfto1HsrpmHcWA0JstLNgC/h39ZS+kct92yMjq/sMbxVXSBeJLs3dvyGrm8Ts4BucZ61s1SabwsZTo64UlhuzcREbQejxlXxKJIDwxMAypto6nFTelDXYuhSnNg4MQioreFMqojXTujHsKjHXObOVKqrsgatIC3qP63/Cv83SqhlznzGmx/vif0b4Qe+KCcrL2uYPrSjATBxP6rpYO585Cu2r42PF9xYlcNvXORS5X5X1UFvScxFuoKihvkjQuGywHlYxLxC5VxdAAsPIyiBNl5BLb2lKVoQRJPArtbbTAaiM+XB3ry7+YSVWjvezZuZhaDPEF837aD9Ap0/x5uu43L+EmKJM96gpDEcEXlal/aNLZV6K0ECLfFxsM/T9VPggWVNCLEFzMPYbArMBvO4On1eSDoTTO2Vh0brGAKfHw15Ysjsv4bOSPJfgUX8+QX57PB4LAoU/PPYMmaC1SpFlFGwSvRP+j6Oaudq99WdWJocpzOEBk92SVJ9ADDKWhYIwy3NoqQtWABdIWs7S9gd3fUoJz1xJHc2Na4MECof/ZtBBxJsLNSdtfktQOt/VNbloG7s+8MXLSVatIzRgcqEcjMhcY9EPagfBtcT5SA4fRKQGUpd7QTc5bkUG+w54zhB1+A2pTZaBrzG7FKpprZOFxqHspiUHUgVdnLYP8w7Sh1r6k4/4Hhac33y1KsmsnETXMEHEN9hD2qKicFSoyJ5oMk/SGbhEZqhKAguEfroJCLHEW/LHJ0QYdOkHvpgXIfY+6Ata5G0wAPdiIXALxNlPD5v/INIVNd3W5nxUnlEcpSvk9H8mWSIJV2lEPDCuNqL1rEkqOT94K6i9Hgb2LrjbaiTW5atgX0+m3VVMfhauB+kEpCjIDuV/O0ErvenyHOx1mK0MPdeijgyTq+hz21Jle18Mns+La3LXyhICQm0rYBGM77bhMAiQ7XWCqCpzMWc5R1US252ysQESKYF6TPE2Ejrw6tcBO5ixfEdF9fiQtaTy+ddUU/kvf61oyXFuAiigBvaRgVxs3wFM5+4zXPjIP38KcIH0kbS9p/LJuWeLF0vdWP6GYCaeuKOGyRJFdZY5GuJ4cwQFswD2QgFe2n+KVgzfwRwMToWlBQbeDBM87PQcXfEUMRICqDBmNTZspd3diJFUtzTKsBQA8ykh0xd/L1iQRjyBsPdZNik/g4IHzw6q9FOuW2Xfg0AesRjQwTD6nHI05g/dW1ziwrD0ddqJ4mKKI5+YLje/l00G/DaAdUvjL0/Unb+fdY3vm8ZEEj6Xh60EkFp4GSFblJ+FPyONPYPuSYFaCkNC5eLJiNp4FFEAZ7gyoR6Q7mACZNG4E0kaNrCDA/G/mGqK4VVAEspaTCc5qcO3f6XwayQJoEfKetTUjTo47UVAWlJta8jQhxhvyE8icp8651P4BXHE79+vYvywPrcrHIhkJtp412/Jr/kxcJvtfKUgmMcKFnrTYwSIE9YJJNNSSCHcb8w/HbWDkxKTBWJpfHuJdaxohqhEngxVOhp/1QxNFEX/pqlYJsQeUKk9/zFmIF7+6uT9RW2TapRVeQ+NP3MYgtU6XvXILvYbt0Ozrat5UAwG5dOZ8SroSQiAPbjJZLSCuIW+Vu67gQ2dBYMVEV9VXo1owEBLIQ0Qc8j94/pIdHF+2KVwEl14ztpiFIb8ihhM1vehjeXW+oJXCoifvc6PExTcyDNIse6h70ahTYhZfNE+qpr3R9BKImfwdtTbgrMJSuVhUmV9/5iI/w0rTBfUJo9F0AgByyXnA+KOSMStMn19rj+tw9eZ/SwGl6GIvT5lmeyT14alkJtJGEwLczGkO668qAsyw3Nvruj59UV7Mnx93nHBLjejujX24wFDC/L2dyXKa00QyC0X+OurVE+g1+miNakijL+POir3Tylyh5gAk/3d4qiV5WZ504wXpYPnwMdrtYwe/Y/C0mUzN3cWYgiJIvjE11yCNOMtFmRlMrbkhLoADuVf7asgw12X/V8VoNV2RtAybOYxhO6LvmNVPDCAKui79NUpLi38ZpFcMDJoXrh8JUf/i1WXYEWt1z6UjRtRcHXW+dkfS4nWueMjNOsFR3kB0JnfUVgIeujgr5ru8k7U4j8vCOr4l7aL7rTeZgjwBtGVyCrEBnn+YgKERTCr8wLAWbwKIC9MgUkwGe8IlXm9BWuIC+vnU6WesB0Il5tvlmInrC6JUJVVKYF2JMdurDdm3D7FYpeI1sjtZOfaXT9mWzAPFekpUhGIYyL++Hrl8YNItv9gTc0M57Glbe1Koq2G9ISldIXlpdEyeB89k81XLDNCkQHgH1qM67baRqsl7N7lT0AmEy+1vielj93ULkoGRWvfaXegqsjQI3nSinvcSgB3FJauymH2ulckyPrMJVjKEcPuvVnEH7qJWtwqVwqYCYF+D74zb994V/TIEtX6NMR+/oRuLCzEWVhRuddSImnTpcQnJ4Gn7fBiaxQtJIZp1nbpDNdWG3NOoyB4KIUD5cV/idqdwhcCb5Lm/htipgD7wkPhkzo3vJu2RvqFY7hEs0oaYnvBe3zhY39nM62Koe/L2LYV0D4xN8P8mo1TP69Yh3RL2gpQgwfQjpS7lc6kWBT5YU83hQQ548vHhiM4JuVO1/CX99xktygbzZl+mm3GsMdHFtK5JZbDqOot1/OHioUUPH0gQ/zpmonbC6AuJdoY36laW02H9QkoFPKLwCJQW5RRGihpfhga6N0hRQK3lsw6K/N6SsyJ8zIHaFOGyqLLamkg+2c6AyGh79PhN8Ey3e2jcyFNCtCDYj5P4sdFBswPQr71k/xzIclXUEgtcrzmF82vsFi2O1kfyH3piy3U/ZOshezTmBq0CFwApVihFqis7u6/9a75CwWO0pfp/MSuKVD4p3eIOSX2SwiwnFk0o8V0SCicAcSjC7bdl7pGmOznfLyqfurMwABoeV+/6jqI3+dFAfvqPRVBsWMFaLtSVPPfbDxaWEBR40kfrpRCdthTIFacUVrC/gZz/a2zL26hb7rfPzo70ZhFsBHykU2T4aNQ4xRUmcEW35nV9fplZdIko5r2SAzSDSgC3dugTUoLbXKkhYOAymgzrr80MzsRynPIsnDJFvKAXUOIt0RMTUDWoPAnQMBpKKtCMbEWVYCX0kr+YLorPZp3GWoFBS/l6brsueCjV8tYm8AusKXPFA8eCYyutsKqy0SoT3ZpGDApuEOzfT29/41gvi1+dA691X5jZNsj2JnSWToEDnEtjM8e03/3ZePkOcJWQMWxzOziU8kTYSErnRaDEkkeklZAabXceOQ76uMqll8q3jJf70NJXqx3zNTERJKq3M8gDlSWp7S1c0lJiCGtkAaVY+6/yGFPPVMd/uCBmfdJXTjEnOfDMdXQoqSUUg5uDLcKUYo5967WwMfYXJxIRN3Yy9CsJNJ9mtfzw2qyztFIJ8JfaA743V0/vsdtuh31ovy41GK8yfqijGm+YHn5zwS/e/bPC0MrIZXGtpGGAq3Br1AD+bYRNy1goSjI5Bjiyy3F2AcR0tvaVkwepeimzjyhJDTSlSkOyd1k0x2FdFwqeq8HixIMNH0Hw2gXcJGhPKiIlCD3MN4yS7WBKiYKXzEFCcATkSJOOAdESIuUsRi41GKg4746CuBfAIrYC/Lo6y22Iz3xWOR7p1xSW+5F/ahzu6VHC51ZOFrJPmVC49YEoHCyHTPPZXICNkRLmdUgJQSTeXuyWRa0N9tqoSmgPp4F17McX6Wc3zVDKaOPiTlFkXGyHiNYxjfoYq1iOU2yjDX8ydfMpXy3R/IrPNd4EWASGJBSIuZTTgx4DeHAVJkoXdwrtEWlWEk7j9jNF2xcS22Uqu54FYdjFZJDRMsgg9Cczpv3buXzIAcEVCThuXr9DZQ1UFn3TRcOwA7ha/9pXDMmQbT/TRg5yMUsVxIuSVRcxUvywWPU3Oefjo4RujmrEzJ679F5SX5xUxkpV641/NTkUAliSVh9Cr+JXUQA3pZ/1Bl2ddkJSr9Kspxlk95e1klwnnb6Qb8iGrUSDjAvL+FYPQh+Hy01JgScwtDkuK+cT1O8qZb90ah3aPDan2g2gPgf4W6/NM9qhCkX/LoYFt5xeDEYnbBjJl295r5XCXAGzhXvw7pWzdkaRiiroh6Qr7NxaECLxhR5lhxyikXcdYVlaH31fBDVEfvIrifSQMXzbHYXZcWyUOT6bcWDLNoGCW30INn80JFzjTQk29QpAH2Ip71hJBCLlSHwjl8qqw9vIzGjrO61eEgaaG0r4EF5kxFz/81G2LdNZ3/ZVxJ427vg2eh6X6s4GC7DdLMsd3gDkDZiyh+BpjmJ/sonlnKNa+x7zBysMLL7toe4gxz0IJTn3j10VR8vMHSCavDmFuKl+1Xg1GS5TWvUjpVL+GduiM4j00j6zydKeCP4+iiT6RO5sPYQv9XRmGCRDsQW17CmNkHTkAxUEw6GPuR3Lz+3sVbkZ4DPxiYgJDw7KaQQyhunRXyCdVI1xatwX7/wSrhfufiwBkjIgqZayc93evsxRMyOUmZlUE/RRDn4+9XPm+Xfui7tEcHRydorGf5uiedipWz7gyAaj9dz8QlPQZRv8nnvEvW7YPjnS9LP5KQkLzQ8yUJCpVYoXdLv+NhdsNJH+iEFkbiQlE38QKYQuZ+gP5TMzwplSyCxif3Y9FOZLacIZLlf/r4/y9sBacOuoI3puv8jaGsE92+DQDXGJKfuCDeeJQbEkUPWUSXZfShcM084VL3eRf59UVmYAeBeWPXPtAt6ip/HGFOp+9uTwk0BcS/UFxxqIJukswHWf7HyT3r4UwHf9xU+tPVkXdDg1/+8owpZBc2UDplyC94uqRf5jw/LWwwapvuvRI8lJJUP5dDzMwscY/2WNEpRGjJGSnRhxXt4Ib1Y2igGi3fikOGoOvKqUJ3e050r/9OD9kYX+sqNiOXDpE+LHdK+KBWleQE3iz2A8GRbowO4oYU26SRVFPmYJlUViuG695MmpyUQWEy31QabIALeUYB6/3TDj5rKOCBQzeo0NbRfabw1Q6XwUpXpHTg8m1FtDyYv1nAoF/e4y5dkhx5QgjRmOQ8XN65L2YheEb6e2HQ32KcpAPdM7+VqW6ut5YLVxdcWJrx3a1qiu6kKyFj0Uzu6wXM+kBp4NzeLrVIwyaqTti6oobzt7/gXqjrWLnHDxJo4C3XtojWIBAOHJABVc+RbHivw9ecWKRgZacKF3gvKSYXxd3cFWvVT9CLfpEkpS56K2glLSXKATmz9huAE1K8imC0e/8e9hgI65lgN9fX+5PI2k+Q73PfIoIeAy7AemI2RDUF89aQ7X8AcKwJinkIf3llChHOpzvkRxVHIdLMjt9ATAyZxWylxuLTzkjMa74xSEebo0L2Z9t6EaOK636ZlF/N8FsOjEp/kASX2VPpoUNAVjhpOB107j9fajJKCh4ix9/E+MCPVTnd+cVDeYyTYMWqRGzrvXzVS1bK6gZm2zoKugdaNqX9wOQaY5I2XhntvL5coCK8pKl8do0Jwroxq+wai5/JLkk//+gqrzGwmfGQsNJLUd8fz7WttSB2YECsr2lglanuLVT8xnZrDP/QzREITds/hjjAmTs04exS4W0W4DICHI4wJ8Syi+ID/ui67IC1jGp2A4KJAIo2Rr6jHjXtgz3XgMKw04bEzBBPu8IcjPwoJP4N9Sp3aiMhpa2+oaOUrtv8ZY/2+cU2fnG9D6xBjqLU8YKveu6x2K63xZySyVRAn0U5apGtA+fraQLKlh/UoRsgfSu5YnwufLcIYX8NBgVql5HE7RdCG3Dw/6JuOYXR52NNmNefkuyoOPDKdCy1IyrWXlvcvdCpsensPkGasEAU3JhkXJCaEDprJDDMSQ4ua0D9wDNrfaJcAki1SQ5mjuVqT90hVghBtssiETNrX7kBHp03AOxS3YJqoC0zpJ8AvMjMQ8wfZ6QhrJKkS00gvTu4Hiu4gT9D3yBaD4MJNJGaiLBaAWw4ArPt1P4ry3CaSZNPjEy1F8tF7WnHHOp7YIdbIJ2oaT8EUt5PpTXETZvBOJ7GSWeqrLNdHqhl6BSrLBrXgfY3eG2L3B/6pxaK8xz5H5Z+3gQVa8EHd7GRPtf0StLhyOCoGpErtjPZQjpPpVggglWUb+LnpcyyQmQBhEPp3bv84a4Jebn1rdlqJh6OzHyd3sR6myZWYuG7nGL+p+HY7GxQAuV8uQ6eQZq/KYqiX/3PPGvPiRT6+2f8Air0QEGUqjL88ynh9yubOlm31Gt3EcqO2ba+l0E2xdxgthi0D8TBxbEIsGRcEJlYru9k1mMVNvfnNT/Ic6mIWUOkHkSptuOmjKYE3N4oYOT0b4bZf+qGDYUERtDWRa+pYeUFgHGEmPSC4GuJIu+grMBE18vzUnxmX9l6V6rqf5KvLp//KdlZqL2aZdF1kwl3Ygf8HNoE9vQ7+3v53ZiAb+vXbuyiLsE/LbpIF8xDm1veGm04eX1/BLM9KHkeRxzp6GavkTI93ychjYtNPWH1rXUVjf/6BPrac2zEOPPCQdbrLPVdjYQXxmwSjXqgG5cKbQvbM+Yj6+zeEjFgyKZjj8AmryugyOmaG5+3LBWgH2uO6+0iso00sSAKgQHIX1GxXf4CPCFIvIhYoRwvt9Z9/g6e1DSs1YW2BgS5pjSIs0616iKLMkBw7gNlNDGoF+Bb7GK6ybiUE6R9n54I2fEPX9/cfU64Y9oJQo5ysUIim+6pPWW0np7lLbTH8TTQqU1iheLKvH4eYthCEu/rsGyWo2Zu0J4HcMrnLpDykyRaiS2mLJMFNukgzZVdqGT4cPd+6NZTRbf9rwTSchV2Vz1YlA9m/5Alr1otZCYXM4gkTLWPmmalN1DAoL3Kw1TUIMSZp9nW4hXZGKoif/jt0Nm1JOLyX8XLS7zX9/zhw8q0tk7ECs+ot43qdqkwZeau6z24go+nfnwBF+JwZ51hrVb4i/hMzDzIukPjjDRZtRN61wKoXfgKnrY8ok8F90dofv4K40Jxy3Sj+v26I4ibycKvBYanR/w1+YTIV1Go1DAV1syLG4ZZMKH353PpTMmjaFXxta7ZPhyssZj8JYO3nFiLwoT2bCf+YfcMNOyBM0UaP5LwRMo9w2Qn6FTVE65dok484pdvN6Lrx31aDbeb6TdQGtkSZRMckYaD+jZaDwYEblpJHjBvGgOU02xpXhTXM1WVFt5qERmL+ITpfpp0cX5BHwOuRJIQTreUaYTdhxslQth1QM01l4s4g3WGWZBFuYyZCksx2IfqhGMhaydhhwMymQwVr/9zcGs0M/UIxXyVHPtIuUGcDar1/C2SHe7j1hasfEjj1u6eYHsz9f1uurgfbq7QOyNN9snmsXFS+uU5i+fjUjCh7WSsVGcO6gPYoyw/eRyNbZdYWrfi/JtVMi/xmXRgC4awBjVPVcgsEoHRc8vFOy8I8G3hvM+savRDcKeQBYyDhNmVwPcY1IIJoyyiF2J/ZPuN6ZFBnDrDzkco+aV5X9rH7zzBwp7D5iIB8YSgBPhlLN5hnMuWjlldErHxNh//Yuz8F6mBb6huh82FyfQmsG9FWRvkAmVUEVDSsg9rlhlc9Sj/YpdUqHP5Lph7bydcJFhvk1OJdt1BjkUSgb5+xSTQSUvG/YBgvdPN6q3g0+iSLtrNJmQgucewEXxSSCHyrjRUuNIP+hjwwswokqgCaZ+bAYMl4CcWoytUowdsX95AmsReXnXH7mI+nEoRQnRrAIyXOS50TCHE6kfgYLCTH5Ceo1391aRV8kat5lVvxQCuQrPx8enQ8ThPGXrXikJ50ZnjifchCJBjZLkfz5vXhadoBDG44crcqn2kxLKhCPmMuK4w8ZeAMKLJJd7+3kmXN/VbucGErd/tg3OtWfJQEtUA1Y7G7CfKfPrESRk18xflapp9BSaxR/Ut+WuPd4W6pPrWDVXKxgcK47DAufVTAxE3P28+UV8S1QB8rmR2h4qQc7LBOUZbAy4k+4rM88T/8BMAeDS9y/MrvdoncQnLPfObq7+t0Z2ixk36SMSmAqeTzTzsJf85fqt/b77/kX21n70Fp16lx4+wxopdBprTcLE2CT/JbZQStNXZ/BDlVpF7XDtaKBsKX1CL1CJHMs8vp6Z5LD5W5wN2YOIMr2PfUWeVlC8SZWjN3mI6A9tv85VsVkKI20Gezx1FVpSN1jc47iuGURUXRMf5LrcrnaC3dXL5eRw7PJYX/DX5Fab9l1lg3K7YS1AwuUVxCx8bfs81/SKTq5TSAt9GFyjFSYO8JXIwP2PoDW++kC1te3+8XMrf82LrP8DMBkIiGF8dqJm9nMKrCaqgy/Ev62e/g8aer0QXgRPhNaN/So55ZtrUCe61SryMO2ZHKTtiuTSf9oEpRADKXp7SPftRS6FmL74BtUQg2qQsf4JuuYuTQ0a2izlxfyecL89vketPVFNIe+OSsWS9mtoBvVJ4hVtFnnd29pGy8+Ryw6/USrtTRm+JXUASKXAlbELgyrgHLwpFJFbUDROfmGD7VYibGdY43X/Fy9qIijcLhC6wpD/ItyEeVafekiKtfRak5S5JJ8FTFhasqOwWVK9hOIR95zTd669ui1mwW2PXoYuGyCeaW89WqMMGPSAQUjAtGcrlhejRzUcGNSe+s2zZf2xGgjSnxMMhjk9IMDhIIj44Z1kMqqoUuUBiDDWLyNKi4ty7BHg9TFsvDbdwlfDf8u1FmNjid65iNVJWIxgXD7a+GQj41SrL2pOPI0mTgml2gEsif2UhSraitfhjGcg0fI+OQY/1VTfcWEgAKJkwb+bGuwtr+siowu3QUoyXA93Y0NRUsWXWbF5M1rl/JC6gI2vXZLwbtMftB7n4OSuLL+f9y3L2Ftzo/U2FWJwg5twv0GXoJrBiyXxC3ExmK85OG6sEnagPm1uVqU3wAi+NZTiTmbx/OIw6QBiLkfRlDUrtVFCTKGMkqj6gKU/tU7FHq+etd6ANlItyHdYhKTQZHv6Xg2JkDDzYP5DjD3pWP+VqMpmkqo6cu//qGVYBqtFuBTUMo4bwbbep4zV2uA/5WVTJNfcEYxDnXuu4PqH0RgO+iGJB/84TGCBYPuncpQM5lwd7BEuempan1G9vremAskSUfq5sjt/W5tojYsqZW4Cafv76/q8rCgNNfqMDLe1zRk6epihqCWutafX1B6qtuWQKF0T3fvl+pSfiVSn9banPLZrIclDvWCwB5js7EQzlByEUGIv/pSvogUW+GOQmx+Hpx8eUyNdNvQZt/K32PLnJJii3xzytFf1kW/zaoBnbofEK2v1wqK7UgZYBRl9fZoxqRFSfy2X+zV5lZx7fLJbeHla9JK5d6hf8AyEY2AaQmM2CBc2mms4voR2s4MUdZhmelCr5ubfe15FUMOCUOFw2rGUzrrLKIIWCnKSF5cPKWVu8/+x+TgGkCF1Y0YmUR80rtqLl8+n5yWtXgqMKclgVf2K4dQDRT41i/TjE0QpdAoZqRjavpZbX/irymbVdgCYxXcXAOPuYV+cJZ0aWYY40VxNcaKbyaZlwfHhEvtXhg3ESJTnRfYCWN+/HPbl1waxb0Sn41h7IztmnrzxgefYcg774f4eUsrMTV5nD2zq72F/ghtUbA3ebRaCSOJJe5NZ4ZBNNhvsHiQEIk9ber7NEEL0EjZAMyE4YxFIGJ8Q91tY1GPUYSxb9yQ6W/GxgACUWEYgsyOHrBXAlwEuMyg2Br8rM6FfiVn8aXrzoCUIrLDm7/YaGVyqU5Qt1RG/zAtBFP8r/ZU6ls5mYFN2uqFRjmxgaPYyIalWbt6bvdXwoPZpSRvlExq10pZD8a3zIy7a33H2xWeatXuXYZfXrQSjeDIIozRANotog/w+dGNk4VNsIPOXtQD00l3wzgesyhny24PG3bJtPMUKxydhUolaMozZYylVMcxeagVZtBZgDnw7DDaXSRD2j9HHrpdh4h4NrmfJYi0wQC3LrQSbUt03uIt8r0xmu7ZdxVTGQBBktJImeXrZ4WWTcGQuXcF8h3wXMwDo500FTGzHipo+i8vJXUgixsfglDJeioREMrHo9PfF/8JCg8Dv96xswg68PhVkQ9tZCkGP+TOoiQm54e5hjJ2WCsCbnKP087+D5qN9d6nz0VNk/vKoXz3vVg8/675ZeuAvZfflkHKdfPiqcwhm4Vf6Y9CFRdI+6V+25NitIsKscXYmyrNuicupdJyqYdAPydw080bZYnno9M2Sq8MH3sCP0lfmKpmRFfKn7ZDJrUj/v+7ZRZ7pQ1iCfYPUDW8gWGy7Dbl6kFu+8BhH6UlRyAzcl1Ml/0RxhmLwXyvUVDupChvnL8E4LiqfHZK9K1+WxWqA5JqBo5kyWpYH3/40yXrCpj7GFZPr0iV5FKQe3174DDN308Lgg5l7wwUBRSmU5D0YmshJ6yo00DQW55XKFgSFvCPlfIlXoQbnvRihjDlb1yX2IHorCvpDkxUluPQ6dSLkaYq4X/POnuq9EqgUWMqgl6DVE19gQN+UuzpZKZig3Q/CuykeWw6/KtrBLTXbT3KL/AoAdVSqDz24m1xgr8tUHMe/6THc5R0c6VfTHCuHnnfQ66qk+E/ioLVf9vSu6WOVQEK6Hj+aG5/hMVMCHRjCgeuiGlLVRzuV/o3NxvuStZK4gK2oAfveMG0pqP/TvlDEZYXCYvnPtchk2hGIXHY5y/k56F8Qll85lmSoGApQdMBF8fYpY3I83bE3BVQcbfqFQWIyr+HflwiuG1HfKJxmRR6Acu4IaOxNcG4VmGMls3vzcd07wEomL8wG25emZ0Y9b+DJGVobwWHcyYRYL5VBvhFKYNQso7ovCb2/DGQ137hljgebL7qtnPDRPT95ayBVuciSsOEhKBEuzYa8eXxxXUxXTo2Orjhjxqw1GuA2bmVYVmOfIp/ap3ewMKLsUjXEtpHmh+PUQnpzZg77HHUdZQAnfKYTmZ6MS6PBUmYJUA6Qng8rq+Zf7W8lGBCwxR4glj6fk+NBrPeF5V06Vdp7ms2g4yc+OOkJJZTeKX2KLa/k8LOqNFG5hPmRMApmr/x2VIiKbwyrqMKx8kIdFh9UkJpzsTsU37rNbAz9lmpRItQaFcNqHcCHG7GoUxKOY1CZlsQWTO9CwIVtcr7a6Lm9BDN4rZQLusgQqHJEtb5OM5X2CN40g0/s8N5A98iSACEM64+pAuRGbiuGpht8EwI/VG5W7iEcGk07NdI3quviUCqssSSshimgyeX0YzSU8M9gb8rXDA6RiHG4pcGeUvpqO1PvVH/r+X/tktOiKOHROYkYFYFB3vuoalIK5NqO8eOcYzvlKbf35pHH1VfxMDcEYCnAyGhO2/CkziTfNfm3E+gbHA/RvWXz5/ttF+//NiRfxjE9csfLBWjTACjv/yqWdyfw6Inz+ameB6GStgmKhQ4FRYlC4KhccL+XR+kxGu4i8ar3EjkJXhMKHJ7Hp34faRsowEvhiTCe9yC3AUJ2N+oLcDfI4PL/0fU2cBqFXx/P0FVECUUEpaRBGREKS7QRoEpbtFupEu6S6BCyKNgHRfOqU774VLg3TX/j/fOQ+/9917n3M2Zmf3nLM7Ozs7OysLBTU5n33cCF+CjwvPuyBKtA7AiZIYWGnKxgt9JZH+ZRk9GlyHqMIycxFw2cMDwTC5RLJJg37Mo6Hif0Bo1GdR/lICLBi0U9otfub4bCCY9p8KiU6+A0Fp8HRn/EO1S/dgR+2KNtuZGGzb8bFZ+x3ids1iUWNrJc15Dhu1RkuKql75lCzKZpLJ+KGjGxUn9R4l6NIgETI7qHBmOs0hX6k4lPMAKh4DEWp+qPRfArBpyIOB18YoH75dCe4oiJivJrInRPWDTyUN8Ce+x+LK42YxY7ljYOI8Wtu791uQNxEaNdnnvuJ3F/QtNPvhX03enJua399qNdw2r4Kd/9UBREnXTgL9hnsUKxyPxr1FJm1eXcQOGOROBm5bQm+omGgSiDOxOR9B4kdK+VfRprzFjapVoJGVEtv/lGVwkxyKtSVNhfwqj7rpT7V8cY4rGG2Zb/Ixr8VQkvaXvvG1+bSqSVfEni6NZQwpLPlkLYg/p5128XYBJNdJioIDtC8zUPOPLUTSIcmLeIxbucIAqSuJ2qgI/ib4FuvwwpG59zZMbXG+rwVcycuO7U0vBMP/3dB3iDGnF0e3CAI1C78/189+ffcGykzcn+UgZY+na7bN0HfapJmlAX1zhKaE64GuFY6OpGrnG9bctwskdIfeK35MxUjfLI8MpgQvyFitNcSWIW2S6eSExpXfgnWe2GzUK6sRQ7V085FIDWS3UqDVs0/oDCm2jYX7iR+nr0ZUMl8pe2gGV0Lh5z/A4jNiFHcpLhBUH4/FbHzXtEaMuACkcpdWfBd3nq0RBAtQkQCFltuj+/0jUPout5te39rVk3EaPzyz3tDCPG9NRMtY1d8GqPbv6oOwPDJiOUVKildMVjSAd/fywY7XJ6PMudHQ/ZdjF4yj3bg/USTLwVtRXXzBhSZpn2U1sP3SRDPkgGAFvi4LCnRM8D3oXjzuufmuH/bU14OYBMCRPo1fmvCF5vb2DYRQ7lpjsl+U3sZnhKhAQmQ/HzFXBA0cPHNEPynrtF3GgOnMABPAH1Wd0UwXgqb8NhCyYqywIMAV5uRCHlJqF0Bh6rrSnAxbCbocAodHn1SRuOeBTy0zHzj6CqOkqwWRxkg0l9N+0gluhnW7a5dNlTr2mt70EdyTmeDXJAYS+wG9fyTCnZO/B9UYQup1mYaSW+BTVsNk4liRZ2XrPJM1m1CTNoDFrP/XqmIvmfR0UX7xDZm8sYeM/tRAdCFNakQDaurjWTC/rOoG+6zTELNZC/EzKcPJ9DSu2gSKSTjO5z72rX+80l3YjMBPVegE9dc8itmLTz6o75XrjNOn/IWU0P4xSXyf0YBEMdBiq/QX9I6YU7Qobfhaq1SOfKHVZJAX1pUSD/qax8deewLjC/0gExet/EyRmMNHlMWygL36NY9YRSX9kw0N33zEtO9UGgKnB4FGrtYWLemkraou12bEKkUtICmErbGAMOL38Gr04ARRwqU/uLsOmFc2holbWb6KHsXUKz9tjC+fNb5hTjkwDXuC3ssHdwbDZQMWH1aDP58WAYQByRKY0gOjpD8rrnIC1ayQpIVBFfkiPfHb6G0ywmooXiBLj4Hym+0jQcUUSH16WN+fhANyFKxx6Em+cwngrzgMyYokWef25Zd5eoEiP34uvv9vgVoigeOYOIFxz7g1QhIagbnc0hQtLi9gOWoaLIehixCDqLyMWasrDtPCNArOWb4Xhr/58X+2iLINNL+yD+F7akYP2VYz8l/V9P+VZMDMlCqA59ohra3iaEFP0/nYKAEk8WvG/CREmqB2UF1z8TYXtAeiem3FzpDVN6KDWfaSpVXe3GCO4nu+b7NjZK8kMfMm5+m5/w5TDsXQs6lJW7z8N1MkagG8i3epeIyswp6R1ZZViGI8dd9VlQd3xUx5eyQePvdUyRvNkXgIMd5C3wym/jnTNX0n/236BUKOtD+qgyQKv4ZwkHrIstmQJbFOpugTJVtbdi80a4De4wLwHX0f+a5jhmyHWbCYYr/Qs0/JimdVt4Vm8Q2Q9X9YYDl0xCpAVyyzBurjkK5L/pOY8LSnsYREIoVvYmZlT43Wzfb9rsydl0XBfcq3LMRs8BrNVLjsZJgE8q2mfV4MU8xZxY+Bfbvt30LHohVPdZfB96lJtKx2penTqUxAwBOy7MFcWkUKC64uWo08pTkiazAWFmN7s5IrPQ+q9OUNvrEeU8pLmcTwvI99IOeKnVeFz/mkTbmRnB6S3tUvWVtF3+nb7L0+niWsNgfWkX+vBRNA/sGmpXWWmBv5H4o+u9axaMRf8jqusAG1I+SkF+tuNyC+8/d+znfBEn/DBY2hFSdt05StLAjnl7sWCTmaPR+h/vA5eW/Smcc0cqlew578OSLDc9+1uAASw0j+5rtcKKjJf56UNcjLyhoknK8BVT06zp7EqnmIEf6LXzgL2l8/Q4TtWHBqYysnk+lDYWt0mgSUWizgK+31YbLWgIVifdGtWdHtXCiwo/fYPSRWOiS9PNoMPr6XFneJM86Tgz/otC51ODGP4FisMdaEqRrjEh0WB9HMNsytYIdFJWlVmeQwi18fK6yvqDo7y2ler0bh0V83NyWMicJlH86r6G9iUxdnvbGIg8SaUu5bLlk1Y2K6FHOuCLQaIo3UMSdpg094ti/Ck0e1NCdPffMthmcCoNVe93I0EVv4Te7ki1dncgbD/KfUGyE59xFjZ5OZpxHWnCynGSsa568d8/V78ab4ar/UJVP8+Up1kquClxVWXRjCD8gyYpad3yntpe/tM/JmoQ5j3AAUyOyIWReiHIfddLLynzzGk6AkHat9ldWkYbTZCBlUaC7zT49HvVNSaOgiVSZyJzevrgrAbAcYFLe3iUyy7jR5mqTkcfczLxLju/Pnga7pCFk09q2vfgJ0nz3KGK4XxYCxsGB/oWAI91+1ROsWfatVRGizIddz1fcxWSVddoiLWlkq7wd+QoJ07sNBmqkrUhl06fnOeyc6e4i1Jct1XvsujvSJrhosvYA7Ui2/7reXSuxEN3CpMRvS/D9fJ7elU/4HHLUyGMjou/iM7KNIIuNFKiYnjSgoNv+L+F36upiSmjCPuNKAGxt7ubYs+YR5B65toKCkbO7eiUAyQKBhn8U2xRGI+LrUgfyTwJ2DTAT+Xm9PBeCXZfiMgUNtCAXGmL73M/qx24g5sftBLVjcWBc8P4BUXIWZJzQU+Bfs22PAvK1I1lfCdb/dgg0MgI1lIZH77MxBri6vMDzvkIVm+gOgQVmzYCAUp9G6jiwq4FzFwH4/3I2m1Pa8fmZm41rG0o/ckXyCokUwYGZH97tjPaWpFGRg2/2P5YTFupl5ADU1XHfvCxXkbraWSjYKsDQH1EeC5/+thcYgLSjI/cWNlhJ9I3YiDvi7qUGePth0XMzSd8OaL3HPw6XjRhta983197hLyr0R+C3sCedUjG4slgrdCnYy97dsvkf4Gpl1ltNjxXNbmLVzNOeyQAeQ6O7bfdu2aMKZtjHUj06HOON3gB9SPX96pA4RAasbOA699NBAIHwantr+4g/GU8BAdrpbO0OBfMoSTNlIqgg2MUVu6ja36OQE2GuSH9Kccvs7ybdN1Lg8yPW6F5xvKVD96HbcGYcRAQR7bRhbZQEm5EqMwzOCyQwP5upClj+z011MPDyoJOPajhSrYwOivT0/+rF4yZqXPyojAWjaoBiUCF2M+77F58hMxLnEvBXgP5ZBldYr+OQGMVNmf0+ImBm+2Nk0eJZLyn6SiNWC+VSZHktwj+ufjIs2IZ0j5Td9MMiaP3ieyK549vdQMou7jO4AXNoAibvndtRjTnycFCVmJV46IfXB11Q1RZKHd3RvvIn5tC7r2kbA6RUpYaYd+qSyr6yBZ6lNa5AGrK5ohRRfMpDSUdUaG1KdIx4BHWkrA1u2NGtsj+Qp8lUpMsxUJnir6crOK96eoSiqvE/cliaBgOaNWFV4lbWAuTOMOgI/FsjOgtPY7ekLqACE5AzdnXYZC6sH5vGz59+mioJkA0pB8/LKP0mPJI8feYtsY+MEmbkynX9S94uiE7WQT2jGz8CkmTftG3GcAzQDnRjdcrYKtpFVq1jO8GgocL4IQ5dwOI3X26iElHRxF2S9KoKxLi2ks3Jg02Ys8SmYyTIBC0MGGZ7dINFhqiFMKjxSZ7gaXibqMbtaOc+4VgqlK8OBgF4vAG4B+0jCdCxKdyEQgcUVhUfMrTUsq5ie0g6kOuJrJV2R7UU7ILBenlS30XqL8W3JlIm41UbQweGl9DIVf5qfHBSNErV2b67DVG7b/I0W+/kqKQsRmGEas7ZyVsCy0rXL/mTG0uFxmmi798VHvggd/Ze0mgwHiDQuG61iXeVr6YChZzAYBawyM0vOOdsk2GFDc3R3swTfgHy7JZQMqdsS/E4kireqOnzD5hUhBM0XDc/Na0WDZHT7W82MpZlKTb/hllPaXWvhJaQReJOmgBul7HsAWq3QvDkCx6XSxfc2lIGZkEE15uSIyCK+BmdWSOSpGiqUqOi3WYDwxxZk3V+VhJxKVeLTWky9kzC1Ptw2TrqT0FBfN+vHbiQvKljeH4Vsv7SUX7aHika/6fJF//hTNZyEiksLFsTr4a5JLpkrl6anFOmZ9Wy9xB4JxI5yPPh/H/4zh/vgKC7htL+z6FZM0HId+nZBtT+GaiAqOpAbeLbXTUNlZqwPf0rkwM99hXbILGytTptmuj/w8dRqBanczOHlxPy4WQeJlDaDnzhcka5G72OaKfrwxyg/FGIcms26DzBxIL3hnSTMOGIr4uXtddniJT3zqiEmO/94//hLuHycX3QNJ6brTh9lbGNA0eF7KvuyswC3h5ECHa1GChJ/rbZGYfwdEWesSZKUBMh1khkI7GN+WvvZ8lPGDtrDFuA5JWyjopQmKP7P+j7cJkM8rVah6Eq5/Jx/5b/F7EpPwQoNEPCVBCCfBqav0dl0/YQOrZZ2OUhgUBtS0c8YoFzoLXZllVGJEWsmiDumX/EVyf4Eq8FvQmiQCsPcPle8HGdEluaFV3DLkaisNFF0FfbYSzgmW5aGr8nrN5pLIEO6qCw7/veWtPt4mx+4gbUPXH/eDozzCEGOW/iW2xZ5d3PZAJODV8EDSFlIi1EcTvR9wnLE8z/K8PZ9yTa9aWfF0JhiebN3yWF0INls/1xmIFy0jwggvPmWGrombxffZI3IrWoo4DU+Xbhy11Dg9DfMCUoB43o7lzL9YJon7ke/OowbDIZ2/o9R1GR19LVzu2p3jQax4NHbYt2dU8hpoI2gNso8g6Ty/vFz4b62NpytEZwCl820sVNQl4RiM8nM42behMcaXkmA7/9JqFWw86y6OO7AnsotNGWqDJY6q1wsX3s8ow2tTU8vJ/WB64GPGd+/Nnt1PZDZ7WEcWrTumZLWtqa71NpgUNda2K03zc7UvVKjr/AnyKBl2s40ECpzRxCp/I2+mfroA6ik/YpiqpacS3t/5LtLwepe+i+Qdl6VzYH5tD0J31fJnK+RDsiQRhWyg6AlP3fwtRvov9N3Vl+weOHOkZjAALXfgSzeCFAQ03XRKgxBCGWXECJtHMXVUZDBTKCopDPPsEyEqu6UvFWOwqAyFzQbfgrtba+2WQC4XZaqdUx/vw1hyId/MZeviHDtRo2G7u8bajo566+WaehaGbTaCFRQkkr8hIlwlB94X3YXcMFzDBfZdswUY2h0g9I3vyIWif/6ut3O2sUqi5cihQta/M6jANY3nY5x4+kqfwjKbRAfNxNhdUnluMeeoNQ8dBMkyssEzsLgxHtM1AyTvpeYAwZHFodKoMBKxG+Csk4uc+Vyqd2ZAXt14jp9ejuLRgguZrlJv594lhu5Qu2JftnSoaSd4mz4YDW3Bo0QrMH/G5+/hX85NZwVplyqdzjxu/UgzaWH71OjmPwcY8r73t4948ZkRUYTzEVAOHbTZ1yBhPjjilf3rSZZ0O0ehbQ1ui2fBI1ScGv4QRiDzcwvWJ/vUSA13zv4AJbPLk181n+DI3YRfl8jT58//Y4BJLHtLdme2F9i6EJF6sRGXDp+yzuU4BpS8uHd4X6KtZHr5nWvjcmostdUoUsR9R/n/3REXdStcnMIrpcG5UjR062Egs83BJ9WAuBQe3TFokBSwgSTIqa+Mr5SQhSQq/HJ+dvtW+19EiQ+90My3rkssOBx4qHKFVtJ41h+70kkjN9G5p0VsgrmcHrZEulgXEs4aeOYry7mjhtKMgPoKe8qFSXGpX3Iu/9SSoLK6MuUtxs8oRL9r9evBDZ7ziKEfOsbsI53WTIRZDvtlCPgA93yZjP83CYBhqCYGzrmXqz4W8beHbZeY1WnZxS9R2c3KC65ogvNO8f4ixtZhvRkrBgEUNqFWfMdxAi2/yg6rszzPpcoYiYh1Op4blzLl6kVpLw+etn2rh7b6D/Q0WtarSNm46xYlXZ9C9RZMtS3cxMtL0m3g/UpvzePdNBWCNUeJoHcrpq0lunnMGAZGxg6eqKG+v1eaqb0SKIdVpcRQzVglXm97xompFMtdWnjGd9vOSEI/S9wa+ZPiEHzQWrbvlBB4nCXsSI+xwzAZDQaqnkUw3RLnemkVpMzAJMNGHz/SBPOp75Q5TaCke+YwK8elokxsmuKEPv7u7jpJMyV4DRuA/kjX7GvrzsanI1DtVChchqQgVA1OvjGDFFmaJ1CWD1piCzJXiEfGikaIJOXoBjDndGGlEP4QulOpJ+PK7dF+kd/BkmPW2j3bfKbnI8BMUQsJOHVWm4jNc8zgT6nQTJEFXWSJLnRPG2ZJmbpchUGJ1yvl4ZS6hxWEqbvA57+H6ksm1o5rNJTIpVMfer9qAyqojZc6pCeWHSw0v5480QQmjduA0ax+oTZJkU39Kh2nVHsAtinSXqYJ4zwwVMM4819+EIvhnh2PVe24VZ4FeEfLjDJbahQmQPwl1P7iYhrDIJ1ezUUc0S5St2bub2bCfIyCEZBJm5YopRM2PX9VoFs9kp8jpvI44JErlRP9pfPMFr+BOR0IjKqBv8KQtpQcg6S6bYzKjF47+ZVjZYxeEVLs0puF1lvqkHlVQ9AF0GR3F92fQWJ5fXLNSjow8oSK8Wxdw6pPVP5eBb8QNvyywvrJsIDByuSp8iGArBVY5Ju9RULWfCdDus54cPwuyURfEHR2oBnEwwThuK6dcz8ULdx6woqeRpjBItiqCnIYNtOEwRHhwWgfYkRbMrv60PvnurD9p/B+5G4BzkTqNfHVOVPS/gM2eyulQ76MCdZ3oDftFLIDv04Xjdma1XFF0J4E8EGpWkEGMtnUExS7QI6r3nXL519vdDqRwfqxLnp8E/R4Qr+xELXFnu/+aMnsOO5yF6UHF+WWhUsiH2nNvoXBaAwdpybsvfAUhcIcGd5+zlN6qBgYnRnSG/s6nPFGr9qIZ9/snJjuYu+hGYO+l+jmxupd1a/NpX9B/bH0Q1nCWUUvWu8DQhu0wCYdJQ7iO1nV80d6d6KMMfkmzoR2TEJ+iF7eey+KUklXQ3Un+gKJWj6vowOjA3z38xl/Lwhe+/u15gzAgTLgxu1gf2SPx5sFp4rnVE0Nkx6InzbEUiaxAx/GMS5jJG2M/7B1iSb4Cl4R9i/gHHTI2RhnKnzdSLgizG+RCBMaS4c/kYiaiidzgeOidev8hvypDe1ryzkzMPs2BYpNdAFj+tObQ5UFVGnuvC7pI4a5hsypq9GFGGn1VCD++ebqPG46v/Se1uvhz69Uw7eHBjsl17QgP7riHbvKVFPoeWCjp0VqgZ/QB+dyBJ3LSJPEjWrfVCzOd/qK2+Mx7AmHKJTvVUzmmCw+JvmXU2f+19P0GCuo1+rrK5tggs6oNntgQRmZJzLp+WETYbVTFjnZ71Fi1bDbmsNOy/7on4bzMvhGZXbT8tmt4J/ULFJFqcNu+7jD65HUP5shJghyCRo9uiriuiTclYM3rToS762PCl8WG6ZW7QkWl0xChrI0qDL057NGuNzj4KZOEyumVj4krHJT/pVZ1G/YQ1PIXRGVjECNzkgJ/UVKmZR/xrn7CdB5loooqtGw4T/4/vYCKS8/DRoQvOuXnfhF38Du3+yTIqcWgiCu0pFBIcD1dXxG2zCh9qQlFZqiS94ntrkd274wr39JysBp2ZJS4afEHr6XBpmdHUZ0ovLThX9Hmaf59yuRFJ1Cbw8pGbYXKgonNxT3vWlvTL9qpgNrw3KLnc2DYQze58CnDq7GRp8bin6JGB4Npd3UFPKVsmko8tMf+jX2lku6mPvWqwNgNeMykJ0ajylPtAila4N5ZgqriRvINgKngSeYvB9f0RjgnpJGaTun8pvGyAa4OEUWbnoBSxWpkpsLolApI7piFbeK5RyifkxdxUptBIVx/sK8nMaeS4MDkjJjXwHSpxI+qX/5HZNIt5fUSOQ6IxsO9GylF3BrUHKiVBA6PD5pSajG1FYae9cVZtekLyT3xtik1Fis8e0iHhzl78kbFUYwB1/Uq7/4a2DHtoXl5h0FiVwzow3tkN7GupyUoZ5HwFLtpVAJ6nht69MNvjsFmHiJ3dFuyxsw4cPI2if50cl6GFh8KvafPOc33GOuLm8SGZQhQyU/mdILgvwK3tNO32XOlZFRRXwm/b4BcduWlkQtJJatq+iVa+Uo/ypcMkoDqmgXMzE/ESpBuyXBswxMWQmumHClQk8fnWiZ3oZO4g+kX/9z1K3Ogo/8EhzZEpjZmECBb/4mpRiNE8L94WT1/OFLZSf8nvagA5Y8o4Yfo6nTKr7Q/NcVx6MKSBei0S76tq8bwNTghE6ICP7GjeIA7cFsZNf8Zlk3NZdym4NvxSOa4uoKq43P+rayA/d5cM3uPEByTkAAEAASURBVM/78Tjk0pf/Qy0vmoqyHxtitkVawb5rLb/xmsDI2UnGcU0jZiz3Y9BWIt3Vr3yjmULd7weu8tgeaZrJGHyffpfbYzICn1KG0Y0/1/vq94zgYPgQOcjLZgSlKnBY72wu23aUdUpKRHTZJ4QfAYI0Lbwgu28C7XnW2pcrYbtOXiAR6kaj1rLkJFRIWKkeQUhsOHGt+PyBj+ts8y32lWEyYMsqqhbvXGy2GmO8GpBwv3Wff4InMrlLK71dgH4fxo7yHua115OyVtxMltMUIX4x6hIILhYBlJnmdwPa9CZAT1ZgrbBC/6/EgG34DXTV4M9MWS2EkYmthqWJBqusE/aqdY/Dp4mALPf/Paeh5vmtLQhrWZ9oUZjA3WMlbWT0T+92bBOwdfa4oTRZCxT/2XnjCsXMzZSe5llxJ9M9JIBg0RfYjxhdM4XGaB267WPwa1pJAlPiWn2e/zRUlbDsUkaeAU8i9g63SQl8i2YoKyiDjBBoreMued37V7Rl6C/F94WKoaafmi1AAfH5WgcfVAbDAEHyr87CzXgorSzKMadq+0Cxhjk+kSPtkyq1dBuGPgRH7xz2F5/T/YIaEGnN7BVherZidYyNy3ZG6gpgy+bfdFaxV5Vi+GEUShBhJmEKKEuSVVzqKUZOVxOFwL4qi95MELvE3wDVUAMTSd7k+tCVEIT10hqSP88CfWcn/sky2F102eZWCSwy7WlusB+4s+8WRSRix7k36WIcEWfwTvXCP9w4kPi2g84nHwTEKQH5Dkf919hsm2cBYh8hGs1JGcvOiNLU8qWWcttUjxRVvZftpxeDfsO2n3vtYIROd2z+oS+18dw0oF6YWBL4sCu5ta7INwQDjQt5JrpKu9ua+VTZLtEmDDaIyqOHikrlt+XA3z//WPehIgJOaL7SV9ND29mT556p6RWpzMsZ3bowCSHg8jU8w/VsOLMNVp31t3uvumhy4Yc+nKfKwNkvujDKd8mU60tZMz6gVEVqLuGPVoph5lUKwzFoGqVxSvJ0kmjB/qyIhumC0ohRrVB8T/oBzP/fdvQLswRiZ7vj4QKcTPq+K8Dwp0sdTJB9qQTitzBWRLyFGI1UK+/g2keQMV0Pv2qZ/7xvavyHp4pjL4eYvK3gD9PXXAMkACqV+2L30Symy4YXVpHIlFyyU0w+WRH7MB5xinV1eqG3U2XaQT7QU2IuKI69kPfEy1bHz+yTeaUpiAj+/Pu+0OPZuTTZpE/b6Tph7caqleHmKlqLPQshJ+NIbahY4YDX0wBhLUUxPW8hzkeswV/hNLDRzEm2q0Wxp51FsXULIL2r918n2xkWRMb+Yp8YNFBbM5vgv/4J9X0Z/ePtM6Z3V87nJPoEpbYHc4f1hN4nwl5BXQbtIhbwn4zXfZ9oeweP3W1Hw6OrTGXtVe5qHuqEsrtl64d/jaxX4R42k/RH8SR+S/fqLS3dlO8HwjzbPeqPN/l7YLWFKDh9c54ci/rDYXyOHUcYZFVNF8xJujv1ZYdoVxDRerCSAFi15BSrA+Rzk76wr6YcyO5IPmKWD3x5zbMS+CHl2WkTA28r26bi7kwoJ7WVvwbtM3vMfBVeYm5tfZB7hgyY218nVxN9hjUBhlyEHe+OxMPDcMwydnW+oeoHEyz4ASE6yG7L75MLz3MYGtutMV2hCQL6FNsVp/6tRlCv9HoS3sgLfwHpdQwhgmPpLEw4UHZBWPMIAt0KKuvDClqslh+wyrsffRqFmcqgBfqf3/VaOgc3dZiKoosKlbvdso7ucnyUg8SgnDG6GzOqy4renWZUakrpxWJUx2CbYX9H2wuehc3JaT1D6pXjmcg2cFvaEiyh6zP20Q5gHIdipExOaTnWkoORBu1d/wF5xZzRkUk50OCesPnrndCdRsj7b1AXu5JMRwxcQTsN4mVQrqwQZIPRENTIWcJT3538Sprcg9v61sWZyciN+oJLWVcwIbdzvvlY05qvM72xn7/qjsp0Kx8+Etyf1aWHgitz89tgZgppaaL5wn2muZQRvFT5wgxOfY7seotLJDCsr+ZCSC9UZl0zC0qbUhsT3v+j5QFsfjf2u3OXloWuxnhXY8/M9XOQg9jYeexRJZsE3fCPuH900UYj16t2DgE7CPCoOXtH30CN8wzlNVCZGf2ZbtiAmWIYH9KhKglxaIZHV6QGilBdOZECq1qDXvpV13hgyyB5XQ04iuYfkCUjehK7fjdZQGWCy4ODxH+jOZo10m10FmV6wY88zzSM9j7qPzm5xddcSxxDz1ifd4QvMkJlbleBzR9rZ/RW5ULupxh+jHLlCOz1uZcWmX7D7+crdZB24Awk9QL4RGRZphlE2+64Ngt0Dh2BgVwHxxcvuhBEH/hiZlgG1LLS7H4tFMmVkQHIHfN7nqWFuZn4Tcz+T1GzlPMUZWTxRTysUrIxy+aOQXM0fpr4gYeIkzLg5mQV2vrVg6BdMHbfs6d9ThTCgf9YHrqrib9BcaG9/HmuGw3QkGA06QTiFIg8ugNNpfJdgBX9WCyd1zlkZqkaaoJN6imUoY1D6+oW7PE1ToqJ+v1KJ6GNMgDqkNqfIVynGIxqHeI68guNlrBASP+OvquE1YYJ0EA9N5GSLslNZF43wE/c3gLW5/p+UlaIgTIQUt2wzw3KtpoRe4HnDNQPDO8E4EB8FpFEb1KBF/RYrYW5o+cIxEB5NRR/2H2Fj93rwSyMNUveQmBiiIWjO50/hwwMKUSzA0jiBHNYroQ1FjmQY5+srf1bKaahUss/SNHYhKEqe0Cke/qxdq88gKnV69BK9/bZZvKYwFxVJY+ikTG/ZpR9m9k3n3y9uel3/UAiQwUljDcILhOWaUeH8zHTG+P7k9SJ1C27kJZB8gpS5aw66y4gOvLPwhQkolYQfY6PuB7B/L300tRgBbMuC9CMDsyHVJS6GR5JUNNrpaIcJMZ4X9cKttu/SG7ph2fPBWzLTRpN/e62R7mAhA9N6OpWVkhY04gAQ6IKborVpkdIlix7cPGle4ndQx59lM0l3wXVQ7QVyIH0Fd03GP6tD58RrFi0k33K/7lNU6d9rcCH4iye4kkoEvbA+EatZskw8CMGKNzFwlKOrcbAEjiXHdIEUlw7E0y574qGZLJE9f5eCWVhCKWZ5tMu4SLgvwtxMQu9PmnzQLwqwDSKvaCJZEFkFUK6CUkzlT8go5e4BHpoBiF7wHEhDpDD5U+KHBz/z++sohQtyfh4dwS7inB3fyiDMiurZTQRgUW0GvNPEENpLn4rvahWriUkmJOE1gdZuK6IxlPa0l4NP2uge/TXt4ZqKVNNtP/yX7YNaKP+MfQcVxuUw/UuvZ7W5SdtXckpjiochbG4gcgQ8VUt3zL5E8Ul3IFazscA8OUBysn1RohQ9utq7yFpBGBJl5kEcSZe2mZJbirxLpd9c/CP3ceyKZHGJ8Lw/YgfGwhckn7Czi+Wu92qxHrOlq7oMCVplyMPfFomuI+1k6S7x3xDKX6adJqsgTkxUoT3/PVS90bMyZXuy7u/m1xUgmJfarw4YboKsYRkJnHHwF55DpexAtJQo6FLfhratw+ByDA03VRqFJUr2lrWD0nPK6kjswPS8uuVway3F/tNRCrOLyYa77U/DECBld9oMqHPa2ld6XNVgzdAmJmsdnAVpsx6cPgbVHbuEzsLcT9Jq8NRou9/YQq+VWZmys/5c9Cc4jcOrSZpvDgaQQD+urg7soCFjtRZcqB0EiPI6OfthxFeZQBAfpZcJ+OO5HnLMYrYzIVV1sJwicNWulEylgBkHNSCmpX4JwXMpGxnqXXgeHiTtu7UCgZnmjJxQeWgoNpD9rWI7lUJP2m/De6HUVkYg0qC8tkFEdLKFxvlDQVDd/ZuH/WjmVReCX2vrwPDOHrmawHwflVp4f+yYgFKfhoXrjdpFRJT7kd6PeLQFR9BDw7Bw6O/7UE6ETDHuPBprCKp1bX3z27xEJ16Imgb7f4xiYFBCLgpv1bafQPdX7rpGCLn6n7Jyx1FZBq9dusP9PDSQS7g+quiFfkNV8zP0spALA7HG0GhEyl10ZLb7/l7PSzDlVGCRv1c1AqX+JH60odE9uEcWZ3+47YAwECGqx1fsHQ4HKaAdQNlIvTJl/lMZaBv8fk4UOdWvjqkAO6vsR4zv32iGggU32JRXpkqDqXPr7PMEP/xPjLEZzMrZFyLq9ndIdi3vCrt+V/owIm5WZslNKm1YrlwFCvz6b7QCjD5zo+Q64zWggyOO24kPzDYIaz0zGj28fYRpR51P7fa0AYB8HgCM5dR3HCcct3yLOUrCiLdpQPrnyb/RXAdDSqzVD7xVbErvpsKMUl0EQ8LvMEmB838Kfr6Ln6ccraJw38aNAzpYN4W5K85n4bYBYQSNrfIAAroH+5dTaQ95H79wu3Mvg0Pb2LsO/mevXYg38PAuM76fnjG7zjt0nb5IQLiEBZLeo5WHy01Bg6iCN5Bd/2MHUSU12twUo7flTWDu6yitdgb9UIW9qecUu5aL12ZSCGhIwEqn94o984Zzyyhvbmsr5jB3i8+tAKx60k6xX2TFcw+jInRMBc+qWuYwuTpZgwjQP5ZIRQ6qYP9T40rdiBVfVY+APrb1SpV4Anvi4D7fuYVgavoon3FjDVqjVhos5DRM8qyFFdWyf4lvV5gCWpu27gnqGcNK/RcJ7U5KSotHSYAmzZoOsshyxl87veX89rIyQSFuPMbgUR6NY9wD2YZLsUxGOf3LJ29l8vlyQxezhK/CnYVqbY/gBv+zVw33HP1pcuZSKl0B9xaWQSsIcMacnfQNO0raDmtAuyGF9TigKK68SovpvNjutrb8p1q3XlzCO8ykhInbuozJYPtVrZbtvnEkIyNk1XAVeni47R+7r49aYZMjFmowseyHLSEe7uRS0RVWaChBTApfgeloPxOzFHy/sNcKJrSFCGoyj/V8/8ulT8Ty5+89azqU3AFdAYXztWnTXg30LH4RRvHbYrH6GYviilwS0PTlSZmLJFLG6CmHY/zA1Px7YXJ/wHt/iJFQEsgL0WDauk4Fk6sVU0ZSgwl0I8+Vw5lc278f35y28syB45r/ZV9suAtJ40u3d77DOa0d/9Dat+mtat1oIBv8Htly0vflPxJpk8C51g+hl/JOS2B0lWBGUFCSxtfTvrUbRXdikhsWHPNuUprdIjn3VdjGf7bz5jhi39ABFvISO34SLII292tHGt83i/Q9dqtYzuYEfit53e+gTPAN64Yk6Ea/9Y9pQAzD6yc0ibikMmzvSG9KW2QlEfWCQcTmaYLnDFg7d3MtNqDhbfGK0Sya58wjLIVbYLaHutKTTYBldqkK4Cgd4O7vW1oBNTGzg7AGobZVClBfORwloqW3vCl+i8O1rkE7EYOTww7mlEl2OoxLBbeZ2pheRXnMkfaLtWtQJTft0hQwXeTjzd7y5tsQ033f+5uJcwfzQbLrcGsKpVABqJem0Uan8UkiatEqBu9N4QJMmQKUCXcZnxb/c9JRRfVKgrepYjqy7HD2vs0iuxf8mK7SvCtxTLt7gaE0eOsma3oFxTfQreVStGSGVLYkTLJ8aUJR/U8sHXqCHHQQCTYsaQYab1pNKB28KnPn2Ff6dQTQiLoV75CwkDUPsbYhtXwQCIhqkN7Lfr2pZNs9oUEz9CXnUxjnKNBBk1IHazdz4MRXAemWlpxx2wuDLuOzvTLfpAJuBa3zwc7F4CGxTaneWMggWenD3v9FalKzlel6IE2rsG4Nm9PdZ5CVb4k4YQehAXTqb8IlACiJNtRYZk+6qqWCndQtqNwKJ3LMStRPsK5lR4N+S5Ll3h7CwziHqjVErFlsKIX0Lh8/TdCsbqpnwnd3VWvAVFQVVKP2j6AOVD1mR2lRmVuMuKWAmKSKys4MxQrv3lTBBHvoN/FMw6Qvk0wAhjPrzaMaksCpW1DlgDV8XP7HhOYx4Ycgq1S0K0ogm/TkXWuxEK17YmUUeZ3S1AP7cZisZoxn+0zvsQE93qn6Ko5FRdmhWpX+F/jgkjFpue3T1NS3KDpXL7PtzOGAr/4qEbEum2B/HcQfg0Lm5SGn6biHysdpbMi+LsoXo6NsLBP6+/vwrYJ9RC1RUWehCf8PuT3VjZBxvlEqfx5tId+QeVD70mg6tSYYhnvXT1XVgj7JvNNcyOPzRf0RtuLpm4hxAgSwFQED/gDnQvuvlAOImq5tluIvrwWyMv+eB86bf0xRuNVDACr+pbFLIOdN/YEdstFoh1N0M59JrckcfsBiydhvpmHgsSNIdqtaUL0plqnhojhixDfJoSjiDTm1r+c1yIoYa5SOn3HTg4+y6QdjC1iZuB8xwAaqoUbzoCq6thw0UAZX8NVx09sKEi4Irwkd+BC7pOqAfM5ZXgV0mHAWnLs1z7m+pBA+kjR86RXPy6h0e4IPzBCCgC2b5VMpORnpyPE9szHoGD/Kv1utX+paUwEwh/oi4DBf66+egv21vDjYKH/szQbR3zUZ8Sdgb1jaq7USQhfGGzZ5MElaN/wkmMVQAsqNdcx+TeXiWJ0EPjLU2PfFRMybKFgGIsbMJwGoYvzi5LaZ77hHjAoib9zPyr794mYV4QAZzB0VFhJpBadalpdPjJ996Akge1Sao5rS6hcWbxC/Vboh+iQcxo362gwgMEw3cX1VNIeFSYqsaWtUgKXt4zQdx/TWZoU3+AF+TDdSrrJlqSY31GCGGnwqmrQy7zL/gEG9b8n+s5Ln5TvJmYz5G4ZtB2iQL3dOhMUFQpM8agEwG7qch09UwhUuArxIza5qqdK9Wtx0SpRgbeUYlomgPzKhLoC0mUGty4xvx7wPiHl10Hnfu7csaDsyS7aq59iGKup8N9VotbKcjxbihAAqIyzRxPx4Cf8cCiy341cz22oa0WzC2GxKtPx/FjoU7NtaTU7XJ4aEJZwYgHCGGar1/71YNsGYrmyFfWL7wkEfdVZSN9yqRxRd00/jTPU8Z/+n5r2ykSTaWD6+EVVeepxnkAZsXJuNbbE1wiTmhlTighLf+p7ZMAjEzh7ByozLpmp/GTYoujC3U+zA6Xqf7SAwdqgBUp+b2AbtFIflOELz+fLZNfC9+yBQla/oOZHUubpLLFMpK8fqWonUyYcOKZkhALOxJ/AVzIKlc5wfWJbWLBaa6qltGuNLweUB4GB6ZjkyJ9DcrXHinKJKqmzusLy29osTHVvyVqL+HzbfLJfBXSHH18kVRcVXU0xCKnTdidENSwEfdhwcA+SaoXEKGiGIv1lPzT2uwUBOgnL+y9NQ51XJ9sOBp/hD8GjUtpan1rbM/q7MxFDlonJhNz+zu3UqGzCDAIdQIzbzw+P6x20ZmmAM2CqpsS2h+DrJfu2h109Ac4SNdd6pfIm9+3bL7JpOJPkfCMtznDaVynCOo1W1bbaK1sRZAld0QcD8IbgavFy52Bka7eSnA0iVYQkQKTS+FQjL73vX4cdt9m3bT9JHSboDaY9D+ypx1gsJYfZ+FDWHe7IbXYL+Kp8yTxB3yv5hAmqH6OXAOByLG2Qw772Tabnn2lhRCj+547dN6+iTO16j8YdjX9QjXMd2aJReW6tW/2iUMh7pX05fl1/1wuiNeMAOdR/QfbeU4yvGU5MnxsiZv6vraJuJhE34L+6M3VuP1GpHZcw7HP4EJJXSUzKzCi9DLZzDIsrBC8XSKcVjKJ82dTgZjhD1D7MxDlCTMs8fAvPZPww2orybAhHrNaTB1tLE1rlr/1VIjJ9zBocY9AAm/xh3/MCHRVORifx9bYK6c1Ec3QbodxzXS+uvJ8lWKdgOo3cLl7dNEqRaX0uvkgK2wPEKTvmlgYry0EAANsQniEUHC5dBj82izU3+IlXILioWlZ3f9fYwS7ocHkTptGh6WIHSHIlNLzkbiJxx4qfDnmOw2CCUuEJ51QwRG8wOuT7AAiXzlw5pckFfk4AThSFVvv36F17faawRf2xl/Mcyuu++kCGbHwqyJuA3JEhfsyxIw2z7kNBgqJUm+xwAPn2yK4JcZhGwcXxmTvf5eQbSOlFBIHHWLqsitBGw1F8sGSVEQ93RmPQftnuk9ogs4WTvtx9WKldZs4Fjdj5bBhiWkmfQakqdKYoZc2wc8dgsx4n9YdboU7tNqX6yHaqX1DZlAdP+eX50jNTqv+6jfok8C5vuPaUiTFzc7WQ4vx3v+f2N7+g58bFAJMS5xS95nMWylcH89PWz7qm+IT9W7Ogg/15DFYaeNWj0tMKhvfYCc9i2t1SsfnD/w2/RTgpl0F8t19t+7PLEDs3kUqACFyRR/2nYB8ipGa9fv5/qOBCiQISGdqOAhSvSrAcrsBQAn4Z8zOPPQBJs3b/iJAGwxNLbYcKMSQ/B1ANLfK7jT47TKvpXGH+oo4vlgFuLBEHiwF2OThs7rI/lkNdGeyVD5MvO7wwB/VWm8YbJm4KZN8Pmy4AfmpfLEwylb+MVuG3jRUJ9SExLj/1cG55zSLdN+P5Br2Uid1BAZDZVwZgQ+tAcUgGBhYrSwS/z4x38cdyMznZArGZlDI9iNqSIvs4UMPVmrH/jFq0Re1GqDBbU8HA3WoHxTrodl4s5SNplKdSKvr7VTwAThfkgEzDmdnPICRCzgfpRjgb0v3PkY/b0XxYe/iWIiVXfOeg10WPxnG8Mew/jmACIdeZ4ZVdDBLFHuTUgpo8fA/Ff9dCVzNxO7pasEa3RZrbOMP4KZ5emfFfdjbW+fUJZrdD1nnDlhi2C6rPmsdrgkVEV/W1zM8QeeGHDfljgWCZ3zPM8GyyBvcAy8lKHxIoud0m8IgNYm5lJrQWYTIYqFZfq8Vof189q76f/y0LzhxaxGifFKoGH/BMV5/khK6pNQGweg4+Rj3w153NRTq0zvXG14WnHByLgMBICLNUWyQgmAK7J1oYTBT5G3zmh/+p0/UB4rgfLIGdv92RGnyujV2QIqGtgFyU+d8oijq+p4UtDfsrN45F47PxNrv+BAz5ivMrhoVxciGW4EbxFgADFF7RNvVaYCpoR901RenQZPH4KMi0zIu8+tI805QSrDDMN+NXQ6DX4nv6iaBirj6UqmFBJQRaqzbCE1wLrrNL4ExUZAM/uDO3YI1HGBk6ntDbxu/90vHK/sLoErKME0owN3gv5WJ1Z3LLwsKrpXRfNcmnTf26iqLxvFY5oZxBelsgnpzoERMRGs2FgnPxPsxdYT7aSQg6GBq+S14Cfvc4Ln8IQq1oXuj7WD+pPqDxCjLskxUATZGX17OcGjI3fXOazq0gvKqdq4B5Bjqj61gD2gUr6j6gA5c7KGXDtvbYQFkhQZsE4CbBocW7FDJpXEu2ugji2jg/oqav1Z60blFcLJN0UgM/FtswEvqpYh+K6hQVhEIXfSTXfM99ZKFQjG/e5z14vY0F1clFd5jy/N0vHHZ9NRCrWSCEFjKC6NFPCs3O1fjQ+2B7xHNWK+4TWPgPl7b+zm9K0WfmshMygi4GMj1lgsYETs/oik3gvfu3owTMDOTnnErTMtS3Os+qSeg9NL5EYveK98QJtue1Dif4O205ojRiSH9yEJK4r/O9MRR+4+Sb4jCAEAXnL6GP+VxYF3Z9ocUG3yoJ2+pfondnTmdZmLuunQRplCHejFLkllOppsM5TMvTZRDZovWkOvVUav8tRNqfwGlzjJobF0O/nhH7R+0PmEVNnQCSsEskD3dVHrnnyJQkKVyh7MrUYie3aLOQTShUx5RuoIbSHWnj3xBXVbIMK/J3f/wsEfHouAk1G0Jps/mkEQj1gncUIKS4DLwR/yb6B9vVPnxD1vWSX9J3+m9pnt3sICbOfmrJ2oemvvcFZBXfsMdScWdpB0oSbgmu/Uh4BaWZe4DS2TiNFVSj3bAh2sRiB4InCe2GIf47//yGYveYRFd66YLuLdbcDFYeQvI6W346IZYwDiZhuuOeDvlFyjnmeHhS0ZpUaFCNCOYlVMAN7WWp8AcHeOBXBKpiJn1Yakmuwt2q9jf98eJ1ECmQdSngiRrVcNUsB696+CJUxLIzXJmjF5sKrD7cs42+zfaFeNRUGKK+dglzQQBUvlXC3m0Yx9SYe03kDn5DkUfVJiYnNWsHXMDY94Ag5jc4Ze8rBLjDzIhNbchPOyqknQ0zk7eZvtha2rKTTAvCmJqG9gcZ7WW7+JdSWHapverpRTjTMl9AwrbvXLBe0L8ftAuGuJn2Ho7c5DIwdGn+4mtPMcUSJc5Uf5E4rpgwi9UBFyMS2naSrO338U/p9cKr4mhnzSFnKs0qYVlMyBQp46K0yK5mhFvCi59Xs/Yh/hT9mVbiROVcCuiXXD6Mq2nWl/8F82VDmPirIIVAYX9K3QHfehr6cUkIYyr863vWGH3IuGKzMwj+JLHtAAuqd6EGpL9Mh33XnzUS3FIv2rdNaf66RnJXKdI2nIRWO50La0QGejfCR8saovtRviRvVbPbPT4L2bezxMnGXp3rygYP57PcFkVQloFiNt5H6qmAlhGjcb0X4Qb1YsCmTfn/EPH6txwNoO+mt1YSgJIz/Oe5YDJCURuRExaxCkBad5y3jRgZSR1njBx5hlluqRJdVltW2e58d+OKH/iWv2hER4kyB/GiydgyAoSdsL5PavhQc7PdhV4bjFwctKSuw132yCBNO+xO7LGc9gyC17bd8+9b+h6FVk3BoFaGLmeuKjG971+TpA36MLZUx8toZIJAPeHhgPts0UT5AqfqeDsmUy9BT62pstq83xkmn/8r20vE+vfYR//pz+erGwiJr/2fV9wpRqyxAR4+hJhXYfON6NU4ZYaMT/57sP9Z9MCCxF6Uf1YQsVV9I1ckfWdHhNKhUUoo2xMdAVvXkD4cCUV+VPSZSZYMUVdoWMHgbn7Uda0ABgfA+Z89tOmPfGN8PzNYthHofbhSVti5NPW9rjM5bR2w00Ro/qNJHF5k5ZJad5Coo7Ai7MdtnO/xoy872cIov0UJFuN1b8rgOT8SqPI+eiWlvlphDUb5qhozLkgOO+sukVom7wpxXrE+dQ9WggqlNfRZeWVZJTxTzsBVlCEqCXeCBrYzg18wnymJ2+tODJZSa0Ro8rMIPqfcEJvt6qO7mgwc7m4HxuAYKtbQ1QcTPsSQPm99lrJM7r9tkuqlvvlSG7/xzfHF3mt+0jQIwjJNIw8dPMjpxhx6hJCt1vpDhL9ExnbXEpgw64nqqCnHAxldoDpKV6bDNtrVuMb2e7GEQxpRM31a9pkmk5FDNDIprxe2LWYg8jsCez6+pv/0uW85L/OXMpjIaWe398blq6k4cxJ3kyXQaRMCjhgLJajm8usRXN55SoOf5ZCVPsjrniMS09xFApkQ2N5fxRdk5oDehNIfDdx4bpvgldTCeDi+o71+oWagU3frg6kjnl2rDVYcCf3+50OsEbzqa8Bs85kvQv3+hZHYLUP4LxswkGbzdfoLt2YWgUtlq0RWgi4n7FVBlitdNDAdwxQleL3Bx5jH5zl+uRZfk0VfEZkWKVQBnV55JY3iSl3hOZTEf6KrZxuQhxxuzBIboL/qil7h8A8Fd5JxqGJghEICoxpSV/N17rJzpjF4r63Wl11JIwqQQYqb4+VryGoy1zNWRto18mN3F+bAVWyPLUlVwDfdyWUOP3r3gSN6I6Zl1j1uOJ76Qc3xSd2LWQfmRsCGvQXqMBWySqQ7QfsuDIj/EBRJMssXVxdXf3XZJ2H+zXkLuJSIy3yb1ZYHFJ1SxZK+iKpgog9ui1mBwcjcYW3P5PMhoY3P/I+7YOJE6Aq/56f3MC3sy8rbi9RTNrATIixQudXLzMdBONKEGfC7MRGKmsdvhHjsDLJp+ZKX24CMMMESsrDNAXysigdoJB6qQekI9XxhoFjsxDCrpcl2KAxeVTdrRCXIg5RAmdhZTRk25rK4EarOQ4SiD3oPvw1DTsaoYxcP51npd6b2iRswjcpDpgfGYZlNVPGJWhI6Nd6vfepvPfdTni9XsVJbQapPoi4zbJDyE8OkCqoI+7fUthxi45y4fG5k+15ZtIK8LvAoIaMEUlr11AkyvD6pzTNT4aG/zm9lUfU4Abi/BJLxNrwsqQZkJ/YU3OaMCjrWRKoZK2dg7uYToGsFj57km9N+weH50g/A3AELy05LHlYfKPvTtZlfn4HLDkxja2YmZxrcFeUpv7zfT0g6i8CqwbudUkbQtmVn32Sf3mW/Z8xfFFuaZd+XxLYQ1aWuNzJsozxhAULZoRRF8H0iKJMyRvTWCa06GtVm3HjBy7U7m2UcPajWe3pbxIgiSsXQNlPs8icSYzKi7i5tC0ohq95+5txGqEvhisyPLSTvHOh+dDbFC+IWkUBXkKaFOZAzFzLpnorxK2r7ZQnxfWKq7MQcH+CygySeEvkdTW7ZdPn1POuW7CuleX0Y2z+amypIEaA5uqBc0OO5b01cgaFzpLgqNE/qsvwnAx1r70dR3LvTKLUyI4BpfPg+pnwXCb5zvjfiM/bkbfoMUNd2xCfKUZbdLq7UegaKO8Ot7oYYVpWRrewuaD8k8EjQf4MddcgxIqmk8rL6BqG9rRz9RHxVaX6lFcG9MnS9ENFP/c6ULoJa+xEwj//eElGsDAA9/ToCFHH9U/y5XZLCCStofoB7q5y6EbTqunAh/uoc4fZt6UcqmPXIfIF/Gdd9ybHaaqAvaknBE1wxNOK0TnTUlIjUkRP91U3cg21q3A8oQC7l6OjudayxQKuGHT+QjZjrQKqCh32ve82+wtPBhGLYJlxTVqiDM1Q0gCtw6BKqZQxYbheUMSg5hLuBf0lUa6sUDXibojeadJ3hOZEqRMUfwiHxDIHm2KkntXyy+P6zNJo2DvURjTSe+AalJopHlQJ1HAae0W7FNwzS8xUD7tFWaHBivSKmjuCcepmXWEZ6T/ii8kG1fKHhrAtlgvq87r6dpGhMwftyp6XrsMhhVWnMHHojyQ//ivRflceCMbROeoD37VUp6aBWOUqja15oETQ2hn9jGW7NZunetJrKI0FC2i4LT3UDPDIseq2t/BeGiaaR4Se7+XqrkyHwDYp8TvGwntFdUvSMrQpcOvEM8rcnpYJLKkUWUXhUeOawOnKUx/MVP7Iz3hTbXp/ke2X+dsVSPlv+XFqjIa6m7Ul9vUxJ1+73FktuTznH/dBXk6+li2f4QjNqhaygBYkqNvBpxWSfODAfPsJPGW62/P0VRUwMAFCU65u3LTV1LBu4F1d9N0gcIxSml0ox/MC2Uxz3tH5rJWL7uHqU/u9QmkHl+Uz71qkuOgNZO9RECnwULxWFX96fsvlzkP1o2h7fWPyYLM2w666CUnyFcQHIRqIr++uxCbltZdr4iDG+XXibRG95S833F+P7VYqwzUg1KespArvE3FWqRC3kuSF/+5W+tggOZXYfSnJcaVZAlHsei4X086H8ynWD98Ri0TWefsssJucHISrN3Qulvn6n5v17CoSfDLvTH1gptqXF3egFSMYa+bQGKyU5yO/FoBbCW/YfOusGPIw3qg0p7aPc98/2H7XPFdhDakOnVhYeVyAXdvG40jN30w7POsNwsFjngbo0TaIhCzfUJEXSlbGHxnt1g9fQbtWpqvWhiEf87gjRP5VdIYzoy+ujGqtw/t3XPpy7/FpHfvwues84WpbTWFq6nSVH9uGBMtkpj0BP94Xf9s+4+K3WyhNo1/hgpsLWePwP+YRDv12Z0r1BeID/R1D4Nb9pfPYL9yFK0BiFE1k9xe+dBVrfPsbZ8TxRKoY8MMSgZ5qQkCdoyNzSpGzPlLESm3lSKr9zW+w5iGNqHk4u/v50P5mufjyB7q39OwXUUYXsKW1NIciTi8jz0yAdthxCVUF3xHU68LesLOGnO5rOi6DhwbgyJPJxlMaQ49IVrx2NYUhzxCc73Asf5i9HKnWPuxVD+9olSmT1T4cdTikZlF/zTB1BfKiQDLHjhIvdtkyN7ojCSsrg3+esod5xlCiImTLa1TFU/dHVibklzarTyorlR9h07UHZ/Nh90E17HNRc/JPM0C0/7GFa2Joqk74odMjkayhignIqU83epGZkstfcDkInACvUnsuIw2Qeew35/Aw3Nifbc2F9jl0pYnZvDnBwpJ84uF51f4U6sr+bpdm/uR9QgFUf6Pl9Tbo6qdYQB5NqbbhBQCstrwXEWLdHZ/PY/vn+2HNcYOoGQJwCnHzzZsIY42nAF+CW1ndLAqWf5/7LKG2idVCFfU9ISe7OVjBOL58/nRfQT0odkcqe3Od6/FqB/+YqizKBmsiTL3WRCIY6ZA0XuAxRWTv5qe34HYUgnKwY5rZ+YLHAHDtWgIwFApEGErO7Ph0TpNXOPZxDKo6JuJVml+nu2i0p5npe3Hs+bv1Cj7TI/M41JZ7/bJITFXBH8/oOnwqU31FpZn0Ju1JDu8OSoYRJtBKmQQ+/ZpXh28lC8sSnf/KVBFZuy+5/pSpMvXC37omlPoYNQh4eqkdWNNxkuEsuXJfYM4cbJzdqyZgLqoPNl0QoQ10wsGXzzJXcbDg754olPRnbnzRW+aFdRwOBvNb5dkyyPYDnFP+FuzbZX3kfr9tagwtdBUabfWuqBek9kM/om/QqOF2IiKnuv03FDlENswKYIIV4BISAUx1oxBKXB55pxbc++c5OholnFyqbgBerOkYiHOu2ZEZPLMqQ3naL2oHATCZ8TExHvjEThHtNRkhaq/x04nh7EK1l3t0ze7CZhugRWhn6ck0Lq4kZncDMZQMENcw7h5BPklnOs+47EqWTfjmYruiN8dMGXIqY5Hucr6BjMlgwVBW1M+mkjMhG10I1rusKgZfy+6q/urgLQlZVTPYEcVxsRMjrm9FBNy3k6Z8QcZZfdaXgFkDd1MsgFZ0MsR5AyhewYkfshRHC9ITzYRRbzp4PpUQR/hmgkII6GUbRRNg77g4uVO2mm5bxpm/imZIun+mNjx3l008QpGuyUisyt92BNrstKzjSMO06HkuigB1dKWDKu22RPl0vJvJMwnLFdivYmtXZMqg+C1zMahPBJt0YibUMcw44tXN+0sYthE3ZAJ63VaLygKVx7vHB4MHEGeHeY6/cYUa++bfptHDAwhAJqyorwtZ+ffEPfYQtxPlD/UZITe27uALDgXA7P3PcD8qzhR90StE260Fl7huElvmyicQvs017liWohDbC2yeeQjtU50jLitJG7sCwk+E3lav6ophmL5w3xXAfXwX5r17uQjQJIPzZMvbTmhuHNarap93BH4TDkBSJYcjSaeMjzwsGOmgKjb7rYYb8oeV13NhHMKIQgDM+/DipdzJqdXjpJh+njmgAsHX+7gVCYYwerNea8PColrgOH6VbNYXW0uvcqBHULtcAUxMchFiK9px2h3NVr2+lDt199NV6qpLghKQYVdb0iH+aEZw8HjkWue65FBp73YUsimMBE4ECjmWjI/49bDANYZXjqx93SYfH/TaGk6jIpgXNZ519nSVFDAdF4RgTWaS7Yf5lM5haa7yihEk+bGDtpYyjxJzPUiDM/9hbMKrA3Ng+62O18fxT2sNvKFrObVmrM0oao81FlcdEqnPDlmKSf/UicaIsOGZiBqRKMsGDF+KVyMDzJtPc8YmL7IXSovHIMbun9gx1NzMgYXp5ESarvzJIthhYFcD7AImOufzoEeKlPH/sWwd3arbbm7k9EHEDaeh7+58usmYt2YzmrEcZW5R00ReyjDR8eHDeoDggd9ZqZyqygE0NjFuPtHZaOCfSMiUjUBSb9Nk4PsjVdyvRG0jIPE51wqPLYy3hBFp+FiPx2hYwmD48S6lvNdZHDROwwJ8UcIPS3aQBysqBCilCUWit493N+JOaY0Hw19ypK0aZws9qYEeZ8fBIpCyfK4PlQj0lKI13iwcop45xSScvnE+izJ/uSr3saiKsc0GBj6BSV8HKl0hHSHhRjFtyi/nlVlyGQDQlTgT3urbvEUMSU1I0aH2GDxIVZolTaaZG6Zw/c5PW7oee03mV5S4zoPzLAYJbgxMgb641aC7OzblUR0Mz42Wfrrf1tFjHEvKE+816JL5CmnizIBWoNiF08nGJ0eNuAhKCNsZHKh+bUkz0k1Tg+umfTX8LGPmmDQ/CJMgFXJ7ml27hQ8K9gP0bneKJlgoTO9ljDzfMQu+tItGWqIzhgrPK5qe9FJ+r4hFeIUMOGW72sXu65shBXVhsf2u2cnNozKkzwZeRFvZ3wbR80wplhNCoolqNaajHeUTcvNZ+43YCpEvUhXxKRpGb7iMcUcZ0cUuZyR6BnNB6VwnJglzEl64wbElOaE1j+HM5iLDkeB8xLJvre3/mWf+ekV09/RUKiysCchyuEN6K+S1udTBSSpxVjK77C1EQUheRz1K5/PnnNfrzWFU8PTMH5CriwoPln8KYHnOtckUQZ447nZDUXu5ss654OECSaU+fFAlM+16PsBpNog7IPOi2y9DfKi7os08tE967piidlzictOpAlVZvxdxBXePdMtqg+TXNwWZSD0l/nGz0IHVRIh/6R9yzqHj+VzRHC7AY0Qgb1ximo3AHE+nofng7sQj1keEb7Cy225BxqdgJLrhLL4XvWZPBw/7hDjIuPzI22ZFmB1QBLVN95UcR5yBrkiEgJRCA33u/LlTugfLBvU6BqnLAy9aKFoQEssDv2+byLS8uNCxEd1Au3Dqu/wRCPx/h/BY+oLn0SkOaFKUzulWeHi9ICjaTW4hJqaKXsvbOBDW7iZMIt/NDz3PW6Wy8ssr8clkg5pn/Hhh2bgiwaGctX38QYxEU5qS+M464XFVt7cHnu7MZllfqzQIMaT/EFAh/M4npy4tndLa9EqMwQDacyn5OR652QPCSKlhGjs6mnUPb+9Cfx8GjQTVuHUE746qSha2dm0Dhet2HwnWqlPyFLU0YaDTMvdaAnEr2IZBhDAA/aCa6lWS5HUSs3Ijsv+CYYA0wiKZSYwUR9pxsk6QJwWMw51swnZmziolyW6uJvNzL63fx8l6G0FnuKs1RW7lA64OiLknmd9/crEH1+QBLxLDonGb4VqSYuoVM2WU1VAm6XOHCMMzyrL0pdiebLKyb0gvP8/MzCSwEHUXcH/wUdF1q0wYJ5fsn3vchiHoG9y7D7/cCPWuASytDaqbSzvfe96sRSiKyESvgd5ek2km4JsyeVc/r6/P7Edw/n8DzJy/0oF8cWTc0iAkApsdqjf/mOhvTe7rCsOIkXfKXpnCr3ixPAMHXYO3KwXF/eO9jEnCWwHULbzaLNMQ5cS06qJb7Z32dFPxtq98yBmZT1Cl1OhCwAUHzvqXy9Wu/BnkLg88+WB7uuAOaN4czEslJzp7vL5R7TdWqpYGsmGs5A4CQ5ggH/vRx7lDBXKFYcYiXZ+XLlhWCSfkppn5ffuNHjaUhgLLpUyE32wZu3hq83V/Bt02HpQ6GEjihWlBcng+uix1XVVBh9UsnW31ncK2zW9klJLK7rszoJCrqtAn22I05Z1HAvOBHvoDI7/Oxx7jv0tVSXupklD0mmqALqwnRsWuCI/5T8dU7j9Lsacse8TWNSzls8z2P8iCZhbYEIszjrnc7pb0KQBhN6R4SnWyr00QeXD9h7evCTJzwd+Wl/xky4Hn0/sxihmuJPm7Xula81gNTk0kwP0S4EXA1Tf0WMFz3Xz/1u9QZSUGyP40xY7dfn9csCWmGn0Xa49IlFMSZ8nrr5xlNXt9x40q8Z1uX/PhWRX3jj5TfT5jPC3+wCfX6r54QXGqRCHPartniJ1CxBGnEN9OgfRwEGPTgMqAFcemhpwszH6Ik8CvCXFOuW/gpbrVNdyb6MhnhtasM4/FuGSM03k+CfQ3yWSYwIAwIUAQd/ZXiZ1nMNbMmPA2BL8HuRqZCmROhTebcuLU+NUIWxT30vTc6lG40QoWpBh3xXG7vmqLI7VBReT3ewIgU5n8R3X8dB66jVhgk39VTBlJa1g0xsrwxa52KjsXPeLPP9sNBbkooDKcNC/OwUoSOPLGVCbjdkNPzSXBOhLgM17zrYVnfmpTJ9c1oDC0Jv/t7jJmtqoYQuVtzfCPaBNuH9sEiPCe61FaJvMifvHCiHfX9TLyXO9EFwmj9/jkbE74xy2ZsbfmL0QdOC6z8x3E3myKSkTeJS5z+zSemx0rnH+d1NCeA5up9Q7uOqBls4Nb6ym7t5o0XAzmqWJgnTPQrs4uxh82blCuGacvGZgQeJwQMLii8mm0a5h37zrprvUZTaD6SeIrWXMnEryDBbL7+7T7YuvhMHPEctXjZz97rz5+V+pTcrX0pNY4VWKGJEsSsCtNB5scuQqGnwtNLPrOjy3t290Ge623lnsgntuexokgTL+Fs6V+wOaVXolbrG85z6FYZC6sHYYHxRnDyBcICv26GT1KP6CWuBUSOkU5UF707Ke+SVRkCBwnDLe545UeVRzxbN8SdBRAtsxCFMMW/Xivb/jZfbqwMeBksECW5RZ1Zs4R8K6eu5uukaXQDOCpePp1cl9tSZZoSKBC7cLKvVyzgQZ/VICIlMeeaHjdd3R5moslAfLhZA+sYECJ3pbGplVZ2u7L8oV5MB6WSvHGWvqwG8UXVcPX9ZhriXJVD1W5ccXEDgFXL2ZJBc0N+Ja3qv9JEQ1BeUocXDcYA6ZZl6XzureT5EX7jHK9a+Y8g50Gkhq+dnjMRI0A3Ujqpar56V/E5Akxt0AIrDEvMeXyKXj5c10CXnvMfQAVkd7ZwHOM+8FuEXGeBE6iBI9WE11juw+GZdOD9RZWJlMFd+sL235YU3LyDx//zkU/xaqd7b5QE6O+qmUwc4hqSsutVN1J0evazlBJDC/uhua4gd32ptoVU64+ZPeASpVZkPHnt0gPPA4UsV5BhKI9yVk0IV3GR1Lytvq6bsDFJ36epACNggyC+sjYAaM3A+pRUaJhxwtzFEA+wgKq+QDBeDSRkXyfFvTq+Tb3VIiGusDDkVUJhckxGcoi/CN5/VHcrdRFDISMogRYAX+vHCGvGzAgEMKkajNZGe0TVhNchyTth0FZpWfVIiYbKgFZTzhg+PWofWkQUd/K3b+t3T81hm12WSf+fUvpohm2ZQyU0QEhm1rx6IhNXPXR6Es3NNPl2awvCm9JjfwLdHE2tWSjRrvIxcHi8Ed5EG0OT9AsCvI4DzPjcdciLXBQn2Oz1HbYLF7HnoQlgp3V2G3hXJfHVdNDCBclKH9JAAqcVFd9tqghPxSMQHXOndRUXpYow7ekyk2merRxvgFcWFdf/l2jT+vfWGwhhmX3VBjX4Bn55pgUKsYmmZWDIc2FEofUQk+fKkBVWOOSos6Z3yxrlMIx1/MLdeiVVOwuVfRIAbXf+y6nIPOXXggNPk2H1McYec5HE/ioK4eKiZGlRukrtnneEYcukLj69wfZr5R0ymtzhrE7Dm/lECbP91aNCa+xC1DbZjOU1okv/di3jxTvhq+f8zWKlWaIn5yGlbaFyYGakSfcGFXdFqm4AnD+CCCNF0maSy10gbjlvPINrMhp2jhn1VZrU/+fIpCXkykSNlFq3bbL8ox5jzZ/voEbZE+mSTmXQ8gcxEjrtzfJvKvIy5Fz/aLJGEKlaZUJMYZEaPER1ax4bppVCFDpZgOAUq3uRnCvTJWem3kRpdsP1vNpJjYOzmMGtVF4eD9sdfJkuLA6xdq44BtO4eXVz35Txf1/nrn/XhnYO8DfpeQi6Ju46L28BguJOCgQTvzcMgsOytLjlG22kkvdsSWFipyY+skw5v+Wt4PyDwXZjYpFEo42qpjFM8hc2VODm+n8FiU+CzJDjIxOhGiD98aMrKnqzjyi/h0mDjE9s2BIAPnwHz52xUZbtGUh9kp91wHOl92GUeFJh4kI8rJuS5bjSlS6FZtbBSQ+KV0PfZfIHQGh8vq/6K37GTNzEdwaF8D91f9fmhmWqhD7LUvGtxaM+n8VLhWeBd2rJ0rJsmKj43DImFbjsalVWPpfSiWWoUeY1ev6ZivULKWx18LlGj07bgdXQ5K6BDm9QF7RK5zQ1OzhakT8Q03dwNnOg0uWoDBHqpZJyz+pAQAAxBAS9ZVHosy9k0OAj/7qVotonCPCoBJuS4RnIYaRIe0mdIj01XNIXhgWfoqdU7bKSO9Mz28egVaWHQTqjm+UT+VLJl2YbbbJE4Vt4IA9CLNbG8iAOmz3UJl8YAVGSXPE+fv5zP+CAP9IHe49EbyYyOygFAGpJxDSyZSOIKDQFXHAOU+rcQ7OsaQvePFxPGFCJX7raIfDkeg4/kNb3FQXcFsIUj9M4cELM8Y6W+RD9WTIzxch9oAvrXLxLIpAG9DuD2DX2KwXpuAHQupd0BWRaMw9IApAFiWgDf/0fCSqRjawSBh+TDqL13nWr2IorOaO2Y7ef7wf0QhJsmvoBKmj6wyScZ3SuJwr7f6oAiCDnmcW1XZeEFWWgmZufDcy2+JeIQXInVqxUop9gjyXocIJklf4e+D/3Xy/1W1pQERvV1cNwexFZkquvvaV6NL3dnQlG8psBLm7auOBXrmEmtJkQNgfTWiTe2pJBy76suXDYrbOiRG7leiMvE+S3RT9u53zJRqZEeNz//mrGsfj+4nTSGgvgqmVvpCWymQS1CeM37pRdVLW31NV+UH35nl3gCMiXtpJWWAm0ZqJpC6iuFr7lx616jnelpmTriIz5BuFqPXFJth0C+CUVW42zo/1KCpsyl9Ztt6FhD457EDyyTz/FSoYexfAZi9wBhtWI2PSl4UyjYFWQtCdiFvsEjrtBSaHQWQnraGuh/IqJheB8qWzfv9BjtOIytZMVywUWBYgH4gr7mPdLwWTyhaWF2oukOj9BNPypWnnTB9+phUYiXFaelAXmTaqCIfsu/hzup/3+kHb72/0Cu+c3v4LLbG/K2T6yBh9W0O86kNkT7uIPL5JUzk3DGIBe+bzBwUizlMXycTYQ+WPrlUt1bEiHaLfq2UJh1/4DW/HXYEBGMWF+cDE8KmCqT1OMZqbyXiK7szcy29J0MQsEQd1rsr5ucDA3EUQNCzJZ4uuNydYwaZVYmdL99BdpvDsE9up0BgoiY7QkweHf9/wPw18HOUPomMCBd4Y9bVFgH7MWNPuCv18BmU0xsJcnTtL7ob8iFUdf714rrh0XMK3k5cPSVYauN04QaSN+tfag4jFsovJO/uZG0mj5dhPytyX1Bj+C0wr8KuWdLuX8h3rKi5tUCVyv4gStAXbQe+sdRO/x+T4k8QNoDp3fX73PZTxNZuDupAI4Z+M7Rqv1rLhP0Rkqb2+StiO818sMr86GcbzlpOoXFBVck+kbfaCotJKK4HQxSQhd2ZDYK/7PBMLTBQD3TnxueZgNd4dwhkyQQUl8cXiMFcTwCZQ9Y2AnoGlKQcvd2Es0RCULi3LTray+2rozthNkJVRlKw/Qcybnt1yKWiWaTmjGXgw59KSBAf5wG7cMJUIc+YTrfmg8qz7sCOcpAJ4gwOlm3fxeFEQtbYGe+DPaYuunwp3JtqGeeFfoPCAKLyrF/olE9Uidv5OFhsR4ZKz1riRYmp6/kVl8yr/sthVUmp3aYUAZAhGP/IDKAOM6lzyBLBELBb1RRubxsXaqmyZu+qM/+gaqaikggu5OrAxviuxDVujDuw+nUhxi4oNE4T3sVl505WL53gFy4iqIcghNWZN0/sOwJlUbM6kG7RqhohoANxc+43ezb6SBcnJNQIQDWhLFJPQxwV+JmGBaCFKjXanFPNghcbif6CYXvw2MdwX53JOKrS4jkfhKE+GEbeCfrkknpaXQfuaOzF8gmB8qUriVwiWlCz/0r8rcRxQE82FIgeW8AUhrdq0htgyhOFiT4zxE7vY+eTAKgJTvcYj18ZRAnzEwN43vTC+tC3nwwwdoizLxMnMaxu4o4WT+1KIwUTnPWAmaX+Ep5cRLJbc1LO14o25uTGoXFcNkxFWA2OzqEnlTwIc6laX1QjN+sq+juaRP0E3Xh0f94gG+6n4322emX6hsXUWvf3VF+TQtkcxEAx1iR34g5CzriLFSgPAFluM0AABAAElEQVSY/ZFbA1ZKkai0z+N86ZpVY0P3SUux5VFX7WO/eqjCN2iIeqOIAhszzFJUJtf2LeSqtKay0j94Q+yh/nj30NM+lWFiF0sPplr12hMtJrev+PkyRPzl5zA18pltdslUE/sfhlMWaDQWx5rVLUp5R6jQv8jQkh//EAmk2ErhLtwJ/Kv9DpGF4pmAXNkLdeslhQKL4MZa82N0Y/C53ecsFgVa7q+3/9jnaYkQmLa50TG3D48RjIKVBE7MHP86v4GgVsuWO78BDE/Q+3oUrsGpGyQzKNmnT+xz/eq7V+5Ah/7TJz8M1ymH2CQwByaxwDm30tBa5dDNNQjyD/36uUzLQP2VY/0N2Q0KPYCfEG2wIn3nsqQO/q9N+Spmd26z5WVclGmJzwwrVskMQZt8pKWE+7RgviyymMoGnrrahkLlyOG2tHB95ItjE6b8KuyQf9ozSnswcRmEz5SbLcjWbDWTbcsgHxpxNdDssxRoil8F57VEBWuBT/kyUsBlapWH0J3UmixbmSi94d427wKIm3IURpRVmN80p8S1n745/B5m7RMgfCuE+alwRMSqhGVd5VM33Q8Vownu78ykGsNMCV1xhfX4Vuo2A+WCZGH2XDpILpE+AOYTV9G8G31RMYABUtRX0rs/aEvsSflfnB3e489/IIwq2a6VF0McvNlqUGlq0x1WcokSREaDItSHThHSGgdlWaJ/gNBN1HKwWNA/3OyCb1lWkJ6v8vE5EYnp7sYeDb1017afotorEpCphhrfdoUQ+8gVelbFF0wz3dWxsb7cGyPulmK4wswbHDEsUu43beSSEXyxlH9RyGQaTZKX7votsaJiTQsK9AfusiBP9SR8YoRc2+p0OvdsEDC3ybvVH9UXkOJEuMu81ecaDhxIczp/YupqDfNyohCuPLNgTD9aBHKN4K76ySHAwNNnf+iorn/tUHBKPS2yuIPCp1C3p5jr6et79/Hht4JMdi1yFFNgwnKmNjoW490A/OsDpUoiGzywYxjc/1F1FoBa3Ey4DlYoLUVKKYXiUigOhUJxd6e4W3F3d9dSvLg7FC9ycC/uDsVdikvu885+/PfenPPtRiaT7G4ymUwmk0mwwAgf0Uq1AjPXGRuUXJjp+R2rlLWcQpbK69F9J0/B/ZCWeYiJy6W5vTZp2kCqXItq9KFPj6AHJ/b0y7EWR+uHsguNBf27dEHJro5FRFLoBjYFxMMsUdR+Ztpwio+UBWPWiH1K+bcLZ3konZywk2SyprulDXEGguEFfkrxeIaOto3LhGjbagtlEYVd+E5J7jVww1fgmyTdA5wRNNqw/7Iz9o2gJmIJObr3PCOsa19eO4dZbGxMwYI2HBDS6Hhax7nje/sjRzuU/3VeHUvOqpP9BAnmxSUz1kAhQ7kGfMopQlC2ZH8I45u07J4YiLhvrFkji814KV1y6JYG5j/AzmP2Q9WQoZRhHCeendi8pskA5/k9cV39YZEsHGXy0HgG6/VUi6cDHCdYCh9e8dxopjuogZZkpdRBZ3uF55gll3dxZl7WZgXB4iAkzFTuE2IGvXFPZM3W2vlESsoOq/aoGgYgaKVU6K/JBUE4ZROBuLAfGCMgci9wYyTW1RNf+Sye+/irDU2TS2Iib5SYoLbPbgUkdPpqt+aGsa6AfsPcTDXI6qeOoirDfTgCH4U06PCq6xDOfOHFvOc0G8bRayFTcRqgTtVJyBVHZRNbBWR8V2/yuUPxJrCDUku13i7q297/OvWywdvlEhxNS4mMghekavTht5x1k5M+ShQ/oZXAbgyYSP6DT/SUgNj/QgTFJP3K4kFSrUTLKWIKVzi1pei2KpgiPpf6OjvN501jmteviQBUW1PN8yy4B1jxuzjkiyyIqj5778abhUWoMy5cmaW4VJbK6OyoxT936YNw3TRGssfkpfVKLTC6XWVimd7xVMrFvABtIeHQb+hP6w9N/du8vDA4FDb48W64kzqbOfOAQN8MIdNHltPTRbSMg7jJU9E4V3yOk3HNra3lsg9XEnOiyHa3y24iDraBAdNaOU42Y1kjS5+b9xTbN1tTsFSwGUI7dtR0Z+yVgEtwEvyBokQwBn6uSNZJDCmLcfUUPPomp+DcuJrGV8uyNIzlX8FrXWQ15UIWfTNy1w1yKwZrGbIDNyd2tX5b39kqXMK+tJ4BBiic+1UAzlZh1AUNg66f+7bvaPvMLBEQPCRhITP0KjEN4O6MIA9vrY60VqUI7XPWeKPtuS4xQTau6ToOHnK7DZ3XJb0EayfFM+2vceRoM/MSa8zBK2PONJl+3of14UEGHSxdMhgMTRFLq0eb4BAHD3lJ2lYyi4ZXQw7B3JJPenZyY9dAU57S57h01AvhSY/5fI/P3YIELGswQ1Ek8dPV3hhiu/U+d+HLKNtarF0gk23uB/tW/IDtlokMNLTyWmJBCNQo+C6QnozC1h9kanCGdQFiscC37utiWsJd7F6fWlIJkM1+drRumdQAsBoPKhPoHiF0jqpscY8+VYuYDaA6QOOtcOLyHkxWCfatVbjBGWji9aDustMFXLavfXKTYIYxeC2jcbVijtW5/YknrmrC8uOlki2dMi7aKDjLDiNkQfRO4ViBagGjNYmaq9iy8RGtF1CferX93+tD6jRKMgRTjVDhpfayp8xl2jum/XztEzYItLXVDgFH9SvXRnvAu8uokpEXQvzMnTk9Ha39NmX4lhWLaECaGwCwLU2DblIbByZg4MNq7KcPY+7Hpq+ou0zOCEIcF5SPpdLn9yC8AUviAEkdf7129Yr+ZMEACDWwDzptpTl80EHbCSGwJ6blhUf1N2RP5YWXqSp9++SM/wKDaUROZ94QWCYdx1ha2zv6rLR4k+Jabd7R7c1kEFYX1PxY40ZEG5ELW9bCKFxx8ODtxiJ02xlgZfRqYj5Y4IM+5RL//qjUGGWgGKe5yEmexfxcZJ2Boc4++WSlWwoX6kgoOPUlLH2wQr1cNX5PPO86cG3q8vX9TCzP0boYrptrBem55vX5Y2oK7jbAvF61FxLXzwjQI07mjDI0BZqoGvcR47+moUyCFjPa7UBtkoaICs5O0xyy0fAeuwupGV9s3j3a5EzpuO6Cph3iQQNXf/O3y2LYqK6963LCdonLfc128Wfw/RZVvtm8LAz05VAyMG2YwW0+yT6Qz/yin2FMccUZFS/Y+FdAegupifpTK21ydfkYQoYmum5aymb7qQ5fsBf456O344MRTC9q1HF3mzH2sqUxAsclRzll9idOtipsNTzkz3S94pfFbdxIZpUkkRDaCwsKJoUtkxOelv56h984pHj8r/v8xM940xLnz1rcRQu452L4leuVxyC5zn/NzIARcZfOeyJB/zDN60yVeZ2gjh6UzfEwy+Of7n/+Gn7BMBDzCuhcMqjm3o89DNuHY3vV97BwbZOY+rDFJKYz7W5DnmcZVz7XeVCuQz6fasZHYblQSbu6cg4vIksIB2e7CkMg4eYu2QwhP+sk204/812i0Oo0Y4dCfJR4jIJK6Ngr3N9XjINiapiTqZ6iqvIrY9v4bwfHSkftLkDq3Wy+PflV7PvMsyjQsmqJCaCVUlvk642eZ4+nyvHSA8dr4Pivr0BwyfXaDAalCoyNRlw62tZ6iQIItJFca6Ili0SPITRaZzSpH6Su7ns8pm0mkwViE1RwxkBzIUuKuXtutLv9fhFdUsxp8QlXYV7YlhVZp8cR13tqbyuVgLuVKhi4EmX8xV5D/zIAFIRfyxMfGBdWkAaiPLyzXWYFDZHBRWJev0ueqrR/kG/GP4E6H6jcNR4IzHJaoYUn7ukm/nTHDIqY/ryrK1tT2ROws2wIjanMYJOlWM9pFr1ebmWDZLHzBbGwSs3DvDsBHQ7xOEyZ7uYG9BK7L2jSR3SNDPvO1EZhrQqSs0KkM2khsE+MhyI6ChrjKeMckzjzKTNCQKqUB/beTf8k1/hd32iL+OQayr8CMQ2iUYZhXHK76rIJkykMlOyjEpCUHP2XfYLyPi0s9r6KNBClPPE2qvo+AralbBWh880ga99Y3kIjhRCxBal+Y+KmAUI2k3LY7jZGyUY30hUcJwT9bvPCj4iWCRKna6hwDdz/f+RrxL/pbDuw/28O+/aWakxHhedz93E32NpbTrI8FpJKho5qVlw7hGU2tP6Qnb5lyRGxnMPUQm/hfmwF0AP0QIRbxRmgbCtaFX5puv6aCNC45BbxywKcpEj66tKLI9QcdSuyyv5CODsoHq7xXyBSaqULacWBzP9x96uWBQVo5gFn805xPH4PZCsXwssaDMLkdie2IOMUvVvPlABe6YxK0JYDvZ+4WMQtMcqYF9QijiPNFoxGcv+xLB4CIjx7uXEYUxCWPYH7Z2sx1k8vknAwHefZZW1nebNNwDIpIMfyIgV8LFbetcmAohgnHk10OXqRkPH8UK0lzWSHVWaC1Z67Som4M0pJRdi9mGSBliAShwLk4NPS43a0qfX9RP5x19t1JSKJVgHcG7UdSt7pC/ZUWmQLkvtB5ydOm99Ji6QEm/5+xAi5/F3jTEeubmRntKTIr9xVvh8J66FfcmzYBwdCqcT+j6FXb+X1Mxiv2bnHTiPrTYLlwQR53yy7uawyefLJ/YQnnYgISFrYkTmDxtKl6vhWtWKbcHWGQV7SZ3RN+kJ64RGDrvj2BNzAkX+2MwtMufZPpXdK6+JMNUY2aH8h+Y+LSfE0xYeCkXnkFhU/KUa4mXqYhX1IOcFPwp6Dg258Mg6jXOLlNfG+Koo75SYgZNDvn7TeJeFTpmvnU7cOjPBYwqu63Daog+7A88k5N9L1p6lZ7gt58JhvLurfuG4V8m3ypzvKi7n4m1+jsYEizrwh2iv3a0Kf5QPx0+eqNrTAs+Nk+ee/B8JAzMu7lq2mxImM4H/rfL8VR+kRKgMnOsBSN6vrfL5qBCxaNMwWxkljSXLbPz6Mke6i0rAgLMz4fOPxde0V6DjPw0wEWbAmPZ4vCy0wAEweIZ4boIBlfaNJWke8dxgMvfs4dp2iT0vqb2ZZ6COclSlbzToP5uZBFSK3OKgswIe+UNmMOjpQCyPXeOoNhB3NBESsDYz+Dd2Qh3k03Mk6X1Up1kXd6TCdpRxaO2pBC4/mh/S7x+HMW4hZ5rfaFms/p6Bm3GbeUivkGOFZiRKWaRdlg9MB3yT/6q2RmjfwqdoQ5pbUQiwZflVg1QgNPoZHcrRHsV+zs3hkGoWOo5Vslx74EWUI7bC2wTMhjMF9Z5vW4cHdrSzfWmvRqYZIlxmFSv8OHkPMNd7kn+XFx8QRksbyyxZ7a2OI0qFh3DK6i0bUQ7p/xKCZsjp56AQyFPxE4dxNd46PwSoyzMFhk5Zgd0A4zFUFwrUWzimaUMMMvEEd6g4qxlc5OcatK6Qkpz1UcgypXbO7hETAciziE2mo4t8WglVb0SFG0KFD7iNBMssWj5SPdYw7i0QPl1b++EDPI85ktGDRbH6qeysSH2iPseL46ZYOjKe17+ep9BqjofMBh58X1WvpFPKBT8G9dAZbXKRIR6jvTyh7wpXwl3dhgIVjNH1ivEMu80AghUprfH8j3VHqaayQqQCtkdieMmFR71TnnSTmTcGLo0KANsr9eT5tWVfsifKwQTpglUfnXTGaDB+TbN8wlDdiyLXTXvukqMIf4T+Nm8qVOroOaaveY76JsFlGupkbqMIA+h20G22SZwOOIHHwCybm/a4i7DlzfPd5lQ8kC0wuk27BAd37BfwKGh2bvWEG8JrRCikO/hkyCfk+yIKQjleUMEZCuq2cYWC4kkfHZD2KGorlC7yUF9fpMOenkZzZp37xGW+vSc+tFu/rNOeOvBOeyaqUHd98FckJotdr/sig1A0v/OS2t9l9gnN+EBIFQcO1/wDrNHzQgMRR/LT5grF1gbdSDVHnQZgLkhta+GQYW95z4hEiySHrVqonv+vBTdeTyCvGBbLPeSQlX0a7hR6CduErGTAkXe6A8gHP7bAka/UQrR8kcAAKaUmkduY3ngneeQ3n5fzg3KNCOSDWYsaPkL7QFZvoGLe3ir2o439giUxPgNsf7xJXlfCRu5i9APEgjbZHMlHuJxEY+5leWeJsrU3DoOTgmmLGBuauEWPTLvUSiclo4sLiM8fjX4GpLovVC5Ixrt7c8EwkGBS/2hY1lRFG4uGMqh8k+TRgWlxw7Dr9wvYPLLAEd0VkfBRfk/HFcKAWALFhGuImt+4iExjIEwwDkbai8gLrMxpZtVBNwu/aGNclVH5PhlPIONGSP5/MFcJJ2GqRyx7q5yrFs/+qwxkb6aFQghR6AczkdnTMLcuUQHE16RH9+KCwQ8PFpPxE3FCTWjGH9QkPGENHVZ92YNfAbOU4jqjO3qRIpSENSrYVQRNnXkN/KiUtGwSzBAE3JoWaZr8s1DOE//q+NObMTBEqEcQEjoqPZ0K3Y1QoxhQU9yiQfpmQTPb1RlFSi/9lCBYPXkukJYmG1q8vPbxWo36oOvf8oT9TpMNuW5rLSO2tHFf3qxfg+9fPc+5QhuehghHNrQW/u3DS/159gEgfFoerWY6BvdkJAGNLmRMNWoXT8FBGEBv2V4Hf/NONiDg1vyVJlgUGSow5gkTGug4uJ9+nzmmkksN9lZv+2s9BPWDghVIOtojJF2f2gH8A3UiUrchekVOYSjSFQHvRTYZ/SK0o3689bMd7k7FJw05oFrEs2QZL/gl8q5mKoDa44cTieWwF8XAf7NPXazeZXtM2lv8YKp7k2vyqjYN9tSg3FWDLxI3CozNTPtqTpVHFFt0F5gNz3OjZ4mLD+D2j/bCzTy271GcP3FzmA6fxmzkp2+UIO2KuVn8/Q8L2BqBwTaF/CIdZ1UFoKdKpU3joBuHV1lWNFvzc8UKmndQlaCOOWZ9rGME/bQDA+giA3frv7Bd6SwwkUk+IJpyofusi9sNeNQH4z2f0wbkt9TxzYIqlRlKuOTeXaRfdw10dvkRJg3yBgaFXSmQULUqT+19hEEIK2Rks4ehL+5Kng+U3OkwCf/RBM3cVgOUGGyz82IaCIVJQiTpNBNOPmh5Qq3A3CXTn971i5dyTJb4kebWAJNzBT9ftvg6T6beBdc2FvXMFMllBVJrbSJCJAnCsUVMreixl+AhrjGepBqdq70B3tTMFzymKIadQXfb3BMvCcQum5NmpPbZaVF0RJ4BfXvV/2meSNHAGee8qlFFJY/DwPi+jufFEhsevQmXhdBeq6e3A21xluaLzpD5JtVyOc/lqExVXEs14MudpR74MoS64ysAMbUenJXrKVGSsQOqfff/Coo0nDy7Hg6wVuvdU9g0BjP2Q+CvKfN5gZ/JGYQiXKObGZ3ug6AjkSgCDSU05m5Vor3Le4uqY/TaFiiClshl+7ey3NyOwIUwl/8lPYpohabmIJAY7t5UkKt3tXXP2DzWhnvUaS1uGiScj1FugtNyuESaM6bM7hdE10gYjuuR2XTNENTIYu9OEWX7wc476CeXvAG9u0WPZwgHA34GyiLAGWmY6XWBQB4ne6fSJTHhaXUW9vyogNF9/fi4jsRXFCTHNuIB1tuZLkhtKcE3mpdIkENHBUOaCVByU5hLWWrmoBG8Vl1djLuF4Ymm1I2hiyoiKQeWaWOqlpVvuHbUd0qppH4rHSshxv+BMYkCGtr8g1zJ/FmRAZAHQ0wd5oB33fF6mFYdSANErHFDKwaUvfQIRTFk4QZlFyTqRIWzgAmEmPf6Du5nsa2xTRNQ9vtDKb4CuC1/ChCGOwQQ0kXRo9hO/aA3DrJUZK1IhldBZ+9VUkOT9u86oyfurwt1WFxzI5Ibp4s5eCDKXwH8KJeevtBy1dCVJ6iQfJFHRTjkTJxrD/rs7IIyrXeblKqQ1XOJkf/I9NWDmQgRUepmZVyOQ02Tq6pqahqR3tba0bREFmAHEWBVhrk5W0QQgFBwS3/ReLci2yi2heLIw+rT2L08qQo6Yq6gSd5KHV40b+JZqGX054OJreNtUqFNQhlJhwRliaf9ncyMrcZtSNJ4BG96T2GJKjlE7AC2OriQj23x6+F64uYNKA0aZK7/0X+rBJT7OtwpREV1QZ1cGcbEEGXNZvmAZDH8F5hZpbX3Nzb2sXOY0NWSN4Iw0qnfAbu8bKORKvmRnxyeXl65xNN0zDTdJ6EbhryNwUVswMGNdfxcud2kkEjvBf3KBn8lb8LRO1uxx+noXrkE2aabLpCxzBf3EVkpawuO4hYvebJfIt03dUWPGEcnSLWkBrs7iNonze98WS4l1hs4kFPgZegBItUBHJqi9q1yaddzbfG8b3ybHGky+HGrSLRSVUduOA0y5IbObFAcfRPKtovJauBSr2KkZ0GkT94kqrEjSOgymvaw8UJlVs4W0a7ns3/nTO1ihwhiW788Y6A/s+bvWtFN4xsfU+Q6OXY2iVf5LeCmW95dpDmoTwi+HSGf8CaRcrE3bmwKSMystn0kXhH89fvD85iU0XGFak0+yW8CohXzi0M5qSsBy5VMklrbM85qQHl4IlgU3wxYg7L/lhTbavjQsIHVXyraUX9QEiIY6vCS34HtyusNsIhH0d9/g7lXSYpEvP5VZRYoXyxoHMxR38Nyxdf76tnK+Q9I3PvIt+NDzqqj2IzPsMtvR5ZHQtRdhcwnCq0Lq8Kwu6b1F94dLczsAC3XLl++nzH8Bx/2obiQBq0WG2jO5o0qg/IkgeufbKqG67zjGIJi0ubj7kkrkHEGC4jJKZfFTLCkTANB8xdLbqPj9UE2/IqM2bXzYRnEGOuvcBA1faH+PILtQBDdaxzuFQafsWoiMujWYtqRRFJExiJ4mzwGpjHC0GHoOK32HcQbv8yC6C8Ze0L1yyZurQeXGYEq8DwBmk2bRYzysTDQQlSOT/oF9uk7RqQjthBEJKqPyiIjhXDb/T6Ge/sh3gMBsAO561qCd2a42IOToWqJvo+xbwBRXpVk2hCjmRxK1HmPGygS/vE3qDOY++oYnj/n0w7expTGejcM/9ALmHxITG8j8JVaSVZG5U5QdNVKQdngCH1oG2Pw65vwO3ccJ9gwktZ8dy+/87vK07y379KCitm1LOPjyUQL5aS6EdoV0apYkOKf1sIXIPZygpjjAKX9afvCeAlrMLNC0yXkW47XGFX/p/3qOrEAVyN6tgRQPcI+Vj1yl6QpDYZlgzHHXZBimuy1KMWmOtQ+mB7j0SjLXkomxYioyz9DSdhFb3voxSLy5EJZs7/Ty2kfJF7IC6MJ+6LCfza9mpBd7JTQ6zvV3IRwAPmAMMrwCK1rSp81z5T9kTQoVrma2o8UGq6HV4aadUW+FpzvWM1DZocYCnWG3JrnqRK2A3RO9dy7+PEReOrY4nZXaObd8wXLCPHQ9llcZfV1hFeU46ombhurFisMBHdefrey6dlUJ5e66OgZ5LMjAdWMARyzpiKxi/+2+H8uog4vAVoPdxIoJ1Uqqn9GnJdHh78h0AvseGZrLKxdLsE94HIYUBewShq8BvjEsJvkFr+cqfw0k7gYgIBNP2rF4mMDrxFmp0iytQDIyTNVUY39boOqhicuvumXRW9piBSRaS4SqTEyXIeYPRRDHUo0vyBNWsUxXBdOI2XmF2+tuwxwjQiCCBcHfmr7RLFp/dxXBazumZJstpidXjtiqjtL9azW2YN7oaiHissiOht9tzcOdmDojuOUH7kuLn7NCn/uVuG5hYEbw0d9+hYFLBQ9k8ocy9whOXX5cVOkt2ZXQDrHSI/yTfWKf/q22SYccM9Uzx0528cPzIm87NvaSRccMNSZN51giO6typE+J6ziYrGSybRhmEqgONb5tSyrh3YW/ZdvIkEdpzAQeMKXybdUiLWWE6Eo/GRP5dk1cvL7FVmGTS0domz87oI0/vKUaYcNjRbsGrs1o+SzyklICf3WfZyHzqWaT9GVONVEsfDEkIZbV+s4LTNbx9ulWgUNdOSeMK3Sd8B+Z43LtBq4mbk5hdzsz9ER1fOUXDIRKGwzPDegRRaMTphuz36D0NxzANWkEzXiX6LGS8o3eEtjXRub2C1CaGyKm0UCYUsRg5py51nsCbMQykxLGwKmgd+KtkRnhz94up9b4FjJ2hgUAlXzPyn7noXih1ZMkxEocKQQpuGzYLLxhPnMi5Zc5hWIwEq5BF1hhQXUVpPv3usqZyS/M9Dn90LPTzipfNPrQ61T4EBm2ZkH8hOiP+vBtjEwov4s/VjtAXRR6T6nI0op4QbQrq/5VyR6pgJRArNuLkV3twl8hmy9Xb/47ypSqJiIzKSi8kU90+YqyhTTfOp6A5yUeKdFCrSK4Pv5RNIIFf5zKIFwGMZ+OBfAFofPiJir6N7/RJJaxvnFSwgJz5OI//ketRdCXqgj7W1JagNeGSyXTI5ZlgP8OJ/ZZGogRfLuf8CgEKgjPf6wP7JGWGmb5lcElIi1moBsDXJ5TBEP/Lp/tHLDMdtDXXj4JmT66GhI+F9DS75YTmfuiVvQIfOTrtkL7dVLLgt9kdzITUZ2+2lXC0vy6/KXfuLyqiB2hWp/7LaVk/pZ2M70/O2b/JnQDNqqQlV8Ec9uJ9bGVxcfrP0vrGaILZeD5RDhNNKI0aaAa0G6JRLdIk0+xrCXpCStdUSDkFrpm6bPtID0Ks2ZXd+u/glBuu/izD0wR6IPrfI4IdV7DMZ1PL/8qw7LS+ATo0kSt4dqK/tw+k/A8MEZpkiyZpEH9R501ewZ/oiCD4qhW6CuojPhC8R3iNG5VjnM57K+xxGViDejtTzQbtSBz35iO/MBXyPc9FnKoi+YLNh4OUgjuwp0bGE4zBM0scNDEgUp5xYUJbBei7CWXTyQfP2hT4kAlr4liTESwWq+Y0bm/Rg92OGRknR3XlG6KrYGjszH7g2izFVHXVwqvz3e7qwBQGtFYwYHKSCvYQIqWnvCUVxpkoVfzkBhBo5+ozETdt6Mt+RT2N58bvPOo7zmJpkLsyXr+yCs9pdaMxefcQuIMK4FDheAzxbtbObkwMfuVG3o14YiL7VfduaMGqxeJAJPivyA17xmmZZ9b5jbYNHPbTAtIk2pA7/l9X74DkDdGaK/L34/xhlZrX0SXa274n8hoYEQ1mb5ODC7UDAlsmokVKYt0vJ0abiVDkztBhCu9d72LPuOC04DEYB+7avkSvlwb5YYHLOkOfR8gkqCTGbf6uV48btYYFhr01Dhi3qlmf2kUkUI4f7v9xE4yNJLHRz4oAESuUIsyykyzaKoBYGOV4Ei2F75SRuaYJX7hRQP4D7w69598r5ZVpT3Rg77Bo5qBDikDhlHG6UbaEKOV1M6aCpCq/w8xdeOvzQcjqv3ix1YQVYHrXM5whkSy1oTHuHfrCd+CMjKLHUdLX6tzTWOmYg5NPVja8UV7AQBoRWjM8zzOf5bcHoGYKYetqOKoZ4r6la/dlsjfUC9E2U5MlXG6EGOK4atQeDVVYTsTGp7KzwTv/IKfTC0R0akUqeNUR1O6n8Cds580B4FVuYJnIT8rUWga+UqHCLipCflW32lXQAJmCuR2j1PSlqOkVltPryUv/9eyINckiHuTfIYkwONb3IT6MuHk0pGBSn7xEA3Yqzv4M5+nJxGIkMP7pTQj5Iv7w9uyrC8VT0+DItRg5qX4fkb7iVvr8MGevw2SCW5mFkR1NqeeLyRMiVfv/7byBby1lJUfAgHtUvNrRhWzOae7+rGjLyLo1zSBRSKVFx4HA4OoPWLmdv93m0z8pudLX6nF48/TA1KHv/VOvoHNb+z27XaFevIBj6i94GBYuW6MHyORPFNN/IokffUAMo5jNqrUc0xbmEnGgLdlh1V3ZUOIyU/ri6Ae6XY0o8LzqkuAo1jLdfHznsyGr772eeFo0O+CvpMieXu66UC15zfVb0NWeGbhEPwk3jH+4ILyTwEtgIrV17SsibhVJHjLtO2GBbQIBRS+J3MGQfK/n19P23AjKSioxB2ToorKQTMGtKzxwd5h1IKw0acSsgtYEIxyu5YsPRBs4gCyin82YJIygXEBl3FihKRhqZGZfnI7h9IiJugDixybriC3j3d9hSfj7fVSfX762ooVlkb3pF3sOg+d4LP/qilsATVeuvxgmufZjtOeA6N91bg/IQc4cv1bhns2Fv5uGB4uooy4s99rlGHOBCL+eHw5QoX+4K6hgS/Bau8t5VNm/qJLtdON7irY2gEnzbvJ4TTTGAv9zL2CBA0zz4H+HZ9rcvfBMD7Dctc9xxURb3W4b2kPxaXKIjI2yEaB5jOwNcXZWnYyH1M7F36ERKC8XKq+e+Msf43nUqnXdEMMzLI7A76528Rr99JvWxU0VThOrLDdUwQflPS1qWMHaV0AuN+y/+xjlMidkIH4ciCBZGEfluTiT+m/QRmOpTQZ4qYSair6ivoyEe+8Q8PUBja9JKX8NdO6oB/8GYGsEujbS3TDwykVKt8Fua2rQ+YyJeBP/3t18u5jw1g3HGN8JFZneTNZiHl1bYCrWQusNPA+UtxHBv+jIOdlf0RhzmyixJpiXWPdTeKteIli3vGgCpexSEbQtkpsrQvZIOA0SQkLJdsknJxojRsGnUF3zYhhaSVq7BdE8xz0Ih/G5k9scrXqhmgvLWMzUfrXa2G1Vq0I9YzPJXmAzkJLiSrFT3fEgKa6RQbx5vwvgZP4lXi0qLO+UITO1hLnHST75hpNHrkcfvviIHWvQILED+JiLbN1HlVAmGBluK46lcgGsgVwVIh4laD5m6Z7OM0DaP7t/AFoi/e9RXFqaftAXUI/rpFVU4YFl4ux3o+uz+WFz6ecwHCzkpAaTfexa8YgNmCX5PnTDAWKdAdARCXhN5pQ/x+0jH7pNAviFQPdmiiksHNRPXsUXwOsm2A1tLNa/ZUH4T2oK0TN6VPezMggCGizNm5ddtIqumgxmGlsItOAXLBIKkXW2VVJH2PeU6EzlHBYuI7QgW99/2LR+8p6YKc01MTt7YF0ZZmrO18lC9z15tKrJOC5tBws53ahLvqVEg3ATJyq+VTzr6/XjbTM38zOm3v8Y5C8MQT3eObNjs/ZQZiKHuMOAd5bkschlnowhGpTgLDv9I8qmmETBkBJ2qENOyG67GbUsagf/JVMleS7sNpUkWeStSrcZn+gayd1pepJ8WXoR2rVyi3oK/0gexrTBdnOfGUsK6vhiTL0WgxOAwIFxnGt3RXjCG+RBjSiYR3d87MSNENi/wEtM+Q0rTBRcU08zCPycOtR5ftQMax7sWh3R+Rfep4M4ob9wg8RZThWln9ovse7uRJDQc1Ws3W+0W7F46fMP81D4BitcKMpVKai19HfeZDKxdNDTH70P/ZMCs5A1pAEaSOlMHouZkudarZ7WTOuJ1NwMoQ7isqSWSDYzxf/g9Q/teKjP73Y1j7c+jvOJeogORxdRxS8XKeikNLbamg6Ejw5lrWp0nIxQAn81uZgVg1RFSrfSDam77hOt4i4NcX1wb7iBzUGWD1xIe7MQbyi7WrYymRHNeBBX6me9SxFR9ZrnTeymJSzkglM20w6Q/sH4y3gP55kDIlfX2hbWepXEog1m4GfcdG/aW/1RFkxIqUdE6WEbSEBTtkfOYXHBnACXxXx/UqfbPWXWVr8zyfWlL09wEV/hFqMF5+uVyoemUjfe+BoqhL0O2SL2+2xFghg2OyiTwXHe2FbcUaAGykDPQxZIb53Xi+dzAgpKuK56tJ//KhZAIuCO0fugfKa3rWB4MV8Mx/P+e+mKoadAXwIXMbtorXScqwEt8qY6Uu8cscGzgYe9Q7aS8FZ8laxPVLSisE4rCICBeLXJvgn3DPgI8RM3tfzEfXlcSkOzwaS1njLZ/opqn0zUtJmFQYmUn5jL+b+tTXwVkci0DJZAqCpjb4nr39XgdfDiTjsLpQGBbldMYL29lTAX5BhjNEdVlxOEEbmgLfsnOZAWC5pD992s+YHNBvTkcB2B74L2Zj4LXWRffw4MHr5sKW4gdj5v/hFE3qnu/sbeAm7kdeIlPThXeUj7orK/C5XPmFG/Ux9h4iMeghU//mq5ipBAlgHFV0Oxi03LIvfWk22jW5oeQ+HRM5FMg/tmrxlXFQ+yghfLlbPqwS3aQxKTXcE8iLfvYcf1AouDJ555mCTjF6weU8VVYEKcClTYRUHFeAdqy5FHB+HJausVZ/7tqVXm4lDafWNdSFTlu3n+BMLkRJsPCcE8EjSn6AArU2qT7BappAusyUe5Xn7SMr+6csNI/GjmTEYvF4thkMpR7kYrmJ6N3rT80I0TdIRz4cOT2LYWzuHYrrwKW0Fh9SKSlcBlCShtVxsNoAwvD+BJ5oBJRKWM0wfyHmB31f+2ursqq7Wq2U0xfkYMw3oD5PHmzecVC4CN1QkjRWF6L1Um96KlImhyLoTwWRP1+XnYUqw3VCruex75yPmb6ITiSMmk9nLYeGbz5Zu9wGxbpf+8Wynz4bEAbceVB8+EVCLycNbmiUhp7HkvK6GKpwFAMwz4aHgl8a8EnXFxCHGZZGgWScjOq46/kYa6JgDK9yrDJJd821RUG43IpJn3N3TnaIqsFD/uESw80fQT+qAhdXAQrfmTnpTqDI33Iw/cPSLK8FnlOiarqIHlaB4Pi+Z8D4u5fRMFgq0ZHVeR5OAnYO8vZAqSaoHypajMJeZ/J6uSKseTh5G7DFtaRxyQiFVOg4K8Sn3+PPUtrWrfL4Bse3rklrQANIn1pu8Er4J6kZd7GMlYqYWEaCX/Nh9MoTZbIxWOyRAplYRApVCTdAZ8ASBvlidUGGdbLoDw/VQhR/P/DnxvAM2F3KNSUNxdX1zumbf6VpBpEGWtGfHIERbvgstlEFVWRDNyEzeV84dSEWbxZ0zRk/FvNUANSRUoKUlQK9sNyYxneucOJsKRukkUYzKYTkSkJxKu15gvwLEvv807dQUpR9AIkS/7hHuPNjfQqUlv+VjW6rOHo2r7GRaTjREIiIwftzVFsIlV4URuKX5RqFEY/Pj0BwgAxDd6V8kkslAINYQLHu3XSXCjZg4tPYRk3HkL/9ym+MVa+701nhrSuIArHf+JwbjfQk17lG5RWA6uVkP85+pS79L0vj7oDKYDWWvDMn6gbBTTWRgMoBmYX0z1ljjoIxQQF9ezqE3OrywxopkgzRfm0MLY/6zaplk2nqqcuSFDgDp/PETL/wXEYQlNhWc/UGx9uOKFfO/paYWuC1K4JPfJ/iuni831noZ0oDoqOMGtbGM4tH7WZbTujIhp2u5Pkw7pq948Vmd7khx6AFKYVnd/cGI2P2dNA+KsfFq5tfEX0w9lpLKAYBTz+ZvDlykWh1kT7U+TW3vhJTyxK9pI0pitS7ShFjmhrViXlRJPBqb1owXZ9SRkoYeYi5XzVwqG3jdLtoU89TmiQfmETXVntO3HOKSM7KsVp4+OgUZGmgqgbqZozPmDorsAdemJVg3Qwmqdjl9HlxjC2mCYYsXsg5P/IDIdBFpuuJnh35ZiYhSUG8F+XdZbvl/RVB7uZx3te8Igu0f1SHi9UA2OqGnV2OQaIc/WJ1LWxtn2EuB5GsNF15IhfO6k4/V3H/97FcggG83jmn9gn3nlvZSmoqSi29XRBnHEiWCXpldPiUzgRQPtbxbFgEkwbub+3Dt9pWbVkeb9XKF0NjT0i5UITLzmbsHCqkcCqgIE5H+7qJuB8cl7b5QJIxZDptqb2VYovf/4nc9pPaQASW2kyjnjb6roPXiFriKlCernBczl2+LpwJJKzPi2a5VNiwGMZL4FqfyA9v/TWmbqGI/OxqRfv9Qma/ve/loFv/ZYZC8tmUSPJLWHhCEyhTb9WdTa0s6V9QPZ4hgAdm+lgwQEaXWA2Qd3QJX+pt1suB2ljniUsiRmh+AK5QzHSFTkipPdwS6FieihDRd+WpHTceNcwH+Z39hbUo2DHU8UlwFLTPsUMxwcyb7zsm3WXCehGBKVRH+3Rp9aHwKQEhH+nm8ycpSlmhEPfM89vFOshY6k0oA0cKPMspfNYCv4Nv2V3Yc6gs1S9002agAUQFYkEafEjZuXCHXWzEHEfrIM3u/3wzHdwUl/xVQ3ItWNPITRrJskt4wk7DC8qxTD4go7HmDVTLJDBAAtyaaQe4VWvQ/KPO7+mR638J0/5steFIQFj43r1PVAH5OYu7NywiNTksejJ2PB4Haz5IJerXBPEvJLDgkDEgG5SsrP/KZ1++sEJHXAiH65Ihmb1dGf7LkhkzH/A9/XEJkUd/f4kNraTwndFIotPbLvavQ7Mtv64gKm9OESLubIEYB7DC/Jl5lUqt8ds3/os7Mk2RSF6oA3MNmgKVpxllKacwW8vFW/RicCyeZ8FxYxvqWmVj2GELuVjkVYW6czJHchFeiAbf2e0lwuQZQvjv4I1SRkM/ekRZGwzYrX34vrJl2RR7X6h8KtM/1xtwNDVmLctmCVd+tyiXBvIsAzFWXLgsfZbuM1wZFam21Bo+9DbCu7Njh9mw3VWcGUSJBkX9MmZeuc0ci0dGyhKJWd4O2fQ7EMI7hv4zpdjcgV0UMqvbxq7YJbT8av6nwc3WYwlj3oMiTI/sZ+jdd9/XjBqwBSTtoPfRfPl7O5+4FNEvG6H9mS6N3iVUYdStsBva0LW33OZEhq3Vw4ZrJ+d6WP4VVTjkQBvS7NNu3YkbBAEsNXZMiMfRZ7YHjuu5o7UhGxSLESj24nWaJJSUAA+SQ1wKGh8upIGpQfh9vED0mgOC6LQBwuUtRCaw719AywUu/aTYk+p71+y9FxAsZ2FCplMuFvf3MdO3EFONSfHoaC+nyAcrsLpRCmHBWVhmdtsT4sgxoVneVnu9bCmda5m+PtMGZMf1ZGfjGM2t9ks3kmAb/hPT4S5CdQJ7DsjfB/c69pkEP/v6DaJF4G/CZUFCFYliL8GYOQEJVJp6tW1uFGHaOaLAfoDW93dq3CYQGR4zLdI16lJyWmbxL/cjQ/kVFnV0q/IZZNeZ/Cm28r/u6jYo1x22bPJLxorCWSf5UPbjM/ZR1L0cVd9NUDWFSdGEpAI8rsEniIwx/rzNaAr+2b2A9ItRsd+YUIAif3K0jVv1MSDdKOBRNIzryxd04UlYTuHZJzrMlROE1AOXXR2MWE8yMkbzo+btxnIFg3h9EaS6peQnlBjw9vyi+JiOf0lP5p4zh77R/m2E1C0gseodrHFVSnqDe5eMK9KMuKg9u5Sk+DWmkP3ro/yiXmPnHa99wgv/AMlfpip1NxOM4pX2W0QDxZIFzbgSzX23yXVxwh+X/lBA8TihUyaqxywCiRz56TEuTc6zooPsBVn+sSg96E9NCM8hPl7Pqv0thE/4i9dMx09sFkFlWJBM2E7GqKVbjivsw0qwzYrf9Zn5OpKEwopl21fKfLy8Gm/J7oEjmSjek5Ui50xUUOy4Xj0DmwFusfN3AM9v4+h/8xcEcHRhUVcfMHEjhf9rHsMvLjE0zG8nZCN+mfr9Fx2zc0iYAPUNdflv4VXVLGWL403+mW++5QpanJuML39sM2bCX8rFbsARiQCn9wvOMP2KzUJEgKxKpdgrAitbT98tKIIM4F+Lq38sLRiKP+z3dEsfgs2v66Jfds8WgQPRmysva4XiBlMeqx+gQU0s55OXXOD/ba/JEUBCCUXmClBgxyeQiDJ5kRqxExGoJVMAmTCiNzOmD2eVeDCFRT0fW1I9bbXZKdtbiijRLm1OzEpPJJEEAvPEriSPoTqfFg9aVzJDNESStbbIqCbLYNwojPRqnckR76KEFJbktRoaJljhbeOTTxaClR7iYXGEa+CpoO5VLbhvx64fSddN/pMw3lAUHCLK3yJWMZ+d1iKi6lYPWIGDoJI0FU9Src1N5Hi2H5Ggehdy6JQncbbBnx2Gs0oKMko5JWXHjP0kb7pPv17CdDantRO2stU2ZeWVMFAGYWVSXuPgE/ZaJ+5lg1rKkWBLgRgmbP7q2PeNkevVqxKGYshgmad98Pyqmxfjza8Ow8WfPIwh5UunmXFp4XycG2GIfrZNqEP7v+NWoTUv7/E1DS6r6zrvPJuNNa0F/AsEeHGsdssHWrrLc/r6RB8hsAGNXzFi01ZGwDC1ZAo1Mt7mEpcTkWldY2Obl1uzDLvoGX+10ObpWgVPxvvLDd3+xktT32i0TLO8SmuAqLqasePyKH9FKSTPa98RoPAnCqc2te0kmmEMBvXKhNlWO7dxOXFGAZav91aEQfJTcr0nfCRC3QZv9wINaTwBcmc2W+xZwWMD14u2eFeBQG9lb66yEpixnNNitQSaVNEN5O+foH5SbGJKofBV1UnQVuA6XomtV9li9WJBNmycGMEzG+qmLf3IADElVvHNvrndmrlxJq3zj+lKHPYd8s0ZaJ5Kh01w7ieFL1Da7RrzOkOUx7Q67GaqgyyeFvjXA9VjF0WWuHaykHAPqbwXMp1fA+toWtAjYHQsOq2TXH3x0GImaBsJQcxLPkN8aUHarbS6vgexFH2qcxBkMUqRiP5oVzBksPgwiNFRv2d2azUKVoUwCkYIEMFUNZGaaLiL/3wybpzV+NxLCh8ZjoG1zgCwHkU7oGQaSv4/Lkhkm4Ph6/zr2QOASIsKP5RKVt7KZ0WpCOPyWx+BjJ6ndql/Zi2Z7xotGYwmdTElMS74NLlSdNph4QZ0hcEv9KGpfwjbd9wvlNdh+/tUFcowIVqfXGmKJpdiOBx4HWTKwT1lO++9eE51bFYfAO5qDvNKiG8YyL744fPXO5CV2AsHpNueN4i4l3Uc/6C38uOP+CC/q8J2taoSarbKU0lHePWrFbvAttNfOAkczqmwtcXuXw+7WzPm/oJu2mgLL+sOvQo+WG7BByVKbsH19sGTMZntgnkhmY85qONOnZdlvi/+1IhQitcoSMf0+gLj/wAzKRaVH/7TAN1gdEsjWvOHzQ5ugrHe5/NSWIVzVN3zyVngNkzbcupii65DA9JbCbQBiigG0MpBjodkceBRYPcAyu6LVC21iSY9J4V8fM8R/CH6hLjo3wUdIprHsX/WzzAIf6eutKXV1Tl8JksE9OYaJq9U8F2iy7PPyYxmzu90qWbvlOesqydwRlxG/vXYzI2CRaI/ZbtrbU2CNTpshRg1apfeBakX8q58eWFQdikwnLKwX/SDAyDSJijSTRDA3/Xatu4IwYNXFwDBJJ4relJJtTul7AfbiuZ15oPfj6iu3C8copLv9a8pU6VuFGVXTRfsXeZwbVTcIA8E32GH6HsSAgUtaDRuuoDtxjBDUy9q/hiaCNwtr0Mi/9gB+OciRawlb4pPFMABgRGPLfo+nA+kzNcfdeSTu58DdYgPMZhjNELtHjF4slECIh+diAdftmyAm37vumduQOrpN7jhKPZmAAcmdJie6Gsolzz+6oaGA37SVtaqDfgNCagP46Ya1QtRFI5jMnYfu5balmi9oyHwz5ArtHu2ij2BQD5HbxUCVypdKoBh+aP6PsvmfVsTE6hDJ8vkM8OwRQxzsC1ore5xnBE6y5kckxI2ggLURjadMM+udeancpNkxJtzuEcxPHDwVJOt7yOUrIdFUVZAC3uH3tRqnSIFMzJtDG3L9hGPuv0esy2tEMqgBPUGbM9DGRHJ1WXsK5e4XR/9MVoFWEejYD7rtztTbgp8NqU+/FUq4HIyrumPuwk8E4yDrTSGGoAsabCRqwWuu/+HVf4J8q8fCFlYfcpxp4WdojMJ9ZFY+WduscE81gskxhurRD/neGWxyQonXjbJmE1rH0Ka7OXdtMPfQg0Cnl7Ny1GqoLZZQhqU4//xsKunPfO2KbKj2MDW8i7n46GlZHe8UX13zvE8ZrYOhhfMy7Kby/wdT+L1BGFw8VXDwy1HuWDxhEOKhcEesJK2DuVZ/KUZM7v+WTA1EEdBcVt+SvrvunyS1XSmFSx4lsjHNMD3g9DvQfW8MMr7IzSe2c5BZlltw454xK0T/gf17gzIHpdpARVICq+CXMn9BtZh4Ukqryr8LGVmv+8kapXCE77hRL3yq+AqtH0WMPOn8N3TMgKEiKNxqZkdpuUjkNLCGZ4k1R3XfsLI78YiK/gnEdD/eCHSy20LC5FfZ/h9X5ONEhfbU9knWH3TTFnxBP3sabJMxXaO/CiEN3/DYHTr+kPoHbiJ4+JsXeuEgXMY8qW6/QGcNMsu4KefWfBncfbcn9ohS9XN+b39VBdohVrWoP3rUpDqFr5vGMbl6Pnzfr60AWtMlrNIGnoG8NX6EIMllo6MOIzUSb2AgP0FY882PGAiVfIa3IQZoF7ogAHUTYyvJUCWLbhnwa83fdIOyAJgWKeKbSnhkz/HVV2LIkvZCM1K14FNVJOWqzYp5mCxsR5wOA/IqjnoK6PQ3R6W1RVOH/lVdkwJlWFQU3C5tDtubE6yTWiWa5pE9HYS3TO9KDqzB6CkczyU2zKNjrwFK6velyeJipY62OpAa0P1eWN5pOhFLhaG3R2Fh8jVcxMoCSiVosPkdl8o6RYJk8SdBfbjvsQxGlKgi3NEmvA0YbPhquBNdGzIW7aFLGf6Kb9fbDC6Dc0fhBGBo97m4sLhyM/kxX/og/Tx8DO7F4sANrGGOCMBJm+0Zx4a8ND+CYdJmJ+emv/z8/JwL5GulzLhfDpEWIJYabOAbzYtMb9v0bIwG6X726JK2IFiZzaOF/EBlwnJAYYFBelYSj7szzrmeVYVrDSYO7KShll39kZxK4yeWZiT8wWh/shNLueIj/0EQ7cPVdYvvzPEnX6Jh8ZUM2n1az3BZG5QqrKx6ArkR8G3xzhE4AoKcjHYQwuAZEglgHeahCFoGgbM++oWvw35Z+cVmEEP6IT8+pX8wslMCvohXq/MzEgf48ZaW4DIPVLmZJI4dfMKTtjsNrHcqW36fmMkv4FOUsRcNHEJlf/2GE5HHNy1GcMd5utYiX0IEnjUtlzYd90V2WJsbpU5ayuw2XA+qO39I9AbEAcvx35wBQGwiTAxw/344EohdLER1WkvPEE/FOjbjmCl7CvdC5CUMd0sK49+kaowa01MMN2nrT7L8yKR2BkmwHnryFRo9gWqbE4BJfoFtJIhNDMoo46jAnEMCS/0bArKEkg8taf3vdf/ezGOZZBO4c75TWKWTkXzKKtv96H61NitvYPcsfSbp7rTWc3xgMdyVeSa26ht/9BrUJ2mIV1TptieFXPt3LEcHKYbP+pnrTRPkmO+89oGywqUDJYv2wP7rM/4oKkKP1UZkrua64ytj5vIIVhG8D/vmF/9FsirwUjgumaGg2nrZ/0wqSL0iabvco8797gnvAL0hggG3KnkHzaAIERzVerOhLx0LSMuzhftAd726WQnnnIvFX9quk2IaYz9VR4Ccu5TLnxg2EC8SDRhRn2MChGq8ELuPViFoLm2ELvDW5qHXYP+O+z4fJLb9jz0bHQPCef5JeRW9P1B0FT45VtBVSjakWrHEgLhuT/zcNLfvvjNKGo8kq+/zkgl5qYNZ/QE6dGiCPUZPrhNuKzKo9Js2/9ICTiiwQ/ToQRHpFV1WIW6sG1QezWufl4AQS7fztw/mp8Xu/+fk5V1+hh0bU8yf0oeQiIf2gu/WTp+mPX73ZgtL0zxVWzsoXnWjKNej3w6/HW66qhbeMOhKo5ujKly05Tgbnf+V/IgZkGUAkdZm/X2e/neVAWuaCObBKta/JokxpCeiDv4OPn5sWxl0FeEzgGJm+RpL1HBV018f0zG682/tTuDGPtVOYUA26W2AZDrDpe4vjqsPy3R1sNkPmHUlDFIiAFkuE5i5pZcUYOAiIoom7M9mK76pJa+qCseH/p7RCLohI8Y/wp9SdoG+AgTecERow03y3AFGxzgVFwwmheQ5RiAaeMnmQn2ewmo01/+ntrAMoOIGallduyXf+XvLCmmo/Lyc1LSUxv919pCd6KdQhr83W2QSJmVAVPm0Ie4iZHHovktd/IVk7oQY7roCqyh+tiAISvJM2xnJJoDu113MOVjeWh7MO6MTRRlAaejMD3G75qLmCiL1Tvxvwa6yc8y7FkrIe2dIOAFflwAAQABJREFUgz5Mg9Zt0RY9t4gG1mQqPfiSsEgqxzQRdy4SZJeRTYfU7IXBvcLIct3teiPmGBa1I+1FYAGJs/NX5yE3DXdLzwz1r+ldmLYCsPbrlvUnLiHzC1J4sU1nqQA3bjvTq1J4RDY1FtDz3aJZMmJHMgvQHwKPhZBowqZQ9JCZG3ylA+jWrbMtI5fXJvPXowmd8ugdiO4peLmonl0Cwq1MmxRVxky6Fsi2lUFDfyNBB0wnf4Dnq67G4CbmskfmcWPw4tWOUEtYYQo0sqWk17l2C0R92FiSTGjWFxnHUgJ0MNVhm7/LYPgQ6ep5IlAVKZXJpxQj49ZHzXhNUSkaclJuoh5oooh7URVrC+068xJ60+7qAR3S8wuLrq1/mIUWrGD8yZPlTJnZ9rx9Isuk7HZRMjTj7SC9Wuq3ZoLvdBiS5Ms2+mMoQ1Gx/4TXUDREPrTfzEQi0SkoKfxbv7DiahZ1/XdlpWYwl5H8/c+71MGKqUhcgT12+3vodrfTZYAnjm7hTL/ALxQA70zDPtFmnPaurzqdo6K3+0aQ2rSmII3ihtVC5pxUoUcwM8hNmIqZJr+kV/pv2pO+AnBTTuVqOpyjfT7SVviLJDTT6vZ3+pKl+EZZkao7s968Wtyu8paj3n2wD1NPBw3lh7sabfGJUmmTG+kn1tSEpyi/Fm/mTH41H2OSWQhDE+lkETB8ftSdcS5GmK98E2YKKMuepzEksulIDWxgyeK2OWb0LeH2vyJCp95fuRJiu58TETxjdJ1jKwwBknm0spTHaSja4azTVtAftC9iyUci+eir9GnTSK7HeOLz+uvfGC5djpuvtAkXhK8xq+E5qily4BaZEIXymqpb1xmakS6BgUXNifPUNQELKqCyXqCqe/rbf7Flx3c+RLyKXgaFxiUV2sjwRsitV8Vw8/YrUro+dpe3zPoWLmcXwA4IFCXt0lxYTTaAkOGdd6ZrRB2u+/LbSOhVlTXkpYzzo7XvrwI8ueWNoPzQjJ3buTUK9CBu+8sbsDfeO57pWbnmQ0KwTLitOJEfCN74X/3k62iUBe8OPGuUnA+lyc0JjvKEfQJ2Y5ViQ+9XRpIkN8dtwWQsroc28YYkj21M5+K4b3DuIhvyT1CKrHMFDLof/cqP76ldsuGUzSpfpA/sXxaZpcRFY2CIzRZYjYX9B9n7NFGgL13dtcqahuGUDqCv6duJ+aHJfoPaEdVBaWKEImyKJs2NysdlJ32H//5vnQF2+JnJTFSklMNjC7DHdwT0//f+wQSXy2wCUpggEq+7y0XdtoEbfKSCa1FUSRuIP+3q/LHaxuQK2ijmX2cWdJZFCbm9KzddpevJ6EiNDNlF+cNI9M3HYdhPPCgQbjume0r6q3wDnyKvv7etD8tJQ43QYtvAdZwlodDjfChOG19MBi3sItlL2pGBXj72LF3RfKflgvSEDKuWHrR/U8lbeSf9JV10mtvEQMG50uyCJDxTaknlUD1j2n09HJy+qnJDQ6ecKar7TMPTmB0rY/CxaU7XRHB1Q0idTGApc+Vc+EcuGc0g2a+jfQLkdire/9MMxpKhUIaUPtDo8IRY3i/vvV2NXwsGaPS99L8sDOTRxNxmHp1HuafAQgSkmftxN7lrdxC8gd0k2Nim4DqKklcYzVViJlqdDwOxEVLqWNjnA1qB7bRTGhcslEIjlKieeVNRt0R2UX3iospB5KfbPCLgKwcJJEhYJfVke4DaVgDQcZSD/9pc++PP4ivXlnIfccy+yz+FC2CItx3DjQJNUZ3ww3fwaRr6vpOapE/xb99nfAurMbFyLrHKGP0N4rB/CCXRKuEwMrMQd+ebjMRM36nimW1Enbi/NNHFlAlVIDMUasMqpMdtBQmnxdzwW2ef0iZ7fygfc86xjBTKbJcYkeuWCakTHXf7mfcptqQuSPStJ14X7FN/uUcoBxb21cqZZrq4DP52dCPnaAdGiFkXyElSWr2u/3YIDb+wzG8ZDFkh2to6OACJWUCVq6u/FhGHBnWjlfbFN9Z1T6kcp7hQb/VB5YYDt2kPKJUhm8uY74M2dJD0NoltA9BDCnZUWFTdtvObNwCfPqoZwLNUBTSURXI3TwqvOQcnhcBjZf2A9M4SA9vtMLoMCRKt+FZDI/8AaKEgyEIEH6s/cWtWsiCIWvixEu4aX/OKO53zjpulUUjwvsT6eLzvBgRMxX0fRDaGGCiQBmckWIovvEiPbq4RFE9ZNzXn3gdPZBTZaNq2AAE5V2rgbsVbzVcx6M7h7XzWAxk+pSm+RJa7Z12NIq5lvaZXBMXchxHFcjzyrvcAOD06yQwghTTOOiXdw3vHpxzRIBci21luWixSZoVHGoIMkVdptopkklwrVMwucLX92VqImYFLy8/+n0Gy2TblZyC+Ax8UUwlndJFB2ptvYYiTTyII9EbiZioX4u148ZjqrSOAFCYmt9U6RCd+6JHfKnt9v6UowltazqSFm6bLet//jPvGO/Srb3m8phhLJhbfmVW6Dx16+Sr5LOcjo9wHVBXju0Av4gSCqGMdS3/15H+sGrG/iQbagymajf9IWcbEsVwue15gYO8glggcAhMDu9itZObxSYrt402CfALzaKbRmCsKFHvbnW+Ia6fQiny8EiBwOcBBHRTQyQhm2hTRAyZMXN3nl+AEs//+h5IAcLKOhb2ixcBmg9yJWqv1RdgWzAWDd8RCEdaKiYaasSvIcirv8gEEGfZe9ilBovD1RF3CKK5wMylJYvGFBfUqxcaEB5jZuh7bpGdovcdXPOXf/8ouG8kf+nB9B5n66EvsTBruDFmftxFLAVMkZJfRf/aHNWymUFUWiCmFApq7ZFGBpquimsVwy26QyWo6Gg+CP9RRsagwi2mXTz4VMhuXg3UWub7DztgDI2Ofn+8rDJKQnf/vdb1DphTBqZJvxjByhNwgomvid8e4PFZkXn+rvBq8n+bcLwdGatPza5dgDikX+cXX6Xc0LhseehEhV7ShisGpivpujU0XUGfAm+IY7aaNq6GEZ/7AoKcGyuXB8zL+h6/JQmuUY2dxTr9xifhvkVNWzspZfCW8a22YwFAC64AIVCnFvQ9z76v4Ui8tIMB8ZIIVsEZNlseUB7FxkWJujiiWWfLSG0TgXIemBPTPLxAs+vN51oZ2Cuw6TKx19J2Wrv6sKq1r5hu+UW7lDB1z4dcWscnwj6HI35Yyd0Z9t3gAp9d2VkgsB9vo/NfrmHKFwpo0/EbKKSKuwvYV7eauqs4xaA3KoAmqzxqmA6BKQ3tJWw8btYJWndLE7VZ9DJFVzj7evh/QpmLiXofKswh45M4a5p706aOibmBwfSoW7Qe6TS8qqpwL6bHn+H/dIf/+CIiTMTFg3OoDgPoTwobmfkqHZu3dW6hy1cCOvEqJMsRe8ulnro7AZujcYqKFGB1K6BdWRlCGkHIzE7BIGTLB15HG4ltfWAipg/rLhWUKl11xTP6V890aQvbSqFgq8wqjZL5mL7LKHsYmJlK7FfF6GkPddXQrftII/BX0k9jhujBzfSIZFDLNWcdBFy0e6gyEaqiK7NL+Y3r4QAHmCy0fSBqj1PSvx+zcYF7KrAG277RnzX1N5z0q8VtLouTqrSmvB9HJfeTaryizN7YsyNv1nm0l2/CVy6vWffqwL7fCj11hRZCvgoHXaVU2n57MNJIbRsq4fn5z5catAbOU45+i9PfKaMRDGoDqJ8e9uLwbfY7b84ojrD78nCDkqpT/9xRDqeb6JO/Q0ChEPpPSvU90TFemJynDcUvD/MtN2IuM0mL7nAd2snmlrLzkUKTx2uZ6TpqHZptlBrcRrgMTuHPppQbrnpY9FeWXb5qJCOHSV/471WtljzpqhQbIYN7usqgjyanX8tiij1z5y6ubBYZqhYd+VFgyVAaOTMB8rb0icCbqQYj3gOS/mk/cSlmTErlJU9hrIRzfMj3wSzq0RRuBpK/TOfojT94fOyK4u/wm+JcfL44j9pL7d0TopADB2vtZq10eF5kTlcs9Bmr6Z4N09SGRcPSAn6dA/t+sgcujkPF82BUqZc6ZX5Vdkgo17psakx92C4at3qbWS2+rsj+Oj9/3qI0l/+lr5GIGCiPE94B5aQ1Bimq01p/5Pb3wXC4j4uEy5Iyjx73ahShVcpVuzLAPMzx2ioT/Z70XUuJVQ0jWHALN+9oDzsQ93mKUVsMYhBtbuW0rCezVHW3jtscAWXpiOpNXVle38phfJEij56mlM5wRWj4mQeG3iMm4He42nzySGvnpqRjpsrQgqBC/yfLi+fg30sE3fRTJN7o4Mzq3tsRPbjX4+yv4gwTuVGr6dolmVUBgm7rHULxLngIzhcL1Zv/T7OyVNbseysu60Sgp4exy72HQgTYDUza1FmaWWzHSEUyeBM7/bRnaVxfScgYcZES/dAWEoFISIgQwhKv5/LM9Ptkm5/KRo61vGKa8ampMmdKuMNpkc3zeUWn6Ylo4lP6QYADQpBQm3CXOp37DfZK/NsFdnkaL5AXWU0qGV1aGBslkw90dVlmDHL741xPxIUYi4kOE9P+5rYSp7DQgtUm+Y5zgwDPbubNWpEKF/Wj324iFlLEVkpaieG4I5/6uirqLlqRQ6q+bVeGXoI51iOYvmp883hVuprE05GL7jfPMi7J+j7hSbhrCNNdRerj7lscqbO9zvVZfLz2JKyNApwGJ6d23WqoD75hCfiWd18qowYkRHeBSE8E+7FKMBh4U35khcvtIhjD4B/n1p4OLeMFZzUoEEUQHfUpa1jQgXD2RXpubQ1Ow52z2PPayuM8rY6ZIHv1bszic/RTqkkBcYgUvQShp3HsiJKB2ZysAWlMFYI4paud/ctBoccskrTFE7Wfo5g59oeh9vrcwx3ymL4v7Vyoskf5RZhYTZli59Cr3WWjuKwNJ0vjTQzn/Q8mW0qLU2LPb9zoh4UtJVYhwBISNXyDX2e/yKbhHF3+69DxLDSrNKrxC91De+XOQaQERTMMw/kjREh+UFypJWog48Motopvij+1vdkMFhc6fgVTVA3ec20j5IBi7WWiO6WcSY6mVEXAKRNfAw87OrBazqUWCupbiUtHp5IP5myE9HRwU0jbK3QlsPRPoX7Fub5AmxltX0xFaDygj+vzbdbdhdMB8JlIK4jYS2V2o7OdSCyGl/GbYK2hl8wE98BeBRqE7Vv4TTzTJcpUhjR6Mvwp+aTjEquRLwcOWmOuzWnZgzgI41zcRTeG/PytmGyQ3GugbRcjB6/v2iZ/5uOdRkmjEcMRv+9uBwKyk0zBcF6ZjQmoc7OUhNIGVhFpeJdYqaZUISopNt/t/3NwABFI5ORTbbIVqKiGfbub/L3j1Ci/h234hTEuzWaog5vu8Ws5g3BM0KyRMIOR4wgnu+udRIYLVBxuPF0RzLWXqcohh4opdMEwgtmJ0mIFitsEVyR4+C2S8ACRTJue2JH+lKYYTFjOuVHQZjgUPLmPhgADGLtAq275mWpVZwFhazI4ckB4FoLzwDzpentk3hQQKhqlf9KUqT8X/ygzhXLrcdUTupJcAzpSDD4zwaYqaaj+ijCkQRzdivo9VCvakGwA+YhfBMVXgxv69lHjtzWXzkZtQnG8+yudnQihBmt87idTzBvFdYsHNLVWfEPqKcBRzXbd2gXqEj3nggD+3GDt9/br75juJXSNgOXS+sZW2epH7kMWemOq0jnhhYRk/C+oGzez953xBzUu2jCDj+CvL2AXWSnM7zIMMI7m7rTPybWQoY7kvQ1hvL9Xm5zm1EJGDc1tsdP9Nhf6Fpno2OnBQPjd4lB0JxR0FKxeK/4f2u427NPEVvriXS2LhrMc+G4e6cm0pgZC0RFC7Deo6Pgkrni6DfMrbUK8L/KK7tvZJqZ222smB5WqfIK05bXWsr8nLAGyjTjO9OFCNVc4tHsuVV0VFbDm864NJL4lGfPlcLPxh6uOv+r8HMhBcAaqV6eW4aMvxx4XG2Dr1iCaEzvsJ02kOE5KSN4Mvf11iEFFKrRWYEUN5IS3c7FiPL+K7ik+JOdLPZz0pYpP8N4mF1JP/cu3raiBi8zHNj5tvE+6N7u/Rey6hbR6o8AvdBZK+QFoAq8/bJ2Bl5G8erOgXtMb13offHFcSsJ3wqjZXDVAafMvAz9S0CyT7EDyfRjDQ1GSYthndttxSGaSViKhRw9v1Ke4rK+vBTAQ4xFZAAuoKzMC3z0f5wk9tRMd8TUjV0ePKZ262uyICiymHzVRG5JD9eG5ZROix/ME2VjxXlGtKFYk3EAXCYd9x/6RS/6ezLNwgUENu+JvdyHxIxONzvk171j5UVI7wAQRQlehDROW/1eQ3DBXbuKkF4E0CKO5Gl1ObQkWeJqeYQIEWb6KKmlr8rhhY8A66ulUvaiX2TTIVR3a+A/BYOldpTF9pwuIW3/IFVrvRY1k0cnUVEbhKMCj3w0y8FxccKEUZHy3vfPY8cP9j0oRoOdyW5egDyO5h1/vVGCch/v4dP1MUgLL2euh7YwyHVVsty2SMxlRH+Ld2Wuv8zIlIVZgWiYLYYaEaY2Pe8C8OnYO7ZfxBXXWHXhUjRhwdpMwkscMQ00kmrhicRrsWNXPjDZzs6jZrxUBSIHILfaIVOh+kYxISN/gFRSS/m2diLyrES9PwdksZw3ilkbl3XOi/HReWrYX6HWq9M2wBBv8UmPsvXuH57ITA4/tX7zI1JKjl8Pv+tlvefPnnfoFGK98za+ygunD/6D0wlCi2l/d1fOazeF/xAVj2lhK+jSAR/PASw6oGK94U6jjwM4Hf8zahKrBQlwyhrVBaIKdEdXbc3m7gHYWnsgiR/zuFiol6i0YSagsG9auvNFyehj7uXyaQiRNaMnhzHBK3UaJPP/m4/6GJX5j+v48M0R0D9fTp28q5WQf9FZVPTwb3qnM0OqCdLB7CpKnJrbeYUnRLVYytOoVpVKHiK/lHb8pMikUKo6dtfLPx01WXjU6FLce0u1ps28b6qq/dOCo402hFaI4lAtb7ouuNv46DALZRZDN+65R812UPawRoZ/xf/sAFl/1NSYoSGxKBEozmamxWjbRRQ3Zx8cDI6oofV4GY+CaExXb/PnpTLYBpzDSdlLYd/42+VnBCllnRl3DsI+ynMDFKhGXUPbuJfWePiPl0j5D2PJRTyWmfZtdLaqWHG/xWqgEPb6P+91iiJ4HhPpNEGYlA6J1petxTR0OEXD/dOYPU9E6UZ7GUb7xrlpgcn3BoThSGFMHCbmvykHgGmyqusJ4ER223MJ9QFk45ojcxZ7cEkbxjhNbCrCoihgxXqO7sj2mKx/w+i4g3sVs6BQowa1gU/5bJ9O8A5iOBjzJYTIjvyuv0Hf7ls7wTjnirgsX/qX5UN+nUBhbRpsPM+/zuW3bGWNcTJDvWl5uG/tvEWsGiKsF/YuYc7uULjac3W8/2nz9i4EdJlVQxD/C60/ygSvgkwt45negj3tAwTEva494RTiVU/O7B7y7FbAKuVlLE8rjDB3S1wlBUKRztjK9aE1UY7dnmgKi6p0+ARaQjt4Bu81saaDzhm3JQI8ADMFt1iXmnxTY5VcxcbVEatp8pwqBGHcejARtWTPbiUsrLlsjBWPDxFbsjIBNTDqEkbewNZWPLsXvWQUAFGKGVjiNBs73SwnnVzWDepiiLjm0A1S3sa/QzyEN+0kkiGJCeMWGzKNPILhBkE/PqfEcqe57q6ZGD3Ppe5c0rQSWxNAhIXuhxi1hBnHcVCtdTuBup0fj9OA/dnbN6FqhSjzdtVmqamBF6Lmc1OKG9npq0hbkUEGG+1yc3sg/qSNBLUQ6mRC0EJm+b8906nLxbUoGSPRRXYJgWbe9saaCDqhOhztXpLGA6TGNOMkb0jZKxazT4kXU7w8C6EwNSVY3PCJ1fI4u5OIkErXiZY+TS8Rr0ycDAiOlppvBr6UjU+bJ3eWn+u32hh/teualTNwaZtNm3Ds9sn6YOZV/SMb8Ipx6A7RhrcHK8v9t+xATnmq+iCJaPuPA2RXwsXbXgWQnY/4nCYUmfPzTI5Vq5JmGPP8gSyxLmrzNXM3hqYRdJrXL/sZ/J1mgX0fXeN1/5mfaH0AYjcAPt0c4pxPZTefh3wRSay81w/+Z/KRKepWWQ1gJIb7g+Fw3xfqDPAPQcVs4KKhe9WUOm/yGZTHwH5S337Qeyhbq4kjRGWQfzWUtbmMuv2ig98cIB9/Gn34tZbRj7C1Gy/DxKMRSIX2jDqx6L/3FoQSYPKYe+N5hd/q9v5sDCGfi12n2gg2TWx8vlHzVd/jYyAxXfUC6YHgeYCf6hOt61YMYp62HhpO8zTYDjWSFTPD/BMPqx8yyc1J3jQdntyIYnJJIGZvp3s2fslofe2cBMwnyq7GACO/izv2NoujmHUcNmgroO78XlHevnrEsAmwuCdiJ7f2stGLcTbUKKS+eHbxaTqE/E1Ye98bOYBdC2kWX7eZF8hY8/jnW7n0tGbM7t3allKPdiEXV6aGrror1moeVdQ8179A5LwxVRZJCFu3zSwNy2G33nI9/aoolpNBtHMIxU6KqBx8If0zYY1tBRZmd8nDPqxxofGr01mB8xEOhL7iVOL4W/Joy5PO9yBsPk4NBpek1Igo8UTBa81/27qTRNmk3vJ4J4eW/7POaxZSTLRfsfDneTf76G/vSeJVMjtumWXUTPJyYBJOgpIXWPoWvUYRYRZ5rzhO1h2ya0MEoaY/UYBKPuFdwJ7N592oLKGIudtjRxVehuJ47tCqzWEnhdKqx63eDHfQrBREfxjxPLsRVPaOEgnm8Ba4pbxS+yHtTdeTRPMt8e0YVBSEaWzJAKLIbPJ6dR/aEMpEko6xrxqaW+aNb68DYP0kZ6HbqhnuV/ise43Pk7GQ9QHnWPRiA33JN86/TCbSkHrLsx1jSLg/KMYrsLjCxq2Vw2+tvb6Hd42zPXv0I7o9PWGEgf9msmc1k2R4h6SQ9V+c5w2/LLgFdVgiDXxFL1+NnXJfFsM9/1NOxLsInbIMh8ddkIdLNsh4eiypKu7ZCdeWWqwCfn2FOKeBiS2ziMN2vR44yCP9NihdzwKsgp9NKY+GZS3qZa5t2Ajw52R+hcxK1YI9GYtIim3FeZEC6W+ECnQfNsu8LiUyJH4v7Qh9nMV3HmgtqI58bRc9+0QgUqSEK2l+5DWljDTm8tVYNIQS2Z5PDLi0pDl9bH5uGr+RgD4eqZJE72r9sYaH5I6TSiFtGTcUEh3AuqY06xhzm0j4STK30i2qjcD0yVnx7jofKrc+qBS/Prt9VPZQCC0FRMjL1NrWCK/mTr6uJQndB2KyYbybWqNNvX8U3p3Gf5qGRhyuYHof+S/OAInTEbVGKk2x9zoZ9pyS51EAfoqDm+3OX2nWSYkpfFQzz4mc4juUdA42D7LlOduYOYrN1XfbYxdVc1fdFKzORRpcRbjgzrWWyd4dukC9S0zrn+wwOF/bo2SA9BVwhe5ZdCA4KDB+/MZZYlBpx1L+bU4Bsv5F9gQpBm/6DtunuKc3z3Of0zwW/U1Z4LLfr0QKSgyo/IeDMGElTv5rsrr5XVtaE+1EWbfE1giWwMwxG4q3wzFaHd6CZIEYC1x2WqfHdevVl8clmjzy3GgG7Hg2Nm95qEueg8ihnwvbLTpYSmvOJw9TXUKr+ddIYmIqIKIzOp/m1kxdE1ShWRT5sDuD5UoxmO6IjMxw0iHY/bCa0tAu7qn1A3cxRXrRUziiwa4EJabHVJwb+eH6YYHtmyn/zO9UZs88LFSBRSHeMlTSX2NpJq3opAuH4pKSGxdIqZFtWJa54g0QBCgBz9Q6SmqT7pYQQ0L+Jqh/j0UF6mU+RRH8HoUD5F2h8EpH4iQkuVVZPgB77XFpJ4/Ma5JeR68Zvfv6APbUSCbj/d+JyuPsp8ViLpz2iRjCGae44kRjXc0x5MfHCfhaTRrSIdy71QETjBl4Usmj+XFvpH+7+WKDSDtrTmiT9NYyX1gWMnPkPENeCxrAuBcNuIVz5YBWHR+DFmqnw+F0+I4p+8MuYuIB2vhD08V/Cu9m+58HwKOtmE8U0DqCa+dUsVM4zLnAbfzB6Uy/9cHaXZa7/s81t3MnzvFjJBSGgwRaQLEeoTDpmU0oRFC9EMJMnr3NsrVHHgo73xF7CYP+bQa5LDkXqF+w9nhUEZgn/5UeckND5ATp/ySx7CHZCuaexQOEV2QVRimaYsGnkZlLHzL0wbByXVwSk3gTqV2ZDNkWm7PVsXWU4/SMzYUOzt4/Ziy7yNPEcZr622HdzSv5hsqQyrid15ufACW1WjKWikOFcB7SErgU1nnzcxQDOH/r/ap+FznQtQ3PVb//THXhrhHizCFw3sk1NYplm7O+4NigLpr+i8uDou5lYIdNn/Fb/4U7rqk1kFYNikyjjzWOXK0ksJlbLifJPfqJJFdLdnx5Cf7EfDRd3ntB5cfMZ0uTHEk20b7Z/mGgFvB5+lC7dD77L5TTFdWpFg371+3WT9YIWpjzsKT7aVOFUBDec742/SbgVks8A46IwOHovQ5XNf7wiRYNcOcBokd+bzmnXJLWodU7sf+yAqO0uTjYQWLrEohfJ6zUVe3hiOM9OdEGr4nz/8HlXs+hmdScKC6T+9EMfMMny/QWa0xlGBeCKyImZ4AgPch83Wisn8tUFJPPFAtta+YkrMXyIxrTdJquPDTUi83/KGD2rsEwOQEd6vhe+t5zw+PGaYngT6B5gVIitDBMJLDhwRflDJUPwjlg6vpXDvemlQghfHof2Rne1loJLBxxY8tbSOzBwIv6kDEKkUXS3q2AriN5sWHp4k/JJ1qpdPScBUvVOTedx32QlkrcxsqpOZ4OIlKT3bz4YhdBYbXZ4lrjpIBPyFRkeYPWf62VDMWfe6JcC4gbXtAYgNwuyhy2gxdtauYndreQY0VeL1KfrFu28rWjF93W9DvvbfD7d8v79yh+6a7/8QdRaAWhVNH1/pkpAUQRBRShBQUuICSioI0khId4N0gzSCIEheurvz0tId0pfu7tzv95/z8H5773POxuycPXt2Z2dnZ2cNSTjaKxUYsrq6D3dLklhYltrkkrN5j7H2hdrEfokd3ZWRmOLaoKf8aBCGG98crO5dCEq0FtY81SdYB4RQBc5kQUCaaWKY02HvB6rloCzWk0YeC9AmvpN9/q/9ChuD/v8N/ZxO/cCkDwicsOr2mGdIZySmWqV9Hx5x2advSCyctjS9NvZIhy55Zmny5GfusnOk9a0qH7BrClSwmFLfgWNY5SPyIrcjLJSIVGYHd5be368S953mc37nDyOsNDt3btFdVYr+ypIhEvi2gTzYEHyhUhH37DVB1I+kUO+3lUF5YPVSHqlzEc3pMfwS2ZPHF8VvzD1163oOzzA2ANL11d5afS0EdNgWTVZCB98RKSYAmUa4bfkLvUEgQQptOgGmD/VwutlXGIxnhuFgo6MsfQQKlf9u1UbOXaiLKuestTqGRWWixzId0qTMXXTH3/n+p105RhsrZtt3fkY1dczg/wzDqnRRwyWGQ1lwjyGAYzBj0QlDBhwkYtPKEC5ZHV0FNY9bAXeAqWXRc62ZUygPBBf3DD4kF4xtxDZYXVqz716dGSM0phRNQ3ZNgOw3wDRuRsUUKjrvf7aMyiAZDDmApDcRfdGFnScxKPF+2lbH1mLybtZwkJuMqrOTxHqfRjjl4fKleYbF5JaPmAntLU0rmfB+FX3Mh1gzDsCBqKEcOFbMC/HaWD2D9kUNNAcl+/rDL0sjiD7LkfRD8bSRJshhz1LWJhrcL3ko/l+oCGjAY6D+XKplGLh2PuIrxfS18rkqX9GmmiqCxF9pVUyXDygQtYhqcGCyjh+wQ5Ix3V/gMVoAs4dp+79/i4nCjF1kW+MoM1LilSRZCxT55HOzAPJYaNWBXpgnyGuQwcEDU4j2xUqK/2TagLzQDs8my8pi81oqDXecyAjzndXeXSwHQ8cINwhYB6Vs9csKfN3TT6gsLWi++deq6dGZ/idDwyzMQleuvDJfRuStDXxYt5EUno7FtRo4WCrU+EYrtne0y8uiH5IyfSnxJfQeM/zldqHvSnxpMegJT/vdBSJJM+cG0vHHqs7fMQ7PWHNwjtQYWo3+8TSYmXPAoARwq/zd3+wRn+qRkpdwx9iArDA4+MF+SX4UHyPboBA+l4h9EF0kIr5YnPFzIR+YyH1uWz//ZxbLv6Rjf6ntacK/HTwfvkCPKE1pmgCBjBL7+fXz5eehMEj2ir0a0Vtpr0tkw6O2ivWxpF59bbyZe13qgTjyiOiZX+9LWFFD7Zg+95r6k/uNaU7IaAPpRUNANCC5YXxB3GSJ5ySCpw2f9lVp06z5EH8Bz7lvOkhxrtoy9rQtLDnBiaF+TXxK0pe0Z26bVqK2a36jFB7WwHuL7HW37H4EikUf77RmLl2TYOtRn3FjEySmt/tn8Dfiid6Sgrjfu9oCOXv76d+01aAiyGrUUMOGJLp6wyUNIHIK3/UtO+l8o27BpMRJXVXrZxAGvYF2pjywLFmJkimOMGW3rFbL/vls6fXmXEzUWWUrRbSWrC1TJ66fm5eFOLfmT4Ai9nOMXRh0of+9Dbbcv9lOs6IHuiOtqvk1C44YesyGsAWH97kSYKKnn/K3Bjiq8xdIIIRtHeVZE4hghkYKzE4W0YOxH0fGVUR8y8RS285bIwviTRa/lv7WXl8mNkTgRfeMg8nPFCoorCQMe0JeaSsnswdP9q1GroCoPZ5AcK6ispVXsZhtyh3lZ49sy/VJnB8IyXwot+f8mizQAjQpwb9uaer4a9BrfALidh9xxCl6+9zNVO9KFKnWkhgVS7plBCAKrEkP/saDleUZcRMI7sKIA4S3yBsBzcrmf69+zl9IicVSYBYoHyLyz7nz2cQG79f+Ls0WKXoDRgaPMtCvuvFbyI/2IzeS3zPnivWh9QxW2qtzXPDsEwnJ6KN2C7EO9OGilrndfIGx18AIHt47go9EIXXV34jSoGykz9KQijiPV5m80mTvdHa5vUqVYQ/4j0T4FHLT1RZCyxLQB1zJmxyFo0iiNU9ABLbIEvzjZTtQrmHOHjsIb6J3C8gcL1gSjxp/Np/045BQeDQojvF7coNGUNgAd3v3M8+OQ1YGDzf1MDREw8zBTyy5PFfR5Fon/MnV2rxTRrXswhTbgEEukFUbqC6XaScUNc5G/NWGJRBrJQ1lrWbq2ayzMf5Ksy5NoGsDsDCxqFnQuQzpsM2NqNRiXLRsmomXotYahGAER1sYAWU7sXsJh8q4vz5awPSeSPuO0UPYfqEc0F6YE5aBgkyir0Rop6XuLIgEj70rwT2BgnkUwdw2iEaseJCFLKi6Oc6iRw9MHfr6awaV7ZJbCtCliF9dx0ss726KgS/pUsHyEsl86uz+y0/1EdzaetqMcd9P2o99n+ysko1XZ5EOVl9b8Phvxd9+5lmiiJPpc93l8OkCSyKxgxtS2s1/QX/EfOgDaGon9ijDQliLIQe2m2538LM1pEityg/p4H51L6JWvhniICFzw0qB5YaWDHMG3FNbSe5pv25HBLZv7amcOKaGB2IQjUa5hdjBaOo2R+Ec8qXgNimnuAukb7uok2EY4RXtPiRf8pImEzfjj0xyjvie74BLbGqrL3hrXEKd+rmXAVd5KH1JayWE2pGI3aPfoT4u1gpZJx+IYJ0XTE0GP+7vC1zbrxjKFUvMkv30xCum7Da1WA8/DhljxqC3M7tJqiK6WptSUK23KSMd2iH2Xc1yBD6RkwpS3Zwyy4VrizLl8ZnuKold1Dv9wTVMdDpIxEDCbvF6HeXrD4C/Poi+ruE4sfUxomNdJrEvP/eCIUSohEfklw+4Dr7bYsby5vfR3GooEANSrVWm0Aro0A5/Xh3AxtP9qCFofH0n2ruLTvPvsCgfuq0x8uj4zAuwwZfEfAMtGfNb9+k1kwzqqS96EdtLS6YkP9R1quDOS3lvoh4EjN3y6ebHdNz7kBVmxVk8b5UGmESxLPUccXkv1lC9ThTyFdZXLA1DrH74US1UJLdTgkm+LAynwBPCJn1+zXy0AIoSZOYPtcatNFz6kEfB4ZstSroWtGyc4G0dgdvJCEssK8CZSivMmLdaINrm1PuVK4H85dS6Xv4UDb9xIkX7yWd0BYSge2BcLZKC/5DmFbSMqVDPtqGzkOBWC7QDv98wjcyw/7TjLNWbYrnRae4N9YmPIIt7yhxRjqT/NKLOUTq/SmJFYihHT0J9EHR/oF3l37GTleqheTWM+M8Q+gQNmd4ajv8MdxArmIvRwTRDPuFvyr31UaRtO1+8Jhyu4+FgKWCAjXHUQyX/oG/KG9WvZdQ8oEXm/X8rhV+fuj1mS9GzJP5YfvkUYYVNfiUMmY1ZlM9AMVgWXxxRaQDqN9KLBU2DBTa1PlzdOL7B1IJgqGVqcfPvIAT6oWP0CDW6/iyM3Ze0U0wtIOsjc/EBZrv8V8lImL1NrMGqIclhZ55OfMZ9DqOAVF6bt9jU+VP8km7UrwU3jAiAsMnagrrPZTqAgK0GcqAlvRBGobqgS/1qx6gaWCK93AnfARV7yPYkYtC9MXXd1jQEt3avu733Ex+3g2mogLgqVKhbcOSB0Eg9ea2fQid7NozQnEsaUtQSk12L7twp+d/vximoQDUpp9F+LK/lzxZPWNgHUPu6SRVEuNqOI66xm7/q0VwtcdgaeBu4XMTShlC9N635tvhfIX+bp1kTmibUPvZlqP4dfzM+zzjrZy+abtNg9wgDKreFS25jeQPlxSF8QVm4Pyt7AjpawvVyBXwpvjZWt3waMN6lDw+imNi03UzmPlLY3IUnEJn7JCuRYXQkjIZBMpC55UlUjs7LifIRYsHq6RmubxTNbmFnOYggONi3pKbe3yknUh+uWrJrkY/FKB+DYU0uploqW7RqKpW/fT8z9+0PPs5nIWGaehQ5aZT4bhhIECFtL+PuX3OXuEGLFjgu1J6b9VTpirFTmIYZGnK2seOAbI9Keja/BmtNzNcE2PA0dhvxRUwmvPktvvF6zwDNJjHWvit9SeFzLwLO98H3f5uxG9+nFvE3M0NuduJZjlr/QcDQJmfAlBscU0a2kIxVmzdIks93WuclohMXWhE4k9IPkmRCEuU0Ka9M/NyNafUs99UNf+53QN7MLjZHuqsZUNOVZZDFLOjPQiohsSGTB6nR+ef39KVOW7F9Y76pRLN+/4KbweNAPvyrn4I3Iv6uZgAMVb5yc6aw/aFcPEd5C8hGCw/DnYdVpRCb6ryebtNNFl8n+lQrBtV9LwC1szk1O9yovMwETLODFo54EuYAB8Lb+f1qiND3VKI+aStF+1I/K+Dc/CcazycPtpMYynz+CRryJdTWq/oj0TsLH4TNhNxG6CGonxFDbKBm49cVPwhdElzC2IL1aSIZ4Yq/EcAwLhu5Z9NbupQSshgIOqUMV+JmxAB+u1WwnO5QSonsoPTxYtXxF6SyUEwFtNRPhZrC6mr/TZAnyrjfvgFi49yjYsoccqwYlCpqUDSqwIXQwF/4JxMY2oOOkd2AvmjaW2O7mALZ4qnLvRATAddT+mS4U2zKR/+qfRhsCg6oXv7hJes7+MfHla5fF3zp1QZIxvu/X1L/oCfP/pqYDlW5kKZGuazWIrYfJ4Vsu8qPiJuHeYBOjfzPUW4j/tkHHJ87mXYwxEdxjwqpgC2GOUYWCMGnISH5yX/XGxOHdMsaVe/sIbYmuJQKKzlKt46qrNI0zS32WF/zC8KLmebXZuAN3Pt7oB1OyY+dIOHYa2rhlK+/xu266h+01FS8vW220vyVN8vGODrSjZnjiwfvaujXQrp4O2ZdF9M5ihP7hApkj0kcDFvvH9YTVvEarII6Dm5lcPPjXw0hu8sLWH6pLXN3OttpTJgBPDyrWefMCzcsxJMQeL13v8hTmB9SMXDUku6PPRuQxeYjVlWEa8qvGfQrs783jeTfBJc6H/MteJhCQXMjx9eHCivhrCbL05ne6g+nixZ2dAyYuwRGhzVoyWHgD7SkLLcOyVZavNKjLk20JnFTiEdUgAsudu0MKWKHbx5twEriw9+kfInNr41KspVEslNvYgtOauWNR1VhYHg9pvoymWdN7Wu39oui3H4ClGEz5Hw919N853QNJa2e6YetgE1sMgFC5zIl2nAcZLFVU7+6ZShS9RBD/EeQgRYZiQIXgQxZMVF5BJ3VBbu628I9/IKkjhG1SOx9Hxsgcnp2OpFs9/iZNT/qW5GjldhIwoLyP/mEvd3zLESzlPf4ZjBgzWLHLa3URrHebvDg4DQiZfKRPSB7dEOGM62lGXUh3L2ansVvHb/6Lv4qAX3il/eQkiVRb2ZCQ+uhLNkmmo+AnR2rb1Zm0b/qXr6wydyRQf4r9VoicKNS2M6pyvITxWEdUCh3JW57gBUxxH/Bst0+2D9zS0XlnbS/g2Q9M959XfnVhMPLxqCZ9NV1A5Z+wD0xUKEt69+0yQKgH7WsBlfKAKPiHuz4L7TppOvoLUlCLSyx//YfEIZLVCdBv5ArpznnknNX0KztMBUndRDB18eY4RipLEyGzlh5GjnK8pFuzviChpb3mlQW8WX/lsRZpNPH7gdQjND7IWvEkTnaLOSG5jZfC0rR97WP0pftBhmd9YivJF8rYBDBnsPzOgeooLJ/ploQg+tHFhYAW+z9pxDZWywYnJYdo0sqWPlHE7r4lxlJJnBCO/yUF/cZM5gK5iMRR6yL5ZculBegON+7irn9L1MLWDuVbgfsqkGFG8TGhHMTUflyFYFXF+ofACSRrDbQLjcbnLbzIIr/QZtL0pLgck41ADZywxOhSGItlKj3JeP5kYRmZ1bUeVpgHJpzctk6sHw13dp/AH15VbjsKx59QYewGRrvpFj92nGNw6+phbb68tUGE10veOcW22EzHos2UO2WZVF/5TNYDksImLkEDNNd7KHEn/I1xOcJapQ/NJ+vefpiena0xooiEcgz5QzfdfQY6YawDZMD87jLdbSAwLqdjGSNhMNsYofFG6qcWOlaQX/I8wNzkJDCw+FAwt9Hn6WhNJ3dxRg0ppfkB6Gw8/+aMPRwLPN1P8HyWurTv7L4qS3+rEV9BHDvYEh305L8D1Xc2lTS2cF/tYQeVuKm3xFpdbrp4pcjvldLmuu25TETEenn3DzjDqZ40NcEWIx5aBb9vc6+FdO+v8kdoKfa3X/ZpOr41WHkgUTiaLE+8aBjsDBazQxUf7gFpslLBUSQBkqUHTskxvitz5SCN5GjA0GHhqTmU8nZc6bgWa0M2DjOc7irPz+f+PyMhi/gmiUV7B4CFD8BXH//wmjzFliRsxzwyt70ZDvIzjsmG/IcsWdUq8c+JsgA/gBYTsHZnjjoOjOcHDwFFeo6+orf+1ZySyamjB56QnSut+khde1xfuWxpwj9qXi3Gc2aK7K5Xst95WbBo3XZAs1/rly9/U/RypDjEv5MHzG8moMeSA/NirGInaXdqkO7MZvwzCTvLuGjSnBcYpLkXIeiHK/XFBkoxCyNRSW7RdrwnNYqHvefEaZSBKpKB2Qd1xyL1ccMgRY+NZPDUUgYjWZ5pLWlXazmirmopZhOpZa1pqz/aMWIxETQ1os8u582nvxLTHiEFVeW5cxouGXdpLgWvvn5ATCXYQT4f94bBNOQcQzIzVapT32J+51Y6jbwh7xfyNoqgEm3dHP9dkmQ2q5+eCT8tYvS0388aWkLzDWDwiWor0yZ17FQAYxMocm4BauJMWBQdhal80RB4m89whUXxBf8wlb6SZ0a4zE1MqgtFL4pCt2HsA3+DMKBlul7htWWNZtpbgW5rj2asjExieJmXFT/SA7eqKqJi4+Rkq7Bo+mM/hhiTnM5j8y3+ZUfLuy8TAAqnt44sLuIDAUjGd3wb0lpHGhYgm0CGzhIOaP9dk1sHolFEbctrbu5+B06PtSgGbgOchNQmNHyf+4IOsU5FIq0E7cYtlWWT6mowzu0ncTC3DR2K0mdRFIN17GAxWx3WytpoYFGlOGVDQ6i2zt0spqZc+F4JlONBPif3HxlWmBQj4gZ/ZyxMAq0Bzu7AJwrQzxl5xXE3Zq9DHshqLtCkvhaetq31GvP8XhwzCJ2QRZ0AipNbggAKqyxjVw5HNz1wxrzbRopM/K1g/9E+pBmF0ASUujGqeez5ZPuqs1KBYgsGDdTAIbM5+nmw4BN14XrBKgI+yznCAQGXttiiRji4x4RvK9TGEC1Ufz8kT8Rt+Nml6iWgj89SKN9pI0kY8YWZAvthKxUSERc8vRtubnhKu04N3SLzpYGKYyLEvekEzzI+B4Kv2c5FlkqtUDkySfoF5SFj8bpqKxVjWlavkUz/4EKt44B71p6fCeRBGe7zxQRf1eD1QExrbrIy54uYbdHqJaG7UpOhEkaGZ7ErZDsNn6pDYTQV6nXd/Dnltr6FXZfpqFEUBNxe585Cc08bqaGr3LHXDaoskYTdMXdOmswPlx4jorZwHCoxNV8Vvzcmgm9uxspf1C2BB/zwl1J5VMWQ3e+vb8A5BXs8tDeI8Qxu6ksJqzaSw7/tD8Kj7REkCRJYwh1FmTB/lGUaJo/Wo10f4YlIXGCRdYP0OOf/YXP9kRxMgMN/U2ePEx+/bb7RxAI9Gy3QILx6KJJAsW4XZnlw5E0Tp/3ChYiVvczySdBsXRP5+otQkIS/xcLaOtlLVObRyY+XDHnT5SrmvgFX2oJqdLrFhoFfMoCoC+qo9DcoQGXMth6E2+fRf1Jz81SC6I5ER8rw/m2HYXIZCjVyC/KxHet9YDIC1aRWcEEbSvjppXz92nySAizX9CSR8yguks5lquo0HsHo7wK44V26NEbXeRbvaVmtPDA+7or3xYFMhC5TCA8YONzVpk7SJFQkrXN5KDD2UMnzbdVwB2JJH8w0ZrSYvlFPbjBQovYUrDZdFrNFHmHh+6nEuv268mCJAp6FVcJKoWUZy1W/EsQJQ0p+brsMcEfc9hxqf3R32wLhE7iQT6GwRlMALhDYPWtB1yX6NKcbm3lQ+WziPrv9HwSvH6Or42/WJpkuqk9+uvSv6mciNPc34WC3FooJsj/fhQ44uobIuNJrUTmCOFcNIt6rBpBTJjT7MNprYxQdy5uzu2ZOizCz0pF+Tgx1fesRKyl+4mXWM/7deBRiuM3Defim9EJoVW4NMDQxQRa0hfNQ4ymaVbZfj528F6nr3hZdVKedRcyRD0nlHl1JkXKNoLCepbQKEsOprb8/SzyOjy1YiovkUR2lK/UxwC6SGASt7lLnkufQAIc8LYR4NcsojBW4fMHb/ie+LKN1IMYxupT23A4012YUhlEYBD9/ZxmuwV6IKDXXCXFfDmbed216jH0YYxsDgv2SswxNa94jYnt8H7jjYR8vhd8Cu+WLt5Te5hWXMzB1vhC9Dxz87n+smJWxaaZGVUSnU4coTea6woGhAaCsS5PnXT7yOHX39NVdfCQu7lecPNE1YrrcxQnonsGpaNn2yiAgxAXZ7OY5vAQNjbd3PVHU2ic196rTUzEKiCWyxFOjuxIKKlFkM+UVY/MnYlz/7lMcb5XS5mic3FF5OitE7X72h/shIqM1H/LlTNWatrvjkFyPNrlcjmL2oJ0lfFAQtaCNvi4A43AYSaf29vqQN3gEX31yOGZCQ3aTLfEFZF5EltNJvDJKz/8Mw3XbJH4lIZUB5/UiMWQmGY4HMM/KWVWeBx4OKdNGHQRWNmP/Kn5btbeyCtE/W5xSkoVpf5ZgdknbCDPbqXhOll21lNG+EWrg4Zntm58hpKcdee7QoRHs2igLHJuG7LdFy5xuu45xR8uGqGU559o3W64uKI/m/v5dIdr2w6iW/XCH1uVUABHVAlasu9LINNVLtotEs20TNoHuFV4nyyjUm4WFB+D0p1tkrFXG5inVM3NOl2EOPg+7UW7bu/CiFJSEMpu/3X4dJoJWYBrAQXzRFOqDRMbFTZYfQC+ioZHnDjG5PCum/ktuLTpRc+SfHffLinRuP580/E+QYuKECtRixm3eUesxoiBT0zmGP63SYDBt2T0/X4cEci5NTbffgx5R1OD1Q/0OqSND2Nrg+FP3JFgUSi3RqRWjGGklkddhGorrSijy8q5kYESYKnNgHSNv7kar0srlL0P9yoonG9/oBLdo7uWkgdrV1NVFHIZNRCQJzjuR4fji+9HlIJwjiffc6xHW77ZIryIKxWwps9jdyqA1QSKyAdTi/teYT+4thJePyEnxB7d/vWKlWAfRz4uX8mbr1Jml3g5wU8sGEo7obs0QCqr/fvDIZLgyuwMTpbWYoD/nDk0XZju2bo5S3y7opDl0DN/vFfLDL/oEXtWLdhBcnJ+oKvvwzNrF4kpoRAxGl8mcmzfrKYgs1N8oOHLfu5L4JPjJKi9f0nkUuKVyMJMW2yykRLUhuamoyw+SM2v2xnXsBLLFMsYDjslUUQaNtSNqK3iNED8dOcw23zPKZ4FIHFtoOppQbyoX8o9azIJaBHJ+b9JzZCU5z2FgKqYUOkQwSeUwc+c5Of8JabxsCD4URn1mG3hnx1olCG7mFjTErjEKA3zjMqzqIDAHyzqiQgxib843SAox09jzrB5qVBaOttL4WsI69uEAYGtIO/IgoCTv+zWmBG184fRS8H1vbyTZLfu7yErhLmGcyXG+oo5F7Gosk+4BRPUmLZJuonfEj67JSaHFmyu40dnTUsb1J96lYGONWZv1J0mROAY4HxRehOOr2JrTGArENPGl+4LJ9djy8kZpaZ6waUmw681Q/x8aT3XkNJ3tPvbYtGMnEPoIcsL1O5VExRkDyBdOFZxCxsY2S6Gob6kd3BMiQwN3WQ37YFBC6rQeQlM8wtS8kOagmkpJRytZIM26q5AingINxRFr7Y0BWwMcCMyogsjix1KTjjF1AxpH6iGoEnk088JxNJKbpPilI9xkdGS9WBaqywwfCBsjF786HsvHhh236CkVhtjMnQT5v/BK4PC3zu6+RjOoIViNFlsxLWQ8fjCButyX2tXLQBXhRR/iphLemCcZC4Dhi7YrSWAD8opQ289oPsno0/5mT+KVB19NyStSdc1nNa7qU3PxpNzSf2PYOeQ9U9+9N/qfLVe+AacZKAp1PetPsWnjK7QGIaLBKyp5GOUxS0l4/1aFTCU+qnvRQxkTrMyykk14J3pE6wS3Aa2OdRUDCQNJ8a3FRu6Vo8fU6NH4qiNtxZlolvUMFr6L2CqGYvX/F+U26zJNdGZ2vKqV1hmN2kSDaxIfL1dWXZm0IrIUY5fEpkxnFvozTJynCDbAjJKRHcOhFl8m4i+bMkfRh1rBMtDXN0SpYvCVqA4CrB6qIiUubD7ZnPOuCHiPk/3kmnJtyGdYyBS84th5WxA+9c+1TlorQR57Xpj/8U0bNBqo0BhesOmo3s479sN6Wypq3VlB0ML6qvgSfVtpJYMBpQ2UsuodiwL8HUAm+2zPdasHUJJSRB3aN0R36Th+vbalGI6kq3I1d5vZNj69HnWwpJhWdPCmtGlnEB0WEemf/khr/Qra+fIUu+ykLB4rLgdtfFRJ+O4TLhFtc5kx24DSnOon87UoE8iLSwiSMCiB6cGk5lm+0KbEL4koV3LF2O4jRC/us3P/kUCxqPWvZWNcUcjZrtz0yXvKfmUORB3ubST0KjSnKXs7qz04woZfu9CQR9I29G1lIWuRyyuH6cR8n60InfqP3sznj7sTG5iw1ds4rAk43jbfrLSCiiZguu42PyUt7wKfTJYnZG3J+8VfY7pH6fPSljODIyY8jS7zNKJ0tuxOvnuWqokAd8NM+90ZQDB85viKRMIn2LmyhYyZBQKWUocUX6qrHy7G/WkF3TR7E45DOPIdXkrAXks+AR6gxjj3yYLwRAMth6gjeHvZHC6xHtiyO1SVA9C0zh7ENXo+yEMA/7YN0Rvo0AUKRd5T5KLcfM1t85mZhvSrb3wYpykquYj+F3zdfESX/94Ru6/0sm4NfCx3wYrt8H562tdQI8AAEAASURBVCqVCatqcvffZKa94Ak2/BKx2qdIAGGloWh5P1i+P+97qYsLyoT0CE2VLDsxIo/mN1PbwggpMtglVUyJMggZSNgRUl5nZYmF70ljF3l/IVjRGbg1+UoHXL/ZDSScBxZI7x45kIs5Y5UlBpw6pXsQ820OlmQ731qbReIy4RAJsH8YNRShzvp7N1if9jIeAxrnkzfgQvNzK/bb6UH+TDPIs3IgHOzaSTI0+XUZpyqGIKGkcp6zLLepXpXOxPtokKNJXfE2WQU22nbP+CqTlfc77cZYh+7goyLgGal8T3ZquGC6+CUxxeG5lkskOi8a3AoNJbnwVZ/rU93RlqugVtW3fPNKlSWqkwOk8V+kcTINrrdKGaiJSDX63ffBvuqtWjGXQoRWO1bKirDAXNRyNFjkrrHNfNAz9Fb9jQNMUfDsFQ/N4mMFPgcC9M5JqjWFOvgi9Lch3EUazCFw+EyzZx4KbZmhSVuV8bee8SltmzllLr0BP+IqIl4FeXjJWUHmJOIvcPegsnyOhYi639ykiIqdxf7iwmu11M17fRBDM7rLoBOiPwKIrP4bQo/ZXr/s2yoLlYfflk0TJDRjmfjhOhlpVLS5jr5tTvZhMGw+tTAJGwM9x9YhiNkP8VTwS0b725sR2f+taKDczk9VmhVJegcRaS3SbW5EXXSRYiaW09LHJg28PO/rJKcEoOkLa6lp5X3/s8XMcGFJBd8wS9EsTZXl7lKOImvlnh/KD4XLr7042t1Cw8LVyoSOdbCQWSUrNTK/N4VzIwuTBK3C/sf1H6m1GauhDPpotRAPFJ2ruQmm2G+sEQY/dhBk8JQE3XIyGYKLnWuOgKyANPTOFokVjHm0pP8yoylNxH5YHjqntbdYQDPCFaGbN1a++0KyIGknBKabGHgOKJnNFnZwiXDxo9UYfqDTl0+tyMA1J4O7pqp/HHp+RdQwVgfrpekFl4qcaatJkeCgiVhcjNez/V8wBxBcHCpoDULowF3Kvc1ksbWy+Nvb8A1X2pLpMmAB+eYGb79eBJqnOQS3hDMsckP7yKTLWB/vf+SdhJP1Q3jRhQT17M+zW2HISvzUQIlMWtrZEB+edRJpDZv4jF6iqil9l3YL7iT8fKx+5Fh3NIseKubS0OYQTvWYRCuIqSa457rAEqY85dum1gLi2U3Xbvc6amst5Tpwe0KTSmuPB24caA7xJaOOFPVnoBwg0aCEEhrvGPjtMZ2AjBYcG6gwfT/XgiPD0HwpKNOLbLzYJ7KMdngKFHcW35Plre48YS3bzBIEknmtKGt8jRA44sYWDEJa9LP61GYl33nASTe3OMkyoT3I70+KrzLpKD8iKnPLj/iJ0X1tMl2SbIOqy15PpPu52/wDQT5R36vZWsjnnvdgrgZjBFOIpEqfqG/SrhVbU/7rbFLpQFiRJt/Z6aQVnP4+Ub+SdaNs28AokOqnJiJiNTxuuN/0DXkiZO+O1ftu/uoA/yCZim+SA3fohMDjMFi5KxRIlKXLwLfC0b+XgsFZiNZdIxuO1NP92QbEI3NjJYSqtJcWpGapRLATJf/bVlhS0fu9sdIqbY9s9d5/b8fLFZpN3NCvSNasXCO3EUad9UR4Bp8waw/itPichIf+uxHIeymoer82hc9YhEGB55KQW2L1oEY0819sO7T29lKcWJP6L3SHbhPBYBU+E0+CLEnIEEMz9+vjp8EoB0uKjs4dcsWU3RQRUegRAkNHE5c4Gf89f27AGBMPKejvN7LbIDJ1eYqV3nki3yv7KrLwR1zGO+bhIad6Rlx2UkMX3ZkLWGkjOnhijrh5/uBYt/oxrPchDG9NsD4wqBJI5VTbMN47iBrOHYptrPFXqnyKYCileGsTGNhSNueQu9E8tmU47Q+mBN1PyFiOnFTVghxmgugW8smYxB6P69+2IAEhx7mM69JAGTdc+66c5glIe+nDCVPbc1R4PEn9yNY+Xt7BshjSDpj7/n4hX72i3z9NADyFOyMf5LOjnhk4XqxsUMxXZMm2jlGbhCmCDwq0JrvuVwlmrxdsZ1JSr5eWyvwnUnAclqewzz6VueNMiqeGflY9ckGUS0rwOSx9Cr6bvidF+4dMtr4qbmoS+5f3ot60lpzENwFK4Ft9GNe3Tbkgj1WaZJoE+vGL5Ecfd03P4JlEx1vOPbho9VSnWEuZYyL98Vlqsj7mqxFj+Qni6ZFW10Z+7lkk38FUBOSrmOBKE3OBqcg6l6LBEGU0ywJQkm82y2omETuRB5xq62PTl87+eR6Qba6iOOhoH2og7Ks1fZaeYoggEJvCP9wsK5XjFNBJNoqFSaMLWDoHlM3zH529zUNhfYIo3XAyKV/Zf3TXs8Zag9B7vT+mOHJrJLUHVTN/bAD88RhlGGydsbuS18oqe8NcxgqIsot3rskM1jhgn1YRku9gcfzREF/5P9WILQtphFgiBJEBiNTL7UFnsV4TQXzwdBpPuAIFuGgdQFpVvglkR7CdSx603RonNDmY7q7fK+Kz5/Bn5jEK+JRp3p6qr8WlDfeEF7FEQ+bmb1xrjZkJNesjmvn0JXoh7f5rFyseCQV3uOYPQ6SVTMwLLxtcDsaFjER8zcTu8hXtohZKnzGbrhodeuUxz0ytyyB3YRMS9rrCsJvRnmRzf8qTWbuN8DxSYJ1SgiNuNtrif13XJp//XgTlGfjzKfVwwB38+zRgac6xj6BUexJ5i/B12r4n57IsZGRqAjpjD6wNQhBr5mdhGKFQf7Ote/SinjlJI9roSH2uq1T9azc9pcpD1XzTy3BxqSSF+CFw101UQw3VpQXiXCEmha5JGCNiq90mBky4W1lx+d/96JaE/NrM7f4KlzUBt+Vz1tBOYjRtP4HGjYSqPcjBhaQJ+P5oJcT2U+KYVTYKD2RBVIwYgZFkXI4B4HM1tYlC3Znur2dxMEiKPbrxF67wBUk47OH7ud30N/mS7iScYSKdNagDtHHjTEojOPgWHDjnjyzko+/FbpgrCyeRGN4zpmRdhkvoYuPF0LqAxRVs8OHV/EGNLIqX020ot1a8xwhWYAbUhEyzyNtzF/2dVM5zsPtBrgu0cEnwfd5R162fseyOhPQQ42AvwYpnY1gcLX+kbbo4Zfxu055bKNai2ncLb/qAtG5gWvrM9+36I+ed8gF/l5DEnHNb2crysy/22PYqy841GecEwpEAZK6PS0f6uQ0moFgKhZjIwcHOFlnbEoQSHAvWk1UO5Gcrz94NCk9b8l0S5fZhvwVwwdvwBP1/5i/RQGTzKKhiEWUhgC/jhheG6wvlYyRQBqpO0oL7eO2vWVhi7vB99lSp0QmKFvJXRkEaZ6ckt4aF0IuyWgIL+4MlMfaM0zq4PSY2x0U5RH3ucalOPIg9WL7dA+d++NntSAYEh11b56Lz7AhtnvmUfAv/5VvS2NT49dhlE7XlbejhQr4vZjggrXvFMLsflYbIjwG6WDN7IG9JZYPBjnUQjGqd8aiBjwJlYSYxQ9sVw0UWbKH6qK0cCdDyb4ApDhyVTqfxaSxUYwtTNbNjpeC30lAt4XI2s6pTjLqz9iTIXdPTzbE7N0yHpnb8logmiPxOE+10Gijh6fij6ak9TMdnvEzMLggZzbDcw6f3DrCgzh1XNiflDPOYlaxj0Ti2IQuZIdkkutjOxeTAvMQGNF5fN/eioWaca8r/stkH9IdWqxS06BrBjcYjjX4RwSugefQETttNmMaZD3Y+L5aeeeaKrryWiUctk94Cj5qrFcgie+PfcId1eWPsfYyPBBOcZaQnVxWQvTl9ihnIKQ257i1t2KKfuDQIEJv4Cp0BeiapyFwS8kkCvanEKOUFDPpQW72abQcKMxBf9bE6M5i2+SiWpAfRBWRJarwJXCUeJPenxj5/9rjX6bTRiItj9hKACdJ1xZpAVO5X8Q1XUDqhun/s214EZ2W8iQjTEHyM87slgGETBRDBR2LPoSnKBGtchZVxsl9aDeBvhMt0eVjNkE+OoehP/CALioBfB8HAwrLQk1oAEFhzHGc0zzfYHAnxNYb2ABlk4Hz2ny4NYJISyeA6nAAv9nf4HSr38V53f/wuFiZ8UpHmemgV+vNo2CDpgrjpSeuH9QG/lDWTyRyWcoNmZcHT6KnZidfMJOOJE0vTTLMxO8lEIM8kfPlIRZ6p2HPKJdtBIpVF2hMoTwzH2gYvPaU2MR/eUMZ8XwSbw1HUcVWAb0eK8nJFHXCyK+lKw/49gOzr7bhgWgsR+GdpAiAB82asrI/VQTYhFVgqAEH9O0Mym4nXj7H3qGjp+NUSIv7W8xPG2RP2AVbngm0nW6yqGJc1pBrNurJYieMSMsQH/DuaGGMlL2rSaBpgY3zPNkb4uhOlWqPHYyGXPrfKiGDvaBLyET2uuh4mb1tIuY6/toAutJNU3MR/6pQKwObruFUaG8OhMk2FDrem3xHo/IqlgHEqdj4/M/UBX2kx3vesf6BmFIulx3HsaZgAxh9QAGolFJNWZqwuI84h2x0TzwoxhhPgpWeQrNBKi1qBZEYZoKrjEZWbTUnOX7E48ed2UHZV2QtOz9nrEEpaACyC33FEMmeXcLrKDzRzdwbFPI7Pd1artUSlv+zPDsWHo/40u/hd0T5qItZG/uGEFVkkhn6X1Az/Y9jBHIaIS1mYQ8NL1lVLD3L9l6MZIQM70LliWZHe5VARhpHCXc+lK44c95q4+zCy6gPVfoctaCf1dSWEW3LY1wJjMjSaNn5CzT3I5o8NXPxlnrY0G8Xc5CdFM8SAzPUTNznY6xvCRP6q3a7AZBOypwgiWZmv6No8JApCoTVcJfzvoiDNKtz4I5drm1Kgql1p9TyezCt4GSJrEviY+YwUPP2q47m1NmKwuoaBkRGehfwb6mU+cxFdlWxigTV4djAADRIrRWdSwgN7Y4LbGfN7Sh3L3JyPk2gifCWKAe1Q49d5UgrprATkuPsXvDMbD4d9ue4X4ImqoeOEk0WYMPfDPWm6IOypel1xoo7D/ODqjwnAzylqwn16EffQPzXB6AEne9Mt1PtWPIqGA7SBatqrLVgI0gFRfUFV37UBYnTaWGEsnk4S7eAUjA66tQsqVIgDl1SZVC0ockW5rziVpzug6YDvpoj4unA+ZyEe2OUfm40R0ZQs/Bs+v7gZWXrBB2DlMbRX+meSQy6yGB5RJmXQoqM9E+9ikzcPUOw7WV9l0Wvih/7aK3TjejA5Wn6PsXnXZF4TAP41nel4WYSQUGlFzNfzUTChm2TyW3vHH0ICliuV9LMU8xWk11pe4gAs7bsPHIdhrJkYx1/qb0/hRCSV5sHPVXeT3tT3bCVWo7Tf9BPwodHWfAESxAub3cp/QUgmxXMbJdEV4/6ZYAFkeRdft+DQd6KJyD+n/y65TtSsvkQ1HmT5RPpe+c2qkZ6bfG1GZvrj6uSbWYT1yVNiFyAucPtv2HcNSq5s+kBf/yS2RP4PTNcrYD/v+y2n52jP3IErAHaOG4h93ANJcU8HrV1FGdhGOpHyabX86jPzJv8Ry6CwAyeQe639UgZX8pOuxq//qQhYLAMyxueKMseurcmIVV0GxHeteDCRlIg64NrCritp6K1/R9+HuY2RlcLATBRGVHRcwVrcTkPcuF3UZTArkD3kEUA7JFnDaISlKy1Zkv8DWmQav3y/dDresngiO593wGm27l9pQTgVDP//Vyz5N4bZzJNhWRX40HZ4Y+rQcG8zwT0pwQIZekDPwakFP5w+KIF4eMsZ+cCTyjZ6WF6ByJUObnYduFVbBZ67R+ng7h70s/z0/vPyJGP1pIZqL+ofueapatqBxsVz85k6sebRI75tibvvyzzpzQZ+4JqiYjiPnHd2QcbyCDita0xrFyfr3y2SBxeTnzbgtt5Sgu0cymcOkb9z6Ta9L57eirLL/X6KSwQCDY2NzbTC72qOYOgeH9mi1rYb/5tQpoKyrH4HaG9lAtoN4fncZtcG8ys3740dYmBpsZigNfG7Rwhsgi96pv7CT5UlL6KP9HQ7vPrrhedU9x7pNSHo6c/+ir0ZImqLiSOfiUgnakLX15Q0dqxnPlQexf1GLx/4/YwBl+iMchXEgeO0nMdwHKzgyWIzPcHwKE0AX5g+UjXEKwxG5PKdkd5p9yC8m76wuxVaOY/Q+ktWSfks56IvWBljCxfdhYjfphOpypRwgAg+qsVLt+IreV1YXZbuD7MP6wiG8FwC59F0yHK3X2Dh40eJ4w5j8FKSxlfK6caN43sz2FbQcPcyFu2brd//wqDg5sZDlfWsS+bGRpfmpsXpwjJIS857wluj0khFQA00nD72L7MHh2AYVECjHomdH33G5mZtAeqGYPLNjXva9kXDI+IYtSk2Sqsy3JI1KuLC53zB/JZQOERVo/onD0hhci5nQgijffkInfE/QcvuAIvE1tLt6JcLZgvhimbP4ql93tW/sLygmssRdfGySSz8l7anaQZKbemPr6saDH5Inn9m4npReVHvL0Fs3+2h5A26TyN6itJ88bxcAp2J/3R25/vTBPbngg6q82ud5vgzFNHqLTHLQ+4qHw8t3v1Lgscl1MgklfdRtCdZUhGrGEz6ql6SwthHtknAyhjoRcE7zEK5NM8fDWHsmWT6PW/AAKnhKgsxyyhSVh9vv8KlfcpDaqaYZQeRWfT00f8tOMkmRPuuQilxl7QxYFZ7IbDDm4Rn/B34BVrtAXbfK4z4wqr+7kALaV1GH72KP3KgBysnEciywLTFH6Hju6ebrjH6DVIu6WpQB24At542q7ZisjgCZ8D7dAFEMX3VIrOfECX2mc8po/2rWUv/+qoOmiKpR2DlC4bIZOukTmGkPfCOxKFmv0Xo1Bs5Ped58CQiXOsj/7OmMdlXgjIyu3qwA3zr66JZcloMOQ3FDV9RDu7Wuaqd4awrWbmIBQyu4zddzf/IbF+1buLvvELUNQoyH9tSUDSaDcTgl9rr9hrohpZFeWQSU6SiJbetJdbAdhqm8hQzo8oqFyYkRwrHfW9gq59goqeyNJL64OlFVOEbrg63XaH44MaWoArRlsi/w/32PR9GpE7u1xByKEAZPUabbVcw05bvHQc20Gb9y0UwiBtb+fUH2KPmIiiPMmWyTo3It6UqkAZfXdEaaW0mJ2QXpI7wgYnjC6B6ph1u7dgtdDvUP8bqTDngojOmj3B3cpitqj/Ix3BMhZdHJZknRqBdB1BzaGLw4Oekwnf/BTVLMmeD9il/zQgbzgyi7mMVXEVnYuqu0Dvg7FOs4baa8fQUgxSd1Z04i3ygjhtYw69YTzVUOgyXtcd6LPLHeQVXhjCA45tAcVgRrFHDIoHgjVVdx4p6iv5srY90fK96CBCwtb/kHIbvbA+bxisyLZy9TOYgSulKp3OrYNhedq1FuVSmWXX9qn1QeNsUW02jS3RFd+QXgx8kkGoe4x5Mg1HD5ZPwbpHlfEQSwtTvA8BAzkbzsjQJ7ePgi1z96ryvllixjjn9VplcZFkojeHiAmWd7ybTpdKgalPDYq8ykk4QlIRkrJvlwpKOffSjhKwZsYGGQpCOi4rQWL1+kJ88F9xajZSLQ50zsZuzxO+j+qMECK5ZjjRRyDrEoGpheO4peH7gPZpz2qW0u4W3J/AzqYsOcH54FZf3YFAn9tTRlrvRGVbQWOW1Nz7kB6dme8ZGFvDS7IvZ8wiNB3aogaWJvqDJAKVmrta+9Cgz1NwlmsJWIu4n0ZOv8p10vsWjI1Ia4d+GJK0n0JEGQiewYezO6kgbM+NYsYL8y3zXB4ZMc1jb4+ejQH/5y6awyJD15e/7eJemqx9Oy9v5A5JL13w52dLyGmFPqCZfOBHAuCSAo2GtXOyngEymwDNvuxBKP6T/WKYSVEtv8UpHNQWXrjvjKw6znsJBT+7NqGYZFr9fZRMjobM0YY8bN9SJFEJPVHvl820emFW2ExhMdAWeGjX2EwcZ0uy+wApgfJ/FX792E8FCTs3oUFFS1jpsGQoP4WJ6EPHW8JGQm66txtqSFV7OmhcK5xen070W2piZdMw4TgzTN3oQ7xXSph5bkejPxHraZvlHTxgK0uuhhoTqh9fPZ1O+7PKziw2xglC4McLUCd8kv69iSP+rpRJstR9PuRL7IkPWaucudNmALliMaOuumUXsWZdOjuzWHK/twvzBFQeF28/t1NQqTX6LkAYebqV2QY+iwWqjcltLFBobrYGjcPCFlkEXDXXmSlcgKNaCuAEPUxpIEgRIdQQ7UV+HPXxZuLnPyn0aBJWiXpkK5cc3sDNZaK60TiuFv5w30GduqqEEwFEmDBWWJjAyp/yfxYicm9R2zrrBQ4E55n/d5b68TLScbtqbIY/qOkanvud9ty6Eju7XOIiHYR4yoM+CnR8+7pqaRHMMEqX7JTmH2clo1v+7xfWmEKDLFEAxDiIO6IritFqW8xrAyk7Ut13/5+TmNBo9cRhLXrIYLMezfOMuTdWEjYJbHJGtXfzffG0eqqkHHHIkl04bsEs8mqP7BDTSD6NCrLYItyS5X4tDxGukOh4dKchgxkPmn9MIq3v6rD9uWiK1sNCCIXkPiaDxnrLlEDvyoobnWNNLzVKtTo9HgJwZbzNq2zcO7Tl1Ad1zvWFtrRxcdlBJq2xiQuMbcIARH7LYsRzk0La8cv0SAb2Kajk+1lO17HdFwYN+ejVj3EnP9hrtzIolbOkhxMyjgyWd055AOnc0i6hNOWv2bNp6J4TBy9EiL4vG7J2nGc/avwVOBoaebmo4p9E29UuP+h7BWGTmi2afuSu+HDg5SSiiz1oiDqjyKd+stRmMVlqQHNyCKfmXh2vHpy2Im9TMLy0F/1pdA+GvYdKFhZAF21zyfL6whlLXbwic96g7twPVO1ldPqBNnaRgwiO0H/cnCbh+YDeli6BuYHovkYQoIin9IIssQdDnhvqJFUIlalvMxbow0h6FiF+QyPDKSjjEeR/TFU/2D31b1FcaUz77Sr79faKzKlGzhwo+6UT5yDzSM8eYTe9PT8LwUr8zxOSo4P5qWkS7RbiYO2pbRfQoukcV8qXg08smLKuhMuJl9nl71XHXjvnr96ig7ZgxcqUxntZRj3h0rLMo4uVuDMZlp+jDLXpjaLnMrDTa7c380Wsit53ZpVg9xUTS8eTjh3b5yx2SPcMyV4/KFoBF0xORUIMWbU5gNQTY5y/pS/tEEYfFAxsi2xeCd6kax+QkyO+Au2fZCpvOPmV3o74yEvW3o8dUtQMBfLcCBkSxp+cQNOIIcupJMrkUeCTFrKEv9dx/9592iM3rlM933wpIk9N0g1j78K2IgiDsJlyJXibXHmLWmCy+fDr/EeTpo9QBqjO8kP+g/79oifnTK82C/CR9WqN69lQu7XZr27cvWv+F5rHK2JVcGlEMgvufo8MxTEe/zuI6NjeVtOcQyGlwnlr0B4ClEa0AFZMp/9kSCm8oU06xtVd3Ysiki7kYF9kM4iSkzs2NxRzqBxXaI1orbyXbVDoOwOkYm272XDed0qC/5FNNW6/dv6oPrmgkr8cTr7D0bOfgw7ZKfta39ps1+2fdjgn5qbivWfr7dQn6nL2V8RhaPUBmjEaicvAfmzsfAV8st66Xz/uRvy+e0SyBGoS/4EyIqub8eDyXU5I8wu5Nkej5P8F+B6NDaTcyMHIM7S2ZHbmgeHPaa9JLHQynEyG+sHscvbT6ePhnRH98m0tpeGiVxn/zxu8qsv01D8Ldi18w5QCA19o7k4l/KgPpnL9qkqpHfmEPP0NDTsilQsB2D73jN1rOL6kMD4NKQzo1EZhZB3jY+/fX6G6vz2yEuDMqoynt38nPm+phBQxU6g58angHxiAmWgYX4TNtkNfO7eKNjtgUFhHHEQzzCsK5ocrtMu0Jgr5n3i+Ihbgqdu+W7/3EBoguCNeyKGmkbWAE3KoQJTPHQW7NymsvZCaCvxk+pgDU1MY9V3NOngf2yxtv6Wl1/M43SPhjMdcV98dLQ7FkZ0pX6KKN7GzB3iKiE4bmR+bfjmPT55lgteQJE9KMjV+fafWFmAU5zOCV1lRlSnvRJDhfuaGud+OfFecaoEdLFS2kYyK2HakoWLXhrARUR48OkPhEzb2id1sdqKNL0H1Dm/m6+82kt9xfBhswMYxhm0bToSDTifZnMo0PJys+KnMGN/PLLtrwdczXSOBfrYIYhvybl2/6XA1XkkDUVTBkCLIMYob89bRA2dVijg8EYSv/6xP/4wQiMgYSz8f+1r0dfirfHufOZDGjfkwjEBhg9qwQM2oe9NKh405yB/bIMLiJezJwbPtsC05ZI+xWX0SXzflV9bObiO5XotbM+YsrkS6GzzQGzmuU/628MGE4eGlPhvfmMZDs7flen0AEeA6gDQvaq9gTEleV3Njlm6SvZPlsms587tGF7HpmWsIs5Q67tgCImCqzJp5+xsHhJvOzTJ8kEcJqwq+dnMIEHO6mCcxdBIRFCltIaof6ZLRve76p4mxQTYkPpGlm3WIpqcW+QeWgWIQXSRvHCldyIvkmCxLlb4uCJNhyu8XZuugk0zNNE4q4b/s6EqHBFA48o89HrFSDpO9qv3ibv0jTtVI6RqeD8jPfotxnTQzotFNKQRziResCENIqyZOrTO4jxjEjyt8ZDuRtwK3TpWlsKSDYFkdeE5o67UwIjTAZY4oHczIInBFl2BNmRPENE2t3p06yilGFIUZvHAPFRajzD+I5zbm7Ialb0ouE43RN6wtzuz1tcJnHgmB4ivkST3/EYQ95grJ1QnLswtf5IxFi5c0VCkZR/MQApCsNXfL6dyMDEKLGtVljEIMshggwLgLyxhewHKOML2UVk3gOX/czjrhRvyCjGgnPULxZkv8s+n9v7SLr197Mxui7N6K/5oF1Q9MOK58u/PEp6ikT2I5x+RbdxLgl3dt3/u9nLL4O9w9TWWoUy0MG/tc0+fSt4O8jjGSd0pUVxOQ3viWMk8+7SUn8qjSDo7rKYvkQxlPe0D3eZDi64N9gEMVc+R4A4n4nC5bRyLZKwebkybZ8DVqL0WX/9XE0WU1rRe4HcLVZHgGcDqEJgzoqn/R1buXJ+8XcXl04PfjULsK4uPwqwzVMYlWP1eXxrBBVf8SuBH8cHmvzYt/pD0H9qYtVcYzuD7Gnl9RKdtwibVp6CFNV+0BYP3grJTzaQmvZBieOWYqO8M+7GZHkFgMGzwpLRNK+cCbi2b/3hWKofKHM7fyFHH5PEsRhROkf3TMs6M2Pec+A6OV+2vKPSJi19HhMW0z6ly5IeNEj9Wd8iX75157lv095xb9A0G66CZYkjLYAIDbE30FfJlC5Y8CTghiRP6qhSzC1VDguI0/yP6/y807vYWPQF37s1rE3/9Ju4AlM3GyTIirUO+Vt6rOUUQ7mdXJRNmG98K1rwmhG6h/HqMRILSS0UmJPaFZRl0YpwXcQAl+hS78avYJwsNJp6UrRVtFmhDD/Eau3NobjX0X9X2CukF55r+iYEhtnuxAadjkUh1+v+97JX2SRLL1OS6cnFxGi0kHqpjtoRsiVcrbvDBryoXK61QkoEoYXoZyE7+nadScJ2TpzydNJkVKykqM0FmLpXLYSFDBFMeyXjrOQYOCmsWl9ShpaQdxJlC3jaja6GSFq8KcxcWSwI0ERjI5Cb1NoNwXPPVM0Qhw24gQhQCjiZjYFG5vAqlJLw+zGzWgm2RnTe+XfRhXKQrAwGp9JnFwf9ZUXSBVKLidhh8ss4D9ilFgKZIoTAfYqRDVxCAEChzyudY6AOfa9B2ACyxXLQsoXh3zpkmVczXn4D/C7+6OVmdlyjYbq3l9r0iyEWf5BpiVdEDnmTc9MQA3z103rPeqWyRqm92HPfHMau2ZKxaB8yspqo8rgisMl3ZcfrX6lXFcNBE6eOlIQq0m4lU/BZPUzQPi4O1n3Ka3H7/M5WvXVwBkgS4YyAZvjoS8JiTqJktvBqNP9haz+cjmdx2uIn/r0U37G/xKOo6tKoNmvHi/NJFOLV//noDstqX3W1q1YB9Bs7HLAQTLNxl3Vtkq29OB17vMaHw6QPbOzhkHMi/87lW1+LOTP0qhkzegXkVrW8IGPTGp2ay1rGg6wQ4rrq23ZuVv8aPLKFFwppwX6P9fWlmM0hxtNmrTmXKSP96XSe9BaDbTjBnGF9OX1iBXi6bAHqu2FCaCGPEWoWl5iQdrSzQ0iBlopwUJCqvbwcYcmfUNEYEpDKF2lnwiu0CsxM54E7UZKZG/uivEF8OoV709xh8qbDueiJTJRxTHCZLVmkNKw+KlHcpR5ibcgCX2NYn9Ab6V54IRFuiTWok0Xwl+dwWM0S2+ijy0Bb5vze13RM52Y45EQ3yJlc//wAxT+MeppU5GRRBd97K9xBkEuZPN/AZnFZemwT9C53QIKKje5RyJ5tobsu472k5u89bu/+ilMo2GtstJT/MGKRB2XVSfjfAt/crB5uGzX+bgfurWrXKoyDAuXSNZrRIK9M/e5vtYybkxBQ4oGhYVL5yXa010ERqtqC+CBPUOR5Jx/1NITFbfqZByVTglJ6WsjDOiJJVLlMMbstj8RwXGlMnruIAjlz48FMPN01EqKOLaNLRKgmz51ni/WV+9rD/lrmCYjaSxJl92Kzxek7aChcewnAY/yQdoIrWWM9pu6BzG7/Rim0wVguuZ5bQRazqTxD44eBPxEOLh5x8Ce0LFsbUCQX6KYKNoqI3S/mWFuPObgvM9rDZykU/Fcus9CNiu7ftcUaLn3YOK8PzcE7NIrODPA5cO7KR2ox8Gg3ZEFBsmmtOvLuoJujUDS0rYVAFoBSwtnpi0TXvfLRa2PYXDit+wE+V4Wi3cdvSvkNm7EU0cpB3KJ6N6bX5QDNW43nQI0HZf4DpbLdKGCXpI34GvrIVNWUrCR5dqH+CL8yXQv3H1IhF6tLxziVntmcmlh24Q4DpKsdHohVsnTk2YIbjLKzn1ILJPg2ig/R/wDuflmW9NpoLwoEJEo3b/jR3PrANUyx6FvEcPx0e1T+lk95pLMPwOA5FlmR5kIZHQKhJ7l0xVmlcb1JGZlaRu6Z5D+7A/xTYEbXPgMe4/84EYKvuY30rZqYxhwu7+59HKN+WaI6Pp7UXWgDAZ6+pGdhVZJsj682gfuw33Up35Rnl5F/qX/G7PAXHLqAaaZKtH+CMBwN5inEhFi2KND/z+nuK6OrAxMdlf76X1w/wEiGdCrpL0ErY1zjKbX0vmrtdHizIuQgTKgnGlbM7qRxkih9TGYryRoIdBDzlktuJsujrRaBwkHzznLgzIZQpUCGFWaSkY8br/xQGbN+bXSMqChqYz2xgfkOxCWS91UJIBcl8PsVGXHhtNPlB9OBpZqBimTFLpwyBXWCvT+ugrZFjOKyiwcDIgz3SxYLfn4QYHZ2QZRaOxPDMD7XojLYDh+fVDS3hYNd7xrOPr5aoRyF13BXCkGmiAA3I8DbHB+k16SGOmmqtHjBlPikSG/bM1l5h1i8eAqpO3alYfr+FYVTauEZ+cFk9+ynUgYD9ZA4+64SAE7P0YnFQmEBNWviMep5Kz4C1yakvAiPlGF8RMIXRzhf/pYnRWnxirQu6hMf5zaNA5i1c9iooTDqBPywI2zmfTOQYJwTTb/Et4vVns9xCW7e/LC123LZIjMwuF39I70n4PGdx7hK99EKeWL7TPHoB1RRSWYwRyUJFf4H26j+GF8/nfENipVOdI3kbwMLS5ACC21RVYCVh4fAfwBElaoqcQAZI3W2fiQWknZ/a3/C9IHjZWqgal5DxEahb/XxfW0KsN3n98INk+V84e3u82I286HlmgA8jt6yRiFnPDKSCQyt3L43vrkt1gpa7gQPhut4F49VwoItuapsmEXy3/ZkxxTnm7zpSZK5RkXq5zvNhhi0Ip0/yOkNxVjwxNBp1XBm6/Th9GR2jjuU0GZ867IQH0FkWg04SpNoM50OoEkJPjlZATXSrYSXjhk6zLO7SIqTrRsgpuOt3SgP4NVKsX0YcHNZfgSqs4RxqTUhcuVDNWdoPcMfju079Xpj94apKE+r6QOeiBvHmtsHKFo3oBBa7AfHukT1CKVmNlnEPm45SJw/vM3QRxC+y5+1G4G8ATP/bEZtk56zcXa8AV8Avj22ddy90ciJ1CG4Mvoafj+EUWRU8oL2u9TxssWkIs6RN2doWVTyp8gBAAbz/KM7fQsTHxr2QGjeVANsFqwkoaFWu8XZ1d+P6JhmGFWXmGnlV/MkfcyARBWd6WrKK7IDkKmAVo2AAqmaVD3O/ZMw5iL7EDJjaFb/pGVnTF6Ft0Ow9hCI8cJDc21vUOkqXkjO/0wiJ+iRx5jAmO5AkyPVVqYTThr4RbpNzQc3G3eCywRpMM3kpb3B4OLHMXoVSiV7Y7jdDDE1DOvSfhR7m6EZFWNsTCpeXSzajdo7Fttc/ZocP7l6z8PIUeuLp8eZId/CylvGpQfLT3zZmTgQ+1blPloaMFdENLsDasGM3DO3+3s/7ulDea1TLCPbDLa/5C0c0s2+iFjXN/1mLROrgcZCdwgrVbckLj2cAQ2JESDJ+DVhgIkq5aHJWCNM1r6dEOcFGiotSd+8+fGsa2nNih5v3Thmk1RY9rZIe54/u/GVyngP/uO2xbbsvMWoPbERdjk211/BQfMNDyDHWBOGtBjJWeSB4E2tGsXPoLfuuTE1UNHFrLjJ+5XHLp/x1hDqNdC3rlY1b5kGCifImYE6PDx/068EZ6xEms7uFRLVBeQBq1C7rC+llhJcgficjSIg/kAYZIiTkLL1LZY9/q2ql9RTbkUTCi1f6SBh/DzfRgXGrf4AWH3oWuae10gVvt3PkRic/xLBA1BJld/AtIch7GnaUvNBhKdUFhCbtWSlOzXG6HvCh2B9tgRYySuC7LjKx1sCkJhqKXvQ7eYoqOf2D2SLvs4vUkyvuCTArQ53HhWBk0xFP9Jd4MGwJNm8YledRme+JB/2J5JuT18nkYwOnwpFuZyv0X+209nEPztNqhaKnrH+5gVIMTKk0tFg0z+zcrRdT8USnZMBoBA8sLeo4FKrL9iUmjSWrw2YRNxacPtJ3A6Or9llOiE341tqU5a3dfU/pXOK8UL4G7mhGd79WvlRjN6gvQqsIaBa1F7xit1BvnO5fY9CmtExXpUQRaq+2mGOVJTMwMg/0A1ua1+T+zDZJgbpnh7CtcXLCGbrVWLAwcN3+fezqWiT3WGwTE6Y5hk6KuYVAx9uB+kg1DO4Fmm1O/iQ07D2fnosn7O2lEvv92I9cmO5NHzP9QykTw418tFWIGZwBE1Z6mEpRBTNNagOcyaORMPsHm+toAr+Xo5SULviF6N+w5wZfuL2/HaXPiEWunKQ+zVJRbmwnGxRpsd3HYD1aNWLlhNPqv9ZtKUDfql9EJf+70/+K+P8WjkSoPWIH2K2WZbtxtxvxMgB4bU1k14W9Ltn1KsM1tfgJEqtNjggpwFLT+XvwiDuWb5liMfn9P3n8hkv6byB1jYpvNWKlhMYyoJDusF6Zj+yw2VOJaHKfSHgXfCRyiWZR1lS3HiUo5ubXeWhFLhmLnMiqf3Yi4BDt2Gd7ZsZhBHPvYZuW6JDIKGmVqLWokwnqLZXuILinYFFwK2TWrHcC7sCkHyfS4orrCqfY5VJRTHs3oFUdFNqRvPZmJsEmkC33oKcDq9PbPfUu7moG0mrhYbZHGDmZtNlX8wweBBVYdvh+/qIeEiKeze1ou4yB95Mw0XnaITbEXcNRpdbVHtRUdYSagj/NKKzVrq+vsaCK0pAy+dU0vn8nnIOLVfVlY55mbiAghMcT9/fVZ8eF+q1wa6KOLbm5RN46/swiwXfFtPX6mh8Pgr13pIqmWYVb7xKqO1Um4BiUHPpP9zU8MTA4vUwaCzqGxQ20V0g8CtQs+jWF14X3M2XWW4VJEGXuTMBQObg8CTZCtngv89mIhFimQ5F4JHelUF6KA2m9FGk7VMh/YIgO7FOtANQY80lBWp+JYhlCV/uWlxAIbt1Ad67443or5xq0lWP5FON2WoeErg/PvE57jIYwadvLugQFnMj6h54B4EMrDjU10fOHSmR8FMSHkeKv1PfG5faGBCbv4HFTWS+Cyo0Piqo44sQq+vGUYIrhCn4z9ZXWBlGz/8XvwbYkSRRGuUYXlfEqjAETtfhJnoYrx6bSnDSnJtS3mJfJmyEE/snHwFAHmomi2QAtd6MXu+BvVietcI0QFubVdmHKf9v8nsMX1tP2s/cJ9kySStLC+JAb150k9BsLv+6c5jaZWpO8AhMgtAH9n6eOa7LuvwtMbu8UTwz4voivcOQ2IfAKJJuyczOxelG4vccCOC0bN3pK93yiABHmV5VF0UmQ4AxxGh/oBHS6JhAsZF6iLX+0N3r3IpPCRXvSH47wmIkZA47L2uZbVIvATzI69Zhu8lv/cOLpF5+w9mUUJQ75FvTE+XG3udriM8vsQ7pjQ1lMw2DrvJF3hWyEcB9TcWveX65YN9fKI67MabYIU36B/9m52W5wOC9qrWda8ywBKxXjGkF/RVoiiCTvWWo0VG92U+xibaw1uIYSuI+ECSrzLwHpNH/yhK6ohuEJh0BMYN/XFXOKP7aMuJAKLRROUed0vQG31+isjmJBTztRaLxAwvv9t//ks21zW51HmNI0C99uUe6YNpGSkbOd1zGukRvr8cWWRXs+KIIBDs2p1wwaKvnwwATOPNDXaLk7As+Th4EqbTPszmImTHxSGBDXLz4JnK+avkCj/ddbWmATyKSv3ef7KH+G5+6BGXmc8lMbMAYZ8z+u/bWgc3NiGl4ndbqbR0shSQ49pxrpjLm2VHv/QYvzgfA7B6OefSkbKgw6Va76Q1WbufT6fGrnU5XFOKxbJsfa6LOorf0Jr4aY1huMqd6Z134V8VECn6WvNzoSt03mLSsru/sxCMZ0IwkiEX3QeNbG34wQ9Zvgra2NL0l8JEQWEDC95ZRKycq7ny+Wde9jreApqTmH5izMtB5ggXMxVb8QuuSI5G8GvuxUw+yeCPSXO7Vtc05FyYM6s+bl9yjSMCgdmHlFJRdhXpKYwGqRxR1V8zW3r2KXrH8RBXbt9G5FZxHFH3MksEsdThcMfNohmq0LvVZycnZZ7nS+qkaeOzZUPMr1B/ZMVo6z5uw8U0rWVVqp5kLnpQcIH8pgwFEVkXsoSc2WXkb+RYyEPJJ1TwdN71Jx4yMyAPlwTvji7xm5nR0pOFiYvMTz1j37ehNpQV6BaszeWREMbVSnbkRAISlw/b6P/5Yntikq74u8m1zSiDHXYhFMjxpoEseys/vPUFPIrTRRoYj806WwS8f2NU09b5x8/9LEqPDFGPnCF1P51VqNFuLSfFKdL+r+zWwu/7TcTqsoYQnElUnQTCnjfXI6DYyqLItIgdmNC2uevvqx0poagsu+BOfBurGlJHyVNI4J25nhCW2vj6KNZFKikyyGYPwxLPqUfEFdRSMy6Ca1dN7FYoOXhDWuEptkZY5VpWorv7MhvUrpoyjKWXMbvipOR9wrDq2yTjglP+s+arI28Q9zDdkeS+KRCRSI0/6pGIT/6/RKZB6W28FqyxBo8uyBuj1fU4VRTzc8jgz43mMF706fOH2aOiUlfPgS7rL35KEX+1rr1WPfdWz/uIX0bUTE5b3ZVS+9TXFZGe6yuk5RYqWECwK2sTSBNQ28ojN1Sa3IT5/t4qamJrAKzZpIvBgz2qRisVFzCl42DZmOn8zEJEEw/mbk3yG9UZf+SMJi+Wu7OfumkWOYacMKoDpWREXOCfM219iP4QOHHTWd9Rx9Mqj795s7GUK7W763ffmM6pFxnGzV7PF1niVlb3t7YOFLDGQ5/5mbhEdHUMly4qalp+X90aoCDWwdSM4JOraJ37tOL4wHLCbXdOIjTPmw7jV1FUUgw3c5SB0zWLXdwfVqQXPGd1usJCnx6mLqNBTfYXUEwzNCdRk4ApYM6JZv7oEprpocqqB+shY/jtQx9D25qH9iDuy5saGUhy525ejGRvcGAiAzBz1GygrZCu6VtYkclEXtKH8O1m+YmlsDe3NFjfhR6E7abrvQHiNU+aa3xysB5/YYE0zFlqyWMmOQLEn9uNHFcSQmz6sEILDb6Bro1KadWhMvH7fLsmYK5i3Wc+Vzk3/GI9ZXSzV2SMgRzggUmx90sAta+roCnYA13xb8CAMt6kavIJrG5kOH8Ns8SWZf2ISLA0FKqR9sGXBJmxk0GnfJB/o2qzjE/jv/odkNTCGHJ4KI0Qc8kiXavkatau8AtMuPDWts0LSl2fZJnN0nXql8Yn2YhRJl4IUXnvI/DeahQnJE/1GQ+uh50LznSirVKCyf7jwkKwzhe7fVP5jH209ymWXFKtoFi6LmZdX6CFyie0yGZLgjSS8lt5YTcrqtQwXq+4I/ngL3PuEql19oU7ftBtvf5mUvx+eorQKrW3/Gn9sd58vaoSpCcIJcqqxzyhGqLFnjVYVVquFZVlTwSRynKj3gcSkxtyR8H8udvOaC+JCOeJU8nT8oqM4hS5+HfZgAwc+Z2vjV97r3H/MuzC+cCg1oEcAvWps1cM4ONoa/DAKe7hU4X/EZ3RxClNLkH6tJ16MJdiBQW15t0lneYhqoIkPmHJ/b0MARRnjGkr/nfcKgd9zyOwwx3JodIHMKiZhFwDNxDZLVvjTiNthebgoDAnmiPnGA8rmE8NjOmHPYd9EYwawQ6V7RkECrAhPKN1580W8UJqQGoTUJr6furMl1LW7k/TQJVulCAKqyIO3sI3Cu4OJ41UGk9xndg5BXQd191lOXA9vsWd/h39RP3P4NRQVQlMQ9xyXiQhYxRmnfy1X9htsjrrjRwknYCBY7djWV/pJarcQKN8abYsDgjF812J00AWuxE9Kj7Qn8EDZLI1CGIaMbyWsgcdb21KpJQurxCIS+TCs2hnFjYtS1bwEF/MsBzWsHpIKS00KivWSk3j+Arvjj9+dc8ia6IJ1G+H1uJZm9SnmDTUrxtHgGGdEKY8ZJW5RJBTqrD5hQdnqLgPTms+LgcaoDPcCanSjt+CMi533y0PYAXCXgYFvvGXn2mcetiOqGV0jClwIrATY10aYvXm46nnpfYAGkcrcV/1mVYED9yL56LgTJBWrGyBAiB1SbO+MNx2hls23wfJdgwgon1MpvMIhih/krXSNvi54FgyJCRLOWWwmoK8Wmb0SGiCPA3Nncwk7ghQBomMq0ehiko8iGTQia+IzwFwToLrECB56A0FQHFDnGNcz0z2JYKw/6SpKPn3iwC0jxQzyeNuvWRyoKq9qKqOaqmh3vxb13XE67TRGyxgn/DRZ64ONiEqn8ZbpOOfQi1KAjWlaZcHwccaQYKMoUJVWFsd62sHJXsdd2PxE+CKoN8CoUyd5EvcAYFKUQRskkYF/3lVVBQfpQVuOOHNf1QeKf3KvoxrOGObkLRXu0ROO6SXspJhy1jdEUZwG0CHILCIQD//w1Vpu7jiDZaOGTGc1OIGMtfnQjpOoYQspzKVkT2VCZmHRtEc0L/e3eiZDe34jd5zg1Q14bZ/IbzJ3sUiur5XR6XD5nLdLS+EZYetvBli9uwQd+yGy6I77kDj3CMpziq830FWgy/D9NLNm5KIEkMFkfLB+SBAq0HPsFwsLGaYi4Yf0NdlccXgWLMZo3nYj84vWVGCuYOQycmzUPKPJf75dcm/OKI8D3n+OpZB3NQvC+/7r6hvqdWGSfaVfqEmk8r1FiiZqTqS4kn9o4TtSTycRC5fsb+Al+1J/MGK0AVoJM6d0+A5BhulMQXH+AzoN2i+sMX3gMYOmiOUPac78FrzOn3EtCenjz4Z4Dzaxn9LzSVh0kw23IgLSA/k5ZHwDbiVeI0Q0m/w/aSkJSLKjNDFiJrkc3/GgJqlp3QA6G/R7CWUZx0X/qlMKMtq7dF2G95+586NIFf7zP6zev7UBJKeUIBzgj/visxSHefTxiptwd9SlhDeI/qom/2otIzchdjnogkJw5yVxx7hI9yXp+Cp0vEaD8qwI53Pe8ayCgEOsZABaibGo1roQgtHu4AxwtKJaaq0BDJRRWojzsV0z2wokfHxrowcJ3PyWWW1URKNye0Qb5/yCwc/uOQvQuX9kmrCKZNMLP4Bt0D1UJ2Ae6bDF+Se86vvtzbIfd21RXZUap2/NGVDxnTw1j5lIswxcFLKoIIfypjEfsmaLQ9duT0eJ+vRNaVvE/pQLD/VaUlCXSpWH48WrGch49LiHeJEdBxdRRLDELyeRToAugK2+A78JtZd6IUAwU2LWJxbPo/okC5St+v4Rru05HDbprDyL9k8XyqankMOnpJGBnumuILVL6w5cB7ovXPcN9rfRhYV8x8f4/IZwfaT7L3CiayJKJ/ZDdwlZg7nZu6xO3MrWmk5+R9PEGa/xN3qRA3U03qRVILvcjvNb7mZmxMgjBKudTksr2lnObl23IG6QcfopI4NBFlCE4iCdVWiCzQsX1l3xtOg+MpP2aiHMDxWaATig/3dN1+QAUHXkGJcb/h5tVSkg3D3DCLEnKYi7kp9xKC4+bRb47t/GfKs6Bb7kSz5jVwr4ncnMAZ3z+fOm6uG7DSMG6b9sEXN6tXNOQgYb2lN8CGrbQXyB5UgtU80vcBc/imzm1KEHoijvoApm0A2qPRTN/yKkvYx6CpX1KcBmLLGilGFQCJf9UH3lgB+u3NSUDKa+RM1P9sQp9vn42XTDteInlVEqlKpyM5L8n+rkFaCNS00NWaiiFwRoetzfh+cVj489r9PQqzV2y3wT5AgVaos4nEEwpylp53RzjhXhn1RW4xsn6zg38b3GP27JEU6M2BCf7zi9iKfaW2yBXows0LPqACaduOA4e5nQQl0f4MMl4/BJDX50mmxc7Xu2lSPPuEbtIXGPoXm7SNI+/hJW6vsRSw/4gsjR5KlxgPiEkQTp24K1Ndi5xfGsaj/K+osALwsnj6+YoLSCIrAgYJBCYhIhyAIiHRJh3SX9NHhkRLS3SIlR8Md3d2hdzRI95H7fr7z/Py/e/d7nt3Z2dl9nmd3dnZ2dhdIXneVMXNHgoPSWa6LNX2yiXEQc6bvGb03ZzTeOlD447KJhNuy/kWF2nrmk4xScyhijZrsCQzOGgV5uPWlaNu1IjfLdrEkU0sC54sbcx6j5Yo+km/Eroq7ailpZik/9NSxiH50iaLLjsKZK9xE5piGkdlb5dN2QP5Ka2ZdX0bDI6PhuSRgiuNTt60gRbd1E7ssE33NP4v7AglMEbetjZ+eCSUn+TBBNA3mYwOHYP9N/wrgL4ojNt78RP6XOWo4QyoRvsJvK8qw13y5aqWovb7Mss2t6QhwbVRYd5HsOM63gJDNLEpRz+IppOxsdCXxJx/bjL/WA0j/GcLAw6+1roankO2FJA+1QjioR+3uBlJ34FEgKEv/FVVfQqTfp55D0HBbJON6992W3R+MwyovvCIYdLD7pPPCmEVo8KJNQCu+IrCZ4DKWxuNCmeBTY6S+pDqOPxngWu41d7M53GoRatbbQoxVZoldwg2WbaOWeyF8rA3KohXE2ulpopgdo/Nl6REbmxNwc/+cjISGTWtT5TUdb8ix9GUMKqLEAvPLwGVwEDUASF1212hPxPAAxMyYW3MC5tkZ2DM9z3qWuirhj6wlj89J7sAULB1mCfAqFMvvIz5VXFMBlAzwJxxWVYc9BbYRxDxHE17PqmDgSWSMv7QeBVo91JpNCPqIO7rC1ZU6I/gFkGF4t/gkDejehtbpC8cHY7mQ6Ji5Etp/GerNmTUrIPOSx5F3NgGV5En0EK5K23IxLJqm8nFQdoC3+UpsRJQ5FqwBLJfdS6+M26W5FBxp/rkbsgOu5SqwFuaUKEo5lr4bWodcDCFZ65NgbXRTSRHnUipSchT8GMShkqK/MsYu9Rjsjb+viECek0UeL+OhFV4Gfz/7yOZTU21hEVup7zVUBmN/OV7TuTgoLxrt00P1D7CrtRJpuZvu06HcWvrGA4r63/4ROBndB7SvAxYgnXNMAAA7wElEQVSrHmiYFzWx4LBj4RWFNjc2+OWIleC+ZilGUEd5qcDBDOMRKuPd/Xllvz/+laQwHOVziwtPHgVWI7ys45rvW6lP03CdrKjujd10P+6if8bLWQfGaZgH+820M8JcUot+EFindO/Tfz9WO4Yt8WgjRLWbr0xdq4SsPQtM1kmBxPIxkVMQlp1WNPgdwOCZZpm4dx0aU13FJQVeW3HqYUe406svsGQI9xHmB7nuM2+PI9iNIRp7HUJuJGR4CUHN5WZMpoZiJ/JLjE7mrm/8pcKRvIR4tNldFFvh38ils1YdKcD8tRtUN/Bn0YJMNgX4V/Aha8iwpJIsQqZt1RBsqn5Jvj9O4J+lXi8hbYDcA9lmTQFe3xT41ANzQhRGTp808p6Pe0TTlmyBO8AgkBHXQvmReMGb65/8LCp60rzNR/Dq87Siu9KG4gH7GoE/2MfivWNmPP6dASBwVpM2ohELUaTMgg+/fuSj39Jg3UfziaHiVh/5caHe4SjQfIeI4lHpua+d/K5mYqOukfsI8bRKzH0LfbISqbpH3VDLFuxRJW6ioCAWjdfk+9VMAhLvBvyZrzmN6PZJXPdz2MTccu7zB5aSYY6YU8cT6pBo5RX0GP7Act2eL9BVf8fHHLOxdy8G+eOUTwMvBox9r2KDvcn2tlSeBGcrWqPlgxLXza0W3FaxDVKYJEtlb81JbwuZ+AQAB+HK+nZU1oyIkijo71KHxgv/nuPANqXKCF+Ty0MVYZeLz/QOG/nqxVw0y9lCz6+Np+b5LatpU7hMltsBSSX8NNS6ItLm6uq61k1uTqvoT9b350zxx9q2Sx7sKkVcPoYGKrfqfcjFVqr9oActQwUc9kdo1YPNnJ+a6FrxylVMnCvi4l0JApypJ88x1UCD6C4sazYua1K//TBvawB1f0ZOwA04hCawVUbDip2rJeJSa+SYFX7yFFFfAzD/dmxiGExY4W7WeySa3Tg24TxAVzq17ZrlUqpAyotbWi6nO39Cw79mM/lbCA96Iz8Vi88TuFRgUbfNvEfpXBQD9NuSyi5vzlc9oOP7zhBGpN9N9TDnfFTCFFthEacv+SX7PwgKTIYLOaWqirRuEVLaBQWpF/R3LItyd9tO/MGnLvPvm8t9GBViBJ0EzVkLsUpAeIUS8Gvmqw3dMkqJ0xMqyw/HC2339KovIgRKqdsF86r/Om6+tl2RUqaW8FsmrzBrrHlhNs88cB4JCvELHG3p0PJkHzPusk+Sj2505Wa4EK93MVO/3CUll9sj9SWKIxIVpWBuUHktrcuvjNAZ+mL958QGFG+fEwyTk480Wtcc1+wmO0tOp5IOejDlXi6LxARfOHI6RQsXzMC9I0iLIMoNLmLLIIXnVtzdoSj8lKACnrV+YhHfaYovqtbEXJ7gDfEqtNHnqNoMT2t44BYlV/NuO8LyU499EJyiqLmT+fRVr//uyvxVJBDXiRo7fh/Zm45WY1NbCPSXvzCItHQ5gZOMLgW7n25h2IU5mOCHqnhV9RpTUGNG7gKPx3HxuFIeOqH3hXtUDxGU5s1AjS0O+WFqosJlOYIDI79MUVl5UPASNgF7xU5wh3LrOQ/J+/sS7J/54u73vFRwrRH4uch8WI6KSvLOtd0ehtNXbfFdTVlosCCxt81/tgYhMEWMOxzoTv+zvYxdjqX/eC1jVXMQo6EiopTEE8HPP1oIN8st8MEtXNL7rNRCPHO1LFn7IY4P9kqow/Qme6Spchxn5r2hj1XV1BoIcy9Flyra55Yve+ZbGdAzjmM4Lda/PGSflBFAexjVRde4BN7haSUCDEUXkRAkXHC5j76hoDClZHygdxMahMDH6WeGrUeiF7a4RJL0P3IlWK2n+hQd8xnarQs9jLASXs2s3S0ifGvVb2S2rn/denWmEK98sS+VJQ7Vft976g9BVu+cCd6WlsXYGnDuBdwfc4tvbMEGAdxsXViQItKiX0B3+/832r2fSHYaL/LBkfvV3DDxLA/H4PMedmbgnM6BvBADuqUzQ2jZ88wRJf9HIz2p79WM07X1ma6ayugHi1vGKPeZ6yM0v7istECAydt9kwtPoC2beAP5pEA7lYh/iZmBI5AFn5Pd0YW4g4wbEDJ/cMU7GppQZUpio8O2hlcPWMeASDJwnNszDGsJgGw58U8a9u7hrAO+gYyoMA7v94gv8FTLi+VOFu4O3hxUdcL30ZlZtjJLVhbQCfsr2AjU4sC1kjYByTX4zAJG4ahEx8TNfKfpxIcJ9BBSporsp5DMoXyFs7ZqhtbXd082JvUBP9jui2CC6WZSYd6TabigH/g/rp7I6YfW49VYWl1xuzCP3ihatmDn6VINZ7Fg1okaXGoZTie8vehCb8VjCrpBDd+akcgXeVyiVieZi5ZF930fr3pLFPeG7fNc0mlAuX09CKQVKRynZpKFHz5nJOvLACHuDgydmy4dO2PVeu6fZf7VFiGfZNiPW45yAvr7xjqEzxKVKpD+47ZcNBnHLFCMrjR7Hs+9ADpFUc/48V/S9gxJgE/xA8KQQmqmv4F/Oh/9YshUoJwxTuSYlb++iHsLvJFwtMOWBBpdRGc45cSZeOGS9/wJy1cDbGMP37tUTe1NUUKIfsYsfzgSGrDW63Ake+fAR+ON48kDmQ6wkrN2OFgsY0HX5Gs3UXazQVTiNdr88FkQMNj+GDPZhb0pKaxNxBd/yccfgLfSOQP/cPIW40q8k3Zwg12KiQUpLAHf9I3vGU8xnrhjhcAwpG4d49i8vxAqLEudh3YgepfElvzt7quGKx/ZVLjk3xTyd3a1EY45lzs6ZLMWIiHT3650CuJUXwPjECuZENjqKOlvk9oWvf4PXiN1qgvPELBpFWFaVmCZXKkyoCO60uH958z4wV8YGNh1gnqaAeC98TCw+TANqUmXwnxclSYo9clBOhbc4yWwfpm0NkS3bA8DQ9aOru/Cu9PZ4837vDFmJ8T+YmMWIe30Y8TDlSI/DRqxAG3tmh9O1pQKom4QUcUKNsrWDmOXeXMWaH9LADysfNFG0gH2qMc7Cyfgx68TOvktYpFbGBrDVPktvYB5VQwh+Qnv6P5xaADPMgCN8HF/CowawHK2LhWvj7F0kvk1O0wt2PmlTQ795WPXqw9gDlXsGn1DSJ47W9FwsUjHuddtWssg/RZSq2lvyvB0es2lNLUNkOZrQZshSzFouduu+lL1BKbxAp7kcmBN18VZKKAocMl93oi1VOBT1Qc3D80vIf9n4XCuTwwxgDRXj3GMtN24B04ReUP+mNMiZWSjT6eS9eR8YgA0yXtC0oMO+OtgIxsUQPSec1y6PCAsrmTvNDvevr7NdiT8dbBKozMMGE20rl871y9P2cTHsqRLJP0JzQ7855YzlSCLFd9lCZuAaS8hF0F1ZK9sLg2Dvf2/A9lsBhGb2e3jf4n3HPbh7BZAx/W3Vm7gMEPmfvE/+k+pUaM6SBswFBALgvkyJW6IekV3qemV3DLl8xVHHubVMl2XThT+db4TagiMNunvYtgVT0CEsCs8VAoJvNOCp9OQuJPizAWZX/CaBBKtoIzmpR+qUKJOKsFvt/w3k280XSkeb32np3uVDzz93WEmUWcdhvOaN9+bwDtDY316KEKuNkPIA4Z1hQgRJlv9VF36De117uvxI0OIVDcbn1cVWkMjKAN9DZNNUhGg1TTQ0kKGbcUDcNCK+UbJ8iHdFcFufpDk+YKIl9lZUII/ti/TWf//QL3cb0stWUpRvIm8Eg7NIy4qgUjjuvr9ndWpnJeGLXD51aoiVKwsAoTD+B5X36b3pJkEKtEDyuem//b7SoG6VHc99+P5aN1IZUE8I5yQj4CBeDsR982rJwv2wD8i3Psq6S/Mz/LcXwuw+jHqkEGgLvd/3Ow2wLcQb+26by9X5AzXqmpURubzUtRXBjX5/Agl9EHOvcKWGgEIaCjvKa4o3ZdpYHYjiIYm4IOpFw0AmZsAs6pL00fZBltt2+GWpVFUC8JcJ0ozjIO/EOIIzn5SCzkSLLFNsWqTH/e6JUQlQLzMM9FNwc9lV6grsIw28lXIMO3ego+DNpf40kjOgEpwkWofYeyseXUx/GnUs0l+PyZSCtI2dYwK09nv8bBQ/BhwGf9gg089EN/MBX7Z3FHJRrjvaP09CklK/DmGjrsEPV6xIbCNHHQMzOyLFG31i0bB2nNC5ni7WBjQsA4H7F6z29rN3/f5pLbSLCGkZdCanUCDJ4GfLSaIaH8MH3rZXzKhSnzNsFQVielNRAfunYoGmxWgyXN+bKTFwbFe3gLdpDUliij5ti1noyfk9aR1Df8b6dIMs/tYOFiCrcoTt833uoxpikQJnxdeyti0+DZl+BJ9CqMmfPzX1dU1Qa2z0RhMUC/aUpF+sEIuJ/UJtqgR2u8HCt50t6ubIcBMscuPq/mUI0WII9/mcmjWEdSAJ/R2hK3/T5d25/kWUZ0Y3kWmn4mgmzwBvXN8ZZr2v/2EhUrDmKwVTX+SKny0pTbC8P+uKz8gap9/Ocm1pjgRIr/jhlSscSTbnAd1OPdaAotSy9S/me3/6B4EDOKLTyeCuWYWscryA74xNoo2RG8a42NeRSFGHk0qCzuX6MFD5mchh91InOWf4k2NUc5rJHs6BTxdkUep6vike+mNBIh/R57LusfzeTMqWGyPqoUvN5hL+ExeiNBX+9NU9MTyq0IGJOz6Ov0nCDY36BJlptcYZxxNG+dwMphfrwIF+DC/3tlpplgknqtfyKc+WMwSfhQMKQEz03EKHT3qWZFcY/NBvnVtAsrErV3nCiwydd/mXOkZi+3rJwI4EG76pdd/w8TIAjRTidGYk9cXYI00cTwH7+KG2Vi+Lqg0BCUZA7vh3yexMFO+FJWNm4e5/kRo9nujzXnYxomveDD1/fyn0lbF8kjUmcX9G/Z4kd2yv7EHCnmb4zPM/OodmirQxECH7MFe7/gxxk9K3mlN93bawcdIPbinrgeZ5jExpLndDvuHfYMcnzR4gZ/6pgmc7HagGAtGdtI9YoCW5ORB0HXSlSX0D27CDF2f2hnd7EvMoQZuTmi1IXzfNx+Mgbm6sLUE9C4Q4IK0dhOPXueX3ElD/5pDZbukSNfrK59zThUzdKnuTAz3FaacQjMUSaw5jOAm/hLyBgQbuhbNmcJl5MOLgIYvatcQjm6/s3OBW/T1F3Q9yko/3V4w8nTfL9r3Af4Z9IApqEaKSDdpzFcjNlPcY7nRmwb4XKlx7vO7zlWdKmObtXvS+Ca9Cyj6tlHT5fLeaZZAaSb6Nxf6DOl97gqY7ehl1Qc6XowX11/Yy9auRqmh9swocj/lsXW6hvB2gJaoIfd6CJv0dKe4+rOvGmzqiPx4CRooTlagGLtWlV6V0GFQrRLpux026/OxqNR5cwMH8SxRPzPWFYke1lDi+49jC8msYrxKguPd9ZCV1nfON4X6ELj3X4KvEX/kOCwotRCmfupK2b06CLmlk2i0qj5RO38ndrXJoxKXnn0Ei6Q6X9lN5I2G4e4fm5Yg8VWJeaXgszi6VlHjup+Wg+ec/I//ZBhFlfsW3cIjwif4mfsyXyPdI63cGtUi7S4eo7p17m8LMaJnhvqCUkyVQklAYr1DPAmcuzhBWSJIjTdApTGuycAAyT8NFmDRusozGAxY5lkf49ixws64PlqM90zaqlh8Qi8+BA7w03gyZp3fXZSWWuuzXrbZoQwZJlCWH4nNwC8zeEP81vNjYZwtNSVzyWfYxBdI7vI8FskdueFawdF/ps9bQzcebor/1Sps1V5W6MzqhmZKJpHgGAOscTe/PGtqe8bertxMkeL3uAcfM0w+ZkwyIdkwvQ+DIFLGzh22+wz7r6xTM1/eE+Bivho9s6KFwIXe2E1aEuGmdwiABE+MI1PFJUQEzd8G64BuDUov1oxRuE+BkoN1HobLKUbC6gfkVwZJy3yOAZrAPSy2ckb0hSVC9DLF82MaGpIYjTbb6RHxOfW0rjzVwC8fbHfkmDUL1Plm04lgQSsJTSGn9pfz+D4y0sZ9oMqIsw9mE33OTZQlqdvEOOGsyOr3pep3iQSyc+MTKU207UVG/Vrxz/dPjET3YCG6H7SP7RwWuyl7/J5Kz0g7XCcyT3J5JycVB1hN8vR6KLkn/FyPNhu4bQ4r+6byuie4660NRJE0dUrAQ5rXdWCdC89SWcg4lDq040DCt/ylOjf3KpmvmVNN4896BFTMz3W36U83hkRTZY6sP+aa2ZEbO6QzqANsxsXwhUzzwDpDOZBZYnpc96C/b7JEanlW+8CKu6xW1ZuoIAOH3PQ1OtS3cDAIEunfZf+U3R9RE5oANVBP3Peds0DzohYvPXDTg0dwNTaVtDVdxChDnG6cCgwfKR8Ku3pu4/myD3gRkS6M14KbKDSVE6c3ctQlqeYi/oVof6NQHu2pImXD32NmUf/3LpRcSDdtbKZDUX1d5SYTc+ocdlPUZvBF/NPeIoX4jGYGD0uvCklgwB/A11azvSZ0bssal4aKbiPVhX5oNhL1922rQ7dVmD9yU9ucbRQlnj93MdgpXhlJw7AyO9RKq4MDWWy8oRj+4LWa6LfpO5k8p3sYaGuohlFaxifbZch8Km0Ijby+UAHsPNNLJeVcEDcmDFkhcI/6AvFptvns54ZTyHogCACJzn4SXbKrrrVXsvodYpY99CjFbKZBzBVy0XowlmI+sdUZ/n5391GLfLUlhW9gHxY6i+TCslkO6Dop0o3+N/DiMpbXMHZQOaqDUyyeMsTItnqrtRl9uzFGADh+5sv3+7jNRkKQD0VSnuH8cm2XiOQLzywsRa22nRfHKlfTp1fdOkTdhPfAVH63l02AtB/DH/F10qc1ALpl42WMsGSd/WTyUeVLPnKDZuyRsWc7xoQqQlGVVZ6jyKVEwxDX2y10OWBLOmscQgBxGDse+RVUZgOChm9buIKInm3ukCABx2/EBlOtb3ZwxRKpZNTrtuH+6fVVaHbDpXjFLjSyxR/QcWiHV67WiVTvo1+NhIJZRnPdieKhG3NEUvyDGKUY3Oil2ta0N3pZlZS/kXYkSeKGxAXcDWAW35BW0UbCSZTrMlGjUr0fnWmlG5MGr3HJ7X5uOVZhft+JVMg4xPVSVf7KMN3Jo3TKtxj/3BVeISJWQOtbIovkMLmsiTRFC+k6liEhBGla1wINd8WuwadtLENVerz0e13ng23p1KccAh18Utdgfz4JEW5aUZ+y1RRK8lILXpjwaQ5rbM3Jz8VBHGrVZJH/cM9SdAH3D7GBCpyY/sPtP73KManvlpMSRPVXMfa8Qf5c0wDKY6VrqiLqWT/mvuMmvu4K+zQjbMfElOsUOQFbPGZINJflLrF5q18wWKSoikr5kIv+ZSOppOq2iqL7u7OJITSTgOuVt566mS/Ei0cRRs9Ai3NZyzCRCaP4O7eoCQdByd8sL3Q8qt8kncktMK4iWNYCZ20omVT77mPLxFlyKKc2EZNOCVUWS+9e0WPwqaMO+hKjwn1+0QzcS/9ocVXbwNW/Vo+tJxgnZdDIAscYbZBlK1I26dCN6IRdsVsR5c3F3Qx9yHqWzUntDjTU0rlz2Emo4MNuKioDFteypqNEcscSSTXh30A5F7AKTBHfOD+OBBPbDMpp6XQ5sU+56m84LGaIb7mXVq1iNzQgsxnz/fwWs0q7r+mV9j7zFztgGdRClElDruyFODfu2r8RwYxBIKy99CWaC0Fzj1hQgsTcEvrBfqcBxmvh62exQZnR4LKZXw9+vlBVKo08ShK6TXa/LA2FZE8Ss5b5bRHX1KVb2Uf1G0aifRUZKSSYijczlYr+r/tdFVAThorGkwsTnvSwFVGj3vy3SPy4prbM6PcBVuB4aV7PhFPj7s9cGdeMXTAaDVUP7DC0xVoKFqt8HOPOZRXmSb8BXiQBJ64euPGU7gmrqmjlQUbKTX5NWFESt27yoZEBBN6ruNXBWBWJIY2P8s9BbOrylx+NcWOSXc5spnc/tvTak0BvCQGJay1YAizjtMs1Ac1EepFkKGok9yrD23j3CuXpiGqnCFdWKRdvEQRPJb2RO5JzenTaLshR0exMDCK9HNvstuS2ld/oLHcfsmNm4pBlvYjvoKpMJ/cyUPmJfdcrgYYkXpybnN54TrhnF+6MtgXSRTNOsERzMmW0CI0aHBuvq3i4F3DLx8kYirknv563ZPCIIHGAzpXNiG8cZlQ+HHOL4ldc8WxUOtJPbXCezVWfucbwCp+qF4u/aEyT3LpWqdB9UAlnXcAcc2Jb9fi93LnoUDG4NQtHodOkfx+8FYaMMXgzH7E+afZvF2sMd2Qeyh86Hg3YXBg3vHUNSzBpKk+5d2jZqIcq+tkjfwL2SALYJNrRGRiuy9S2Wo2eloCOJkjDTY//kp9LfoXXBzfalBAlVBBtd7Xelj5WKNriXJMOo3ytnwiZ+ZCy9hmoL2vxqdr4BNdKCjktI1/ug9ed4cBZsNtJH609CfRZiAguwnS1pU7Ftf+6IKMeXK4zDtXOv0QZJki1IzGs7WH7dUwIfSNxuCwMxe8E4Tt6qM/YDl4E9MnlZqXhchdh5eOfS6QSAIp8JtPU+7v5BNG0eZ1LZbjnRXF+S9/cjF3dy+hcAFUEtz1VSAmi6ZM9qPU5pVj5hEpCLfmQEKdVW+bAzzMvQTdVvaAAV/29s8By7vdzq/AqrK//TT2Fkr+mhF6SWPUg8bIf/yOCKAYbBYffKX53P8F8s44GwXyT+UXNXC6IxhoRwUK5rxfRVatlPvjvaDf5km1z/0VeIwIvZSDORx3CW8MELZ8zm2195SDLf9qPphH/5YcMPO4K3KVpOTKSLkLRVHVfJ9s0AjuqCLLaJw82dwS+jR8vT9k8L4RXakxN6xnlwzLfbEB1X9vVzDESfuOHNmTngl8PcghYD3COcwqlb/kz/XtVaaaVIa2BB7zGHUve69gHUedVApvepzTfq0Qq9kHhqvcF4MIz6xXIi0vOnqgf8s1zii/jXNv6wpFMYG9KehyYqP9wbLpXSmGzwOI/PIMouyG8aMbtfDqLNdOHCb7GaZ5068ShINTKaFHMYEqfp8UTqWYmTqek/AXf934BoSDeDHZnX0md7tzNA8oNvuCea8zL/YxtT6OicyjpB8Y2GbDAWEdGAPrlGN+trr1K9ghwkel1yOGiL0S3dhFd/7Ftq3kjCTQ7+UTv/LMNEPvFVpUJgyQBp8DfmncsGFgTtVhUOgnMUpZqKn3XjHdkszq8MoulqsgkcCOCNNxZ7DejNi3TYDq5eK7zVc7xJneI1iQaBH8qf/Cy5kP9qxscaBoEGR0HWwe61PRs7z7jlY8seWIfO/Cwc8hHJLoltadoJvlCNETokgw/+lNRSTsD/QcsXTWAyGDgV97YRHDeRC6d+9J8SLFVNEOsH40ANJgnUgJcmCWcH82Ju6UDCA8NUyB+739h3TtagPVgv6bQlP0ouvJTPg1dsR5gPj+0JA0LM3LWs16LQxFwh80j7EgARYK3fqduUxmyv5TH1ufLGoevlcm2lJd8Zf+6jddFiGcaUKnuhSLKS1HUQNNVX1O7z/tG8JA3ZaPqXDVQPjExd6lPa09q+Xbv4x/W2uYGQ6l/YUF+sRJaAfJMWMonzCx/v3iGnX199EXpXjNjILYJcHbpW3CkGYpkbjhsvUY/KgsyRidAMBdHq4WPTVE4wQ9ZsKIfthA+vfyfXQHnFwHD1GhUgwQCZcMBaTwTUvIotEGn7UFT2D79zp6+iN99zPfiVePiAKaUuW6DU8cUry3KX/h7Ujj76fz4Y5++mx+UHyqJoClKgFC1ThKNzdcMTB7pSXzjIqJ+kzrFUWSN2DgwcMQ8B9KSOrszGnOYyoBvdPbjqiqnkq848CTA68ZtdfUnXKWGs0xhExxGtY49DWvSpVzUKEWxKs27mTWvhhiB2OI29Q3jO44i6Wwes5a6oR+0oeCSQCEAPKU71k8vCMPoz2VnM9RFAdXn2WcbfZPd891ZfFEAyoCBCq0aJm7BeWFJEVDbUQv4KyeYRaib3Uao0Z8xQWl19ANRFbi8RGlAgE+HlodYCaW+Wmur9rYc3qhg/T+vMIZcD0vYBBcN0ygTx06ZDJK1pIO0hdcuh1nIC70ysFb3XPtqjEbJ67Rd970Z1AWECFhGNlv+HyVTb9VFCSPaHoVMcG0xERhMcx4QJ2I3pUqY7Co+xvLJyk/FNl5rAS5TbxBG6JivZRZWEPYoZ6SLFuOolt8BwjV+kFw3Qld1ZUs8vPqFNpo2oyHCQ4XFVMUJjU/O+u3onH1kbhsWGqEfDz2qvMuy9tG/vhLF5qwojU8rjlXCTe2YKn4f/UAhpCuz+HLpZk5k6LAjMNa3LL8RJRRnWj5NN7O8SlN/bQOyro2zEhK5T6Z56nUoXzbh+EyFfP1pjDv1gFpd+MFDf34Gvu5F66QTqOo0wXE1WTO9Dshbbn2N2uwzHt8OjrymqAuQSyNVavo8kGHYYaKGz4I6WtE2e5BLLNWH6aLXw3zttCA2UL3PlrR31rcooW9qhVEs/1LnFEqDyEs16fiHjMxuMgD6VaoTWZ90Bl7aUD8+yPrbYMXRPwmAWuoV/mq1rWj2jRbX74GuGnxBscl+oebCtSb5eOKs2T5nhkh1duvwzoE5ma2GjNOiCiY9NiCX+0S/R72ewBVhZN/A7363oqjkVBmLyLfChBFGS9Sn/zavQJNrFqMylBBigMf1HizA7yoTpvHWSkaWVPfVgL9bzJcI3mDPlgVZm7KM+SdoMC6bDLNs6+virysqoOGtKVGCBA/p6SVfMghAe+vWTWOsR/tXbdI/5l54w9f5OohfpFPS3J/4Jqs4e4eV6siU6Mn+YpAquhqCgLGiqj/Tk49B5ysKusRzsGkF+OEZ3KOJIuwUR1Vu3u3LHki43273E4Zg6ZNESKbv4VO5OXU+UEiw3mp4yJ1TJbx0zI8gcdq6eGkZf56OgJPp7fq+wn00PLDkpxd2X/1WCxit26bJy1UekJWkttZdMg5TGT5GcAY8uixrkSCrnlE/iSk+9pTrQ9W4/fV1Hj+Hb/tDNYNTD6xIL6N85+tCPeNtPk8p3arDJJEnZ/tp6otihZxjH1tvZ13lV5Um4UvF65dCw00YZm/rucR4UZH8/TcgFcFJnxk6sjq7Y0EpYItrT7VQEcPVn/vP+qojsSQpziL2hIl2r1WJSKuBLUrlkg1czTJ4CMiSaDgK0ed0CypjzCB7lrbuRmRbjcg0sbHJTxsJ7p8yox/l9mUXDX5SAgW7Gai7fH+FdNNXMtwxiWQ6g7hR/epqOwncVZuZpzqX5wFxaha1pmcqZlTUElkB7qRDvvu2QBu0vAwrSOVyrZ49mS/B8Koiw04615BDgKHsY2qsMSr6Xgn6slcrsRkWcNHQi0GObK5a+UXZNcfSTEo7sO0/zq+9GbxUFCD7rIJ1qySVrayN7n+ku2oD/27qWn9HzYDs/v012se+KyyYzhvYSp31ezNq3CUDe9h3MtVVDvXmCe+EdMngGlVRxINkyjcyP41SbVKxaPJDm3B2xddBoeQ2Tpv4G17cOtBiAH+KWFNIzWunfxWhfgr4CpF44VqHWxHVYWlSKNVLY7uK00wcsJqBX2dZTMG6UM1TOm1GXJVQ+LJLRpMxtbUypgJEsWiHrbOvJPEIpR1BRSOgFHqjdl/LlW/nIjfZVI8mhW6aCscXeGxqiwDvExhJSv9Z2khQeTN9g8SyuN8yTgRzqFQbh7D2eaJ89XWRsD8Uz2Cd/2TmeJSIKQUGHKRIDAw7xIBQfXf+rn97kAKzPwSeMqS9qdaTRk+GqkY3gg0dJF9SGNwH/BAB7Qy++b6P2p9ck8rbqwa+/LTJNsor5a8f5+MrmcEdtXzsLbIAfPMbzYdq1Hduso3laID55xMxnV9oxljPUZ7OM6jAMsZr72ZcPJ72ossSJSzf+gwYi5kMSgalmiLnD5fXRiLKQYs7lshDqD/fpBwlV11xx9P8Hlhx6GBHQxCSXEnxKp4xre9yHS68n4FNtffcqZuynT2oA1SIjmXPchLlRw89R+Ot8F48HuZKT3TFieAxJrmucw7oUlk7WqYAZ1emBRHI4eN2hhA3I1gUHW6JEiGTKmk3RYnIjJDtfn9U1UX4KAacJGL5xhJYDPZUrJG6++iDLlXzv/tYsh/QVb+Oz9SUIrdPpBDZKd3JnKmrWQiwdl1QClWCWIZe2/ADRBBCb3NFYzaSfceQrZxFjNDMdnwBRc33nWkbpqKfkSLax9SHbwGXu3IOSdRCvhajzLf8tQM+yXbF0lQVs7ySYueiD1Coi+i1H4D2CU/9Oe5Q9LZOmgdHQ/JUeCxM4/CAknkEASNTX+28f4JzjxiZxmdg8KdPNEp4/3MHTQlu1RGSysIvyYHwuENLBKeeYZkB50hpf4QUJSzSUJiRLDJPa5N0PgSTl/flCxKr90ZiFx1gI7it/VABgpXV0XUZopWTVKOG2pCZkYlQWxkyoTyD/ur72ZLHzhUlcElRKV8+4yrBHVr1zzGsLUkYh7lW6U/i/MI397sGF5fbBukprjG8lOOLiKLaixbVY6rujsKtnZtHGOvtP0VgCjRp4RLV3cs7mpdFAZUSU5rnwGZhN7pitu9+iydPJWwTIknAXxM6iyZqdheBTmFbWyvbKBcbSwMTZuDICrf+fl/fPiItyToodQ6VgnNE5FdzuaJglC+4jpp/VjIJL3VYrx09lVSIoYVG51La0oYA6przGna7EbcgEWSiUpXzD4tj9PSUwcYpeiMmXkTCrD9ifZ9/zeJvK3PzwwCvVwyul/az6KSd1GisEnzl2PZ0a4gu70xHZLuMF80yT+IPGqtAAgjk1DfBnJKK/GPLqLRG1bdbcMKqAQ+2sZAvPSMgC+XcxP8RNFiVoA78Jhss7nX/rdZes1mICicyu1z1zutUQeSSMDS6ifBhAbvcAinlkOLuFQw6Y5Cn4F8GGKyHgc0dS6TQeFpb0EUnd01UvofHhxUFrkS8xVnPX9qj0p/oDzfBpmAemzgd+7OGzKGnSlaW+GgtBAgwoUzcO1x+BzI27yFCt93D4QRyuTC/nVrel/xK3cBcxko2xOZJuuwJ8nHNVK/NSciaAfTMKL+uDM114X8RqG+GXi8Cx0BZFFpQWMQKCcXJQD5v0LZ2khgfodk53CRayFtY9BDYBGQAjFmnouJ9LqHdRszsjhl6UN/2jh+hd0ottIEnN5Crpw2X3NXojTOWEsXJZKM+ym/6OlA46X3s941T5PmUBKfogUaSEoeymiQwU1YqVoeLj+axAJgm7UurXAv1ttgappsEO42Dh1UfHSxnmlIhdot2IDkoNfGw1aAd8ZtaPUN9xnKOoMD0M1Pcl/V8440iCkNlYMylOi/HaXVGFXswLlLQPfoeK/J+wY4RwRCisN4GCXlBfwbFaqHC/N2hWpP7Gv4ReG4zey8QMSsWW0GPc1xb+8u19cmQrln7DNooH3HFh/vPeAIlYjNHhk96lg6+prqZvKIkuR2eaBj+5Mo/1Jydm/HKPZMYQOdB5aBY7/33KYYbZllw1grxsm+UdSpx1WUGQp+JmNCQVQLzqNQz0f3y147LygJEUCZrJSCVorWmY9hKFHURxlYYVp75tQtf8FHO+xqL9OgMMpqbpklt3cWKNL+kh2TL4EqVU2NBd/jCNv2UOLugke1O2Qmkar6I/64HCb4bRR5RAVdUWW4DE5ksXJhCdiPbqwjvGrQ/1+qDR7qnuYVh41GJ2esBL7PZZ58yYVlhSvuSNWi//fbTJ6hkTEyPYKi50rc8pVqlpeFyN9ZKojXvj3bV5WFnbYKndDS5jrtd03GRAhPssNHvLi7vRduJQtC33MBAvPRfDcZC0fpwQ/6bx7zqvmfll/GvkROkyCCrZKYGgxgRPmUOhoey/0HytBwk0Ko9BkafPORzxMoG/vCnvt5F2nwbtsugJ8xU320cjtUeXOcT4WpdmyuaVmNAm76l/g4W1DfLpFxuY3rhMubgM8ph/Yqse52XHT8dIUoyuguLTvsQdfnp3mD060qtlvTGbEUyhnAQJzK/dNA+6sApQtpdtyCwvoroomhWLxVrvlj3YKWcIckc7FvLwpUqTVNVzdByQqXST5di6FZOxOIZhT3M5eSsAMV/2a/TrC0Yy/lFtrfm4hvNrBcSXZTWl0yva3ewWhaSCaPwMS8ODP2W7w9lsY/dizMd7ItMTnRhZMagju1kkHPA/V1qPx31HTtOUPuQyYlOkDcr+k9Y6dfwYmeq8CwINcu8f4Zt83NGBU/mr86lx0vp8k30r/y29vZegjEQS8FpmRQwp3anuG6kofwT+p/c9PtHLL3Wwvov3ikcIytqK/OJ7zQl0UwhwlaY3isH2SqE2Y99DDycd+UX/EFxfN7V2+EuJwCtSjNR+JZJaCNiM2M0pd/Zh37b+NjXoFagP6LlgOqgTWbNcz7LUIRQMEXbIkGD6BvgXDbYioxZt/P2trAURTDZgfilTztomQRBJtyxs52Nv4XspZW8elJk9sMMB8L92O+xaa0NtIIyidvgMCdBg/Fkn1X/8ci/wH+Wqj39Q9tQATjrAk6SIgFPXh1hovtg5Gwav1J0BuaYWOL2bO+CH1//wW989jjIVNdenMd6h3sZjBSjBNg1Q9dgCet5NOMjw3jd433SN5DNdbAHw3IVYITfvVzaC/kpphu6WT5bSSZg6Tjf8Y5NW6LkgefhaBkjWOnmC5JdBi3vvOeLLXDR2iqPhUJX7jEKSgyWcx0+bW4sCmFT76vdJP85H8+XrSWVV7BBjPKqqWyVJ+0y5GbA9u/xaekdBOeamgOUeQrTvKeDeICI8GuOvaC7wMuFjAtNpSuwhhDS0U1EZdlbn3YzWHL3Ui9AzlJY1vlkhGXhhIjUm58ToP8aupEmOJGD/ULbLDOQv4wlGZFRoZzwWjINuSMYiwckOzIFgFc4I+dliOVVZFMIo9CVXCsHG/z5u8mJ//tFjwi4AkIX4zZDipzsH1+qafaXrK9CVHRPlZT6VbkiE7mwkiDvMf67ntpNltA3EQjT6r+eSAtzgpkBNLwmnqaPFFX4ulvPtCfKiCNkNWPeUeWowq7TFfhPa/1QXrFG21ys20MWeCD23Yacn4EznSwUae8i4XPEKz3l6i51sJPAo4oJ/0P8pGHJdVhD49EQZUdOpavkR5c6jVQFH7URMlmhQYEL44YKgVYu8ryhbQiqwyxCbyQNA1Q6L/qOrI8kJWjFdm5husiUhDb4AVNHan7Q8vfjGWThEKWlXjXYYF+fOYSuampyrvajcQPZzpw4MgJP3H4B7bQ0kWlY2IAdn448/HZCoN6rEbNzGfplHgyGvK4DPa2RucoVftsiOHw1L6ETnTfG0iywBemt0lyKYlf1Ljzhe5dh82mtLBgJoI/4XgQyo4350sq6DuO6zQh22vRc5cHpm3GqAL37/A77kQWP3X7Lz9tcH/U/8eubfYRR8GI/68mAtje3BLavX/qPxDRjguTXv/V3YgoEg+sEZJxMO8exSLJqEcmxKhz8qL6yKaRjSlt+YnWEOWv4qXRG1KXXR7MrT2Z8yZSlXD6zHrjc3cKfiEZRv+RUXYvlQl8mk8FCCjOm7BNSJVPBJilG20W5BvC2/hydVEko5rKod2CqNQWKpgWaNsVcrKLMh1b3U/zjyYwfz/r6JdYG6KSb7dMOhdRx2kFRkWFtQEkZNuoLl8JAmjN58Ce4yAU0cZlNwQo2gaUAGE0aN136Lzk6nvU2FZuh4RgD7OKasDQorOcvQlV7Oc2//LeN1n0sfV/vDSqu1xKf57dWLpzZPAC0VViMja3vEzRuzykZWtMgfLVLN5NZKpQcCAz5xZ0zjcQLISp7EgYBv2pUOTsAdYakVW8/YSMJ3PqM2Kaw5tPfmwOCkUS88gnWa5Om+yqn3OuK6KvGxv2CgbjAYIhvo2K48ClC4d1q4Tfj7ZNq7t9jbkD3skAvhLU3fxChdmE0MXxQunZ2ZZvRZj5jEptFUPKQW8Xbmw2/YUoTZ2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diff --git a/docs/reference/fmt.html b/docs/reference/fmt.html
new file mode 100644
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+<meta property="og:title" content="Set a column format with a formatter function — fmt" />
+<meta property="og:description" content="The fmt() function provides greater control in formatting raw data values
+than any of the specialized fmt_*() functions that are available in
+gt. Along with the columns and rows arguments that provide some
+precision in targeting data cells, the fns argument allows you to define
+one or more functions for manipulating the raw data.
+If providing a single function to fns, the recommended format is in the
+form: fns = function(x) .... This single function will format the targeted
+data cells the same way regardless of the output format (e.g., HTML, LaTeX,
+RTF).
+If you require formatting of x that depends on the output format, a list of
+functions can be provided for the html, latex, and default contexts.
+This can be in the form of fns = list(html = function(x) ..., latex = function(x) ..., default = function(x) ...). In this multiple-function case,
+we recommended including the default function as a fallback if all contexts
+aren't provided." />
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Set a column format with a formatter function</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>fmt()</code> function provides greater control in formatting raw data values
+than any of the specialized <code>fmt_*()</code> functions that are available in
+<strong>gt</strong>. Along with the <code>columns</code> and <code>rows</code> arguments that provide some
+precision in targeting data cells, the <code>fns</code> argument allows you to define
+one or more functions for manipulating the raw data.
+If providing a single function to <code>fns</code>, the recommended format is in the
+form: <code>fns = function(x) ...</code>. This single function will format the targeted
+data cells the same way regardless of the output format (e.g., HTML, LaTeX,
+RTF).
+If you require formatting of <code>x</code> that depends on the output format, a list of
+functions can be provided for the <code>html</code>, <code>latex</code>, and <code>default</code> contexts.
+This can be in the form of <code>fns = list(html = function(x) ..., latex = function(x) ..., default = function(x) ...)</code>. In this multiple-function case,
+we recommended including the <code>default</code> function as a fallback if all contexts
+aren't provided.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt</span>(<span class='no'>data</span>, <span class='kw'>columns</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='no'>fns</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>fns</th>
+      <td><p>Either a single formatting function or a named list of functions.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>As with all of the <code>fmt_*()</code> functions, targeting of values is done through
+<code>columns</code> and additionally by <code>rows</code> (if nothing is provided for <code>rows</code> then
+entire columns are selected). A number of helper functions exist to make
+targeting more effective. Conditional formatting is possible by providing a
+conditional expression to the <code>rows</code> argument. See the Arguments section for
+more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-11</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># format the numeric values in the `num`</span>
+<span class='co'># column with a function supplied to</span>
+<span class='co'># the `fns` argument</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>row</span>, -<span class='no'>group</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
+      <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='st'>"'"</span>, <span class='no'>x</span> * <span class='fl'>1000</span>, <span class='st'>"'"</span>)
+    }
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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+</div>
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diff --git a/docs/reference/fmt_currency.html b/docs/reference/fmt_currency.html
new file mode 100644
index 000000000..81c0a204d
--- /dev/null
+++ b/docs/reference/fmt_currency.html
@@ -0,0 +1,440 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Format values as currencies — fmt_currency • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
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+<meta property="og:title" content="Format values as currencies — fmt_currency" />
+<meta property="og:description" content="With numeric values in a gt table, we can perform currency-based
+formatting. This function supports both automatic formatting with a
+three-letter or numeric currency code. We can also specify a custom currency
+that is formatted according to the output context with the currency()
+helper function. Numeric formatting facilitated through the use of a locale
+ID. We have fine control over the conversion from numeric values to currency
+values, where we could take advantage of the following options:
+the currency: providing a currency code or common currency name will
+procure the correct currency symbol and number of currency subunits; we could
+also use the currency() helper function to specify a custom currency
+currency symbol placement: the currency symbol can be placed before
+or after the values
+decimals/subunits: choice of the number of decimal places, and a
+choice of the decimal symbol, and an option on whether to include or exclude
+the currency subunits (decimal portion)
+negative values: choice of a negative sign or parentheses for values
+less than zero
+digit grouping separators: options to enable/disable digit separators
+and provide a choice of separator symbol
+scaling: we can choose to scale targeted values by a multiplier value
+large-number suffixing: larger figures (thousands, millions, etc.) can
+be autoscaled and decorated with the appropriate suffixes
+pattern: option to use a text pattern for decoration of the formatted
+currency values
+locale-based formatting: providing a locale ID will result in
+currency formatting specific to the chosen locale
+We can use the info_currencies() function for a useful reference on all of
+the possible inputs to the currency argument." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Format values as currencies</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_currency.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>With numeric values in a <strong>gt</strong> table, we can perform currency-based
+formatting. This function supports both automatic formatting with a
+three-letter or numeric currency code. We can also specify a custom currency
+that is formatted according to the output context with the <code><a href='currency.html'>currency()</a></code>
+helper function. Numeric formatting facilitated through the use of a locale
+ID. We have fine control over the conversion from numeric values to currency
+values, where we could take advantage of the following options:</p><ul>
+<li><p>the currency: providing a currency code or common currency name will
+procure the correct currency symbol and number of currency subunits; we could
+also use the <code><a href='currency.html'>currency()</a></code> helper function to specify a custom currency</p></li>
+<li><p>currency symbol placement: the currency symbol can be placed before
+or after the values</p></li>
+<li><p>decimals/subunits: choice of the number of decimal places, and a
+choice of the decimal symbol, and an option on whether to include or exclude
+the currency subunits (decimal portion)</p></li>
+<li><p>negative values: choice of a negative sign or parentheses for values
+less than zero</p></li>
+<li><p>digit grouping separators: options to enable/disable digit separators
+and provide a choice of separator symbol</p></li>
+<li><p>scaling: we can choose to scale targeted values by a multiplier value</p></li>
+<li><p>large-number suffixing: larger figures (thousands, millions, etc.) can
+be autoscaled and decorated with the appropriate suffixes</p></li>
+<li><p>pattern: option to use a text pattern for decoration of the formatted
+currency values</p></li>
+<li><p>locale-based formatting: providing a locale ID will result in
+currency formatting specific to the chosen locale</p></li>
+</ul><p>We can use the <code><a href='info_currencies.html'>info_currencies()</a></code> function for a useful reference on all of
+the possible inputs to the <code>currency</code> argument.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_currency</span>(
+  <span class='no'>data</span>,
+  <span class='no'>columns</span>,
+  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"USD"</span>,
+  <span class='kw'>use_subunits</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='kw'>accounting</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>,
+  <span class='kw'>suffixing</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
+  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
+  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
+  <span class='kw'>placement</span> <span class='kw'>=</span> <span class='st'>"left"</span>,
+  <span class='kw'>incl_space</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>currency</th>
+      <td><p>The currency to use for the numeric value. This input can be
+supplied as a 3-letter currency code (e.g., <code>"USD"</code> for U.S. Dollars,
+<code>"EUR"</code> for the Euro currency). Use <code><a href='info_currencies.html'>info_currencies()</a></code> to get an
+information table with all of the valid currency codes and examples of
+each. Alternatively, we can provide a common currency name (e.g.,
+<code>"dollar"</code>, <code>"pound"</code>, <code>"yen"</code>, etc.) to simplify the process. Use
+<code><a href='info_currencies.html'>info_currencies()</a></code> with the <code>type == "symbol"</code> option to view an
+information table with all of the supported currency symbol names along
+with examples.</p>
+<p>We can also use the <code><a href='currency.html'>currency()</a></code> helper function to specify a custom
+currency, where the string could vary across output contexts. For example,
+using <code><a href='currency.html'>currency(html = "&amp;fnof;", default = "f")</a></code> would give us a suitable
+glyph for the Dutch guilder in an HTML output table, and it would simply be
+the letter "f" in all other output contexts). Please note that <code>decimals</code>
+will default to <code>2</code> when using the <code><a href='currency.html'>currency()</a></code> helper function.</p>
+<p>If nothing is provided to <code>currency</code> then <code>"USD"</code> (U.S. dollars) will be
+used.</p></td>
+    </tr>
+    <tr>
+      <th>use_subunits</th>
+      <td><p>An option for whether the subunits portion of a currency
+value should be displayed. By default, this is <code>TRUE</code>.</p></td>
+    </tr>
+    <tr>
+      <th>accounting</th>
+      <td><p>An option to use accounting style for currency values. With
+<code>FALSE</code> (the default), negative values will be shown with a minus sign.
+Using <code>accounting = TRUE</code> will put negative values in parentheses.</p></td>
+    </tr>
+    <tr>
+      <th>decimals</th>
+      <td><p>An option to specify the exact number of decimal places to
+use. The default number of decimal places is <code>2</code>.</p></td>
+    </tr>
+    <tr>
+      <th>use_seps</th>
+      <td><p>An option to use digit group separators. The type of digit
+group separator is set by <code>sep_mark</code> and overridden if a locale ID is
+provided to <code>locale</code>. This setting is <code>TRUE</code> by default.</p></td>
+    </tr>
+    <tr>
+      <th>scale_by</th>
+      <td><p>A value to scale the input. The default is <code>1.0</code>. All numeric
+values will be multiplied by this value first before undergoing formatting.
+This value will be ignored if using any of the <code>suffixing</code> options (i.e.,
+where <code>suffixing</code> is not set to <code>FALSE</code>).</p></td>
+    </tr>
+    <tr>
+      <th>suffixing</th>
+      <td><p>An option to scale and apply suffixes to larger numbers
+(e.g., <code>1924000</code> can be transformed to <code>1.92M</code>). This option can accept a
+logical value, where <code>FALSE</code> (the default) will not perform this
+transformation and <code>TRUE</code> will apply thousands (<code>K</code>), millions (<code>M</code>),
+billions (<code>B</code>), and trillions (<code>T</code>) suffixes after automatic value scaling.
+We can also specify which symbols to use for each of the value ranges by
+using a character vector of the preferred symbols to replace the defaults
+(e.g., <code><a href='https://rdrr.io/r/base/c.html'>c("k", "Ml", "Bn", "Tr")</a></code>).</p>
+<p>Including <code>NA</code> values in the vector will ensure that the particular range
+will either not be included in the transformation (e.g, <code><a href='https://rdrr.io/r/base/c.html'>c(NA, "M", "B", "T")</a></code> won't modify numbers in the thousands range) or the range will
+inherit a previous suffix (e.g., with <code><a href='https://rdrr.io/r/base/c.html'>c("K", "M", NA, "T")</a></code>, all numbers
+in the range of millions and billions will be in terms of millions).</p>
+<p>Any use of <code>suffixing</code> (where it is not set expressly as <code>FALSE</code>) means
+that any value provided to <code>scale_by</code> will be ignored.</p></td>
+    </tr>
+    <tr>
+      <th>pattern</th>
+      <td><p>A formatting pattern that allows for decoration of the
+formatted value. The value itself is represented by <code>{x}</code> and all other
+characters are taken to be string literals.</p></td>
+    </tr>
+    <tr>
+      <th>sep_mark</th>
+      <td><p>The mark to use as a separator between groups of digits
+(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
+of <code>1,000</code>).</p></td>
+    </tr>
+    <tr>
+      <th>dec_mark</th>
+      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
+    </tr>
+    <tr>
+      <th>placement</th>
+      <td><p>The placement of the currency symbol. This can be either be
+<code>left</code> (the default) or <code>right</code>.</p></td>
+    </tr>
+    <tr>
+      <th>incl_space</th>
+      <td><p>An option for whether to include a space between the value
+and the currency symbol. The default is to not introduce a space character.</p></td>
+    </tr>
+    <tr>
+      <th>locale</th>
+      <td><p>An optional locale ID that can be used for formatting the value
+according the locale's rules. Examples include <code>"en_US"</code> for English
+(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
+locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
+We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
+the locales that are supported.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_currency_1.png' width=100% /></p>
+<p><img src='figures/man_fmt_currency_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># format the `currency` column to have</span>
+<span class='co'># currency values in euros (EUR)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_currency</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"EUR"</span>
+  )
+
+<span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># Keep only the `num` and `currency`,</span>
+<span class='co'># columns, then, format those columns</span>
+<span class='co'># using the "CNY" and "GBP" currencies</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_currency</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"CNY"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_currency</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"GBP"</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
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+<meta property="og:description" content="Format input date values that are either of the Date type, or, are
+character-based and expressed according to the ISO 8601 date format
+(YYYY-MM-DD). Once the appropriate data cells are targeted with columns
+(and, optionally, rows), we can simply apply a preset date style to format
+the dates. The following date styles are available for simpler formatting of
+ISO dates (all using the input date of 2000-02-29 in the example output
+dates):
+iso: 2000-02-29
+wday_month_day_year: Tuesday, February 29, 2000
+wd_m_day_year: Tue, Feb 29, 2000
+wday_day_month_year: Tuesday 29 February 2000
+month_day_year: February 29, 2000
+m_day_year: Feb 29, 2000
+day_m_year: 29 Feb 2000
+day_month_year: 29 February 2000
+day_month: 29 February
+year: 2000
+month: February
+day: 29
+year.mn.day: 2000/02/29
+y.mn.day: 0/02/29
+We can use the info_date_style() function for a useful reference on all of
+the possible inputs to date_style." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Format values as dates</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_date.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Format input date values that are either of the <code>Date</code> type, or, are
+character-based and expressed according to the ISO 8601 date format
+(<code>YYYY-MM-DD</code>). Once the appropriate data cells are targeted with <code>columns</code>
+(and, optionally, <code>rows</code>), we can simply apply a preset date style to format
+the dates. The following date styles are available for simpler formatting of
+ISO dates (all using the input date of <code>2000-02-29</code> in the example output
+dates):</p><ol>
+<li><p>iso: <code>2000-02-29</code></p></li>
+<li><p>wday_month_day_year: <code>Tuesday, February 29, 2000</code></p></li>
+<li><p>wd_m_day_year: <code>Tue, Feb 29, 2000</code></p></li>
+<li><p>wday_day_month_year: <code>Tuesday 29 February 2000</code></p></li>
+<li><p>month_day_year: <code>February 29, 2000</code></p></li>
+<li><p>m_day_year: <code>Feb 29, 2000</code></p></li>
+<li><p>day_m_year: <code>29 Feb 2000</code></p></li>
+<li><p>day_month_year: <code>29 February 2000</code></p></li>
+<li><p>day_month: <code>29 February</code></p></li>
+<li><p>year: <code>2000</code></p></li>
+<li><p>month: <code>February</code></p></li>
+<li><p>day: <code>29</code></p></li>
+<li><p>year.mn.day: <code>2000/02/29</code></p></li>
+<li><p>y.mn.day: <code>0/02/29</code></p></li>
+</ol><p>We can use the <code><a href='info_date_style.html'>info_date_style()</a></code> function for a useful reference on all of
+the possible inputs to <code>date_style</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_date</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>2</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>date_style</th>
+      <td><p>The date style to use. Supply a number (from <code>1</code> to <code>14</code>)
+that corresponds to the preferred date style. Use <code><a href='info_date_style.html'>info_date_style()</a></code> to
+see the different numbered and named date presets.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_date_1.png' width=100% /></p>
+<p><img src='figures/man_fmt_date_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># keep only the `date` and `time` columns;</span>
+<span class='co'># format the `date` column to have</span>
+<span class='co'># dates formatted as `month_day_year`</span>
+<span class='co'># (date style `5`)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_date</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>),
+    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>5</span>
+  )
+
+<span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># keep only the `date` and `time` columns;</span>
+<span class='co'># format the `date` column to have mixed</span>
+<span class='co'># date formats (dates after April will</span>
+<span class='co'># be different than the others)</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_date</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span>
+      <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='no'>date</span>) <span class='kw'>&gt;</span> <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2015-04-01"</span>),
+    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>6</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_date</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span>
+      <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='no'>date</span>) <span class='kw'>&lt;=</span> <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2015-04-01"</span>),
+    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>7</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+</div>
+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/fmt_datetime.html b/docs/reference/fmt_datetime.html
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--- /dev/null
+++ b/docs/reference/fmt_datetime.html
@@ -0,0 +1,326 @@
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+<title>Format values as date-times — fmt_datetime • gt</title>
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+<meta property="og:title" content="Format values as date-times — fmt_datetime" />
+<meta property="og:description" content="Format input date-time values that are character-based and expressed
+according to the ISO 8601 date-time format (YYYY-MM-DD HH:MM:SS). Once the
+appropriate data cells are targeted with columns (and, optionally, rows),
+we can simply apply preset date and time styles to format the date-time
+values. The following date styles are available for simpler formatting of the
+date portion (all using the input date of 2000-02-29 in the example output
+dates):
+iso: 2000-02-29
+wday_month_day_year: Tuesday, February 29, 2000
+wd_m_day_year: Tue, Feb 29, 2000
+wday_day_month_year: Tuesday 29 February 2000
+month_day_year: February 29, 2000
+m_day_year: Feb 29, 2000
+day_m_year: 29 Feb 2000
+day_month_year: 29 February 2000
+day_month: 29 February
+year: 2000
+month: February
+day: 29
+year.mn.day: 2000/02/29
+y.mn.day: 0/02/29
+The following time styles are available for simpler formatting of the time
+portion (all using the input time of 14:35:00 in the example output times):
+hms: 14:35:00
+hm: 14:35
+hms_p: 2:35:00 PM
+hm_p: 2:35 PM
+h_p: 2 PM
+We can use the info_date_style() and info_time_style() functions as
+useful references for all of the possible inputs to date_style and
+time_style." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+    <div class="page-header">
+    <h1>Format values as date-times</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_datetime.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Format input date-time values that are character-based and expressed
+according to the ISO 8601 date-time format (<code>YYYY-MM-DD HH:MM:SS</code>). Once the
+appropriate data cells are targeted with <code>columns</code> (and, optionally, <code>rows</code>),
+we can simply apply preset date and time styles to format the date-time
+values. The following date styles are available for simpler formatting of the
+date portion (all using the input date of <code>2000-02-29</code> in the example output
+dates):</p><ol>
+<li><p>iso: <code>2000-02-29</code></p></li>
+<li><p>wday_month_day_year: <code>Tuesday, February 29, 2000</code></p></li>
+<li><p>wd_m_day_year: <code>Tue, Feb 29, 2000</code></p></li>
+<li><p>wday_day_month_year: <code>Tuesday 29 February 2000</code></p></li>
+<li><p>month_day_year: <code>February 29, 2000</code></p></li>
+<li><p>m_day_year: <code>Feb 29, 2000</code></p></li>
+<li><p>day_m_year: <code>29 Feb 2000</code></p></li>
+<li><p>day_month_year: <code>29 February 2000</code></p></li>
+<li><p>day_month: <code>29 February</code></p></li>
+<li><p>year: <code>2000</code></p></li>
+<li><p>month: <code>February</code></p></li>
+<li><p>day: <code>29</code></p></li>
+<li><p>year.mn.day: <code>2000/02/29</code></p></li>
+<li><p>y.mn.day: <code>0/02/29</code></p></li>
+</ol><p>The following time styles are available for simpler formatting of the time
+portion (all using the input time of <code>14:35:00</code> in the example output times):</p><ol>
+<li><p>hms: <code>14:35:00</code></p></li>
+<li><p>hm: <code>14:35</code></p></li>
+<li><p>hms_p: <code>2:35:00 PM</code></p></li>
+<li><p>hm_p: <code>2:35 PM</code></p></li>
+<li><p>h_p: <code>2 PM</code></p></li>
+</ol><p>We can use the <code><a href='info_date_style.html'>info_date_style()</a></code> and <code><a href='info_time_style.html'>info_time_style()</a></code> functions as
+useful references for all of the possible inputs to <code>date_style</code> and
+<code>time_style</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_datetime</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>2</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>date_style</th>
+      <td><p>The date style to use. Supply a number (from <code>1</code> to <code>14</code>)
+that corresponds to the preferred date style. Use <code><a href='info_date_style.html'>info_date_style()</a></code> to
+see the different numbered and named date presets.</p></td>
+    </tr>
+    <tr>
+      <th>time_style</th>
+      <td><p>The time style to use. Supply a number (from <code>1</code> to <code>5</code>)
+that corresponds to the preferred time style. Use <code><a href='info_time_style.html'>info_time_style()</a></code> to
+see the different numbered and named time presets.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_datetime_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-7</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># keep only the `datetime` column;</span>
+<span class='co'># format the column to have dates</span>
+<span class='co'># formatted as `month_day_year` and</span>
+<span class='co'># times to be `hms_p`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>datetime</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_datetime</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>datetime</span>),
+    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>5</span>,
+    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>3</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/fmt_markdown.html b/docs/reference/fmt_markdown.html
new file mode 100644
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+<meta property="og:description" content="Any Markdown-formatted text in the incoming cells will be transformed to the
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+    <div class="page-header">
+    <h1>Format Markdown text</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_markdown.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Any Markdown-formatted text in the incoming cells will be transformed to the
+appropriate output type during render when using <code>fmt_markdown()</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_markdown</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_markdown_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-8</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Create a few Markdown-based</span>
+<span class='co'># text snippets</span>
+<span class='no'>text_1a</span> <span class='kw'>&lt;-</span> <span class='st'>"
+### This is Markdown.
+
+Markdown’s syntax is comprised entirely of
+punctuation characters, which punctuation
+characters have been carefully chosen so as
+to look like what they mean... assuming
+you’ve ever used email.
+"</span>
+
+<span class='no'>text_1b</span> <span class='kw'>&lt;-</span> <span class='st'>"
+Info on Markdown syntax can be found
+[here](https://daringfireball.net/projects/markdown/).
+"</span>
+
+<span class='no'>text_2a</span> <span class='kw'>&lt;-</span> <span class='st'>"
+The **gt** package has these datasets:
+
+ - `countrypops`
+ - `sza`
+ - `gtcars`
+ - `sp500`
+ - `pizzaplace`
+ - `exibble`
+"</span>
+
+<span class='no'>text_2b</span> <span class='kw'>&lt;-</span> <span class='st'>"
+There's a quick reference [here](https://commonmark.org/help/).
+"</span>
+
+<span class='co'># Arrange the text snippets as a tibble</span>
+<span class='co'># using the `dplyr::tribble()` function;</span>
+<span class='co'># then, create a gt table and format</span>
+<span class='co'># all columns with `fmt_markdown()`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tribble</a></span>(
+    ~<span class='no'>Markdown</span>, ~<span class='no'>md</span>,
+    <span class='no'>text_1a</span>,   <span class='no'>text_2a</span>,
+    <span class='no'>text_1b</span>,   <span class='no'>text_2b</span>,
+  ) <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+    <span class='fu'>fmt_markdown</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='tab_options.html'>tab_options</a></span>(<span class='kw'>table.width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>400</span>))</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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+</div>
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diff --git a/docs/reference/fmt_missing.html b/docs/reference/fmt_missing.html
new file mode 100644
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+++ b/docs/reference/fmt_missing.html
@@ -0,0 +1,266 @@
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+<meta property="og:description" content="Wherever there is missing data (i.e., NA values) a customizable mark may
+present better than the standard NA text that would otherwise appear. The
+fmt_missing() function allows for this replacement through its
+missing_text argument (where an em dash serves as the default)." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Format missing values</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_missing.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Wherever there is missing data (i.e., <code>NA</code> values) a customizable mark may
+present better than the standard <code>NA</code> text that would otherwise appear. The
+<code>fmt_missing()</code> function allows for this replacement through its
+<code>missing_text</code> argument (where an em dash serves as the default).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_missing</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"---"</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>missing_text</th>
+      <td><p>The text to be used in place of <code>NA</code> values in the
+rendered table.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_missing_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-10</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># NA values in different columns will</span>
+<span class='co'># be given replacement text</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>row</span>, -<span class='no'>group</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_missing</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>2</span>,
+    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"missing"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_missing</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>4</span>:<span class='fl'>7</span>,
+    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"nothing"</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+<meta property="og:title" content="Format numeric values — fmt_number" />
+<meta property="og:description" content="With numeric values in a gt table, we can perform number-based
+formatting so that the targeted values are rendered with a higher
+consideration for tabular presentation. Furthermore, there is finer control
+over numeric formatting with the following options:
+decimals: choice of the number of decimal places, option to drop
+trailing zeros, and a choice of the decimal symbol
+digit grouping separators: options to enable/disable digit separators
+and provide a choice of separator symbol
+scaling: we can choose to scale targeted values by a multiplier value
+large-number suffixing: larger figures (thousands, millions, etc.) can
+be autoscaled and decorated with the appropriate suffixes
+pattern: option to use a text pattern for decoration of the formatted
+values
+locale-based formatting: providing a locale ID will result in number
+formatting specific to the chosen locale
+
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+    <div class="page-header">
+    <h1>Format numeric values</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_number.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>With numeric values in a <strong>gt</strong> table, we can perform number-based
+formatting so that the targeted values are rendered with a higher
+consideration for tabular presentation. Furthermore, there is finer control
+over numeric formatting with the following options:</p><ul>
+<li><p>decimals: choice of the number of decimal places, option to drop
+trailing zeros, and a choice of the decimal symbol</p></li>
+<li><p>digit grouping separators: options to enable/disable digit separators
+and provide a choice of separator symbol</p></li>
+<li><p>scaling: we can choose to scale targeted values by a multiplier value</p></li>
+<li><p>large-number suffixing: larger figures (thousands, millions, etc.) can
+be autoscaled and decorated with the appropriate suffixes</p></li>
+<li><p>pattern: option to use a text pattern for decoration of the formatted
+values</p></li>
+<li><p>locale-based formatting: providing a locale ID will result in number
+formatting specific to the chosen locale</p></li>
+</ul>
+
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_number</span>(
+  <span class='no'>data</span>,
+  <span class='no'>columns</span>,
+  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
+  <span class='kw'>drop_trailing_zeros</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>,
+  <span class='kw'>suffixing</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
+  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
+  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
+  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>decimals</th>
+      <td><p>An option to specify the exact number of decimal places to
+use. The default number of decimal places is <code>2</code>.</p></td>
+    </tr>
+    <tr>
+      <th>drop_trailing_zeros</th>
+      <td><p>A logical value that allows for removal of
+trailing zeros (those redundant zeros after the decimal mark).</p></td>
+    </tr>
+    <tr>
+      <th>use_seps</th>
+      <td><p>An option to use digit group separators. The type of digit
+group separator is set by <code>sep_mark</code> and overridden if a locale ID is
+provided to <code>locale</code>. This setting is <code>TRUE</code> by default.</p></td>
+    </tr>
+    <tr>
+      <th>scale_by</th>
+      <td><p>A value to scale the input. The default is <code>1.0</code>. All numeric
+values will be multiplied by this value first before undergoing formatting.
+This value will be ignored if using any of the <code>suffixing</code> options (i.e.,
+where <code>suffixing</code> is not set to <code>FALSE</code>).</p></td>
+    </tr>
+    <tr>
+      <th>suffixing</th>
+      <td><p>An option to scale and apply suffixes to larger numbers
+(e.g., <code>1924000</code> can be transformed to <code>1.92M</code>). This option can accept a
+logical value, where <code>FALSE</code> (the default) will not perform this
+transformation and <code>TRUE</code> will apply thousands (<code>K</code>), millions (<code>M</code>),
+billions (<code>B</code>), and trillions (<code>T</code>) suffixes after automatic value scaling.
+We can also specify which symbols to use for each of the value ranges by
+using a character vector of the preferred symbols to replace the defaults
+(e.g., <code><a href='https://rdrr.io/r/base/c.html'>c("k", "Ml", "Bn", "Tr")</a></code>).</p>
+<p>Including <code>NA</code> values in the vector will ensure that the particular range
+will either not be included in the transformation (e.g, <code><a href='https://rdrr.io/r/base/c.html'>c(NA, "M", "B", "T")</a></code> won't modify numbers in the thousands range) or the range will
+inherit a previous suffix (e.g., with <code><a href='https://rdrr.io/r/base/c.html'>c("K", "M", NA, "T")</a></code>, all numbers
+in the range of millions and billions will be in terms of millions).</p>
+<p>Any use of <code>suffixing</code> (where it is not set expressly as <code>FALSE</code>) means
+that any value provided to <code>scale_by</code> will be ignored.</p></td>
+    </tr>
+    <tr>
+      <th>pattern</th>
+      <td><p>A formatting pattern that allows for decoration of the
+formatted value. The value itself is represented by <code>{x}</code> and all other
+characters are taken to be string literals.</p></td>
+    </tr>
+    <tr>
+      <th>sep_mark</th>
+      <td><p>The mark to use as a separator between groups of digits
+(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
+of <code>1,000</code>).</p></td>
+    </tr>
+    <tr>
+      <th>dec_mark</th>
+      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
+    </tr>
+    <tr>
+      <th>locale</th>
+      <td><p>An optional locale ID that can be used for formatting the value
+according the locale's rules. Examples include <code>"en_US"</code> for English
+(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
+locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
+We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
+the locales that are supported.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_number_1.png' width=100% /></p>
+<p><img src='figures/man_fmt_number_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>tidyr</span>)
+
+<span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># format the `num` column as numeric</span>
+<span class='co'># with three decimal places and with no</span>
+<span class='co'># use of digit separators</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_number</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>3</span>,
+    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
+  )
+
+<span class='co'># Use `countrypops` to create a gt</span>
+<span class='co'># table; format all numeric columns</span>
+<span class='co'># to use large-number suffixing</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>country_code_3</span>, <span class='no'>year</span>, <span class='no'>population</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>country_code_3</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(
+      <span class='st'>"CHN"</span>, <span class='st'>"IND"</span>, <span class='st'>"USA"</span>, <span class='st'>"PAK"</span>, <span class='st'>"IDN"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>year</span> <span class='kw'>&gt;</span> <span class='fl'>1975</span> <span class='kw'>&amp;</span> <span class='no'>year</span> <span class='kw'>%%</span> <span class='fl'>5</span> <span class='kw'>==</span> <span class='fl'>0</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>tidyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://tidyr.tidyverse.org/reference/spread.html'>spread</a></span>(<span class='no'>year</span>, <span class='no'>population</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='fu'>desc</span>(<span class='no'>`2015`</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"country_code_3"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_number</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>2</span>:<span class='fl'>9</span>,
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
+    <span class='kw'>suffixing</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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diff --git a/docs/reference/fmt_passthrough.html b/docs/reference/fmt_passthrough.html
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+coercing to character (as all the fmt_*() functions do), and (2) applying
+text via the pattern argument (the default is to apply nothing). All of
+this is useful when don't want to modify the input data other than to
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+    <div class="page-header">
+    <h1>Format by simply passing data through</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_passthrough.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Format by passing data through no other transformation other than: (1)
+coercing to <code>character</code> (as all the <code>fmt_*()</code> functions do), and (2) applying
+text via the <code>pattern</code> argument (the default is to apply nothing). All of
+this is useful when don't want to modify the input data other than to
+decorate it within a pattern. Also, this function is useful when used as the
+<code>formatter</code> function in the <code><a href='summary_rows.html'>summary_rows()</a></code> function, where the output may
+be text or useful as is.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_passthrough</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>escape</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>escape</th>
+      <td><p>An option to escape text according to the final output format
+of the table. For example, if a LaTeX table is to be generated then LaTeX
+escaping would be performed during rendering. By default this is set to
+<code>TRUE</code> and setting to <code>FALSE</code> is useful in the case where LaTeX-formatted
+text should be passed through to the output LaTeX table unchanged.</p></td>
+    </tr>
+    <tr>
+      <th>pattern</th>
+      <td><p>A formatting pattern that allows for decoration of the
+formatted value. The value itself is represented by <code>{x}</code> and all other
+characters are taken to be string literals.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_passthrough_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-9</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># keep only the `char` column;</span>
+<span class='co'># pass the data in that column through</span>
+<span class='co'># but apply a simple pattern that adds</span>
+<span class='co'># an 's' to the non-NA values</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>char</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_passthrough</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>char</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span> !<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>char</span>),
+    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}s"</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+</div>
+
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diff --git a/docs/reference/fmt_percent.html b/docs/reference/fmt_percent.html
new file mode 100644
index 000000000..98df2eaf5
--- /dev/null
+++ b/docs/reference/fmt_percent.html
@@ -0,0 +1,357 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Format values as a percentage — fmt_percent • gt</title>
+
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+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
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+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
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+<meta property="og:title" content="Format values as a percentage — fmt_percent" />
+<meta property="og:description" content="With numeric values in a gt table, we can perform percentage-based
+formatting. It is assumed the input numeric values are in a fractional format
+since the numbers will be automatically multiplied by 100 before decorating
+with a percent sign. For more control over percentage formatting, we can use
+the following options:
+percent sign placement: the percent sign can be placed after or
+before the values and a space can be inserted between the symbol and the
+value.
+decimals: choice of the number of decimal places, option to drop
+trailing zeros, and a choice of the decimal symbol
+digit grouping separators: options to enable/disable digit separators
+and provide a choice of separator symbol
+pattern: option to use a text pattern for decoration of the formatted
+values
+locale-based formatting: providing a locale ID will result in number
+formatting specific to the chosen locale
+
+" />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Format values as a percentage</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_percent.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>With numeric values in a <strong>gt</strong> table, we can perform percentage-based
+formatting. It is assumed the input numeric values are in a fractional format
+since the numbers will be automatically multiplied by <code>100</code> before decorating
+with a percent sign. For more control over percentage formatting, we can use
+the following options:</p><ul>
+<li><p>percent sign placement: the percent sign can be placed after or
+before the values and a space can be inserted between the symbol and the
+value.</p></li>
+<li><p>decimals: choice of the number of decimal places, option to drop
+trailing zeros, and a choice of the decimal symbol</p></li>
+<li><p>digit grouping separators: options to enable/disable digit separators
+and provide a choice of separator symbol</p></li>
+<li><p>pattern: option to use a text pattern for decoration of the formatted
+values</p></li>
+<li><p>locale-based formatting: providing a locale ID will result in number
+formatting specific to the chosen locale</p></li>
+</ul>
+
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_percent</span>(
+  <span class='no'>data</span>,
+  <span class='no'>columns</span>,
+  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
+  <span class='kw'>drop_trailing_zeros</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
+  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
+  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
+  <span class='kw'>incl_space</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>placement</span> <span class='kw'>=</span> <span class='st'>"right"</span>,
+  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>decimals</th>
+      <td><p>An option to specify the exact number of decimal places to
+use. The default number of decimal places is <code>2</code>.</p></td>
+    </tr>
+    <tr>
+      <th>drop_trailing_zeros</th>
+      <td><p>A logical value that allows for removal of
+trailing zeros (those redundant zeros after the decimal mark).</p></td>
+    </tr>
+    <tr>
+      <th>use_seps</th>
+      <td><p>An option to use digit group separators. The type of digit
+group separator is set by <code>sep_mark</code> and overridden if a locale ID is
+provided to <code>locale</code>. This setting is <code>TRUE</code> by default.</p></td>
+    </tr>
+    <tr>
+      <th>pattern</th>
+      <td><p>A formatting pattern that allows for decoration of the
+formatted value. The value itself is represented by <code>{x}</code> and all other
+characters are taken to be string literals.</p></td>
+    </tr>
+    <tr>
+      <th>sep_mark</th>
+      <td><p>The mark to use as a separator between groups of digits
+(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
+of <code>1,000</code>).</p></td>
+    </tr>
+    <tr>
+      <th>dec_mark</th>
+      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
+    </tr>
+    <tr>
+      <th>incl_space</th>
+      <td><p>An option for whether to include a space between the value
+and the percent sign. The default is to not introduce a space character.</p></td>
+    </tr>
+    <tr>
+      <th>placement</th>
+      <td><p>The placement of the percent sign. This can be either be
+<code>right</code> (the default) or <code>left</code>.</p></td>
+    </tr>
+    <tr>
+      <th>locale</th>
+      <td><p>An optional locale ID that can be used for formatting the value
+according the locale's rules. Examples include <code>"en_US"</code> for English
+(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
+locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
+We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
+the locales that are supported.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_percent_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `pizzaplace` to create a gt table;</span>
+<span class='co'># format the `frac_of_quota` column to</span>
+<span class='co'># display values as percentages</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>month</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='no'>date</span>, <span class='fl'>6</span>, <span class='fl'>7</span>))) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>month</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(<span class='kw'>pizzas_sold</span> <span class='kw'>=</span> <span class='fu'>n</span>()) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>ungroup</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>frac_of_quota</span> <span class='kw'>=</span> <span class='no'>pizzas_sold</span> / <span class='fl'>4000</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"month"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_percent</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>frac_of_quota</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
+  )</div><div class='output co'>#&gt; <span class='error'>Error: `summarise()` argument `pizzas_sold` errored.</span>
+#&gt; <span class='error'><span style='color: #0000BB;'>ℹ</span><span> `pizzas_sold` is `n()`.</span>
+#&gt; <span class='error'></span><span style='color: #0000BB;'>ℹ</span><span> The error occured in group 1: month = 1.</span>
+#&gt; <span class='error'></span><span style='color: #BB0000;'>x</span><span> could not find function "n"</span></div><div class='input'>
+</div></span></pre>
+  </div>
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diff --git a/docs/reference/fmt_scientific.html b/docs/reference/fmt_scientific.html
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+<meta property="og:title" content="Format values to scientific notation — fmt_scientific" />
+<meta property="og:description" content="With numeric values in a gt table, we can perform formatting so that the
+targeted values are rendered in scientific notation. Furthermore, there is
+fine control with the following options:
+decimals: choice of the number of decimal places, option to drop
+trailing zeros, and a choice of the decimal symbol
+scaling: we can choose to scale targeted values by a multiplier value
+pattern: option to use a text pattern for decoration of the formatted
+values
+locale-based formatting: providing a locale ID will result in
+formatting specific to the chosen locale
+
+" />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Format values to scientific notation</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_scientific.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>With numeric values in a <strong>gt</strong> table, we can perform formatting so that the
+targeted values are rendered in scientific notation. Furthermore, there is
+fine control with the following options:</p><ul>
+<li><p>decimals: choice of the number of decimal places, option to drop
+trailing zeros, and a choice of the decimal symbol</p></li>
+<li><p>scaling: we can choose to scale targeted values by a multiplier value</p></li>
+<li><p>pattern: option to use a text pattern for decoration of the formatted
+values</p></li>
+<li><p>locale-based formatting: providing a locale ID will result in
+formatting specific to the chosen locale</p></li>
+</ul>
+
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_scientific</span>(
+  <span class='no'>data</span>,
+  <span class='no'>columns</span>,
+  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
+  <span class='kw'>drop_trailing_zeros</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>,
+  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
+  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
+  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
+  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>decimals</th>
+      <td><p>An option to specify the exact number of decimal places to
+use. The default number of decimal places is <code>2</code>.</p></td>
+    </tr>
+    <tr>
+      <th>drop_trailing_zeros</th>
+      <td><p>A logical value that allows for removal of
+trailing zeros (those redundant zeros after the decimal mark).</p></td>
+    </tr>
+    <tr>
+      <th>scale_by</th>
+      <td><p>A value to scale the input. The default is <code>1.0</code>. All numeric
+values will be multiplied by this value first before undergoing formatting.
+This value will be ignored if using any of the <code>suffixing</code> options (i.e.,
+where <code>suffixing</code> is not set to <code>FALSE</code>).</p></td>
+    </tr>
+    <tr>
+      <th>pattern</th>
+      <td><p>A formatting pattern that allows for decoration of the
+formatted value. The value itself is represented by <code>{x}</code> and all other
+characters are taken to be string literals.</p></td>
+    </tr>
+    <tr>
+      <th>sep_mark</th>
+      <td><p>The mark to use as a separator between groups of digits
+(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
+of <code>1,000</code>).</p></td>
+    </tr>
+    <tr>
+      <th>dec_mark</th>
+      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
+    </tr>
+    <tr>
+      <th>locale</th>
+      <td><p>An optional locale ID that can be used for formatting the value
+according the locale's rules. Examples include <code>"en_US"</code> for English
+(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
+locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
+We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
+the locales that are supported.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_scientific_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># format the `num` column as partially</span>
+<span class='co'># numeric and partially in scientific</span>
+<span class='co'># notation</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;</span> <span class='fl'>500</span>,
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>,
+    <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>/<span class='fl'>1000</span>,
+    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}K"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_scientific</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&lt;=</span> <span class='fl'>500</span>,
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+<meta property="og:title" content="Format values as times — fmt_time" />
+<meta property="og:description" content="Format input time values that are character-based and expressed according to
+the ISO 8601 time format (HH:MM:SS). Once the appropriate data cells are
+targeted with columns (and, optionally, rows), we can simply apply a
+preset time style to format the times. The following time styles are
+available for simpler formatting of ISO times (all using the input time of
+14:35:00 in the example output times):
+hms: 14:35:00
+hm: 14:35
+hms_p: 2:35:00 PM
+hm_p: 2:35 PM
+h_p: 2 PM
+We can use the info_time_style() function for a useful reference on all of
+the possible inputs to time_style." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Format values as times</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
+    <div class="hidden name"><code>fmt_time.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Format input time values that are character-based and expressed according to
+the ISO 8601 time format (<code>HH:MM:SS</code>). Once the appropriate data cells are
+targeted with <code>columns</code> (and, optionally, <code>rows</code>), we can simply apply a
+preset time style to format the times. The following time styles are
+available for simpler formatting of ISO times (all using the input time of
+<code>14:35:00</code> in the example output times):</p><ol>
+<li><p>hms: <code>14:35:00</code></p></li>
+<li><p>hm: <code>14:35</code></p></li>
+<li><p>hms_p: <code>2:35:00 PM</code></p></li>
+<li><p>hm_p: <code>2:35 PM</code></p></li>
+<li><p>h_p: <code>2 PM</code></p></li>
+</ol><p>We can use the <code><a href='info_time_style.html'>info_time_style()</a></code> function for a useful reference on all of
+the possible inputs to <code>time_style</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>fmt_time</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>2</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to format. Can either be a series of column names
+provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
+focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>Optional rows to format. Not providing any value results in all
+rows in <code>columns</code> being formatted. Can either be a vector of row captions
+provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
+selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
+We can also use expressions to filter down to the rows we need (e.g.,
+<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
+    </tr>
+    <tr>
+      <th>time_style</th>
+      <td><p>The time style to use. Supply a number (from <code>1</code> to <code>5</code>)
+that corresponds to the preferred time style. Use <code><a href='info_time_style.html'>info_time_style()</a></code> to
+see the different numbered and named time presets.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
+nothing is provided for <code>rows</code> then entire columns are selected). A number of
+helper functions exist to make targeting more effective. Conditional
+formatting is possible by providing a conditional expression to the <code>rows</code>
+argument. See the Arguments section for more information on this.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_fmt_time_1.png' width=100% /></p>
+<p><img src='figures/man_fmt_time_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-6</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code>,
+<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># keep only the `date` and `time` columns;</span>
+<span class='co'># format the `time` column to have</span>
+<span class='co'># times formatted as `hms_p`</span>
+<span class='co'># (time style `3`)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_time</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>time</span>),
+    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>3</span>
+  )
+
+<span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># keep only the `date` and `time` columns;</span>
+<span class='co'># format the `time` column to have mixed</span>
+<span class='co'># time formats (times after 16:00 will</span>
+<span class='co'># be different than the others)</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_time</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>time</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span>
+      <span class='no'>time</span> <span class='kw'>&gt;</span> <span class='st'>"16:00"</span>,
+    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>3</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>fmt_time</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>time</span>),
+    <span class='kw'>rows</span> <span class='kw'>=</span>
+      <span class='no'>time</span> <span class='kw'>&lt;=</span> <span class='st'>"16:00"</span>,
+    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>4</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/ggplot_image.html b/docs/reference/ggplot_image.html
new file mode 100644
index 000000000..24004bfb3
--- /dev/null
+++ b/docs/reference/ggplot_image.html
@@ -0,0 +1,280 @@
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+<meta property="og:title" content="Helper function for adding a ggplot — ggplot_image" />
+<meta property="og:description" content="We can add a ggplot2 plot inside of a table with the help of the
+ggplot_image() function. The function provides a convenient way to generate
+an HTML fragment with a ggplot object. Because this function is currently
+HTML-based, it is only useful for HTML table output. To use this function
+inside of data cells, it is recommended that the text_transform() function
+is used. With that function, we can specify which data cells to target and
+then include a call to ggplot_image() within the required user-defined
+function (for the fn argument). If we want to include a plot in other
+places (e.g., in the header, within footnote text, etc.) we need to use
+ggplot_image() within the html() helper function." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper function for adding a ggplot</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
+    <div class="hidden name"><code>ggplot_image.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>We can add a <strong>ggplot2</strong> plot inside of a table with the help of the
+<code>ggplot_image()</code> function. The function provides a convenient way to generate
+an HTML fragment with a <code>ggplot</code> object. Because this function is currently
+HTML-based, it is only useful for HTML table output. To use this function
+inside of data cells, it is recommended that the <code><a href='text_transform.html'>text_transform()</a></code> function
+is used. With that function, we can specify which data cells to target and
+then include a call to <code>ggplot_image()</code> within the required user-defined
+function (for the <code>fn</code> argument). If we want to include a plot in other
+places (e.g., in the header, within footnote text, etc.) we need to use
+<code>ggplot_image()</code> within the <code><a href='html.html'>html()</a></code> helper function.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>ggplot_image</span>(<span class='no'>plot_object</span>, <span class='kw'>height</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>aspect_ratio</span> <span class='kw'>=</span> <span class='fl'>1</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>plot_object</th>
+      <td><p>A ggplot plot object.</p></td>
+    </tr>
+    <tr>
+      <th>height</th>
+      <td><p>The absolute height (px) of the image in the table cell.</p></td>
+    </tr>
+    <tr>
+      <th>aspect_ratio</th>
+      <td><p>The plot's final aspect ratio. Where the height of the
+plot is fixed using the <code>height</code> argument, the <code>aspect_ratio</code>
+will either compress (<code>aspect_ratio</code> &lt; <code>1.0</code>) or expand
+(<code>aspect_ratio</code> &gt; <code>1.0</code>) the plot horizontally. The default value
+of <code>1.0</code> will neither compress nor expand the plot.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character object with an HTML fragment that can be placed inside of
+a cell.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>By itself, the function creates an HTML image tag with an image URI embedded
+within (a 100 dpi PNG). We can easily experiment with any <code>ggplot2</code> plot
+object, and using it within <code>ggplot_image(plot_object = &lt;plot object&gt;</code>
+evaluates to:</p>
+<p><code>&lt;img cid=&lt;random CID&gt; src=&lt;data URI&gt; style=\"height:100px;\"&gt;</code></p>
+<p>where a height of <code>100px</code> is a default height chosen to work well within the
+heights of most table rows. There is the option to modify the aspect ratio of
+the plot (the default <code>aspect_ratio</code> is <code>1.0</code>) and this is useful for
+elongating any given plot to fit better within the table construct.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_ggplot_image_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>8-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Image Addition Functions: 
+<code><a href='local_image.html'>local_image</a>()</code>,
+<code><a href='test_image.html'>test_image</a>()</code>,
+<code><a href='web_image.html'>web_image</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>ggplot2</span>)
+
+<span class='co'># Create a ggplot plot</span>
+<span class='no'>plot_object</span> <span class='kw'>&lt;-</span>
+  <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(
+    <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>gtcars</span>,
+    <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>hp</span>, <span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>trq</span>,
+        <span class='kw'>size</span> <span class='kw'>=</span> <span class='no'>msrp</span>)) +
+  <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_point.html'>geom_point</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"blue"</span>) +
+  <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/theme.html'>theme</a></span>(<span class='kw'>legend.position</span> <span class='kw'>=</span> <span class='st'>"none"</span>)
+
+<span class='co'># Create a tibble that contains two</span>
+<span class='co'># cells (where one is a placeholder for</span>
+<span class='co'># an image), then, create a gt table;</span>
+<span class='co'># use the `text_transform()` function</span>
+<span class='co'># to insert the plot using by calling</span>
+<span class='co'># `ggplot_object()` within the user-</span>
+<span class='co'># defined function</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
+    <span class='kw'>text</span> <span class='kw'>=</span> <span class='st'>"Here is a ggplot:"</span>,
+    <span class='kw'>ggplot</span> <span class='kw'>=</span> <span class='fl'>NA</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='text_transform.html'>text_transform</a></span>(
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>ggplot</span>)),
+    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
+      <span class='no'>plot_object</span> <span class='kw'>%&gt;%</span>
+        <span class='fu'>ggplot_image</span>(<span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>200</span>))
+    }
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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+
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+
+
diff --git a/docs/reference/grand_summary_rows.html b/docs/reference/grand_summary_rows.html
new file mode 100644
index 000000000..7eadd24ba
--- /dev/null
+++ b/docs/reference/grand_summary_rows.html
@@ -0,0 +1,289 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Add grand summary rows using aggregation functions — grand_summary_rows • gt</title>
+
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+<meta property="og:description" content="Add grand summary rows to the gt table by using applying aggregation
+functions to the table data. The summary rows incorporate all of the
+available data, regardless of whether some of the data are part of row
+groups. You choose how to format the values in the resulting summary cells by
+use of a formatter function (e.g, fmt_number) and any relevant options." />
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+    <div class="page-header">
+    <h1>Add grand summary rows using aggregation functions</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/summary_rows.R'><code>R/summary_rows.R</code></a></small>
+    <div class="hidden name"><code>grand_summary_rows.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Add grand summary rows to the <strong>gt</strong> table by using applying aggregation
+functions to the table data. The summary rows incorporate all of the
+available data, regardless of whether some of the data are part of row
+groups. You choose how to format the values in the resulting summary cells by
+use of a <code>formatter</code> function (e.g, <code>fmt_number</code>) and any relevant options.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>grand_summary_rows</span>(
+  <span class='no'>data</span>,
+  <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='no'>fns</span>,
+  <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"---"</span>,
+  <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+  <span class='no'>...</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns for which the summaries should be calculated.</p></td>
+    </tr>
+    <tr>
+      <th>fns</th>
+      <td><p>Functions used for aggregations. This can include base functions
+like <code>mean</code>, <code>min</code>, <code>max</code>, <code>median</code>, <code>sd</code>, or <code>sum</code> or any other
+user-defined aggregation function. The function(s) should be supplied
+within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. Within that list, we can specify the functions by use of
+function names in quotes (e.g., <code>"sum"</code>), as bare functions (e.g., <code>sum</code>),
+or as one-sided R formulas using a leading <code>~</code>. In the formula
+representation, a <code>.</code> serves as the data to be summarized (e.g., <code><a href='https://rdrr.io/r/base/sum.html'>sum(., na.rm = TRUE)</a></code>). The use of named arguments is recommended as the names
+will serve as summary row labels for the corresponding summary rows data
+(the labels can derived from the function names but only when not providing
+bare function names).</p></td>
+    </tr>
+    <tr>
+      <th>missing_text</th>
+      <td><p>The text to be used in place of <code>NA</code> values in summary
+cells with no data outputs.</p></td>
+    </tr>
+    <tr>
+      <th>formatter</th>
+      <td><p>A formatter function name. These can be any of the <code>fmt_*()</code>
+functions available in the package (e.g., <code><a href='fmt_number.html'>fmt_number()</a></code>, <code><a href='fmt_percent.html'>fmt_percent()</a></code>,
+etc.), or a custom function using <code><a href='fmt.html'>fmt()</a></code>. The default function is
+<code><a href='fmt_number.html'>fmt_number()</a></code> and its options can be accessed through <code>...</code>.</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>Values passed to the <code>formatter</code> function, where the provided
+values are to be in the form of named vectors. For example, when using the
+default <code>formatter</code> function, <code><a href='fmt_number.html'>fmt_number()</a></code>, options such as <code>decimals</code>,
+<code>use_seps</code>, and <code>locale</code> can be used.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Should we need to obtain the summary data for external purposes, the
+<code><a href='extract_summary.html'>extract_summary()</a></code> function can be used with a <code>gt_tbl</code> object where grand
+summary rows were added via <code>grand_summary_rows()</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_grand_summary_rows_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>6-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Add Rows: 
+<code><a href='summary_rows.html'>summary_rows</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table with</span>
+<span class='co'># row groups; create grand summary rows</span>
+<span class='co'># (`min`, `max`, `avg`) for the table</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
+      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-16"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='no'>date</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
+    <span class='kw'>week</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
+      <span class='st'>"W"</span>, <span class='fu'><a href='https://rdrr.io/r/base/strptime.html'>strftime</a></span>(<span class='no'>date</span>, <span class='kw'>format</span> <span class='kw'>=</span> <span class='st'>"%V"</span>))
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>adj_close</span>, -<span class='no'>volume</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(
+    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
+    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"week"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>grand_summary_rows</span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>high</span>, <span class='no'>low</span>, <span class='no'>close</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>),
+      <span class='kw'>avg</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/mean.html'>mean</a></span>(<span class='no'>.</span>)),
+    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/gt-options.html b/docs/reference/gt-options.html
new file mode 100644
index 000000000..243ed9fe3
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+++ b/docs/reference/gt-options.html
@@ -0,0 +1,188 @@
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+    <div class="page-header">
+    <h1><strong>gt</strong> package options</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/zzz.R'><code>R/zzz.R</code></a></small>
+    <div class="hidden name"><code>gt-options.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p><strong>gt</strong> package options</p>
+    </div>
+
+
+
+    <h2 class="hasAnchor" id="package-options"><a class="anchor" href="#package-options"></a>Package options</h2>
+
+    
+
+
+<p><strong>gt</strong> uses the following <code><a href='https://rdrr.io/r/base/options.html'>options()</a></code> to configure behavior:</p><ul>
+<li><p><code>gt.row_group.sep</code>: a separator between groups for the row group
+label.</p></li>
+</ul>
+
+
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>gt: Easily Create Presentation-Ready Display Tables</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/gt-package.R'><code>R/gt-package.R</code></a></small>
+    <div class="hidden name"><code>gt-package.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Build display tables from tabular data using with an easy-to-use
+    API. With its progressive approach, we can construct display tables with a
+    clear separation of concerns: you don't have to decide how the tabular data
+    gets transformed and structured whilst also worrying about aesthetics.</p>
+    </div>
+
+
+
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Useful links:</p><ul>
+<li><p><a href='https://github.com/rstudio/gt'>https://github.com/rstudio/gt</a></p></li>
+<li><p>Report bugs at <a href='https://github.com/rstudio/gt/issues'>https://github.com/rstudio/gt/issues</a></p></li>
+</ul>
+
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diff --git a/docs/reference/gt.html b/docs/reference/gt.html
new file mode 100644
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+<meta property="og:description" content="The gt() function creates a gt table object when provided with table
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+Once we have the gt table object, we can perform styling transformations
+before rendering to a display table of various formats." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+      </span>
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+
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+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
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+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
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+
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+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Create a <strong>gt</strong> table object</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/gt.R'><code>R/gt.R</code></a></small>
+    <div class="hidden name"><code>gt.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>gt()</code> function creates a <strong>gt</strong> table object when provided with table
+data. Using this function is the first step in a typical <strong>gt</strong> workflow.
+Once we have the <strong>gt</strong> table object, we can perform styling transformations
+before rendering to a display table of various formats.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>gt</span>(
+  <span class='no'>data</span>,
+  <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"rowname"</span>,
+  <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_data.html'>group_vars</a></span>(<span class='no'>data</span>),
+  <span class='kw'>rownames_to_stub</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>auto_align</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='kw'>id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.sep</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span>(<span class='st'>"gt.row_group.sep"</span>, <span class='st'>" - "</span>)
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A <code>data.frame</code> object or a tibble.</p></td>
+    </tr>
+    <tr>
+      <th>rowname_col</th>
+      <td><p>The column name in the input <code>data</code> table to use as row
+captions to be placed in the display table stub. If the <code>rownames_to_stub</code>
+option is <code>TRUE</code> then any column name provided to <code>rowname_col</code> will be
+ignored.</p></td>
+    </tr>
+    <tr>
+      <th>groupname_col</th>
+      <td><p>The column name in the input <code>data</code> table to use as
+group labels for generation of stub row groups. If the input <code>data</code> table
+has the <code>grouped_df</code> class (through use of the <code><a href='https://dplyr.tidyverse.org/reference/group_by.html'>dplyr::group_by()</a></code> function
+or associated <code>group_by*()</code> functions) then any input here is ignored.</p></td>
+    </tr>
+    <tr>
+      <th>rownames_to_stub</th>
+      <td><p>An option to take rownames from the input <code>data</code>
+table as row captions in the display table stub.</p></td>
+    </tr>
+    <tr>
+      <th>auto_align</th>
+      <td><p>Optionally have column data be aligned depending on the
+content contained in each column of the input <code>data</code>. Internally, this
+calls <code><a href='cols_align.html'>cols_align(align = "auto")</a></code> for all columns.</p></td>
+    </tr>
+    <tr>
+      <th>id</th>
+      <td><p>The table ID. By default, with <code>NULL</code>, this will be a random,
+ten-letter ID as generated by using the <code><a href='random_id.html'>random_id()</a></code> function. A custom
+table ID can be used with any single-length character vector.</p></td>
+    </tr>
+    <tr>
+      <th>row_group.sep</th>
+      <td><p>The separator to use between consecutive group names (a
+possibility when providing <code>data</code> as a <code>grouped_df</code> with multiple groups)
+in the displayed stub row group label.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>There are a few data ingest options we can consider at this stage. We can
+choose to create a table stub with rowname captions using the <code>rowname_col</code>
+argument. Further to this, stub row groups can be created with the
+<code>groupname_col</code>. Both arguments take the name of a column in the input table
+data. Typically, the data in the <code>groupname_col</code> will consist of categories
+of data in a table and the data in the <code>rowname_col</code> are unique labels
+(perhaps unique across the entire table or unique within groups).</p>
+<p>Row groups can also be created by passing a <code>grouped_df</code> to <code>gt()</code> by using
+the <code><a href='https://dplyr.tidyverse.org/reference/group_by.html'>dplyr::group_by()</a></code> function on the table data. In this way, two or more
+columns of categorical data can be used to make row groups. The
+<code>row_group.sep</code> argument allows for control in how the row group label will
+appear in the display table.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_gt_1.png' width=100% /></p>
+<p><img src='figures/man_gt_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>1-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create Table: 
+<code><a href='gt_preview.html'>gt_preview</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Create a table object using the</span>
+<span class='co'># `exibble` dataset; use the `row`</span>
+<span class='co'># and `group` columns to add a stub</span>
+<span class='co'># and row groups</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>gt</span>(
+    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>,
+    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>
+  )
+
+<span class='co'># The resulting object can be used</span>
+<span class='co'># in transformations (with `tab_*()`,</span>
+<span class='co'># `fmt_*()`, `cols_*()` functions)</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"Table Title"</span>,
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"Subtitle"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(<span class='kw'>num</span> <span class='kw'>=</span> <span class='st'>"number"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
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+
+  </body>
+</html>
+
+
diff --git a/docs/reference/gt_latex_dependencies.html b/docs/reference/gt_latex_dependencies.html
new file mode 100644
index 000000000..96f0e3559
--- /dev/null
+++ b/docs/reference/gt_latex_dependencies.html
@@ -0,0 +1,249 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Get the LaTeX dependencies required for a <strong>gt</strong> table — gt_latex_dependencies • gt</title>
+
+<!-- favicons -->
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
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+
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+<link href="../pkgdown.css" rel="stylesheet">
+<script src="../pkgdown.js"></script>
+
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+
+
+<meta property="og:title" content="Get the LaTeX dependencies required for a <strong>gt</strong> table — gt_latex_dependencies" />
+<meta property="og:description" content="When working with Rnw (Sweave) files or otherwise writing LaTeX code,
+including a gt table can be problematic if we don't have knowledge
+of the LaTeX dependencies. For the most part, these dependencies are the
+LaTeX packages that are required for rendering a gt table. The
+gt_latex_dependencies() function provides an object that can be
+used to provide the LaTeX in an Rnw file, allowing gt tables to work
+and not yield errors due to missing packages." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
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+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
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+    <div class="container template-reference-topic">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
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+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Get the LaTeX dependencies required for a <strong>gt</strong> table</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>gt_latex_dependencies.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>When working with Rnw (Sweave) files or otherwise writing LaTeX code,
+including a <strong>gt</strong> table can be problematic if we don't have knowledge
+of the LaTeX dependencies. For the most part, these dependencies are the
+LaTeX packages that are required for rendering a <strong>gt</strong> table. The
+<code>gt_latex_dependencies()</code> function provides an object that can be
+used to provide the LaTeX in an Rnw file, allowing <strong>gt</strong> tables to work
+and not yield errors due to missing packages.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>gt_latex_dependencies</span>()</pre>
+
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>knit_asis</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Here is an example Rnw document that shows how the
+<code>gt_latex_dependencies()</code> can be used in conjunction with a <strong>gt</strong>
+table:</p>
+<pre>
+%!sweave=knitr
+
+\documentclass{article}
+
+&lt;&lt;echo=FALSE&gt;&gt;=
+library(gt)
+ @
+
+&lt;&lt;results='asis', echo=FALSE&gt;&gt;=
+gt_latex_dependencies()
+ @
+
+\begin{document}
+
+&lt;&lt;results='asis', echo=FALSE&gt;&gt;=
+exibble <!-- %&gt;% gt() -->
+ @
+
+\end{document}
+</pre>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-21</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+   </div>
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+  </body>
+</html>
+
+
diff --git a/docs/reference/gt_output.html b/docs/reference/gt_output.html
new file mode 100644
index 000000000..25f3e0331
--- /dev/null
+++ b/docs/reference/gt_output.html
@@ -0,0 +1,251 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Create a <strong>gt</strong> display table output element for Shiny — gt_output • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
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+
+<!-- pkgdown -->
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+<script src="../pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Create a <strong>gt</strong> display table output element for Shiny — gt_output" />
+<meta property="og:description" content="Using gt_output() we can render a reactive gt table, a process
+initiated by using the render_gt() function in the server component of a
+Shiny app. The gt_output() call is to be used in the Shiny ui component,
+the position and context wherein this call is made determines the where the
+gt table is rendered on the app page. It's important to note that the
+ID given during the render_gt() call is needed as the outputId in
+gt_output() (e.g., server: output$&amp;lt;id&amp;gt; &amp;lt;- render_gt(...); ui:
+gt_output(outputId = &quot;&amp;lt;id&amp;gt;&quot;)." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
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+
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+    <div class="container template-reference-topic">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
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+    <div class="navbar-header">
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+
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+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
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+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
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+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Create a <strong>gt</strong> display table output element for Shiny</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/shiny.R'><code>R/shiny.R</code></a></small>
+    <div class="hidden name"><code>gt_output.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Using <code>gt_output()</code> we can render a reactive <strong>gt</strong> table, a process
+initiated by using the <code><a href='render_gt.html'>render_gt()</a></code> function in the <code>server</code> component of a
+Shiny app. The <code>gt_output()</code> call is to be used in the Shiny <code>ui</code> component,
+the position and context wherein this call is made determines the where the
+<strong>gt</strong> table is rendered on the app page. It's important to note that the
+ID given during the <code><a href='render_gt.html'>render_gt()</a></code> call is needed as the <code>outputId</code> in
+<code>gt_output()</code> (e.g., <strong>server</strong>: <code>output$&lt;id&gt; &lt;- render_gt(...)</code>; <strong>ui</strong>:
+<code>gt_output(outputId = "&lt;id&gt;"</code>).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>gt_output</span>(<span class='no'>outputId</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>outputId</th>
+      <td><p>An output variable from which to read the table.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>We need to ensure that we have the <strong>shiny</strong> package installed first. This
+is easily by using <code><a href='https://rdrr.io/r/utils/install.packages.html'>install.packages("shiny")</a></code>. More information on creating
+Shiny apps can be found at the <a href='https://shiny.rstudio.com'>Shiny Site</a>.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>12-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Shiny functions: 
+<code><a href='render_gt.html'>render_gt</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>shiny</span>)
+
+<span class='co'># Here is a Shiny app (contained within</span>
+<span class='co'># a single file) that (1) prepares a</span>
+<span class='co'># gt table, (2) sets up the `ui` with</span>
+<span class='co'># `gt_output()`, and (3) sets up the</span>
+<span class='co'># `server` with a `render_gt()` that</span>
+<span class='co'># uses the `gt_tbl` object as the input</span>
+<span class='co'># expression</span>
+
+<span class='no'>gt_tbl</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='cols_hide.html'>cols_hide</a></span>(<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"_"</span>))
+
+<span class='no'>ui</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/fluidPage.html'>fluidPage</a></span>(
+
+  <span class='fu'>gt_output</span>(<span class='kw'>outputId</span> <span class='kw'>=</span> <span class='st'>"table"</span>)
+)
+
+<span class='no'>server</span> <span class='kw'>&lt;-</span> <span class='kw'>function</span>(<span class='no'>input</span>,
+                   <span class='no'>output</span>,
+                   <span class='no'>session</span>) {
+
+  <span class='no'>output</span>$<span class='no'>table</span> <span class='kw'>&lt;-</span>
+    <span class='fu'><a href='render_gt.html'>render_gt</a></span>(
+      <span class='kw'>expr</span> <span class='kw'>=</span> <span class='no'>gt_tbl</span>,
+      <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>),
+      <span class='kw'>width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>)
+    )
+}
+
+<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span>()) {
+  <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/shinyApp.html'>shinyApp</a></span>(<span class='no'>ui</span>, <span class='no'>server</span>)
+}</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
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+
+  </body>
+</html>
+
+
diff --git a/docs/reference/gt_preview.html b/docs/reference/gt_preview.html
new file mode 100644
index 000000000..3f8ded0aa
--- /dev/null
+++ b/docs/reference/gt_preview.html
@@ -0,0 +1,247 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Preview a <strong>gt</strong> table object — gt_preview • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+<!-- Bootstrap -->
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
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+
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+<script src="../pkgdown.js"></script>
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+
+<meta property="og:title" content="Preview a <strong>gt</strong> table object — gt_preview" />
+<meta property="og:description" content="Sometimes you may want to see just a small portion of your input data. We can
+use gt_preview() in place of gt() to get the first x rows of data and the
+last y rows of data (which can be set by the top_n and bottom_n
+arguments). It's not advised to use additional gt functions to further
+modify the output of gt_preview(). Furthermore, you cannot pass a gt
+object to gt_preview()." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
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+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
+  </head>
+
+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-reference-topic">
+      <header>
+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
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+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
+</li>
+<li>
+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
+    <span class="caret"></span>
+  </a>
+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Preview a <strong>gt</strong> table object</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/gt_preview.R'><code>R/gt_preview.R</code></a></small>
+    <div class="hidden name"><code>gt_preview.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Sometimes you may want to see just a small portion of your input data. We can
+use <code>gt_preview()</code> in place of <code><a href='gt.html'>gt()</a></code> to get the first x rows of data and the
+last y rows of data (which can be set by the <code>top_n</code> and <code>bottom_n</code>
+arguments). It's not advised to use additional <strong>gt</strong> functions to further
+modify the output of <code>gt_preview()</code>. Furthermore, you cannot pass a <strong>gt</strong>
+object to <code>gt_preview()</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>gt_preview</span>(<span class='no'>data</span>, <span class='kw'>top_n</span> <span class='kw'>=</span> <span class='fl'>5</span>, <span class='kw'>bottom_n</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>incl_rownums</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A <code>data.frame</code> object or a tibble.</p></td>
+    </tr>
+    <tr>
+      <th>top_n</th>
+      <td><p>This value will be used as the number of rows from the top of
+the table to display. The default, <code>5</code>, will show the first five rows of
+the table.</p></td>
+    </tr>
+    <tr>
+      <th>bottom_n</th>
+      <td><p>The value will be used as the number of rows from the bottom
+of the table to display. The default, <code>1</code>, will show the final row of the
+table.</p></td>
+    </tr>
+    <tr>
+      <th>incl_rownums</th>
+      <td><p>An option to include the row numbers for <code>data</code> in the
+table stub. By default, this is <code>TRUE</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Any grouped data or magic columns such as <code>rowname</code> and <code>groupname</code> will be
+ignored by <code>gt_preview()</code> and, as such, one cannot add a stub or group rows
+in the output table. By default, the output table will include row numbers in
+a stub (including a range of row numbers for the omitted rows). This row
+numbering option can be deactivated by setting <code>incl_rownums</code> to <code>FALSE</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_gt_preview_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>1-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create Table: 
+<code><a href='gt.html'>gt</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table</span>
+<span class='co'># preview (with only a few of its</span>
+<span class='co'># columns); you'll see the first five</span>
+<span class='co'># rows and the last row</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>year</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>gt_preview</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/gtcars.html b/docs/reference/gtcars.html
new file mode 100644
index 000000000..da24b700a
--- /dev/null
+++ b/docs/reference/gtcars.html
@@ -0,0 +1,254 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Deluxe automobiles from the 2014-2017 period — gtcars • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
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+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+<meta property="og:title" content="Deluxe automobiles from the 2014-2017 period — gtcars" />
+<meta property="og:description" content="Expensive and fast cars. Not your father's mtcars. Each row describes a car
+of a certain make, model, year, and trim. Basic specifications such as
+horsepower, torque, EPA MPG ratings, type of drivetrain, and transmission
+characteristics are provided. The country of origin for the car manufacturer
+is also given." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
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+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
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+  <a href="../news/index.html">News</a>
+</li>
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+      <ul class="nav navbar-nav navbar-right">
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+</li>
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+
+      
+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Deluxe automobiles from the 2014-2017 period</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
+    <div class="hidden name"><code>gtcars.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Expensive and fast cars. Not your father's <code>mtcars</code>. Each row describes a car
+of a certain make, model, year, and trim. Basic specifications such as
+horsepower, torque, EPA MPG ratings, type of drivetrain, and transmission
+characteristics are provided. The country of origin for the car manufacturer
+is also given.</p>
+    </div>
+
+    <pre class="usage"><span class='no'>gtcars</span></pre>
+
+
+    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+
+    <p>A tibble with 47 rows and 15 variables:</p><dl'>
+<dt>mfr</dt><dd><p>The name of the car manufacturer</p></dd>
+<dt>model</dt><dd><p>The car's model name</p></dd>
+<dt>year</dt><dd><p>The car's model year</p></dd>
+<dt>trim</dt><dd><p>A short description of the car model's trim</p></dd>
+<dt>bdy_style</dt><dd><p>An identifier of the car's body style, which is either
+<code>coupe</code>, <code>convertible</code>, <code>sedan</code>, or <code>hatchback</code></p></dd>
+<dt>hp, hp_rpm</dt><dd><p>The car's horsepower and the associated RPM level</p></dd>
+<dt>trq, trq_rpm</dt><dd><p>The car's torque and the associated RPM level</p></dd>
+<dt>mpg_c, mpg_h</dt><dd><p>The miles per gallon fuel efficiency rating for city
+and highway driving</p></dd>
+<dt>drivetrain</dt><dd><p>The car's drivetrain which, for this dataset is either
+<code>rwd</code> (Rear Wheel Drive) or <code>awd</code> (All Wheel Drive)</p></dd>
+<dt>trsmn</dt><dd><p>The codified transmission type, where the number part is
+the number of gears; the car could have automatic transmission
+(<code>a</code>), manual transmission (<code>m</code>), an option to switch between
+both types (<code>am</code>), or, direct drive (<code>dd</code>)</p></dd>
+<dt>ctry_origin</dt><dd><p>The country name for where the vehicle manufacturer
+is headquartered</p></dd>
+
+</dl>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>All of the <code>gtcars</code> have something else in common (aside from the high asking
+prices): they are all grand tourer vehicles. These are proper GT cars that
+blend pure driving thrills with a level of comfort that is more expected from
+a fine limousine (e.g., a Rolls-Royce Phantom EWB). You'll find that, with
+these cars, comfort is emphasized over all-out performance. Nevertheless, the
+driving experience should also mean motoring at speed, doing so in style and
+safety.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>11-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Datasets: 
+<code><a href='countrypops.html'>countrypops</a></code>,
+<code><a href='exibble.html'>exibble</a></code>,
+<code><a href='pizzaplace.html'>pizzaplace</a></code>,
+<code><a href='sp500.html'>sp500</a></code>,
+<code><a href='sza.html'>sza</a></code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
+<span class='co'># available in `gtcars`</span>
+<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>gtcars</span>)</div><div class='output co'>#&gt; Rows: 47
+#&gt; Columns: 15
+#&gt; $ mfr         <span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "Ford", "Ferrari", "Ferrari", "Ferrari", "Ferrari", "Ferr…
+#&gt; $ model       </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "GT", "458 Speciale", "458 Spider", "458 Italia", "488 GT…
+#&gt; $ year        </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2017, 2015, 2015, 2014, 2016, 2015, 2017, 2015, 2015, 201…
+#&gt; $ trim        </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "Base Coupe", "Base Coupe", "Base", "Base Coupe", "Base C…
+#&gt; $ bdy_style   </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "coupe", "coupe", "convertible", "coupe", "coupe", "conve…
+#&gt; $ hp          </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 647, 597, 562, 562, 661, 553, 680, 652, 731, 949, 573, 54…
+#&gt; $ hp_rpm      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 6250, 9000, 9000, 9000, 8000, 7500, 8250, 8000, 8250, 900…
+#&gt; $ trq         </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 550, 398, 398, 398, 561, 557, 514, 504, 509, 664, 476, 43…
+#&gt; $ trq_rpm     </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 5900, 6000, 6000, 6000, 3000, 4750, 5750, 6000, 6000, 675…
+#&gt; $ mpg_c       </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 11, 13, 13, 13, 15, 16, 12, 11, 11, 12, 21, 16, 11, 16, 1…
+#&gt; $ mpg_h       </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 18, 17, 17, 17, 22, 23, 17, 16, 16, 16, 22, 22, 18, 20, 2…
+#&gt; $ drivetrain  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "rwd", "rwd", "rwd", "rwd", "rwd", "rwd", "awd", "awd", "…
+#&gt; $ trsmn       </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a…
+#&gt; $ ctry_origin </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "United States", "Italy", "Italy", "Italy", "Italy", "Ita…
+#&gt; $ msrp        </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 447000, 291744, 263553, 233509, 245400, 198973, 298000, 2…</div><div class='input'>
+</div></span></pre>
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diff --git a/docs/reference/gtsave.html b/docs/reference/gtsave.html
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+    <div class="page-header">
+    <h1>Save a <strong>gt</strong> table as a file</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
+    <div class="hidden name"><code>gtsave.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>gtsave()</code> function makes it easy to save a <strong>gt</strong> table to a file. The
+function guesses the file type by the extension provided in the output
+filename, producing either an HTML, PDF, PNG, LaTeX, or RTF file.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>gtsave</span>(<span class='no'>data</span>, <span class='no'>filename</span>, <span class='kw'>path</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='no'>...</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>filename</th>
+      <td><p>The file name to create on disk. Ensure that an extension
+compatible with the output types is provided (<code>.html</code>, <code>.tex</code>, <code>.ltx</code>,
+<code>.rtf</code>). If a custom save function is provided then the file extension is
+disregarded.</p></td>
+    </tr>
+    <tr>
+      <th>path</th>
+      <td><p>An optional path to which the file should be saved (combined with
+filename).</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>All other options passed to the appropriate internal saving
+function.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Output filenames with either the <code>.html</code> or <code>.htm</code> extensions will produce an
+HTML document. In this case, we can pass a <code>TRUE</code> or <code>FALSE</code> value to the
+<code>inline_css</code> option to obtain an HTML document with inlined CSS styles (the
+default is <code>FALSE</code>). More details on CSS inlining are available at
+<code><a href='as_raw_html.html'>as_raw_html()</a></code>. We can pass values to arguments in <code><a href='https://rdrr.io/pkg/htmltools/man/save_html.html'>htmltools::save_html()</a></code>
+through the <code>...</code>. Those arguments are either <code>background</code> or <code>libdir</code>,
+please refer to the <strong>htmltools</strong> documentation for more details on the use
+of these arguments.</p>
+<p>We can create an image file based on the HTML version of the <code>gt</code> table. With
+the filename extension <code>.png</code>, we get a PNG image file. A PDF document can be
+generated by using the <code>.pdf</code> extension. This process is facilitated by the
+<strong>webshot</strong> package, so, this package needs to be installed before
+attempting to save any table as an image file. There is the option of passing
+values to the underlying <code><a href='https://rdrr.io/pkg/webshot/man/webshot.html'>webshot::webshot()</a></code> function though <code>...</code>. Some of
+the more useful arguments for PNG saving are <code>zoom</code> (defaults to a scale
+level of <code>2</code>) and <code>expand</code> (adds whitespace pixels around the cropped table
+image, and has a default value of <code>5</code>). There are several more options
+available so have a look at the <strong>webshot</strong> documentation for further
+details.</p>
+<p>If the output filename extension is either of <code>.tex</code>, <code>.ltx</code>, or <code>.rnw</code>, a
+LaTeX document is produced. An output filename of <code>.rtf</code> will generate an RTF
+document. The LaTeX and RTF saving functions don't have any options to pass
+to <code>...</code>.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>13-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Export Functions: 
+<code><a href='as_latex.html'>as_latex</a>()</code>,
+<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
+<code><a href='as_rtf.html'>as_rtf</a>()</code>,
+<code><a href='extract_summary.html'>extract_summary</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table; add</span>
+<span class='co'># a stubhead label to describe what is</span>
+<span class='co'># in the stub</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_stubhead.html'>tab_stubhead</a></span>(<span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"car"</span>)
+
+<span class='co'># Get an HTML file with inlined CSS</span>
+<span class='co'># (which is necessary for including the</span>
+<span class='co'># table as part of an HTML email)</span>
+<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>gtsave</span>(
+    <span class='st'>"tab_1.html"</span>, <span class='kw'>inline_css</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+    <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>()
+  )
+
+<span class='co'># By leaving out the `inline_css` option,</span>
+<span class='co'># we get a more conventional HTML file</span>
+<span class='co'># with embedded CSS styles</span>
+<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>gtsave</span>(<span class='st'>"tab_1.html"</span>, <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>())
+
+<span class='co'># Saving as PNG file results in a cropped</span>
+<span class='co'># image of an HTML table; the amount of</span>
+<span class='co'># whitespace can be set</span>
+<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>gtsave</span>(
+    <span class='st'>"tab_1.png"</span>, <span class='kw'>expand</span> <span class='kw'>=</span> <span class='fl'>10</span>,
+    <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>()
+  )
+
+<span class='co'># Any use of the `.tex`, `.ltx`, or `.rnw`</span>
+<span class='co'># will result in the output of a LaTeX</span>
+<span class='co'># document</span>
+<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>gtsave</span>(<span class='st'>"tab_1.tex"</span>, <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>())</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/html.html b/docs/reference/html.html
new file mode 100644
index 000000000..83d08fa5c
--- /dev/null
+++ b/docs/reference/html.html
@@ -0,0 +1,243 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Interpret input text as HTML-formatted text — html • gt</title>
+
+<!-- favicons -->
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+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
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+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
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+
+<meta property="og:title" content="Interpret input text as HTML-formatted text — html" />
+<meta property="og:description" content="For certain pieces of text (like in column labels or table headings) we may
+want to express them as raw HTML. In fact, with HTML, anything goes so it can
+be much more than just text. The html() function will guard the input HTML
+against escaping, so, your HTML tags will come through as HTML when
+rendered... to HTML." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
+
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+  <body data-spy="scroll" data-target="#toc">
+    <div class="container template-reference-topic">
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+      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
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+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+</li>
+<li class="dropdown">
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Interpret input text as HTML-formatted text</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>html.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>For certain pieces of text (like in column labels or table headings) we may
+want to express them as raw HTML. In fact, with HTML, anything goes so it can
+be much more than just text. The <code>html()</code> function will guard the input HTML
+against escaping, so, your HTML tags will come through as HTML when
+rendered... to HTML.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>html</span>(<span class='no'>text</span>, <span class='no'>...</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>text, ...</th>
+      <td><p>The text that is understood to be HTML text, which is to be
+preserved.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character object of class <code>html</code>. It's tagged as an HTML fragment
+that is not to be sanitized.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_html_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># when adding a title, use the `html()`</span>
+<span class='co'># helper to use html formatting</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>currency</span>, <span class='no'>char</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'>html</span>(<span class='st'>"&lt;em&gt;HTML&lt;/em&gt;"</span>))</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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+
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diff --git a/docs/reference/index.html b/docs/reference/index.html
new file mode 100644
index 000000000..52b5a5f63
--- /dev/null
+++ b/docs/reference/index.html
@@ -0,0 +1,864 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
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+<!-- Bootstrap -->
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+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="contents col-md-9">
+    <div class="page-header">
+      <h1>Reference</h1>
+    </div>
+
+    <table class="ref-index">
+
+    <colgroup>
+      
+      <col class="alias" />
+      <col class="title" />
+    </colgroup>
+
+    <tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-create-table" class="hasAnchor"><a href="#section-create-table" class="anchor"></a>Create Table</h2>
+          <p class="section-desc"><p>All <strong>gt</strong> tables begin with a call to <code><a href="../reference/gt.html">gt()</a></code>, where we would supply the input data table (data frame or tibble) and some basic options for creating a stub (<code>rowname_col</code>) and row groups (<code>groupname_col</code>). We can also introduce a grouped tibble (via <strong>dplyr</strong>’s <code>group_by()</code>) for more precise divisions of rows into row groups. The <code><a href="../reference/gt_preview.html">gt_preview()</a></code> function is great for getting a nicely-formatted preview of a data table (defaulting to the first 5 rows and the last row).</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="gt.html">gt()</a></code> </p>
+        </td>
+        <td><p>Create a <strong>gt</strong> table object</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="gt_preview.html">gt_preview()</a></code> </p>
+        </td>
+        <td><p>Preview a <strong>gt</strong> table object</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-create-or-modify-parts" class="hasAnchor"><a href="#section-create-or-modify-parts" class="anchor"></a>Create or Modify Parts</h2>
+          <p class="section-desc"><p>A <strong>gt</strong> table can contain a few useful parts for conveying additional information. These include a header (with a titles and subtitle), a footer (with footnotes and source notes), and additional areas for labels (row group labels, column spanner labels, the stubhead label). We can modify the look of table parts more generally with <code><a href="../reference/tab_options.html">tab_options()</a></code> and perform styling on targeted table locations with <code><a href="../reference/tab_style.html">tab_style()</a></code>.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="tab_header.html">tab_header()</a></code> </p>
+        </td>
+        <td><p>Add a table header</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_spanner.html">tab_spanner()</a></code> </p>
+        </td>
+        <td><p>Add a spanner column label</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_spanner_delim.html">tab_spanner_delim()</a></code> </p>
+        </td>
+        <td><p>Create column labels and spanners via delimited names</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_row_group.html">tab_row_group()</a></code> </p>
+        </td>
+        <td><p>Add a row group to a <strong>gt</strong> table</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_stubhead.html">tab_stubhead()</a></code> </p>
+        </td>
+        <td><p>Add label text to the stubhead</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_footnote.html">tab_footnote()</a></code> </p>
+        </td>
+        <td><p>Add a table footnote</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_source_note.html">tab_source_note()</a></code> </p>
+        </td>
+        <td><p>Add a source note citation</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_style.html">tab_style()</a></code> </p>
+        </td>
+        <td><p>Add custom styles to one or more cells</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="tab_options.html">tab_options()</a></code> </p>
+        </td>
+        <td><p>Modify the table output options</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-format-data" class="hasAnchor"><a href="#section-format-data" class="anchor"></a>Format Data</h2>
+          <p class="section-desc"><p>Columns of data can be formatted with the <code>fmt_*()</code> functions. We can specify the rows of these columns quite precisely with the <code>rows</code> argument. We get to apply these functions exactly once to each data cell (last call wins). Need to do custom formatting? Use the <code><a href="../reference/fmt.html">fmt()</a></code> function and define your own formatter within (or, create a wrapper with <code><a href="../reference/fmt.html">fmt()</a></code> if you prefer). The <code><a href="../reference/text_transform.html">text_transform()</a></code> function allows for post-processing of any data, and we provide a function for that transformation.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="fmt_number.html">fmt_number()</a></code> </p>
+        </td>
+        <td><p>Format numeric values</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_scientific.html">fmt_scientific()</a></code> </p>
+        </td>
+        <td><p>Format values to scientific notation</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_percent.html">fmt_percent()</a></code> </p>
+        </td>
+        <td><p>Format values as a percentage</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_currency.html">fmt_currency()</a></code> </p>
+        </td>
+        <td><p>Format values as currencies</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_date.html">fmt_date()</a></code> </p>
+        </td>
+        <td><p>Format values as dates</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_time.html">fmt_time()</a></code> </p>
+        </td>
+        <td><p>Format values as times</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_datetime.html">fmt_datetime()</a></code> </p>
+        </td>
+        <td><p>Format values as date-times</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_markdown.html">fmt_markdown()</a></code> </p>
+        </td>
+        <td><p>Format Markdown text</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_passthrough.html">fmt_passthrough()</a></code> </p>
+        </td>
+        <td><p>Format by simply passing data through</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt_missing.html">fmt_missing()</a></code> </p>
+        </td>
+        <td><p>Format missing values</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="fmt.html">fmt()</a></code> </p>
+        </td>
+        <td><p>Set a column format with a formatter function</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="text_transform.html">text_transform()</a></code> </p>
+        </td>
+        <td><p>Perform targeted text transformation with a function</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="data_color.html">data_color()</a></code> </p>
+        </td>
+        <td><p>Set data cell colors using a palette or a color function</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-modify-columns" class="hasAnchor"><a href="#section-modify-columns" class="anchor"></a>Modify Columns</h2>
+          <p class="section-desc"><p>The <code>cols_*()</code> functions allow for modifications that act on entire columns. This includes alignment of the data in columns (<code><a href="../reference/cols_align.html">cols_align()</a></code>), hiding columns from view (<code><a href="../reference/cols_hide.html">cols_hide()</a></code>), re-labeling the column labels (<code><a href="../reference/cols_label.html">cols_label()</a></code>), merging two columns together (<code>cols_merge*()</code>), moving columns around (<code>cols_move*()</code>)</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="cols_align.html">cols_align()</a></code> </p>
+        </td>
+        <td><p>Set the alignment of columns</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_width.html">cols_width()</a></code> </p>
+        </td>
+        <td><p>Set the widths of columns</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_label.html">cols_label()</a></code> </p>
+        </td>
+        <td><p>Relabel one or more columns</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_move_to_start.html">cols_move_to_start()</a></code> </p>
+        </td>
+        <td><p>Move one or more columns to the start</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_move_to_end.html">cols_move_to_end()</a></code> </p>
+        </td>
+        <td><p>Move one or more columns to the end</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_move.html">cols_move()</a></code> </p>
+        </td>
+        <td><p>Move one or more columns</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_hide.html">cols_hide()</a></code> </p>
+        </td>
+        <td><p>Hide one or more columns</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_merge_range.html">cols_merge_range()</a></code> </p>
+        </td>
+        <td><p>Merge two columns to a value range column</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_merge_uncert.html">cols_merge_uncert()</a></code> </p>
+        </td>
+        <td><p>Merge two columns to a value &amp; uncertainty column</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cols_merge.html">cols_merge()</a></code> </p>
+        </td>
+        <td><p>Merge data from two or more columns to a single column</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-modify-rows" class="hasAnchor"><a href="#section-modify-rows" class="anchor"></a>Modify Rows</h2>
+          <p class="section-desc"><p>The only function currently that modifies entire rows is the <code><a href="../reference/row_group_order.html">row_group_order()</a></code> function. It lets us modify the ordering of any row groups in the table.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="row_group_order.html">row_group_order()</a></code> </p>
+        </td>
+        <td><p>Modify the ordering of any row groups</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-add-rows" class="hasAnchor"><a href="#section-add-rows" class="anchor"></a>Add Rows</h2>
+          <p class="section-desc"><p>There are two functions that will add rows to a <strong>gt</strong> table: <code><a href="../reference/summary_rows.html">summary_rows()</a></code> and <code><a href="../reference/grand_summary_rows.html">grand_summary_rows()</a></code>. These functions will both add summary rows but one will do it in a groupwise fashion while the other will create grand summary rows.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="summary_rows.html">summary_rows()</a></code> </p>
+        </td>
+        <td><p>Add groupwise summary rows using aggregation functions</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="grand_summary_rows.html">grand_summary_rows()</a></code> </p>
+        </td>
+        <td><p>Add grand summary rows using aggregation functions</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-helper-functions" class="hasAnchor"><a href="#section-helper-functions" class="anchor"></a>Helper Functions</h2>
+          <p class="section-desc"><p>A small assortment of helper functions is available in the <strong>gt</strong> package. The various <code>cells_*()</code> functions are used for targeting cells with the <code>locations</code> argument in the <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code>, <code><a href="../reference/tab_style.html">tab_style()</a></code>, and <code><a href="../reference/text_transform.html">text_transform()</a></code> functions. The <code>cells_styles()</code> function is used exclusively with <code><a href="../reference/tab_style.html">tab_style()</a></code>’s <code>style</code> argument (and the <code><a href="../reference/px.html">px()</a></code> &amp; <code><a href="../reference/pct.html">pct()</a></code> functions may be useful there for specifying units in pixels or percentages). The <code><a href="../reference/md.html">md()</a></code> and <code><a href="../reference/html.html">html()</a></code> helpers can used be during label creation with the <code><a href="../reference/tab_header.html">tab_header()</a></code>, <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code>, <code><a href="../reference/tab_spanner.html">tab_spanner()</a></code>, <code>tab_stubhead_label()</code>, and <code><a href="../reference/tab_source_note.html">tab_source_note()</a></code> functions.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="md.html">md()</a></code> </p>
+        </td>
+        <td><p>Interpret input text as Markdown-formatted text</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="html.html">html()</a></code> </p>
+        </td>
+        <td><p>Interpret input text as HTML-formatted text</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="px.html">px()</a></code> </p>
+        </td>
+        <td><p>Helper for providing a numeric value as pixels value</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="pct.html">pct()</a></code> </p>
+        </td>
+        <td><p>Helper for providing a numeric value as percentage</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_title.html">cells_title()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting the table title and subtitle</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_stubhead.html">cells_stubhead()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting the table stubhead cell</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_column_spanners.html">cells_column_spanners()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting the column spanners</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_column_labels.html">cells_column_labels()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting the column labels</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_row_groups.html">cells_row_groups()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting row groups</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_stub.html">cells_stub()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting cells in the table stub</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_body.html">cells_body()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting data cells in the table body</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_summary.html">cells_summary()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting group summary cells</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cells_grand_summary.html">cells_grand_summary()</a></code> </p>
+        </td>
+        <td><p>Location helper for targeting cells in a grand summary</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="currency.html">currency()</a></code> </p>
+        </td>
+        <td><p>Supply a custom currency symbol to <code>fmt_currency()</code></p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cell_text.html">cell_text()</a></code> </p>
+        </td>
+        <td><p>Helper for defining custom text styles for table cells</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cell_fill.html">cell_fill()</a></code> </p>
+        </td>
+        <td><p>Helper for defining custom fills for table cells</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="cell_borders.html">cell_borders()</a></code> </p>
+        </td>
+        <td><p>Helper for defining custom borders for table cells</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="adjust_luminance.html">adjust_luminance()</a></code> </p>
+        </td>
+        <td><p>Adjust the luminance for a palette of colors</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="random_id.html">random_id()</a></code> </p>
+        </td>
+        <td><p>Helper for creating a random <code>id</code> for a <strong>gt</strong> table</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="escape_latex.html">escape_latex()</a></code> </p>
+        </td>
+        <td><p>Perform LaTeX escaping</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="gt_latex_dependencies.html">gt_latex_dependencies()</a></code> </p>
+        </td>
+        <td><p>Get the LaTeX dependencies required for a <strong>gt</strong> table</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-image-addition-functions" class="hasAnchor"><a href="#section-image-addition-functions" class="anchor"></a>Image Addition Functions</h2>
+          <p class="section-desc"><p>We can add images into a <strong>gt</strong> table with the help of the <code>*_image()</code> functions. Two common ways to do this: (1) use <code><a href="../reference/text_transform.html">text_transform()</a></code> to insert images into data cells, (2) use any function that creates new labels (e.g., <code><a href="../reference/tab_header.html">tab_header()</a></code>) and use a <code>*_image()</code> function within the <code><a href="../reference/html.html">html()</a></code> helper.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="web_image.html">web_image()</a></code> </p>
+        </td>
+        <td><p>Helper function for adding an image from the web</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="local_image.html">local_image()</a></code> </p>
+        </td>
+        <td><p>Helper function for adding a local image</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="ggplot_image.html">ggplot_image()</a></code> </p>
+        </td>
+        <td><p>Helper function for adding a ggplot</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="test_image.html">test_image()</a></code> </p>
+        </td>
+        <td><p>Generate a path to a test image</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-table-option-functions" class="hasAnchor"><a href="#section-table-option-functions" class="anchor"></a>Table Option Functions</h2>
+          <p class="section-desc"><p>With the <code>opt_*()</code> functions, we have an easy way to set commonly-used table options without having to use <code><a href="../reference/tab_options.html">tab_options()</a></code> directly. For instance, we can modify the set of marks to use with footnotes, turn on row striping, change the alignment of the table header, and much more.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="opt_footnote_marks.html">opt_footnote_marks()</a></code> </p>
+        </td>
+        <td><p>Option to modify the set of footnote marks</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="opt_row_striping.html">opt_row_striping()</a></code> </p>
+        </td>
+        <td><p>Option to add or remove row striping</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="opt_align_table_header.html">opt_align_table_header()</a></code> </p>
+        </td>
+        <td><p>Option to align the table header</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="opt_all_caps.html">opt_all_caps()</a></code> </p>
+        </td>
+        <td><p>Option to use all caps in select table locations</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="opt_table_lines.html">opt_table_lines()</a></code> </p>
+        </td>
+        <td><p>Option to set table lines to different extents</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="opt_table_outline.html">opt_table_outline()</a></code> </p>
+        </td>
+        <td><p>Option to wrap an outline around the entire table</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-information-functions" class="hasAnchor"><a href="#section-information-functions" class="anchor"></a>Information Functions</h2>
+          <p class="section-desc"><p>These <code>info_*()</code> functions present us with <strong>gt</strong> tables containing useful information. So far, we can get reference information on date styles (<code><a href="../reference/info_date_style.html">info_date_style()</a></code>), on time styles (<code><a href="../reference/info_time_style.html">info_time_style()</a></code>), on a huge number of color palettes (<code><a href="../reference/info_paletteer.html">info_paletteer()</a></code>), on currencies (<code><a href="../reference/info_currencies.html">info_currencies()</a></code>), and, on all of the different locales supported in the formatter functions (<code><a href="../reference/info_locales.html">info_locales()</a></code>).</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="info_date_style.html">info_date_style()</a></code> </p>
+        </td>
+        <td><p>View a table with info on date styles</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="info_time_style.html">info_time_style()</a></code> </p>
+        </td>
+        <td><p>View a table with info on time styles</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="info_currencies.html">info_currencies()</a></code> </p>
+        </td>
+        <td><p>View a table with info on supported currencies</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="info_locales.html">info_locales()</a></code> </p>
+        </td>
+        <td><p>View a table with info on supported locales</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="info_paletteer.html">info_paletteer()</a></code> </p>
+        </td>
+        <td><p>View a table with info on color palettes</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-datasets" class="hasAnchor"><a href="#section-datasets" class="anchor"></a>Datasets</h2>
+          <p class="section-desc"><p>The <strong>gt</strong> package is equipped with six datasets that come in all shapes and sizes. Use them to experiment with the package. Many examples in the internal help documents use these datasets to quickly demonstrate the key features of <strong>gt</strong>.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="countrypops.html">countrypops</a></code> </p>
+        </td>
+        <td><p>Yearly populations of countries from 1960 to 2017</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="sza.html">sza</a></code> </p>
+        </td>
+        <td><p>Twice hourly solar zenith angles by month &amp; latitude</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="gtcars.html">gtcars</a></code> </p>
+        </td>
+        <td><p>Deluxe automobiles from the 2014-2017 period</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="sp500.html">sp500</a></code> </p>
+        </td>
+        <td><p>Daily S&amp;P 500 Index data from 1950 to 2015</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="pizzaplace.html">pizzaplace</a></code> </p>
+        </td>
+        <td><p>A year of pizza sales from a pizza place</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="exibble.html">exibble</a></code> </p>
+        </td>
+        <td><p>A toy example tibble for testing with gt: exibble</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-shiny-functions" class="hasAnchor"><a href="#section-shiny-functions" class="anchor"></a>Shiny Functions</h2>
+          <p class="section-desc"><p>Shiny is great for building interactive web apps with R. There’s really nothing quite like it. The <strong>gt</strong> package includes two functions that work nicely with Shiny: a table render function <code><a href="../reference/render_gt.html">render_gt()</a></code> (for the <code>server</code>) and a table output element <code><a href="../reference/gt_output.html">gt_output()</a></code> (for the <code>ui</code>).</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="render_gt.html">render_gt()</a></code> </p>
+        </td>
+        <td><p>A <strong>gt</strong> display table render function for use in Shiny</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="gt_output.html">gt_output()</a></code> </p>
+        </td>
+        <td><p>Create a <strong>gt</strong> display table output element for Shiny</p></td>
+      </tr>
+    </tbody><tbody>
+      <tr>
+        <th colspan="2">
+          <h2 id="section-export-functions" class="hasAnchor"><a href="#section-export-functions" class="anchor"></a>Export Functions</h2>
+          <p class="section-desc"><p>There may come a day when you need to export a <strong>gt</strong> table to some specific format. A great function for that is <code><a href="../reference/gtsave.html">gtsave()</a></code>, which allows us to save as an HTML file or an image file. Some other functions give us table code as a character vector (e.g., <code><a href="../reference/as_raw_html.html">as_raw_html()</a></code>). Did you use the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function and wish you had that summary data in a tibble? You can get it out with <code><a href="../reference/extract_summary.html">extract_summary()</a></code>.</p></p>
+        </th>
+      </tr>
+      
+      
+    </tbody><tbody>
+      
+      
+      <tr>
+        
+        <td>
+          <p><code><a href="gtsave.html">gtsave()</a></code> </p>
+        </td>
+        <td><p>Save a <strong>gt</strong> table as a file</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="as_raw_html.html">as_raw_html()</a></code> </p>
+        </td>
+        <td><p>Get the HTML content of a <strong>gt</strong> table</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="as_latex.html">as_latex()</a></code> </p>
+        </td>
+        <td><p>Output a gt object as LaTeX</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="as_rtf.html">as_rtf()</a></code> </p>
+        </td>
+        <td><p>Output a <strong>gt</strong> object as RTF</p></td>
+      </tr><tr>
+        
+        <td>
+          <p><code><a href="extract_summary.html">extract_summary()</a></code> </p>
+        </td>
+        <td><p>Extract a summary list from a <strong>gt</strong> object</p></td>
+      </tr>
+    </tbody>
+    </table>
+  </div>
+
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
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+
+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
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diff --git a/docs/reference/info_currencies.html b/docs/reference/info_currencies.html
new file mode 100644
index 000000000..7b3c80489
--- /dev/null
+++ b/docs/reference/info_currencies.html
@@ -0,0 +1,244 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>View a table with info on supported currencies — info_currencies • gt</title>
+
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+<meta property="og:title" content="View a table with info on supported currencies — info_currencies" />
+<meta property="og:description" content="The fmt_currency() function lets us format numeric values as currencies.
+The table generated by the info_currencies() function provides a quick
+reference to all the available currencies. The currency identifiers are
+provided (name, 3-letter currency code, and 3-digit currency code) along with
+the each currency's exponent value (number of digits of the currency
+subunits). A formatted example is provided (based on the value of 49.95) to
+demonstrate the default formatting of each currency." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+<!-- mathjax -->
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+    <li class="dropdown-header">Case Studies</li>
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>View a table with info on supported currencies</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
+    <div class="hidden name"><code>info_currencies.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code><a href='fmt_currency.html'>fmt_currency()</a></code> function lets us format numeric values as currencies.
+The table generated by the <code>info_currencies()</code> function provides a quick
+reference to all the available currencies. The currency identifiers are
+provided (name, 3-letter currency code, and 3-digit currency code) along with
+the each currency's exponent value (number of digits of the currency
+subunits). A formatted example is provided (based on the value of <code>49.95</code>) to
+demonstrate the default formatting of each currency.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>info_currencies</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"code"</span>, <span class='st'>"symbol"</span>), <span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>type</th>
+      <td><p>The type of currency information provided. Can either be <code>code</code>
+where currency information corresponding to 3-letter currency codes is
+provided, or <code>symbol</code> where currency info for common currency names (e.g.,
+dollar, pound, yen, etc.) is returned.</p></td>
+    </tr>
+    <tr>
+      <th>begins_with</th>
+      <td><p>Providing a single letter will filter currencies to only
+those that begin with that letter in their currency code. The default
+(<code>NULL</code>) will produce a table with all currencies displayed. This option
+only constrains the information table where <code>type == "code"</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>There are 172 currencies, which can lead to a verbose display table. To make
+this presentation more focused on retrieval, we can provide an initial letter
+corresponding to the 3-letter currency code to <code>begins_with</code>. This will
+filter currencies in the info table to just the set beginning with the
+supplied letter.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_info_currencies_1.png' width=100% /></p>
+<p><img src='figures/man_info_currencies_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>10-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Information Functions: 
+<code><a href='info_date_style.html'>info_date_style</a>()</code>,
+<code><a href='info_locales.html'>info_locales</a>()</code>,
+<code><a href='info_paletteer.html'>info_paletteer</a>()</code>,
+<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get a table of info on all of</span>
+<span class='co'># the currencies where the three-</span>
+<span class='co'># letter code begins with a "h"</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_currencies</span>(<span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='st'>"h"</span>)
+
+<span class='co'># Get a table of info on all of the</span>
+<span class='co'># common currency name/symbols that</span>
+<span class='co'># can be used with `fmt_currency()`</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span> <span class='fu'>info_currencies</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"symbol"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+
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diff --git a/docs/reference/info_date_style.html b/docs/reference/info_date_style.html
new file mode 100644
index 000000000..a4efe0f07
--- /dev/null
+++ b/docs/reference/info_date_style.html
@@ -0,0 +1,210 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>View a table with info on date styles — info_date_style • gt</title>
+
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+
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+<meta property="og:title" content="View a table with info on date styles — info_date_style" />
+<meta property="og:description" content="The fmt_date() function lets us format date-based values in a convenient
+manner using preset styles. The table generated by the info_date_style()
+function provides a quick reference to all 14 styles, with associated number
+codes, the format names, and example outputs using a fixed date
+(2000-02-29)." />
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+
+      
+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>View a table with info on date styles</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
+    <div class="hidden name"><code>info_date_style.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code><a href='fmt_date.html'>fmt_date()</a></code> function lets us format date-based values in a convenient
+manner using preset styles. The table generated by the <code>info_date_style()</code>
+function provides a quick reference to all 14 styles, with associated number
+codes, the format names, and example outputs using a fixed date
+(<code>2000-02-29</code>).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>info_date_style</span>()</pre>
+
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_info_date_style_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>10-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Information Functions: 
+<code><a href='info_currencies.html'>info_currencies</a>()</code>,
+<code><a href='info_locales.html'>info_locales</a>()</code>,
+<code><a href='info_paletteer.html'>info_paletteer</a>()</code>,
+<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get a table of info on the different</span>
+<span class='co'># date-formatting styles (which are used</span>
+<span class='co'># by supplying a number code to the</span>
+<span class='co'># `fmt_date()` function)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_date_style</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/info_locales.html b/docs/reference/info_locales.html
new file mode 100644
index 000000000..c283de15a
--- /dev/null
+++ b/docs/reference/info_locales.html
@@ -0,0 +1,225 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>View a table with info on supported locales — info_locales • gt</title>
+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
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+<meta property="og:title" content="View a table with info on supported locales — info_locales" />
+<meta property="og:description" content="Many of the fmt_*() functions have a locale argument that makes
+locale-based formatting easier. The table generated by the info_locales()
+function provides a quick reference to all the available locales. The locale
+identifiers are provided (base locale ID, common display name) along with the
+each locale's group and decimal separator marks. A formatted numeric example
+is provided (based on the value of 11027) to demonstrate the default
+formatting of each locale." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>View a table with info on supported locales</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
+    <div class="hidden name"><code>info_locales.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Many of the <code>fmt_*()</code> functions have a <code>locale</code> argument that makes
+locale-based formatting easier. The table generated by the <code>info_locales()</code>
+function provides a quick reference to all the available locales. The locale
+identifiers are provided (base locale ID, common display name) along with the
+each locale's group and decimal separator marks. A formatted numeric example
+is provided (based on the value of <code>11027</code>) to demonstrate the default
+formatting of each locale.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>info_locales</span>(<span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>begins_with</th>
+      <td><p>Providing a single letter will filter locales to only
+those that begin with that letter in their base locale ID. The default
+(<code>NULL</code>) will produce a table with all locales displayed.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>There are 712 locales, which means that a very long display table is provided
+by default. To trim down the output table size, we can provide an initial
+letter corresponding to the base locale ID to <code>begins_with</code>. This will filter
+locales in the info table to just the set that begins with the supplied
+letter.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>10-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Information Functions: 
+<code><a href='info_currencies.html'>info_currencies</a>()</code>,
+<code><a href='info_date_style.html'>info_date_style</a>()</code>,
+<code><a href='info_paletteer.html'>info_paletteer</a>()</code>,
+<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get a table of info on all of</span>
+<span class='co'># the locales where the base</span>
+<span class='co'># locale ID begins with a "v"</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_locales</span>(<span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='st'>"v"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+   </div>
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+  </body>
+</html>
+
+
diff --git a/docs/reference/info_paletteer.html b/docs/reference/info_paletteer.html
new file mode 100644
index 000000000..c66f8508c
--- /dev/null
+++ b/docs/reference/info_paletteer.html
@@ -0,0 +1,263 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>View a table with info on color palettes — info_paletteer • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
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+
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+
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+<meta property="og:title" content="View a table with info on color palettes — info_paletteer" />
+<meta property="og:description" content="While the data_color() function allows us to flexibly color data cells in
+our gt table, the harder part of this process is discovering and
+choosing color palettes that are suitable for the table output. We can make
+this process much easier in two ways: (1) by using the paletteer
+package, which makes a wide range of palettes from various R packages readily
+available, and (2) calling the info_paletteer() function to give us an
+information table that serves as a quick reference for all of the discrete
+color palettes available in paletteer." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+    <div class="page-header">
+    <h1>View a table with info on color palettes</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
+    <div class="hidden name"><code>info_paletteer.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>While the <code><a href='data_color.html'>data_color()</a></code> function allows us to flexibly color data cells in
+our <strong>gt</strong> table, the harder part of this process is discovering and
+choosing color palettes that are suitable for the table output. We can make
+this process much easier in two ways: (1) by using the <strong>paletteer</strong>
+package, which makes a wide range of palettes from various R packages readily
+available, and (2) calling the <code>info_paletteer()</code> function to give us an
+information table that serves as a quick reference for all of the discrete
+color palettes available in <strong>paletteer</strong>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>info_paletteer</span>(<span class='kw'>color_pkgs</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>color_pkgs</th>
+      <td><p>A vector of color packages that determines which sets of
+palettes should be displayed in the information table. If this is
+<code>NULL</code> (the default) then all of the discrete palettes from all of the
+color packages represented in <strong>paletteer</strong> will be displayed.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The palettes displayed are organized by package and by palette name. These
+values are required when obtaining a palette (as a vector of hexadecimal
+colors), from the the <code><a href='https://rdrr.io/pkg/paletteer/man/paletteer_d.html'>paletteer::paletteer_d()</a></code> function. Once we are
+familiar with the names of the color palette packages (e.g.,
+<strong>RColorBrewer</strong>, <strong>ggthemes</strong>, <strong>wesanderson</strong>), we can narrow down
+the content of this information table by supplying a vector of such package
+names to <code>color_pkgs</code>.</p>
+<p>Colors from the following color packages (all supported by <strong>paletteer</strong>)
+are shown by default with <code>info_paletteer()</code>:</p><ul>
+<li><p><strong>awtools</strong>, 5 palettes</p></li>
+<li><p><strong>dichromat</strong>, 17 palettes</p></li>
+<li><p><strong>dutchmasters</strong>, 6 palettes</p></li>
+<li><p><strong>ggpomological</strong>, 2 palettes</p></li>
+<li><p><strong>ggsci</strong>, 42 palettes</p></li>
+<li><p><strong>ggthemes</strong>, 31 palettes</p></li>
+<li><p><strong>ghibli</strong>, 27 palettes</p></li>
+<li><p><strong>grDevices</strong>, 1 palette</p></li>
+<li><p><strong>jcolors</strong>, 13 palettes</p></li>
+<li><p><strong>LaCroixColoR</strong>, 21 palettes</p></li>
+<li><p><strong>NineteenEightyR</strong>, 12 palettes</p></li>
+<li><p><strong>nord</strong>, 16 palettes</p></li>
+<li><p><strong>ochRe</strong>, 16 palettes</p></li>
+<li><p><strong>palettetown</strong>, 389 palettes</p></li>
+<li><p><strong>pals</strong>, 8 palettes</p></li>
+<li><p><strong>Polychrome</strong>, 7 palettes</p></li>
+<li><p><strong>quickpalette</strong>, 17 palettes</p></li>
+<li><p><strong>rcartocolor</strong>, 34 palettes</p></li>
+<li><p><strong>RColorBrewer</strong>, 35 palettes</p></li>
+<li><p><strong>Redmonder</strong>, 41 palettes</p></li>
+<li><p><strong>wesanderson</strong>, 19 palettes</p></li>
+<li><p><strong>yarrr</strong>, 21 palettes</p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_info_paletteer_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>10-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Information Functions: 
+<code><a href='info_currencies.html'>info_currencies</a>()</code>,
+<code><a href='info_date_style.html'>info_date_style</a>()</code>,
+<code><a href='info_locales.html'>info_locales</a>()</code>,
+<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get a table of info on just the</span>
+<span class='co'># `ggthemes` color palette (easily</span>
+<span class='co'># accessible from the paletteer pkg)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='fu'>info_paletteer</span>(
+    <span class='kw'>color_pkgs</span> <span class='kw'>=</span> <span class='st'>"ggthemes"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/info_time_style.html b/docs/reference/info_time_style.html
new file mode 100644
index 000000000..d8e64a40d
--- /dev/null
+++ b/docs/reference/info_time_style.html
@@ -0,0 +1,210 @@
+<!-- Generated by pkgdown: do not edit by hand -->
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+<title>View a table with info on time styles — info_time_style • gt</title>
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
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+<meta property="og:title" content="View a table with info on time styles — info_time_style" />
+<meta property="og:description" content="The fmt_time() function lets us format time-based values in a convenient
+manner using preset styles. The table generated by the info_time_style()
+function provides a quick reference to all five styles, with associated
+number codes, the format names, and example outputs using a fixed time
+(14:35)." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>View a table with info on time styles</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
+    <div class="hidden name"><code>info_time_style.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code><a href='fmt_time.html'>fmt_time()</a></code> function lets us format time-based values in a convenient
+manner using preset styles. The table generated by the <code>info_time_style()</code>
+function provides a quick reference to all five styles, with associated
+number codes, the format names, and example outputs using a fixed time
+(<code>14:35</code>).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>info_time_style</span>()</pre>
+
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_info_time_style_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>10-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Information Functions: 
+<code><a href='info_currencies.html'>info_currencies</a>()</code>,
+<code><a href='info_date_style.html'>info_date_style</a>()</code>,
+<code><a href='info_locales.html'>info_locales</a>()</code>,
+<code><a href='info_paletteer.html'>info_paletteer</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get a table of info on the different</span>
+<span class='co'># time-formatting styles (which are used</span>
+<span class='co'># by supplying a number code to the</span>
+<span class='co'># `fmt_time()` function)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_time_style</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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diff --git a/docs/reference/local_image.html b/docs/reference/local_image.html
new file mode 100644
index 000000000..fb3d465a4
--- /dev/null
+++ b/docs/reference/local_image.html
@@ -0,0 +1,261 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Helper function for adding a local image — local_image • gt</title>
+
+<!-- favicons -->
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+
+<!-- jquery -->
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+<meta property="og:description" content="We can flexibly add a local image (i.e., an image residing on disk) inside of
+a table with local_image() function. The function provides a convenient way
+to generate an HTML fragment using an on-disk PNG or SVG. Because this
+function is currently HTML-based, it is only useful for HTML table output. To
+use this function inside of data cells, it is recommended that the
+text_transform() function is used. With that function, we can specify which
+data cells to target and then include a local_image() call within the
+required user-defined function (for the fn argument). If we want to include
+an image in other places (e.g., in the header, within footnote text, etc.) we
+need to use local_image() within the html() helper function." />
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper function for adding a local image</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
+    <div class="hidden name"><code>local_image.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>We can flexibly add a local image (i.e., an image residing on disk) inside of
+a table with <code>local_image()</code> function. The function provides a convenient way
+to generate an HTML fragment using an on-disk PNG or SVG. Because this
+function is currently HTML-based, it is only useful for HTML table output. To
+use this function inside of data cells, it is recommended that the
+<code><a href='text_transform.html'>text_transform()</a></code> function is used. With that function, we can specify which
+data cells to target and then include a <code>local_image()</code> call within the
+required user-defined function (for the <code>fn</code> argument). If we want to include
+an image in other places (e.g., in the header, within footnote text, etc.) we
+need to use <code>local_image()</code> within the <code><a href='html.html'>html()</a></code> helper function.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>local_image</span>(<span class='no'>filename</span>, <span class='kw'>height</span> <span class='kw'>=</span> <span class='fl'>30</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>filename</th>
+      <td><p>A path to an image file.</p></td>
+    </tr>
+    <tr>
+      <th>height</th>
+      <td><p>The absolute height (px) of the image in the table cell.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character object with an HTML fragment that can be placed inside of
+a cell.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>By itself, the function creates an HTML image tag with an image URI embedded
+within. We can easily experiment with a local PNG or SVG image that's
+available in the <strong>gt</strong> package using the <code><a href='test_image.html'>test_image()</a></code> function. Using
+that, the call <code>local_image(file = test_image(type = "png"))</code> evaluates to:</p>
+<p><code>&lt;img cid=&lt;random CID&gt; src=&lt;data URI&gt; style=\"height:30px;\"&gt;</code></p>
+<p>where a height of <code>30px</code> is a default height chosen to work well within the
+heights of most table rows.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_local_image_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>8-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Image Addition Functions: 
+<code><a href='ggplot_image.html'>ggplot_image</a>()</code>,
+<code><a href='test_image.html'>test_image</a>()</code>,
+<code><a href='web_image.html'>web_image</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Create a tibble that contains heights</span>
+<span class='co'># of an image in pixels (one column as a</span>
+<span class='co'># string, the other as numerical values),</span>
+<span class='co'># then, create a gt table; use the</span>
+<span class='co'># `text_transform()` function to insert</span>
+<span class='co'># a local test image (PNG) image with the</span>
+<span class='co'># various sizes</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
+    <span class='kw'>pixels</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)),
+    <span class='kw'>image</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='text_transform.html'>text_transform</a></span>(
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>image</span>)),
+    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
+      <span class='fu'>local_image</span>(
+        <span class='kw'>filename</span> <span class='kw'>=</span> <span class='fu'><a href='test_image.html'>test_image</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"png"</span>),
+        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='no'>x</span>)
+      )
+    }
+  )</div></pre>
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diff --git a/docs/reference/md.html b/docs/reference/md.html
new file mode 100644
index 000000000..a619e4f8b
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+<meta property="og:description" content="Markdown! It's a wonderful thing. We can use it in certain places (e.g.,
+footnotes, source notes, the table title, etc.) and expect it to render to
+HTML as Markdown does. There is the html() helper that allows you to ferry
+in HTML but this function md()... it's almost like a two-for-one deal (you
+get to use Markdown plus any HTML fragments at the same time)." />
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+    <div class="page-header">
+    <h1>Interpret input text as Markdown-formatted text</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>md.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Markdown! It's a wonderful thing. We can use it in certain places (e.g.,
+footnotes, source notes, the table title, etc.) and expect it to render to
+HTML as Markdown does. There is the <code><a href='html.html'>html()</a></code> helper that allows you to ferry
+in HTML but this function <code>md()</code>... it's almost like a two-for-one deal (you
+get to use Markdown plus any HTML fragments <em>at the same time</em>).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>md</span>(<span class='no'>text</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>text</th>
+      <td><p>The text that is understood to contain Markdown formatting.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character object of class <code>from_markdown</code>. It's tagged as being
+Markdown text and it will undergo conversion to HTML.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_md_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># when adding a title, use the `md()`</span>
+<span class='co'># helper to use Markdown formatting</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>currency</span>, <span class='no'>char</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'>md</span>(<span class='st'>"Using *Markdown*"</span>))</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+</div>
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diff --git a/docs/reference/opt_align_table_header.html b/docs/reference/opt_align_table_header.html
new file mode 100644
index 000000000..a40762de4
--- /dev/null
+++ b/docs/reference/opt_align_table_header.html
@@ -0,0 +1,252 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Option to align the table header — opt_align_table_header • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
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+
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+
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+
+
+<meta property="og:title" content="Option to align the table header — opt_align_table_header" />
+<meta property="og:description" content="By default, a table header added to a gt table has center alignment
+for both the title and the subtitle elements. This function allows us to
+easily set the horizontal alignment of the title and subtitle to the left
+or right by using the &quot;align&quot; argument. This function serves as a
+convenient shortcut for &amp;lt;gt_tbl&amp;gt; %&amp;gt;% tab_options(heading.align = &amp;lt;align&amp;gt;)." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+
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+<!-- mathjax -->
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Option to align the table header</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
+    <div class="hidden name"><code>opt_align_table_header.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>By default, a table header added to a <strong>gt</strong> table has center alignment
+for both the title and the subtitle elements. This function allows us to
+easily set the horizontal alignment of the title and subtitle to the left
+or right by using the <code>"align"</code> argument. This function serves as a
+convenient shortcut for <code>&lt;gt_tbl&gt; %&gt;% tab_options(heading.align = &lt;align&gt;)</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>opt_align_table_header</span>(<span class='no'>data</span>, <span class='kw'>align</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"left"</span>, <span class='st'>"center"</span>, <span class='st'>"right"</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>align</th>
+      <td><p>The alignment of the title and subtitle elements in the table
+header. Options are <code>"left"</code> (the default), <code>"center"</code>, or <code>"right"</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_opt_align_table_header_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>9-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Table Option Functions: 
+<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
+<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
+<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
+<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
+<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
+<span class='co'># a number of table parts added; the header</span>
+<span class='co'># (consisting of the title and the subtitle)</span>
+<span class='co'># are to be aligned to the left with the</span>
+<span class='co'># `opt_align_table_header()` function</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_align_table_header</span>(<span class='kw'>align</span> <span class='kw'>=</span> <span class='st'>"left"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/opt_all_caps.html b/docs/reference/opt_all_caps.html
new file mode 100644
index 000000000..d7a74ffb5
--- /dev/null
+++ b/docs/reference/opt_all_caps.html
@@ -0,0 +1,264 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Option to use all caps in select table locations — opt_all_caps • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
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+
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+<meta property="og:title" content="Option to use all caps in select table locations — opt_all_caps" />
+<meta property="og:description" content="Sometimes an all-capitalized look is suitable for a table. With the
+opt_all_caps() function, we can transform characters in the column labels,
+the stub, and in all row groups in this way (and there's control over which
+of these locations are transformed)." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+</li>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Option to use all caps in select table locations</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
+    <div class="hidden name"><code>opt_all_caps.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Sometimes an all-capitalized look is suitable for a table. With the
+<code>opt_all_caps()</code> function, we can transform characters in the column labels,
+the stub, and in all row groups in this way (and there's control over which
+of these locations are transformed).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>opt_all_caps</span>(
+  <span class='no'>data</span>,
+  <span class='kw'>all_caps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"column_labels"</span>, <span class='st'>"stub"</span>, <span class='st'>"row_group"</span>)
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>all_caps</th>
+      <td><p>A logical value to indicate whether the text transformation
+to all caps should be performed (<code>TRUE</code>, the default) or reset to default
+values (<code>FALSE</code>) for the <code>locations</code> targeted.</p></td>
+    </tr>
+    <tr>
+      <th>locations</th>
+      <td><p>Which locations should undergo this text transformation? By
+default it includes all of the <code>"column_labels"</code>, the <code>"stub"</code>, and the
+<code>"row_group"</code> locations. However, we could just choose one or two of those.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>This function serves as a convenient shortcut for <code>&lt;gt_tbl&gt; %&gt;% tab_options(&lt;location&gt;.text_transform = "uppercase", &lt;location&gt;.font.size = pct(80), &lt;location&gt;.font.weight = "bolder")</code> (for all <code>locations</code> selected).</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_opt_all_caps_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>9-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Table Option Functions: 
+<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
+<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
+<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
+<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
+<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
+<span class='co'># a number of table parts added; all text</span>
+<span class='co'># in the column labels, the stub, and in</span>
+<span class='co'># all row groups is to be transformed to</span>
+<span class='co'># all caps using `opt_all_caps()`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_all_caps</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/opt_footnote_marks.html b/docs/reference/opt_footnote_marks.html
new file mode 100644
index 000000000..eb5c458d7
--- /dev/null
+++ b/docs/reference/opt_footnote_marks.html
@@ -0,0 +1,279 @@
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+<meta property="og:title" content="Option to modify the set of footnote marks — opt_footnote_marks" />
+<meta property="og:description" content="Alter the footnote marks for any footnotes that may be present in the table.
+Either a vector of marks can be provided (including Unicode characters), or,
+a specific keyword could be used to signify a preset sequence. This function
+serves as a shortcut for using tab_options(footnotes.marks = {marks})" />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+
+      
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+      </header>
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Option to modify the set of footnote marks</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
+    <div class="hidden name"><code>opt_footnote_marks.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Alter the footnote marks for any footnotes that may be present in the table.
+Either a vector of marks can be provided (including Unicode characters), or,
+a specific keyword could be used to signify a preset sequence. This function
+serves as a shortcut for using <code><a href='tab_options.html'>tab_options(footnotes.marks = {marks})</a></code></p>
+    </div>
+
+    <pre class="usage"><span class='fu'>opt_footnote_marks</span>(<span class='no'>data</span>, <span class='no'>marks</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>marks</th>
+      <td><p>Either a character vector of length greater than 1 (that will
+represent the series of marks) or a single keyword that represents a preset
+sequence of marks. The valid keywords are: <code>"numbers"</code> (for numeric marks),
+<code>"letters"</code> and <code>"LETTERS"</code> (for lowercase and uppercase alphabetic marks),
+<code>"standard"</code> (for a traditional set of four symbol marks), and <code>"extended"</code>
+(which adds two more symbols to the standard set).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>We can supply a vector of that will represent the series of marks.
+The series of footnote marks is recycled when its usage goes beyond the
+length of the set. At each cycle, the marks are simply doubled, tripled, and
+so on (e.g., <code>*</code> -&gt; <code>**</code> -&gt; <code>***</code>). The option exists for providing keywords
+for certain types of footnote marks. The keywords are:</p>
+<ul>
+<li><p><code>"numbers"</code>: numeric marks, they begin from 1 and these marks are not
+subject to recycling behavior</p></li>
+<li><p><code>"letters"</code>: miniscule alphabetic marks, internally uses the <code>letters</code>
+vector
+which contains 26 lowercase letters of the Roman alphabet</p></li>
+<li><p><code>"LETTERS"</code>: majuscule alphabetic marks, using the <code>LETTERS</code> vector
+which has 26 uppercase letters of the Roman alphabet</p></li>
+<li><p><code>"standard"</code>: symbolic marks, four symbols in total</p></li>
+<li><p><code>"extended"</code>: symbolic marks, extends the standard set by adding two
+more symbols, making six</p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_opt_footnote_marks_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>9-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Table Option Functions: 
+<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
+<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
+<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
+<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
+<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sza` to create a gt table,</span>
+<span class='co'># adding three footnotes; call</span>
+<span class='co'># `opt_footnote_marks()` to specify</span>
+<span class='co'># which footnote marks to use</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>latitude</span>, <span class='no'>tst</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(
+    <span class='kw'>SZA.Max</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>sza</span>),
+    <span class='kw'>SZA.Min</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>sza</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>ungroup</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>30</span>, !<span class='fu'><a href='https://rdrr.io/r/base/is.finite.html'>is.infinite</a></span>(<span class='no'>SZA.Min</span>)) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"tst"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_spanner_delim.html'>tab_spanner_delim</a></span>(<span class='kw'>delim</span> <span class='kw'>=</span> <span class='st'>"."</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_missing.html'>fmt_missing</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>(),
+    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"90+"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_stubhead.html'>tab_stubhead</a></span>(<span class='st'>"TST"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"True solar time."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_stubhead.html'>cells_stubhead</a></span>()
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Solar zenith angle."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_spanners.html'>cells_column_spanners</a></span>(<span class='kw'>spanners</span> <span class='kw'>=</span> <span class='st'>"SZA"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"The Lowest SZA."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_stub.html'>cells_stub</a></span>(<span class='kw'>rows</span> <span class='kw'>=</span> <span class='st'>"1200"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_footnote_marks</span>(<span class='kw'>marks</span> <span class='kw'>=</span> <span class='st'>"standard"</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='input'>
+</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/opt_row_striping.html b/docs/reference/opt_row_striping.html
new file mode 100644
index 000000000..f2b86963c
--- /dev/null
+++ b/docs/reference/opt_row_striping.html
@@ -0,0 +1,249 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
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+<title>Option to add or remove row striping — opt_row_striping • gt</title>
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+<meta property="og:description" content="By default, a gt table does not have row striping enabled. However, this
+function allows us to easily enable or disable striped rows in the table
+body. This function serves as a convenient shortcut for
+&amp;lt;gt_tbl&amp;gt; %&amp;gt;% tab_options(row.striping.include_table_body = TRUE|FALSE)." />
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+
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Option to add or remove row striping</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
+    <div class="hidden name"><code>opt_row_striping.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>By default, a <strong>gt</strong> table does not have row striping enabled. However, this
+function allows us to easily enable or disable striped rows in the table
+body. This function serves as a convenient shortcut for
+<code>&lt;gt_tbl&gt; %&gt;% tab_options(row.striping.include_table_body = TRUE|FALSE)</code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>opt_row_striping</span>(<span class='no'>data</span>, <span class='kw'>row_striping</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>row_striping</th>
+      <td><p>A logical value to indicate whether row striping should
+be added or removed.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_opt_row_striping_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>9-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Table Option Functions: 
+<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
+<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
+<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
+<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
+<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
+<span class='co'># a number of table parts added; next, we</span>
+<span class='co'># add row striping to every second row with</span>
+<span class='co'># the `opt_row_striping()` function</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_row_striping</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/opt_table_lines.html b/docs/reference/opt_table_lines.html
new file mode 100644
index 000000000..a072b240f
--- /dev/null
+++ b/docs/reference/opt_table_lines.html
@@ -0,0 +1,254 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Option to set table lines to different extents — opt_table_lines • gt</title>
+
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+<meta property="og:title" content="Option to set table lines to different extents — opt_table_lines" />
+<meta property="og:description" content="The opt_table_lines() function sets table lines in one of three possible
+ways: (1) all possible table lines drawn (&quot;all&quot;), (2) no table lines at all
+(&quot;none&quot;), and (3) resetting to the default line styles (&quot;default&quot;). This
+is great if you want to start off with lots of lines and subtract just a few
+of them with tab_options() or tab_style(). Or, use it to start with a
+completely lineless table, adding individual lines as needed." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+<!-- mathjax -->
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+</li>
+      </ul>
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+     
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+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Option to set table lines to different extents</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
+    <div class="hidden name"><code>opt_table_lines.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>opt_table_lines()</code> function sets table lines in one of three possible
+ways: (1) all possible table lines drawn (<code>"all"</code>), (2) no table lines at all
+(<code>"none"</code>), and (3) resetting to the default line styles (<code>"default"</code>). This
+is great if you want to start off with lots of lines and subtract just a few
+of them with <code><a href='tab_options.html'>tab_options()</a></code> or <code><a href='tab_style.html'>tab_style()</a></code>. Or, use it to start with a
+completely lineless table, adding individual lines as needed.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>opt_table_lines</span>(<span class='no'>data</span>, <span class='kw'>extent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"all"</span>, <span class='st'>"none"</span>, <span class='st'>"default"</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>extent</th>
+      <td><p>The extent to which lines will be visible in the table. Options
+are <code>"all"</code>, <code>"none"</code>, or <code>"default"</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_opt_table_lines_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>9-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Table Option Functions: 
+<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
+<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
+<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
+<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
+<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
+<span class='co'># a number of table parts added; then, use</span>
+<span class='co'># the `opt_table_lines()` function to</span>
+<span class='co'># haves lines everywhere there can possibly</span>
+<span class='co'># be lines</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_table_lines</span>()</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
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+</div>
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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diff --git a/docs/reference/opt_table_outline.html b/docs/reference/opt_table_outline.html
new file mode 100644
index 000000000..65753f80b
--- /dev/null
+++ b/docs/reference/opt_table_outline.html
@@ -0,0 +1,260 @@
+<!-- Generated by pkgdown: do not edit by hand -->
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<title>Option to wrap an outline around the entire table — opt_table_outline • gt</title>
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+<meta property="og:title" content="Option to wrap an outline around the entire table — opt_table_outline" />
+<meta property="og:description" content="This function puts an outline of consistent style, width, and color
+around the entire table. It'll write over any existing outside lines so long
+as the width is larger that of the existing lines. The default value of
+style (&quot;solid&quot;) will draw a solid outline, whereas a value of &quot;none&quot;
+will remove any present outline." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Option to wrap an outline around the entire table</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
+    <div class="hidden name"><code>opt_table_outline.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This function puts an outline of consistent <code>style</code>, <code>width</code>, and <code>color</code>
+around the entire table. It'll write over any existing outside lines so long
+as the <code>width</code> is larger that of the existing lines. The default value of
+<code>style</code> (<code>"solid"</code>) will draw a solid outline, whereas a value of <code>"none"</code>
+will remove any present outline.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>opt_table_outline</span>(<span class='no'>data</span>, <span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"solid"</span>, <span class='kw'>width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>3</span>), <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#D3D3D3"</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>style, width, color</th>
+      <td><p>The style, width, and color properties for the table
+outline. By default, these are <code>"solid"</code>, <code><a href='px.html'>px(3)</a></code> (or, <code>"3px"</code>), and
+<code>"#D3D3D3"</code>. If <code>"none"</code> is used then the outline is removed and any values
+provided for <code>width</code> and <code>color</code> will be ignored (i.e., not set).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_opt_table_outline_1.png' width=100% /></p>
+<p><img src='figures/man_opt_table_outline_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>9-6</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Table Option Functions: 
+<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
+<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
+<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
+<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
+<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
+<span class='co'># a number of table parts added; have an</span>
+<span class='co'># outline wrap around the entire table by</span>
+<span class='co'># using `opt_table_outline()`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+    )) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_table_outline</span>()
+
+<span class='co'># Remove the table outline with the</span>
+<span class='co'># `style = "none"` option</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>opt_table_outline</span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"none"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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+</div>
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diff --git a/docs/reference/pct.html b/docs/reference/pct.html
new file mode 100644
index 000000000..13b5460df
--- /dev/null
+++ b/docs/reference/pct.html
@@ -0,0 +1,250 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
+<title>Helper for providing a numeric value as percentage — pct • gt</title>
+
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+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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+<meta property="og:title" content="Helper for providing a numeric value as percentage — pct" />
+<meta property="og:description" content="A percentage value acts as a length value that is relative to an initial
+state. For instance an 80 percent value for something will size the target
+to 80 percent the size of its 'previous' value. This type of sizing is
+useful for sizing up or down a length value with an intuitive measure. This
+helper function can be used for the setting of font sizes (e.g., in
+cell_text()) and altering the thicknesses of lines (e.g., in
+cell_borders()). Should a more exact definition of size be required, the
+analogous helper function pct() will be more useful." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper for providing a numeric value as percentage</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>pct.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>A percentage value acts as a length value that is relative to an initial
+state. For instance an 80 percent value for something will size the target
+to 80 percent the size of its 'previous' value. This type of sizing is
+useful for sizing up or down a length value with an intuitive measure. This
+helper function can be used for the setting of font sizes (e.g., in
+<code><a href='cell_text.html'>cell_text()</a></code>) and altering the thicknesses of lines (e.g., in
+<code><a href='cell_borders.html'>cell_borders()</a></code>). Should a more exact definition of size be required, the
+analogous helper function <code>pct()</code> will be more useful.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>pct</span>(<span class='no'>x</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>x</th>
+      <td><p>the numeric value to format as a string percentage for some
+<code><a href='tab_options.html'>tab_options()</a></code> arguments that can take percentage values
+(e.g., <code>table.width</code>).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character vector with a single value in percentage units.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_pct_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='px.html'>px</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># use the `pct()` helper to define the</span>
+<span class='co'># font size for the column labels</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>size</span> <span class='kw'>=</span> <span class='fu'>pct</span>(<span class='fl'>75</span>)),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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diff --git a/docs/reference/pipe.html b/docs/reference/pipe.html
new file mode 100644
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+<meta property="og:title" content="A year of pizza sales from a pizza place — pizzaplace" />
+<meta property="og:description" content="A synthetic dataset that describes pizza sales for a pizza place somewhere in
+the US. While the contents are artificial, the ingredients used to make the
+pizzas are far from it. There are 32 different pizzas that fall into 4
+different categories: classic (classic pizzas: 'You probably had one like
+it before, but never like this!'), chicken (pizzas with chicken as a major
+ingredient: 'Try the Southwest Chicken Pizza! You'll love it!'), supreme
+(pizzas that try a little harder: 'My Soppressata pizza uses only the finest
+salami from my personal salumist!'), and, veggie (pizzas without any meats
+whatsoever: 'My Five Cheese pizza has so many cheeses, I can only offer it in
+Large Size!')." />
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+    <h1>A year of pizza sales from a pizza place</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
+    <div class="hidden name"><code>pizzaplace.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>A synthetic dataset that describes pizza sales for a pizza place somewhere in
+the US. While the contents are artificial, the ingredients used to make the
+pizzas are far from it. There are 32 different pizzas that fall into 4
+different categories: <code>classic</code> (classic pizzas: 'You probably had one like
+it before, but never like this!'), <code>chicken</code> (pizzas with chicken as a major
+ingredient: 'Try the Southwest Chicken Pizza! You'll love it!'), <code>supreme</code>
+(pizzas that try a little harder: 'My Soppressata pizza uses only the finest
+salami from my personal salumist!'), and, <code>veggie</code> (pizzas without any meats
+whatsoever: 'My Five Cheese pizza has so many cheeses, I can only offer it in
+Large Size!').</p>
+    </div>
+
+    <pre class="usage"><span class='no'>pizzaplace</span></pre>
+
+
+    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+
+    <p>A tibble with 49574 rows and 7 variables:</p><dl'>
+<dt>id</dt><dd><p>The ID for the order, which consists of one or more pizzas
+at a give <code>date</code> and <code>time</code></p></dd>
+<dt>date</dt><dd><p>A character representation of the <code>order</code> date,
+expressed in the ISO 8601 date format (YYYY-MM-DD)</p></dd>
+<dt>time</dt><dd><p>A character representation of the <code>order</code> time,
+expressed as a 24-hour time the ISO 8601 extended time format
+(hh:mm:ss)</p></dd>
+<dt>name</dt><dd><p>The short name for the pizza</p></dd>
+<dt>size</dt><dd><p>The size of the pizza, which can either be <code>S</code>,
+<code>M</code>, <code>L</code>, <code>XL</code> (rare!), or <code>XXL</code> (even rarer!);
+most pizzas are available in the <code>S</code>, <code>M</code>, and <code>L</code> sizes
+but exceptions apply</p></dd>
+<dt>type</dt><dd><p>The category or type of pizza, which can either be
+<code>classic</code>, <code>chicken</code>, <code>supreme</code>, or <code>veggie</code></p></dd>
+<dt>price</dt><dd><p>The price of the pizza and the amount that it sold for
+(in USD)</p></dd>
+
+</dl>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Each pizza in the dataset is identified by a short <code>name</code>. The following
+listings provide the full names of each pizza and their main ingredients.</p>
+<p>Classic Pizzas:</p><ul>
+<li><p><code>classic_dlx</code>: The Classic Deluxe Pizza (Pepperoni, Mushrooms, Red
+Onions, Red Peppers, Bacon)</p></li>
+<li><p><code>big_meat</code>: The Big Meat Pizza (Bacon, Pepperoni, Italian Sausage,
+Chorizo Sausage)</p></li>
+<li><p><code>pepperoni</code>: The Pepperoni Pizza (Mozzarella Cheese, Pepperoni)</p></li>
+<li><p><code>hawaiian</code>: The Hawaiian Pizza (Sliced Ham, Pineapple, Mozzarella
+Cheese)</p></li>
+<li><p><code>pep_msh_pep</code>: The Pepperoni, Mushroom, and Peppers Pizza
+(Pepperoni, Mushrooms, and Green Peppers)</p></li>
+<li><p><code>ital_cpcllo</code>: The Italian Capocollo Pizza (Capocollo, Red
+Peppers, Tomatoes, Goat Cheese, Garlic, Oregano)</p></li>
+<li><p><code>napolitana</code>: The Napolitana Pizza (Tomatoes, Anchovies, Green
+Olives, Red Onions, Garlic)</p></li>
+<li><p><code>the_greek</code>: The Greek Pizza (Kalamata Olives, Feta Cheese,
+Tomatoes, Garlic, Beef Chuck Roast, Red Onions)</p></li>
+</ul>
+
+<p>Chicken Pizzas:</p><ul>
+<li><p><code>thai_ckn</code>: The Thai Chicken Pizza (Chicken, Pineapple, Tomatoes,
+Red Peppers, Thai Sweet Chilli Sauce)</p></li>
+<li><p><code>bbq_ckn</code>: The Barbecue Chicken Pizza (Barbecued Chicken, Red
+Peppers, Green Peppers, Tomatoes, Red Onions, Barbecue Sauce)</p></li>
+<li><p><code>southw_ckn</code>: The Southwest Chicken Pizza (Chicken, Tomatoes, Red
+Peppers, Red Onions, Jalapeno Peppers, Corn, Cilantro, Chipotle Sauce)</p></li>
+<li><p><code>cali_ckn</code>: The California Chicken Pizza (Chicken, Artichoke,
+Spinach, Garlic, Jalapeno Peppers, Fontina Cheese, Gouda Cheese)</p></li>
+<li><p><code>ckn_pesto</code>: The Chicken Pesto Pizza (Chicken, Tomatoes, Red
+Peppers, Spinach, Garlic, Pesto Sauce)</p></li>
+<li><p><code>ckn_alfredo</code>: The Chicken Alfredo Pizza (Chicken, Red Onions,
+Red Peppers, Mushrooms, Asiago Cheese, Alfredo Sauce)</p></li>
+</ul>
+
+<p>Supreme Pizzas:</p><ul>
+<li><p><code>brie_carre</code>: The Brie Carre Pizza (Brie Carre Cheese, Prosciutto,
+Caramelized Onions, Pears, Thyme, Garlic)</p></li>
+<li><p><code>calabrese</code>: The Calabrese Pizza (‘Nduja Salami, Pancetta,
+Tomatoes, Red Onions, Friggitello Peppers, Garlic)</p></li>
+<li><p><code>soppressata</code>: The Soppressata Pizza (Soppressata Salami, Fontina
+Cheese, Mozzarella Cheese, Mushrooms, Garlic)</p></li>
+<li><p><code>sicilian</code>: The Sicilian Pizza (Coarse Sicilian Salami, Tomatoes,
+Green Olives, Luganega Sausage, Onions, Garlic)</p></li>
+<li><p><code>ital_supr</code>: The Italian Supreme Pizza (Calabrese Salami,
+Capocollo, Tomatoes, Red Onions, Green Olives, Garlic)</p></li>
+<li><p><code>peppr_salami</code>: The Pepper Salami Pizza (Genoa Salami, Capocollo,
+Pepperoni, Tomatoes, Asiago Cheese, Garlic)</p></li>
+<li><p><code>prsc_argla</code>: The Prosciutto and Arugula Pizza (Prosciutto di San
+Daniele, Arugula, Mozzarella Cheese)</p></li>
+<li><p><code>spinach_supr</code>: The Spinach Supreme Pizza (Spinach, Red Onions,
+Pepperoni, Tomatoes, Artichokes, Kalamata Olives, Garlic, Asiago Cheese)</p></li>
+<li><p><code>spicy_ital</code>: The Spicy Italian Pizza (Capocollo, Tomatoes, Goat
+Cheese, Artichokes, Peperoncini verdi, Garlic)</p></li>
+</ul>
+
+<p>Vegetable Pizzas</p><ul>
+<li><p><code>mexicana</code>: The Mexicana Pizza (Tomatoes, Red Peppers, Jalapeno
+Peppers, Red Onions, Cilantro, Corn, Chipotle Sauce, Garlic)</p></li>
+<li><p><code>four_cheese</code>: The Four Cheese Pizza (Ricotta Cheese, Gorgonzola
+Piccante Cheese, Mozzarella Cheese, Parmigiano Reggiano Cheese, Garlic)</p></li>
+<li><p><code>five_cheese</code>: The Five Cheese Pizza (Mozzarella Cheese, Provolone
+Cheese, Smoked Gouda Cheese, Romano Cheese, Blue Cheese, Garlic)</p></li>
+<li><p><code>spin_pesto</code>: The Spinach Pesto Pizza (Spinach, Artichokes,
+Tomatoes, Sun-dried Tomatoes, Garlic, Pesto Sauce)</p></li>
+<li><p><code>veggie_veg</code>: The Vegetables + Vegetables Pizza (Mushrooms,
+Tomatoes, Red Peppers, Green Peppers, Red Onions, Zucchini, Spinach, Garlic)</p></li>
+<li><p><code>green_garden</code>: The Green Garden Pizza (Spinach, Mushrooms,
+Tomatoes, Green Olives, Feta Cheese)</p></li>
+<li><p><code>mediterraneo</code>: The Mediterranean Pizza (Spinach, Artichokes,
+Kalamata Olives, Sun-dried Tomatoes, Feta Cheese, Plum Tomatoes, Red Onions)</p></li>
+<li><p><code>spinach_fet</code>: The Spinach and Feta Pizza (Spinach, Mushrooms,
+Red Onions, Feta Cheese, Garlic)</p></li>
+<li><p><code>ital_veggie</code>: The Italian Vegetables Pizza (Eggplant, Artichokes,
+Tomatoes, Zucchini, Red Peppers, Garlic, Pesto Sauce)</p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>11-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Datasets: 
+<code><a href='countrypops.html'>countrypops</a></code>,
+<code><a href='exibble.html'>exibble</a></code>,
+<code><a href='gtcars.html'>gtcars</a></code>,
+<code><a href='sp500.html'>sp500</a></code>,
+<code><a href='sza.html'>sza</a></code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
+<span class='co'># available in `pizzaplace`</span>
+<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>pizzaplace</span>)</div><div class='output co'>#&gt; Rows: 49,574
+#&gt; Columns: 7
+#&gt; $ id    <span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2015-000001", "2015-000002", "2015-000002", "2015-000002", "20…
+#&gt; $ date  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2015-01-01", "2015-01-01", "2015-01-01", "2015-01-01", "2015-0…
+#&gt; $ time  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "11:38:36", "11:57:40", "11:57:40", "11:57:40", "11:57:40", "11…
+#&gt; $ name  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "hawaiian", "classic_dlx", "mexicana", "thai_ckn", "five_cheese…
+#&gt; $ size  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "M", "M", "M", "L", "L", "L", "L", "M", "M", "M", "S", "S", "S"…
+#&gt; $ type  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "classic", "classic", "veggie", "chicken", "veggie", "supreme",…
+#&gt; $ price </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 13.25, 16.00, 16.00, 20.75, 18.50, 20.75, 20.75, 16.50, 16.50, …</div><div class='input'>
+</div></span></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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+    </nav>
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+</div>
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diff --git a/docs/reference/print.gt_tbl.html b/docs/reference/print.gt_tbl.html
new file mode 100644
index 000000000..647096fd9
--- /dev/null
+++ b/docs/reference/print.gt_tbl.html
@@ -0,0 +1,196 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
+<title>Print the table — print.gt_tbl • gt</title>
+
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+<meta property="og:title" content="Print the table — print.gt_tbl" />
+<meta property="og:description" content="This facilitates printing of the HTML table to the R console." />
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
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+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+  <a href="../news/index.html">News</a>
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+    <span class="fa fa-github fa-lg"></span>
+     
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+      </ul>
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+    </div><!--/.nav-collapse -->
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Print the table</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/print.R'><code>R/print.R</code></a></small>
+    <div class="hidden name"><code>print.gt_tbl.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This facilitates printing of the HTML table to the R console.</p>
+    </div>
+
+    <pre class="usage"><span class='co'># S3 method for gt_tbl</span>
+<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='kw'>view</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span>())</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>x</th>
+      <td><p>An object of class <code>gt_tbl</code>.</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>Any additional parameters.</p></td>
+    </tr>
+    <tr>
+      <th>view</th>
+      <td><p>The value for <code><a href='https://rdrr.io/r/base/print.html'>print()</a></code>s <code>browse</code> argument.</p></td>
+    </tr>
+    </table>
+
+
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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diff --git a/docs/reference/px.html b/docs/reference/px.html
new file mode 100644
index 000000000..6f09131d6
--- /dev/null
+++ b/docs/reference/px.html
@@ -0,0 +1,244 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Helper for providing a numeric value as pixels value — px • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
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+
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+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
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+<meta property="og:title" content="Helper for providing a numeric value as pixels value — px" />
+<meta property="og:description" content="For certain parameters, a length value is required. Examples include the
+setting of font sizes (e.g., in cell_text()) and thicknesses of lines
+(e.g., in cell_borders()). Setting a length in pixels with px() allows
+for an absolute definition of size as opposed to the analogous helper
+function pct()." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+
+<!-- mathjax -->
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
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+
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+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
+     
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+  <ul class="dropdown-menu" role="menu">
+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper for providing a numeric value as pixels value</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>px.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>For certain parameters, a length value is required. Examples include the
+setting of font sizes (e.g., in <code><a href='cell_text.html'>cell_text()</a></code>) and thicknesses of lines
+(e.g., in <code><a href='cell_borders.html'>cell_borders()</a></code>). Setting a length in pixels with <code>px()</code> allows
+for an absolute definition of size as opposed to the analogous helper
+function <code><a href='pct.html'>pct()</a></code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>px</span>(<span class='no'>x</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>x</th>
+      <td><p>the numeric value to format as a string (e.g., <code>"12px"</code>) for
+some <code><a href='tab_options.html'>tab_options()</a></code> arguments that can take values as units of
+pixels (e.g., <code>table.font.size</code>).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character vector with a single value in pixel units.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_px_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
+<code><a href='cell_fill.html'>cell_fill</a>()</code>,
+<code><a href='cell_text.html'>cell_text</a>()</code>,
+<code><a href='cells_body.html'>cells_body</a>()</code>,
+<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
+<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
+<code><a href='cells_stub.html'>cells_stub</a>()</code>,
+<code><a href='cells_summary.html'>cells_summary</a>()</code>,
+<code><a href='cells_title.html'>cells_title</a>()</code>,
+<code><a href='currency.html'>currency</a>()</code>,
+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='random_id.html'>random_id</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># use the `px()` helper to define the</span>
+<span class='co'># font size for the column labels</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>size</span> <span class='kw'>=</span> <span class='fu'>px</span>(<span class='fl'>20</span>)),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
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+
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+      <div class="copyright">
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+</div>
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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diff --git a/docs/reference/random_id.html b/docs/reference/random_id.html
new file mode 100644
index 000000000..fc42ee3ca
--- /dev/null
+++ b/docs/reference/random_id.html
@@ -0,0 +1,220 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+    <div class="page-header">
+    <h1>Helper for creating a random <code>id</code> for a <strong>gt</strong> table</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
+    <div class="hidden name"><code>random_id.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This helper function can be used to create a random, character-based ID
+value argument of variable length (the default is 10 letters).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>random_id</span>(<span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>10</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>n</th>
+      <td><p>The number of lowercase letters to use for the random ID.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character vector containing a single, random ID.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>7-19</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Helper Functions: 
+<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
+<code><a href='cell_borders.html'>cell_borders</a>()</code>,
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+<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
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+<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
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+<code><a href='escape_latex.html'>escape_latex</a>()</code>,
+<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
+<code><a href='html.html'>html</a>()</code>,
+<code><a href='md.html'>md</a>()</code>,
+<code><a href='pct.html'>pct</a>()</code>,
+<code><a href='px.html'>px</a>()</code></p></div>
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diff --git a/docs/reference/reexports.html b/docs/reference/reexports.html
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diff --git a/docs/reference/render_gt.html b/docs/reference/render_gt.html
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+<meta property="og:description" content="With render_gt() we can create a reactive gt table that works
+wonderfully once assigned to an output slot (with gt_output()). This
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>A <strong>gt</strong> display table render function for use in Shiny</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/shiny.R'><code>R/shiny.R</code></a></small>
+    <div class="hidden name"><code>render_gt.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>With <code>render_gt()</code> we can create a reactive <strong>gt</strong> table that works
+wonderfully once assigned to an output slot (with <code><a href='gt_output.html'>gt_output()</a></code>). This
+function is to be used within Shiny's <code>server()</code> component. We have some
+options for controlling the size of the container holding the <strong>gt</strong> table.
+The <code>width</code> and <code>height</code> arguments allow for sizing the container, and the
+<code>align</code> argument allows us to align the table within the container (some
+other fine-grained options for positioning are available in the
+<code><a href='tab_options.html'>tab_options()</a></code> function).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>render_gt</span>(
+  <span class='no'>expr</span>,
+  <span class='kw'>width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>height</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>env</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/sys.parent.html'>parent.frame</a></span>(),
+  <span class='kw'>quoted</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
+  <span class='kw'>outputArgs</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>()
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>expr</th>
+      <td><p>An expression that creates a <strong>gt</strong> table object. For sake of
+convenience, a data frame or tibble can be used here (it will be
+automatically introduced to <code><a href='gt.html'>gt()</a></code> with its default options).</p></td>
+    </tr>
+    <tr>
+      <th>width, height</th>
+      <td><p>The width and height of the table's container. Either can
+be specified as a single-length character with units of pixels or as a
+percentage. If provided as a single-length numeric vector, it is assumed
+that the value is given in units of pixels. The <code><a href='px.html'>px()</a></code> and <code><a href='pct.html'>pct()</a></code> helper
+functions can also be used to pass in numeric values and obtain values as
+pixel or percent units.</p></td>
+    </tr>
+    <tr>
+      <th>align</th>
+      <td><p>The alignment of the table in its container. By default, this is
+<code>"center"</code>. Other options are <code>"left"</code> and <code>"right"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>env</th>
+      <td><p>The environment in which to evaluate the <code>expr</code>.</p></td>
+    </tr>
+    <tr>
+      <th>quoted</th>
+      <td><p>Is <code>expr</code> a quoted expression (with <code><a href='https://rdrr.io/r/base/substitute.html'>quote()</a></code>)? This is useful
+if you want to save an expression in a variable.</p></td>
+    </tr>
+    <tr>
+      <th>outputArgs</th>
+      <td><p>A list of arguments to be passed through to the implicit
+call to <code><a href='gt_output.html'>gt_output()</a></code> when <code>render_gt</code> is used in an interactive R Markdown
+document.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>We need to ensure that we have the <strong>shiny</strong> package installed first. This
+is easily by using <code><a href='https://rdrr.io/r/utils/install.packages.html'>install.packages("shiny")</a></code>. More information on creating
+Shiny apps can be found at the <a href='https://shiny.rstudio.com'>Shiny Site</a>.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>12-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Shiny functions: 
+<code><a href='gt_output.html'>gt_output</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>shiny</span>)
+
+<span class='co'># Here is a Shiny app (contained within</span>
+<span class='co'># a single file) that (1) prepares a</span>
+<span class='co'># gt table, (2) sets up the `ui` with</span>
+<span class='co'># `gt_output()`, and (3) sets up the</span>
+<span class='co'># `server` with a `render_gt()` that</span>
+<span class='co'># uses the `gt_tbl` object as the input</span>
+<span class='co'># expression</span>
+
+<span class='no'>gt_tbl</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='cols_hide.html'>cols_hide</a></span>(<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"_"</span>))
+
+<span class='no'>ui</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/fluidPage.html'>fluidPage</a></span>(
+
+  <span class='fu'><a href='gt_output.html'>gt_output</a></span>(<span class='kw'>outputId</span> <span class='kw'>=</span> <span class='st'>"table"</span>)
+)
+
+<span class='no'>server</span> <span class='kw'>&lt;-</span> <span class='kw'>function</span>(<span class='no'>input</span>,
+                   <span class='no'>output</span>,
+                   <span class='no'>session</span>) {
+
+  <span class='no'>output</span>$<span class='no'>table</span> <span class='kw'>&lt;-</span>
+    <span class='fu'>render_gt</span>(
+      <span class='kw'>expr</span> <span class='kw'>=</span> <span class='no'>gt_tbl</span>,
+      <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>),
+      <span class='kw'>width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>)
+    )
+}
+
+<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span>()) {
+  <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/shinyApp.html'>shinyApp</a></span>(<span class='no'>ui</span>, <span class='no'>server</span>)
+}</div></pre>
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diff --git a/docs/reference/row_group_order.html b/docs/reference/row_group_order.html
new file mode 100644
index 000000000..d155819f1
--- /dev/null
+++ b/docs/reference/row_group_order.html
@@ -0,0 +1,237 @@
+<!-- Generated by pkgdown: do not edit by hand -->
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<meta property="og:title" content="Modify the ordering of any row groups — row_group_order" />
+<meta property="og:description" content="We can modify the display order of any row groups in a gt object with
+the row_group_order() function. The groups argument can either take a
+vector of row group names or a numeric vector of row group indices; whichever
+is provided, the row groups will adhere to this revised ordering. It isn't
+necessary to provide all row group names in groups, rather, what is
+provided will assume the specified ordering at the top of the table and the
+remaining row groups will follow in their original ordering." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Modify the ordering of any row groups</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_rows.R'><code>R/modify_rows.R</code></a></small>
+    <div class="hidden name"><code>row_group_order.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>We can modify the display order of any row groups in a <strong>gt</strong> object with
+the <code>row_group_order()</code> function. The <code>groups</code> argument can either take a
+vector of row group names or a numeric vector of row group indices; whichever
+is provided, the row groups will adhere to this revised ordering. It isn't
+necessary to provide all row group names in <code>groups</code>, rather, what is
+provided will assume the specified ordering at the top of the table and the
+remaining row groups will follow in their original ordering.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>row_group_order</span>(<span class='no'>data</span>, <span class='no'>groups</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>groups</th>
+      <td><p>A vector of row group names, or, a numeric vector of indices
+corresponding to the new ordering. Either vector must correspond to
+assigned group names or the index positions. Also, either type of vector is
+not required to have all of the row group names or available index
+positions within it; any omitted values will be added to the end while
+preserving the original ordering.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_row_group_order_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>5-1</p>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table</span>
+<span class='co'># with a stub and with row groups;</span>
+<span class='co'># modify the order of the row groups</span>
+<span class='co'># with `row_group_order()`, specifying</span>
+<span class='co'># the new ordering in `groups`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>char</span>, <span class='no'>currency</span>, <span class='no'>row</span>, <span class='no'>group</span>) <span class='kw'>%&gt;%</span>
+    <span class='fu'><a href='gt.html'>gt</a></span>(
+      <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>,
+      <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>
+    ) <span class='kw'>%&gt;%</span>
+    <span class='fu'>row_group_order</span>(
+      <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"grp_b"</span>, <span class='st'>"grp_a"</span>)
+    )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/sp500.html b/docs/reference/sp500.html
new file mode 100644
index 000000000..09910aa1e
--- /dev/null
+++ b/docs/reference/sp500.html
@@ -0,0 +1,220 @@
+<!-- Generated by pkgdown: do not edit by hand -->
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+<meta property="og:description" content="This dataset provides daily price indicators for the S&amp;amp;P 500 index from the
+beginning of 1950 to the end of 2015. The index includes 500 leading
+companies and captures about 80\" />
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Daily S&amp;P 500 Index data from 1950 to 2015</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
+    <div class="hidden name"><code>sp500.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This dataset provides daily price indicators for the S&amp;P 500 index from the
+beginning of 1950 to the end of 2015. The index includes 500 leading
+companies and captures about 80\<!-- % coverage of available market capitalization. --></p>
+    </div>
+
+    <pre class="usage"><span class='no'>sp500</span></pre>
+
+
+    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+
+    <p>A tibble with 16607 rows and 7 variables:</p><dl'>
+<dt>date</dt><dd><p>The date expressed as <code>Date</code> values</p></dd>
+<dt>open, high, low, close</dt><dd><p>The day's opening, high, low, and closing
+prices in USD; the <code>close</code> price is adjusted for splits</p></dd>
+<dt>volume</dt><dd><p>the number of trades for the given <code>date</code></p></dd>
+<dt>adj_close</dt><dd><p>The close price adjusted for both dividends and splits</p></dd>
+
+</dl>
+
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>11-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Datasets: 
+<code><a href='countrypops.html'>countrypops</a></code>,
+<code><a href='exibble.html'>exibble</a></code>,
+<code><a href='gtcars.html'>gtcars</a></code>,
+<code><a href='pizzaplace.html'>pizzaplace</a></code>,
+<code><a href='sza.html'>sza</a></code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
+<span class='co'># available in `sp500`</span>
+<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>sp500</span>)</div><div class='output co'>#&gt; Rows: 16,607
+#&gt; Columns: 7
+#&gt; $ date      <span style='color: #555555;font-style: italic;'>&lt;date&gt;</span><span> 2015-12-31, 2015-12-30, 2015-12-29, 2015-12-28, 2015-12-24…
+#&gt; $ open      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2060.59, 2077.34, 2060.54, 2057.77, 2063.52, 2042.20, 2023.…
+#&gt; $ high      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2062.54, 2077.34, 2081.56, 2057.77, 2067.36, 2064.73, 2042.…
+#&gt; $ low       </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2043.62, 2061.97, 2060.54, 2044.20, 2058.73, 2042.20, 2020.…
+#&gt; $ close     </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2043.94, 2063.36, 2078.36, 2056.50, 2060.99, 2064.29, 2038.…
+#&gt; $ volume    </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2655330000, 2367430000, 2542000000, 2492510000, 1411860000,…
+#&gt; $ adj_close </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2043.94, 2063.36, 2078.36, 2056.50, 2060.99, 2064.29, 2038.…</div><div class='input'>
+</div></span></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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diff --git a/docs/reference/summary_rows.html b/docs/reference/summary_rows.html
new file mode 100644
index 000000000..72e3909e6
--- /dev/null
+++ b/docs/reference/summary_rows.html
@@ -0,0 +1,299 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Add groupwise summary rows using aggregation functions — summary_rows • gt</title>
+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
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+
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+<meta property="og:title" content="Add groupwise summary rows using aggregation functions — summary_rows" />
+<meta property="og:description" content="Add summary rows to one or more row groups by using the table data and any
+suitable aggregation functions. You choose how to format the values in the
+resulting summary cells by use of a formatter function (e.g, fmt_number,
+etc.) and any relevant options." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
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+    </li>
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+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add groupwise summary rows using aggregation functions</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/summary_rows.R'><code>R/summary_rows.R</code></a></small>
+    <div class="hidden name"><code>summary_rows.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Add summary rows to one or more row groups by using the table data and any
+suitable aggregation functions. You choose how to format the values in the
+resulting summary cells by use of a <code>formatter</code> function (e.g, <code>fmt_number</code>,
+etc.) and any relevant options.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>summary_rows</span>(
+  <span class='no'>data</span>,
+  <span class='kw'>groups</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+  <span class='no'>fns</span>,
+  <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"---"</span>,
+  <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+  <span class='no'>...</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>groups</th>
+      <td><p>The groups to consider for generation of groupwise summary
+rows. By default this is set to <code>NULL</code>, which results in the formation of
+grand summary rows (a grand summary operates on all table data). Providing
+the names of row groups in <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code> will create a groupwise summary and
+generate summary rows for the specified groups. Setting this to <code>TRUE</code>
+indicates that all available groups will receive groupwise summary rows.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns for which the summaries should be calculated.</p></td>
+    </tr>
+    <tr>
+      <th>fns</th>
+      <td><p>Functions used for aggregations. This can include base functions
+like <code>mean</code>, <code>min</code>, <code>max</code>, <code>median</code>, <code>sd</code>, or <code>sum</code> or any other
+user-defined aggregation function. The function(s) should be supplied
+within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. Within that list, we can specify the functions by use of
+function names in quotes (e.g., <code>"sum"</code>), as bare functions (e.g., <code>sum</code>),
+or as one-sided R formulas using a leading <code>~</code>. In the formula
+representation, a <code>.</code> serves as the data to be summarized (e.g., <code><a href='https://rdrr.io/r/base/sum.html'>sum(., na.rm = TRUE)</a></code>). The use of named arguments is recommended as the names
+will serve as summary row labels for the corresponding summary rows data
+(the labels can derived from the function names but only when not providing
+bare function names).</p></td>
+    </tr>
+    <tr>
+      <th>missing_text</th>
+      <td><p>The text to be used in place of <code>NA</code> values in summary
+cells with no data outputs.</p></td>
+    </tr>
+    <tr>
+      <th>formatter</th>
+      <td><p>A formatter function name. These can be any of the <code>fmt_*()</code>
+functions available in the package (e.g., <code><a href='fmt_number.html'>fmt_number()</a></code>, <code><a href='fmt_percent.html'>fmt_percent()</a></code>,
+etc.), or a custom function using <code><a href='fmt.html'>fmt()</a></code>. The default function is
+<code><a href='fmt_number.html'>fmt_number()</a></code> and its options can be accessed through <code>...</code>.</p></td>
+    </tr>
+    <tr>
+      <th>...</th>
+      <td><p>Values passed to the <code>formatter</code> function, where the provided
+values are to be in the form of named vectors. For example, when using the
+default <code>formatter</code> function, <code><a href='fmt_number.html'>fmt_number()</a></code>, options such as <code>decimals</code>,
+<code>use_seps</code>, and <code>locale</code> can be used.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Should we need to obtain the summary data for external purposes, the
+<code><a href='extract_summary.html'>extract_summary()</a></code> function can be used with a <code>gt_tbl</code> object where summary
+rows were added via <code>summary_rows()</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_summary_rows_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>6-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Add Rows: 
+<code><a href='grand_summary_rows.html'>grand_summary_rows</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table with</span>
+<span class='co'># row groups; create summary rows (`min`,</span>
+<span class='co'># `max`, `avg`) by row group, where each</span>
+<span class='co'># each row group is a week number</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
+      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-16"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='no'>date</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
+    <span class='kw'>week</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
+      <span class='st'>"W"</span>, <span class='fu'><a href='https://rdrr.io/r/base/strptime.html'>strftime</a></span>(<span class='no'>date</span>, <span class='kw'>format</span> <span class='kw'>=</span> <span class='st'>"%V"</span>))
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>adj_close</span>, -<span class='no'>volume</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(
+    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
+    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"week"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>summary_rows</span>(
+    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>high</span>, <span class='no'>low</span>, <span class='no'>close</span>),
+    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>),
+      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>),
+      <span class='kw'>avg</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/mean.html'>mean</a></span>(<span class='no'>.</span>)),
+    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
+    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
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+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
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+<meta property="og:description" content="This dataset contains solar zenith angles (in degrees, with the range of
+0-90) every half hour from 04:00 to 12:00, true solar time. This set of
+values is calculated on the first of every month for 4 different northern
+hemisphere latitudes. For determination of afternoon values, the presented
+tabulated values are symmetric about noon." />
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Twice hourly solar zenith angles by month &amp; latitude</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
+    <div class="hidden name"><code>sza.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This dataset contains solar zenith angles (in degrees, with the range of
+0-90) every half hour from 04:00 to 12:00, true solar time. This set of
+values is calculated on the first of every month for 4 different northern
+hemisphere latitudes. For determination of afternoon values, the presented
+tabulated values are symmetric about noon.</p>
+    </div>
+
+    <pre class="usage"><span class='no'>sza</span></pre>
+
+
+    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+
+    <p>A tibble with 816 rows and 4 variables:</p><dl'>
+<dt>latitude</dt><dd><p>The latitude in decimal degrees for the observations</p></dd>
+<dt>month</dt><dd><p>The measurement month; all calculations where conducted
+for the first day of each month</p></dd>
+<dt>tst</dt><dd><p>The true solar time at the given <code>latitude</code> and date
+(first of <code>month</code>) for which the solar zenith angle is calculated</p></dd>
+<dt>sza</dt><dd><p>The solar zenith angle in degrees, where <code>NA</code>s
+indicate that sunrise hadn't yet occurred by the <code>tst</code> value</p></dd>
+
+</dl>
+
+    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
+
+    <p>Calculated Actinic Fluxes (290 - 700 nm) for Air Pollution
+Photochemistry Applications (Peterson, 1976), available at:
+<a href='https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=9100JA26.txt'>https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=9100JA26.txt</a>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The solar zenith angle (SZA) is one measure that helps to describe the sun's
+path across the sky. It's defined as the angle of the sun relative to a line
+perpendicular to the earth's surface. It is useful to calculate the SZA in
+relation to the true solar time. True solar time relates to the position of
+the sun with respect to the observer, which is different depending on the
+exact longitude. For example, two hours before the sun crosses the meridian
+(the highest point it would reach that day) corresponds to a true solar time
+of 10 a.m. The SZA has a strong dependence on the observer's latitude. For
+example, at a latitude of 50 degrees N at the start of January, the noontime
+SZA is 73.0 but a different observer at 20 degrees N would measure the
+noontime SZA to be 43.0 degrees.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>11-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Datasets: 
+<code><a href='countrypops.html'>countrypops</a></code>,
+<code><a href='exibble.html'>exibble</a></code>,
+<code><a href='gtcars.html'>gtcars</a></code>,
+<code><a href='pizzaplace.html'>pizzaplace</a></code>,
+<code><a href='sp500.html'>sp500</a></code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
+<span class='co'># available in `sza`</span>
+<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>sza</span>)</div><div class='output co'>#&gt; Rows: 816
+#&gt; Columns: 4
+#&gt; $ latitude <span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, …
+#&gt; $ month    </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span> jan, jan, jan, jan, jan, jan, jan, jan, jan, jan, jan, jan, …
+#&gt; $ tst      </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "0400", "0430", "0500", "0530", "0600", "0630", "0700", "073…
+#&gt; $ sza      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> NA, NA, NA, NA, NA, NA, 84.9, 78.7, 72.7, 66.1, 61.5, 56.5, …</div><div class='input'>
+</div></span></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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diff --git a/docs/reference/tab_footnote.html b/docs/reference/tab_footnote.html
new file mode 100644
index 000000000..b60b895d2
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@@ -0,0 +1,284 @@
+<!-- Generated by pkgdown: do not edit by hand -->
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+<title>Add a table footnote — tab_footnote • gt</title>
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+<meta property="og:title" content="Add a table footnote — tab_footnote" />
+<meta property="og:description" content="The tab_footnote() function can make it a painless process to add a
+footnote to a gt table. There are two components to a footnote: (1) a
+footnote mark that is attached to the targeted cell text, and (2) the
+footnote text (that starts with the corresponding footnote mark) that is
+placed in the table's footer area. Each call of tab_footnote() will add a
+different note, and one or more cells can be targeted via the location helper
+functions (e.g., cells_body(), cells_column_labels(), etc.)." />
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+
+      
+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add a table footnote</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_footnote.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>The <code>tab_footnote()</code> function can make it a painless process to add a
+footnote to a <strong>gt</strong> table. There are two components to a footnote: (1) a
+footnote mark that is attached to the targeted cell text, and (2) the
+footnote text (that starts with the corresponding footnote mark) that is
+placed in the table's footer area. Each call of <code>tab_footnote()</code> will add a
+different note, and one or more cells can be targeted via the location helper
+functions (e.g., <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_column_labels.html'>cells_column_labels()</a></code>, etc.).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_footnote</span>(<span class='no'>data</span>, <span class='no'>footnote</span>, <span class='no'>locations</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>footnote</th>
+      <td><p>The text to be used in the footnote. We can optionally use
+the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> functions to style the text as Markdown or to
+retain HTML elements in the footnote text.</p></td>
+    </tr>
+    <tr>
+      <th>locations</th>
+      <td><p>The cell or set of cells to be associated with the footnote.
+Supplying any of the <code>cells_*()</code> helper functions is a useful way to target
+the location cells that are associated with the footnote text. These helper
+functions are: <code><a href='cells_title.html'>cells_title()</a></code>, <code><a href='cells_stubhead.html'>cells_stubhead()</a></code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>, <code><a href='cells_column_labels.html'>cells_column_labels()</a></code>, <code><a href='cells_row_groups.html'>cells_row_groups()</a></code>,
+<code><a href='cells_stub.html'>cells_stub()</a></code>, <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_summary.html'>cells_summary()</a></code>, and
+<code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>. Additionally, we can enclose several <code>cells_*()</code>
+calls within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code> if we wish to link the footnote text to different
+types of locations (e.g., body cells, row group labels, the table title,
+etc.).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>The formatting of the footnotes can be controlled through the use of various
+parameters in the <code><a href='tab_options.html'>tab_options()</a></code> function:</p>
+<ul>
+<li><p><code>footnotes.sep</code>: allows for a choice of the separator between
+consecutive footnotes in the table footer. By default, this is set to a
+linebreak.</p></li>
+<li><p><code>footnotes.marks</code>: the set of sequential characters or numbers used
+to identify the footnotes.</p></li>
+<li><p><code>footnotes.font.size</code>: the size of the font used in the footnote
+section.</p></li>
+<li><p><code>footnotes.padding</code>: the amount of padding to apply between the
+footnote and source note sections in the table footer.</p></li>
+</ul>
+
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_footnote_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-6</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `sza` to create a gt table; color</span>
+<span class='co'># the `sza` column using the `data_color()`</span>
+<span class='co'># function, then, add a footnote to the</span>
+<span class='co'># `sza` column label explaining what the</span>
+<span class='co'># color scale signifies</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>20</span> <span class='kw'>&amp;</span>
+      <span class='no'>month</span> <span class='kw'>==</span> <span class='st'>"jan"</span> <span class='kw'>&amp;</span>
+      !<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>sza</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>, -<span class='no'>month</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='data_color.html'>data_color</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sza</span>),
+    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
+      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"white"</span>, <span class='st'>"yellow"</span>, <span class='st'>"navyblue"</span>),
+      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>0</span>, <span class='fl'>90</span>))
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_footnote</span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Color indicates height of sun."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sza</span>))
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+</div>
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diff --git a/docs/reference/tab_header.html b/docs/reference/tab_header.html
new file mode 100644
index 000000000..288a2aea9
--- /dev/null
+++ b/docs/reference/tab_header.html
@@ -0,0 +1,239 @@
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<meta property="og:title" content="Add a table header — tab_header" />
+<meta property="og:description" content="We can add a table header to the gt table with a title and even a
+subtitle. A table header is an optional table part that is positioned above
+the column labels. We have the flexibility to use Markdown formatting for the
+header's title and subtitle. Furthermore, if the table is intended for HTML
+output, we can use HTML in either of the title or subtitle." />
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add a table header</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_header.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>We can add a table header to the <strong>gt</strong> table with a title and even a
+subtitle. A table header is an optional table part that is positioned above
+the column labels. We have the flexibility to use Markdown formatting for the
+header's title and subtitle. Furthermore, if the table is intended for HTML
+output, we can use HTML in either of the title or subtitle.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_header</span>(<span class='no'>data</span>, <span class='no'>title</span>, <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>title, subtitle</th>
+      <td><p>Text to be used in the table title and, optionally, for
+the table subtitle. We can elect to use the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> helper
+functions to style the text as Markdown or to retain HTML elements in the
+text.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_header_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># add a header part to contain a title</span>
+<span class='co'># and subtitle</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_header</span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
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+
+
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+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
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+</html>
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diff --git a/docs/reference/tab_options.html b/docs/reference/tab_options.html
new file mode 100644
index 000000000..9629ff247
--- /dev/null
+++ b/docs/reference/tab_options.html
@@ -0,0 +1,647 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<title>Modify the table output options — tab_options • gt</title>
+
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+
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+
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+<meta property="og:title" content="Modify the table output options — tab_options" />
+<meta property="og:description" content="Modify the options available in a table. These options are named by the
+components, the subcomponents, and the element that can adjusted." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
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+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+     
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+    <li class="dropdown-header">How to Use</li>
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Modify the table output options</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_options.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Modify the options available in a table. These options are named by the
+components, the subcomponents, and the element that can adjusted.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_options</span>(
+  <span class='no'>data</span>,
+  <span class='kw'>container.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>container.height</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>container.overflow.x</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>container.overflow.y</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.margin.left</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.margin.right</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.font.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.font.color.light</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.right.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.right.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.right.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.left.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.left.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table.border.left.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.title.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.title.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.subtitle.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.subtitle.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>heading.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.vlines.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.vlines.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.vlines.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>column_labels.hidden</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.left.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.left.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.left.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.right.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.right.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row_group.border.right.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.hlines.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.hlines.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.hlines.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.vlines.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.vlines.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.vlines.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>table_body.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.border.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.border.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>stub.border.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>data_row.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>summary_row.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>summary_row.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>summary_row.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>summary_row.border.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>summary_row.border.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>summary_row.border.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>grand_summary_row.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>grand_summary_row.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>grand_summary_row.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>grand_summary_row.border.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>grand_summary_row.border.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>grand_summary_row.border.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.sep</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>footnotes.marks</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>source_notes.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row.striping.background_color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row.striping.include_stub</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
+  <span class='kw'>row.striping.include_table_body</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
+)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>container.width, container.height</th>
+      <td><p>The width and height of the table's
+container. Can be specified as a single-length character with units of
+pixels or as a percentage. If provided as a single-length numeric vector,
+it is assumed that the value is given in units of pixels. The <code><a href='px.html'>px()</a></code> and
+<code><a href='pct.html'>pct()</a></code> helper functions can also be used to pass in numeric values and
+obtain values as pixel or percent units.</p></td>
+    </tr>
+    <tr>
+      <th>container.overflow.x, container.overflow.y</th>
+      <td><p>Options to enable scrolling
+in the horizontal and vertical directions when the table content overflows
+the container dimensions. Using <code>TRUE</code> (the default for both) means that
+horizontal or vertical scrolling is enabled to view the entire table in
+those directions. With <code>FALSE</code>, the table may be clipped if the table width
+or height exceeds the <code>container.width</code> or <code>container.height</code>.</p></td>
+    </tr>
+    <tr>
+      <th>table.width</th>
+      <td><p>The width of the table. Can be specified as a
+single-length character with units of pixels or as a percentage. If
+provided as a single-length numeric vector, it is assumed that the value is
+given in units of pixels. The <code><a href='px.html'>px()</a></code> and <code><a href='pct.html'>pct()</a></code> helper functions can also
+be used to pass in numeric values and obtain values as pixel or percent
+units.</p></td>
+    </tr>
+    <tr>
+      <th>table.align</th>
+      <td><p>The horizontal alignment of the table in its container. By
+default, this is <code>"center"</code>. Other options are <code>"left"</code> and <code>"right"</code>. This
+will automatically set <code>table.margin.left</code> and <code>table.margin.right</code> to the
+appropriate values.</p></td>
+    </tr>
+    <tr>
+      <th>table.margin.left, table.margin.right</th>
+      <td><p>The size of the margins on the
+left and right of the table within the container. Can be specified as a
+single-length character with units of pixels or as a percentage. If
+provided as a single-length numeric vector, it is assumed that the value is
+given in units of pixels. The <code><a href='px.html'>px()</a></code> and <code><a href='pct.html'>pct()</a></code> helper functions can also
+be used to pass in numeric values and obtain values as pixel or percent
+units. Using <code>table.margin.left</code> or <code>table.margin.right</code> will overwrite any
+values set by <code>table.align</code>.</p></td>
+    </tr>
+    <tr>
+      <th>table.background.color, heading.background.color, column_labels.background.color, row_group.background.color, stub.background.color, summary_row.background.color, grand_summary_row.background.color, footnotes.background.color, source_notes.background.color</th>
+      <td><p>Background colors for the parent element <code>table</code> and the following child
+elements: <code>heading</code>, <code>column_labels</code>, <code>row_group</code>, <code>stub</code>, <code>summary_row</code>,
+<code>grand_summary_row</code>, <code>footnotes</code>, and <code>source_notes</code>. A color name or a
+hexadecimal color code should be provided.</p></td>
+    </tr>
+    <tr>
+      <th>table.font.color, table.font.color.light</th>
+      <td><p>The text color used throughout the table. There are two variants:
+<code>table.font.color</code> is for text overlaid on lighter background colors, and
+<code>table.font.color.light</code> is automatically used when text needs to be
+overlaid on darker background colors. A color name or a hexadecimal color
+code should be provided.</p></td>
+    </tr>
+    <tr>
+      <th>table.font.size, heading.title.font.size, heading.subtitle.font.size, column_labels.font.size, row_group.font.size, stub.font.size, footnotes.font.size, source_notes.font.size</th>
+      <td><p>The font sizes for the parent text element <code>table</code> and the following child
+elements: <code>heading.title</code>, <code>heading.subtitle</code>, <code>column_labels</code>,
+<code>row_group</code>, <code>footnotes</code>, and <code>source_notes</code>. Can be specified as a
+single-length character vector with units of pixels (e.g., <code>12px</code>) or as a
+percentage (e.g., <code>80\%</code>). If provided as a single-length numeric vector,
+it is assumed that the value is given in units of pixels. The <code><a href='px.html'>px()</a></code> and
+<code><a href='pct.html'>pct()</a></code> helper functions can also be used to pass in numeric values and
+obtain values as pixel or percentage units.</p></td>
+    </tr>
+    <tr>
+      <th>table.border.top.style, table.border.top.width, table.border.top.color, table.border.right.style, table.border.right.width, table.border.right.color, table.border.bottom.style, table.border.bottom.width, table.border.bottom.color, table.border.left.style, table.border.left.width, table.border.left.color</th>
+      <td><p>The style, width, and color properties of the table's absolute top and
+absolute bottom borders.</p></td>
+    </tr>
+    <tr>
+      <th>heading.align</th>
+      <td><p>Controls the horizontal alignment of the heading title
+and subtitle. We can either use <code>"center"</code>, <code>"left"</code>, or <code>"right"</code>.</p></td>
+    </tr>
+    <tr>
+      <th>heading.title.font.weight, heading.subtitle.font.weight, column_labels.font.weight, row_group.font.weight, stub.font.weight</th>
+      <td><p>The font weights of the <code>heading.title</code>, <code>heading.subtitle</code>,
+<code>column_labels</code>, <code>row_group</code>, and <code>stub</code> text elements. Can be a text-based
+keyword such as <code>"normal"</code>, <code>"bold"</code>, <code>"lighter"</code>, <code>"bolder"</code>, or, a
+numeric value between <code>1</code> and <code>1000</code>, inclusive. Note that only variable
+fonts may support the numeric mapping of weight.</p></td>
+    </tr>
+    <tr>
+      <th>heading.border.bottom.style, heading.border.bottom.width, heading.border.bottom.color</th>
+      <td><p>The style, width, and color properties of the header's bottom border. This
+border shares space with that of the <code>column_labels</code> location. If the
+<code>width</code> of this border is larger, then it will be the visible border.</p></td>
+    </tr>
+    <tr>
+      <th>heading.border.lr.style, heading.border.lr.width, heading.border.lr.color</th>
+      <td><p>The style, width, and color properties for the left and right borders of
+the <code>heading</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>column_labels.text_transform, row_group.text_transform, stub.text_transform, summary_row.text_transform, grand_summary_row.text_transform</th>
+      <td><p>Options to apply text transformations to the <code>column_labels</code>, <code>row_group</code>,
+<code>stub</code>, <code>summary_row</code>, and <code>grand_summary_row</code> text elements. Either of the
+<code>"uppercase"</code>, <code>"lowercase"</code>, or <code>"capitalize"</code> keywords can be used.</p></td>
+    </tr>
+    <tr>
+      <th>column_labels.vlines.style, column_labels.vlines.width, column_labels.vlines.color</th>
+      <td><p>The style, width, and color properties for all vertical lines ('vlines')
+of the the <code>column_labels</code>.</p></td>
+    </tr>
+    <tr>
+      <th>column_labels.border.top.style, column_labels.border.top.width, column_labels.border.top.color</th>
+      <td><p>The style, width, and color properties for the top border of the
+<code>column_labels</code> location. This border shares space with that of the
+<code>heading</code> location. If dthe <code>width</code> of this border is larger, then it will
+be the visible border.</p></td>
+    </tr>
+    <tr>
+      <th>column_labels.border.bottom.style, column_labels.border.bottom.width, column_labels.border.bottom.color</th>
+      <td><p>The style, width, and color properties for the bottom border of the
+<code>column_labels</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>column_labels.border.lr.style, column_labels.border.lr.width, column_labels.border.lr.color</th>
+      <td><p>The style, width, and color properties for the left and right borders of
+the <code>column_labels</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>column_labels.hidden</th>
+      <td><p>An option to hide the column labels. If providing
+<code>TRUE</code> then the entire <code>column_labels</code> location won't be seen and the table
+header (if present) will collapse downward.</p></td>
+    </tr>
+    <tr>
+      <th>row_group.border.top.style, row_group.border.top.width, row_group.border.top.color, row_group.border.bottom.style, row_group.border.bottom.width, row_group.border.bottom.color, row_group.border.left.style, row_group.border.left.width, row_group.border.left.color, row_group.border.right.style, row_group.border.right.width, row_group.border.right.color</th>
+      <td><p>The style, width, and color properties for all top, bottom, left, and right
+borders of the <code>row_group</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>table_body.hlines.style, table_body.hlines.width, table_body.hlines.color, table_body.vlines.style, table_body.vlines.width, table_body.vlines.color</th>
+      <td><p>The style, width, and color properties for all horizontal lines ('hlines')
+and vertical lines ('vlines') in the <code>table_body</code>.</p></td>
+    </tr>
+    <tr>
+      <th>table_body.border.top.style, table_body.border.top.width, table_body.border.top.color, table_body.border.bottom.style, table_body.border.bottom.width, table_body.border.bottom.color</th>
+      <td><p>The style, width, and color properties for all top and bottom borders of
+the <code>table_body</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>stub.border.style, stub.border.width, stub.border.color</th>
+      <td><p>The style, width, and color properties for the vertical border of the table
+stub.</p></td>
+    </tr>
+    <tr>
+      <th>data_row.padding, row_group.padding, summary_row.padding, grand_summary_row.padding, footnotes.padding, source_notes.padding</th>
+      <td><p>The amount of vertical padding to incorporate in the <code>data_row</code>,
+<code>row_group</code>, <code>summary_row</code>, <code>grand_summary_row</code>, <code>footnotes</code>, and
+<code>source_notes</code> locations.</p></td>
+    </tr>
+    <tr>
+      <th>summary_row.border.style, summary_row.border.width, summary_row.border.color</th>
+      <td><p>The style, width, and color properties for all horizontal borders of the
+<code>summary_row</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>grand_summary_row.border.style, grand_summary_row.border.width, grand_summary_row.border.color</th>
+      <td><p>The style, width, and color properties for the top borders of the
+<code>grand_summary_row</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>footnotes.border.bottom.style, footnotes.border.bottom.width, footnotes.border.bottom.color</th>
+      <td><p>The style, width, and color properties for the bottom border of the
+<code>footnotes</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>footnotes.border.lr.style, footnotes.border.lr.width, footnotes.border.lr.color</th>
+      <td><p>The style, width, and color properties for the left and right borders of
+the <code>footnotes</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>footnotes.sep</th>
+      <td><p>The separating characters between adjacent footnotes in
+the footnotes section. The default value produces a linebreak.</p></td>
+    </tr>
+    <tr>
+      <th>footnotes.marks</th>
+      <td><p>The set of sequential marks used to reference and
+identify each of the footnotes (same input as the <code><a href='opt_footnote_marks.html'>opt_footnote_marks()</a></code>
+function. We can supply a vector that represents the series of footnote
+marks. This vector is recycled when its usage goes beyond the length of the
+set. At each cycle, the marks are simply combined (e.g., <code>*</code> -&gt; <code>**</code> -&gt;
+<code>***</code>). The option exists for providing keywords for certain types of
+footnote marks. The keyword <code>"numbers"</code> (the default, indicating that we
+want to use numeric marks). We can use lowercase <code>"letters"</code> or uppercase
+<code>"LETTERS"</code>. There is the option for using a traditional symbol set where
+<code>"standard"</code> provides four symbols, and, <code>"extended"</code> adds two more
+symbols, making six.</p></td>
+    </tr>
+    <tr>
+      <th>source_notes.border.bottom.style, source_notes.border.bottom.width, source_notes.border.bottom.color</th>
+      <td><p>The style, width, and color properties for the bottom border of the
+<code>source_notes</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>source_notes.border.lr.style, source_notes.border.lr.width, source_notes.border.lr.color</th>
+      <td><p>The style, width, and color properties for the left and right borders of
+the <code>source_notes</code> location.</p></td>
+    </tr>
+    <tr>
+      <th>row.striping.background_color</th>
+      <td><p>The background color for striped table
+body rows. A color name or a hexadecimal color code should be provided.</p></td>
+    </tr>
+    <tr>
+      <th>row.striping.include_stub</th>
+      <td><p>An option for whether to include the stub
+when striping rows.</p></td>
+    </tr>
+    <tr>
+      <th>row.striping.include_table_body</th>
+      <td><p>An option for whether to include the
+table body when striping rows.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_options_1.png' width=100% /></p>
+<p><img src='figures/man_tab_options_2.png' width=100% /></p>
+<p><img src='figures/man_tab_options_3.png' width=100% /></p>
+<p><img src='figures/man_tab_options_4.png' width=100% /></p>
+<p><img src='figures/man_tab_options_5.png' width=100% /></p>
+<p><img src='figures/man_tab_options_6.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-9</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
+<span class='co'># all the main parts added; we can use this</span>
+<span class='co'># going forward to demo some `tab_options()`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
+    -<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='no'>fctr</span>, <span class='no'>date</span>, <span class='no'>time</span>, <span class='no'>datetime</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(
+    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>,
+    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **exibble**"</span>),
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`exibble` is an R dataset"</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_currency.html'>fmt_currency</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Using commas for separators."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;</span> <span class='fl'>1000</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Using commas for separators."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&gt;</span> <span class='fl'>1000</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
+    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Alphabetical fruit."</span>,
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>char</span>))
+  )
+
+<span class='co'># Modify the table width to 100% (which</span>
+<span class='co'># spans the entire content width area)</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_options</span>(
+    <span class='kw'>table.width</span> <span class='kw'>=</span> <span class='fu'><a href='pct.html'>pct</a></span>(<span class='fl'>100</span>)
+  )
+
+<span class='co'># Modify the table's background color</span>
+<span class='co'># to be "lightcyan"</span>
+<span class='no'>tab_3</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_options</span>(
+    <span class='kw'>table.background.color</span> <span class='kw'>=</span> <span class='st'>"lightcyan"</span>
+  )
+
+<span class='co'># Use letters as the marks for footnote</span>
+<span class='co'># references; also, separate footnotes in</span>
+<span class='co'># the footer by spaces instead of newlines</span>
+<span class='no'>tab_4</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_options</span>(
+    <span class='kw'>footnotes.sep</span> <span class='kw'>=</span> <span class='st'>" "</span>,
+    <span class='kw'>footnotes.marks</span> <span class='kw'>=</span> <span class='no'>letters</span>
+  )
+
+<span class='co'># Change the padding of data rows to 5px</span>
+<span class='no'>tab_5</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_options</span>(
+    <span class='kw'>data_row.padding</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>5</span>)
+  )
+
+<span class='co'># Reduce the size of the title and the</span>
+<span class='co'># subtitle text</span>
+<span class='no'>tab_6</span> <span class='kw'>&lt;-</span>
+  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_options</span>(
+    <span class='kw'>heading.title.font.size</span> <span class='kw'>=</span> <span class='st'>"small"</span>,
+    <span class='kw'>heading.subtitle.font.size</span> <span class='kw'>=</span> <span class='st'>"small"</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/tab_row_group.html b/docs/reference/tab_row_group.html
new file mode 100644
index 000000000..ab4c0bbc6
--- /dev/null
+++ b/docs/reference/tab_row_group.html
@@ -0,0 +1,273 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<title>Add a row group to a <strong>gt</strong> table — tab_row_group • gt</title>
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+<meta property="og:description" content="Create a row group with a collection of rows. This requires specification of
+the rows to be included, either by supplying row labels, row indices, or
+through use of a select helper function like starts_with()." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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+    </li>
+    <li class="dropdown-header">Case Studies</li>
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+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+
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+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add a row group to a <strong>gt</strong> table</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_row_group.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Create a row group with a collection of rows. This requires specification of
+the rows to be included, either by supplying row labels, row indices, or
+through use of a select helper function like <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_row_group</span>(<span class='no'>data</span>, <span class='kw'>group</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>others</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>group</th>
+      <td><p>The name of the row group. This text will also serve as the row
+group label.</p></td>
+    </tr>
+    <tr>
+      <th>rows</th>
+      <td><p>The rows to be made components of the row group. Can either be a
+vector of row captions provided in <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a
+helper function focused on selections. The select helper functions are:
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and
+<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>others</th>
+      <td><p>An option to set a default row group label for any rows not
+formally placed in a row group named by <code>group</code> in any call of
+<code>tab_row_group()</code>. A separate call to <code>tab_row_group()</code> with only a value
+to <code>others</code> is possible and makes explicit that the call is meant to
+provide a default row group label. If this is not set and there are rows
+that haven't been placed into a row group (where one or more row groups
+already exist), those rows will be automatically placed into a row group
+without a label.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_row_group_1.png' width=100% /></p>
+<p><img src='figures/man_tab_row_group_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table and</span>
+<span class='co'># add two row groups with the labels:</span>
+<span class='co'># `numbered` and `NA` (a group without</span>
+<span class='co'># a title, or, the rest)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_row_group</span>(
+    <span class='kw'>group</span> <span class='kw'>=</span> <span class='st'>"numbered"</span>,
+    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches</a></span>(<span class='st'>"^[0-9]"</span>)
+  )
+
+<span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># add two row groups with the labels</span>
+<span class='co'># `powerful` and `super powerful`: the</span>
+<span class='co'># distinction being `hp` lesser or</span>
+<span class='co'># greater than `600`</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_row_group</span>(
+    <span class='kw'>group</span> <span class='kw'>=</span> <span class='st'>"powerful"</span>,
+    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>hp</span> <span class='kw'>&lt;=</span> <span class='fl'>600</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_row_group</span>(
+    <span class='kw'>group</span> <span class='kw'>=</span> <span class='st'>"super powerful"</span>,
+    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>hp</span> <span class='kw'>&gt;</span> <span class='fl'>600</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/tab_source_note.html b/docs/reference/tab_source_note.html
new file mode 100644
index 000000000..14f3fc6cc
--- /dev/null
+++ b/docs/reference/tab_source_note.html
@@ -0,0 +1,237 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Add a source note citation — tab_source_note • gt</title>
+
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+
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+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="../pkgdown.css" rel="stylesheet">
+<script src="../pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Add a source note citation — tab_source_note" />
+<meta property="og:description" content="Add a source note to the footer part of the gt table. A source note is
+useful for citing the data included in the table. Several can be added to the
+footer, simply use multiple calls of tab_source_note() and they will be
+inserted in the order provided. We can use Markdown formatting for the note,
+or, if the table is intended for HTML output, we can include HTML formatting." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
+<!--[if lt IE 9]>
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+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
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+
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+    Articles
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+    <li class="dropdown-header">How to Use</li>
+    <li>
+      <a href="../articles/gt-datasets.html">gt Datasets</a>
+    </li>
+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
+      <ul class="nav navbar-nav navbar-right">
+        <li>
+  <a href="https://github.com/rstudio/gt">
+    <span class="fa fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add a source note citation</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_source_note.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Add a source note to the footer part of the <strong>gt</strong> table. A source note is
+useful for citing the data included in the table. Several can be added to the
+footer, simply use multiple calls of <code>tab_source_note()</code> and they will be
+inserted in the order provided. We can use Markdown formatting for the note,
+or, if the table is intended for HTML output, we can include HTML formatting.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_source_note</span>(<span class='no'>data</span>, <span class='no'>source_note</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>source_note</th>
+      <td><p>Text to be used in the source note. We can optionally use
+the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> functions to style the text as Markdown or to
+retain HTML elements in the text.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_source_note_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-7</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># add a source note to the table</span>
+<span class='co'># footer that cites the data source</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_source_note</span>(
+    <span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"From edmunds.com"</span>
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/tab_spanner.html b/docs/reference/tab_spanner.html
new file mode 100644
index 000000000..57ba4af1e
--- /dev/null
+++ b/docs/reference/tab_spanner.html
@@ -0,0 +1,248 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Add a spanner column label — tab_spanner • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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+
+<!-- jquery -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+<!-- Bootstrap -->
+
+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" />
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
+<!-- clipboard.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
+
+<!-- headroom.js -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
+
+<!-- pkgdown -->
+<link href="../pkgdown.css" rel="stylesheet">
+<script src="../pkgdown.js"></script>
+
+
+
+
+<meta property="og:title" content="Add a spanner column label — tab_spanner" />
+<meta property="og:description" content="Set a spanner column label by mapping it to columns already in the table.
+This label is placed above one or more column labels, spanning the width of
+those columns and column labels." />
+<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
+
+
+
+
+<!-- mathjax -->
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
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+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+
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+    <div class="container template-reference-topic">
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+        <a class="navbar-link" href="../index.html">gt</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav">
+        <li>
+  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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+  <a href="../reference/index.html">Reference</a>
+</li>
+<li class="dropdown">
+  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
+    Articles
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+      <a href="../articles/gt-datasets.html">gt Datasets</a>
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+    <li>
+      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
+    </li>
+    <li class="dropdown-header">Case Studies</li>
+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
+    </li>
+  </ul>
+</li>
+<li>
+  <a href="../news/index.html">News</a>
+</li>
+      </ul>
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+  <a href="https://github.com/rstudio/gt">
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+     
+  </a>
+</li>
+      </ul>
+      
+    </div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add a spanner column label</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_spanner.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Set a spanner column label by mapping it to columns already in the table.
+This label is placed above one or more column labels, spanning the width of
+those columns and column labels.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_spanner</span>(<span class='no'>data</span>, <span class='no'>label</span>, <span class='no'>columns</span>, <span class='kw'>gather</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>label</th>
+      <td><p>The text to use for the spanner column label.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>The columns to be components of the spanner heading.</p></td>
+    </tr>
+    <tr>
+      <th>gather</th>
+      <td><p>An option to move the specified <code>columns</code> such that they are
+unified under the spanner column label. Ordering of the moved-into-place
+columns will be preserved in all cases.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_spanner_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-2</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
+<span class='co'># Group several columns related to car</span>
+<span class='co'># performance under a spanner column</span>
+<span class='co'># with the label `performance`</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
+    -<span class='no'>mfr</span>, -<span class='no'>trim</span>, <span class='no'>bdy_style</span>, <span class='no'>drivetrain</span>,
+    -<span class='no'>drivetrain</span>, -<span class='no'>trsmn</span>, -<span class='no'>ctry_origin</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_spanner</span>(
+    <span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"performance"</span>,
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(
+      <span class='no'>hp</span>, <span class='no'>hp_rpm</span>, <span class='no'>trq</span>, <span class='no'>trq_rpm</span>,
+      <span class='no'>mpg_c</span>, <span class='no'>mpg_h</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
+      <h2 data-toc-skip>Contents</h2>
+    </nav>
+  </div>
+</div>
+
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
+</div>
+
+      </footer>
+   </div>
+
+  
+
+
+  </body>
+</html>
+
+
diff --git a/docs/reference/tab_spanner_delim.html b/docs/reference/tab_spanner_delim.html
new file mode 100644
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+<meta property="og:description" content="This function will split selected delimited column names such that the first
+components (LHS) are promoted to being spanner column labels, and the
+secondary components (RHS) will become the column labels. Please note that
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+    <h1>Create column labels and spanners via delimited names</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_spanner_delim.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>This function will split selected delimited column names such that the first
+components (LHS) are promoted to being spanner column labels, and the
+secondary components (RHS) will become the column labels. Please note that
+reference to individual columns must continue to be the column names from the
+input table data (which are unique by necessity).</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_spanner_delim</span>(<span class='no'>data</span>, <span class='no'>delim</span>, <span class='kw'>columns</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>gather</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>delim</th>
+      <td><p>The delimiter to use to split an input column name. The
+delimiter supplied will be autoescaped for the internal splitting
+procedure. The first component of the split will become the group name and
+the second component will be the column label.</p></td>
+    </tr>
+    <tr>
+      <th>columns</th>
+      <td><p>An optional vector of column names that this operation should
+be limited to. The default is to consider all columns in the table.</p></td>
+    </tr>
+    <tr>
+      <th>gather</th>
+      <td><p>An option to move the specified <code>columns</code> such that they are
+unified under the spanner column label. Ordering of the moved-into-place
+columns will be preserved in all cases.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>If we look to the column names in the <code>iris</code> dataset as an example of how
+<code>tab_spanner_delim()</code> might be useful, we find the names <code>Sepal.Length</code>,
+<code>Sepal.Width</code>, <code>Petal.Length</code>, <code>Petal.Width</code>. From this naming system, it's
+easy to see that the <code>Sepal</code> and <code>Petal</code> can group together the repeated
+common <code>Length</code> and <code>Width</code> values. In your own datasets, we can avoid a
+lengthy relabeling with <code><a href='cols_label.html'>cols_label()</a></code> if column names can be fashioned
+beforehand to contain both the spanner column label and the column label. An
+additional advantage is that the column names in the input table data remain
+unique even though there may eventually be repeated column labels in the
+rendered output table).</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_spanner_delim_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-3</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `iris` to create a gt table; split</span>
+<span class='co'># any columns that are dot-separated</span>
+<span class='co'># between column spanner labels (first</span>
+<span class='co'># part) and column labels (second part)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>iris</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>Species</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>4</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_spanner_delim</span>(<span class='kw'>delim</span> <span class='kw'>=</span> <span class='st'>"."</span>)</div></pre>
+  </div>
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diff --git a/docs/reference/tab_stubhead.html b/docs/reference/tab_stubhead.html
new file mode 100644
index 000000000..29000bd03
--- /dev/null
+++ b/docs/reference/tab_stubhead.html
@@ -0,0 +1,237 @@
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+<meta property="og:description" content="Add a label to the stubhead of a gt table. The stubhead is the lone
+element that is positioned left of the column labels, and above the stub. If
+a stub does not exist, then there is no stubhead (so no change will be made
+when using this function in that case). We have the flexibility to use
+Markdown formatting for the stubhead label. Furthermore, if the table is
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+    <div class="page-header">
+    <h1>Add label text to the stubhead</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_stubhead.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Add a label to the stubhead of a <strong>gt</strong> table. The stubhead is the lone
+element that is positioned left of the column labels, and above the stub. If
+a stub does not exist, then there is no stubhead (so no change will be made
+when using this function in that case). We have the flexibility to use
+Markdown formatting for the stubhead label. Furthermore, if the table is
+intended for HTML output, we can use HTML for the stubhead label.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_stubhead</span>(<span class='no'>data</span>, <span class='no'>label</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>label</th>
+      <td><p>The text to be used as the stubhead label We can optionally use
+the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> functions to style the text as Markdown or to
+retain HTML elements in the text.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_stubhead_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-5</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table; add</span>
+<span class='co'># a stubhead label to describe what is</span>
+<span class='co'># in the stub</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_stubhead</span>(<span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"car"</span>)</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/tab_style.html b/docs/reference/tab_style.html
new file mode 100644
index 000000000..6a08cbe73
--- /dev/null
+++ b/docs/reference/tab_style.html
@@ -0,0 +1,324 @@
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
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+<meta property="og:title" content="Add custom styles to one or more cells — tab_style" />
+<meta property="og:description" content="With the tab_style() function we can target specific cells and apply styles
+to them. This is best done in conjunction with the helper functions
+cell_text(), cell_fill(), and cell_borders(). At present this function
+is focused on the application of styles for HTML output only (as such, other
+output formats will ignore all tab_style() calls). Using the aforementioned
+helper functions, here are some of the styles we can apply:
+the background color of the cell (cell_fill(): color)
+the cell's text color, font, and size (cell_text(): color, font,
+size)
+the text style (cell_text(): style), enabling the use of italics or
+oblique text.
+the text weight (cell_text(): weight), allowing the use of thin to
+bold text (the degree of choice is greater with variable fonts)
+the alignment and indentation of text (cell_text(): align and
+indent)
+the cell borders (cell_borders())
+
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
+
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+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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+    <li>
+      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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+</div><!--/.navbar -->
+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Add custom styles to one or more cells</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
+    <div class="hidden name"><code>tab_style.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>With the <code>tab_style()</code> function we can target specific cells and apply styles
+to them. This is best done in conjunction with the helper functions
+<code><a href='cell_text.html'>cell_text()</a></code>, <code><a href='cell_fill.html'>cell_fill()</a></code>, and <code><a href='cell_borders.html'>cell_borders()</a></code>. At present this function
+is focused on the application of styles for HTML output only (as such, other
+output formats will ignore all <code>tab_style()</code> calls). Using the aforementioned
+helper functions, here are some of the styles we can apply:</p><ul>
+<li><p>the background color of the cell (<code><a href='cell_fill.html'>cell_fill()</a></code>: <code>color</code>)</p></li>
+<li><p>the cell's text color, font, and size (<code><a href='cell_text.html'>cell_text()</a></code>: <code>color</code>, <code>font</code>,
+<code>size</code>)</p></li>
+<li><p>the text style (<code><a href='cell_text.html'>cell_text()</a></code>: <code>style</code>), enabling the use of italics or
+oblique text.</p></li>
+<li><p>the text weight (<code><a href='cell_text.html'>cell_text()</a></code>: <code>weight</code>), allowing the use of thin to
+bold text (the degree of choice is greater with variable fonts)</p></li>
+<li><p>the alignment and indentation of text (<code><a href='cell_text.html'>cell_text()</a></code>: <code>align</code> and
+<code>indent</code>)</p></li>
+<li><p>the cell borders (<code><a href='cell_borders.html'>cell_borders()</a></code>)</p></li>
+</ul>
+
+    </div>
+
+    <pre class="usage"><span class='fu'>tab_style</span>(<span class='no'>data</span>, <span class='no'>style</span>, <span class='no'>locations</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>style</th>
+      <td><p>a vector of styles to use. The <code><a href='cell_text.html'>cell_text()</a></code>, <code><a href='cell_fill.html'>cell_fill()</a></code>, and
+<code><a href='cell_borders.html'>cell_borders()</a></code> helper functions can be used here to more easily generate
+valid styles. If using more than one helper function to define styles, all
+calls must be enclosed in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>.</p></td>
+    </tr>
+    <tr>
+      <th>locations</th>
+      <td><p>the cell or set of cells to be associated with the style.
+Supplying any of the <code>cells_*()</code> helper functions is a useful way to target
+the location cells that are associated with the styling. These helper
+functions are: <code><a href='cells_title.html'>cells_title()</a></code>, <code><a href='cells_stubhead.html'>cells_stubhead()</a></code>,
+<code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>, <code><a href='cells_column_labels.html'>cells_column_labels()</a></code>, <code><a href='cells_row_groups.html'>cells_row_groups()</a></code>,
+<code><a href='cells_stub.html'>cells_stub()</a></code>, <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_summary.html'>cells_summary()</a></code>, and
+<code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>. Additionally, we can enclose several <code>cells_*()</code>
+calls within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code> if we wish to apply styling to different types of
+locations (e.g., body cells, row group labels, the table title, etc.).</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_tab_style_1.png' width=100% /></p>
+<p><img src='figures/man_tab_style_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>2-8</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p><code><a href='cell_text.html'>cell_text()</a></code>, <code><a href='cell_fill.html'>cell_fill()</a></code>, and <code><a href='cell_borders.html'>cell_borders()</a></code> as helpers for
+defining custom styles and <code><a href='cells_body.html'>cells_body()</a></code> as one of many useful helper
+functions for targeting the locations to be styled.</p>
+<p>Other Create or Modify Parts: 
+<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
+<code><a href='tab_header.html'>tab_header</a>()</code>,
+<code><a href='tab_options.html'>tab_options</a>()</code>,
+<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
+<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
+<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
+<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
+<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># add styles that are to be applied</span>
+<span class='co'># to data cells that satisfy a</span>
+<span class='co'># condition (using `tab_style()`)</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
+    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
+    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_style</span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightcyan"</span>),
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>weight</span> <span class='kw'>=</span> <span class='st'>"bold"</span>)
+      ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;=</span> <span class='fl'>5000</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_style</span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#F9E3D6"</span>),
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>)
+      ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&lt;</span> <span class='fl'>100</span>)
+  )
+
+<span class='co'># Use `sp500` to create a gt table;</span>
+<span class='co'># color entire rows of cells based</span>
+<span class='co'># on values in a particular column</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
+    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-12-01"</span> <span class='kw'>&amp;</span>
+    <span class='no'>date</span> <span class='kw'>&lt;=</span> <span class='st'>"2015-12-15"</span>
+  ) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='no'>adj_close</span>, <span class='no'>volume</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_style</span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightgreen"</span>),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>close</span> <span class='kw'>&gt;</span> <span class='no'>open</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'>tab_style</span>(
+    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
+      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"red"</span>),
+      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"white"</span>)
+      ),
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>open</span> <span class='kw'>&gt;</span> <span class='no'>close</span>)
+  )</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/test_image.html b/docs/reference/test_image.html
new file mode 100644
index 000000000..2b5951f0f
--- /dev/null
+++ b/docs/reference/test_image.html
@@ -0,0 +1,208 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+  <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+
+<title>Generate a path to a test image — test_image • gt</title>
+
+<!-- favicons -->
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+
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+<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
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+<meta property="og:description" content="Two test images are available within the gt package. Both contain the
+same imagery (sized at 200px by 200px) but one is a PNG file while the other
+is an SVG file. This function is most useful when paired with local_image()
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+
+      
+
+      </header>
+
+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Generate a path to a test image</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
+    <div class="hidden name"><code>test_image.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Two test images are available within the <strong>gt</strong> package. Both contain the
+same imagery (sized at 200px by 200px) but one is a PNG file while the other
+is an SVG file. This function is most useful when paired with <code><a href='local_image.html'>local_image()</a></code>
+since we test various sizes of the test image within that function.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>test_image</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"png"</span>, <span class='st'>"svg"</span>))</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>type</th>
+      <td><p>The type of the image, which can either be <code>png</code> (the default) or
+<code>svg</code>.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character vector with a single path to an image file.</p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>8-4</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Image Addition Functions: 
+<code><a href='ggplot_image.html'>ggplot_image</a>()</code>,
+<code><a href='local_image.html'>local_image</a>()</code>,
+<code><a href='web_image.html'>web_image</a>()</code></p></div>
+
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top">
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+    </nav>
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+</div>
+
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diff --git a/docs/reference/text_transform.html b/docs/reference/text_transform.html
new file mode 100644
index 000000000..6b8e1b7fe
--- /dev/null
+++ b/docs/reference/text_transform.html
@@ -0,0 +1,253 @@
+<!-- Generated by pkgdown: do not edit by hand -->
+<!DOCTYPE html>
+<html lang="en">
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+
+<title>Perform targeted text transformation with a function — text_transform • gt</title>
+
+<!-- favicons -->
+<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png" />
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+
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+<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
+
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+
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+
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+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Perform targeted text transformation with a function</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/text_transform.R'><code>R/text_transform.R</code></a></small>
+    <div class="hidden name"><code>text_transform.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Perform targeted text transformation with a function</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>text_transform</span>(<span class='no'>data</span>, <span class='no'>locations</span>, <span class='no'>fn</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>data</th>
+      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
+    </tr>
+    <tr>
+      <th>locations</th>
+      <td><p>The cell or set of cells to be associated with the text
+transformation. Only the <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_stub.html'>cells_stub()</a></code>, and
+<code><a href='cells_column_labels.html'>cells_column_labels()</a></code> helper functions can be used here. We can enclose
+several of these calls within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code> if we wish to make the
+transformation happen at different locations.</p></td>
+    </tr>
+    <tr>
+      <th>fn</th>
+      <td><p>The function to use for text transformation.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>An object of class <code>gt_tbl</code>.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_text_transform_1.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>3-12</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Format Data: 
+<code><a href='data_color.html'>data_color</a>()</code>,
+<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
+<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
+<code><a href='fmt_date.html'>fmt_date</a>()</code>,
+<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
+<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
+<code><a href='fmt_number.html'>fmt_number</a>()</code>,
+<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
+<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
+<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
+<code><a href='fmt_time.html'>fmt_time</a>()</code>,
+<code><a href='fmt.html'>fmt</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
+<span class='co'># transform the formatted text in the</span>
+<span class='co'># `num` and `currency` columns using</span>
+<span class='co'># a function within `text_transform()`,</span>
+<span class='co'># where `x` is a formatted vector of</span>
+<span class='co'># column values</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>char</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>4</span>) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='fmt_currency.html'>fmt_currency</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>)) <span class='kw'>%&gt;%</span>
+  <span class='fu'>text_transform</span>(
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
+      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)),
+    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
+      <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
+        <span class='no'>x</span>, <span class='st'>" ("</span>,
+        <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/case_when.html'>case_when</a></span>(
+          <span class='no'>x</span> <span class='kw'>&gt;</span> <span class='fl'>20</span>   ~ <span class='st'>"large"</span>,
+          <span class='no'>x</span> <span class='kw'>&lt;=</span> <span class='fl'>20</span>  ~ <span class='st'>"small"</span>),
+        <span class='st'>")"</span>)
+    }
+  )</div></pre>
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+<meta property="og:title" content="Helper function for adding an image from the web — web_image" />
+<meta property="og:description" content="We can flexibly add a web image inside of a table with web_image()
+function. The function provides a convenient way to generate an HTML fragment
+with an image URL. Because this function is currently HTML-based, it is only
+useful for HTML table output. To use this function inside of data cells, it
+is recommended that the text_transform() function is used. With that
+function, we can specify which data cells to target and then include a
+web_image() call within the required user-defined function (for the fn
+argument). If we want to include an image in other places (e.g., in the
+header, within footnote text, etc.) we need to use web_image() within the
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+<div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Helper function for adding an image from the web</h1>
+    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
+    <div class="hidden name"><code>web_image.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>We can flexibly add a web image inside of a table with <code>web_image()</code>
+function. The function provides a convenient way to generate an HTML fragment
+with an image URL. Because this function is currently HTML-based, it is only
+useful for HTML table output. To use this function inside of data cells, it
+is recommended that the <code><a href='text_transform.html'>text_transform()</a></code> function is used. With that
+function, we can specify which data cells to target and then include a
+<code>web_image()</code> call within the required user-defined function (for the <code>fn</code>
+argument). If we want to include an image in other places (e.g., in the
+header, within footnote text, etc.) we need to use <code>web_image()</code> within the
+<code><a href='html.html'>html()</a></code> helper function.</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>web_image</span>(<span class='no'>url</span>, <span class='kw'>height</span> <span class='kw'>=</span> <span class='fl'>30</span>)</pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>url</th>
+      <td><p>A url that resolves to an image file.</p></td>
+    </tr>
+    <tr>
+      <th>height</th>
+      <td><p>The absolute height (px) of the image in the table cell.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>A character object with an HTML fragment that can be placed inside of
+a cell.</p>
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>By itself, the function creates an HTML image tag, so, the call
+<code>web_image("http://some.web.site/image.png")</code> evaluates to:</p>
+<p><code>&lt;img src=\"http://some.web.site/image.png\" style=\"height:30px;\"&gt;</code></p>
+<p>where a height of <code>30px</code> is a default height chosen to work well within the
+heights of most table rows.</p>
+    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
+
+    
+
+<p><img src='figures/man_web_image_1.png' width=100% /></p>
+<p><img src='figures/man_web_image_2.png' width=100% /></p>
+    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
+
+    
+
+<p>8-1</p>
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <div class='dont-index'><p>Other Image Addition Functions: 
+<code><a href='ggplot_image.html'>ggplot_image</a>()</code>,
+<code><a href='local_image.html'>local_image</a>()</code>,
+<code><a href='test_image.html'>test_image</a>()</code></p></div>
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Get the PNG-based logo for the R</span>
+<span class='co'># Project from an image URL</span>
+<span class='no'>r_png_url</span> <span class='kw'>&lt;-</span>
+  <span class='st'>"https://www.r-project.org/logo/Rlogo.png"</span>
+
+<span class='co'># Create a tibble that contains heights</span>
+<span class='co'># of an image in pixels (one column as a</span>
+<span class='co'># string, the other as numerical values),</span>
+<span class='co'># then, create a gt table; use the</span>
+<span class='co'># `text_transform()` function to insert</span>
+<span class='co'># the R logo PNG image with the various</span>
+<span class='co'># sizes</span>
+<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
+    <span class='kw'>pixels</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)),
+    <span class='kw'>image</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='text_transform.html'>text_transform</a></span>(
+    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>image</span>)),
+    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
+      <span class='fu'>web_image</span>(
+        <span class='kw'>url</span> <span class='kw'>=</span> <span class='no'>r_png_url</span>,
+        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='no'>x</span>)
+      )
+    }
+  )
+
+<span class='co'># Get the SVG-based logo for the R</span>
+<span class='co'># Project from an image URL</span>
+<span class='no'>r_svg_url</span> <span class='kw'>&lt;-</span>
+  <span class='st'>"https://www.r-project.org/logo/Rlogo.svg"</span>
+
+<span class='co'># Create a tibble that contains heights</span>
+<span class='co'># of an image in pixels (one column as a</span>
+<span class='co'># string, the other as numerical values),</span>
+<span class='co'># then, create a gt table; use the</span>
+<span class='co'># `tab_header()` function to insert</span>
+<span class='co'># the R logo SVG image once in the title</span>
+<span class='co'># and five times in the subtitle</span>
+<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
+  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
+    <span class='kw'>pixels</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)),
+    <span class='kw'>image</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)
+  ) <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
+  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
+    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='html.html'>html</a></span>(
+      <span class='st'>"&lt;strong&gt;R Logo&lt;/strong&gt;"</span>,
+      <span class='fu'>web_image</span>(
+        <span class='kw'>url</span> <span class='kw'>=</span> <span class='no'>r_svg_url</span>,
+        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>50</span>)
+      )
+    ),
+    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='html.html'>html</a></span>(
+      <span class='fu'>web_image</span>(
+        <span class='kw'>url</span> <span class='kw'>=</span> <span class='no'>r_svg_url</span>,
+        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>12</span>)
+      ) <span class='kw'>%&gt;%</span>
+        <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='fl'>5</span>)
+    )
+  )</div></pre>
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+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_align.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_hide.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_label.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_merge.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_merge_range.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_merge_uncert.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_move.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_move_to_end.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_move_to_start.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/cols_width.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/countrypops.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/currency.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/data_color.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/escape_latex.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/exibble.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/extract_summary.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_currency.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_date.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_datetime.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_markdown.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_missing.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_number.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_passthrough.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_percent.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_scientific.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/fmt_time.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/ggplot_image.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/grand_summary_rows.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gt-options.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gt-package.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gt.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gt_latex_dependencies.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gt_output.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gt_preview.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gtcars.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/gtsave.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/html.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/info_currencies.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/info_date_style.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/info_locales.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/info_paletteer.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/info_time_style.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/local_image.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/md.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/opt_align_table_header.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/opt_all_caps.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/opt_footnote_marks.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/opt_row_striping.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/opt_table_lines.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/opt_table_outline.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/pct.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/pipe.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/pizzaplace.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/print.gt_tbl.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/px.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/random_id.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/reexports.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/render_gt.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/row_group_order.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/sp500.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/summary_rows.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/sza.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_footnote.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_header.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_options.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_row_group.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_source_note.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_spanner.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_spanner_delim.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_stubhead.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/tab_style.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/test_image.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/text_transform.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/reference/web_image.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/articles/case-study-gtcars.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/articles/creating-summary-lines.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/articles/gt-datasets.html</loc>
+  </url>
+  <url>
+    <loc>https://gt.rstudio.com/articles/intro-creating-gt-tables.html</loc>
+  </url>
+</urlset>
diff --git a/man/gt_output.Rd b/man/gt_output.Rd
index 06ba97dd2..83b1e4454 100644
--- a/man/gt_output.Rd
+++ b/man/gt_output.Rd
@@ -62,8 +62,8 @@ server <- function(input,
     )
 }
 
-\donttest{
-shinyApp(ui, server)
+if (interactive()) {
+  shinyApp(ui, server)
 }
 
 }
diff --git a/man/gtsave.Rd b/man/gtsave.Rd
index de7ebf11d..31447e574 100644
--- a/man/gtsave.Rd
+++ b/man/gtsave.Rd
@@ -58,7 +58,6 @@ to \code{...}.
 }
 
 \examples{
-\donttest{
 # Use `gtcars` to create a gt table; add
 # a stubhead label to describe what is
 # in the stub
@@ -98,7 +97,6 @@ tab_1 \%>\%
 # document
 tab_1 \%>\%
   gtsave("tab_1.tex", path = tempdir())
-}
 
 }
 \seealso{
diff --git a/man/render_gt.Rd b/man/render_gt.Rd
index 88417db00..da30a5280 100644
--- a/man/render_gt.Rd
+++ b/man/render_gt.Rd
@@ -91,8 +91,8 @@ server <- function(input,
     )
 }
 
-\donttest{
-shinyApp(ui, server)
+if (interactive()) {
+  shinyApp(ui, server)
 }
 
 }

From e19c7324bdd31aaed8d1cb1b5b5b57168e059b35 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 3 Apr 2020 16:20:01 -0400
Subject: [PATCH 07/30] Add \dontrun{} around `gtsave()` examples (#527)

* Add \dontrun{} around `gtsave()` examples

* Use `wait = TRUE` in `webshot()` call

* Use `\donttest()` instead of `\dontrun()`
---
 R/export.R    | 3 +++
 man/gtsave.Rd | 2 ++
 2 files changed, 5 insertions(+)

diff --git a/R/export.R b/R/export.R
index 535501b03..95ab41325 100644
--- a/R/export.R
+++ b/R/export.R
@@ -41,6 +41,7 @@
 #'   function.
 #'
 #' @examples
+#' \donttest{
 #' # Use `gtcars` to create a gt table; add
 #' # a stubhead label to describe what is
 #' # in the stub
@@ -80,6 +81,7 @@
 #' # document
 #' tab_1 %>%
 #'   gtsave("tab_1.tex", path = tempdir())
+#' }
 #'
 #' @family Export Functions
 #' @section Function ID:
@@ -200,6 +202,7 @@ gt_save_webshot <- function(data,
       selector = "table",
       zoom = zoom,
       expand = expand,
+      wait = TRUE,
       ...
     )
   }
diff --git a/man/gtsave.Rd b/man/gtsave.Rd
index 31447e574..c125530db 100644
--- a/man/gtsave.Rd
+++ b/man/gtsave.Rd
@@ -58,6 +58,7 @@ to \code{...}.
 }
 
 \examples{
+\dontrun{
 # Use `gtcars` to create a gt table; add
 # a stubhead label to describe what is
 # in the stub
@@ -97,6 +98,7 @@ tab_1 \%>\%
 # document
 tab_1 \%>\%
   gtsave("tab_1.tex", path = tempdir())
+}
 
 }
 \seealso{

From 86aa190069ff6835dd654c6faba03b355aff617f Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Wed, 15 Apr 2020 16:54:37 -0400
Subject: [PATCH 08/30] Remove `wait = TRUE` from `webshot()` call (#544)

---
 R/export.R | 1 -
 1 file changed, 1 deletion(-)

diff --git a/R/export.R b/R/export.R
index 95ab41325..f218e7b76 100644
--- a/R/export.R
+++ b/R/export.R
@@ -202,7 +202,6 @@ gt_save_webshot <- function(data,
       selector = "table",
       zoom = zoom,
       expand = expand,
-      wait = TRUE,
       ...
     )
   }

From 4c51fbb3331c62177e8f5d93356ed74ba05fa748 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Thu, 16 Apr 2020 15:08:22 -0400
Subject: [PATCH 09/30] Use GitHub Actions (#550)

* Add YAML files for github workflows

* Remove Travis and Appveyor YAML files

* Update README
---
 .github/workflows/R-CMD-check.yaml | 84 ++++++++++++++++++++++++++++++
 .github/workflows/pkgdown.yaml     | 42 +++++++++++++++
 .travis.yml                        | 57 --------------------
 README.Rmd                         | 25 ++++++---
 README.md                          | 23 +++++---
 appveyor.yml                       | 54 -------------------
 6 files changed, 160 insertions(+), 125 deletions(-)
 create mode 100644 .github/workflows/R-CMD-check.yaml
 create mode 100644 .github/workflows/pkgdown.yaml
 delete mode 100644 .travis.yml
 delete mode 100644 appveyor.yml

diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
new file mode 100644
index 000000000..a619c788b
--- /dev/null
+++ b/.github/workflows/R-CMD-check.yaml
@@ -0,0 +1,84 @@
+on:
+  push:
+    branches:
+      - master
+  pull_request:
+    branches:
+      - master
+
+name: R-CMD-check
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: windows-latest, r: '3.6'}
+          - {os: macOS-latest, r: '3.6'}
+          - {os: ubuntu-16.04, r: '3.4', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04, r: '3.5', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04, r: '3.6', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
+
+    env:
+      R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
+      _R_CHECK_FORCE_SUGGESTS_: false
+      RSPM: ${{ matrix.config.rspm }}
+
+    steps:
+      - uses: actions/checkout@v2
+
+      - uses: r-lib/actions/setup-r@master
+        with:
+          r-version: ${{ matrix.config.r }}
+
+      - uses: r-lib/actions/setup-pandoc@master
+
+      - name: Query dependencies
+        run: |
+          install.packages('remotes')
+          saveRDS(remotes::dev_package_deps(dependencies = TRUE), "depends.Rds", version = 2)
+        shell: Rscript {0}
+
+      - name: Cache R packages
+        if: runner.os != 'Windows'
+        uses: actions/cache@v1
+        with:
+          path: ${{ env.R_LIBS_USER }}
+          key: ${{ runner.os }}-r-${{ matrix.config.r }}-${{ hashFiles('depends.Rds') }}
+          restore-keys: ${{ runner.os }}-r-${{ matrix.config.r }}-
+
+      - name: Install system dependencies
+        if: runner.os == 'Linux'
+        env:
+          RHUB_PLATFORM: linux-x86_64-ubuntu-gcc
+        run: |
+          Rscript -e "remotes::install_github('r-hub/sysreqs')"
+          sysreqs=$(Rscript -e "cat(sysreqs::sysreq_commands('DESCRIPTION'))")
+          sudo -s eval "$sysreqs"
+
+      - name: Install dependencies
+        run: |
+          remotes::install_deps(dependencies = TRUE)
+          remotes::install_cran("rcmdcheck")
+        shell: Rscript {0}
+
+      - name: Check
+        run: rcmdcheck::rcmdcheck(args = "--no-manual", error_on = "warning", check_dir = "check")
+        shell: Rscript {0}
+
+      - name: Upload check results
+        if: failure()
+        uses: actions/upload-artifact@master
+        with:
+          name: ${{ runner.os }}-r${{ matrix.config.r }}-results
+          path: check
+
+      - name: Test coverage
+        if: matrix.config.os == 'macOS-latest' && matrix.config.r == '3.6'
+        run: covr::codecov()
+        shell: Rscript {0}
diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml
new file mode 100644
index 000000000..0ec9d2862
--- /dev/null
+++ b/.github/workflows/pkgdown.yaml
@@ -0,0 +1,42 @@
+on:
+  push:
+    branches: master
+
+name: pkgdown
+
+jobs:
+  pkgdown:
+    runs-on: macOS-latest
+    steps:
+      - uses: actions/checkout@v2
+
+      - uses: r-lib/actions/setup-r@master
+
+      - uses: r-lib/actions/setup-pandoc@master
+
+      - name: Query dependencies
+        run: |
+          install.packages('remotes')
+          saveRDS(remotes::dev_package_deps(dependencies = TRUE), "depends.Rds", version = 2)
+        shell: Rscript {0}
+
+      - name: Cache R packages
+        uses: actions/cache@v1
+        with:
+          path: ${{ env.R_LIBS_USER }}
+          key: macOS-r-3.6-${{ hashFiles('depends.Rds') }}
+          restore-keys: macOS-r-3.6-
+
+      - name: Install dependencies
+        run: |
+          install.packages("remotes")
+          remotes::install_deps(dependencies = TRUE)
+          remotes::install_dev("pkgdown")
+        shell: Rscript {0}
+
+      - name: Install package
+        run: R CMD INSTALL .
+
+      - name: Deploy package
+        run: pkgdown::deploy_to_branch(new_process = FALSE)
+        shell: Rscript {0}
diff --git a/.travis.yml b/.travis.yml
deleted file mode 100644
index a14fc2a44..000000000
--- a/.travis.yml
+++ /dev/null
@@ -1,57 +0,0 @@
-# R for travis: documentation at https://docs.travis-ci.com/user/languages/r
-
-language: R
-sudo: false
-cache:
-  packages: true
-warnings_are_errors: false
-
-# This library is required for installing the `rgl` pkg dependency
-addons:
-  apt:
-    packages:
-    - libglu1-mesa-dev
-
-r:
-  - oldrel
-  - release
-  - devel
-
-notifications:
-  email:
-    on_success: change
-    on_failure: change
-
-jobs:
-  include:
-    - stage: deploy
-      name: covr
-      r: release
-      cache:
-        packages: false
-      r_binary_packages:
-        - covr
-      script:
-        - Rscript -e "covr::codecov()"
-
-    - stage: deploy
-      name: pkgdown
-      r: release
-      cache:
-        packages: false
-      if: branch IN (master, travis) AND repo = rstudio/gt AND type = push
-      script:
-      - Rscript -e "remotes::install_cran(c('pkgdown', 'devtools'))"
-      - Rscript -e "devtools::install()"
-      - Rscript -e "pkgdown::build_site()"
-      - Rscript -e "remove.packages(devtools::as.package('.')$package)"
-      deploy:
-        provider: pages
-        script: Rscript -e 'devtools::install()'
-        local-dir: docs
-        skip-cleanup: true
-        keep-history: false
-        on:
-          all_branches: true
-        github-token:
-          secure: "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"
diff --git a/README.Rmd b/README.Rmd
index 07a0378d6..0a2400149 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -15,11 +15,16 @@ knitr::opts_chunk$set(
 
 # gt <img src="man/figures/logo.svg" align="right" height="250px" />
 
-[![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
-[![CRAN status](https://www.r-pkg.org/badges/version/gt)](https://cran.r-project.org/package=gt)
-[![Travis build status](https://travis-ci.com/rstudio/gt.svg?token=P7T9dzi5RLEq9j2Yepx5&branch=master)](https://travis-ci.com/rstudio/gt)
-[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/rstudio/gt?branch=master&svg=true)](https://ci.appveyor.com/project/rstudio/gt)
-[![Coverage status](https://codecov.io/gh/rstudio/gt/branch/master/graph/badge.svg)](https://codecov.io/github/rstudio/gt?branch=master)
+<!-- badges: start -->
+[![Lifecycle:
+maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
+[![CRAN
+status](https://www.r-pkg.org/badges/version/gt)](https://cran.r-project.org/package=gt)
+[![R build 
+status](https://github.com/rstudio/gt/workflows/R-CMD-check/badge.svg)](https://github.com/rstudio/gt/actions?workflow=R-CMD-check)
+[![Coverage
+status](https://codecov.io/gh/rstudio/gt/branch/master/graph/badge.svg)](https://codecov.io/github/rstudio/gt?branch=master)
+<!-- badges: end -->
 
 With the **gt** package, anyone can make wonderful-looking tables using the **R** programming language. The **gt** philosophy: we can construct a wide variety of useful tables with a cohesive set of table parts. These include the *table header*, the *stub*, the *column labels* and *spanner column labels*, the *table body*, and the *table footer*.
 
@@ -78,10 +83,16 @@ Want to try this out? Then, take the **gt** Test Drive on **RStudio Cloud**. It'
 </a>
 </p>
 
-You can install the development version of **gt** from **GitHub**:
+The **gt** package can be installed from **CRAN** with:
+
+```{r install_cran, eval=FALSE}
+install.packages("gt")
+```
+
+You can also choose to install the development version of **gt** from **GitHub**:
 
 ```{r install_github, eval=FALSE}
-remotes::install_github("rstudio/gt")
+devtools::install_github("rstudio/gt")
 ```
 
 If you encounter a bug, have usage questions, or want to share ideas to make this package better, please feel free to file an [issue](https://github.com/rstudio/gt/issues).
diff --git a/README.md b/README.md
index e18b6817a..8b87792d1 100644
--- a/README.md
+++ b/README.md
@@ -3,15 +3,17 @@
 
 # gt <img src="man/figures/logo.svg" align="right" height="250px" />
 
-[![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
+<!-- badges: start -->
+
+[![Lifecycle:
+maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
 [![CRAN
 status](https://www.r-pkg.org/badges/version/gt)](https://cran.r-project.org/package=gt)
-[![Travis build
-status](https://travis-ci.com/rstudio/gt.svg?token=P7T9dzi5RLEq9j2Yepx5&branch=master)](https://travis-ci.com/rstudio/gt)
-[![AppVeyor Build
-Status](https://ci.appveyor.com/api/projects/status/github/rstudio/gt?branch=master&svg=true)](https://ci.appveyor.com/project/rstudio/gt)
+[![R build
+status](https://github.com/rstudio/gt/workflows/R-CMD-check/badge.svg)](https://github.com/rstudio/gt/actions?workflow=R-CMD-check)
 [![Coverage
 status](https://codecov.io/gh/rstudio/gt/branch/master/graph/badge.svg)](https://codecov.io/github/rstudio/gt?branch=master)
+<!-- badges: end -->
 
 With the **gt** package, anyone can make wonderful-looking tables using
 the **R** programming language. The **gt** philosophy: we can construct
@@ -101,10 +103,17 @@ Cloud**. It’s full of ready-to-run examples.
 
 </p>
 
-You can install the development version of **gt** from **GitHub**:
+The **gt** package can be installed from **CRAN** with:
+
+``` r
+install.packages("gt")
+```
+
+You can also choose to install the development version of **gt** from
+**GitHub**:
 
 ``` r
-remotes::install_github("rstudio/gt")
+devtools::install_github("rstudio/gt")
 ```
 
 If you encounter a bug, have usage questions, or want to share ideas to
diff --git a/appveyor.yml b/appveyor.yml
deleted file mode 100644
index 39c1c3c51..000000000
--- a/appveyor.yml
+++ /dev/null
@@ -1,54 +0,0 @@
-# DO NOT CHANGE the "init" and "install" sections below
-
-# Download script file from GitHub
-init:
-  ps: |
-        $ErrorActionPreference = "Stop"
-        Invoke-WebRequest http://raw.github.com/krlmlr/r-appveyor/master/scripts/appveyor-tool.ps1 -OutFile "..\appveyor-tool.ps1"
-        Import-Module '..\appveyor-tool.ps1'
-
-install:
-  ps: Bootstrap
-
-# Adapt as necessary starting from here
-
-environment:
-  global:
-    USE_RTOOLS: true
-
-  matrix:
-    - R_VERSION: release
-      arch: x64
-      GCC_PATH: mingw_64
-    - R_VERSION: devel
-      R_ARCH: x64
-      GCC_PATH: mingw_64
-
-build_script:
-  - travis-tool.sh install_deps
-
-test_script:
-  - travis-tool.sh run_tests
-
-on_failure:
-  - 7z a failure.zip *.Rcheck\*
-  - appveyor PushArtifact failure.zip
-
-artifacts:
-  - path: '*.Rcheck\**\*.log'
-    name: Logs
-
-  - path: '*.Rcheck\**\*.out'
-    name: Logs
-
-  - path: '*.Rcheck\**\*.fail'
-    name: Logs
-
-  - path: '*.Rcheck\**\*.Rout'
-    name: Logs
-
-  - path: '\*_*.tar.gz'
-    name: Bits
-
-  - path: '\*_*.zip'
-    name: Bits

From d1d3782a9e2d2f70cd99deb9f10674bfd151c16f Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Thu, 16 Apr 2020 17:10:38 -0400
Subject: [PATCH 10/30] pkgdown fixes (#551)

* Update .Rbuildignore

* Update intro-creating-gt-tables.Rmd

* Modify image links vignettes; move files to man/figures

* Use the `release` development mode
---
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diff --git a/_pkgdown.yml b/_pkgdown.yml
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+++ b/_pkgdown.yml
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 development:
-  mode: auto
+  mode: release
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-      <div class="copyright">
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diff --git a/docs/CODE_OF_CONDUCT.html b/docs/CODE_OF_CONDUCT.html
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+++ /dev/null
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-<!-- Generated by pkgdown: do not edit by hand -->
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-<!-- favicons -->
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-<p>Where might you answer user questions? Some of the forums for Q&amp;A on <strong>gt</strong> include the <a href="https://community.rstudio.com">RStudio community</a>, on Twitter (a good search term is <code>gt #rstats</code>), and on <a href="https://stackoverflow.com">Stack Overflow</a>. Good etiquette is key during these interactions: be a good person to all who ask questions.</p>
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-<p>Should you consider making a pull request (PR), please file an issue first and explain the problem in some detail. If the PR is an enhancement, detail how the change would make things better for package users. Bugfix PRs also requre some explanation about the bug and how the proposed fix will remove that bug. A great way to illustrate the bug is to include a <a href="https://reprex.tidyverse.org">reprex</a>. While all this upfront work prior to preparing a PR can be time-consuming it opens a line of communication with the package authors and the community, perhaps leading to better enhancement or more effective fixes!</p>
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-      <h1 data-toc-skip>Case Study: gtcars</h1>
-            
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-      <small class="dont-index">Source: <a href="https://github.com/rstudio/gt/blob/master/vignettes/case-study-gtcars.Rmd"><code>vignettes/case-study-gtcars.Rmd</code></a></small>
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-<p align="center">
-<img src="images/gtcars.svg" width="50%"></p>
-<p>Let’s make a display table using the <code>gtcars</code> dataset. We all know <code>mtcars</code>… what is <code>gtcars</code>? It’s basically a modernized <code>mtcars</code> for the <strong>gt</strong> age. It’s part of the <strong>gt</strong> package, and here is a preview of the tibble:</p>
-<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># This is `gtcars`</span>
-<span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">glimpse</a></span>(<span class="no">gtcars</span>)
-<span class="co">#&gt; Rows: 47</span>
-<span class="co">#&gt; Columns: 15</span>
-<span class="co">#&gt; $ mfr         &lt;chr&gt; "Ford", "Ferrari", "Ferrari", "Ferrari", "Ferrari", "Ferr…</span>
-<span class="co">#&gt; $ model       &lt;chr&gt; "GT", "458 Speciale", "458 Spider", "458 Italia", "488 GT…</span>
-<span class="co">#&gt; $ year        &lt;dbl&gt; 2017, 2015, 2015, 2014, 2016, 2015, 2017, 2015, 2015, 201…</span>
-<span class="co">#&gt; $ trim        &lt;chr&gt; "Base Coupe", "Base Coupe", "Base", "Base Coupe", "Base C…</span>
-<span class="co">#&gt; $ bdy_style   &lt;chr&gt; "coupe", "coupe", "convertible", "coupe", "coupe", "conve…</span>
-<span class="co">#&gt; $ hp          &lt;dbl&gt; 647, 597, 562, 562, 661, 553, 680, 652, 731, 949, 573, 54…</span>
-<span class="co">#&gt; $ hp_rpm      &lt;dbl&gt; 6250, 9000, 9000, 9000, 8000, 7500, 8250, 8000, 8250, 900…</span>
-<span class="co">#&gt; $ trq         &lt;dbl&gt; 550, 398, 398, 398, 561, 557, 514, 504, 509, 664, 476, 43…</span>
-<span class="co">#&gt; $ trq_rpm     &lt;dbl&gt; 5900, 6000, 6000, 6000, 3000, 4750, 5750, 6000, 6000, 675…</span>
-<span class="co">#&gt; $ mpg_c       &lt;dbl&gt; 11, 13, 13, 13, 15, 16, 12, 11, 11, 12, 21, 16, 11, 16, 1…</span>
-<span class="co">#&gt; $ mpg_h       &lt;dbl&gt; 18, 17, 17, 17, 22, 23, 17, 16, 16, 16, 22, 22, 18, 20, 2…</span>
-<span class="co">#&gt; $ drivetrain  &lt;chr&gt; "rwd", "rwd", "rwd", "rwd", "rwd", "rwd", "awd", "awd", "…</span>
-<span class="co">#&gt; $ trsmn       &lt;chr&gt; "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a…</span>
-<span class="co">#&gt; $ ctry_origin &lt;chr&gt; "United States", "Italy", "Italy", "Italy", "Italy", "Ita…</span>
-<span class="co">#&gt; $ msrp        &lt;dbl&gt; 447000, 291744, 263553, 233509, 245400, 198973, 298000, 2…</span></pre></body></html></div>
-<p>For the purpose of simply learning more about <strong>gt</strong>, let’s reduce this 47-row tibble to one that has only 8 rows:</p>
-<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Get a subset of 8 cars from the `gtcars` dataset: two</span>
-<span class="co"># from each manufacturer country of origin except the UK</span>
-<span class="no">gtcars_8</span> <span class="kw">&lt;-</span>
-  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/top_n.html">top_n</a></span>(<span class="fl">2</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">ungroup</a></span>() <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">ctry_origin</span> <span class="kw">!=</span> <span class="st">"United Kingdom"</span>)
-<span class="co">#&gt; Selecting by msrp</span>
-
-<span class="co"># Show the `gtcars_8` tibble</span>
-<span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">glimpse</a></span>(<span class="no">gtcars_8</span>)
-<span class="co">#&gt; Rows: 8</span>
-<span class="co">#&gt; Columns: 15</span>
-<span class="co">#&gt; $ mfr         &lt;chr&gt; "Ford", "Ferrari", "Acura", "Nissan", "Lamborghini", "BMW…</span>
-<span class="co">#&gt; $ model       &lt;chr&gt; "GT", "LaFerrari", "NSX", "GT-R", "Aventador", "i8", "Vip…</span>
-<span class="co">#&gt; $ year        &lt;dbl&gt; 2017, 2015, 2017, 2016, 2015, 2016, 2017, 2016</span>
-<span class="co">#&gt; $ trim        &lt;chr&gt; "Base Coupe", "Base Coupe", "Base Coupe", "Premium Coupe"…</span>
-<span class="co">#&gt; $ bdy_style   &lt;chr&gt; "coupe", "coupe", "coupe", "coupe", "coupe", "coupe", "co…</span>
-<span class="co">#&gt; $ hp          &lt;dbl&gt; 647, 949, 573, 545, 700, 357, 645, 503</span>
-<span class="co">#&gt; $ hp_rpm      &lt;dbl&gt; 6250, 9000, 6500, 6400, 8250, 5800, 5000, 6250</span>
-<span class="co">#&gt; $ trq         &lt;dbl&gt; 550, 664, 476, 436, 507, 420, 600, 479</span>
-<span class="co">#&gt; $ trq_rpm     &lt;dbl&gt; 5900, 6750, 2000, 3200, 5500, 3700, 5000, 1750</span>
-<span class="co">#&gt; $ mpg_c       &lt;dbl&gt; 11, 12, 21, 16, 11, 28, 12, 16</span>
-<span class="co">#&gt; $ mpg_h       &lt;dbl&gt; 18, 16, 22, 22, 18, 29, 19, 22</span>
-<span class="co">#&gt; $ drivetrain  &lt;chr&gt; "rwd", "rwd", "awd", "awd", "awd", "awd", "rwd", "rwd"</span>
-<span class="co">#&gt; $ trsmn       &lt;chr&gt; "7a", "7a", "9a", "6a", "7a", "6am", "6m", "7a"</span>
-<span class="co">#&gt; $ ctry_origin &lt;chr&gt; "United States", "Italy", "Japan", "Japan", "Italy", "Ger…</span>
-<span class="co">#&gt; $ msrp        &lt;dbl&gt; 447000, 1416362, 156000, 101770, 397500, 140700, 95895, 1…</span></pre></body></html></div>
-<p>Let’s make a display table from this dataset. In doing so we’ll fulfill the following 10 requirements:</p>
-<ol style="list-style-type: decimal">
-<li>putting the cars into characteristic groups (by the car manufacturer’s country of origin)</li>
-<li>removing some of the columns that we don’t want to present</li>
-<li>incorporating some columns into a column group</li>
-<li>formatting the currency data and using a monospaced font for easier reading of that data</li>
-<li>giving the table a title and a subtitle</li>
-<li>adding footnotes to draw attention to some of the more interesting data points and to explain some of the more unusual aspects of the data</li>
-<li>placing a citation for the dataset at the bottom of the table</li>
-<li>transforming the transmission (<code>trsmn</code>) codes so that they are readable and understandable</li>
-<li>styling some cells according to basic criteria</li>
-<li>highlighting the cars that are considered to be <em>grand tourers</em>
-</li>
-</ol>
-<div id="row-groups" class="section level3">
-<h3 class="hasAnchor">
-<a href="#row-groups" class="anchor"></a>Row Groups</h3>
-<p>Let’s again use <strong>dplyr</strong> to help make groupings by the <code>ctry_origin</code> column, which provides the country of origin for the vehicle manufacturer of the car. We can simply use <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">dplyr::group_by()</a></code> on the <code>gtcars</code> dataset and pass that to <code><a href="../reference/gt.html">gt()</a></code>. What you get is a display table that arranges the cars into row groups, with the name of the group displayed prominently above.</p>
-<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Use `group_by()` on `gtcars` and pass that to `gt()`</span>
-<span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#wdxgxlbuhb .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#wdxgxlbuhb .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#wdxgxlbuhb .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#wdxgxlbuhb .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#wdxgxlbuhb .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#wdxgxlbuhb .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#wdxgxlbuhb .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#wdxgxlbuhb .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#wdxgxlbuhb .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#wdxgxlbuhb .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#wdxgxlbuhb .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#wdxgxlbuhb .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#wdxgxlbuhb .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#wdxgxlbuhb .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#wdxgxlbuhb .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#wdxgxlbuhb .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#wdxgxlbuhb .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#wdxgxlbuhb .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#wdxgxlbuhb .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#wdxgxlbuhb .gt_left {
-  text-align: left;
-}
-
-#wdxgxlbuhb .gt_center {
-  text-align: center;
-}
-
-#wdxgxlbuhb .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#wdxgxlbuhb .gt_font_normal {
-  font-weight: normal;
-}
-
-#wdxgxlbuhb .gt_font_bold {
-  font-weight: bold;
-}
-
-#wdxgxlbuhb .gt_font_italic {
-  font-style: italic;
-}
-
-#wdxgxlbuhb .gt_super {
-  font-size: 65%;
-}
-
-#wdxgxlbuhb .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="wdxgxlbuhb" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">mfr</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">model</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Ford</td>
-      <td class="gt_row gt_left">GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">647</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">550</td>
-      <td class="gt_row gt_right">5900</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">447000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Dodge</td>
-      <td class="gt_row gt_left">Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">645</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">600</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">19</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">95895</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Ferrari</td>
-      <td class="gt_row gt_left">LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">949</td>
-      <td class="gt_row gt_right">9000</td>
-      <td class="gt_row gt_right">664</td>
-      <td class="gt_row gt_right">6750</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">1416362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Lamborghini</td>
-      <td class="gt_row gt_left">Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">700</td>
-      <td class="gt_row gt_right">8250</td>
-      <td class="gt_row gt_right">507</td>
-      <td class="gt_row gt_right">5500</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Acura</td>
-      <td class="gt_row gt_left">NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">573</td>
-      <td class="gt_row gt_right">6500</td>
-      <td class="gt_row gt_right">476</td>
-      <td class="gt_row gt_right">2000</td>
-      <td class="gt_row gt_right">21</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">156000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Nissan</td>
-      <td class="gt_row gt_left">GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">545</td>
-      <td class="gt_row gt_right">6400</td>
-      <td class="gt_row gt_right">436</td>
-      <td class="gt_row gt_right">3200</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">101770</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">BMW</td>
-      <td class="gt_row gt_left">i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">357</td>
-      <td class="gt_row gt_right">5800</td>
-      <td class="gt_row gt_right">420</td>
-      <td class="gt_row gt_right">3700</td>
-      <td class="gt_row gt_right">28</td>
-      <td class="gt_row gt_right">29</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">140700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Mercedes-Benz</td>
-      <td class="gt_row gt_left">AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">503</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">479</td>
-      <td class="gt_row gt_right">1750</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">129900</td>
-    </tr>
-</tbody>
-</table></div>
-<p>Getting the row groups in the preferred order can be done easily with <strong>dplyr</strong>’s <code>arrange()</code> function. For example, we can have groups that are arranged alphabetically by manufacturer (<code>mfr</code>) and then sorted by highest sticker price (<code>msrp</code>) to lowest.</p>
-<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
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-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">mfr</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">model</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
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-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Acura</td>
-      <td class="gt_row gt_left">NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">573</td>
-      <td class="gt_row gt_right">6500</td>
-      <td class="gt_row gt_right">476</td>
-      <td class="gt_row gt_right">2000</td>
-      <td class="gt_row gt_right">21</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">156000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Nissan</td>
-      <td class="gt_row gt_left">GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">545</td>
-      <td class="gt_row gt_right">6400</td>
-      <td class="gt_row gt_right">436</td>
-      <td class="gt_row gt_right">3200</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">101770</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">BMW</td>
-      <td class="gt_row gt_left">i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">357</td>
-      <td class="gt_row gt_right">5800</td>
-      <td class="gt_row gt_right">420</td>
-      <td class="gt_row gt_right">3700</td>
-      <td class="gt_row gt_right">28</td>
-      <td class="gt_row gt_right">29</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">140700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Mercedes-Benz</td>
-      <td class="gt_row gt_left">AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">503</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">479</td>
-      <td class="gt_row gt_right">1750</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">129900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Dodge</td>
-      <td class="gt_row gt_left">Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">645</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">600</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">19</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">95895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Ford</td>
-      <td class="gt_row gt_left">GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">647</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">550</td>
-      <td class="gt_row gt_right">5900</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">447000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Ferrari</td>
-      <td class="gt_row gt_left">LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">949</td>
-      <td class="gt_row gt_right">9000</td>
-      <td class="gt_row gt_right">664</td>
-      <td class="gt_row gt_right">6750</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">1416362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Lamborghini</td>
-      <td class="gt_row gt_left">Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">700</td>
-      <td class="gt_row gt_right">8250</td>
-      <td class="gt_row gt_right">507</td>
-      <td class="gt_row gt_right">5500</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
-</tbody>
-</table></div>
-<p>We could also use factor levels to get a more particular ordering within <code>arrange()</code>. For example, we can first arrange the groups themselves (the country of origin–<code>ctry_origin</code>) by our own preferred ordering and then arrange by <code>mfr</code> and descending <code>msrp</code> as before. Then, <code>group_by(ctry_origin)</code> can be used on the sorted tibble before passing this to <code><a href="../reference/gt.html">gt()</a></code>.</p>
-<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Define our preferred order `ctry_origin`</span>
-<span class="no">order_countries</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Germany"</span>, <span class="st">"Italy"</span>, <span class="st">"United States"</span>, <span class="st">"Japan"</span>)
-
-<span class="co"># Reorder the table rows by our specific ordering of groups</span>
-<span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(
-    <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="no">ctry_origin</span>, <span class="kw">levels</span> <span class="kw">=</span> <span class="no">order_countries</span>), <span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
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-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">mfr</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">model</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
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-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
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-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
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-<tr class="gt_group_heading_row">
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-<tr>
-<td class="gt_row gt_left">BMW</td>
-      <td class="gt_row gt_left">i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">357</td>
-      <td class="gt_row gt_right">5800</td>
-      <td class="gt_row gt_right">420</td>
-      <td class="gt_row gt_right">3700</td>
-      <td class="gt_row gt_right">28</td>
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-      <td class="gt_row gt_right">140700</td>
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-      <td class="gt_row gt_left">AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
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-      <td class="gt_row gt_right">503</td>
-      <td class="gt_row gt_right">6250</td>
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-      <td class="gt_row gt_right">16</td>
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-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">949</td>
-      <td class="gt_row gt_right">9000</td>
-      <td class="gt_row gt_right">664</td>
-      <td class="gt_row gt_right">6750</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">16</td>
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-      <td class="gt_row gt_left">Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">700</td>
-      <td class="gt_row gt_right">8250</td>
-      <td class="gt_row gt_right">507</td>
-      <td class="gt_row gt_right">5500</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="14" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Dodge</td>
-      <td class="gt_row gt_left">Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">645</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">600</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">19</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">95895</td>
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-      <td class="gt_row gt_left">GT</td>
-      <td class="gt_row gt_right">2017</td>
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-      <td class="gt_row gt_right">647</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">550</td>
-      <td class="gt_row gt_right">5900</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">447000</td>
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-<td class="gt_row gt_left">Acura</td>
-      <td class="gt_row gt_left">NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">573</td>
-      <td class="gt_row gt_right">6500</td>
-      <td class="gt_row gt_right">476</td>
-      <td class="gt_row gt_right">2000</td>
-      <td class="gt_row gt_right">21</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">156000</td>
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-<tr>
-<td class="gt_row gt_left">Nissan</td>
-      <td class="gt_row gt_left">GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">545</td>
-      <td class="gt_row gt_right">6400</td>
-      <td class="gt_row gt_right">436</td>
-      <td class="gt_row gt_right">3200</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">101770</td>
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-</tbody>
-</table></div>
-<p>The last variation is to combine the manufacturer name with the model name, using those combined strings as row labels for the table. This is just a little more <strong>dplyr</strong> where we can use <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">dplyr::mutate()</a></code> to make a new <code>car</code> column followed by <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> where we remove the <code>mfr</code> and <code>model</code> columns. When introducing the tibble to the <code><a href="../reference/gt.html">gt()</a></code> function, we can now use the <code>rowname_col</code> argument to specify a column that will serve as row labels (which is the newly made <code>car</code> column).</p>
-<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Reorder the table rows by our specific ordering of groups</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">gtcars_8</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(
-    <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="no">ctry_origin</span>, <span class="kw">levels</span> <span class="kw">=</span> <span class="no">order_countries</span>),
-    <span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)
-    ) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">mfr</span>, -<span class="no">model</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"car"</span>)
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
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-</style>
-<div id="iqocbggiwh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">bdy_style</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">drivetrain</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="13" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">357</td>
-      <td class="gt_row gt_right">5800</td>
-      <td class="gt_row gt_right">420</td>
-      <td class="gt_row gt_right">3700</td>
-      <td class="gt_row gt_right">28</td>
-      <td class="gt_row gt_right">29</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">140700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">503</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">479</td>
-      <td class="gt_row gt_right">1750</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">129900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="13" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">949</td>
-      <td class="gt_row gt_right">9000</td>
-      <td class="gt_row gt_right">664</td>
-      <td class="gt_row gt_right">6750</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">1416362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">700</td>
-      <td class="gt_row gt_right">8250</td>
-      <td class="gt_row gt_right">507</td>
-      <td class="gt_row gt_right">5500</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="13" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">645</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">600</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">19</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">95895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">647</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">550</td>
-      <td class="gt_row gt_right">5900</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_left">rwd</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">447000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="13" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">573</td>
-      <td class="gt_row gt_right">6500</td>
-      <td class="gt_row gt_right">476</td>
-      <td class="gt_row gt_right">2000</td>
-      <td class="gt_row gt_right">21</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">156000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">coupe</td>
-      <td class="gt_row gt_right">545</td>
-      <td class="gt_row gt_right">6400</td>
-      <td class="gt_row gt_right">436</td>
-      <td class="gt_row gt_right">3200</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_left">awd</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">101770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="hiding-and-moving-some-columns" class="section level3">
-<h3 class="hasAnchor">
-<a href="#hiding-and-moving-some-columns" class="anchor"></a>Hiding and Moving Some Columns</h3>
-<p>Let’s hide two columns that we don’t need to the final table: <code>drivetrain</code> and <code>bdy_style</code>. We can use the <code><a href="../reference/cols_hide.html">cols_hide()</a></code> function to hide columns. The same end result might also have been achieved by using <code>gtcars %&gt;% dplyr::select(-c(drivetrain, bdy_style))</code>, before introducing the table to <code><a href="../reference/gt.html">gt()</a></code>. Why this function then? Sometimes you’ll need variables for conditional statements within <strong>gt</strong> but won’t want to display them in the end.</p>
-<p>Aside from hiding columns, let’s <em>move</em> some of them. Again, this could be done with <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> but there are options here in <strong>gt</strong> via the <code><a href="../reference/cols_move_to_start.html">cols_move_to_start()</a></code>, <code><a href="../reference/cols_move.html">cols_move()</a></code>, and <code><a href="../reference/cols_move_to_end.html">cols_move_to_end()</a></code> functions.</p>
-<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># Use a few `cols_*()` functions to hide and move columns </span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_hide.html">cols_hide</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>, <span class="no">bdy_style</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_move.html">cols_move</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
-    <span class="kw">after</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>)
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#euyfsfmrya .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#euyfsfmrya .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#euyfsfmrya .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#euyfsfmrya .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#euyfsfmrya .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#euyfsfmrya .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#euyfsfmrya .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#euyfsfmrya .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#euyfsfmrya .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#euyfsfmrya .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#euyfsfmrya .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#euyfsfmrya .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#euyfsfmrya .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#euyfsfmrya .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#euyfsfmrya .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#euyfsfmrya .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#euyfsfmrya .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#euyfsfmrya .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#euyfsfmrya .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#euyfsfmrya .gt_left {
-  text-align: left;
-}
-
-#euyfsfmrya .gt_center {
-  text-align: center;
-}
-
-#euyfsfmrya .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#euyfsfmrya .gt_font_normal {
-  font-weight: normal;
-}
-
-#euyfsfmrya .gt_font_bold {
-  font-weight: bold;
-}
-
-#euyfsfmrya .gt_font_italic {
-  font-style: italic;
-}
-
-#euyfsfmrya .gt_super {
-  font-size: 65%;
-}
-
-#euyfsfmrya .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="euyfsfmrya" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trim</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">trsmn</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_c</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">mpg_h</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">hp_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">trq_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">msrp</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">28</td>
-      <td class="gt_row gt_right">29</td>
-      <td class="gt_row gt_right">357</td>
-      <td class="gt_row gt_right">5800</td>
-      <td class="gt_row gt_right">420</td>
-      <td class="gt_row gt_right">3700</td>
-      <td class="gt_row gt_right">140700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_right">503</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">479</td>
-      <td class="gt_row gt_right">1750</td>
-      <td class="gt_row gt_right">129900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">949</td>
-      <td class="gt_row gt_right">9000</td>
-      <td class="gt_row gt_right">664</td>
-      <td class="gt_row gt_right">6750</td>
-      <td class="gt_row gt_right">1416362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_right">700</td>
-      <td class="gt_row gt_right">8250</td>
-      <td class="gt_row gt_right">507</td>
-      <td class="gt_row gt_right">5500</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">19</td>
-      <td class="gt_row gt_right">645</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">600</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">95895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_right">647</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">550</td>
-      <td class="gt_row gt_right">5900</td>
-      <td class="gt_row gt_right">447000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">21</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_right">573</td>
-      <td class="gt_row gt_right">6500</td>
-      <td class="gt_row gt_right">476</td>
-      <td class="gt_row gt_right">2000</td>
-      <td class="gt_row gt_right">156000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_right">545</td>
-      <td class="gt_row gt_right">6400</td>
-      <td class="gt_row gt_right">436</td>
-      <td class="gt_row gt_right">3200</td>
-      <td class="gt_row gt_right">101770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="putting-columns-into-groups" class="section level3">
-<h3 class="hasAnchor">
-<a href="#putting-columns-into-groups" class="anchor"></a>Putting Columns Into Groups</h3>
-<p>It’s sometimes useful to arrange variables/columns into groups by using spanner column labels. This can be done in <strong>gt</strong> by using the <code><a href="../reference/tab_spanner.html">tab_spanner()</a></code> function. It takes the <code>label</code> and <code>columns</code> arguments; <code>label</code> is the spanner column label and the <code>columns</code> are those columns that belong in this group.</p>
-<p>Here, we’ll put the <code>mpg_c</code>, <code>mpg_h</code>, <code>hp</code>, <code>hp_rpm</code>, <code>trq</code>, <code>trq_rpm</code> columns under the <code>Performance</code> spanner column, and the remaining columns won’t be grouped together. This single spanner column label is styled with Markdown by using the <code><a href="../reference/md.html">md()</a></code> helper.</p>
-<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># Put the first three columns under a spanner</span>
-<span class="co"># column with the label 'Performance'</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
-    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Performance"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>, <span class="no">hp</span>, <span class="no">hp_rpm</span>, <span class="no">trq</span>, <span class="no">trq_rpm</span>)
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#ybltdcxcyx .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
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-</style>
-<div id="ybltdcxcyx" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">trsmn</th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="6">
-        <span class="gt_column_spanner">Performance</span>
-      </th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">msrp</th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">mpg_c</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">mpg_h</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">hp</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">hp_rpm</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">trq</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">trq_rpm</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">28</td>
-      <td class="gt_row gt_right">29</td>
-      <td class="gt_row gt_right">357</td>
-      <td class="gt_row gt_right">5800</td>
-      <td class="gt_row gt_right">420</td>
-      <td class="gt_row gt_right">3700</td>
-      <td class="gt_row gt_right">140700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_right">503</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">479</td>
-      <td class="gt_row gt_right">1750</td>
-      <td class="gt_row gt_right">129900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">949</td>
-      <td class="gt_row gt_right">9000</td>
-      <td class="gt_row gt_right">664</td>
-      <td class="gt_row gt_right">6750</td>
-      <td class="gt_row gt_right">1416362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_right">700</td>
-      <td class="gt_row gt_right">8250</td>
-      <td class="gt_row gt_right">507</td>
-      <td class="gt_row gt_right">5500</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">12</td>
-      <td class="gt_row gt_right">19</td>
-      <td class="gt_row gt_right">645</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">600</td>
-      <td class="gt_row gt_right">5000</td>
-      <td class="gt_row gt_right">95895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11</td>
-      <td class="gt_row gt_right">18</td>
-      <td class="gt_row gt_right">647</td>
-      <td class="gt_row gt_right">6250</td>
-      <td class="gt_row gt_right">550</td>
-      <td class="gt_row gt_right">5900</td>
-      <td class="gt_row gt_right">447000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="11" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">21</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_right">573</td>
-      <td class="gt_row gt_right">6500</td>
-      <td class="gt_row gt_right">476</td>
-      <td class="gt_row gt_right">2000</td>
-      <td class="gt_row gt_right">156000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">16</td>
-      <td class="gt_row gt_right">22</td>
-      <td class="gt_row gt_right">545</td>
-      <td class="gt_row gt_right">6400</td>
-      <td class="gt_row gt_right">436</td>
-      <td class="gt_row gt_right">3200</td>
-      <td class="gt_row gt_right">101770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="merging-columns-together-and-labeling-them" class="section level3">
-<h3 class="hasAnchor">
-<a href="#merging-columns-together-and-labeling-them" class="anchor"></a>Merging Columns Together and Labeling Them</h3>
-<p>Sometimes we’d like to combine the data from two columns into a single column. The <code><a href="../reference/cols_merge.html">cols_merge()</a></code> function allows us to do this, we just need to describe how the data should be combined. For our table, let’s merge together the following pairs of columns:</p>
-<ul>
-<li>
-<code>mpg_c</code> and <code>mpg_h</code> (miles per gallon in city and highway driving modes)</li>
-<li>
-<code>hp</code> and <code>hp_rpm</code> (horsepower and associated RPM)</li>
-<li>
-<code>trq</code> and <code>trq_rpm</code> (torque and associated RPM)</li>
-</ul>
-<p>The <code><a href="../reference/cols_merge.html">cols_merge()</a></code> function uses a <code>col_1</code> column and a <code>col_2</code> column. Once combined, the <code>col_1</code> column will be retained and the <code>col_2</code> column will be dropped. The pattern argument uses <code>{1}</code> and <code>{2}</code> to represent the content of <code>col_1</code> and <code>col_2</code>. Here, we can use string literals to add text like <code>rpm</code> or the <code>@</code> sign. Furthermore, because we are targeting an HTML table, we can use the <code>&lt;br&gt;</code> tag to insert a linebreak.</p>
-<p>Labeling columns essentially means that we are choosing display-friendly labels that are no longer simply the column names (the default label). The <code><a href="../reference/cols_label.html">cols_label()</a></code> function makes this relabeling possible. It accepts a series of named arguments in the form of <code>&lt;column_name&gt; = &lt;column_label&gt;, ...</code>.</p>
-<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># Perform three column merges to better present</span>
-<span class="co"># MPG, HP, and torque; relabel all the remaining</span>
-<span class="co"># columns for a nicer-looking presentation</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_h</span>),
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}c&lt;br&gt;{2}h"</span>
-    ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp</span>, <span class="no">hp_rpm</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp_rpm</span>),
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq</span>, <span class="no">trq_rpm</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq_rpm</span>),
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
-    <span class="kw">mpg_c</span> <span class="kw">=</span> <span class="st">"MPG"</span>,
-    <span class="kw">hp</span> <span class="kw">=</span> <span class="st">"HP"</span>,
-    <span class="kw">trq</span> <span class="kw">=</span> <span class="st">"Torque"</span>,
-    <span class="kw">year</span> <span class="kw">=</span> <span class="st">"Year"</span>,
-    <span class="kw">trim</span> <span class="kw">=</span> <span class="st">"Trim"</span>,
-    <span class="kw">trsmn</span> <span class="kw">=</span> <span class="st">"Transmission"</span>,
-    <span class="kw">msrp</span> <span class="kw">=</span> <span class="st">"MSRP"</span>
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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-
-#twectbdcrq .gt_table {
-  display: table;
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-  color: #333333;
-  font-size: 16px;
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-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
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-        <span class="gt_column_spanner">Performance</span>
-      </th>
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-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">28c<br>29h</td>
-      <td class="gt_row gt_right">357<br>@5800rpm</td>
-      <td class="gt_row gt_right">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">140700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">7a</td>
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-      <td class="gt_row gt_right">503<br>@6250rpm</td>
-      <td class="gt_row gt_right">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">129900</td>
-    </tr>
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-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">12c<br>16h</td>
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-      <td class="gt_row gt_right">664<br>@6750rpm</td>
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-    </tr>
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-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11c<br>18h</td>
-      <td class="gt_row gt_right">700<br>@8250rpm</td>
-      <td class="gt_row gt_right">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">397500</td>
-    </tr>
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-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">12c<br>19h</td>
-      <td class="gt_row gt_right">645<br>@5000rpm</td>
-      <td class="gt_row gt_right">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">95895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11c<br>18h</td>
-      <td class="gt_row gt_right">647<br>@6250rpm</td>
-      <td class="gt_row gt_right">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">447000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">21c<br>22h</td>
-      <td class="gt_row gt_right">573<br>@6500rpm</td>
-      <td class="gt_row gt_right">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">156000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">16c<br>22h</td>
-      <td class="gt_row gt_right">545<br>@6400rpm</td>
-      <td class="gt_row gt_right">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">101770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="using-formatter-functions" class="section level3">
-<h3 class="hasAnchor">
-<a href="#using-formatter-functions" class="anchor"></a>Using Formatter Functions</h3>
-<p>There are a number of formatter functions, all with the general naming convention <code>fmt*()</code>. The various formatters are convenient for applying formats to numeric or character values in the table’s field. Here, we will simply use <code><a href="../reference/fmt_currency.html">fmt_currency()</a></code> on the <code>msrp</code> column (we still refer to columns by their original names) to get USD currency will no decimal places. We’re not supplying anything for the <code>rows</code> argument and this means we want to apply the formatting to the entire column of data.</p>
-<div class="sourceCode" id="cb10"><html><body><pre class="r"><span class="co"># Format the `msrp` column to USD currency</span>
-<span class="co"># with no display of the currency subunits</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
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-</style>
-<div id="kpobecsdpo" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Performance</span>
-      </th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Mega World Coupe</td>
-      <td class="gt_row gt_left">6am</td>
-      <td class="gt_row gt_right">28c<br>29h</td>
-      <td class="gt_row gt_right">357<br>@5800rpm</td>
-      <td class="gt_row gt_right">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">$140,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">S Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">16c<br>22h</td>
-      <td class="gt_row gt_right">503<br>@6250rpm</td>
-      <td class="gt_row gt_right">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">$129,900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">12c<br>16h</td>
-      <td class="gt_row gt_right">949<br>@9000rpm</td>
-      <td class="gt_row gt_right">664<br>@6750rpm</td>
-      <td class="gt_row gt_right">$1,416,362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11c<br>18h</td>
-      <td class="gt_row gt_right">700<br>@8250rpm</td>
-      <td class="gt_row gt_right">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">$397,500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">GT Coupe</td>
-      <td class="gt_row gt_left">6m</td>
-      <td class="gt_row gt_right">12c<br>19h</td>
-      <td class="gt_row gt_right">645<br>@5000rpm</td>
-      <td class="gt_row gt_right">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">$95,895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">7a</td>
-      <td class="gt_row gt_right">11c<br>18h</td>
-      <td class="gt_row gt_right">647<br>@6250rpm</td>
-      <td class="gt_row gt_right">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">$447,000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left">Base Coupe</td>
-      <td class="gt_row gt_left">9a</td>
-      <td class="gt_row gt_right">21c<br>22h</td>
-      <td class="gt_row gt_right">573<br>@6500rpm</td>
-      <td class="gt_row gt_right">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">$156,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left">Premium Coupe</td>
-      <td class="gt_row gt_left">6a</td>
-      <td class="gt_row gt_right">16c<br>22h</td>
-      <td class="gt_row gt_right">545<br>@6400rpm</td>
-      <td class="gt_row gt_right">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">$101,770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="column-alignment-and-style-changes" class="section level3">
-<h3 class="hasAnchor">
-<a href="#column-alignment-and-style-changes" class="anchor"></a>Column Alignment and Style Changes</h3>
-<p>We can change the alignment of data in columns with <code><a href="../reference/cols_align.html">cols_align()</a></code>. For our table, let’s center-align the <code>mpg_c</code>, <code>hp</code>, and <code>trq</code> columns. All other columns will maintain their default alignments.</p>
-<p>It’s sometimes useful to modify the default styles of table cells. We can do this in a targeted way with the <code><a href="../reference/tab_style.html">tab_style()</a></code> function. That function require two key pieces of information: a <code>style</code> definition, and one or more <code>locations</code> (which cells should the styles be applied to?). The <code>style</code> argument commonly uses the <code>cells_styles()</code> helper function, which contains arguments for all the styles that are supported (use <code>?cells_styles</code> for more information on this). Here we will use a text size of <code>12px</code> in our targeted cells—both <code><a href="../reference/px.html">px(12)</a></code> and <code>"12px"</code> work equally well here. We also use helper functions with the <code>locations</code> argument and these are the <code>cells_*()</code> functions. We would like to target the data cells in all columns except <code>year</code> and <code>msrp</code> so we need to use <code>cells_body</code> and then supply our target columns to the <code>columns</code> argument.</p>
-<div class="sourceCode" id="cb11"><html><body><pre class="r"><span class="co"># Center-align three columns in the gt table</span>
-<span class="co"># and modify the text size of a few columns</span>
-<span class="co"># of data</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_align.html">cols_align</a></span>(
-    <span class="kw">align</span> <span class="kw">=</span> <span class="st">"center"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_style.html">tab_style</a></span>(
-    <span class="kw">style</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cell_text.html">cell_text</a></span>(<span class="kw">size</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">12</span>)),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>, <span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>))
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
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-<div id="dpmwnzbpry" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Performance</span>
-      </th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6am</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">$140,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">$129,900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
-      <td class="gt_row gt_right">$1,416,362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">$397,500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6m</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">$95,895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7a</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">$447,000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">9a</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">$156,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6a</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">$101,770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="text-transforms" class="section level3">
-<h3 class="hasAnchor">
-<a href="#text-transforms" class="anchor"></a>Text Transforms</h3>
-<p>A text transform via the <code><a href="../reference/text_transform.html">text_transform()</a></code> function is a great way to further manipulate text in data cells (even after they’ve been formatted with the <code>fmt*()</code> function). After targeting data cells with the <code><a href="../reference/cells_body.html">cells_body()</a></code> location helper function, we supply a function to the <code>fn</code> argument that processes a vector of text. If we intend to render as an HTML table, we can directly apply HTML tags in the transformation function. The function we provide here will build strings that read better in a display table.</p>
-<div class="sourceCode" id="cb12"><html><body><pre class="r"><span class="co"># Transform the column of text in `trsmn` using</span>
-<span class="co"># a custom function within `text_transform()`;</span>
-<span class="co"># here `x` represents a character vector defined</span>
-<span class="co"># in the `cells_body()` function</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>)),
-    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) {
-
-      <span class="co"># The first character of `x` always</span>
-      <span class="co"># indicates the number of transmission speeds</span>
-      <span class="no">speed</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">1</span>, <span class="fl">1</span>)
-
-      <span class="co"># We can carefully determine which transmission</span>
-      <span class="co"># type we have in `x` with a `dplyr::case_when()`</span>
-      <span class="co"># statement</span>
-      <span class="no">type</span> <span class="kw">&lt;-</span>
-        <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/case_when.html">case_when</a></span>(
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"am"</span> ~ <span class="st">"Automatic/Manual"</span>,
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"m"</span> ~ <span class="st">"Manual"</span>,
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"a"</span> ~ <span class="st">"Automatic"</span>,
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"dd"</span> ~ <span class="st">"Direct Drive"</span>
-        )
-
-      <span class="co"># Let's paste together the `speed` and `type`</span>
-      <span class="co"># vectors to create HTML text replacing `x`</span>
-      <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">speed</span>, <span class="st">" Speed&lt;br&gt;&lt;em&gt;"</span>, <span class="no">type</span>, <span class="st">"&lt;/em&gt;"</span>)
-    }
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
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-  margin: 0px;
-  font-size: 90%;
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-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
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-}
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-  font-size: 90%;
-  padding: 4px;
-}
-
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-  text-align: left;
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-  font-weight: bold;
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-  font-style: italic;
-}
-
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-  font-size: 65%;
-}
-
-#gcnqemjpsc .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="gcnqemjpsc" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Performance</span>
-      </th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">$140,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">$129,900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
-      <td class="gt_row gt_right">$1,416,362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">$397,500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">$95,895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">$447,000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">$156,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">$101,770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="table-header-title-and-subtitle" class="section level3">
-<h3 class="hasAnchor">
-<a href="#table-header-title-and-subtitle" class="anchor"></a>Table Header: Title and Subtitle</h3>
-<p>The <code><a href="../reference/tab_header.html">tab_header()</a></code> function allows us to place a table title and, optionally, a subtitle at the top of the display table. It’s generally a good idea to have both in a table, where the subtitle provides additional information (though that isn’t quite the case in our example below).</p>
-<div class="sourceCode" id="cb13"><html><body><pre class="r"><span class="co"># Add a table title and subtitle; we can use</span>
-<span class="co"># markdown with the `md()` helper function</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The Cars of **gtcars**"</span>),
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"These are some fine automobiles"</span>
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
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-  padding: 8px;
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-</style>
-<div id="vuoznuokzk" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="8" class="gt_heading gt_title gt_font_normal" style>The Cars of <strong>gtcars</strong>
-</th>
-    </tr>
-<tr>
-<th colspan="8" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>These are some fine automobiles</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Performance</span>
-      </th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP</th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">$140,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">$129,900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
-      <td class="gt_row gt_right">$1,416,362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">$397,500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">$95,895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">$447,000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">$156,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">$101,770</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="adding-a-source-citation" class="section level3">
-<h3 class="hasAnchor">
-<a href="#adding-a-source-citation" class="anchor"></a>Adding a Source Citation</h3>
-<p>A <em>source note</em> can be added below the display table using the <code><a href="../reference/tab_source_note.html">tab_source_note()</a></code> function. We can even add multiple source notes with multiple calls of that function. Here, we supply a web URL and by using Markdown (with <code><a href="../reference/md.html">md()</a></code>) it’s easy to create a link to the source of the data.</p>
-<div class="sourceCode" id="cb14"><html><body><pre class="r"><span class="co"># Add a source note to the bottom of the table; this</span>
-<span class="co"># appears below the footnotes</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">tab</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
-    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(
-      <span class="st">"Source: Various pages within the Edmonds website."</span>)
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
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-<thead class="gt_header">
-<tr>
-<th colspan="8" class="gt_heading gt_title gt_font_normal" style>The Cars of <strong>gtcars</strong>
-</th>
-    </tr>
-<tr>
-<th colspan="8" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>These are some fine automobiles</th>
-    </tr>
-</thead>
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-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
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-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
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-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">$140,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">$129,900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
-      <td class="gt_row gt_right">$1,416,362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">$397,500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">$95,895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">$447,000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">$156,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">$101,770</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes"><tr>
-<td class="gt_sourcenote" colspan="8">Source: Various pages within the Edmonds website.</td>
-    </tr></tfoot>
-</table></div>
-</div>
-<div id="using-the-complete-gtcars-table-and-adding-footnotes" class="section level3">
-<h3 class="hasAnchor">
-<a href="#using-the-complete-gtcars-table-and-adding-footnotes" class="anchor"></a>Using the Complete <code>gtcars</code> table and Adding Footnotes</h3>
-<p>Let’s bring it all together by putting together all the statements we developed for <code>gtcars_8</code>, and applying that to the complete <code>gtcars</code> dataset. At the same time, we’ll add a few interesting footnotes and our specific requirements for footnoting are:</p>
-<pre><code>a. identifying the car with the best gas mileage (city)
-b. identifying the car with the highest horsepower
-c. stating the currency of the MSRP</code></pre>
-<p>The <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> function expects note text for the <code>footnote</code> argument, and locations for where the footnote mark should be attached. It will handle the placement of the footnote mark and also place the footnote in the footnotes area. Here, we’ll use the <code><a href="../reference/cells_body.html">cells_body()</a></code> <em>location helper</em> function. There are several location helper functions for targeting all parts of the table (e.g,. <code><a href="../reference/cells_body.html">cells_body()</a></code>, <code><a href="../reference/cells_stub.html">cells_stub()</a></code>, etc.). Each <em>location helper</em> has their own interface for targeting cells so refer to the documentation for examples of how they work in practice.</p>
-<p>What <code><a href="../reference/cells_body.html">cells_body()</a></code> expects is <code>columns</code> (column names, which can be conveniently provided in <code><a href="https://dplyr.tidyverse.org/reference/vars.html">vars()</a></code>) and <code>rows</code> (which can be a vector of row names or row indices). The <code><a href="../reference/cells_stub.html">cells_stub()</a></code> location helper only expects a vector of <code>rows</code>. For <code><a href="../reference/cells_column_labels.html">cells_column_labels()</a></code>, we can either provided targeted column labels in the <code>columns</code> argument or spanner column labels in the <code>groups</code> argument. Here, we are targeting a footnote to the <code>msrp</code> column label so we will use <code>columns = vars(msrp)</code>.</p>
-<p>In terms of structuring the code, we’re taking all the previous statements and putting those in first. It should be noted that the order of the statements does not matter to the end result, we could also put in all of the <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> statements first (again, any in order) and expect the same output table.</p>
-<div class="sourceCode" id="cb16"><html><body><pre class="r"><span class="co"># Use dplyr functions to get the car with the best city gas mileage;</span>
-<span class="co"># this will be used to target the correct cell for a footnote</span>
-<span class="no">best_gas_mileage_city</span> <span class="kw">&lt;-</span>
-  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="fu">desc</span>(<span class="no">mpg_c</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/slice.html">slice</a></span>(<span class="fl">1</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(<span class="no">car</span>)
-
-<span class="co"># Use dplyr functions to get the car with the highest horsepower</span>
-<span class="co"># this will be used to target the correct cell for a footnote</span>
-<span class="no">highest_horsepower</span> <span class="kw">&lt;-</span>
-  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="fu">desc</span>(<span class="no">hp</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/slice.html">slice</a></span>(<span class="fl">1</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/pull.html">pull</a></span>(<span class="no">car</span>)
-
-<span class="co"># Create a display table with `gtcars`, using all of the previous</span>
-<span class="co"># statements piped together + additional `tab_footnote()` stmts</span>
-<span class="no">tab</span> <span class="kw">&lt;-</span>
-  <span class="no">gtcars</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(
-    <span class="fu"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="no">ctry_origin</span>, <span class="kw">levels</span> <span class="kw">=</span> <span class="no">order_countries</span>),
-    <span class="no">mfr</span>, <span class="fu">desc</span>(<span class="no">msrp</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">car</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">mfr</span>, <span class="no">model</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">mfr</span>, -<span class="no">model</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">ctry_origin</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"car"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_hide.html">cols_hide</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>, <span class="no">bdy_style</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_move.html">cols_move</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
-    <span class="kw">after</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
-    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Performance"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>, <span class="no">hp</span>, <span class="no">hp_rpm</span>, <span class="no">trq</span>, <span class="no">trq_rpm</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">mpg_h</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_h</span>),
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}c&lt;br&gt;{2}h"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp</span>, <span class="no">hp_rpm</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp_rpm</span>),
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq</span>, <span class="no">trq_rpm</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trq_rpm</span>),
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{1}&lt;br&gt;@{2}rpm"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
-    <span class="kw">mpg_c</span> <span class="kw">=</span> <span class="st">"MPG"</span>,
-    <span class="kw">hp</span> <span class="kw">=</span> <span class="st">"HP"</span>,
-    <span class="kw">trq</span> <span class="kw">=</span> <span class="st">"Torque"</span>,
-    <span class="kw">year</span> <span class="kw">=</span> <span class="st">"Year"</span>,
-    <span class="kw">trim</span> <span class="kw">=</span> <span class="st">"Trim"</span>,
-    <span class="kw">trsmn</span> <span class="kw">=</span> <span class="st">"Transmission"</span>,
-    <span class="kw">msrp</span> <span class="kw">=</span> <span class="st">"MSRP"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_align.html">cols_align</a></span>(
-    <span class="kw">align</span> <span class="kw">=</span> <span class="st">"center"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_style.html">tab_style</a></span>(
-    <span class="kw">style</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cell_text.html">cell_text</a></span>(<span class="kw">size</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">12</span>)),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trim</span>, <span class="no">trsmn</span>, <span class="no">mpg_c</span>, <span class="no">hp</span>, <span class="no">trq</span>)
-    )
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">trsmn</span>)),
-    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) {
-
-      <span class="no">speed</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">1</span>, <span class="fl">1</span>)
-
-      <span class="no">type</span> <span class="kw">&lt;-</span>
-        <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/case_when.html">case_when</a></span>(
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"am"</span> ~ <span class="st">"Automatic/Manual"</span>,
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"m"</span> ~ <span class="st">"Manual"</span>,
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">2</span>) <span class="kw">==</span> <span class="st">"a"</span> ~ <span class="st">"Automatic"</span>,
-          <span class="fu"><a href="https://rdrr.io/r/base/substr.html">substr</a></span>(<span class="no">x</span>, <span class="fl">2</span>, <span class="fl">3</span>) <span class="kw">==</span> <span class="st">"dd"</span> ~ <span class="st">"Direct Drive"</span>
-        )
-
-      <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">speed</span>, <span class="st">" Speed&lt;br&gt;&lt;em&gt;"</span>, <span class="no">type</span>, <span class="st">"&lt;/em&gt;"</span>)
-    }
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The Cars of **gtcars**"</span>),
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"These are some fine automobiles"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
-    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(
-      <span class="st">"Source: Various pages within the Edmonds website."</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Best gas mileage (city) of all the **gtcars**."</span>),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mpg_c</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">best_gas_mileage_city</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The highest horsepower of all the **gtcars**."</span>),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">hp</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">highest_horsepower</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"All prices in U.S. dollars (USD)."</span>,
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_column_labels.html">cells_column_labels</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>))
-  )
-
-<span class="co"># Show the table</span>
-<span class="no">tab</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#wtflhoisbj .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
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-<div id="wtflhoisbj" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="8" class="gt_heading gt_title gt_font_normal" style>The Cars of <strong>gtcars</strong>
-</th>
-    </tr>
-<tr>
-<th colspan="8" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>These are some fine automobiles</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Year</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Trim</th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">Transmission</th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Performance</span>
-      </th>
-      <th class="gt_col_heading gt_center gt_columns_bottom_border" rowspan="2" colspan="1">MSRP<sup class="gt_footnote_marks">1</sup>
-</th>
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-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">MPG</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">HP</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Torque</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Germany</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Audi R8</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">4.2 (Manual) Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>20h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">430<br>@7900rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">317<br>@4500rpm</td>
-      <td class="gt_row gt_right">$115,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Audi S8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>25h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">520<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">481<br>@1700rpm</td>
-      <td class="gt_row gt_right">$114,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Audi RS 7</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Quattro Hatchback</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>25h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">560<br>@5700rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">516<br>@1750rpm</td>
-      <td class="gt_row gt_right">$108,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Audi S7</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Prestige quattro Hatchback</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">17c<br>27h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">450<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1400rpm</td>
-      <td class="gt_row gt_right">$82,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Audi S6</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Premium Plus quattro Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">18c<br>27h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">450<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1400rpm</td>
-      <td class="gt_row gt_right">$70,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW i8</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Mega World Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">28c<br>29h<sup class="gt_footnote_marks">2</sup>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">357<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">420<br>@3700rpm</td>
-      <td class="gt_row gt_right">$140,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW M6</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">560<br>@6000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">500<br>@1500rpm</td>
-      <td class="gt_row gt_right">$113,400</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW M5</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">560<br>@6000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">500<br>@1500rpm</td>
-      <td class="gt_row gt_right">$94,100</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW 6-Series</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">640 I Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>30h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">315<br>@5800rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">330<br>@1400rpm</td>
-      <td class="gt_row gt_right">$77,300</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">BMW M4</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">17c<br>24h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">425<br>@5500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1850rpm</td>
-      <td class="gt_row gt_right">$65,700</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz AMG GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">S Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">503<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">479<br>@1750rpm</td>
-      <td class="gt_row gt_right">$129,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Mercedes-Benz SL-Class</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">SL400 Convertible</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>27h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">329<br>@5250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">354<br>@1600rpm</td>
-      <td class="gt_row gt_right">$85,050</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Porsche 911</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Carrera Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>28h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">350<br>@7400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">287<br>@5600rpm</td>
-      <td class="gt_row gt_right">$84,300</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Porsche Panamera</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">18c<br>28h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">310<br>@6200rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">295<br>@3750rpm</td>
-      <td class="gt_row gt_right">$78,100</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Porsche 718 Boxster</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Convertible</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>28h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">300<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">280<br>@1950rpm</td>
-      <td class="gt_row gt_right">$56,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Porsche 718 Cayman</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">20c<br>29h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">300<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">280<br>@1950rpm</td>
-      <td class="gt_row gt_right">$53,900</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Italy</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari LaFerrari</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">949<br>@9000rpm<sup class="gt_footnote_marks">3</sup>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">664<br>@6750rpm</td>
-      <td class="gt_row gt_right">$1,416,362</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari F12Berlinetta</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">731<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">509<br>@6000rpm</td>
-      <td class="gt_row gt_right">$319,995</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari GTC4Lusso</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>17h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">680<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">514<br>@5750rpm</td>
-      <td class="gt_row gt_right">$298,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari FF</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>16h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">652<br>@8000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">504<br>@6000rpm</td>
-      <td class="gt_row gt_right">$295,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari 458 Speciale</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>17h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">597<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6000rpm</td>
-      <td class="gt_row gt_right">$291,744</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari 458 Spider</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>17h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">562<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6000rpm</td>
-      <td class="gt_row gt_right">$263,553</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari 488 GTB</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">661<br>@8000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">561<br>@3000rpm</td>
-      <td class="gt_row gt_right">$245,400</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari 458 Italia</td>
-      <td class="gt_row gt_right">2014</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>17h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">562<br>@9000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6000rpm</td>
-      <td class="gt_row gt_right">$233,509</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ferrari California</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Convertible</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>23h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">553<br>@7500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">557<br>@4750rpm</td>
-      <td class="gt_row gt_right">$198,973</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Aventador</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 700-4 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">700<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">507<br>@5500rpm</td>
-      <td class="gt_row gt_right">$397,500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Huracan</td>
-      <td class="gt_row gt_right">2015</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 610-4 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>20h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">610<br>@8250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">413<br>@6500rpm</td>
-      <td class="gt_row gt_right">$237,250</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lamborghini Gallardo</td>
-      <td class="gt_row gt_right">2014</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">LP 550-2 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>20h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@8000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">398<br>@6500rpm</td>
-      <td class="gt_row gt_right">$191,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Maserati Granturismo</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Sport Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>21h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">454<br>@7600rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">384<br>@4750rpm</td>
-      <td class="gt_row gt_right">$132,825</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Maserati Quattroporte</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">S Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>23h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">404<br>@5500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">406<br>@1500rpm</td>
-      <td class="gt_row gt_right">$99,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Maserati Ghibli</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">17c<br>24h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">345<br>@5250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">369<br>@1750rpm</td>
-      <td class="gt_row gt_right">$70,600</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United States</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Chevrolet Corvette</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Z06 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">650<br>@6400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">650<br>@3600rpm</td>
-      <td class="gt_row gt_right">$88,345</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Dodge Viper</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">GT Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">645<br>@5000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">600<br>@5000rpm</td>
-      <td class="gt_row gt_right">$95,895</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Ford GT</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">11c<br>18h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">647<br>@6250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">550<br>@5900rpm</td>
-      <td class="gt_row gt_right">$447,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Tesla Model S</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">75D</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">1  Speed<br><em> Direct Drive </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">NAc<br>NAh</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">259<br>@6100rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">243<br>@NArpm</td>
-      <td class="gt_row gt_right">$74,500</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">Japan</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Acura NSX</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">9  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">21c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">573<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">476<br>@2000rpm</td>
-      <td class="gt_row gt_right">$156,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nissan GT-R</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Premium Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>22h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">545<br>@6400rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">436<br>@3200rpm</td>
-      <td class="gt_row gt_right">$101,770</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="8" class="gt_group_heading">United Kingdom</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Aston Martin Vanquish</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>21h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">568<br>@6650rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">465<br>@5500rpm</td>
-      <td class="gt_row gt_right">$287,250</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Aston Martin DB11</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>21h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">608<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">516<br>@1500rpm</td>
-      <td class="gt_row gt_right">$211,195</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Aston Martin Rapide S</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Sedan</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">14c<br>21h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">552<br>@6650rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">465<br>@5500rpm</td>
-      <td class="gt_row gt_right">$205,300</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Aston Martin Vantage</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">V8 GT (Manual) Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">430<br>@7300rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">361<br>@5000rpm</td>
-      <td class="gt_row gt_right">$103,300</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Bentley Continental GT</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">V8 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic/Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">15c<br>25h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">500<br>@6000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">487<br>@1700rpm</td>
-      <td class="gt_row gt_right">$198,500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Jaguar F-Type</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base (Manual) Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>24h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">340<br>@6500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">332<br>@3500rpm</td>
-      <td class="gt_row gt_right">$65,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Lotus Evora</td>
-      <td class="gt_row gt_right">2017</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">2+2 Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">6  Speed<br><em> Manual </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>24h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">400<br>@7000rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">302<br>@3500rpm</td>
-      <td class="gt_row gt_right">$91,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">McLaren 570</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">7  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">16c<br>23h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">570<br>@7500rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">443<br>@5000rpm</td>
-      <td class="gt_row gt_right">$184,900</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Rolls-Royce Dawn</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Convertible</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">12c<br>19h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">563<br>@5250rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">575<br>@1500rpm</td>
-      <td class="gt_row gt_right">$335,000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Rolls-Royce Wraith</td>
-      <td class="gt_row gt_right">2016</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">Base Coupe</td>
-      <td class="gt_row gt_left" style="font-size: 12px;">8  Speed<br><em> Automatic </em>
-</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">13c<br>21h</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">624<br>@5600rpm</td>
-      <td class="gt_row gt_center" style="font-size: 12px;">590<br>@1500rpm</td>
-      <td class="gt_row gt_right">$304,350</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes"><tr>
-<td class="gt_sourcenote" colspan="8">Source: Various pages within the Edmonds website.</td>
-    </tr></tfoot>
-<tfoot><tr class="gt_footnotes">
-<td colspan="8">
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>1</em>
-          </sup>
-           
-          All prices in U.S. dollars (USD).
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>2</em>
-          </sup>
-           
-          Best gas mileage (city) of all the <strong>gtcars</strong>.
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>3</em>
-          </sup>
-           
-          The highest horsepower of all the <strong>gtcars</strong>.
-          <br></p>
-      </td>
-    </tr></tfoot>
-</table></div>
-<p>That is it. The final table looks pretty good and conveys the additional information we planned for. That table can be used in a lot of different places like R Markdown, Shiny, email messages… wherever HTML is accepted.</p>
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diff --git a/docs/articles/creating-summary-lines.html b/docs/articles/creating-summary-lines.html
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-<p>We can use the <strong>gt</strong> <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function to insert summary rows into a table. There are two main types of summary rows: (1) groupwise summaries, and (2) the grand summary. The groupwise summaries operate on one or more row groups, which can themselves be generated in a variety of ways:</p>
-<ul>
-<li>with the <code><a href="../reference/gt.html">gt()</a></code> function’s <code>groupname_col</code> option</li>
-<li>using the <code><a href="../reference/tab_row_group.html">tab_row_group()</a></code> function on a gt object</li>
-<li>by passing in a grouped <code>tbl_df</code> object to <code><a href="../reference/gt.html">gt()</a></code> (using <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">dplyr::group_by()</a></code>)</li>
-</ul>
-<p>We generate the summary data through specification of aggregation functions. You choose how to format the values in the resulting summary cells by use of a formatter function (e.g, <code><a href="../reference/fmt_number.html">fmt_number()</a></code>) and any relevant options. These summary rows are automatically inserted within the relevant row groups (for groupwise summaries) or at the bottom of the table (as a grand summary), where each summary row is the result of a different aggregation function.</p>
-<div id="preparing-the-input-data-table" class="section level3">
-<h3 class="hasAnchor">
-<a href="#preparing-the-input-data-table" class="anchor"></a>Preparing the Input Data Table</h3>
-<p>Let’s use the <code>exibble</code> dataset (included in the <strong>gt</strong> package) to demonstrate how summary rows can be added. That table contains categorical columns named <code>row</code> and <code>group</code>, along several columns with varying data types. Here is a preview of the <code>exibble</code> dataset using solely the <code><a href="../reference/gt.html">gt()</a></code> function with no other options:</p>
-<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="no">exibble</span> <span class="kw">%&gt;%</span> <span class="fu"><a href="../reference/gt.html">gt</a></span>()</pre></body></html></div>
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-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">fctr</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">date</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">time</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">datetime</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">row</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">group</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_right">1.111e-01</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_center">one</td>
-      <td class="gt_row gt_left">2015-01-15</td>
-      <td class="gt_row gt_left">13:35</td>
-      <td class="gt_row gt_left">2018-01-01 02:22</td>
-      <td class="gt_row gt_right">49.950</td>
-      <td class="gt_row gt_left">row_1</td>
-      <td class="gt_row gt_left">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">2.222e+00</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_center">two</td>
-      <td class="gt_row gt_left">2015-02-15</td>
-      <td class="gt_row gt_left">14:40</td>
-      <td class="gt_row gt_left">2018-02-02 14:33</td>
-      <td class="gt_row gt_right">17.950</td>
-      <td class="gt_row gt_left">row_2</td>
-      <td class="gt_row gt_left">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">3.333e+01</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_center">three</td>
-      <td class="gt_row gt_left">2015-03-15</td>
-      <td class="gt_row gt_left">15:45</td>
-      <td class="gt_row gt_left">2018-03-03 03:44</td>
-      <td class="gt_row gt_right">1.390</td>
-      <td class="gt_row gt_left">row_3</td>
-      <td class="gt_row gt_left">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">4.444e+02</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_center">four</td>
-      <td class="gt_row gt_left">2015-04-15</td>
-      <td class="gt_row gt_left">16:50</td>
-      <td class="gt_row gt_left">2018-04-04 15:55</td>
-      <td class="gt_row gt_right">65100.000</td>
-      <td class="gt_row gt_left">row_4</td>
-      <td class="gt_row gt_left">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">5.550e+03</td>
-      <td class="gt_row gt_left">NA</td>
-      <td class="gt_row gt_center">five</td>
-      <td class="gt_row gt_left">2015-05-15</td>
-      <td class="gt_row gt_left">17:55</td>
-      <td class="gt_row gt_left">2018-05-05 04:00</td>
-      <td class="gt_row gt_right">1325.810</td>
-      <td class="gt_row gt_left">row_5</td>
-      <td class="gt_row gt_left">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">NA</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_center">six</td>
-      <td class="gt_row gt_left">2015-06-15</td>
-      <td class="gt_row gt_left">NA</td>
-      <td class="gt_row gt_left">2018-06-06 16:11</td>
-      <td class="gt_row gt_right">13.255</td>
-      <td class="gt_row gt_left">row_6</td>
-      <td class="gt_row gt_left">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">7.770e+05</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_center">seven</td>
-      <td class="gt_row gt_left">NA</td>
-      <td class="gt_row gt_left">19:10</td>
-      <td class="gt_row gt_left">2018-07-07 05:22</td>
-      <td class="gt_row gt_right">NA</td>
-      <td class="gt_row gt_left">row_7</td>
-      <td class="gt_row gt_left">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_right">8.880e+06</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_center">eight</td>
-      <td class="gt_row gt_left">2015-08-15</td>
-      <td class="gt_row gt_left">20:20</td>
-      <td class="gt_row gt_left">NA</td>
-      <td class="gt_row gt_right">0.440</td>
-      <td class="gt_row gt_left">row_8</td>
-      <td class="gt_row gt_left">grp_b</td>
-    </tr>
-</tbody>
-</table></div>
-<p>We’ll create a table stub with both row labels (using the <code>row</code> column) and row groups (using the <code>group</code> column). The end result will be a table organized with labeled rows that are grouped together (the row group labels identify each of the row groups). To make the examples a bit easier to follow, some of the columns in exibble will first be dropped through a <code><a href="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> statement.</p>
-<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Create a gt table using the `exibble` dataset</span>
-<span class="no">exibble_a</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="no">fctr</span>, <span class="no">date</span>, <span class="no">time</span>, <span class="no">datetime</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"row"</span>, <span class="kw">groupname_col</span> <span class="kw">=</span> <span class="st">"group"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_missing.html">fmt_missing</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">everything</a></span>())
-
-<span class="no">exibble_a</span></pre></body></html></div>
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-</style>
-<div id="mgboivgpsa" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1.111e-01</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">49.950</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_2</td>
-      <td class="gt_row gt_right">2.222e+00</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_right">17.950</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_3</td>
-      <td class="gt_row gt_right">3.333e+01</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_right">1.390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_4</td>
-      <td class="gt_row gt_right">4.444e+02</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">65100.000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5.550e+03</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">1325.810</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">13.255</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7.770e+05</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8.880e+06</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">0.440</td>
-    </tr>
-</tbody>
-</table></div>
-<p>There are two groups in this data table: <code>grp_a</code> and <code>grp_b</code>. This gives us flexibility to create both a grand summary and groupwise summary rows.</p>
-</div>
-<div id="generating-groupwise-summary-rows" class="section level3">
-<h3 class="hasAnchor">
-<a href="#generating-groupwise-summary-rows" class="anchor"></a>Generating Groupwise Summary Rows</h3>
-<p>Groupwise summary rows can be generated by using the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function and, importantly, through specifying the groups that will receive summary rows. We can provide a vector group names, as in <code><a href="https://rdrr.io/r/base/c.html">c("grp_a", "grp_b")</a></code>, or, use <code>TRUE</code> to signify that all groups should receive summary rows. Aside from the selection of groups, there is control over which columns are to used for the summary. Since each call to <code><a href="../reference/summary_rows.html">summary_rows()</a></code> only performs one set of aggregation functions, we may want specific aggregations for different subsets of columns.</p>
-<p>To make any sort of summary, we need to use functions that will perform the aggregation. We can provide base functions such as <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html">min()</a></code>, <code><a href="https://rdrr.io/r/base/Extremes.html">max()</a></code>, and more, within a <code><a href="https://rdrr.io/r/base/list.html">list()</a></code>. Each function provided will result in a summary row for each <code>group</code>.</p>
-<p>Because each function will yield a row, we need to be able to label that row. So, each summary row will receive a summary row label. We can provide our preferred names by naming the functions within the list (e.g, <code><a href="https://rdrr.io/r/base/list.html">list(average = "mean", total = "sum", SD = "sd")</a></code>).</p>
-<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Create groupwise summary rows for both</span>
-<span class="co"># groups (using `groups = TRUE`); use the</span>
-<span class="co"># `mean()`, `sum()`, and `sd()` functions</span>
-<span class="co"># (only for the `num` column)</span>
-<span class="no">exibble_b</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
-      <span class="kw">average</span> <span class="kw">=</span> <span class="st">"mean"</span>,
-      <span class="kw">total</span> <span class="kw">=</span> <span class="st">"sum"</span>,
-      <span class="kw">SD</span> <span class="kw">=</span> <span class="st">"sd"</span>)
-  )
-
-<span class="no">exibble_b</span></pre></body></html></div>
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-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
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-<td colspan="4" class="gt_group_heading">grp_a</td>
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-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1.111e-01</td>
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-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">120.02</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
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-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">480.06</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">SD</td>
-      <td class="gt_row gt_right gt_summary_row">216.79</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
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-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5.550e+03</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">1325.810</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">13.255</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7.770e+05</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8.880e+06</td>
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-      <td class="gt_row gt_right">0.440</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">average</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">SD</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-</tbody>
-</table></div>
-<p>We can specify the aggregation functions by use of function names in quotes (e.g., <code>"sum"</code>), as bare functions (e.g., <code>sum</code>), or as one-sided R formulas using a leading <code>~</code>. In the formula representation, a <code>.</code> serves as the data to be summarized, so we can use <code><a href="https://rdrr.io/r/base/sum.html">sum(., na.rm = TRUE)</a></code>. The use of named arguments is recommended as those names will serve as summary row labels (the labels can derived from the function names but only when not providing bare function names).</p>
-<p>Now that the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function has been somewhat explained, let’s look at how we can create groupwise summary rows for the <code>exibble_a</code> table. We’ll create summaries for both available groups (<code>groups = TRUE</code>) and use the <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code>, and <code><a href="https://rdrr.io/r/stats/sd.html">sd()</a></code> functions with the <em>function-name-in-quotes</em> method (and this will only pertain to the <code>num</code> column).</p>
-<p>In the previous example we have an <code>NA</code> value in the <code>num/row_6</code> cell, and so we get <code>NA</code> outputs from <code><a href="https://rdrr.io/r/base/mean.html">mean()</a></code>, <code><a href="https://rdrr.io/r/base/sum.html">sum()</a></code>, and <code><a href="https://rdrr.io/r/stats/sd.html">sd()</a></code> in <code>grp_b</code>’s summary rows (which are replaced with em dashes, itself controllable through the <code>missing_text</code> option). To avoid this, let’s rewrite the above using the <em>names-and-formulae</em> method.</p>
-<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># Create groupwise summary rows for both</span>
-<span class="co"># groups (using `groups = TRUE`); we will</span>
-<span class="co"># use names and formulas this time in `fns`</span>
-<span class="no">exibble_c</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
-      <span class="kw">avg</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/mean.html">mean</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
-      <span class="kw">total</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
-      <span class="kw">s.d.</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/stats/sd.html">sd</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>)
-    )
-  )
-
-<span class="no">exibble_c</span></pre></body></html></div>
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-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">216.79</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
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-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">1325.810</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">13.255</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7.770e+05</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
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-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">0.440</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,220,850.00</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">9,662,550.00</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">4,916,123.25</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-</tbody>
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-<p>Here we see that summary rows were created for both groups. However, the output of the summary row data is quite different than that of the cell data. The <code>formatter</code> argument (and extra <code>...</code> arguments) allows for use of any of the <code>fmt_*()</code> functions that we’d normally use to format cell data. In this example (another rewrite of the above), the cell data in the <code>num</code> column is formatted in scientific notation and the resulting summary cell data is also formatted in the same way (including the options of <code>decimals = 3</code>).</p>
-<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Define a named list of aggregation</span>
-<span class="co"># functions and summary row labels</span>
-<span class="no">fns_labels</span> <span class="kw">&lt;-</span>
-  <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
-    <span class="kw">avg</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/mean.html">mean</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
-    <span class="kw">total</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>),
-    <span class="kw">s.d.</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/stats/sd.html">sd</a></span>(<span class="no">.</span>, <span class="kw">na.rm</span> <span class="kw">=</span> <span class="fl">TRUE</span>)
-  )
-
-<span class="co"># Create groupwise summary rows as</span>
-<span class="co"># before, supply `fns_labels` to `fns`,</span>
-<span class="co"># and format the cell summary data</span>
-<span class="no">exibble_d</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_scientific.html">fmt_scientific</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_scientific</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
-  )
-
-<span class="no">exibble_d</span></pre></body></html></div>
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-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1.111 × 10<sup class="gt_super">−1</sup>
-</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">49.950</td>
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-      <td class="gt_row gt_right">2.222</td>
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-      <td class="gt_row gt_right">17.950</td>
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-<tr>
-<td class="gt_row gt_left gt_stub">row_3</td>
-      <td class="gt_row gt_right">3.333 × 10<sup class="gt_super">1</sup>
-</td>
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-      <td class="gt_row gt_right">4.444 × 10<sup class="gt_super">2</sup>
-</td>
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-      <td class="gt_row gt_right">65100.000</td>
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-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1.200 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">4.801 × 10<sup class="gt_super">2</sup>
-</td>
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-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">2.168 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
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-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5.550 × 10<sup class="gt_super">3</sup>
-</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">1325.810</td>
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-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">13.255</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7.770 × 10<sup class="gt_super">5</sup>
-</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8.880 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">0.440</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3.221 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">9.663 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">4.916 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
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-<p>The input to <code>fns</code> is very permissive in regard to how the functions are defined. It is entirely valid to provide functions in the various forms shown earlier such that <code><a href="https://rdrr.io/r/base/list.html">list("sum", avg = ~mean(., na.rm = TRUE), SD = "sd")</a></code> will be correctly interpreted. It is recommended to use formula notation.</p>
-<p>The default for <code>formatter</code> is set to <code>fmt_number</code> which is a sensible default for many scenarios. The setting of argument values for a particular formatter can be done in the <code>...</code> area of the function call (as was done above for the <code>decimals</code> argument).</p>
-</div>
-<div id="using-multiple-calls-of-summary_rows" class="section level3">
-<h3 class="hasAnchor">
-<a href="#using-multiple-calls-of-summary_rows" class="anchor"></a>Using Multiple Calls of <code>summary_rows()</code>
-</h3>
-<p>We can re-use summary row labels and fill the otherwise empty summary cells with similar aggregations but perhaps with different formatting options. Here’s an example where the <code>currency</code> column contains aggregate values that share the same summary rows as for the <code>num</code> column, adds two more rows, and uses currency formatting:</p>
-<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Create groupwise summary rows as</span>
-<span class="co"># before, supply `fns_labels` to `fns`,</span>
-<span class="co"># and format the cell summary data</span>
-<span class="no">exibble_e</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_scientific.html">fmt_scientific</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
-    ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_scientific</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="st">"grp_a"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(
-      <span class="no">fns_labels</span>,
-      <span class="kw">min</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">min</a></span>(<span class="no">.</span>),
-      <span class="kw">max</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">max</a></span>(<span class="no">.</span>)),
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
-  )
-
-<span class="no">exibble_e</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
-<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
-<span class="co">#&gt; * ...</span></pre></body></html></div>
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-  margin-top: 0;
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-
-#vwzdspbffd .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
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-  border-top-style: solid;
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-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#vwzdspbffd .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
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-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#vwzdspbffd .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#vwzdspbffd .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#vwzdspbffd .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#vwzdspbffd .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#vwzdspbffd .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#vwzdspbffd .gt_footnotes {
-  color: #333333;
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-  border-bottom-style: none;
-  border-bottom-width: 2px;
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-  border-left-width: 2px;
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-  border-right-style: none;
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-  border-right-color: #D3D3D3;
-}
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-#vwzdspbffd .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
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-#vwzdspbffd .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
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-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#vwzdspbffd .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#vwzdspbffd .gt_left {
-  text-align: left;
-}
-
-#vwzdspbffd .gt_center {
-  text-align: center;
-}
-
-#vwzdspbffd .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
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-#vwzdspbffd .gt_font_normal {
-  font-weight: normal;
-}
-
-#vwzdspbffd .gt_font_bold {
-  font-weight: bold;
-}
-
-#vwzdspbffd .gt_font_italic {
-  font-style: italic;
-}
-
-#vwzdspbffd .gt_super {
-  font-size: 65%;
-}
-
-#vwzdspbffd .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="vwzdspbffd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1.111 × 10<sup class="gt_super">−1</sup>
-</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">€49.95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_2</td>
-      <td class="gt_row gt_right">2.222</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_right">€17.95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_3</td>
-      <td class="gt_row gt_right">3.333 × 10<sup class="gt_super">1</sup>
-</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_right">€1.39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_4</td>
-      <td class="gt_row gt_right">4.444 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">€65,100.00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1.200 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16,292.32</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">4.801 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65,169.29</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">2.168 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€32,538.46</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€1.39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65,100.00</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5.550 × 10<sup class="gt_super">3</sup>
-</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">€1,325.81</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">€13.26</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7.770 × 10<sup class="gt_super">5</sup>
-</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8.880 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">€0.44</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3.221 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">9.663 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">4.916 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-</tbody>
-</table></div>
-<p>A thing to again note in the above example is that even though two independent calls of <code><a href="../reference/summary_rows.html">summary_rows()</a></code> were made, summary data within common summary row names were ‘squashed’ together, thus avoiding the fragmentation of summary rows. Put another way, we don’t create additional summary rows across separate calls if we are referencing the same summary row labels. If the summary row labels provided in <code>fns</code> were to be different across columns however, additional summary rows would be produced even if the types of data aggregations were to be functionally equivalent.</p>
-<p>We can also store these argument values as local variables and pass them in both separate <code>fmt_*number*()</code> calls also to arguments within <code><a href="../reference/summary_rows.html">summary_rows()</a></code> calls. This is useful for standardizing formatting parameters across different table cell types. Here’s an example of that, which additional passes the <code>fr_BE</code> locale to all functions that take a <code>locale</code> value.</p>
-<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># Provide common formatting parameters to a list</span>
-<span class="co"># object named `formats`; the number of decimal</span>
-<span class="co"># places will be `2` and the locale is "fr_BE"</span>
-<span class="no">formats</span> <span class="kw">&lt;-</span>
-  <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">3</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="st">"fr_BE"</span>,
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
-  )
-
-<span class="co"># Format the `num` and `currency` columns</span>
-<span class="co"># (using the values stored in `formats`);</span>
-<span class="co"># when generating summary rows we can also</span>
-<span class="co"># supply formatter options from this list</span>
-<span class="no">exibble_f</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_scientific.html">fmt_scientific</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">decimals</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">currency</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
-    ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_scientific</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">decimals</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="st">"grp_a"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(
-      <span class="no">fns_labels</span>,
-      <span class="kw">min</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">min</a></span>(<span class="no">.</span>),
-      <span class="kw">max</span> <span class="kw">=</span> ~<span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">max</a></span>(<span class="no">.</span>)),
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">currency</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
-  )
-
-<span class="no">exibble_f</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
-<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
-<span class="co">#&gt; * ...</span></pre></body></html></div>
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-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#rvsmkcqcok .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#rvsmkcqcok .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#rvsmkcqcok .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#rvsmkcqcok .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#rvsmkcqcok .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#rvsmkcqcok .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#rvsmkcqcok .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#rvsmkcqcok .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#rvsmkcqcok .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#rvsmkcqcok .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#rvsmkcqcok .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#rvsmkcqcok .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#rvsmkcqcok .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#rvsmkcqcok .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#rvsmkcqcok .gt_left {
-  text-align: left;
-}
-
-#rvsmkcqcok .gt_center {
-  text-align: center;
-}
-
-#rvsmkcqcok .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#rvsmkcqcok .gt_font_normal {
-  font-weight: normal;
-}
-
-#rvsmkcqcok .gt_font_bold {
-  font-weight: bold;
-}
-
-#rvsmkcqcok .gt_font_italic {
-  font-style: italic;
-}
-
-#rvsmkcqcok .gt_super {
-  font-size: 65%;
-}
-
-#rvsmkcqcok .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="rvsmkcqcok" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1,111 × 10<sup class="gt_super">−1</sup>
-</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">€49,95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_2</td>
-      <td class="gt_row gt_right">2,222</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_right">€17,95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_3</td>
-      <td class="gt_row gt_right">3,333 × 10<sup class="gt_super">1</sup>
-</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_right">€1,39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_4</td>
-      <td class="gt_row gt_right">4,444 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">€65 100,00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1,200 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16 292,32</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">4,801 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65 169,29</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">2,168 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€32 538,46</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€1,39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65 100,00</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5,550 × 10<sup class="gt_super">3</sup>
-</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">€1 325,81</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">€13,26</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7,770 × 10<sup class="gt_super">5</sup>
-</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8,880 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">€0,44</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,221 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">9,663 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">4,916 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-</tbody>
-</table></div>
-<p>Passing in parameters like this is useful, especially if there are larger numbers of columns. When we store formatting parameters outside of the <code><a href="../reference/gt.html">gt()</a></code> pipeline, we separate our concerns between data structuring and data formatting. Putting styles and options into objects becomes more important if we intend to centralize formatting options for reuse.</p>
-</div>
-<div id="creating-a-grand-summary" class="section level3">
-<h3 class="hasAnchor">
-<a href="#creating-a-grand-summary" class="anchor"></a>Creating a Grand Summary</h3>
-<p>A grand summary aggregates column data regardless of the groups within the data. Grand summaries can also be created for <strong>gt</strong> tables that don’t have row groups, or, don’t have a stub. Finally, we can create a table that has both groupwise summaries and a grand summary.</p>
-<p>Let’s keep it simple and create group summary rows on a table without a stub. We’ll use <code>exibble</code> dataset for this once more. A few <code>exibble</code> columns are <code>select()</code>ed, passed to <code><a href="../reference/gt.html">gt()</a></code>, and then <code><a href="../reference/summary_rows.html">summary_rows()</a></code>. Notice that, in the resulting table, a stub is created just for the summary row labels (they have to go somewhere).</p>
-<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># Create a simple grand summary on a gt</span>
-<span class="co"># table that contains no stub</span>
-<span class="no">exibble_g</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="no">num</span>, <span class="no">char</span>, <span class="no">currency</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>, <span class="no">currency</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>
-  )
-
-<span class="no">exibble_g</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#uyexgsegin .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#uyexgsegin .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#uyexgsegin .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#uyexgsegin .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#uyexgsegin .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#uyexgsegin .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#uyexgsegin .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#uyexgsegin .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#uyexgsegin .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#uyexgsegin .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#uyexgsegin .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#uyexgsegin .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#uyexgsegin .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#uyexgsegin .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#uyexgsegin .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#uyexgsegin .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#uyexgsegin .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#uyexgsegin .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
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-}
-
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-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
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-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
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-
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-  font-size: 90%;
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-}
-
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-</style>
-<div id="uyexgsegin" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">1.111e-01</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">49.950</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">2.222e+00</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_right">17.950</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">3.333e+01</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_right">1.390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">4.444e+02</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">65100.000</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">5.550e+03</td>
-      <td class="gt_row gt_left">NA</td>
-      <td class="gt_row gt_right">1325.810</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">NA</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">13.255</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">7.770e+05</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">NA</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub"></td>
-      <td class="gt_row gt_right">8.880e+06</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">0.440</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">avg</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">1,380,432.87</td>
-      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">9,501.26</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row">total</td>
-      <td class="gt_row gt_right gt_grand_summary_row">9,663,030.06</td>
-      <td class="gt_row gt_left gt_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row">66,508.79</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_grand_summary_row">3,319,613.32</td>
-      <td class="gt_row gt_left gt_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row">24,521.60</td>
-    </tr>
-</tbody>
-</table></div>
-<p>By default, <code>groups</code> in the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function is set to <code>NULL</code> and will produce a grand summary.</p>
-<p>A grand summary can be used in conjunction with groupwise summaries. Here’s an mashup where both types are present:</p>
-<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># Using the table in `exibble_f`, create</span>
-<span class="co"># additional grand summary rows (using two</span>
-<span class="co"># separate calls of `grand_summary_rows()`</span>
-<span class="co"># since the formatting</span>
-<span class="co"># will be different)</span>
-<span class="no">exibble_h</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_f</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_number</span>,
-    <span class="kw">suffixing</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="no">fns_labels</span>,
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
-    <span class="kw">suffixing</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">locale</span> <span class="kw">=</span> <span class="no">formats</span>$<span class="no">locale</span>
-  )
-
-<span class="no">exibble_h</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...1`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...2`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY3` -&gt; `::GRAND_SUMMARY3...3`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...4`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...5`</span>
-<span class="co">#&gt; * ...</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
-<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
-<span class="co">#&gt; * ...</span></pre></body></html></div>
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-
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-
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-</style>
-<div id="fzzordqyyd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1,111 × 10<sup class="gt_super">−1</sup>
-</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">€49,95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_2</td>
-      <td class="gt_row gt_right">2,222</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_right">€17,95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_3</td>
-      <td class="gt_row gt_right">3,333 × 10<sup class="gt_super">1</sup>
-</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_right">€1,39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_4</td>
-      <td class="gt_row gt_right">4,444 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">€65 100,00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1,200 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16 292,32</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">4,801 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65 169,29</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">2,168 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€32 538,46</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€1,39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65 100,00</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5,550 × 10<sup class="gt_super">3</sup>
-</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">€1 325,81</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">€13,26</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7,770 × 10<sup class="gt_super">5</sup>
-</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8,880 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">€0,44</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,221 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">9,663 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">4,916 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">avg</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">1,38M</td>
-      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">$9,50K</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row">total</td>
-      <td class="gt_row gt_right gt_grand_summary_row">9,66M</td>
-      <td class="gt_row gt_left gt_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row">$66,51K</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_grand_summary_row">3,32M</td>
-      <td class="gt_row gt_left gt_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row">$24,52K</td>
-    </tr>
-</tbody>
-</table></div>
-<p>Note that the grand summary has a double line separating it from groupwise summary that’s part of <code>grp_b</code>. If this default styling appears to be too subtle, we can elect to add further styling to both groupwise summaries and the grand summary by using <code><a href="../reference/tab_options.html">tab_options()</a></code>.</p>
-</div>
-<div id="adding-some-style-to-the-summary-cells" class="section level3">
-<h3 class="hasAnchor">
-<a href="#adding-some-style-to-the-summary-cells" class="anchor"></a>Adding Some Style to the Summary Cells</h3>
-<p>While the summary cells (both groupwise and grand) have a distinct appearance that sets them apart from the data cells, there’s always the option to modify their appearance. We can use the <code><a href="../reference/tab_options.html">tab_options()</a></code> function to perform these customizations. Here are the options specific to the summary cells (for groupwise summaries) and the grand summary cells:</p>
-<ul>
-<li>
-<code>summary_row.background.color</code> &amp; <code>grand_summary_row.background.color</code>
-</li>
-<li>
-<code>summary_row.padding</code> &amp; <code>grand_summary_row.padding</code>
-</li>
-<li>
-<code>summary_row.text_transform</code> &amp; <code>grand_summary_row.text_transform</code>
-</li>
-</ul>
-<p>We can also target the summary cells and grand summary cells with the location helper functions <code><a href="../reference/cells_summary.html">cells_summary()</a></code> and <code><a href="../reference/cells_grand_summary.html">cells_grand_summary()</a></code>. This is important for adding footnotes with <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> and for setting styles with <code><a href="../reference/tab_style.html">tab_style()</a></code> (both have the <code>locations</code> argument).</p>
-<p>Here is an example that uses multiple calls of <code><a href="../reference/tab_options.html">tab_options()</a></code> and <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code>. The cell background color for both types of summary cells is modified and two footnotes are added.</p>
-<div class="sourceCode" id="cb10"><html><body><pre class="r"><span class="co"># Using the gt table of `exibble_h` as a</span>
-<span class="co"># starting point, style summary cells with</span>
-<span class="co"># `tab_options()` and add two footnotes</span>
-<span class="no">exibble_i</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_h</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
-    <span class="kw">summary_row.background.color</span> <span class="kw">=</span> <span class="st">"lightblue"</span>,
-    <span class="kw">grand_summary_row.background.color</span> <span class="kw">=</span> <span class="st">"lightgreen"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Mean of all *num* values."</span>),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_grand_summary.html">cells_grand_summary</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>), <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">avg</span>)
-    )
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Highest `currency` value in **grp_a**"</span>),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_summary.html">cells_summary</a></span>(
-      <span class="kw">groups</span> <span class="kw">=</span> <span class="st">"grp_a"</span>,
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="st">"max"</span>
-    )
-  )
-
-<span class="no">exibble_i</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...1`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...2`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY3` -&gt; `::GRAND_SUMMARY3...3`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY1` -&gt; `::GRAND_SUMMARY1...4`</span>
-<span class="co">#&gt; * `::GRAND_SUMMARY2` -&gt; `::GRAND_SUMMARY2...5`</span>
-<span class="co">#&gt; * ...</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...1</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...2</span>
-<span class="co">#&gt; * grp_a3 -&gt; grp_a3...3</span>
-<span class="co">#&gt; * grp_a1 -&gt; grp_a1...4</span>
-<span class="co">#&gt; * grp_a2 -&gt; grp_a2...5</span>
-<span class="co">#&gt; * ...</span></pre></body></html></div>
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-
-#qaanlwhcaz .gt_table {
-  display: table;
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-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#qaanlwhcaz .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#qaanlwhcaz .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#qaanlwhcaz .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#qaanlwhcaz .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
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-  margin-bottom: 0;
-}
-
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-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
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-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#qaanlwhcaz .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#qaanlwhcaz .gt_summary_row {
-  color: #333333;
-  background-color: lightblue;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#qaanlwhcaz .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#qaanlwhcaz .gt_grand_summary_row {
-  color: #333333;
-  background-color: lightgreen;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#qaanlwhcaz .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
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-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
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-  border-bottom-width: 2px;
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-}
-
-#qaanlwhcaz .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
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-  border-left-color: #D3D3D3;
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-
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-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
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-
-#qaanlwhcaz .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
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-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
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-
-#qaanlwhcaz .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#qaanlwhcaz .gt_left {
-  text-align: left;
-}
-
-#qaanlwhcaz .gt_center {
-  text-align: center;
-}
-
-#qaanlwhcaz .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#qaanlwhcaz .gt_font_normal {
-  font-weight: normal;
-}
-
-#qaanlwhcaz .gt_font_bold {
-  font-weight: bold;
-}
-
-#qaanlwhcaz .gt_font_italic {
-  font-style: italic;
-}
-
-#qaanlwhcaz .gt_super {
-  font-size: 65%;
-}
-
-#qaanlwhcaz .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="qaanlwhcaz" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_a</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_1</td>
-      <td class="gt_row gt_right">1,111 × 10<sup class="gt_super">−1</sup>
-</td>
-      <td class="gt_row gt_left">apricot</td>
-      <td class="gt_row gt_right">€49,95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_2</td>
-      <td class="gt_row gt_right">2,222</td>
-      <td class="gt_row gt_left">banana</td>
-      <td class="gt_row gt_right">€17,95</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_3</td>
-      <td class="gt_row gt_right">3,333 × 10<sup class="gt_super">1</sup>
-</td>
-      <td class="gt_row gt_left">coconut</td>
-      <td class="gt_row gt_right">€1,39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_4</td>
-      <td class="gt_row gt_right">4,444 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">€65 100,00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">1,200 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">€16 292,32</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">4,801 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65 169,29</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">2,168 × 10<sup class="gt_super">2</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€32 538,46</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">min</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€1,39</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">max</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">€65 100,00<sup class="gt_footnote_marks">1</sup>
-</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5,550 × 10<sup class="gt_super">3</sup>
-</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">€1 325,81</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">€13,26</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7,770 × 10<sup class="gt_super">5</sup>
-</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8,880 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">€0,44</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">avg</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">3,221 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row gt_first_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">total</td>
-      <td class="gt_row gt_right gt_summary_row">9,663 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_summary_row">4,916 × 10<sup class="gt_super">6</sup>
-</td>
-      <td class="gt_row gt_left gt_summary_row">—</td>
-      <td class="gt_row gt_right gt_summary_row">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">avg</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">1,38M<sup class="gt_footnote_marks">2</sup>
-</td>
-      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">$9,50K</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row">total</td>
-      <td class="gt_row gt_right gt_grand_summary_row">9,66M</td>
-      <td class="gt_row gt_left gt_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row">$66,51K</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row">s.d.</td>
-      <td class="gt_row gt_right gt_grand_summary_row">3,32M</td>
-      <td class="gt_row gt_left gt_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row">$24,52K</td>
-    </tr>
-</tbody>
-<tfoot><tr class="gt_footnotes">
-<td colspan="4">
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>1</em>
-          </sup>
-           
-          Highest <code>currency</code> value in <strong>grp_a</strong>
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>2</em>
-          </sup>
-           
-          Mean of all <em>num</em> values.
-          <br></p>
-      </td>
-    </tr></tfoot>
-</table></div>
-</div>
-<div id="extracting-the-summary-data-from-the-gt-table-object" class="section level3">
-<h3 class="hasAnchor">
-<a href="#extracting-the-summary-data-from-the-gt-table-object" class="anchor"></a>Extracting the Summary Data from the <strong>gt</strong> Table Object</h3>
-<p>For a reproducible workflow, we do not want to have situations where any data created or modified cannot be accessed. While having summarized values be created in a <strong>gt</strong> pipeline presents advantages to readability and intent of analysis, it is recognized that the output table itself is essentially ‘read only’, as the input data undergoes processing and movement to an entirely different format.</p>
-<p>However, the object created still contains data and we can obtain the summary data from a <strong>gt</strong> table object using the <code><a href="../reference/extract_summary.html">extract_summary()</a></code> function. Taking the <code>gt_summary</code> object, we get a list of tibbles containing the summary data while preserving the correct data types:</p>
-<div class="sourceCode" id="cb11"><html><body><pre class="r"><span class="co"># Extract the summary data from `exibble_d`</span>
-<span class="co"># to a list  object</span>
-<span class="no">summary_list</span> <span class="kw">&lt;-</span> <span class="no">exibble_d</span> <span class="kw">%&gt;%</span> <span class="fu"><a href="../reference/extract_summary.html">extract_summary</a></span>()</pre></body></html></div>
-<div class="sourceCode" id="cb12"><html><body><pre class="r"><span class="co"># Print out the summary for the `grp_a` group</span>
-<span class="no">summary_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">summary_df_data_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">grp_a</span>
-<span class="co">#&gt; # A tibble: 3 x 7</span>
-<span class="co">#&gt;   groupname rowname   num  char currency   row group</span>
-<span class="co">#&gt;   &lt;chr&gt;     &lt;chr&gt;   &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
-<span class="co">#&gt; 1 grp_a     avg      120.    NA       NA    NA    NA</span>
-<span class="co">#&gt; 2 grp_a     total    480.    NA       NA    NA    NA</span>
-<span class="co">#&gt; 3 grp_a     s.d.     217.    NA       NA    NA    NA</span></pre></body></html></div>
-<div class="sourceCode" id="cb13"><html><body><pre class="r"><span class="co"># Print out the summary for the `grp_b` group</span>
-<span class="no">summary_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">summary_df_data_list</span> <span class="kw">%&gt;%</span> <span class="no">.</span>$<span class="no">grp_b</span>
-<span class="co">#&gt; # A tibble: 3 x 7</span>
-<span class="co">#&gt;   groupname rowname      num  char currency   row group</span>
-<span class="co">#&gt;   &lt;chr&gt;     &lt;chr&gt;      &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt; &lt;dbl&gt; &lt;dbl&gt;</span>
-<span class="co">#&gt; 1 grp_b     avg     3220850     NA       NA    NA    NA</span>
-<span class="co">#&gt; 2 grp_b     total   9662550     NA       NA    NA    NA</span>
-<span class="co">#&gt; 3 grp_b     s.d.    4916123.    NA       NA    NA    NA</span></pre></body></html></div>
-<p>The output tibbles within the list always contain the <code>groupname</code> and <code>rowname</code> columns. The <code>groupname</code> column is filled with the name of the row group that was given to <code><a href="../reference/summary_rows.html">summary_rows()</a></code>. The <code>rowname</code> column contains the descriptive stub labels for the summary rows (recall that values are either supplied explicitly in <code><a href="../reference/summary_rows.html">summary_rows()</a></code>, or, are generated from the function names). The remaining columns are those from the original dataset.</p>
-<p>The output data from <code><a href="../reference/extract_summary.html">extract_summary()</a></code> can be reintroduced to a reproducible workflow and serve as downstream inputs or undergo validation. Perhaps interestingly, the output tibbles are structured in a way that facilitates direct input back to <code><a href="../reference/gt.html">gt()</a></code> (i.e., it has the magic <code>groupname</code> and <code>rowname</code> columns). This can produce a new, standalone summary table where the summary rows are now data rows:</p>
-<div class="sourceCode" id="cb14"><html><body><pre class="r"><span class="co"># Take `exibble_d`, which internally has a list</span>
-<span class="co"># of summary data frames, extract the summaries,</span>
-<span class="co"># and then combine them; input that into `gt()`,</span>
-<span class="co"># and format the `num` column with `fmt_number()`</span>
-<span class="no">exibble_d</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/extract_summary.html">extract_summary</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="https://rdrr.io/r/base/unlist.html">unlist</a></span>(<span class="kw">recursive</span> <span class="kw">=</span> <span class="fl">FALSE</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind.html">bind_rows</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">1</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_missing.html">fmt_missing</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">char</span>, <span class="no">currency</span>, <span class="no">row</span>, <span class="no">group</span>)
-  )</pre></body></html></div>
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-}
-
-#czzpxmlttm .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
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-  background-color: #FFFFFF;
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-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
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-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
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-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
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-}
-
-#czzpxmlttm .gt_subtitle {
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-  font-size: 85%;
-  font-weight: initial;
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-  padding-bottom: 4px;
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-  border-top-width: 0;
-}
-
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-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#czzpxmlttm .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
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-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
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-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#czzpxmlttm .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
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-}
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-  padding-left: 0;
-}
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-#czzpxmlttm .gt_column_spanner_outer:last-child {
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-}
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-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#czzpxmlttm .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
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-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#czzpxmlttm .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
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-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#czzpxmlttm .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#czzpxmlttm .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#czzpxmlttm .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#czzpxmlttm .gt_row {
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-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
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-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
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-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#czzpxmlttm .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#czzpxmlttm .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#czzpxmlttm .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#czzpxmlttm .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#czzpxmlttm .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#czzpxmlttm .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#czzpxmlttm .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
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-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#czzpxmlttm .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#czzpxmlttm .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#czzpxmlttm .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#czzpxmlttm .gt_left {
-  text-align: left;
-}
-
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-}
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-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="czzpxmlttm" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">groupname</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">num</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">char</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">currency</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">row</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">group</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left gt_stub">avg</td>
-      <td class="gt_row gt_left">grp_a</td>
-      <td class="gt_row gt_right">120.0</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">total</td>
-      <td class="gt_row gt_left">grp_a</td>
-      <td class="gt_row gt_right">480.1</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">s.d.</td>
-      <td class="gt_row gt_left">grp_a</td>
-      <td class="gt_row gt_right">216.8</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">avg</td>
-      <td class="gt_row gt_left">grp_b</td>
-      <td class="gt_row gt_right">3,220,850.0</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">total</td>
-      <td class="gt_row gt_left">grp_b</td>
-      <td class="gt_row gt_right">9,662,550.0</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">s.d.</td>
-      <td class="gt_row gt_left">grp_b</td>
-      <td class="gt_row gt_right">4,916,123.3</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-<div id="providing-our-own-aggregation-functions-to-generate-summary-rows" class="section level3">
-<h3 class="hasAnchor">
-<a href="#providing-our-own-aggregation-functions-to-generate-summary-rows" class="anchor"></a>Providing Our Own Aggregation Functions to Generate Summary Rows</h3>
-<p>While many of the functions available in base R and within packages are useful as aggregate functions, we may occasionally have the need to create our own custom functions. When taking this approach the main things to keep in mind are that a vector of values is the main input, and, a single value should be returned. The return value can be pretty much any class (e.g., <code>numeric</code>, <code>character</code>, <code>logical</code>) and it’s the <code>formatter</code> function that will handle any custom formatting while also converting to <code>character</code>.</p>
-<p>Here, we’ll define a function that takes a vector of numeric values and outputs the two highest values (sorted low to high) above a <code>threshold</code> value. The output from this function is always a formatted <code>character</code> string.</p>
-<div class="sourceCode" id="cb15"><html><body><pre class="r"><span class="co"># Define a function that gives the</span>
-<span class="co"># highest two values above a threshold</span>
-<span class="no">agg_highest_two_above_value</span> <span class="kw">&lt;-</span> <span class="kw">function</span>(<span class="no">x</span>, <span class="no">threshold</span>) {
-
-  <span class="co"># Get sorted values above threshold value</span>
-  <span class="no">values</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/sort.html">sort</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/Round.html">round</a></span>(<span class="no">x</span>[<span class="no">x</span> <span class="kw">&gt;=</span> <span class="no">threshold</span>], <span class="fl">2</span>))
-
-  <span class="co"># Return character string with 2 highest values above threshold</span>
-  <span class="kw">if</span> (<span class="fu"><a href="https://rdrr.io/r/base/length.html">length</a></span>(<span class="no">values</span>) <span class="kw">==</span> <span class="fl">0</span>) {
-    <span class="fu"><a href="https://rdrr.io/r/base/function.html">return</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste0</a></span>(<span class="st">"No values above "</span>, <span class="no">threshold</span>))
-  } <span class="kw">else</span> {
-    <span class="fu"><a href="https://rdrr.io/r/base/function.html">return</a></span>(
-      <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(
-        <span class="fu"><a href="https://rdrr.io/r/base/formatc.html">formatC</a></span>(
-          <span class="fu"><a href="https://rdrr.io/r/utils/head.html">tail</a></span>(
-            <span class="fu"><a href="https://rdrr.io/r/base/sort.html">sort</a></span>(<span class="fu"><a href="https://rdrr.io/r/base/Round.html">round</a></span>(<span class="no">x</span>[<span class="no">x</span> <span class="kw">&gt;</span> <span class="no">threshold</span>], <span class="fl">2</span>)), <span class="fl">2</span>),
-          <span class="kw">format</span> <span class="kw">=</span> <span class="st">"f"</span>, <span class="kw">digits</span> <span class="kw">=</span> <span class="fl">2</span>), <span class="kw">collapse</span> <span class="kw">=</span> <span class="st">", "</span>))
-  }
-}
-
-<span class="co"># Let's test this function with some values</span>
-<span class="fu">agg_highest_two_above_value</span>(
-  <span class="kw">x</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">0.73</span>, <span class="fl">0.93</span>, <span class="fl">0.75</span>, <span class="fl">0.86</span>, <span class="fl">0.23</span>, <span class="fl">0.81</span>),
-  <span class="kw">threshold</span> <span class="kw">=</span> <span class="fl">0.8</span>
-)
-<span class="co">#&gt; [1] "0.86, 0.93"</span></pre></body></html></div>
-<p>Because this is character value that’s returned, we don’t need formatting functions like <code><a href="../reference/fmt_number.html">fmt_number()</a></code>, <code><a href="../reference/fmt_percent.html">fmt_percent()</a></code>, etc. However, a useful formatter (and we do need <em>some</em> formatter) is the <code><a href="../reference/fmt_passthrough.html">fmt_passthrough()</a></code> function. Like the name suggests, it to great extent passes values through but formats as <code>character</code> (like all the <code>fmt_*()</code> function do) and it provides the option to decorate the output with a <code>pattern</code>. Let’s have a look at how the <code>agg_highest_two_above_value()</code> function can be used with the <code><a href="../reference/fmt_passthrough.html">fmt_passthrough()</a></code> formatter function.</p>
-<div class="sourceCode" id="cb16"><html><body><pre class="r"><span class="co"># Create a gt table with `exibble_a` and use</span>
-<span class="co"># the custom function with a threshold of `20`;</span>
-<span class="co"># the `fmt_passthrough` funtion allows for</span>
-<span class="co"># minimal formatting of the aggregate values</span>
-<span class="no">exibble_j</span> <span class="kw">&lt;-</span>
-  <span class="no">exibble_a</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/grand_summary_rows.html">grand_summary_rows</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>, <span class="no">currency</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(
-      <span class="kw">high</span> <span class="kw">=</span> ~<span class="fu">agg_highest_two_above_value</span>(<span class="no">.</span>, <span class="fl">20</span>)),
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_passthrough</span>,
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"({x})"</span>
-  )
-
-<span class="no">exibble_j</span></pre></body></html></div>
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-      <td class="gt_row gt_right">4.444e+02</td>
-      <td class="gt_row gt_left">durian</td>
-      <td class="gt_row gt_right">65100.000</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">grp_b</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_5</td>
-      <td class="gt_row gt_right">5.550e+03</td>
-      <td class="gt_row gt_left">—</td>
-      <td class="gt_row gt_right">1325.810</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_6</td>
-      <td class="gt_row gt_right">—</td>
-      <td class="gt_row gt_left">fig</td>
-      <td class="gt_row gt_right">13.255</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_7</td>
-      <td class="gt_row gt_right">7.770e+05</td>
-      <td class="gt_row gt_left">grapefruit</td>
-      <td class="gt_row gt_right">—</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">row_8</td>
-      <td class="gt_row gt_right">8.880e+06</td>
-      <td class="gt_row gt_left">honeydew</td>
-      <td class="gt_row gt_right">0.440</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_grand_summary_row gt_first_grand_summary_row">high</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">(777000.00, 8880000.00)</td>
-      <td class="gt_row gt_left gt_grand_summary_row gt_first_grand_summary_row">—</td>
-      <td class="gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row">(1325.81, 65100.00)</td>
-    </tr>
-</tbody>
-</table></div>
-<p>We can extract the grand summary data from the <code>exibble_j</code> object. Note that columns <code>num</code> and <code>currency</code> are classed as character since it was character outputs that were generated by the <code>agg_highest_two_above_value()</code> function.</p>
-<div class="sourceCode" id="cb17"><html><body><pre class="r"><span class="co"># Extract the summary list from `exibble_j`</span>
-<span class="co"># and inspect using `str()`</span>
-<span class="no">exibble_j</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/extract_summary.html">extract_summary</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="https://rdrr.io/r/utils/str.html">str</a></span>()
-<span class="co">#&gt; List of 1</span>
-<span class="co">#&gt;  $ summary_df_data_list:List of 1</span>
-<span class="co">#&gt;   ..$ ::GRAND_SUMMARY: tibble [1 × 7] (S3: tbl_df/tbl/data.frame)</span>
-<span class="co">#&gt;   .. ..$ groupname: chr "::GRAND_SUMMARY"</span>
-<span class="co">#&gt;   .. ..$ rowname  : chr "high"</span>
-<span class="co">#&gt;   .. ..$ num      : chr "777000.00, 8880000.00"</span>
-<span class="co">#&gt;   .. ..$ char     : num NA</span>
-<span class="co">#&gt;   .. ..$ currency : chr "1325.81, 65100.00"</span>
-<span class="co">#&gt;   .. ..$ row      : num NA</span>
-<span class="co">#&gt;   .. ..$ group    : num NA</span></pre></body></html></div>
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-      <h1 data-toc-skip>gt Datasets</h1>
-            
-      
-      <small class="dont-index">Source: <a href="https://github.com/rstudio/gt/blob/master/vignettes/gt-datasets.Rmd"><code>vignettes/gt-datasets.Rmd</code></a></small>
-      <div class="hidden name"><code>gt-datasets.Rmd</code></div>
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-<p>The <strong>gt</strong> package comes with six built-in datasets for experimenting with the <strong>gt</strong> API: <code>countrypops</code>, <code>sza</code>, <code>gtcars</code>, <code>sp500</code>, <code>pizzaplace</code>, and <code>exibble</code>. While each dataset has different subject matter, all of them will be used to develop <strong>gt</strong> examples with consistent syntax.</p>
-<p><img src="images/countrypops.png" width="30%"><img src="images/sza.svg" width="30%"><img src="images/gtcars.svg" width="30%"></p>
-<p><img src="images/sp500.svg" width="30%"><img src="images/pizzaplace.svg" width="30%"><img src="images/exibble.svg" width="30%"></p>
-<p>Each dataset is stored as a tibble, ranging from very small (like <code>exibble</code>, an example tibble of 8 rows) to quite large in size (e.g., at nearly 50,000 rows: <code>pizzaplace</code>). Larger datasets are typically impractical as <strong>gt output tables</strong> but they provide opportunities for demonstrating preprocessing using tidyverse tools like <strong>dplyr</strong> and <strong>tidyr</strong> (upstream of <strong>gt</strong>’s <code><a href="../reference/gt.html">gt()</a></code> entry point).</p>
-<p>In many <strong>gt</strong> workflows, there will often be prep work like this where the creation of the input table and any salient information (e.g., metadata for footnotes) will be done alongside the preparation of the display table.</p>
-<p>In the next few examples, we’ll show how tables can be created with each of these datasets. Each example will be preceded with a set of requirements that serve as a design brief. This planning stage can be very useful in your own work for the purpose of organization. The hope is that this collection of simple examples will inspire the creation of much more interesting display tables with <strong>gt</strong>.</p>
-<div id="countrypops" class="section level3">
-<h3 class="hasAnchor">
-<a href="#countrypops" class="anchor"></a><code>countrypops</code>
-</h3>
-<p>This dataset provides the total populations of 215 countries on a yearly basis, from 1960 to 2017. The source data comes from the <a href="https://data.worldbank.org/indicator/SP.POP.TOTL">World Bank</a>, where it has been cleaned and tidied up for inclusion into this package. Each row contains a population value for a country in a given year, where <code>NA</code> values for <code>population</code> indicate that the country did not exist in that particular year.</p>
-<p>The <code>countrypops</code> dataset is a tibble with 12,470 rows and 5 variables. Here are explanations for each of the variables:</p>
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-  border-top-style: solid;
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-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
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-<div id="ntmtsrqqnk" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">country_name</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">Name of the country</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">country_code_2</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The 2-letter ISO 3166-1 country code</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">country_code_3</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The 3-letter ISO 3166-1 country code</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">year</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
-      <td class="gt_row gt_left">The year for the population estimate</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">population</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
-      <td class="gt_row gt_left">The population estimate, midway through the year</td>
-    </tr>
-</tbody>
-</table></div>
-<div id="a-countrypops-example" class="section level4">
-<h4 class="hasAnchor">
-<a href="#a-countrypops-example" class="anchor"></a>A <code>countrypops</code> Example</h4>
-<p>The table that we’ll create from <code>countrypops</code> will meet these requirements:</p>
-<ol style="list-style-type: decimal">
-<li>use countries from Oceania</li>
-<li>countries in different regions of Oceania will be grouped together</li>
-<li>provide populations for the 1995, 2005, and 2015 years only; they should appear as separate columns with a spanner group column stating that these columns refer to population values</li>
-<li>format population figures to contain commas</li>
-<li>provide a descriptive title</li>
-</ol>
-<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># Get vectors of 2-letter country codes for</span>
-<span class="co"># each region of Oceania</span>
-<span class="no">Australasia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"AU"</span>, <span class="st">"NZ"</span>)
-<span class="no">Melanesia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"NC"</span>, <span class="st">"PG"</span>, <span class="st">"SB"</span>, <span class="st">"VU"</span>)
-<span class="no">Micronesia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"FM"</span>, <span class="st">"GU"</span>, <span class="st">"KI"</span>, <span class="st">"MH"</span>, <span class="st">"MP"</span>, <span class="st">"NR"</span>, <span class="st">"PW"</span>)
-<span class="no">Polynesia</span> <span class="kw">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"PF"</span>, <span class="st">"WS"</span>, <span class="st">"TO"</span>, <span class="st">"TV"</span>)
-
-<span class="co"># Create a gt table based on a preprocessed `countrypops`</span>
-<span class="no">countrypops</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(
-    <span class="no">Australasia</span>, <span class="no">Melanesia</span>, <span class="no">Micronesia</span>, <span class="no">Polynesia</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">year</span> <span class="kw">%in%</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="fl">1995</span>, <span class="fl">2005</span>, <span class="fl">2015</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="kw">region</span> <span class="kw">=</span> <span class="fu">case_when</span>(
-    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Australasia</span> ~ <span class="st">"Australasia"</span>,
-    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Melanesia</span> ~ <span class="st">"Melanesia"</span>,
-    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Micronesia</span> ~ <span class="st">"Micronesia"</span>,
-    <span class="no">country_code_2</span> <span class="kw">%in%</span> <span class="no">Polynesia</span> ~ <span class="st">"Polynesia"</span>,
-  )) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">tidyr</span><span class="kw ns">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(<span class="kw">key</span> <span class="kw">=</span> <span class="no">year</span>, <span class="kw">value</span> <span class="kw">=</span> <span class="no">population</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="no">region</span>, <span class="fu">desc</span>(<span class="no">`2015`</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="fu"><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">starts_with</a></span>(<span class="st">"country_code"</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(
-    <span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"country_name"</span>,
-    <span class="kw">groupname_col</span> <span class="kw">=</span> <span class="st">"region"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"Populations of Oceania's Countries in 1995, 2005, and 2015"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
-    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Total Population"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">`1995`</span>, <span class="no">`2005`</span>, <span class="no">`2015`</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">`1995`</span>, <span class="no">`2005`</span>, <span class="no">`2015`</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>,
-    <span class="kw">use_seps</span> <span class="kw">=</span> <span class="fl">TRUE</span>
-  )</pre></body></html></div>
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-<thead class="gt_header">
-<tr>
-<th colspan="4" class="gt_heading gt_title gt_font_normal" style>Populations of Oceania's Countries in 1995, 2005, and 2015</th>
-    </tr>
-<tr>
-<th colspan="4" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
-    </tr>
-</thead>
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1"></th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Total Population</span>
-      </th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">1995</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">2005</th>
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-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">Australasia</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Australia</td>
-      <td class="gt_row gt_center">18,072,000</td>
-      <td class="gt_row gt_center">20,394,800</td>
-      <td class="gt_row gt_center">23,850,784</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">New Zealand</td>
-      <td class="gt_row gt_center">3,673,400</td>
-      <td class="gt_row gt_center">4,133,900</td>
-      <td class="gt_row gt_center">4,595,700</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">Melanesia</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Papua New Guinea</td>
-      <td class="gt_row gt_center">4,894,276</td>
-      <td class="gt_row gt_center">6,314,709</td>
-      <td class="gt_row gt_center">7,919,825</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Solomon Islands</td>
-      <td class="gt_row gt_center">359,225</td>
-      <td class="gt_row gt_center">469,885</td>
-      <td class="gt_row gt_center">587,482</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">New Caledonia</td>
-      <td class="gt_row gt_center">193,816</td>
-      <td class="gt_row gt_center">232,250</td>
-      <td class="gt_row gt_center">272,400</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Vanuatu</td>
-      <td class="gt_row gt_center">168,235</td>
-      <td class="gt_row gt_center">209,370</td>
-      <td class="gt_row gt_center">264,603</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">Micronesia</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Guam</td>
-      <td class="gt_row gt_center">145,561</td>
-      <td class="gt_row gt_center">158,402</td>
-      <td class="gt_row gt_center">161,797</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Kiribati</td>
-      <td class="gt_row gt_center">77,730</td>
-      <td class="gt_row gt_center">92,325</td>
-      <td class="gt_row gt_center">112,407</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Micronesia (Federated States)</td>
-      <td class="gt_row gt_center">107,556</td>
-      <td class="gt_row gt_center">106,196</td>
-      <td class="gt_row gt_center">104,433</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Northern Mariana Islands</td>
-      <td class="gt_row gt_center">56,278</td>
-      <td class="gt_row gt_center">63,744</td>
-      <td class="gt_row gt_center">54,816</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Marshall Islands</td>
-      <td class="gt_row gt_center">51,015</td>
-      <td class="gt_row gt_center">52,055</td>
-      <td class="gt_row gt_center">52,994</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Palau</td>
-      <td class="gt_row gt_center">17,253</td>
-      <td class="gt_row gt_center">19,906</td>
-      <td class="gt_row gt_center">21,288</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Nauru</td>
-      <td class="gt_row gt_center">9,969</td>
-      <td class="gt_row gt_center">10,114</td>
-      <td class="gt_row gt_center">12,475</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="4" class="gt_group_heading">Polynesia</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">French Polynesia</td>
-      <td class="gt_row gt_center">215,196</td>
-      <td class="gt_row gt_center">254,886</td>
-      <td class="gt_row gt_center">277,690</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Samoa</td>
-      <td class="gt_row gt_center">170,157</td>
-      <td class="gt_row gt_center">179,929</td>
-      <td class="gt_row gt_center">193,759</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Tonga</td>
-      <td class="gt_row gt_center">96,076</td>
-      <td class="gt_row gt_center">101,041</td>
-      <td class="gt_row gt_center">106,364</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Tuvalu</td>
-      <td class="gt_row gt_center">9,230</td>
-      <td class="gt_row gt_center">10,027</td>
-      <td class="gt_row gt_center">11,001</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-</div>
-<div id="sza" class="section level3">
-<h3 class="hasAnchor">
-<a href="#sza" class="anchor"></a><code>sza</code>
-</h3>
-<p>The solar zenith angle is one measure of the solar position. It can be thought of as ‘height’ of the sun in relation to an observer. A solar zenith angle of 0° indicates that the sun is directly overhead (a different solar angle, the <em>solar altitude angle</em>, is 90° in this instance). With the sun at the horizontal (e.g., during sunrise/sunset) we observe the solar zenith angle to be around 90° (there is the matter of atmospheric refraction). During nighttime, solar zenith angles in the range of 90–180 are possible (again, depending on the location of the observer).</p>
-<p>The <code>sza</code> dataset has calculated values for the solar zenith angles every 30 minutes from 04:00 to 12:00 (true solar time). Temporally, these calculations are for the 1st of every month of the year. Spatially, the observer is located at somewhere along latitudes 20°N, 30°N, 40°N, and 50°N (because we are using true solar time, the longitude is unimportant). This is quite an extensive topic, and more information can be found by using <code><a href="../reference/sza.html">?sza</a></code> in the R console or by visiting <a href="https://en.wikipedia.org/wiki/Solar_zenith_angle">this page</a>.</p>
-<p>The <code>sza</code> dataset is a tibble with 816 rows and 4 variables. Here are explanations for each of the variables:</p>
-<style>html {
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-
-#mpwkaodbur .gt_table {
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-}
-
-#mpwkaodbur .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#mpwkaodbur .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#mpwkaodbur .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#mpwkaodbur .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#mpwkaodbur .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#mpwkaodbur .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#mpwkaodbur .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#mpwkaodbur .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#mpwkaodbur .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#mpwkaodbur .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#mpwkaodbur .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#mpwkaodbur .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#mpwkaodbur .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#mpwkaodbur .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#mpwkaodbur .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#mpwkaodbur .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#mpwkaodbur .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#mpwkaodbur .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#mpwkaodbur .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
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-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
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-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
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-#mpwkaodbur .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#mpwkaodbur .gt_left {
-  text-align: left;
-}
-
-#mpwkaodbur .gt_center {
-  text-align: center;
-}
-
-#mpwkaodbur .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#mpwkaodbur .gt_font_normal {
-  font-weight: normal;
-}
-
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-  font-weight: bold;
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-  font-size: 65%;
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-
-#mpwkaodbur .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="mpwkaodbur" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">latitude</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">The latitude in decimal degrees for the observations</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">month</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">fct</td>
-      <td class="gt_row gt_left">The measurement month; all calculations where conducted for the first day of each month</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">tst</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The true solar time at the given latitude and date (first of month) for which the solar zenith angle is calculated</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">sza</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">The solar zenith angle in degrees, where NAs indicate that sunrise hadn't yet occurred by the tst value</td>
-    </tr>
-</tbody>
-</table></div>
-<div id="an-sza-example" class="section level4">
-<h4 class="hasAnchor">
-<a href="#an-sza-example" class="anchor"></a>An <code>sza</code> Example</h4>
-<p>The table that we’ll create from <code>sza</code> will meet these requirements:</p>
-<ol style="list-style-type: decimal">
-<li>filter the data to just use the 20°N data and remove the <code>latitude</code> column</li>
-<li>
-<code>NA</code> values from <code>sza</code> column are to be removed</li>
-<li>reshape the table so that columns of <code>tst</code> (true solar time) contain angles in degrees (from the <code>sza</code> column)</li>
-<li>the <strong>gt output table</strong> will have the <code>month</code>s as row labels in the stub</li>
-<li>missing values will be replaced with an empty string (so that those cells are blank)</li>
-<li>a stubhead label will state what’s inside the stubs (months, at 20°N)</li>
-<li>the table will have a heading decorated with the HTML <em>Black Sun with Rays</em> (<code>&amp;#x2600;</code>) symbol</li>
-<li>to fit the large amount of data in a small area, use some table options to reduce text size and row padding</li>
-</ol>
-<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Create a gt table based on a preprocessed `sza`</span>
-<span class="no">sza</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">latitude</span> <span class="kw">==</span> <span class="fl">20</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">latitude</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(!<span class="fu"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span>(<span class="no">sza</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">tidyr</span><span class="kw ns">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(<span class="kw">key</span> <span class="kw">=</span> <span class="st">"tst"</span>, <span class="kw">value</span> <span class="kw">=</span> <span class="no">sza</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"month"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_missing.html">fmt_missing</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">missing_text</span> <span class="kw">=</span> <span class="st">""</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_stubhead.html">tab_stubhead</a></span>(<span class="kw">label</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"month&lt;br&gt;(20&amp;deg;N)"</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"&amp;#x2600; Solar Zenith Angles &amp;#x2600;"</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
-    <span class="kw">column_labels.font.size</span> <span class="kw">=</span> <span class="st">"smaller"</span>,
-    <span class="kw">table.font.size</span> <span class="kw">=</span> <span class="st">"smaller"</span>,
-    <span class="kw">data_row.padding</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">3</span>)
-  )</pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#sutwoosmmg .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: smaller;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#sutwoosmmg .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
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-<div id="sutwoosmmg" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="15" class="gt_heading gt_title gt_font_normal" style>☀ Solar Zenith Angles ☀</th>
-    </tr>
-<tr>
-<th colspan="15" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">month<br>(20°N)</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0530</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0600</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0630</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0700</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0730</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0800</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0830</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0900</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">0930</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1000</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1030</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1100</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1130</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">1200</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left gt_stub">jan</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">84.9</td>
-      <td class="gt_row gt_right">78.7</td>
-      <td class="gt_row gt_right">72.7</td>
-      <td class="gt_row gt_right">66.1</td>
-      <td class="gt_row gt_right">61.5</td>
-      <td class="gt_row gt_right">56.5</td>
-      <td class="gt_row gt_right">52.1</td>
-      <td class="gt_row gt_right">48.3</td>
-      <td class="gt_row gt_right">45.5</td>
-      <td class="gt_row gt_right">43.6</td>
-      <td class="gt_row gt_right">43.0</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">feb</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">88.9</td>
-      <td class="gt_row gt_right">82.5</td>
-      <td class="gt_row gt_right">75.8</td>
-      <td class="gt_row gt_right">69.6</td>
-      <td class="gt_row gt_right">63.3</td>
-      <td class="gt_row gt_right">57.7</td>
-      <td class="gt_row gt_right">52.2</td>
-      <td class="gt_row gt_right">47.4</td>
-      <td class="gt_row gt_right">43.1</td>
-      <td class="gt_row gt_right">40.0</td>
-      <td class="gt_row gt_right">37.8</td>
-      <td class="gt_row gt_right">37.2</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">mar</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">85.7</td>
-      <td class="gt_row gt_right">78.8</td>
-      <td class="gt_row gt_right">72.0</td>
-      <td class="gt_row gt_right">65.2</td>
-      <td class="gt_row gt_right">58.6</td>
-      <td class="gt_row gt_right">52.3</td>
-      <td class="gt_row gt_right">46.2</td>
-      <td class="gt_row gt_right">40.5</td>
-      <td class="gt_row gt_right">35.5</td>
-      <td class="gt_row gt_right">31.4</td>
-      <td class="gt_row gt_right">28.6</td>
-      <td class="gt_row gt_right">27.7</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">apr</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">88.5</td>
-      <td class="gt_row gt_right">81.5</td>
-      <td class="gt_row gt_right">74.4</td>
-      <td class="gt_row gt_right">67.4</td>
-      <td class="gt_row gt_right">60.3</td>
-      <td class="gt_row gt_right">53.4</td>
-      <td class="gt_row gt_right">46.5</td>
-      <td class="gt_row gt_right">39.7</td>
-      <td class="gt_row gt_right">33.2</td>
-      <td class="gt_row gt_right">26.9</td>
-      <td class="gt_row gt_right">21.3</td>
-      <td class="gt_row gt_right">17.2</td>
-      <td class="gt_row gt_right">15.5</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">may</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">85.0</td>
-      <td class="gt_row gt_right">78.2</td>
-      <td class="gt_row gt_right">71.2</td>
-      <td class="gt_row gt_right">64.3</td>
-      <td class="gt_row gt_right">57.2</td>
-      <td class="gt_row gt_right">50.2</td>
-      <td class="gt_row gt_right">43.2</td>
-      <td class="gt_row gt_right">36.1</td>
-      <td class="gt_row gt_right">29.1</td>
-      <td class="gt_row gt_right">26.1</td>
-      <td class="gt_row gt_right">15.2</td>
-      <td class="gt_row gt_right">8.8</td>
-      <td class="gt_row gt_right">5.0</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">jun</td>
-      <td class="gt_row gt_right">89.2</td>
-      <td class="gt_row gt_right">82.7</td>
-      <td class="gt_row gt_right">76.0</td>
-      <td class="gt_row gt_right">69.3</td>
-      <td class="gt_row gt_right">62.5</td>
-      <td class="gt_row gt_right">55.7</td>
-      <td class="gt_row gt_right">48.8</td>
-      <td class="gt_row gt_right">41.9</td>
-      <td class="gt_row gt_right">35.0</td>
-      <td class="gt_row gt_right">28.1</td>
-      <td class="gt_row gt_right">21.1</td>
-      <td class="gt_row gt_right">14.2</td>
-      <td class="gt_row gt_right">7.3</td>
-      <td class="gt_row gt_right">2.0</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">jul</td>
-      <td class="gt_row gt_right">88.8</td>
-      <td class="gt_row gt_right">82.3</td>
-      <td class="gt_row gt_right">75.7</td>
-      <td class="gt_row gt_right">69.1</td>
-      <td class="gt_row gt_right">62.3</td>
-      <td class="gt_row gt_right">55.5</td>
-      <td class="gt_row gt_right">48.7</td>
-      <td class="gt_row gt_right">41.8</td>
-      <td class="gt_row gt_right">35.0</td>
-      <td class="gt_row gt_right">28.1</td>
-      <td class="gt_row gt_right">21.2</td>
-      <td class="gt_row gt_right">14.3</td>
-      <td class="gt_row gt_right">7.7</td>
-      <td class="gt_row gt_right">3.1</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">aug</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">83.8</td>
-      <td class="gt_row gt_right">77.1</td>
-      <td class="gt_row gt_right">70.2</td>
-      <td class="gt_row gt_right">63.3</td>
-      <td class="gt_row gt_right">56.4</td>
-      <td class="gt_row gt_right">49.4</td>
-      <td class="gt_row gt_right">42.4</td>
-      <td class="gt_row gt_right">35.4</td>
-      <td class="gt_row gt_right">28.3</td>
-      <td class="gt_row gt_right">21.3</td>
-      <td class="gt_row gt_right">14.3</td>
-      <td class="gt_row gt_right">7.3</td>
-      <td class="gt_row gt_right">1.9</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">sep</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">87.2</td>
-      <td class="gt_row gt_right">80.2</td>
-      <td class="gt_row gt_right">73.2</td>
-      <td class="gt_row gt_right">66.1</td>
-      <td class="gt_row gt_right">59.1</td>
-      <td class="gt_row gt_right">52.1</td>
-      <td class="gt_row gt_right">45.1</td>
-      <td class="gt_row gt_right">38.1</td>
-      <td class="gt_row gt_right">31.3</td>
-      <td class="gt_row gt_right">24.7</td>
-      <td class="gt_row gt_right">18.6</td>
-      <td class="gt_row gt_right">13.7</td>
-      <td class="gt_row gt_right">11.6</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">oct</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">84.1</td>
-      <td class="gt_row gt_right">77.1</td>
-      <td class="gt_row gt_right">70.2</td>
-      <td class="gt_row gt_right">63.3</td>
-      <td class="gt_row gt_right">56.5</td>
-      <td class="gt_row gt_right">49.9</td>
-      <td class="gt_row gt_right">43.5</td>
-      <td class="gt_row gt_right">37.5</td>
-      <td class="gt_row gt_right">32.0</td>
-      <td class="gt_row gt_right">27.4</td>
-      <td class="gt_row gt_right">24.3</td>
-      <td class="gt_row gt_right">23.1</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">nov</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">87.8</td>
-      <td class="gt_row gt_right">81.3</td>
-      <td class="gt_row gt_right">74.5</td>
-      <td class="gt_row gt_right">68.3</td>
-      <td class="gt_row gt_right">61.8</td>
-      <td class="gt_row gt_right">56.0</td>
-      <td class="gt_row gt_right">50.2</td>
-      <td class="gt_row gt_right">45.3</td>
-      <td class="gt_row gt_right">40.7</td>
-      <td class="gt_row gt_right">37.4</td>
-      <td class="gt_row gt_right">35.1</td>
-      <td class="gt_row gt_right">34.4</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">dec</td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right"></td>
-      <td class="gt_row gt_right">84.3</td>
-      <td class="gt_row gt_right">78.0</td>
-      <td class="gt_row gt_right">71.8</td>
-      <td class="gt_row gt_right">66.1</td>
-      <td class="gt_row gt_right">60.5</td>
-      <td class="gt_row gt_right">55.6</td>
-      <td class="gt_row gt_right">50.9</td>
-      <td class="gt_row gt_right">47.2</td>
-      <td class="gt_row gt_right">44.2</td>
-      <td class="gt_row gt_right">42.4</td>
-      <td class="gt_row gt_right">41.8</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-</div>
-<div id="gtcars" class="section level3">
-<h3 class="hasAnchor">
-<a href="#gtcars" class="anchor"></a><code>gtcars</code>
-</h3>
-<p>The <code>gtcars</code> dataset takes off where <code>mtcars</code> left off. It contains 47 cars from the 2014-2017 model years. Many of the <code>gtcars</code> vehicles are grand tourers. Indeed, many of these provide the ability to cross an entire continent at speed and in comfort yet, when it’s called for, they will allow you to experience driving thrills. The chassis and suspension are in most cases top-notch and supply superb handling and roadholding on all routes one would conceivably encounter during the grand touring experience. The two plus two (2 + 2) seating configuration is smartly designed to deliver comfort for a driver and passenger, adequate space for luggage, and have room to spare.</p>
-<p>The <code>gtcars</code> dataset is a tibble with 47 rows and 15 variables. Here are explanations for each of the variables:</p>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#sdequqnald .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: smaller;
-  background-color: #FFFFFF;
-  width: 80%;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#sdequqnald .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#sdequqnald .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#sdequqnald .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#sdequqnald .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#sdequqnald .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#sdequqnald .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#sdequqnald .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#sdequqnald .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#sdequqnald .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#sdequqnald .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#sdequqnald .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#sdequqnald .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#sdequqnald .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#sdequqnald .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#sdequqnald .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#sdequqnald .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#sdequqnald .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#sdequqnald .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#sdequqnald .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#sdequqnald .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#sdequqnald .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#sdequqnald .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#sdequqnald .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#sdequqnald .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#sdequqnald .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#sdequqnald .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#sdequqnald .gt_left {
-  text-align: left;
-}
-
-#sdequqnald .gt_center {
-  text-align: center;
-}
-
-#sdequqnald .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#sdequqnald .gt_font_normal {
-  font-weight: normal;
-}
-
-#sdequqnald .gt_font_bold {
-  font-weight: bold;
-}
-
-#sdequqnald .gt_font_italic {
-  font-style: italic;
-}
-
-#sdequqnald .gt_super {
-  font-size: 65%;
-}
-
-#sdequqnald .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="sdequqnald" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">mfr</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The name of the car manufacturer</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">model</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The car's model name</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">year</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
-      <td class="gt_row gt_left">The car's model year</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">trim</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">A short description of the car model's trim</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">bdy_style</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">An identifier of the car's body style, which is either coupe, convertible,     sedan, or hatchback</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">hp, hp_rpm</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
-      <td class="gt_row gt_left">The car's horsepower and the associated RPM level</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">trq, trq_rpm</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
-      <td class="gt_row gt_left">The car's torque and the associated RPM level</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">mpg_c, mpg_h</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">int</td>
-      <td class="gt_row gt_left">The miles per gallon fuel efficiency rating for city and highway driving</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">drivetrain</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The car's drivetrain which, for this dataset is either rwd (Rear Wheel Drive)     or awd (All Wheel Drive)</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">trsmn</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The codified transmission type, where the number part is the number of gears; the car could have automatic transmission (a), manual transmission (m), an option to switch between both types (am), or, direct drive (dd)</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">ctry_origin</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The country name for where the vehicle manufacturer is headquartered</td>
-    </tr>
-</tbody>
-</table></div>
-<div id="a-gtcars-example" class="section level4">
-<h4 class="hasAnchor">
-<a href="#a-gtcars-example" class="anchor"></a>A <code>gtcars</code> Example</h4>
-<p>The table that we’ll create from <code>gtcars</code> will meet these requirements:</p>
-<ol style="list-style-type: decimal">
-<li>only include German cars</li>
-<li>limit the dataset to the top two most expensive offerings from each German manufacturer</li>
-<li>the information included will be the manufacturer (<code>mfr</code>), the car model (<code>model</code>), the <code>drivetrain</code>, and the price (<code>msrp</code>)</li>
-<li>add a table title</li>
-<li>combine the car make and model into a single column</li>
-<li>capitalize the <code>drivetrain</code> text</li>
-<li>format the prices as USD currency with commas and no decimal places shown</li>
-<li>relabel the column headings to provide nicer labels</li>
-<li>add two footnotes that explain the <code>drivetrain</code> abbreviations and that state the currency of the <code>msrp</code> prices; ensure that the footnote marks are lowercase letters</li>
-</ol>
-<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Create a gt table based on a preprocessed `gtcars`</span>
-<span class="no">gtcars</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">ctry_origin</span> <span class="kw">==</span> <span class="st">"Germany"</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">mfr</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/top_n.html">top_n</a></span>(<span class="fl">2</span>, <span class="no">msrp</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">ungroup</a></span>() <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="no">mfr</span>, <span class="no">model</span>, <span class="no">drivetrain</span>, <span class="no">msrp</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"Select German Automobiles"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_merge.html">cols_merge</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">mfr</span>, <span class="no">model</span>),
-    <span class="kw">hide_columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">model</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>)),
-    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) <span class="fu"><a href="https://rdrr.io/r/base/chartr.html">toupper</a></span>(<span class="no">x</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
-    <span class="kw">mfr</span> <span class="kw">=</span> <span class="st">"Car"</span>,
-    <span class="kw">drivetrain</span> <span class="kw">=</span> <span class="st">"Drivetrain"</span>,
-    <span class="kw">msrp</span> <span class="kw">=</span> <span class="st">"MSRP"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"Prices in USD."</span>,
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_column_labels.html">cells_column_labels</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">msrp</span>))
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"AWD = All Wheel Drive, RWD = Rear Wheel Drive."</span>,
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_column_labels.html">cells_column_labels</a></span>(<span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">drivetrain</span>))
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/opt_footnote_marks.html">opt_footnote_marks</a></span>(<span class="kw">marks</span> <span class="kw">=</span> <span class="st">"letters"</span>)</pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#gvwnpsiqmg .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#gvwnpsiqmg .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
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-<th colspan="3" class="gt_heading gt_title gt_font_normal" style>Select German Automobiles</th>
-    </tr>
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-</th>
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-<td class="gt_row gt_left">BMW i8</td>
-      <td class="gt_row gt_left">AWD</td>
-      <td class="gt_row gt_right">$140,700</td>
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-          <sup class="gt_footnote_marks"><em>b</em>
-          </sup>
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-</div>
-<div id="sp500" class="section level3">
-<h3 class="hasAnchor">
-<a href="#sp500" class="anchor"></a><code>sp500</code>
-</h3>
-<p>The S&amp;P 500 is a capitalization-weighted index of about 500 leading companies (where bigger companies have more influence within the index) that have common stock listed in either the NYSE or NASDAQ markets. The companies chosen are intended to provide representation of the U.S. economy. This index is a managed list (managed by S&amp;P Dow Jones Indices LLC) with occasional changes of the constituent companies based on their performance and changes in the economy.</p>
-<p>There is daily S&amp;P 500 data available in the <code>sp500</code> dataset, with daily indicators (price statistics, <code>volume</code>, etc.) from 1950 to 2015, inclusive. There are 16,607 rows in the dataset, and 7 variables:</p>
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-}
-</style>
-<div id="fqzkghpubl" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">date</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">date</td>
-      <td class="gt_row gt_left">The date expressed as `Date` values</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">open, high, low, close</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">The day's opening, high, low, and closing prices in USD; the close price is adjusted for splits</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">volume</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">The number of trades for the given `date`</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">adj_close</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">The close price adjusted for both dividends and splits</td>
-    </tr>
-</tbody>
-</table></div>
-<div id="an-sp500-example" class="section level4">
-<h4 class="hasAnchor">
-<a href="#an-sp500-example" class="anchor"></a>An <code>sp500</code> Example</h4>
-<p>The table that we’ll create from <code>sp500</code> will meet these requirements:</p>
-<ol style="list-style-type: decimal">
-<li>use only data from the period <code>2010-06-02</code> to <code>2010-06-15</code>
-</li>
-<li>the adjusted close <code>adj_close</code> column won’t be included</li>
-<li>a title and subtitle will be added to describe the contents of the table</li>
-<li>put the column labels in title case</li>
-<li>format the <code>date</code> column to appear as ‘2 Jun 2010’</li>
-<li>have the price columns (<code>open</code>, <code>high</code>, <code>low</code>, <code>close</code>) appear in USD</li>
-<li>the large numbers in <code>volume</code> will be shown as billions (with the <code>B</code> suffix)</li>
-<li>up- and down-pointing triangles (in green and red) will be added alongside the <code>close</code> price as appropriate</li>
-</ol>
-<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># Define the start and end dates for the data range</span>
-<span class="no">start_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-02"</span>
-<span class="no">end_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-15"</span>
-
-<span class="co"># The HTML decimal references for the black</span>
-<span class="co"># up- and down-pointing triangles are: #9650 and #9660;</span>
-<span class="co"># use an in-line style to apply color</span>
-<span class="no">up_arrow</span> <span class="kw">&lt;-</span> <span class="st">"&lt;span style=\"color:green\"&gt;&amp;#9650;&lt;/span&gt;"</span>
-<span class="no">down_arrow</span> <span class="kw">&lt;-</span> <span class="st">"&lt;span style=\"color:red\"&gt;&amp;#9660;&lt;/span&gt;"</span>
-
-<span class="co"># Create a gt table based on a preprocessed `sp500`</span>
-<span class="no">sp500</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">date</span> <span class="kw">&gt;=</span> <span class="no">start_date</span> <span class="kw">&amp;</span> <span class="no">date</span> <span class="kw">&lt;=</span> <span class="no">end_date</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">adj_close</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"S&amp;P 500"</span>,
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="kw pkg">glue</span><span class="kw ns">::</span><span class="fu"><a href="https://glue.tidyverse.org/reference/glue.html">glue</a></span>(<span class="st">"{start_date} to {end_date}"</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_date.html">fmt_date</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">date</span>),
-    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">7</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">open</span>, <span class="no">high</span>, <span class="no">low</span>, <span class="no">close</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">volume</span>),
-    <span class="kw">scale_by</span> <span class="kw">=</span> <span class="fl">1</span> / <span class="fl">1E9</span>,
-    <span class="kw">pattern</span> <span class="kw">=</span> <span class="st">"{x}B"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="st">"close"</span>,
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">close</span> <span class="kw">&gt;</span> <span class="no">open</span>),
-    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">x</span>, <span class="no">up_arrow</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/text_transform.html">text_transform</a></span>(
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="st">"close"</span>,
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">close</span> <span class="kw">&lt;</span> <span class="no">open</span>),
-    <span class="kw">fn</span> <span class="kw">=</span> <span class="kw">function</span>(<span class="no">x</span>) <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste</a></span>(<span class="no">x</span>, <span class="no">down_arrow</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
-    <span class="kw">date</span> <span class="kw">=</span> <span class="st">"Date"</span>, <span class="kw">open</span> <span class="kw">=</span> <span class="st">"Open"</span>, <span class="kw">high</span> <span class="kw">=</span> <span class="st">"High"</span>,
-    <span class="kw">low</span> <span class="kw">=</span> <span class="st">"Low"</span>, <span class="kw">close</span> <span class="kw">=</span> <span class="st">"Close"</span>, <span class="kw">volume</span> <span class="kw">=</span> <span class="st">"Volume"</span>
-  )</pre></body></html></div>
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-</style>
-<div id="cpmgcykcvp" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="6" class="gt_heading gt_title gt_font_normal" style>S&amp;P 500</th>
-    </tr>
-<tr>
-<th colspan="6" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>2010-06-02 to 2010-06-15</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Date</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Open</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">High</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Low</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Close</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Volume</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">15 Jun 2010</td>
-      <td class="gt_row gt_right">$1,091.21</td>
-      <td class="gt_row gt_right">$1,115.59</td>
-      <td class="gt_row gt_right">$1,091.21</td>
-      <td class="gt_row gt_right">$1,115.23 <span style="color:green">▲</span>
-</td>
-      <td class="gt_row gt_right">4.64B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">14 Jun 2010</td>
-      <td class="gt_row gt_right">$1,095.00</td>
-      <td class="gt_row gt_right">$1,105.91</td>
-      <td class="gt_row gt_right">$1,089.03</td>
-      <td class="gt_row gt_right">$1,089.63 <span style="color:red">▼</span>
-</td>
-      <td class="gt_row gt_right">4.43B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">11 Jun 2010</td>
-      <td class="gt_row gt_right">$1,082.65</td>
-      <td class="gt_row gt_right">$1,092.25</td>
-      <td class="gt_row gt_right">$1,077.12</td>
-      <td class="gt_row gt_right">$1,091.60 <span style="color:green">▲</span>
-</td>
-      <td class="gt_row gt_right">4.06B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">10 Jun 2010</td>
-      <td class="gt_row gt_right">$1,058.77</td>
-      <td class="gt_row gt_right">$1,087.85</td>
-      <td class="gt_row gt_right">$1,058.77</td>
-      <td class="gt_row gt_right">$1,086.84 <span style="color:green">▲</span>
-</td>
-      <td class="gt_row gt_right">5.14B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">9 Jun 2010</td>
-      <td class="gt_row gt_right">$1,062.75</td>
-      <td class="gt_row gt_right">$1,077.74</td>
-      <td class="gt_row gt_right">$1,052.25</td>
-      <td class="gt_row gt_right">$1,055.69 <span style="color:red">▼</span>
-</td>
-      <td class="gt_row gt_right">5.98B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">8 Jun 2010</td>
-      <td class="gt_row gt_right">$1,050.81</td>
-      <td class="gt_row gt_right">$1,063.15</td>
-      <td class="gt_row gt_right">$1,042.17</td>
-      <td class="gt_row gt_right">$1,062.00 <span style="color:green">▲</span>
-</td>
-      <td class="gt_row gt_right">6.19B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">7 Jun 2010</td>
-      <td class="gt_row gt_right">$1,065.84</td>
-      <td class="gt_row gt_right">$1,071.36</td>
-      <td class="gt_row gt_right">$1,049.86</td>
-      <td class="gt_row gt_right">$1,050.47 <span style="color:red">▼</span>
-</td>
-      <td class="gt_row gt_right">5.47B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">4 Jun 2010</td>
-      <td class="gt_row gt_right">$1,098.43</td>
-      <td class="gt_row gt_right">$1,098.43</td>
-      <td class="gt_row gt_right">$1,060.50</td>
-      <td class="gt_row gt_right">$1,064.88 <span style="color:red">▼</span>
-</td>
-      <td class="gt_row gt_right">6.18B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">3 Jun 2010</td>
-      <td class="gt_row gt_right">$1,098.82</td>
-      <td class="gt_row gt_right">$1,105.67</td>
-      <td class="gt_row gt_right">$1,091.81</td>
-      <td class="gt_row gt_right">$1,102.83 <span style="color:green">▲</span>
-</td>
-      <td class="gt_row gt_right">5.00B</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">2 Jun 2010</td>
-      <td class="gt_row gt_right">$1,073.01</td>
-      <td class="gt_row gt_right">$1,098.56</td>
-      <td class="gt_row gt_right">$1,072.03</td>
-      <td class="gt_row gt_right">$1,098.38 <span style="color:green">▲</span>
-</td>
-      <td class="gt_row gt_right">5.03B</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-</div>
-<div id="pizzaplace" class="section level3">
-<h3 class="hasAnchor">
-<a href="#pizzaplace" class="anchor"></a><code>pizzaplace</code>
-</h3>
-<p>The <code>pizzaplace</code> dataset is unusual to say the least. It brings up more questions than answers. Why is it that the ‘The Greek’ pizza (<code>the_greek</code>) comes in <code>XL</code> and <code>XXL</code> sizes whilst (almost) all the other pizzas adhere to the <code>S</code>-<code>M</code>-<code>L</code> paradigm? Why is the ‘Brie Carre’ pizza (<code>brie_carre</code>) only small? Also, is any of this real (?), and, what is the nature of reality? (All of these questions are quite complicated… however, while I can doubt the existence of the material world, I cannot doubt the existence of myself as someone thinking about all the delicious pizzas on offer at <code>pizzaplace</code>.)</p>
-<p>We have somehow obtained the 2015 sales from the pizzaplace, where each row is a pizza sold. There are 32 different types of pizza in 4 different categories: <code>classic</code>, <code>chicken</code>, <code>supreme</code>, and <code>veggie</code>. It was a great year of sales, personal problems notwithstanding. A kitchen fire in late September did not help with the morale situation. Nevertheless, $817,860 in sales for the year! That was indeed something to be cheerful about.</p>
-<p>Let’s learn more about how this fascinating dataset is structured:</p>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#qpiyasedvl .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: smaller;
-  background-color: #FFFFFF;
-  width: 80%;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#qpiyasedvl .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#qpiyasedvl .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#qpiyasedvl .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#qpiyasedvl .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#qpiyasedvl .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#qpiyasedvl .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#qpiyasedvl .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#qpiyasedvl .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#qpiyasedvl .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#qpiyasedvl .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#qpiyasedvl .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#qpiyasedvl .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#qpiyasedvl .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#qpiyasedvl .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#qpiyasedvl .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#qpiyasedvl .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#qpiyasedvl .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#qpiyasedvl .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#qpiyasedvl .gt_left {
-  text-align: left;
-}
-
-#qpiyasedvl .gt_center {
-  text-align: center;
-}
-
-#qpiyasedvl .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#qpiyasedvl .gt_font_normal {
-  font-weight: normal;
-}
-
-#qpiyasedvl .gt_font_bold {
-  font-weight: bold;
-}
-
-#qpiyasedvl .gt_font_italic {
-  font-style: italic;
-}
-
-#qpiyasedvl .gt_super {
-  font-size: 65%;
-}
-
-#qpiyasedvl .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="qpiyasedvl" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">id</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The ID for the order, which consists of one or more pizzas at a given `date` and `time`</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">date</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">A character representation of the order `date`, expressed in the ISO 8601 date format (YYYY-MM-DD)</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">time</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">A character representation of the order time, expressed as a 24-hour time the ISO 8601 extended time format (hh:mm:ss)</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">name</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The short name for the pizza</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">size</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The size of the pizza, which can either be S, M, L, XL (rare!), or XXL (even rarer!); most pizzas are available in the S, M, and L sizes but exceptions apply</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">type</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">The category or type of pizza, which can either be `classic`, `chicken`, `supreme`, or `veggie`</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">price</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">The price of the pizza and the amount that it sold for (in USD)</td>
-    </tr>
-</tbody>
-</table></div>
-<div id="a-pizzaplace-example" class="section level4">
-<h4 class="hasAnchor">
-<a href="#a-pizzaplace-example" class="anchor"></a>A <code>pizzaplace</code> Example</h4>
-<p>Let’s make a reporting table from the <code>pizzaplace</code> dataset with these requirements:</p>
-<ol style="list-style-type: decimal">
-<li>obtain the total sale numbers and revenue from each <code>size</code> of pizza from each category (<code>type</code>)</li>
-<li>create a gt table where each row represents a combination of <code>size</code>-<code>type</code> (<code>size</code> provides the row labels and <code>type</code> forms the row groups)</li>
-<li>add a title to explain the contents of the table</li>
-<li>format the numeric <code>sold</code> column to use commas and no decimal places</li>
-<li>format the currency values (<code>income</code>) to be in <code>USD</code> currency</li>
-<li>add a summary for each grouping that provides total sell counts and revenue amounts</li>
-<li>color the row groups and summary cells to add a little pizzazz</li>
-</ol>
-<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Create a gt table based on a preprocessed `pizzaplace`</span>
-<span class="no">pizzaplace</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="no">type</span>, <span class="no">size</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarize</a></span>(
-    <span class="kw">sold</span> <span class="kw">=</span> <span class="fu">n</span>(),
-    <span class="kw">income</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span>(<span class="no">price</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"size"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(<span class="kw">title</span> <span class="kw">=</span> <span class="st">"Pizzas Sold in 2015"</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">sold</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>,
-    <span class="kw">use_seps</span> <span class="kw">=</span> <span class="fl">TRUE</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">income</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">sold</span>),
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(<span class="kw">TOTAL</span> <span class="kw">=</span> <span class="st">"sum"</span>),
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_number</span>,
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">0</span>,
-    <span class="kw">use_seps</span> <span class="kw">=</span> <span class="fl">TRUE</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/summary_rows.html">summary_rows</a></span>(
-    <span class="kw">groups</span> <span class="kw">=</span> <span class="fl">TRUE</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="st">"income"</span>,
-    <span class="kw">fns</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span>(<span class="kw">TOTAL</span> <span class="kw">=</span> <span class="st">"sum"</span>),
-    <span class="kw">formatter</span> <span class="kw">=</span> <span class="no">fmt_currency</span>,
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
-    <span class="kw">summary_row.background.color</span> <span class="kw">=</span> <span class="st">"#ACEACE"</span>,
-    <span class="kw">row_group.background.color</span> <span class="kw">=</span> <span class="st">"#FFEFDB"</span>
-  )
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * chicken -&gt; chicken...1</span>
-<span class="co">#&gt; * chicken -&gt; chicken...2</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * classic -&gt; classic...1</span>
-<span class="co">#&gt; * classic -&gt; classic...2</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * supreme -&gt; supreme...1</span>
-<span class="co">#&gt; * supreme -&gt; supreme...2</span>
-<span class="co">#&gt; New names:</span>
-<span class="co">#&gt; * veggie -&gt; veggie...1</span>
-<span class="co">#&gt; * veggie -&gt; veggie...2</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#ckaehssopn .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
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-  border-right-color: #D3D3D3;
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-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#ckaehssopn .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#ckaehssopn .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#ckaehssopn .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#ckaehssopn .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#ckaehssopn .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#ckaehssopn .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#ckaehssopn .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFEFDB;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#ckaehssopn .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFEFDB;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#ckaehssopn .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#ckaehssopn .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#ckaehssopn .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#ckaehssopn .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#ckaehssopn .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#ckaehssopn .gt_summary_row {
-  color: #333333;
-  background-color: #ACEACE;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#ckaehssopn .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#ckaehssopn .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#ckaehssopn .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#ckaehssopn .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#ckaehssopn .gt_left {
-  text-align: left;
-}
-
-#ckaehssopn .gt_center {
-  text-align: center;
-}
-
-#ckaehssopn .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#ckaehssopn .gt_font_normal {
-  font-weight: normal;
-}
-
-#ckaehssopn .gt_font_bold {
-  font-weight: bold;
-}
-
-#ckaehssopn .gt_font_italic {
-  font-style: italic;
-}
-
-#ckaehssopn .gt_super {
-  font-size: 65%;
-}
-
-#ckaehssopn .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="ckaehssopn" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="3" class="gt_heading gt_title gt_font_normal" style>Pizzas Sold in 2015</th>
-    </tr>
-<tr>
-<th colspan="3" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style></th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">sold</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">income</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="3" class="gt_group_heading">chicken</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">L</td>
-      <td class="gt_row gt_center">4,932</td>
-      <td class="gt_row gt_right">$102,339.00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">M</td>
-      <td class="gt_row gt_center">3,894</td>
-      <td class="gt_row gt_right">$65,224.50</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">S</td>
-      <td class="gt_row gt_center">2,224</td>
-      <td class="gt_row gt_right">$28,356.00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
-      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">11,050</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$195,919.50</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="3" class="gt_group_heading">classic</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">L</td>
-      <td class="gt_row gt_center">4,057</td>
-      <td class="gt_row gt_right">$74,518.50</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">M</td>
-      <td class="gt_row gt_center">4,112</td>
-      <td class="gt_row gt_right">$60,581.75</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">S</td>
-      <td class="gt_row gt_center">6,139</td>
-      <td class="gt_row gt_right">$69,870.25</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">XL</td>
-      <td class="gt_row gt_center">552</td>
-      <td class="gt_row gt_right">$14,076.00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">XXL</td>
-      <td class="gt_row gt_center">28</td>
-      <td class="gt_row gt_right">$1,006.60</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
-      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">14,888</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$220,053.10</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="3" class="gt_group_heading">supreme</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">L</td>
-      <td class="gt_row gt_center">4,564</td>
-      <td class="gt_row gt_right">$94,258.50</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">M</td>
-      <td class="gt_row gt_center">4,046</td>
-      <td class="gt_row gt_right">$66,475.00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">S</td>
-      <td class="gt_row gt_center">3,377</td>
-      <td class="gt_row gt_right">$47,463.50</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
-      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">11,987</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$208,197.00</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="3" class="gt_group_heading">veggie</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">L</td>
-      <td class="gt_row gt_center">5,403</td>
-      <td class="gt_row gt_right">$104,202.70</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">M</td>
-      <td class="gt_row gt_center">3,583</td>
-      <td class="gt_row gt_right">$57,101.00</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">S</td>
-      <td class="gt_row gt_center">2,663</td>
-      <td class="gt_row gt_right">$32,386.75</td>
-    </tr>
-<tr>
-<td class="gt_row gt_stub gt_right gt_summary_row gt_first_summary_row">TOTAL</td>
-      <td class="gt_row gt_center gt_summary_row gt_first_summary_row">11,649</td>
-      <td class="gt_row gt_right gt_summary_row gt_first_summary_row">$193,690.45</td>
-    </tr>
-</tbody>
-</table></div>
-</div>
-</div>
-<div id="exibble" class="section level3">
-<h3 class="hasAnchor">
-<a href="#exibble" class="anchor"></a><code>exibble</code>
-</h3>
-<p>The example tibble that’s useful for <strong>gt</strong> is called <code>exibble</code>. It’s 8 rows, has clear ordering of data, and the columns contain data that can be tested with the various <strong>gt</strong> formatter functions (<code>fmt*()</code>). Here is a table describing the columns of <code>exibble</code>:</p>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#ptfncyashx .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: smaller;
-  background-color: #FFFFFF;
-  width: 80%;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#ptfncyashx .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#ptfncyashx .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#ptfncyashx .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#ptfncyashx .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#ptfncyashx .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#ptfncyashx .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#ptfncyashx .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#ptfncyashx .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#ptfncyashx .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#ptfncyashx .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#ptfncyashx .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#ptfncyashx .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#ptfncyashx .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#ptfncyashx .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#ptfncyashx .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#ptfncyashx .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#ptfncyashx .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#ptfncyashx .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#ptfncyashx .gt_left {
-  text-align: left;
-}
-
-#ptfncyashx .gt_center {
-  text-align: center;
-}
-
-#ptfncyashx .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#ptfncyashx .gt_font_normal {
-  font-weight: normal;
-}
-
-#ptfncyashx .gt_font_bold {
-  font-weight: bold;
-}
-
-#ptfncyashx .gt_font_italic {
-  font-style: italic;
-}
-
-#ptfncyashx .gt_super {
-  font-size: 65%;
-}
-
-#ptfncyashx .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="ptfncyashx" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Column</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Type</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">Description</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">num</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">A numeric column ordered with increasingly larger values</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">char</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">A character column composed of names of fruits from a to h</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">fctr</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">fct</td>
-      <td class="gt_row gt_left">A factor column with numbers from 1 to 8, written out</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">date, time, datetime</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">Character columns with dates, times, and datetimes</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">currency</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">dbl</td>
-      <td class="gt_row gt_left">A numeric column that is useful for testing currency-based formatting</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">row</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">A character column in the format `row_X` which can be useful for testing with row label in a table stub</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left" style="font-family: Courier;">group</td>
-      <td class="gt_row gt_left" style="font-family: Courier;">chr</td>
-      <td class="gt_row gt_left">A character column with four `grp_a` values and four `grp_b` values which can be useful for testing tables that contain row groups</td>
-    </tr>
-</tbody>
-</table></div>
-<div id="an-exibble-example" class="section level4">
-<h4 class="hasAnchor">
-<a href="#an-exibble-example" class="anchor"></a>An <code>exibble</code> Example</h4>
-<p>Let’s test as many formatter functions as possible with <code>exibble</code> while also using row labels and row groups (furnished by the <code>row</code> and <code>group</code> columns). We’ll format <code>num</code> to display numbers with 2 decimal places. The dates in <code>date</code> will be formatted with <code>date_style</code> <code>6</code> (the <code>m_day_year</code> style, use <code><a href="../reference/info_date_style.html">info_date_style()</a></code> to learn about all of them). The 24-h time values in <code>time</code> will use <code>time_style</code> <code>4</code> (<code>hm_p</code>, more info at <code><a href="../reference/info_time_style.html">info_time_style()</a></code>). Datetimes as in <code>datetime</code> column can be formatted with the <code><a href="../reference/fmt_datetime.html">fmt_datetime()</a></code> function (which uses the <code>date_style</code> and <code>time_style</code> arguments). The column <code>currency</code> will be formatted as a currency with <code>fmt_currency</code> and we’ll consider these values to be euros (<code>currency = "EUR"</code>).</p>
-<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Create a gt table based on `exibble`</span>
-<span class="no">exibble</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(
-    <span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"row"</span>,
-    <span class="kw">groupname_col</span> <span class="kw">=</span> <span class="st">"group"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_number.html">fmt_number</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">num</span>),
-    <span class="kw">decimals</span> <span class="kw">=</span> <span class="fl">2</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_date.html">fmt_date</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">date</span>),
-    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">6</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_time.html">fmt_time</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">time</span>),
-    <span class="kw">time_style</span> <span class="kw">=</span> <span class="fl">4</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_datetime.html">fmt_datetime</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">datetime</span>),
-    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">6</span>,
-    <span class="kw">time_style</span> <span class="kw">=</span> <span class="fl">4</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">currency</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"EUR"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_options.html">tab_options</a></span>(
-    <span class="kw">column_labels.font.size</span> <span class="kw">=</span> <span class="st">"small"</span>,
-    <span class="kw">table.font.size</span> <span class="kw">=</span> <span class="st">"small"</span>,
-    <span class="kw">row_group.font.size</span> <span class="kw">=</span> <span class="st">"small"</span>,
-    <span class="kw">data_row.padding</span> <span class="kw">=</span> <span class="fu"><a href="../reference/px.html">px</a></span>(<span class="fl">3</span>)
-  )</pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#cyfkjzuccx .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: small;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#cyfkjzuccx .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#cyfkjzuccx .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#cyfkjzuccx .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#cyfkjzuccx .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#cyfkjzuccx .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#cyfkjzuccx .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#cyfkjzuccx .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#cyfkjzuccx .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: small;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#cyfkjzuccx .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#cyfkjzuccx .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#cyfkjzuccx .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#cyfkjzuccx .gt_row {
-  padding-top: 3px;
-  padding-bottom: 3px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#cyfkjzuccx .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#cyfkjzuccx .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#cyfkjzuccx .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#cyfkjzuccx .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#cyfkjzuccx .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#cyfkjzuccx .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#cyfkjzuccx .gt_left {
-  text-align: left;
-}
-
-#cyfkjzuccx .gt_center {
-  text-align: center;
-}
-
-#cyfkjzuccx .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#cyfkjzuccx .gt_font_normal {
-  font-weight: normal;
-}
-
-#cyfkjzuccx .gt_font_bold {
-  font-weight: bold;
-}
-
-#cyfkjzuccx .gt_font_italic {
-  font-style: italic;
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-      <td class="gt_row gt_left">May 5, 2018 4:00 AM</td>
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-      <td class="gt_row gt_left">NA</td>
-      <td class="gt_row gt_left">Jun 6, 2018 4:11 PM</td>
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-      <td class="gt_row gt_left">8:20 PM</td>
-      <td class="gt_row gt_left">NA</td>
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-<p>The <strong>gt</strong> package is all about making it simple to produce nice-looking display tables. Display tables? Well yes, we are trying to distinguish between data tables (e.g., tibbles, <code>data.frame</code>s, etc.) and those tables you’d find in a web page, a journal article, or in a magazine. Such tables can likewise be called presentation tables, summary tables, or just tables really. Here are some examples, ripped straight from the web:</p>
-<p><img src="images/tables_from_the_web.png" width="100%"></p>
-<p>We can think of display tables as output only, where we’d not want to use them as input ever again. Other features include annotations, table element styling, and text transformations that serve to communicate the subject matter more clearly.</p>
-<div id="a-walkthrough-of-the-gt-basics-with-a-simple-table" class="section level3">
-<h3 class="hasAnchor">
-<a href="#a-walkthrough-of-the-gt-basics-with-a-simple-table" class="anchor"></a>A Walkthrough of the <strong>gt</strong> Basics with a Simple Table</h3>
-<p>Let’s use a less common dataset that is available in the R <strong>datasets</strong> package: <code>islands</code>. It’s actually not a data frame but a named vector. That’s okay though, we can use use <strong>dplyr</strong> and prepare a tibble from it:</p>
-<div class="sourceCode" id="cb1"><html><body><pre class="r"><span class="co"># Take the `islands` dataset and use some</span>
-<span class="co"># dplyr functionality to obtain the ten</span>
-<span class="co"># biggest islands in the world</span>
-<span class="no">islands_tbl</span> <span class="kw">&lt;-</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/reexports.html">tibble</a></span>(
-    <span class="kw">name</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html">names</a></span>(<span class="no">islands</span>),
-    <span class="kw">size</span> <span class="kw">=</span> <span class="no">islands</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html">arrange</a></span>(<span class="fu">desc</span>(<span class="no">size</span>)) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/slice.html">slice</a></span>(<span class="fl">1</span>:<span class="fl">10</span>)
-
-<span class="co"># Display the table</span>
-<span class="no">islands_tbl</span>
-<span class="co">#&gt; # A tibble: 10 x 2</span>
-<span class="co">#&gt;    name           size</span>
-<span class="co">#&gt;    &lt;chr&gt;         &lt;dbl&gt;</span>
-<span class="co">#&gt;  1 Asia          16988</span>
-<span class="co">#&gt;  2 Africa        11506</span>
-<span class="co">#&gt;  3 North America  9390</span>
-<span class="co">#&gt;  4 South America  6795</span>
-<span class="co">#&gt;  5 Antarctica     5500</span>
-<span class="co">#&gt;  6 Europe         3745</span>
-<span class="co">#&gt;  7 Australia      2968</span>
-<span class="co">#&gt;  8 Greenland       840</span>
-<span class="co">#&gt;  9 New Guinea      306</span>
-<span class="co">#&gt; 10 Borneo          280</span></pre></body></html></div>
-<p>Given that <code>islands_tbl</code> is a tibble, we now have a suitable input for <strong>gt</strong>.</p>
-<p>The main entry point into the <strong>gt</strong> API is the <code><a href="../reference/gt.html">gt()</a></code> function. If we pass <code>islands_tbl</code> to the <em>function</em> <code><a href="../reference/gt.html">gt()</a></code>, we’ll get a <strong>gt Table</strong> as output. As an aside, we could have easily used a data frame instead as valid <strong>Table Data</strong> for <strong>gt</strong>.</p>
-<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="co"># Create a display table showing ten of</span>
-<span class="co"># the largest islands in the world</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span> <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">islands_tbl</span>)
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#skmoceplzt .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#skmoceplzt .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#skmoceplzt .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#skmoceplzt .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#skmoceplzt .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#skmoceplzt .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#skmoceplzt .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#skmoceplzt .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#skmoceplzt .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#skmoceplzt .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#skmoceplzt .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#skmoceplzt .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#skmoceplzt .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#skmoceplzt .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#skmoceplzt .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#skmoceplzt .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#skmoceplzt .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#skmoceplzt .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#skmoceplzt .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#skmoceplzt .gt_left {
-  text-align: left;
-}
-
-#skmoceplzt .gt_center {
-  text-align: center;
-}
-
-#skmoceplzt .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#skmoceplzt .gt_font_normal {
-  font-weight: normal;
-}
-
-#skmoceplzt .gt_font_bold {
-  font-weight: bold;
-}
-
-#skmoceplzt .gt_font_italic {
-  font-style: italic;
-}
-
-#skmoceplzt .gt_super {
-  font-size: 65%;
-}
-
-#skmoceplzt .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="skmoceplzt" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-</table></div>
-<p>That doesn’t look too bad. Sure, it’s basic but we really didn’t really ask for much. We did receive a proper table with column labels and the data. Also, that default striping is a nice touch. Oftentimes however, you’ll want a bit more: a <strong>Table header</strong>, a <strong>Stub</strong>, and sometimes <em>footnotes</em> and <em>source notes</em> in the <strong>Table Footer</strong> part.</p>
-</div>
-<div id="adding-parts-to-this-simple-table" class="section level3">
-<h3 class="hasAnchor">
-<a href="#adding-parts-to-this-simple-table" class="anchor"></a>Adding Parts to this Simple Table</h3>
-<p>The <strong>gt</strong> package makes it relatively easy to add parts so that the resulting <strong>gt Table</strong> better conveys the information you want to present. These table parts work well together and there the possible variations in arrangement can handle most tabular presentation needs. The previous <strong>gt Table</strong> demonstrated had only two parts, the <strong>Column Labels</strong> and the <strong>Table Body</strong>. The next few examples will show all of the other table parts that are available.</p>
-<p>This is the way the main parts of a table (and their subparts) fit together:</p>
-<p align="center">
-<img src="../man/figures/gt_parts_of_a_table.svg" width="100%"></p>
-<p>The parts (roughly from top to bottom) are:</p>
-<ul>
-<li>the <strong>Table Header</strong> (optional; with a <strong>title</strong> and possibly a <strong>subtitle</strong>)</li>
-<li>the <strong>Stub</strong> and the <strong>Stub Head</strong> (optional; contains <em>row labels</em>, optionally within <em>row groups</em> having <em>row group labels</em> and possibly <em>summary labels</em> when a summary is present)</li>
-<li>the <strong>Column Labels</strong> (contains <em>column labels</em>, optionally under <em>spanner column labels</em>)</li>
-<li>the <strong>Table Body</strong> (contains <em>columns</em> and <em>rows</em> of <em>cells</em>)</li>
-<li>the <strong>Table Footer</strong> (optional; possibly with <strong>footnotes</strong> and <strong>source notes</strong>)</li>
-</ul>
-<p>The way that we add parts like the <strong>Table Header</strong> and <em>footnotes</em> in the <strong>Table Footer</strong> is to use the <code>tab_*()</code> family of functions. A <strong>Table Header</strong> is easy to add so let’s see how the previous table looks with a <strong>title</strong> and a <strong>subtitle</strong>. We can add this part using the <code><a href="../reference/tab_header.html">tab_header()</a></code> function:</p>
-<div class="sourceCode" id="cb3"><html><body><pre class="r"><span class="co"># Make a display table with the `islands_tbl`</span>
-<span class="co"># table; put a heading just above the column labels</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"Large Landmasses of the World"</span>,
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"The top ten largest are presented"</span>
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#caiiyhzwxp .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#caiiyhzwxp .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#caiiyhzwxp .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#caiiyhzwxp .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#caiiyhzwxp .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#caiiyhzwxp .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#caiiyhzwxp .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#caiiyhzwxp .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#caiiyhzwxp .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#caiiyhzwxp .gt_column_spanner_outer:last-child {
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-<div id="caiiyhzwxp" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
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-<td class="gt_row gt_left">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
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-      <td class="gt_row gt_right">2968</td>
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-      <td class="gt_row gt_right">840</td>
-    </tr>
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-      <td class="gt_row gt_right">306</td>
-    </tr>
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-<td class="gt_row gt_left">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-</table></div>
-<p>The <strong>Header</strong> table part provides an opportunity to describe the data that’s presented. The <code>subtitle</code>, which functions as a subtitle, is an optional part of the <strong>Header</strong>. We may also style the <code>title</code> and <code>subtitle</code> using Markdown! We do this by wrapping the values passed to <code>title</code> or <code>subtitle</code> with the <code><a href="../reference/md.html">md()</a></code> function. Here is an example with the table data truncated for brevity:</p>
-<div class="sourceCode" id="cb4"><html><body><pre class="r"><span class="co"># Use markdown for the heading's `title` and `subtitle` to</span>
-<span class="co"># add bold and italicized characters</span>
-<span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="no">islands_tbl</span>[<span class="fl">1</span>:<span class="fl">2</span>,]) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"**Large Landmasses of the World**"</span>),
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The *top two* largest are presented"</span>)
-  )</pre></body></html></div>
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-</style>
-<div id="metfygbmlu" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style><strong>Large Landmasses of the World</strong></th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The <em>top two</em> largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-</tbody>
-</table></div>
-<p>A <strong>source note</strong> can be added to the table’s <strong>footer</strong> through use of the <code><a href="../reference/tab_source_note.html">tab_source_note()</a></code> function. It works in the same way as <code><a href="../reference/tab_header.html">tab_header()</a></code> (it also allows for Markdown inputs) except it can be called multiple times—each invocation results in the addition of a source note.</p>
-<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="co"># Display the `islands_tbl` data with a heading and</span>
-<span class="co"># two source notes</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
-    <span class="kw">source_note</span> <span class="kw">=</span> <span class="st">"Source: The World Almanac and Book of Facts, 1975, page 406."</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
-    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Reference: McNeil, D. R. (1977) *Interactive Data Analysis*. Wiley."</span>)
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
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-  border-bottom-style: solid;
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-  border-top-style: solid;
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-}
-
-#juozpleoga .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
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-  padding-left: 5px;
-  padding-right: 5px;
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-}
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-#juozpleoga .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
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-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
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-}
-
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-  padding-left: 0;
-}
-
-#juozpleoga .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
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-#juozpleoga .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#juozpleoga .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#juozpleoga .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#juozpleoga .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
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-#juozpleoga .gt_from_md > :first-child {
-  margin-top: 0;
-}
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-#juozpleoga .gt_from_md > :last-child {
-  margin-bottom: 0;
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-#juozpleoga .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
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-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
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-}
-
-#juozpleoga .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#juozpleoga .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#juozpleoga .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#juozpleoga .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#juozpleoga .gt_first_grand_summary_row {
-  padding-top: 8px;
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-  border-top-color: #D3D3D3;
-}
-
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-  border-top-style: solid;
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-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
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-
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-  color: #333333;
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-}
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-  color: #333333;
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-}
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-  font-style: italic;
-}
-
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-  font-size: 65%;
-}
-
-#juozpleoga .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="juozpleoga" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes">
-<tr>
-<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
-    </tr>
-<tr>
-<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
-    </tr>
-</tfoot>
-</table></div>
-<p>Footnotes live inside the <strong>Footer</strong> part and their footnote marks are attached to cell data. Footnotes are added with the <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> function. The helper function <code><a href="../reference/cells_body.html">cells_body()</a></code> can be used with the <code>location</code> argument to specify which data cells should be the target of the footnote. The <code><a href="../reference/cells_body.html">cells_body()</a></code> helper has the two arguments <code>columns</code> and <code>rows</code>. For each of these, we can supply (1) a vector of colnames or rownames, (2) a vector of column/row indices, (3) bare column names wrapped in <code><a href="https://dplyr.tidyverse.org/reference/vars.html">vars()</a></code> or row labels within <code><a href="https://rdrr.io/r/base/c.html">c()</a></code>, or (4) a select helper function (<code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">starts_with()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">ends_with()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">contains()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">matches()</a></code>, <code><a href="https://tidyselect.r-lib.org/reference/one_of.html">one_of()</a></code>, and <code><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">everything()</a></code>). For <code>rows</code> specifically, we can use a conditional statement with column names as variables (e.g., <code>size &gt; 15000</code>).</p>
-<p>Here is a simple example on how a footnotes can be added to a table cell. Let’s add a footnote that references the <code>North America</code> and <code>South America</code> cells in the <code>name</code> column:</p>
-<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="co"># Add footnotes (the same text) to two different</span>
-<span class="co"># cell; data cells are targeted with `data_cells()`</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"The Americas."</span>,
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">name</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="fl">3</span>:<span class="fl">4</span>)
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
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-  display: table;
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-  width: auto;
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-  border-top-width: 2px;
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-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#hmnrehstnd .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
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-}
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-  border-bottom-width: 2px;
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-  border-top-style: solid;
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-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
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-  color: #333333;
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-  font-size: 100%;
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-  vertical-align: bottom;
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-}
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-<div id="hmnrehstnd" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">North America<sup class="gt_footnote_marks">1</sup>
-</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">South America<sup class="gt_footnote_marks">1</sup>
-</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes">
-<tr>
-<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
-    </tr>
-<tr>
-<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
-    </tr>
-</tfoot>
-<tfoot><tr class="gt_footnotes">
-<td colspan="2">
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>1</em>
-          </sup>
-           
-          The Americas.
-          <br></p>
-      </td>
-    </tr></tfoot>
-</table></div>
-<p>Here is a slightly more complex example of adding footnotes that use expressions in <code>rows</code> to help target cells in a column by the underlying data in <code>islands_tbl</code>. First, a set of <strong>dplyr</strong> statements obtains the name of the ‘island’ by largest landmass. This is assigned to the <code>largest</code> object and is used in the first <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> call that targets the cell in the <code>size</code> column that is next to a <code>name</code> value that is stored in <code>largest</code> (‘Asia’). The second <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code> is similar except we are supplying a conditional statement that gets the lowest population.</p>
-<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="co"># Determine the row that contains the</span>
-<span class="co"># largest landmass ('Asia')</span>
-<span class="no">largest</span> <span class="kw">&lt;-</span>
-  <span class="no">islands_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu">arrange</span>(<span class="fu">desc</span>(<span class="no">size</span>)) <span class="kw">%&gt;%</span>
-  <span class="fu">slice</span>(<span class="fl">1</span>) <span class="kw">%&gt;%</span>
-  <span class="fu">pull</span>(<span class="no">name</span>)
-
-<span class="co"># Create two additional footnotes, using the</span>
-<span class="co"># `columns` and `where` arguments of `data_cells()`</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The **largest** by area."</span>),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">name</span> <span class="kw">==</span> <span class="no">largest</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"The lowest by population."</span>,
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">size</span> <span class="kw">==</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html">min</a></span>(<span class="no">size</span>))
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
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-}
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-<div id="pvhjxgvrhp" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">name</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left">Asia</td>
-      <td class="gt_row gt_right">16988<sup class="gt_footnote_marks">1</sup>
-</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">North America<sup class="gt_footnote_marks">2</sup>
-</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">South America<sup class="gt_footnote_marks">2</sup>
-</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left">Borneo</td>
-      <td class="gt_row gt_right">280<sup class="gt_footnote_marks">3</sup>
-</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes">
-<tr>
-<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
-    </tr>
-<tr>
-<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
-    </tr>
-</tfoot>
-<tfoot><tr class="gt_footnotes">
-<td colspan="2">
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>1</em>
-          </sup>
-           
-          The <strong>largest</strong> by area.
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>2</em>
-          </sup>
-           
-          The Americas.
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>3</em>
-          </sup>
-           
-          The lowest by population.
-          <br></p>
-      </td>
-    </tr></tfoot>
-</table></div>
-<p>We were able to supply the reference locations in the table by using the <code><a href="../reference/cells_body.html">cells_body()</a></code> helper function and supplying the necessary targeting through the <code>columns</code> and <code>rows</code> arguments. Other <code>cells_*()</code> functions have similar interfaces and they allow us to target cells in different parts of the table.</p>
-</div>
-<div id="the-stub" class="section level3">
-<h3 class="hasAnchor">
-<a href="#the-stub" class="anchor"></a>The Stub</h3>
-<p>The <strong>Stub</strong> is the area to the left in a table that contains <em>row labels</em>, and may contain <em>row group labels</em>, and <em>summary labels</em>. Those subparts can be grouped in a sequence of <em>row groups</em>. The <strong>Stub Head</strong> provides a location for a label that describes the <strong>Stub</strong>. The <strong>Stub</strong> is optional since there are cases where a <strong>Stub</strong> wouldn’t be useful (e.g., the display tables presented above were just fine without a <strong>Stub</strong>).</p>
-<p>An easy way to generate a <strong>Stub</strong> part is by specifying a stub column in the <code><a href="../reference/gt.html">gt()</a></code> function with the <code>rowname_col</code> argument. Alternatively, we can have an input dataset with a column named <code>rowname</code>—this magic column will signal to <strong>gt</strong> that that column should be used as the stub, making <em>row labels</em>. Let’s add a stub with our <code>islands_tbl</code> dataset by modifying the call to <code><a href="../reference/gt.html">gt()</a></code>:</p>
-<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="co"># Create a gt table showing ten of the</span>
-<span class="co"># largest islands in the world; this</span>
-<span class="co"># time with a stub</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">islands_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">rowname_col</span> <span class="kw">=</span> <span class="st">"name"</span>)
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
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-#hpjmvzyces .gt_col_headings {
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-  border-top-width: 2px;
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-  border-bottom-style: solid;
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-  border-left-width: 1px;
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-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
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-#hpjmvzyces .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#hpjmvzyces .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
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-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#hpjmvzyces .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#hpjmvzyces .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#hpjmvzyces .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#hpjmvzyces .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#hpjmvzyces .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#hpjmvzyces .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#hpjmvzyces .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#hpjmvzyces .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#hpjmvzyces .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#hpjmvzyces .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#hpjmvzyces .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#hpjmvzyces .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#hpjmvzyces .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#hpjmvzyces .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#hpjmvzyces .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#hpjmvzyces .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#hpjmvzyces .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#hpjmvzyces .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#hpjmvzyces .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#hpjmvzyces .gt_left {
-  text-align: left;
-}
-
-#hpjmvzyces .gt_center {
-  text-align: center;
-}
-
-#hpjmvzyces .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#hpjmvzyces .gt_font_normal {
-  font-weight: normal;
-}
-
-#hpjmvzyces .gt_font_bold {
-  font-weight: bold;
-}
-
-#hpjmvzyces .gt_font_italic {
-  font-style: italic;
-}
-
-#hpjmvzyces .gt_super {
-  font-size: 65%;
-}
-
-#hpjmvzyces .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="hpjmvzyces" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1"></th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left gt_stub">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-</table></div>
-<p>Notice that the landmass names are off the the left in an unstriped area? That’s the <strong>stub</strong>. We can apply what’s known as a <strong>stubhead label</strong>. This label can be added with the <code><a href="../reference/tab_stubhead.html">tab_stubhead()</a></code> function:</p>
-<div class="sourceCode" id="cb9"><html><body><pre class="r"><span class="co"># Generate a simple table with a stub</span>
-<span class="co"># and add a stubhead label</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_stubhead.html">tab_stubhead</a></span>(<span class="kw">label</span> <span class="kw">=</span> <span class="st">"landmass"</span>)
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#fekohyxzvq .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
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-
-#fekohyxzvq .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#fekohyxzvq .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#fekohyxzvq .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#fekohyxzvq .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#fekohyxzvq .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#fekohyxzvq .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#fekohyxzvq .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#fekohyxzvq .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#fekohyxzvq .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#fekohyxzvq .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#fekohyxzvq .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#fekohyxzvq .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#fekohyxzvq .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#fekohyxzvq .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#fekohyxzvq .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#fekohyxzvq .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#fekohyxzvq .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#fekohyxzvq .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#fekohyxzvq .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#fekohyxzvq .gt_left {
-  text-align: left;
-}
-
-#fekohyxzvq .gt_center {
-  text-align: center;
-}
-
-#fekohyxzvq .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#fekohyxzvq .gt_font_normal {
-  font-weight: normal;
-}
-
-#fekohyxzvq .gt_font_bold {
-  font-weight: bold;
-}
-
-#fekohyxzvq .gt_font_italic {
-  font-style: italic;
-}
-
-#fekohyxzvq .gt_super {
-  font-size: 65%;
-}
-
-#fekohyxzvq .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="fekohyxzvq" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">landmass</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left gt_stub">Asia</td>
-      <td class="gt_row gt_right">16988</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Antarctica</td>
-      <td class="gt_row gt_right">5500</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-</table></div>
-<p>A very important thing to note here is that the table now has one column. Before, when there was no <strong>stub</strong>, two columns were present (with <strong>column labels</strong> <code>name</code> and <code>size</code>) but now column number <code>1</code> (the only column) is <code>size</code>.</p>
-<p>To apply our table parts as before (up to and including the footnotes) we use the following statements:</p>
-<div class="sourceCode" id="cb10"><html><body><pre class="r"><span class="co"># Display the `islands_tbl` data with a stub,</span>
-<span class="co"># a heading, source notes, and footnotes</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"Large Landmasses of the World"</span>,
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"The top ten largest are presented"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
-    <span class="kw">source_note</span> <span class="kw">=</span> <span class="st">"Source: The World Almanac and Book of Facts, 1975, page 406."</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_source_note.html">tab_source_note</a></span>(
-    <span class="kw">source_note</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"Reference: McNeil, D. R. (1977) *Interactive Data Analysis*. Wiley."</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="fu"><a href="../reference/md.html">md</a></span>(<span class="st">"The **largest** by area."</span>),
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="no">largest</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_footnote.html">tab_footnote</a></span>(
-    <span class="kw">footnote</span> <span class="kw">=</span> <span class="st">"The lowest by population."</span>,
-    <span class="kw">locations</span> <span class="kw">=</span> <span class="fu"><a href="../reference/cells_body.html">cells_body</a></span>(
-      <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">size</span>),
-      <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/select_helpers.html">contains</a></span>(<span class="st">"arc"</span>))
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#xhzkicahqh .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#xhzkicahqh .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#xhzkicahqh .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
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-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#xhzkicahqh .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#xhzkicahqh .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#xhzkicahqh .gt_column_spanner_outer:last-child {
-  padding-right: 0;
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-#xhzkicahqh .gt_column_spanner {
-  border-bottom-style: solid;
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-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#xhzkicahqh .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
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-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#xhzkicahqh .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#xhzkicahqh .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#xhzkicahqh .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#xhzkicahqh .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#xhzkicahqh .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#xhzkicahqh .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#xhzkicahqh .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#xhzkicahqh .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#xhzkicahqh .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#xhzkicahqh .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#xhzkicahqh .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#xhzkicahqh .gt_left {
-  text-align: left;
-}
-
-#xhzkicahqh .gt_center {
-  text-align: center;
-}
-
-#xhzkicahqh .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#xhzkicahqh .gt_font_normal {
-  font-weight: normal;
-}
-
-#xhzkicahqh .gt_font_bold {
-  font-weight: bold;
-}
-
-#xhzkicahqh .gt_font_italic {
-  font-style: italic;
-}
-
-#xhzkicahqh .gt_super {
-  font-size: 65%;
-}
-
-#xhzkicahqh .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="xhzkicahqh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">landmass</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_left gt_stub">Asia</td>
-      <td class="gt_row gt_right">16988<sup class="gt_footnote_marks">1</sup>
-</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Antarctica</td>
-      <td class="gt_row gt_right">5500<sup class="gt_footnote_marks">2</sup>
-</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes">
-<tr>
-<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
-    </tr>
-<tr>
-<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
-    </tr>
-</tfoot>
-<tfoot><tr class="gt_footnotes">
-<td colspan="2">
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>1</em>
-          </sup>
-           
-          The <strong>largest</strong> by area.
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>2</em>
-          </sup>
-           
-          The lowest by population.
-          <br></p>
-      </td>
-    </tr></tfoot>
-</table></div>
-<p>Let’s incorporate row groups into the display table. This divides rows into groups, creating <em>row groups</em>, and results in a display of a <em>row group labels</em> right above the each group. This can be easily done with a table containing row labels. We can make a new <em>row group</em> with each call of the <code><a href="../reference/tab_row_group.html">tab_row_group()</a></code> function. The inputs are group names in the <code>group</code> argument, and row references in the <code>rows</code> argument. We can use any of the strategies to reference rows as we did we footnotes (e.g., vectors of names/indices, select helpers, etc.).</p>
-<p>Here we will create three row groups (with row group labels <code>continent</code>, <code>country</code>, and <code>subregion</code>) to have a grouping of rows.</p>
-<div class="sourceCode" id="cb11"><html><body><pre class="r"><span class="co"># Create three row groups with the</span>
-<span class="co"># `tab_row_group()` function</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_row_group.html">tab_row_group</a></span>(
-    <span class="kw">group</span> <span class="kw">=</span> <span class="st">"continent"</span>,
-    <span class="kw">rows</span> <span class="kw">=</span> <span class="fl">1</span>:<span class="fl">6</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_row_group.html">tab_row_group</a></span>(
-    <span class="kw">group</span> <span class="kw">=</span> <span class="st">"country"</span>,
-    <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Australia"</span>, <span class="st">"Greenland"</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_row_group.html">tab_row_group</a></span>(
-    <span class="kw">group</span> <span class="kw">=</span> <span class="st">"subregion"</span>,
-    <span class="kw">rows</span> <span class="kw">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"New Guinea"</span>, <span class="st">"Borneo"</span>)
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span>
-<span class="co">#&gt; Warning in min(rows_matched): no non-missing arguments to min; returning Inf</span>
-<span class="co">#&gt; Warning in max(rows_matched): no non-missing arguments to max; returning -Inf</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#mtfklilywh .gt_table {
-  display: table;
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-}
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-#mtfklilywh .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
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-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#mtfklilywh .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
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-}
-
-#mtfklilywh .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
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-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#mtfklilywh .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#mtfklilywh .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#mtfklilywh .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#mtfklilywh .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#mtfklilywh .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#mtfklilywh .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#mtfklilywh .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#mtfklilywh .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#mtfklilywh .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#mtfklilywh .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#mtfklilywh .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#mtfklilywh .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#mtfklilywh .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#mtfklilywh .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#mtfklilywh .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#mtfklilywh .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#mtfklilywh .gt_left {
-  text-align: left;
-}
-
-#mtfklilywh .gt_center {
-  text-align: center;
-}
-
-#mtfklilywh .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#mtfklilywh .gt_font_normal {
-  font-weight: normal;
-}
-
-#mtfklilywh .gt_font_bold {
-  font-weight: bold;
-}
-
-#mtfklilywh .gt_font_italic {
-  font-style: italic;
-}
-
-#mtfklilywh .gt_super {
-  font-size: 65%;
-}
-
-#mtfklilywh .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="mtfklilywh" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="2" class="gt_heading gt_title gt_font_normal" style>Large Landmasses of the World</th>
-    </tr>
-<tr>
-<th colspan="2" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>The top ten largest are presented</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings"><tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">landmass</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">size</th>
-    </tr></thead>
-<tbody class="gt_table_body">
-<tr class="gt_group_heading_row">
-<td colspan="2" class="gt_group_heading">subregion</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">New Guinea</td>
-      <td class="gt_row gt_right">306</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Borneo</td>
-      <td class="gt_row gt_right">280</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="2" class="gt_group_heading">country</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Australia</td>
-      <td class="gt_row gt_right">2968</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Greenland</td>
-      <td class="gt_row gt_right">840</td>
-    </tr>
-<tr class="gt_group_heading_row">
-<td colspan="2" class="gt_group_heading">continent</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Asia</td>
-      <td class="gt_row gt_right">16988<sup class="gt_footnote_marks">1</sup>
-</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Africa</td>
-      <td class="gt_row gt_right">11506</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">North America</td>
-      <td class="gt_row gt_right">9390</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">South America</td>
-      <td class="gt_row gt_right">6795</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Antarctica</td>
-      <td class="gt_row gt_right">5500<sup class="gt_footnote_marks">2</sup>
-</td>
-    </tr>
-<tr>
-<td class="gt_row gt_left gt_stub">Europe</td>
-      <td class="gt_row gt_right">3745</td>
-    </tr>
-</tbody>
-<tfoot class="gt_sourcenotes">
-<tr>
-<td class="gt_sourcenote" colspan="2">Source: The World Almanac and Book of Facts, 1975, page 406.</td>
-    </tr>
-<tr>
-<td class="gt_sourcenote" colspan="2">Reference: McNeil, D. R. (1977) <em>Interactive Data Analysis</em>. Wiley.</td>
-    </tr>
-</tfoot>
-<tfoot><tr class="gt_footnotes">
-<td colspan="2">
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>1</em>
-          </sup>
-           
-          The <strong>largest</strong> by area.
-          <br></p>
-        <p class="gt_footnote">
-          <sup class="gt_footnote_marks"><em>2</em>
-          </sup>
-           
-          The lowest by population.
-          <br></p>
-      </td>
-    </tr></tfoot>
-</table></div>
-<p>Three <em>row groups</em> have been made since there are three unique categories under <code>groupname</code>. Across the top of each <em>row group</em> is the <em>row group label</em> contained in a separate row (these cut across the field and they contain nothing but the <em>row group label</em>). A rearrangement of rows is carried out to ensure each of the rows is collected within the appropriate <em>row groups</em>.</p>
-<p>Having groups of rows in <em>row groups</em> is a great way to present information. Including data summaries particular to each group is a natural extension of this idea. This process of adding summary rows with <em>summary labels</em> is covered in a separate article (<em>Creating Summary Lines</em>).</p>
-<p>Another way to make row groups is to have the magic column <code>groupname</code> present in the input data table. For our above example with <code>islands_tbl</code>, a <code>groupname</code> column with the categories <code>continent</code>, <code>country</code>, and <code>subregion</code> in the appropriate rows would produce row groups automatically (i.e., there would be no need to use the <code><a href="../reference/tab_row_group.html">tab_row_group()</a></code> statements). This strategy of supplying group names in a <code>groupname</code> column name can sometimes be advantageous since we can rely on functions such as those available in <strong>dplyr</strong> to generate the categories (e.g., using <code>case_when()</code> or <code>if_else()</code>).</p>
-</div>
-<div id="the-column-labels" class="section level3">
-<h3 class="hasAnchor">
-<a href="#the-column-labels" class="anchor"></a>The Column Labels</h3>
-<p>The table’s <strong>Column Labels</strong> part contains, at a minimum, columns and their <em>column labels</em>. The last example had a single column: <code>size</code>. Just as in the <strong>Stub</strong>, we can create groupings called <em>spanner columns</em> that encompass one or more columns.</p>
-<p>To better demonstrate how <strong>Column Labels</strong> work and are displayed, let’s use an input data table with more columns. In this case, that input table will be <code>airquality</code>. It has the following columns:</p>
-<ul>
-<li>
-<code>Ozone</code>: mean ground-level ozone in parts per billion by volume (ppbV), measured between 13:00 and 15:00</li>
-<li>
-<code>Solar.R</code>: solar radiation in Langley units (cal/m<sup>2</sup>), measured between 08:00 and noon</li>
-<li>
-<code>Wind</code>: mean wind speed in miles per hour (mph)</li>
-<li>
-<code>Temp</code>: maximum daily air temperature in degrees Fahrenheit (°F)</li>
-<li>
-<code>Month</code>, <code>Day</code>: the numeric month and day of month for the record</li>
-</ul>
-<p>We know that all measurements took place in 1973, so a <code>year</code> column will be added to the dataset before it is passed to <code><a href="../reference/gt.html">gt()</a></code>.</p>
-<p>Let’s organize the time information under a <code>Time</code> <em>spanner column label</em>, and put the other columns under a <code>Measurement</code> <em>spanner column label</em>. We can do this with the <code><a href="../reference/tab_spanner.html">tab_spanner()</a></code> function.</p>
-<div class="sourceCode" id="cb12"><html><body><pre class="r"><span class="co"># Modify the `airquality` dataset by adding the year</span>
-<span class="co"># of the measurements (1973) and limiting to 10 rows</span>
-<span class="no">airquality_m</span> <span class="kw">&lt;-</span>
-  <span class="no">airquality</span> <span class="kw">%&gt;%</span>
-  <span class="fu">mutate</span>(<span class="kw">Year</span> <span class="kw">=</span> <span class="fl">1973L</span>) <span class="kw">%&gt;%</span>
-  <span class="fu">slice</span>(<span class="fl">1</span>:<span class="fl">10</span>)
-
-<span class="co"># Create a display table using the `airquality`</span>
-<span class="co"># dataset; arrange columns into groups</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="fu"><a href="../reference/gt.html">gt</a></span>(<span class="kw">data</span> <span class="kw">=</span> <span class="no">airquality_m</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"New York Air Quality Measurements"</span>,
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="st">"Daily measurements in New York City (May 1-10, 1973)"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
-    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Time"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">Year</span>, <span class="no">Month</span>, <span class="no">Day</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/tab_spanner.html">tab_spanner</a></span>(
-    <span class="kw">label</span> <span class="kw">=</span> <span class="st">"Measurement"</span>,
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">Ozone</span>, <span class="no">Solar.R</span>, <span class="no">Wind</span>, <span class="no">Temp</span>)
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#qnfyrrzvuy .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#qnfyrrzvuy .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#qnfyrrzvuy .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#qnfyrrzvuy .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#qnfyrrzvuy .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#qnfyrrzvuy .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#qnfyrrzvuy .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#qnfyrrzvuy .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#qnfyrrzvuy .gt_empty_group_heading {
-  padding: 0.5px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: middle;
-}
-
-#qnfyrrzvuy .gt_striped {
-  background-color: rgba(128, 128, 128, 0.05);
-}
-
-#qnfyrrzvuy .gt_from_md > :first-child {
-  margin-top: 0;
-}
-
-#qnfyrrzvuy .gt_from_md > :last-child {
-  margin-bottom: 0;
-}
-
-#qnfyrrzvuy .gt_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  margin: 10px;
-  border-top-style: solid;
-  border-top-width: 1px;
-  border-top-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: middle;
-  overflow-x: hidden;
-}
-
-#qnfyrrzvuy .gt_stub {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-right-style: solid;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  padding-left: 12px;
-}
-
-#qnfyrrzvuy .gt_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#qnfyrrzvuy .gt_first_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_grand_summary_row {
-  color: #333333;
-  background-color: #FFFFFF;
-  text-transform: inherit;
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-}
-
-#qnfyrrzvuy .gt_first_grand_summary_row {
-  padding-top: 8px;
-  padding-bottom: 8px;
-  padding-left: 5px;
-  padding-right: 5px;
-  border-top-style: double;
-  border-top-width: 6px;
-  border-top-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_table_body {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_footnotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_footnote {
-  margin: 0px;
-  font-size: 90%;
-  padding: 4px;
-}
-
-#qnfyrrzvuy .gt_sourcenotes {
-  color: #333333;
-  background-color: #FFFFFF;
-  border-bottom-style: none;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-}
-
-#qnfyrrzvuy .gt_sourcenote {
-  font-size: 90%;
-  padding: 4px;
-}
-
-#qnfyrrzvuy .gt_left {
-  text-align: left;
-}
-
-#qnfyrrzvuy .gt_center {
-  text-align: center;
-}
-
-#qnfyrrzvuy .gt_right {
-  text-align: right;
-  font-variant-numeric: tabular-nums;
-}
-
-#qnfyrrzvuy .gt_font_normal {
-  font-weight: normal;
-}
-
-#qnfyrrzvuy .gt_font_bold {
-  font-weight: bold;
-}
-
-#qnfyrrzvuy .gt_font_italic {
-  font-style: italic;
-}
-
-#qnfyrrzvuy .gt_super {
-  font-size: 65%;
-}
-
-#qnfyrrzvuy .gt_footnote_marks {
-  font-style: italic;
-  font-size: 65%;
-}
-</style>
-<div id="qnfyrrzvuy" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="7" class="gt_heading gt_title gt_font_normal" style>New York Air Quality Measurements</th>
-    </tr>
-<tr>
-<th colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>Daily measurements in New York City (May 1-10, 1973)</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4">
-        <span class="gt_column_spanner">Measurement</span>
-      </th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Time</span>
-      </th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Ozone</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Solar.R</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Wind</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Temp</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Month</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Day</th>
-    </tr>
-</thead>
-<tbody class="gt_table_body">
-<tr>
-<td class="gt_row gt_center">41</td>
-      <td class="gt_row gt_center">190</td>
-      <td class="gt_row gt_right">7.4</td>
-      <td class="gt_row gt_center">67</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">1</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">36</td>
-      <td class="gt_row gt_center">118</td>
-      <td class="gt_row gt_right">8.0</td>
-      <td class="gt_row gt_center">72</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">2</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">12</td>
-      <td class="gt_row gt_center">149</td>
-      <td class="gt_row gt_right">12.6</td>
-      <td class="gt_row gt_center">74</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">3</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">18</td>
-      <td class="gt_row gt_center">313</td>
-      <td class="gt_row gt_right">11.5</td>
-      <td class="gt_row gt_center">62</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">4</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_right">14.3</td>
-      <td class="gt_row gt_center">56</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">5</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">28</td>
-      <td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_right">14.9</td>
-      <td class="gt_row gt_center">66</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">6</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">23</td>
-      <td class="gt_row gt_center">299</td>
-      <td class="gt_row gt_right">8.6</td>
-      <td class="gt_row gt_center">65</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">7</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">19</td>
-      <td class="gt_row gt_center">99</td>
-      <td class="gt_row gt_right">13.8</td>
-      <td class="gt_row gt_center">59</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">8</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">8</td>
-      <td class="gt_row gt_center">19</td>
-      <td class="gt_row gt_right">20.1</td>
-      <td class="gt_row gt_center">61</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">9</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_center">194</td>
-      <td class="gt_row gt_right">8.6</td>
-      <td class="gt_row gt_center">69</td>
-      <td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">10</td>
-    </tr>
-</tbody>
-</table></div>
-<p>We can do two more things to make this presentable:</p>
-<ul>
-<li>move the <code>Time</code> columns to the beginning of the series (using <code><a href="../reference/cols_move_to_start.html">cols_move_to_start()</a></code>)</li>
-<li>customize the column labels so that they are more descriptive (using <code><a href="../reference/cols_label.html">cols_label()</a></code>)</li>
-</ul>
-<p>Let’s do both of these things in the next example.</p>
-<div class="sourceCode" id="cb13"><html><body><pre class="r"><span class="co"># Move the time-based columns to the start of</span>
-<span class="co"># the column series; modify the column labels of</span>
-<span class="co"># the measurement-based columns</span>
-<span class="no">gt_tbl</span> <span class="kw">&lt;-</span>
-  <span class="no">gt_tbl</span> <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_move_to_start.html">cols_move_to_start</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">Year</span>, <span class="no">Month</span>, <span class="no">Day</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="../reference/cols_label.html">cols_label</a></span>(
-    <span class="kw">Ozone</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Ozone,&lt;br&gt;ppbV"</span>),
-    <span class="kw">Solar.R</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Solar R.,&lt;br&gt;cal/m&lt;sup&gt;2&lt;/sup&gt;"</span>),
-    <span class="kw">Wind</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Wind,&lt;br&gt;mph"</span>),
-    <span class="kw">Temp</span> <span class="kw">=</span> <span class="fu"><a href="../reference/html.html">html</a></span>(<span class="st">"Temp,&lt;br&gt;&amp;deg;F"</span>)
-  )
-
-<span class="co"># Show the gt Table</span>
-<span class="no">gt_tbl</span></pre></body></html></div>
-<style>html {
-  font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;
-}
-
-#jjpqqgmdxw .gt_table {
-  display: table;
-  border-collapse: collapse;
-  margin-left: auto;
-  margin-right: auto;
-  color: #333333;
-  font-size: 16px;
-  background-color: #FFFFFF;
-  width: auto;
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #A8A8A8;
-  border-right-style: none;
-  border-right-width: 2px;
-  border-right-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #A8A8A8;
-  border-left-style: none;
-  border-left-width: 2px;
-  border-left-color: #D3D3D3;
-}
-
-#jjpqqgmdxw .gt_heading {
-  background-color: #FFFFFF;
-  text-align: center;
-  border-bottom-color: #FFFFFF;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#jjpqqgmdxw .gt_title {
-  color: #333333;
-  font-size: 125%;
-  font-weight: initial;
-  padding-top: 4px;
-  padding-bottom: 4px;
-  border-bottom-color: #FFFFFF;
-  border-bottom-width: 0;
-}
-
-#jjpqqgmdxw .gt_subtitle {
-  color: #333333;
-  font-size: 85%;
-  font-weight: initial;
-  padding-top: 0;
-  padding-bottom: 4px;
-  border-top-color: #FFFFFF;
-  border-top-width: 0;
-}
-
-#jjpqqgmdxw .gt_bottom_border {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-}
-
-#jjpqqgmdxw .gt_col_headings {
-  border-top-style: solid;
-  border-top-width: 2px;
-  border-top-color: #D3D3D3;
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-}
-
-#jjpqqgmdxw .gt_col_heading {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  border-left-style: none;
-  border-left-width: 1px;
-  border-left-color: #D3D3D3;
-  border-right-style: none;
-  border-right-width: 1px;
-  border-right-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  padding-left: 5px;
-  padding-right: 5px;
-  overflow-x: hidden;
-}
-
-#jjpqqgmdxw .gt_column_spanner_outer {
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: normal;
-  text-transform: inherit;
-  padding-top: 0;
-  padding-bottom: 0;
-  padding-left: 4px;
-  padding-right: 4px;
-}
-
-#jjpqqgmdxw .gt_column_spanner_outer:first-child {
-  padding-left: 0;
-}
-
-#jjpqqgmdxw .gt_column_spanner_outer:last-child {
-  padding-right: 0;
-}
-
-#jjpqqgmdxw .gt_column_spanner {
-  border-bottom-style: solid;
-  border-bottom-width: 2px;
-  border-bottom-color: #D3D3D3;
-  vertical-align: bottom;
-  padding-top: 5px;
-  padding-bottom: 6px;
-  overflow-x: hidden;
-  display: inline-block;
-  width: 100%;
-}
-
-#jjpqqgmdxw .gt_group_heading {
-  padding: 8px;
-  color: #333333;
-  background-color: #FFFFFF;
-  font-size: 100%;
-  font-weight: initial;
-  text-transform: inherit;
-  border-top-style: solid;
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-  color: #333333;
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-<div id="jjpqqgmdxw" style="overflow-x:auto;overflow-y:auto;width:auto;height:auto;"><table class="table gt_table">
-<thead class="gt_header">
-<tr>
-<th colspan="7" class="gt_heading gt_title gt_font_normal" style>New York Air Quality Measurements</th>
-    </tr>
-<tr>
-<th colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>Daily measurements in New York City (May 1-10, 1973)</th>
-    </tr>
-</thead>
-<thead class="gt_col_headings">
-<tr>
-<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3">
-        <span class="gt_column_spanner">Time</span>
-      </th>
-      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4">
-        <span class="gt_column_spanner">Measurement</span>
-      </th>
-    </tr>
-<tr>
-<th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Year</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Month</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Day</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Ozone,<br>ppbV</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Solar R.,<br>cal/m<sup>2</sup>
-</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Wind,<br>mph</th>
-      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Temp,<br>°F</th>
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-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">1</td>
-      <td class="gt_row gt_center">41</td>
-      <td class="gt_row gt_center">190</td>
-      <td class="gt_row gt_right">7.4</td>
-      <td class="gt_row gt_center">67</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">2</td>
-      <td class="gt_row gt_center">36</td>
-      <td class="gt_row gt_center">118</td>
-      <td class="gt_row gt_right">8.0</td>
-      <td class="gt_row gt_center">72</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">3</td>
-      <td class="gt_row gt_center">12</td>
-      <td class="gt_row gt_center">149</td>
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-      <td class="gt_row gt_center">74</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">4</td>
-      <td class="gt_row gt_center">18</td>
-      <td class="gt_row gt_center">313</td>
-      <td class="gt_row gt_right">11.5</td>
-      <td class="gt_row gt_center">62</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_right">14.3</td>
-      <td class="gt_row gt_center">56</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">6</td>
-      <td class="gt_row gt_center">28</td>
-      <td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_right">14.9</td>
-      <td class="gt_row gt_center">66</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">7</td>
-      <td class="gt_row gt_center">23</td>
-      <td class="gt_row gt_center">299</td>
-      <td class="gt_row gt_right">8.6</td>
-      <td class="gt_row gt_center">65</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">8</td>
-      <td class="gt_row gt_center">19</td>
-      <td class="gt_row gt_center">99</td>
-      <td class="gt_row gt_right">13.8</td>
-      <td class="gt_row gt_center">59</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">9</td>
-      <td class="gt_row gt_center">8</td>
-      <td class="gt_row gt_center">19</td>
-      <td class="gt_row gt_right">20.1</td>
-      <td class="gt_row gt_center">61</td>
-    </tr>
-<tr>
-<td class="gt_row gt_center">1973</td>
-      <td class="gt_row gt_center">5</td>
-      <td class="gt_row gt_center">10</td>
-      <td class="gt_row gt_center">NA</td>
-      <td class="gt_row gt_center">194</td>
-      <td class="gt_row gt_right">8.6</td>
-      <td class="gt_row gt_center">69</td>
-    </tr>
-</tbody>
-</table></div>
-<p>Note that even though columns were moved using <code><a href="../reference/cols_move_to_start.html">cols_move_to_start()</a></code>, the <em>spanner column labels</em> still spanned above the correct <em>column labels</em>. There are a number of functions that <strong>gt</strong> provides to move columns, including <code><a href="../reference/cols_move.html">cols_move()</a></code>, <code><a href="../reference/cols_move_to_end.html">cols_move_to_end()</a></code>; there’s even a function to hide columns: <code><a href="../reference/cols_hide.html">cols_hide()</a></code>.</p>
-<p>Multiple columns can be renamed in a single use of <code><a href="../reference/cols_label.html">cols_label()</a></code>. Further to this, the helper functions <code><a href="../reference/md.html">md()</a></code> and <code><a href="../reference/html.html">html()</a></code> can be used to create column labels with additional styling. In the above example, we provided column labels as HTML so that we can insert linebreaks with <code>&lt;br&gt;</code>, insert a superscripted <code>2</code> (with <code>&lt;sup&gt;2&lt;/sup&gt;</code>), and insert a degree symbol as an HTML entity (<code>&amp;deg;</code>).</p>
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diff --git a/docs/authors.html b/docs/authors.html
deleted file mode 100644
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-        <p><strong>Richard Iannone</strong>. Author, maintainer. <a href='https://orcid.org/0000-0003-3925-190X' target='orcid.widget' aria-label='ORCID'><span class='fab fa-orcid orcid' aria-hidden='true'></span></a>
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- * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
- * Copyright 2015 Aidan Feldman
- * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
-
-/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */
-
-/* All levels of nav */
-nav[data-toggle='toc'] .nav > li > a {
-  display: block;
-  padding: 4px 20px;
-  font-size: 13px;
-  font-weight: 500;
-  color: #767676;
-}
-nav[data-toggle='toc'] .nav > li > a:hover,
-nav[data-toggle='toc'] .nav > li > a:focus {
-  padding-left: 19px;
-  color: #563d7c;
-  text-decoration: none;
-  background-color: transparent;
-  border-left: 1px solid #563d7c;
-}
-nav[data-toggle='toc'] .nav > .active > a,
-nav[data-toggle='toc'] .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav > .active:focus > a {
-  padding-left: 18px;
-  font-weight: bold;
-  color: #563d7c;
-  background-color: transparent;
-  border-left: 2px solid #563d7c;
-}
-
-/* Nav: second level (shown on .active) */
-nav[data-toggle='toc'] .nav .nav {
-  display: none; /* Hide by default, but at >768px, show it */
-  padding-bottom: 10px;
-}
-nav[data-toggle='toc'] .nav .nav > li > a {
-  padding-top: 1px;
-  padding-bottom: 1px;
-  padding-left: 30px;
-  font-size: 12px;
-  font-weight: normal;
-}
-nav[data-toggle='toc'] .nav .nav > li > a:hover,
-nav[data-toggle='toc'] .nav .nav > li > a:focus {
-  padding-left: 29px;
-}
-nav[data-toggle='toc'] .nav .nav > .active > a,
-nav[data-toggle='toc'] .nav .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav .nav > .active:focus > a {
-  padding-left: 28px;
-  font-weight: 500;
-}
-
-/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */
-nav[data-toggle='toc'] .nav > .active > ul {
-  display: block;
-}
diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js
deleted file mode 100644
index 1cdd573b2..000000000
--- a/docs/bootstrap-toc.js
+++ /dev/null
@@ -1,159 +0,0 @@
-/*!
- * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
- * Copyright 2015 Aidan Feldman
- * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
-(function() {
-  'use strict';
-
-  window.Toc = {
-    helpers: {
-      // return all matching elements in the set, or their descendants
-      findOrFilter: function($el, selector) {
-        // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/
-        // http://stackoverflow.com/a/12731439/358804
-        var $descendants = $el.find(selector);
-        return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])');
-      },
-
-      generateUniqueIdBase: function(el) {
-        var text = $(el).text();
-        var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-');
-        return anchor || el.tagName.toLowerCase();
-      },
-
-      generateUniqueId: function(el) {
-        var anchorBase = this.generateUniqueIdBase(el);
-        for (var i = 0; ; i++) {
-          var anchor = anchorBase;
-          if (i > 0) {
-            // add suffix
-            anchor += '-' + i;
-          }
-          // check if ID already exists
-          if (!document.getElementById(anchor)) {
-            return anchor;
-          }
-        }
-      },
-
-      generateAnchor: function(el) {
-        if (el.id) {
-          return el.id;
-        } else {
-          var anchor = this.generateUniqueId(el);
-          el.id = anchor;
-          return anchor;
-        }
-      },
-
-      createNavList: function() {
-        return $('<ul class="nav"></ul>');
-      },
-
-      createChildNavList: function($parent) {
-        var $childList = this.createNavList();
-        $parent.append($childList);
-        return $childList;
-      },
-
-      generateNavEl: function(anchor, text) {
-        var $a = $('<a></a>');
-        $a.attr('href', '#' + anchor);
-        $a.text(text);
-        var $li = $('<li></li>');
-        $li.append($a);
-        return $li;
-      },
-
-      generateNavItem: function(headingEl) {
-        var anchor = this.generateAnchor(headingEl);
-        var $heading = $(headingEl);
-        var text = $heading.data('toc-text') || $heading.text();
-        return this.generateNavEl(anchor, text);
-      },
-
-      // Find the first heading level (`<h1>`, then `<h2>`, etc.) that has more than one element. Defaults to 1 (for `<h1>`).
-      getTopLevel: function($scope) {
-        for (var i = 1; i <= 6; i++) {
-          var $headings = this.findOrFilter($scope, 'h' + i);
-          if ($headings.length > 1) {
-            return i;
-          }
-        }
-
-        return 1;
-      },
-
-      // returns the elements for the top level, and the next below it
-      getHeadings: function($scope, topLevel) {
-        var topSelector = 'h' + topLevel;
-
-        var secondaryLevel = topLevel + 1;
-        var secondarySelector = 'h' + secondaryLevel;
-
-        return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
-      },
-
-      getNavLevel: function(el) {
-        return parseInt(el.tagName.charAt(1), 10);
-      },
-
-      populateNav: function($topContext, topLevel, $headings) {
-        var $context = $topContext;
-        var $prevNav;
-
-        var helpers = this;
-        $headings.each(function(i, el) {
-          var $newNav = helpers.generateNavItem(el);
-          var navLevel = helpers.getNavLevel(el);
-
-          // determine the proper $context
-          if (navLevel === topLevel) {
-            // use top level
-            $context = $topContext;
-          } else if ($prevNav && $context === $topContext) {
-            // create a new level of the tree and switch to it
-            $context = helpers.createChildNavList($prevNav);
-          } // else use the current $context
-
-          $context.append($newNav);
-
-          $prevNav = $newNav;
-        });
-      },
-
-      parseOps: function(arg) {
-        var opts;
-        if (arg.jquery) {
-          opts = {
-            $nav: arg
-          };
-        } else {
-          opts = arg;
-        }
-        opts.$scope = opts.$scope || $(document.body);
-        return opts;
-      }
-    },
-
-    // accepts a jQuery object, or an options object
-    init: function(opts) {
-      opts = this.helpers.parseOps(opts);
-
-      // ensure that the data attribute is in place for styling
-      opts.$nav.attr('data-toggle', 'toc');
-
-      var $topContext = this.helpers.createChildNavList(opts.$nav);
-      var topLevel = this.helpers.getTopLevel(opts.$scope);
-      var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
-      this.helpers.populateNav($topContext, topLevel, $headings);
-    }
-  };
-
-  $(function() {
-    $('nav[data-toggle="toc"]').each(function(i, el) {
-      var $nav = $(el);
-      Toc.init($nav);
-    });
-  });
-})();
diff --git a/docs/docsearch.css b/docs/docsearch.css
deleted file mode 100644
index e5f1fe1df..000000000
--- a/docs/docsearch.css
+++ /dev/null
@@ -1,148 +0,0 @@
-/* Docsearch -------------------------------------------------------------- */
-/*
-  Source: https://github.com/algolia/docsearch/
-  License: MIT
-*/
-
-.algolia-autocomplete {
-  display: block;
-  -webkit-box-flex: 1;
-  -ms-flex: 1;
-  flex: 1
-}
-
-.algolia-autocomplete .ds-dropdown-menu {
-  width: 100%;
-  min-width: none;
-  max-width: none;
-  padding: .75rem 0;
-  background-color: #fff;
-  background-clip: padding-box;
-  border: 1px solid rgba(0, 0, 0, .1);
-  box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
-}
-
-@media (min-width:768px) {
-  .algolia-autocomplete .ds-dropdown-menu {
-      width: 175%
-  }
-}
-
-.algolia-autocomplete .ds-dropdown-menu::before {
-  display: none
-}
-
-.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
-  padding: 0;
-  background-color: rgb(255,255,255);
-  border: 0;
-  max-height: 80vh;
-}
-
-.algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
-  margin-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion {
-  padding: 0;
-  overflow: visible
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--category-header {
-  padding: .125rem 1rem;
-  margin-top: 0;
-  font-size: 1.3em;
-  font-weight: 500;
-  color: #00008B;
-  border-bottom: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
-    float: none;
-    padding-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
-  float: none;
-  width: auto;
-  padding: 0;
-  text-align: left
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content {
-  float: none;
-  width: auto;
-  padding: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content::before {
-  display: none
-}
-
-.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
-  padding-top: .75rem;
-  margin-top: .75rem;
-  border-top: 1px solid rgba(0, 0, 0, .1)
-}
-
-.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
-  display: block;
-  padding: .1rem 1rem;
-  margin-bottom: 0.1;
-  font-size: 1.0em;
-  font-weight: 400
-  /* display: none */
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--title {
-  display: block;
-  padding: .25rem 1rem;
-  margin-bottom: 0;
-  font-size: 0.9em;
-  font-weight: 400
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text {
-  padding: 0 1rem .5rem;
-  margin-top: -.25rem;
-  font-size: 0.8em;
-  font-weight: 400;
-  line-height: 1.25
-}
-
-.algolia-autocomplete .algolia-docsearch-footer {
-  width: 110px;
-  height: 20px;
-  z-index: 3;
-  margin-top: 10.66667px;
-  float: right;
-  font-size: 0;
-  line-height: 0;
-}
-
-.algolia-autocomplete .algolia-docsearch-footer--logo {
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diff --git a/docs/docsearch.js b/docs/docsearch.js
deleted file mode 100644
index b35504cd3..000000000
--- a/docs/docsearch.js
+++ /dev/null
@@ -1,85 +0,0 @@
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-  var url = "";
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-<script src="pkgdown.js"></script><meta property="og:title" content="Easily Create Presentation-Ready Display Tables">
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-<div id="gt-" class="section level1">
-
-
-<p>With the <strong>gt</strong> package, anyone can make wonderful-looking tables using the <strong>R</strong> programming language. The <strong>gt</strong> philosophy: we can construct a wide variety of useful tables with a cohesive set of table parts. These include the <em>table header</em>, the <em>stub</em>, the <em>column labels</em> and <em>spanner column labels</em>, the <em>table body</em>, and the <em>table footer</em>.</p>
-<p align="center">
-</p>
-<p><img src="reference/figures/gt_parts_of_a_table.svg" width="800px"></p>
-
-<p>It all begins with preprocessed <strong>table data</strong> (be it a tibble or a data frame). You then decide how to compose your <strong>gt table</strong> with the elements and formatting you need for the task at hand. Finally, the table is rendered by printing it at the console, including it in an R Markdown document, or exporting to a file using <code><a href="reference/gtsave.html">gtsave()</a></code>. Currently, <strong>gt</strong> supports <strong>HTML</strong> output, with <strong>LaTeX</strong> and <strong>RTF</strong> planned for the future.</p>
-<p align="center">
-</p>
-<p><img src="reference/figures/gt_workflow_diagram.svg" width="800px"></p>
-
-<p>The <strong>gt</strong> package is designed to be both straightforward yet powerful. The emphasis is on simple functions for the everyday display table needs. Here is a brief example of how to use <strong>gt</strong> to create a table from the included <code>sp500</code> dataset:</p>
-<div class="sourceCode" id="cb1"><pre class="r"><span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">gt</span>)
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">tidyverse</span>)
-<span class="fu"><a href="https://rdrr.io/r/base/library.html">library</a></span>(<span class="no">glue</span>)
-
-<span class="co"># Define the start and end dates for the data range</span>
-<span class="no">start_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-07"</span>
-<span class="no">end_date</span> <span class="kw">&lt;-</span> <span class="st">"2010-06-14"</span>
-
-<span class="co"># Create a gt table based on preprocessed</span>
-<span class="co"># `sp500` table data</span>
-<span class="no">sp500</span> <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="no">date</span> <span class="kw">&gt;=</span> <span class="no">start_date</span> <span class="kw">&amp;</span> <span class="no">date</span> <span class="kw">&lt;=</span> <span class="no">end_date</span>) <span class="kw">%&gt;%</span>
-  <span class="kw pkg">dplyr</span><span class="kw ns">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(-<span class="no">adj_close</span>) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="reference/gt.html">gt</a></span>() <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="reference/tab_header.html">tab_header</a></span>(
-    <span class="kw">title</span> <span class="kw">=</span> <span class="st">"S&amp;P 500"</span>,
-    <span class="kw">subtitle</span> <span class="kw">=</span> <span class="kw pkg">glue</span><span class="kw ns">::</span><span class="fu"><a href="https://glue.tidyverse.org/reference/glue.html">glue</a></span>(<span class="st">"{start_date} to {end_date}"</span>)
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="reference/fmt_date.html">fmt_date</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">date</span>),
-    <span class="kw">date_style</span> <span class="kw">=</span> <span class="fl">3</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="reference/fmt_currency.html">fmt_currency</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">open</span>, <span class="no">high</span>, <span class="no">low</span>, <span class="no">close</span>),
-    <span class="kw">currency</span> <span class="kw">=</span> <span class="st">"USD"</span>
-  ) <span class="kw">%&gt;%</span>
-  <span class="fu"><a href="reference/fmt_number.html">fmt_number</a></span>(
-    <span class="kw">columns</span> <span class="kw">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span>(<span class="no">volume</span>),
-    <span class="kw">suffixing</span> <span class="kw">=</span> <span class="fl">TRUE</span>
-  )</pre></div>
-<p align="center">
-</p>
-<p><img src="reference/figures/gt_sp500_table.svg" width="1200px"></p>
-
-<p>There are six datasets included in <strong>gt</strong>: <code>countrypops</code>, <code>sza</code>, <code>gtcars</code>, <code>sp500</code>, <code>pizzaplace</code>, and <code>exibble</code>. All of them are useful for experimenting with <strong>gt</strong>’s functions.</p>
-<p>Beyond this simple example, there are many functions available in <strong>gt</strong> for creating super-customized tables.</p>
-<p>Want to try this out? Then, take the <strong>gt</strong> Test Drive on <strong>RStudio Cloud</strong>. It’s full of ready-to-run examples.</p>
-<p align="center">
-</p>
-<p><a href="https://rstudio.cloud/project/779965"> <img src="reference/figures/gt-test-drive.svg" alt="RStudio Cloud Example" height="60px"></a></p>
-
-<p>You can install the development version of <strong>gt</strong> from <strong>GitHub</strong>:</p>
-<div class="sourceCode" id="cb2"><pre class="r"><span class="kw pkg">remotes</span><span class="kw ns">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html">install_github</a></span>(<span class="st">"rstudio/gt"</span>)</pre></div>
-<p>If you encounter a bug, have usage questions, or want to share ideas to make this package better, please feel free to file an <a href="https://github.com/rstudio/gt/issues">issue</a>.</p>
-<hr>
-<div id="how-gt-fits-in-with-other-packages-that-generate-display-tables" class="section level4">
-<h4 class="hasAnchor">
-<a href="#how-gt-fits-in-with-other-packages-that-generate-display-tables" class="anchor"></a>How <strong>gt</strong> fits in with Other Packages that Generate Display Tables</h4>
-<p>The <strong>gt</strong> package joins a burgeoning collection of packages for display table generation. Why another? We feel that there is enough room in this space to innovate further. Here are some of the ways that <strong>gt</strong> contributes to this ecosystem:</p>
-<ul>
-<li>the interface is high-level and declarative (general instructions versus very specific)</li>
-<li>the formatting options are ‘batteries included’ (scientific notation, uncertainty, ranges, percentages, suffixes, localized currency, dates/times + much more)</li>
-<li>there is excellent, pain-free support for footnotes</li>
-<li>the output is ‘camera-ready’</li>
-<li>it will eventually support multiple output formats (including LaTeX) with the same declarative interface</li>
-<li>the API closely follows tidyverse conventions by adhering to the <a href="https://style.tidyverse.org">tidyverse style guide</a>
-</li>
-<li>a focus on making the package documentation and examples the best they can be</li>
-<li>rigorous QA/QC measures: high test coverage for automated tests, and thorough manual testing by QA engineers (with every proposed code change)</li>
-</ul>
-<p>While <strong>gt</strong> is trying to do something different with its own interface, it may not suit your specific needs. Here is a listing of leading table-making <strong>R</strong> packages, with links to their respective project pages:</p>
-<p><strong>knitr</strong> (<a href="https://github.com/yihui/knitr">GITHUB</a>, <a href="https://yihui.org/knitr/">WEBSITE</a>) — <strong>kableExtra</strong> (<a href="https://github.com/haozhu233/kableExtra">GITHUB</a>, <a href="https://haozhu233.github.io/kableExtra/">WEBSITE</a>) — <strong>formattable</strong> (<a href="https://github.com/renkun-ken/formattable">GITHUB</a>, <a href="https://renkun-ken.github.io/formattable/">WEBSITE</a>) — <strong>DT</strong> (<a href="https://github.com/rstudio/DT">GITHUB</a>, <a href="https://rstudio.github.io/DT/">WEBSITE</a>) — <strong>pander</strong> (<a href="https://github.com/Rapporter/pander">GITHUB</a>, <a href="http://rapporter.github.io/pander">WEBSITE</a>) — <strong>huxtable</strong> (<a href="https://github.com/hughjonesd/huxtable">GITHUB</a>, <a href="https://hughjonesd.github.io/huxtable/">WEBSITE</a>) — <strong>reactable</strong> (<a href="https://github.com/glin/reactable">GITHUB</a>, <a href="https://glin.github.io/reactable/">WEBSITE</a>) — <strong>flextable</strong> (<a href="https://github.com/davidgohel/flextable">GITHUB</a>, <a href="https://davidgohel.github.io/flextable/">WEBSITE</a>) — <strong>pixiedust</strong> (<a href="https://github.com/nutterb/pixiedust">GITHUB</a>) — <strong>tangram</strong> (<a href="https://github.com/spgarbet/tangram">GITHUB</a>) — <strong>ztable</strong> (<a href="https://github.com/cardiomoon/ztable">GITHUB</a>) — <strong>condformat</strong> (<a href="https://github.com/zeehio/condformat">GITHUB</a>) — <strong>stargazer</strong> (<a href="https://CRAN.R-project.org/package=stargazer">CRAN</a>) — <strong>xtable</strong> (<a href="https://CRAN.R-project.org/package=xtable">CRAN</a>)</p>
-</div>
-<div id="code-of-conduct" class="section level4">
-<h4 class="hasAnchor">
-<a href="#code-of-conduct" class="anchor"></a>Code of Conduct</h4>
-<p>Please note that this project is released with a <a href="https://contributor-covenant.org/version/1/0/0">Contributor Code of Conduct</a>.<br>By participating in this project you agree to abide by its terms.</p>
-</div>
-<div id="license" class="section level4">
-<h4 class="hasAnchor">
-<a href="#license" class="anchor"></a>License</h4>
-<p>MIT © RStudio, PBC</p>
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-<li>Download from CRAN at <br><a href="https://cloud.r-project.org/package=gt">https://​cloud.r-project.org/​package=gt</a>
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-<li>Report a bug at <br><a href="https://github.com/rstudio/gt/issues">https://​github.com/​rstudio/​gt/​issues</a>
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-<li>Richard Iannone <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/0000-0003-3925-190X" target="orcid.widget" aria-label="ORCID"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>Joe Cheng <br><small class="roles"> Author </small>  </li>
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-    <li class="dropdown-header">Case Studies</li>
-    <li>
-      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
-    </li>
-  </ul>
-</li>
-<li>
-  <a href="../news/index.html">News</a>
-</li>
-      </ul>
-      <ul class="nav navbar-nav navbar-right">
-        <li>
-  <a href="https://github.com/rstudio/gt">
-    <span class="fa fa-github fa-lg"></span>
-     
-  </a>
-</li>
-      </ul>
-      
-    </div><!--/.nav-collapse -->
-  </div><!--/.container -->
-</div><!--/.navbar -->
-
-      
-
-      </header>
-
-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Adjust the luminance for a palette of colors</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>adjust_luminance.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This function can brighten or darken a palette of colors by an arbitrary
-number of steps, which is defined by a real number between -2.0 and 2.0. The
-transformation of a palette by a fixed step in this function will tend to
-apply greater darkening or lightening for those colors in the midrange
-compared to any very dark or very light colors in the input palette.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>adjust_luminance</span>(<span class='no'>colors</span>, <span class='no'>steps</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>colors</th>
-      <td><p>A vector of colors that will undergo an adjustment in
-luminance. Each color value provided must either be a color name (in the
-set of colors provided by <code><a href='https://rdrr.io/r/grDevices/colors.html'>grDevices::colors()</a></code>) or a hexadecimal string in
-the form of "#RRGGBB" or "#RRGGBBAA".</p></td>
-    </tr>
-    <tr>
-      <th>steps</th>
-      <td><p>A positive or negative factor by which the luminance will be
-adjusted. Must be a number between <code>-2.0</code> and <code>2.0</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A vector of color values.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>This function can be useful when combined with the <code><a href='data_color.html'>data_color()</a></code> function's
-<code>palette</code> argument, which can use a vector of colors or any of the <code>col_*</code>
-functions from the <strong>scales</strong> package (all of which have a <code>palette</code>
-argument).</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_adjust_luminance_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-18</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get a palette of 8 pastel colors from</span>
-<span class='co'># the RColorBrewer package</span>
-<span class='no'>pal</span> <span class='kw'>&lt;-</span> <span class='kw pkg'>RColorBrewer</span><span class='kw ns'>::</span><span class='fu'><a href='https://rdrr.io/pkg/RColorBrewer/man/ColorBrewer.html'>brewer.pal</a></span>(<span class='fl'>8</span>, <span class='st'>"Pastel2"</span>)
-
-<span class='co'># Create lighter and darker variants</span>
-<span class='co'># of the base palette (one step lower, one</span>
-<span class='co'># step higher)</span>
-<span class='no'>pal_darker</span>  <span class='kw'>&lt;-</span> <span class='no'>pal</span> <span class='kw'>%&gt;%</span> <span class='fu'>adjust_luminance</span>(-<span class='fl'>1.0</span>)
-<span class='no'>pal_lighter</span> <span class='kw'>&lt;-</span> <span class='no'>pal</span> <span class='kw'>%&gt;%</span> <span class='fu'>adjust_luminance</span>(+<span class='fl'>1.0</span>)
-
-<span class='co'># Create a tibble and make a gt table</span>
-<span class='co'># from it; color each column in order of</span>
-<span class='co'># increasingly darker palettes (with</span>
-<span class='co'># `data_color()`)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(<span class='kw'>a</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>8</span>, <span class='kw'>b</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>8</span>, <span class='kw'>c</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='data_color.html'>data_color</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>a</span>),
-    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
-      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='no'>pal_lighter</span>,
-      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>8</span>)
-    )
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='data_color.html'>data_color</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>b</span>),
-    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
-      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='no'>pal</span>,
-      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>8</span>)
-    )
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='data_color.html'>data_color</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>c</span>),
-    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
-      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='no'>pal_darker</span>,
-      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>8</span>)
-    )
-  )</div></pre>
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-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/as.data.frame.gt_tbl.html b/docs/reference/as.data.frame.gt_tbl.html
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-    <h1>Transform a <strong>gt</strong> object to a data frame</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/as_data_frame.R'><code>R/as_data_frame.R</code></a></small>
-    <div class="hidden name"><code>as.data.frame.gt_tbl.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This facilitates conversion of the <code>gt_tbl</code> object to a data frame.</p>
-    </div>
-
-    <pre class="usage"><span class='co'># S3 method for gt_tbl</span>
-<span class='fu'><a href='https://rdrr.io/r/base/as.data.frame.html'>as.data.frame</a></span>(<span class='no'>x</span>, <span class='no'>...</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>An object of class <code>gt_tbl</code>.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>Any additional parameters.</p></td>
-    </tr>
-    </table>
-
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-<meta property="og:description" content="Get the LaTeX content from a gt_tbl object as a knit_asis object. This
-object contains the LaTeX code and attributes that serve as LaTeX
-dependencies (i.e., the LaTeX packages required for the table). Using
-as.character() on the created object will result in a single-element vector
-containing the LaTeX code." />
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-      <ul class="nav navbar-nav">
-        <li>
-  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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-</li>
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-    <div class="page-header">
-    <h1>Output a gt object as LaTeX</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
-    <div class="hidden name"><code>as_latex.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Get the LaTeX content from a <code>gt_tbl</code> object as a <code>knit_asis</code> object. This
-object contains the LaTeX code and attributes that serve as LaTeX
-dependencies (i.e., the LaTeX packages required for the table). Using
-<code><a href='https://rdrr.io/r/base/character.html'>as.character()</a></code> on the created object will result in a single-element vector
-containing the LaTeX code.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>as_latex</span>(<span class='no'>data</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>13-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Export Functions: 
-<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
-<code><a href='as_rtf.html'>as_rtf</a>()</code>,
-<code><a href='extract_summary.html'>extract_summary</a>()</code>,
-<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># add a header and then export as</span>
-<span class='co'># an object with LaTeX code</span>
-<span class='no'>tab_latex</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>as_latex</span>()
-
-<span class='co'># `tab_latex` is a `knit_asis` object,</span>
-<span class='co'># which makes it easy to include in</span>
-<span class='co'># R Markdown documents that are knit to</span>
-<span class='co'># PDF; we can use `as.character()` to</span>
-<span class='co'># get just the LaTeX code as a single-</span>
-<span class='co'># element vector</span>
-<span class='no'>tab_latex</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/base/character.html'>as.character</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/base/cat.html'>cat</a></span>()</div><div class='output co'>#&gt; \captionsetup[table]{labelformat=empty,skip=1pt}
-#&gt; \begin{longtable}{llr}
-#&gt; \caption*{
-#&gt; \large Data listing from \textbf{gtcars}\\ 
-#&gt; \small \texttt{gtcars} is an R dataset\\ 
-#&gt; } \\ 
-#&gt; \toprule
-#&gt; mfr &amp; model &amp; msrp \\ 
-#&gt; \midrule
-#&gt; Ford &amp; GT &amp; 447000 \\ 
-#&gt; Ferrari &amp; 458 Speciale &amp; 291744 \\ 
-#&gt; Ferrari &amp; 458 Spider &amp; 263553 \\ 
-#&gt; Ferrari &amp; 458 Italia &amp; 233509 \\ 
-#&gt; Ferrari &amp; 488 GTB &amp; 245400 \\ 
-#&gt; \bottomrule
-#&gt; \end{longtable}</div><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/as_raw_html.html b/docs/reference/as_raw_html.html
deleted file mode 100644
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--- a/docs/reference/as_raw_html.html
+++ /dev/null
@@ -1,243 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<title>Get the HTML content of a <strong>gt</strong> table — as_raw_html • gt</title>
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-<meta property="og:description" content="Get the HTML content from a gt_tbl object as a single-element character
-vector. By default, the generated HTML will have inlined styles, where CSS
-styles (that were previously contained in CSS rule sets external to the
-&amp;lt;table&amp;gt; element) are included as style attributes in the HTML table's
-tags. This option is preferable when using the output HTML table in an
-emailing context." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
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-<!-- mathjax -->
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
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-        <a class="navbar-link" href="../index.html">gt</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.0.5</span>
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-    <div id="navbar" class="navbar-collapse collapse">
-      <ul class="nav navbar-nav">
-        <li>
-  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
-</li>
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-  <a href="../reference/index.html">Reference</a>
-</li>
-<li class="dropdown">
-  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
-    Articles
-     
-    <span class="caret"></span>
-  </a>
-  <ul class="dropdown-menu" role="menu">
-    <li class="dropdown-header">How to Use</li>
-    <li>
-      <a href="../articles/gt-datasets.html">gt Datasets</a>
-    </li>
-    <li>
-      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
-    </li>
-    <li class="dropdown-header">Case Studies</li>
-    <li>
-      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
-    </li>
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-<li>
-  <a href="../news/index.html">News</a>
-</li>
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-</div><!--/.navbar -->
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-
-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Get the HTML content of a <strong>gt</strong> table</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
-    <div class="hidden name"><code>as_raw_html.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Get the HTML content from a <code>gt_tbl</code> object as a single-element character
-vector. By default, the generated HTML will have inlined styles, where CSS
-styles (that were previously contained in CSS rule sets external to the
-<code>&lt;table&gt; element</code>) are included as <code>style</code> attributes in the HTML table's
-tags. This option is preferable when using the output HTML table in an
-emailing context.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>as_raw_html</span>(<span class='no'>data</span>, <span class='kw'>inline_css</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>inline_css</th>
-      <td><p>An option to supply styles to table elements as inlined CSS
-styles. This is useful when including the table HTML as part of an HTML
-email message body, since inlined styles are largely supported in email
-clients over using CSS in a <code>&lt;style&gt;</code> block.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>13-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Export Functions: 
-<code><a href='as_latex.html'>as_latex</a>()</code>,
-<code><a href='as_rtf.html'>as_rtf</a>()</code>,
-<code><a href='extract_summary.html'>extract_summary</a>()</code>,
-<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># add a header and then export as</span>
-<span class='co'># HTML code with CSS inlined</span>
-<span class='no'>tab_html</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>as_raw_html</span>()
-
-<span class='co'># `tab_html` is a single-element vector</span>
-<span class='co'># containing inlined HTML for the table;</span>
-<span class='co'># it has only the `&lt;table&gt;...&lt;/table&gt;` part</span>
-<span class='co'># so it's not a complete HTML document but</span>
-<span class='co'># rather an HTML fragment</span>
-<span class='no'>tab_html</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='fl'>1</span>, <span class='fl'>700</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/base/cat.html'>cat</a></span>()</div><div class='output co'>#&gt; &lt;table style="font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif; display: table; border-collapse: collapse; margin-left: auto; margin-right: auto; color: #333333; font-size: 16px; background-color: #FFFFFF; width: auto; border-top-style: solid; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3;"&gt;
-#&gt;   &lt;thead style=""&gt;
-#&gt;     &lt;tr&gt;
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diff --git a/docs/reference/as_rtf.html b/docs/reference/as_rtf.html
deleted file mode 100644
index d420eeefc..000000000
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+++ /dev/null
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-<!DOCTYPE html>
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-<meta property="og:description" content="Get the RTF content from a gt_tbl object as as a single-element character
-vector. This object can be used with writeLines() to generate a valid .rtf
-file that can be opened by RTF readers." />
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-    <div class="page-header">
-    <h1>Output a <strong>gt</strong> object as RTF</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
-    <div class="hidden name"><code>as_rtf.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Get the RTF content from a <code>gt_tbl</code> object as as a single-element character
-vector. This object can be used with <code><a href='https://rdrr.io/r/base/writeLines.html'>writeLines()</a></code> to generate a valid .rtf
-file that can be opened by RTF readers.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>as_rtf</span>(<span class='no'>data</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>a table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>13-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Export Functions: 
-<code><a href='as_latex.html'>as_latex</a>()</code>,
-<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
-<code><a href='extract_summary.html'>extract_summary</a>()</code>,
-<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># add a header and then export as</span>
-<span class='co'># RTF code</span>
-<span class='no'>tab_rtf</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>2</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>as_rtf</span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/cell_borders.html b/docs/reference/cell_borders.html
deleted file mode 100644
index f09565aab..000000000
--- a/docs/reference/cell_borders.html
+++ /dev/null
@@ -1,300 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-
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-<meta property="og:description" content="The cell_borders() helper function is to be used with the tab_style()
-function, which itself allows for the setting of custom styles to one or more
-cells. Specifically, the call to cell_borders() should be bound to the
-styles argument of tab_style(). The selection argument is where we
-define which borders should be modified (e.g., &quot;left&quot;, &quot;right&quot;, etc.).
-With that selection, the color, style, and weight of the selected
-borders can then be modified." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <h1>Helper for defining custom borders for table cells</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cell_borders.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cell_borders()</code> helper function is to be used with the <code><a href='tab_style.html'>tab_style()</a></code>
-function, which itself allows for the setting of custom styles to one or more
-cells. Specifically, the call to <code>cell_borders()</code> should be bound to the
-<code>styles</code> argument of <code><a href='tab_style.html'>tab_style()</a></code>. The <code>selection</code> argument is where we
-define which borders should be modified (e.g., <code>"left"</code>, <code>"right"</code>, etc.).
-With that selection, the <code>color</code>, <code>style</code>, and <code>weight</code> of the selected
-borders can then be modified.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cell_borders</span>(<span class='kw'>sides</span> <span class='kw'>=</span> <span class='st'>"all"</span>, <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#000000"</span>, <span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"solid"</span>, <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>1</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>sides</th>
-      <td><p>The border sides to be modified. Options include <code>"left"</code>,
-<code>"right"</code>, <code>"top"</code>, and <code>"bottom"</code>. For all borders surrounding the
-selected cells, we can use the <code>"all"</code> option.</p></td>
-    </tr>
-    <tr>
-      <th>color, style, weight</th>
-      <td><p>The border color, style, and weight. The <code>color</code>
-can be defined with a color name or with a hexadecimal color code. The
-default <code>color</code> value is <code>"#000000"</code> (black). The <code>style</code> can be one of
-either <code>"solid"</code> (the default), <code>"dashed"</code>, or <code>"dotted"</code>. The <code>weight</code> of
-the border lines is to be given in pixel values (the <code><a href='px.html'>px()</a></code> helper function
-is useful for this. The default value for <code>weight</code> is <code>"1px"</code>. Borders for
-any defined <code>sides</code> can be removed by supplying <code>NULL</code> to any of <code>color</code>,
-<code>style</code>, or <code>weight</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object of class <code>cell_styles</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cell_borders_1.png' width=100% /></p>
-<p><img src='figures/man_cell_borders_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-17</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Add horizontal border lines for</span>
-<span class='co'># all table body rows in `exibble`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='tab_options.html'>tab_options</a></span>(<span class='kw'>row.striping.include_table_body</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>) <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-      <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_borders</span>(
-        <span class='kw'>sides</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"top"</span>, <span class='st'>"bottom"</span>),
-        <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#BBBBBB"</span>,
-        <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>1.5</span>),
-        <span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"solid"</span>
-      ),
-      <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-        <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>(),
-        <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>()
-      )
-    )
-
-<span class='co'># Incorporate different horizontal and</span>
-<span class='co'># vertical borders at several locations;</span>
-<span class='co'># this uses multiple `cell_borders()` and</span>
-<span class='co'># `cells_body()` calls within `list()`s</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-      <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-        <span class='fu'>cell_borders</span>(
-          <span class='kw'>sides</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"top"</span>, <span class='st'>"bottom"</span>),
-          <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#FF0000"</span>,
-          <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>2</span>)
-        ),
-        <span class='fu'>cell_borders</span>(
-          <span class='kw'>sides</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"left"</span>, <span class='st'>"right"</span>),
-          <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#0000FF"</span>,
-          <span class='kw'>weight</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>2</span>)
-        )
-      ),
-      <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-        <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-          <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-          <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>num</span>)
-        ),
-        <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-          <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-          <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>currency</span>)
-        )
-      )
-    )</div></pre>
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diff --git a/docs/reference/cell_fill.html b/docs/reference/cell_fill.html
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-<meta property="og:title" content="Helper for defining custom fills for table cells — cell_fill" />
-<meta property="og:description" content="The cell_fill() helper function is to be used with the tab_style()
-function, which itself allows for the setting of custom styles to one or more
-cells. Specifically, the call to cell_fill() should be bound to the
-styles argument of tab_style()." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <h1>Helper for defining custom fills for table cells</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cell_fill.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cell_fill()</code> helper function is to be used with the <code><a href='tab_style.html'>tab_style()</a></code>
-function, which itself allows for the setting of custom styles to one or more
-cells. Specifically, the call to <code>cell_fill()</code> should be bound to the
-<code>styles</code> argument of <code><a href='tab_style.html'>tab_style()</a></code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cell_fill</span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#D3D3D3"</span>, <span class='kw'>alpha</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>color</th>
-      <td><p>The fill color. If nothing is provided, then <code>"#D3D3D3"</code> (light
-gray) will be used as a default.</p></td>
-    </tr>
-    <tr>
-      <th>alpha</th>
-      <td><p>An optional alpha transparency value for the <code>color</code> as single
-value in the range of <code>0</code> (fully transparent) to <code>1</code> (fully opaque). If not
-provided the fill color will either be fully opaque or use alpha
-information from the color value if it is supplied in the #RRGGBBAA format.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object of class <code>cell_styles</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cell_fill_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-16</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># add styles with `tab_style()` and</span>
-<span class='co'># the `cell_fill()` helper function</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_fill</span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;=</span> <span class='fl'>5000</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_fill</span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"gray85"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&lt;</span> <span class='fl'>100</span>
-    )
-  )</div></pre>
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-<meta property="og:description" content="This helper function is to be used with the tab_style() function, which
-itself allows for the setting of custom styles to one or more cells. We can
-also define several styles within a single call of cell_text() and
-tab_style() will reliably apply those styles to the targeted element." />
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-    <h1>Helper for defining custom text styles for table cells</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cell_text.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This helper function is to be used with the <code><a href='tab_style.html'>tab_style()</a></code> function, which
-itself allows for the setting of custom styles to one or more cells. We can
-also define several styles within a single call of <code>cell_text()</code> and
-<code><a href='tab_style.html'>tab_style()</a></code> will reliably apply those styles to the targeted element.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cell_text</span>(
-  <span class='kw'>color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>font</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>v_align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stretch</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>indent</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>decorate</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>color</th>
-      <td><p>The text color.</p></td>
-    </tr>
-    <tr>
-      <th>font</th>
-      <td><p>The font or collection of fonts (subsequent font names are) used
-as fallbacks.</p></td>
-    </tr>
-    <tr>
-      <th>size</th>
-      <td><p>The size of the font. Can be provided as a number that is assumed
-to represent <code>px</code> values (or could be wrapped in the <code><a href='px.html'>px()</a></code>) helper
-function. We can also use one of the following absolute size keywords:
-<code>"xx-small"</code>, <code>"x-small"</code>, <code>"small"</code>, <code>"medium"</code>, <code>"large"</code>, <code>"x-large"</code>,
-or <code>"xx-large"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>align</th>
-      <td><p>The text alignment. Can be one of either <code>"center"</code>, <code>"left"</code>,
-<code>"right"</code>, or <code>"justify"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>v_align</th>
-      <td><p>The vertical alignment of the text in the cell. Options are
-<code>"middle"</code>, <code>"top"</code>, or <code>"bottom"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>style</th>
-      <td><p>The text style. Can be one of either <code>"center"</code>, <code>"normal"</code>,
-<code>"italic"</code>, or <code>"oblique"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>weight</th>
-      <td><p>The weight of the font. Can be a text-based keyword such as
-<code>"normal"</code>, <code>"bold"</code>, <code>"lighter"</code>, <code>"bolder"</code>, or, a numeric value between
-<code>1</code> and <code>1000</code>, inclusive. Note that only variable fonts may support the
-numeric mapping of weight.</p></td>
-    </tr>
-    <tr>
-      <th>stretch</th>
-      <td><p>Allows for text to either be condensed or expanded. We can use
-one of the following text-based keywords to describe the degree of
-condensation/expansion: <code>"ultra-condensed"</code>, <code>"extra-condensed"</code>,
-<code>"condensed"</code>, <code>"semi-condensed"</code>, <code>"normal"</code>, <code>"semi-expanded"</code>,
-<code>"expanded"</code>, <code>"extra-expanded"</code>, or <code>"ultra-expanded"</code>. Alternatively, we
-can supply percentage values from <code>0\%</code> to <code>200\%</code>, inclusive. Negative
-percentage values are not allowed.</p></td>
-    </tr>
-    <tr>
-      <th>indent</th>
-      <td><p>The indentation of the text. Can be provided as a number that
-is assumed to represent <code>px</code> values (or could be wrapped in the <code><a href='px.html'>px()</a></code>)
-helper function. Alternatively, this can be given as a percentage (easily
-constructed with <code><a href='pct.html'>pct()</a></code>).</p></td>
-    </tr>
-    <tr>
-      <th>decorate</th>
-      <td><p>allows for text decoration effect to be applied. Here, we can
-use <code>"overline"</code>, <code>"line-through"</code>, or <code>"underline"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>transform</th>
-      <td><p>Allows for the transformation of text. Options are
-<code>"uppercase"</code>, <code>"lowercase"</code>, or <code>"capitalize"</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object of class <code>cell_styles</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cell_text_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-15</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># add styles with `tab_style()` and</span>
-<span class='co'># the `cell_text()` helper function</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_text</span>(<span class='kw'>weight</span> <span class='kw'>=</span> <span class='st'>"bold"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;=</span> <span class='fl'>5000</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'>cell_text</span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&lt;</span> <span class='fl'>100</span>
-    )
-  )</div></pre>
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-<meta property="og:description" content="The cells_body() function is used to target the data cells in the table
-body. The function can be used to apply a footnote with tab_footnote(), to
-add custom styling with tab_style(), or the transform the targeted cells
-with text_transform(). The function is expressly used in each of those
-functions' locations argument." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <div class="page-header">
-    <h1>Location helper for targeting data cells in the table body</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_body.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_body()</code> function is used to target the data cells in the table
-body. The function can be used to apply a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code>, to
-add custom styling with <code><a href='tab_style.html'>tab_style()</a></code>, or the transform the targeted cells
-with <code><a href='text_transform.html'>text_transform()</a></code>. The function is expressly used in each of those
-functions' <code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_body</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>columns</th>
-      <td><p>The names of the columns that are to be targeted.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>The names of the rows that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_body</code> and <code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code>cells_body()</code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_body_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-11</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table; add</span>
-<span class='co'># a footnote that targets a single data cell</span>
-<span class='co'># with `tab_footnote()`, using `cells_body()`</span>
-<span class='co'># in `locations` (`rows = hp == max(hp)` will</span>
-<span class='co'># target a single row in the `hp` column)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>ctry_origin</span> <span class='kw'>==</span> <span class='st'>"United Kingdom"</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Highest horsepower."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_body</span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>hp</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>hp</span> <span class='kw'>==</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>hp</span>))
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='opt_footnote_marks.html'>opt_footnote_marks</a></span>(<span class='kw'>marks</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"*"</span>, <span class='st'>"+"</span>))</div></pre>
-  </div>
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diff --git a/docs/reference/cells_column_labels.html b/docs/reference/cells_column_labels.html
deleted file mode 100644
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-<meta property="og:description" content="The cells_column_labels() function is used to target the table's column
-labels when applying a footnote with tab_footnote() or adding custom style
-with tab_style(). The function is expressly used in each of those
-functions' locations argument." />
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-    <h1>Location helper for targeting the column labels</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_column_labels.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_column_labels()</code> function is used to target the table's column
-labels when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style
-with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those
-functions' <code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_column_labels</span>(<span class='no'>columns</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>columns</th>
-      <td><p>The names of the column labels that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_column_labels</code> and
-<code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code>cells_column_labels()</code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_column_labels_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-8</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sza` to create a gt table; add a</span>
-<span class='co'># header and then add footnotes to the</span>
-<span class='co'># column labels with `tab_footnote()` and</span>
-<span class='co'># `cells_column_labels()` in `locations`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>20</span> <span class='kw'>&amp;</span> <span class='no'>month</span> <span class='kw'>==</span> <span class='st'>"jan"</span> <span class='kw'>&amp;</span>
-      !<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>sza</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>, -<span class='no'>month</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"True solar time."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_column_labels</span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>tst</span>)
-    )
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Solar zenith angle."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_column_labels</span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sza</span>)
-    )
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
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-</div>
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diff --git a/docs/reference/cells_column_spanners.html b/docs/reference/cells_column_spanners.html
deleted file mode 100644
index 2fe98e951..000000000
--- a/docs/reference/cells_column_spanners.html
+++ /dev/null
@@ -1,275 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-
-<title>Location helper for targeting the column spanners — cells_column_spanners • gt</title>
-
-<!-- favicons -->
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-<meta property="og:description" content="The cells_column_spanners() function is used to target the cells that
-contain the table column spanners. This is useful when applying a footnote
-with tab_footnote() or adding custom style with tab_style(). The function
-is expressly used in each of those functions' locations argument." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <div class="page-header">
-    <h1>Location helper for targeting the column spanners</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_column_spanners.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_column_spanners()</code> function is used to target the cells that
-contain the table column spanners. This is useful when applying a footnote
-with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with <code><a href='tab_style.html'>tab_style()</a></code>. The function
-is expressly used in each of those functions' <code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_column_spanners</span>(<span class='no'>spanners</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>spanners</th>
-      <td><p>The names of the spanners that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_column_spanners</code> and
-<code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code>cells_column_spanners()</code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_column_spanners_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-7</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table; add a</span>
-<span class='co'># spanner column label over three column</span>
-<span class='co'># labels and then use `tab_style()` to make</span>
-<span class='co'># the spanner label text bold</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>fctr</span>, -<span class='no'>currency</span>, -<span class='no'>group</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_spanner.html'>tab_spanner</a></span>(
-    <span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"dates and times"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>, <span class='no'>time</span>, <span class='no'>datetime</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>weight</span> <span class='kw'>=</span> <span class='st'>"bold"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_column_spanners</span>(<span class='kw'>spanners</span> <span class='kw'>=</span> <span class='st'>"dates and times"</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
-</div>
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-</html>
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diff --git a/docs/reference/cells_data.html b/docs/reference/cells_data.html
deleted file mode 100644
index 2ef2e97e0..000000000
--- a/docs/reference/cells_data.html
+++ /dev/null
@@ -1,191 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-
-<title>Location helper for targeting data cells in the table body (deprecated) — cells_data • gt</title>
-
-<!-- favicons -->
-<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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-<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png" />
-<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png" />
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_data.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Location helper for targeting data cells in the table body (deprecated)</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_data</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>columns</th>
-      <td><p>The names of the columns that are to be targeted.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>The names of the rows that are to be targeted.</p></td>
-    </tr>
-    </table>
-
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-<meta property="og:description" content="The cells_grand_summary() function is used to target the cells in a grand
-summary and it is useful when applying a footnote with tab_footnote() or
-adding custom styles with tab_style(). The function is expressly used in
-each of those functions' locations argument." />
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-    <h1>Location helper for targeting cells in a grand summary</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_grand_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_grand_summary()</code> function is used to target the cells in a grand
-summary and it is useful when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or
-adding custom styles with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in
-each of those functions' <code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_grand_summary</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>columns</th>
-      <td><p>The names of the columns that are to be targeted.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>The names of the rows that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_summary</code> and <code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code>cells_grand_summary()</code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_grand_summary_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-13</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table; add</span>
-<span class='co'># some styling to a grand summary cell with</span>
-<span class='co'># with `tab_style()` and `cells_grand_summary()`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Spain"</span>,
-    <span class='no'>year</span> <span class='kw'>&lt;</span> <span class='fl'>1970</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"country"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"year"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>change</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>) - <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>)
-    ),
-    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>)
-    ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_grand_summary</span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cells_group.html b/docs/reference/cells_group.html
deleted file mode 100644
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_group.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Location helper for targeting row groups (deprecated)</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_group</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>groups</th>
-      <td><p>The names of the row groups that are to be targeted.</p></td>
-    </tr>
-    </table>
-
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diff --git a/docs/reference/cells_row_groups.html b/docs/reference/cells_row_groups.html
deleted file mode 100644
index 57dfd7e36..000000000
--- a/docs/reference/cells_row_groups.html
+++ /dev/null
@@ -1,287 +0,0 @@
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-<meta property="og:description" content="The cells_row_groups() function is used to target the table's row groups
-when applying a footnote with tab_footnote() or adding custom style with
-tab_style(). The function is expressly used in each of those functions'
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-    <h1>Location helper for targeting row groups</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_row_groups.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_row_groups()</code> function is used to target the table's row groups
-when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with
-<code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those functions'
-<code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_row_groups</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>groups</th>
-      <td><p>The names of the row groups that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_row_groups</code> and
-<code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code>cells_row_groups()</code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_row_groups_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-9</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `pizzaplace` to create a gt table</span>
-<span class='co'># with grouped data; add a summary with the</span>
-<span class='co'># `summary_rows()` function and then add a</span>
-<span class='co'># footnote to the "peppr_salami" row group</span>
-<span class='co'># label with `tab_footnote()` and with</span>
-<span class='co'># `cells_row_groups()` in `locations`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>name</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"soppressata"</span>, <span class='st'>"peppr_salami"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>name</span>, <span class='no'>size</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(
-    <span class='kw'>`Pizzas Sold`</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>()
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"size"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='st'>"Pizzas Sold"</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>TOTAL</span> <span class='kw'>=</span> <span class='st'>"sum"</span>),
-    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>,
-    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"The Pepper-Salami."</span>,
-    <span class='fu'>cells_row_groups</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"peppr_salami"</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-<meta property="og:description" content="The cells_stub() function is used to target the table's stub cells and it
-is useful when applying a footnote with tab_footnote() or adding a custom
-style with tab_style(). The function is expressly used in each of those
-functions' locations argument." />
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-    <h1>Location helper for targeting cells in the table stub</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_stub.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_stub()</code> function is used to target the table's stub cells and it
-is useful when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding a custom
-style with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those
-functions' <code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_stub</span>(<span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>rows</th>
-      <td><p>The names of the rows that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_stub</code> and <code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code>cells_stub()</code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_stub_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-10</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>tidyr</span>)
-
-<span class='co'># Use `sza` to create a gt table; color</span>
-<span class='co'># all of the `month` values in the table</span>
-<span class='co'># stub with `tab_style()`, using `cells_stub()`</span>
-<span class='co'># in `locations` (`rows = TRUE` targets</span>
-<span class='co'># all stub rows)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>20</span> <span class='kw'>&amp;</span> <span class='no'>tst</span> <span class='kw'>&lt;=</span> <span class='st'>"1000"</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(!<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>sza</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>tidyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://tidyr.tidyverse.org/reference/spread.html'>spread</a></span>(<span class='kw'>key</span> <span class='kw'>=</span> <span class='st'>"tst"</span>, <span class='kw'>value</span> <span class='kw'>=</span> <span class='no'>sza</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"month"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_missing.html'>fmt_missing</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>""</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"darkblue"</span>),
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"white"</span>)
-      ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_stub</span>(<span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-  )</div></pre>
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-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cells_stubhead.html b/docs/reference/cells_stubhead.html
deleted file mode 100644
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-tab_style(). The function is expressly used in each of those functions'
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-    <h1>Location helper for targeting the table stubhead cell</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_stubhead.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_stubhead()</code> function is used to target the table stubhead location
-when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with
-<code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those functions'
-<code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_stubhead</span>()</pre>
-
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_stubhead</code> and <code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code>cells_stubhead()</code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_stubhead_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-6</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `pizzaplace` to create a gt table;</span>
-<span class='co'># add a stubhead label and then style it</span>
-<span class='co'># with `tab_style()` and `cells_stubhead()`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>month</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='no'>date</span>, <span class='fl'>6</span>, <span class='fl'>7</span>))) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>month</span>, <span class='no'>type</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(<span class='kw'>sold</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>()) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>ungroup</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>month</span> <span class='kw'>%in%</span> <span class='fl'>1</span>:<span class='fl'>2</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"type"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_stubhead.html'>tab_stubhead</a></span>(<span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"type"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_stubhead</span>()
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cells_summary.html b/docs/reference/cells_summary.html
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-custom style with tab_style(). The function is expressly used in each of
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-        <li>
-  <a href="https://github.com/rstudio/gt">
-    <span class="fa fa-github fa-lg"></span>
-     
-  </a>
-</li>
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-      
-    </div><!--/.nav-collapse -->
-  </div><!--/.container -->
-</div><!--/.navbar -->
-
-      
-
-      </header>
-
-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Location helper for targeting group summary cells</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_summary()</code> function is used to target the cells in a group summary
-and it is useful when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding a
-custom style with <code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of
-those functions' <code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_summary</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>groups</th>
-      <td><p>The names of the groups that the summary rows reside in.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The names of the columns that are to be targeted.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>The names of the rows that are to be targeted.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object with the classes <code>cells_summary</code> and <code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code><a href='cells_title.html'>cells_title()</a></code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code>cells_summary()</code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_summary_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-12</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table; add</span>
-<span class='co'># some styling to the summary data cells with</span>
-<span class='co'># with `tab_style()`, using `cells_summary()`</span>
-<span class='co'># in `locations`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Japan"</span>,
-    <span class='no'>year</span> <span class='kw'>&lt;</span> <span class='fl'>1970</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"country"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
-    <span class='kw'>decade</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='no'>year</span>, <span class='fl'>1</span>, <span class='fl'>3</span>), <span class='st'>"0s"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>decade</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(
-    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"year"</span>,
-    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"decade"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"1960s"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='st'>"min"</span>, <span class='st'>"max"</span>),
-    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>0</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightblue"</span>)
-      ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_summary</span>(
-      <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"1960s"</span>,
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>),
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightgreen"</span>)
-      ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_summary</span>(
-      <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"1960s"</span>,
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>2</span>)
-  )</div></pre>
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-<meta property="og:description" content="The cells_title() function is used to target the table title or subtitle
-when applying a footnote with tab_footnote() or adding custom style with
-tab_style(). The function is expressly used in each of those functions'
-locations argument." />
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-    <h1>Location helper for targeting the table title and subtitle</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>cells_title.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cells_title()</code> function is used to target the table title or subtitle
-when applying a footnote with <code><a href='tab_footnote.html'>tab_footnote()</a></code> or adding custom style with
-<code><a href='tab_style.html'>tab_style()</a></code>. The function is expressly used in each of those functions'
-<code>locations</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cells_title</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"title"</span>, <span class='st'>"subtitle"</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>groups</th>
-      <td><p>We can either specify <code>"title"</code> or <code>"subtitle"</code> to target the
-title element or the subtitle element.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object of classes <code>cells_title</code> and <code>location_cells</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When using any of the location helper functions with an appropriate function
-that has a <code>locations</code> argument, multiple locations can be targeted by
-enclosing several <code>cells_*()</code> helper functions in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. The following
-helper functions can be used to target cells (roughly in order from the top
-to the bottom of a table):</p><ul>
-<li><p><code>cells_title()</code>: targets the table title or the table subtitle
-depending on the value given to the <code>groups</code> argument (<code>"title"</code> or
-<code>"subtitle"</code>).</p></li>
-<li><p><code><a href='cells_stubhead.html'>cells_stubhead()</a></code>: targets the stubhead location, a cell of which is
-only available when there is a stub; a label in that location can be created
-by using the <code><a href='tab_stubhead.html'>tab_stubhead()</a></code> function.</p></li>
-<li><p><code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>: targets the spanner column labels, which
-appear above the column labels.</p></li>
-<li><p><code><a href='cells_column_labels.html'>cells_column_labels()</a></code>: targets the column labels.</p></li>
-<li><p><code><a href='cells_row_groups.html'>cells_row_groups()</a></code>: targets the row group labels in any available row
-groups using the <code>groups</code> argument.</p></li>
-<li><p><code><a href='cells_stub.html'>cells_stub()</a></code>: targets row labels in the table stub using the <code>rows</code>
-argument.</p></li>
-<li><p><code><a href='cells_body.html'>cells_body()</a></code>: targets data cells in the table body using
-intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_summary.html'>cells_summary()</a></code>: targets summary cells in the table body using the
-<code>groups</code> argument and intersections of <code>columns</code> and <code>rows</code>.</p></li>
-<li><p><code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>: targets cells of the table's grand summary
-using intersections of <code>columns</code> and <code>rows</code></p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cells_title_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table; add</span>
-<span class='co'># a header with a title, and then add a</span>
-<span class='co'># footnote to the title with `tab_footnote()`</span>
-<span class='co'># and `cells_title()` (in `locations`)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
-      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-10"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
-    -<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='no'>adj_close</span>, <span class='no'>volume</span>, <span class='no'>high</span>, <span class='no'>low</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(<span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"S&amp;P 500"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"All values in USD."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'>cells_title</span>(<span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"title"</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
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diff --git a/docs/reference/cols_align.html b/docs/reference/cols_align.html
deleted file mode 100644
index f85ee09dd..000000000
--- a/docs/reference/cols_align.html
+++ /dev/null
@@ -1,255 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-
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-
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-<meta property="og:description" content="The individual alignments of columns (which includes the column labels and
-all of their data cells) can be modified. We have the option to align text to
-the left, the center, and the right. In a less explicit manner, we can
-allow gt to automatically choose the alignment of each column based on
-the data type (with the auto option)." />
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Set the alignment of columns</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_align.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The individual alignments of columns (which includes the column labels and
-all of their data cells) can be modified. We have the option to align text to
-the <code>left</code>, the <code>center</code>, and the <code>right</code>. In a less explicit manner, we can
-allow <strong>gt</strong> to automatically choose the alignment of each column based on
-the data type (with the <code>auto</code> option).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_align</span>(<span class='no'>data</span>, <span class='kw'>align</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"auto"</span>, <span class='st'>"left"</span>, <span class='st'>"center"</span>, <span class='st'>"right"</span>), <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>align</th>
-      <td><p>The alignment type. This can be any of <code>"center"</code>, <code>"left"</code>, or
-<code>"right"</code> for center-, left-, or center-alignment. Alternatively, the
-<code>"auto"</code> option (the default), will automatically align values in columns
-according to the data type (see the Details section for specifics on which
-alignments are applied).</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>An optional vector of column names for which the alignment
-should be applied. If nothing is supplied, or if <code>columns</code> is <code>TRUE</code>, then
-the chosen alignment affects all columns.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>When you create a <strong>gt</strong> table object using <code><a href='gt.html'>gt()</a></code>, automatic alignment of
-column labels and their data cells is performed. By default, left-alignment
-is applied to columns of class <code>character</code>, <code>Date</code>, or <code>POSIXct</code>;
-center-alignment is for columns of class <code>logical</code>, <code>factor</code>, or <code>list</code>; and
-right-alignment is used for the <code>numeric</code> and <code>integer</code> columns.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_align_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># align the `population` column data to</span>
-<span class='co'># the left</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_align</span>(
-    <span class='kw'>align</span> <span class='kw'>=</span> <span class='st'>"left"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/cols_hide.html b/docs/reference/cols_hide.html
deleted file mode 100644
index 12dade009..000000000
--- a/docs/reference/cols_hide.html
+++ /dev/null
@@ -1,270 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<meta property="og:description" content="The cols_hide() function allows us to hide one or more columns from
-appearing in the final output table. While it's possible and often desirable
-to omit columns from the input table data before introduction to the gt()
-function, there can be cases where the data in certain columns is useful (as
-a column reference during formatting of other columns) but the final display
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Hide one or more columns</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_hide.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cols_hide()</code> function allows us to hide one or more columns from
-appearing in the final output table. While it's possible and often desirable
-to omit columns from the input table data before introduction to the <code><a href='gt.html'>gt()</a></code>
-function, there can be cases where the data in certain columns is useful (as
-a column reference during formatting of other columns) but the final display
-of those columns is not necessary.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_hide</span>(<span class='no'>data</span>, <span class='no'>columns</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The column names to hide from the output display table. The
-order of the remaining columns will be preserved. Values provided that do
-not correspond to column names will be disregarded.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The hiding of columns is internally a rendering directive, so, all columns
-that are 'hidden' are still accessible and useful in any expression provided
-to a <code>rows</code> argument. Furthermore, the <code>cols_hide()</code> function (as with many
-<strong>gt</strong> functions) can be placed anywhere in a pipeline of <strong>gt</strong> function
-calls (acting as a promise to hide columns when the timing is right). However
-there's perhaps greater readability when placing this call closer to the end
-of such a pipeline.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_hide_1.png' width=100% /></p>
-<p><img src='figures/man_cols_hide_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-7</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># Hide the columns `country_code_2` and</span>
-<span class='co'># `country_code_3`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_hide</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(
-      <span class='no'>country_code_2</span>, <span class='no'>country_code_3</span>)
-  )
-
-<span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># Use the `population` column to provide</span>
-<span class='co'># the conditional placement of footnotes,</span>
-<span class='co'># then hide that column and one other</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_hide</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>country_code_3</span>, <span class='no'>population</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Population above 3,000,000."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>population</span> <span class='kw'>&gt;</span> <span class='fl'>3000000</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cols_label.html b/docs/reference/cols_label.html
deleted file mode 100644
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+++ /dev/null
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-<meta property="og:description" content="Column labels can be modified from their default values (the names of the
-columns from the input table data). When you create a gt table object
-using gt(), column names effectively become the column labels. While this
-serves as a good first approximation, column names aren't often appealing as
-column labels in a gt output table. The cols_label() function
-provides the flexibility to relabel one or more columns and we even have the
-option to use the md() or html() helper functions for rendering column
-labels from Markdown or using HTML." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <div class="page-header">
-    <h1>Relabel one or more columns</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_label.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Column labels can be modified from their default values (the names of the
-columns from the input table data). When you create a <strong>gt</strong> table object
-using <code><a href='gt.html'>gt()</a></code>, column names effectively become the column labels. While this
-serves as a good first approximation, column names aren't often appealing as
-column labels in a <strong>gt</strong> output table. The <code>cols_label()</code> function
-provides the flexibility to relabel one or more columns and we even have the
-option to use the <code><a href='md.html'>md()</a></code> or <code><a href='html.html'>html()</a></code> helper functions for rendering column
-labels from Markdown or using HTML.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_label</span>(<span class='no'>data</span>, <span class='no'>...</span>, <span class='kw'>.list</span> <span class='kw'>=</span> <span class='fu'>list2</span>(<span class='no'>...</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>One or more named arguments of column names from the input <code>data</code>
-table along with their labels for display as the column labels. We can
-optionally wrap the column labels with <code><a href='md.html'>md()</a></code> (to interpret text as
-Markdown) or <code><a href='html.html'>html()</a></code> (to interpret text as HTML).</p></td>
-    </tr>
-    <tr>
-      <th>.list</th>
-      <td><p>Allows for the use of a list as an input alternative to <code>...</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>It's important to note that while columns can be freely relabeled, we
-continue to refer to columns by their original column names. Column names in
-a tibble or data frame must be unique whereas column labels in <strong>gt</strong> have
-no requirement for uniqueness (which is useful for labeling columns as, say,
-measurement units that may be repeated several times---usually under
-different spanner column labels). Thus, we can still easily distinguish
-between columns in other <strong>gt</strong> function calls (e.g., in all of the
-<code>fmt*()</code> functions) even though we may lose distinguishability in column
-labels once they have been relabeled.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_label_1.png' width=100% /></p>
-<p><img src='figures/man_cols_label_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># label all the table's columns to</span>
-<span class='co'># present better</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_label</span>(
-    <span class='kw'>country_name</span> <span class='kw'>=</span> <span class='st'>"Name"</span>,
-    <span class='kw'>year</span> <span class='kw'>=</span> <span class='st'>"Year"</span>,
-    <span class='kw'>population</span> <span class='kw'>=</span> <span class='st'>"Population"</span>
-  )
-
-<span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># label columns as before but make them</span>
-<span class='co'># bold with markdown formatting</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_label</span>(
-    <span class='kw'>country_name</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"**Name**"</span>),
-    <span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"**Year**"</span>),
-    <span class='kw'>population</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"**Population**"</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cols_merge.html b/docs/reference/cols_merge.html
deleted file mode 100644
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-<meta property="og:description" content="This function takes input from two or more columns and allows the contents to
-be merged them into a single column, using a pattern that specifies the
-formatting. We can specify which columns to merge together in the columns
-argument. The string-combining pattern is given in the pattern argument.
-The first column in the columns series operates as the target column (i.e.,
-will undergo mutation) whereas all following columns will be untouched.
-There is the option to hide the non-target columns (i.e., second and
-subsequent columns given in columns)." />
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-    <h1>Merge data from two or more columns to a single column</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_merge.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This function takes input from two or more columns and allows the contents to
-be merged them into a single column, using a pattern that specifies the
-formatting. We can specify which columns to merge together in the <code>columns</code>
-argument. The string-combining pattern is given in the <code>pattern</code> argument.
-The first column in the <code>columns</code> series operates as the target column (i.e.,
-will undergo mutation) whereas all following <code>columns</code> will be untouched.
-There is the option to hide the non-target columns (i.e., second and
-subsequent columns given in <code>columns</code>).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_merge</span>(
-  <span class='no'>data</span>,
-  <span class='no'>columns</span>,
-  <span class='kw'>hide_columns</span> <span class='kw'>=</span> <span class='no'>columns</span>[-<span class='fl'>1</span>],
-  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='st'>"{"</span>, <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq_along</a></span>(<span class='no'>columns</span>), <span class='st'>"}"</span>, <span class='kw'>collapse</span> <span class='kw'>=</span> <span class='st'>" "</span>)
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns that will participate in the merging process. The
-first column name provided will be the target column (i.e., undergo
-mutation) and the other columns will serve to provide input.</p></td>
-    </tr>
-    <tr>
-      <th>hide_columns</th>
-      <td><p>Any column names provided here will have their state
-changed to <code>hidden</code> (via internal use of <code><a href='cols_hide.html'>cols_hide()</a></code> if they aren't
-already hidden. This is convenient if the shared purpose of these specified
-columns is only to provide string input to the target column.</p></td>
-    </tr>
-    <tr>
-      <th>pattern</th>
-      <td><p>A formatting pattern that specifies the arrangement of the
-<code>column</code> values and any string literals. We need to use column numbers
-(corresponding to the position of columns provided in <code>columns</code>) within the
-pattern. These indices are to be placed in curly braces (e.g., <code>{1}</code>). All
-characters outside of braces are taken to be string literals.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>There are two other column-merging functions that offer specialized behavior
-that is optimized for common table tasks: <code><a href='cols_merge_range.html'>cols_merge_range()</a></code> and
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert()</a></code>. These functions operate similarly, where the
-non-target columns can be optionally hidden from the output table through the
-<code>autohide</code> option.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_merge_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-10</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table;</span>
-<span class='co'># merge the `open` &amp; `close` columns</span>
-<span class='co'># together, and, the `low` &amp; `high`</span>
-<span class='co'># columns (putting an em dash between</span>
-<span class='co'># both); rename the columns</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>50</span>:<span class='fl'>55</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>volume</span>, -<span class='no'>adj_close</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_merge</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>close</span>),
-    <span class='kw'>hide_columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>close</span>),
-    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{1}&amp;mdash;{2}"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_merge</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>low</span>, <span class='no'>high</span>),
-    <span class='kw'>hide_columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>high</span>),
-    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{1}&amp;mdash;{2}"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(
-    <span class='kw'>open</span> <span class='kw'>=</span> <span class='st'>"open/close"</span>,
-    <span class='kw'>low</span> <span class='kw'>=</span> <span class='st'>"low/high"</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
-
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-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
-</div>
-
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-   </div>
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diff --git a/docs/reference/cols_merge_range.html b/docs/reference/cols_merge_range.html
deleted file mode 100644
index 3ce796ac9..000000000
--- a/docs/reference/cols_merge_range.html
+++ /dev/null
@@ -1,286 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-
-<title>Merge two columns to a value range column — cols_merge_range • gt</title>
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-a range of values (col_begin and col_end) and merges them into a single
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-    <h1>Merge two columns to a value range column</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_merge_range.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>cols_merge_range()</code> function is a specialized variant of the
-<code><a href='cols_merge.html'>cols_merge()</a></code> function. It operates by taking a two columns that constitute
-a range of values (<code>col_begin</code> and <code>col_end</code>) and merges them into a single
-column. What results is a column containing both values separated by a long
-dash (e.g., <code>12.0 — 20.0</code>). The column specified in <code>col_end</code> is dropped from
-the output table.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_merge_range</span>(<span class='no'>data</span>, <span class='no'>col_begin</span>, <span class='no'>col_end</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>"--"</span>, <span class='kw'>autohide</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>col_begin</th>
-      <td><p>A column that contains values for the start of the range.</p></td>
-    </tr>
-    <tr>
-      <th>col_end</th>
-      <td><p>A column that contains values for the end of the range.</p></td>
-    </tr>
-    <tr>
-      <th>sep</th>
-      <td><p>The separator text that indicates the values are ranged. The
-default value of <code>"--"</code> indicates that an en dash will be used for the
-range separator. Using <code>"---"</code> will be taken to mean that an em dash should
-be used. Should you want these special symbols to be taken literally, they
-can be supplied within the base <code><a href='https://rdrr.io/r/base/AsIs.html'>I()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>autohide</th>
-      <td><p>An option to automatically hide the column specified as
-<code>col_end</code>. Any columns with their state changed to hidden will behave
-the same as before, they just won't be displayed in the finalized table.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>This function could be somewhat replicated using <code><a href='cols_merge.html'>cols_merge()</a></code>, however,
-<code>cols_merge_range()</code> employs the following specialized operations for <code>NA</code>
-handling:</p>
-<ol>
-<li><p><code>NA</code>s in <code>col_begin</code> (but not <code>col_end</code>) result in a display of only</p></li>
-<li><p><code>NA</code>s in <code>col_end</code> (but not <code>col_begin</code>) result in a display of only
-the <code>col_begin</code> values only for the merged column (this is the converse of
-the previous)</p></li>
-<li><p><code>NA</code>s both in <code>col_begin</code> and <code>col_end</code> result in missing values for
-the merged column</p></li>
-</ol>
-
-<p>Any resulting <code>NA</code> values in the <code>col_begin</code> column following the merge
-operation can be easily formatted using the <code><a href='fmt_missing.html'>fmt_missing()</a></code> function.
-Separate calls of <code><a href='fmt_missing.html'>fmt_missing()</a></code> can be used for the <code>col_begin</code> and
-<code>col_end</code> columns for finer control of the replacement values.</p>
-<p>This function is part of a set of three column-merging functions. The other
-two are the general <code><a href='cols_merge.html'>cols_merge()</a></code> function and the specialized
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert()</a></code> function. These functions operate similarly, where the
-non-target columns can be optionally hidden from the output table through the
-<code>hide_columns</code> or <code>autohide</code> options.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_merge_range_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-9</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table,</span>
-<span class='co'># keeping only the `model`, `mpg_c`,</span>
-<span class='co'># and `mpg_h` columns; merge the mpg</span>
-<span class='co'># columns together as a single range</span>
-<span class='co'># column (which is labeled as MPG,</span>
-<span class='co'># in italics)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with</a></span>(<span class='st'>"mpg"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_merge_range</span>(
-    <span class='kw'>col_begin</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>mpg_c</span>),
-    <span class='kw'>col_end</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>mpg_h</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(
-    <span class='kw'>mpg_c</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"*MPG*"</span>)
-  )</div></pre>
-  </div>
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-<meta property="og:description" content="The cols_merge_uncert() function is a specialized variant of the
-cols_merge() function. It operates by taking a base value column
-(col_val) and an uncertainty column (col_uncert) and merges them into a
-single column. What results is a column with values and associated
-uncertainties (e.g., 12.0 ± 0.1), and, the column specified in col_uncert
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_merge_uncert.Rd</code></div>
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-
-    <div class="ref-description">
-    <p>The <code>cols_merge_uncert()</code> function is a specialized variant of the
-<code><a href='cols_merge.html'>cols_merge()</a></code> function. It operates by taking a base value column
-(<code>col_val</code>) and an uncertainty column (<code>col_uncert</code>) and merges them into a
-single column. What results is a column with values and associated
-uncertainties (e.g., <code>12.0 ± 0.1</code>), and, the column specified in <code>col_uncert</code>
-is dropped from the output table.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_merge_uncert</span>(<span class='no'>data</span>, <span class='no'>col_val</span>, <span class='no'>col_uncert</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" +/- "</span>, <span class='kw'>autohide</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>col_val</th>
-      <td><p>A single column name that contains the base values. This is
-the column where values will be mutated.</p></td>
-    </tr>
-    <tr>
-      <th>col_uncert</th>
-      <td><p>A single column name that contains the uncertainty values.
-These values will be combined with those in <code>col_val</code>. We have the option
-to automatically hide the <code>col_uncert</code> column through <code>autohide</code>.</p></td>
-    </tr>
-    <tr>
-      <th>sep</th>
-      <td><p>The separator text that contains the uncertainty mark. The
-default value of <code>" +/- "</code> indicates that an appropriate plus/minus mark
-will be used depending on the output context. Should you want this special
-symbol to be taken literally, it can be supplied within the base <code><a href='https://rdrr.io/r/base/AsIs.html'>I()</a></code>
-function.</p></td>
-    </tr>
-    <tr>
-      <th>autohide</th>
-      <td><p>An option to automatically hide the column specified as
-<code>col_uncert</code>. Any columns with their state changed to hidden will behave
-the same as before, they just won't be displayed in the finalized table.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>This function could be somewhat replicated using <code><a href='cols_merge.html'>cols_merge()</a></code>, however,
-<code>cols_merge_uncert()</code> employs the following specialized semantics for <code>NA</code>
-handling:</p>
-<ol>
-<li><p><code>NA</code>s in <code>col_val</code> result in missing values for the merged
-column (e.g., <code>NA</code> + <code>0.1</code> = <code>NA</code>)</p></li>
-<li><p><code>NA</code>s in <code>col_uncert</code> (but not <code>col_val</code>) result in
-base values only for the merged column (e.g.,
-<code>12.0</code> + <code>NA</code> = <code>12.0</code>)</p></li>
-<li><p><code>NA</code>s both <code>col_val</code> and <code>col_uncert</code> result in
-missing values for the merged column (e.g., <code>NA</code> + <code>NA</code> =
-<code>NA</code>)</p></li>
-</ol>
-
-<p>Any resulting <code>NA</code> values in the <code>col_val</code> column following the merge
-operation can be easily formatted using the <code><a href='fmt_missing.html'>fmt_missing()</a></code> function.</p>
-<p>This function is part of a set of three column-merging functions. The other
-two are the general <code><a href='cols_merge.html'>cols_merge()</a></code> function and the specialized
-<code><a href='cols_merge_range.html'>cols_merge_range()</a></code> function. These functions operate similarly, where the
-non-target columns can be optionally hidden from the output table through the
-<code>hide_columns</code> or <code>autohide</code> options.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_merge_uncert_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-8</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table,</span>
-<span class='co'># keeping only the `currency` and `num`</span>
-<span class='co'># columns; merge columns into one with</span>
-<span class='co'># a base value and uncertainty (after</span>
-<span class='co'># formatting the `num` column)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>currency</span>, <span class='no'>num</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>7</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>3</span>,
-    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_merge_uncert</span>(
-    <span class='kw'>col_val</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>col_uncert</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(
-    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"value + uncert."</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/cols_move.html b/docs/reference/cols_move.html
deleted file mode 100644
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+++ /dev/null
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-<meta property="og:title" content="Move one or more columns — cols_move" />
-<meta property="og:description" content="On those occasions where you need to move columns this way or that way, we
-can make use of the cols_move() function. While it's true that the movement
-of columns can be done upstream of gt, it is much easier and less error
-prone to use the function provided here. The movement procedure here takes
-one or more specified columns (in the columns argument) and places them to
-the right of a different column (the after argument). The ordering of the
-columns to be moved is preserved, as is the ordering of all other columns
-in the table." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
-
-
-
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-    <div class="page-header">
-    <h1>Move one or more columns</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_move.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>On those occasions where you need to move columns this way or that way, we
-can make use of the <code>cols_move()</code> function. While it's true that the movement
-of columns can be done upstream of <strong>gt</strong>, it is much easier and less error
-prone to use the function provided here. The movement procedure here takes
-one or more specified columns (in the <code>columns</code> argument) and places them to
-the right of a different column (the <code>after</code> argument). The ordering of the
-<code>columns</code> to be moved is preserved, as is the ordering of all other columns
-in the table.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_move</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='no'>after</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The column names to move to as a group to a different
-position. The order of the remaining columns will be preserved.</p></td>
-    </tr>
-    <tr>
-      <th>after</th>
-      <td><p>A column name used to anchor the insertion of the moved columns.
-All of the moved columns will be placed to the right of this column.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The columns supplied in <code>columns</code> must all exist in the table and none of
-them can be in the <code>after</code> argument. The <code>after</code> column must also exist and
-only one column should be provided here. If you need to place one or columns
-at the beginning of the column series, the <code><a href='cols_move_to_start.html'>cols_move_to_start()</a></code> function
-should be used. Similarly, if those columns to move should be placed at the
-end of the column series then use <code><a href='cols_move_to_end.html'>cols_move_to_end()</a></code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_move_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-6</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># With the remaining columns, position</span>
-<span class='co'># `population` after `country_name`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_move</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-    <span class='kw'>after</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>country_name</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/cols_move_to_end.html b/docs/reference/cols_move_to_end.html
deleted file mode 100644
index dfc8db1f9..000000000
--- a/docs/reference/cols_move_to_end.html
+++ /dev/null
@@ -1,260 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-upstream of gt, this function makes to process much easier and it's less
-error prone. The ordering of the columns that are moved to the end is
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-    <h1>Move one or more columns to the end</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_move_to_end.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>It's possible to move a set of columns to the end of the column series, we
-only need to specify which <code>columns</code> are to be moved. While this can be done
-upstream of <strong>gt</strong>, this function makes to process much easier and it's less
-error prone. The ordering of the <code>columns</code> that are moved to the end is
-preserved (same with the ordering of all other columns in the table).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_move_to_end</span>(<span class='no'>data</span>, <span class='no'>columns</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The column names to move to the right-most side of the table.
-The order in which columns are provided will be preserved (as is the case
-with the remaining columns).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The columns supplied in <code>columns</code> must all exist in the table. If you need to
-place one or columns at the start of the column series, the
-<code><a href='cols_move_to_start.html'>cols_move_to_start()</a></code> function should be used. More control is offered with
-the <code><a href='cols_move.html'>cols_move()</a></code> function, where columns could be placed after a specific
-column.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_move_to_end_1.png' width=100% /></p>
-<p><img src='figures/man_cols_move_to_end_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># With the remaining columns, move the</span>
-<span class='co'># `year` column to the end</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_move_to_end</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>)
-  )
-
-<span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># With the remaining columns, move `year`</span>
-<span class='co'># and `country_name` to the end</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_move_to_end</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>, <span class='no'>country_name</span>)
-  )</div></pre>
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diff --git a/docs/reference/cols_move_to_start.html b/docs/reference/cols_move_to_start.html
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-we only need to specify which columns. It's possible to do this upstream of
-gt, however, it is easier with this function and it presents less
-possibility for error. The ordering of the columns that are moved to the
-start is preserved (same with the ordering of all other columns in the
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-    <h1>Move one or more columns to the start</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_move_to_start.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>We can easily move set of columns to the beginning of the column series and
-we only need to specify which <code>columns</code>. It's possible to do this upstream of
-<strong>gt</strong>, however, it is easier with this function and it presents less
-possibility for error. The ordering of the <code>columns</code> that are moved to the
-start is preserved (same with the ordering of all other columns in the
-table).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_move_to_start</span>(<span class='no'>data</span>, <span class='no'>columns</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The column names to move to the left-most side of the table.
-The order in which columns are provided will be preserved (as is the case
-with the remaining columns).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The columns supplied in <code>columns</code> must all exist in the table. If you need to
-place one or columns at the end of the column series, the
-<code><a href='cols_move_to_end.html'>cols_move_to_end()</a></code> function should be used. More control is offered with
-the <code><a href='cols_move.html'>cols_move()</a></code> function, where columns could be placed after a specific
-column.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_move_to_start_1.png' width=100% /></p>
-<p><img src='figures/man_cols_move_to_start_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code>,
-<code><a href='cols_width.html'>cols_width</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># With the remaining columns, move the</span>
-<span class='co'># `year` column to the start</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_move_to_start</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>)
-  )
-
-<span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># With the remaining columns, move `year`</span>
-<span class='co'># and `population` to the start</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_move_to_start</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>year</span>, <span class='no'>population</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/cols_width.html b/docs/reference/cols_width.html
deleted file mode 100644
index fe056238b..000000000
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+++ /dev/null
@@ -1,269 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta property="og:description" content="Manual specifications of column widths can be performed using the
-cols_width() function. We choose which columns get specific widths (in
-pixels, usually by use of the px() helper function). Width assignments are
-supplied in ... through two-sided formulas, where the left-hand side
-defines the target columns and the right-hand side is a single width value in
-pixels." />
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-    <div class="page-header">
-    <h1>Set the widths of columns</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_columns.R'><code>R/modify_columns.R</code></a></small>
-    <div class="hidden name"><code>cols_width.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Manual specifications of column widths can be performed using the
-<code>cols_width()</code> function. We choose which columns get specific widths (in
-pixels, usually by use of the <code><a href='px.html'>px()</a></code> helper function). Width assignments are
-supplied in <code>...</code> through two-sided formulas, where the left-hand side
-defines the target columns and the right-hand side is a single width value in
-pixels.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>cols_width</span>(<span class='no'>data</span>, <span class='no'>...</span>, <span class='kw'>.list</span> <span class='kw'>=</span> <span class='fu'>list2</span>(<span class='no'>...</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>Expressions for the assignment of column widths for the table
-columns in <code>data</code>. Two-sided formulas (e.g, <code>&lt;LHS&gt; ~ &lt;RHS&gt;</code>) can be used,
-where the left-hand side corresponds to selections of columns and the
-right-hand side evaluates to single-length character values in the form
-<code>{##}px</code> (i.e., pixel dimensions); the <code><a href='px.html'>px()</a></code> helper function is best used
-for this purpose. Column names should be enclosed in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>. The
-column-based select helpers <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code> can be used in the LHS.
-Subsequent expressions that operate on the columns assigned previously will
-result in overwriting column width values (both in the same <code>cols_width()</code>
-call and across separate calls). All other columns can be assigned a
-default width value by using <code>TRUE</code> or <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code> on the left-hand
-side.</p></td>
-    </tr>
-    <tr>
-      <th>.list</th>
-      <td><p>Allows for the use of a list as an input alternative to <code>...</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Normally, column widths are automatically set to span across the width of the
-container (both table and container widths can be individually modified with
-the <code>table.width</code> and <code>container.width</code> options within <code><a href='tab_options.html'>tab_options()</a></code>). When
-using <code>cols_width()</code> though, the <code>table.width</code> option is disregarded in
-favor of the pixel values set for each column.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_cols_width_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>4-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Modify Columns: 
-<code><a href='cols_align.html'>cols_align</a>()</code>,
-<code><a href='cols_hide.html'>cols_hide</a>()</code>,
-<code><a href='cols_label.html'>cols_label</a>()</code>,
-<code><a href='cols_merge_range.html'>cols_merge_range</a>()</code>,
-<code><a href='cols_merge_uncert.html'>cols_merge_uncert</a>()</code>,
-<code><a href='cols_merge.html'>cols_merge</a>()</code>,
-<code><a href='cols_move_to_end.html'>cols_move_to_end</a>()</code>,
-<code><a href='cols_move_to_start.html'>cols_move_to_start</a>()</code>,
-<code><a href='cols_move.html'>cols_move</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># with named arguments in `...`, we</span>
-<span class='co'># can specify the exact widths for</span>
-<span class='co'># table columns (using `everything()`</span>
-<span class='co'># or `TRUE` at the end will capture</span>
-<span class='co'># all remaining columns)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
-    <span class='no'>num</span>, <span class='no'>char</span>, <span class='no'>date</span>,
-    <span class='no'>datetime</span>, <span class='no'>row</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>cols_width</span>(
-    <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>) ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>150</span>),
-    <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with</a></span>(<span class='st'>"r"</span>) ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>100</span>),
-    <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with</a></span>(<span class='st'>"date"</span>) ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>200</span>),
-    <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>() ~ <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>60</span>)
-  )</div></pre>
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-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/countrypops.html b/docs/reference/countrypops.html
deleted file mode 100644
index 5a52d2a44..000000000
--- a/docs/reference/countrypops.html
+++ /dev/null
@@ -1,227 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-
-<title>Yearly populations of countries from 1960 to 2017 — countrypops • gt</title>
-
-<!-- favicons -->
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-<meta property="og:description" content="A dataset that presents yearly, total populations of countries. Total
-population is based on counts of all residents regardless of legal status or
-citizenship. Country identifiers include the English-language country names,
-and the 2- and 3-letter ISO 3166-1 country codes. Each row contains a
-population value for a given year (from 1960 to 2017). Any NA values
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-    <div class="page-header">
-    <h1>Yearly populations of countries from 1960 to 2017</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
-    <div class="hidden name"><code>countrypops.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>A dataset that presents yearly, total populations of countries. Total
-population is based on counts of all residents regardless of legal status or
-citizenship. Country identifiers include the English-language country names,
-and the 2- and 3-letter ISO 3166-1 country codes. Each row contains a
-<code>population</code> value for a given <code>year</code> (from 1960 to 2017). Any <code>NA</code> values
-for <code>populations</code> indicate the non-existence of the country during that year.</p>
-    </div>
-
-    <pre class="usage"><span class='no'>countrypops</span></pre>
-
-
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>A tibble with 12470 rows and 5 variables:</p><dl'>
-<dt>country_name</dt><dd><p>Name of the country</p></dd>
-<dt>country_code_2</dt><dd><p>The 2-letter ISO 3166-1 country code</p></dd>
-<dt>country_code_3</dt><dd><p>The 3-letter ISO 3166-1 country code</p></dd>
-<dt>year</dt><dd><p>The year for the population estimate</p></dd>
-<dt>population</dt><dd><p>The population estimate, midway through the year</p></dd>
-
-</dl>
-
-    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
-
-    <p><a href='https://data.worldbank.org/indicator/SP.POP.TOTL'>https://data.worldbank.org/indicator/SP.POP.TOTL</a></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>11-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Datasets: 
-<code><a href='exibble.html'>exibble</a></code>,
-<code><a href='gtcars.html'>gtcars</a></code>,
-<code><a href='pizzaplace.html'>pizzaplace</a></code>,
-<code><a href='sp500.html'>sp500</a></code>,
-<code><a href='sza.html'>sza</a></code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
-<span class='co'># available in `countrypops`</span>
-<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>countrypops</span>)</div><div class='output co'>#&gt; Rows: 12,470
-#&gt; Columns: 5
-#&gt; $ country_name   <span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "Aruba", "Aruba", "Aruba", "Aruba", "Aruba", "Aruba", …
-#&gt; $ country_code_2 </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", "AW", …
-#&gt; $ country_code_3 </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "ABW", "ABW"…
-#&gt; $ year           </span><span style='color: #555555;font-style: italic;'>&lt;int&gt;</span><span> 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, …
-#&gt; $ population     </span><span style='color: #555555;font-style: italic;'>&lt;int&gt;</span><span> 54211, 55438, 56225, 56695, 57032, 57360, 57715, 58055…</div><div class='input'>
-</div></span></pre>
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diff --git a/docs/reference/currency.html b/docs/reference/currency.html
deleted file mode 100644
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-<meta property="og:description" content="The currency() helper function makes it easy to specify a context-aware
-currency symbol to currency argument of fmt_currency(). Since gt can
-render tables to several output formats, currency() allows for different
-variations of the custom symbol based on the output context (which are
-html, latex, rtf, and default). The number of decimal places for
-the custom currency defaults to 2, however, a value set for the decimals
-argument of fmt_currency() will take precedence." />
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-    <h1>Supply a custom currency symbol to <code>fmt_currency()</code></h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>currency.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>currency()</code> helper function makes it easy to specify a context-aware
-currency symbol to <code>currency</code> argument of <code><a href='fmt_currency.html'>fmt_currency()</a></code>. Since <strong>gt</strong> can
-render tables to several output formats, <code>currency()</code> allows for different
-variations of the custom symbol based on the output context (which are
-<code>html</code>, <code>latex</code>, <code>rtf</code>, and <code>default</code>). The number of decimal places for
-the custom currency defaults to <code>2</code>, however, a value set for the <code>decimals</code>
-argument of <code><a href='fmt_currency.html'>fmt_currency()</a></code> will take precedence.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>currency</span>(<span class='no'>...</span>, <span class='kw'>.list</span> <span class='kw'>=</span> <span class='fu'>list2</span>(<span class='no'>...</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>...</th>
-      <td><p>One or more named arguments using output contexts as the names and
-currency symbol text as the values.</p></td>
-    </tr>
-    <tr>
-      <th>.list</th>
-      <td><p>Allows for the use of a list as an input alternative to <code>...</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list object of class <code>gt_currency</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>We can use any combination of <code>html</code>, <code>latex</code>, <code>rtf</code>, and <code>default</code> as named
-arguments for the currency text in each of the namesake contexts. The
-<code>default</code> value is used as a fallback when there doesn't exist a dedicated
-currency text value for a particular output context (e.g., when a table is
-rendered as HTML and we use <code>currency(latex = "LTC", default = "ltc")</code>, the
-currency symbol will be <code>"ltc"</code>. For convenience, if we provide only a single
-string without a name, it will be taken as the <code>default</code> (i.e.,
-<code>currency("ltc")</code> is equivalent to <code>currency(default = "ltc")</code>). However, if
-we were to specify currency strings for multiple output contexts, names are
-required each and every context.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_currency_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-14</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># format the `currency` column to have</span>
-<span class='co'># currency values in guilder (a defunct</span>
-<span class='co'># Dutch currency)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_currency.html'>fmt_currency</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='fu'>currency</span>(
-      <span class='kw'>html</span> <span class='kw'>=</span> <span class='st'>"&amp;fnof;"</span>,
-      <span class='kw'>default</span> <span class='kw'>=</span> <span class='st'>"f"</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>
-  )</div></pre>
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-<meta property="og:description" content="It's possible to add color to data cells according to their values. The
-data_color() function colors all rows of any columns supplied. There are
-two ways to define how cells are colored: (1) through the use of a supplied
-color palette, and (2) through use of a color mapping function available from
-the scales package. The first method colorizes cell data according to
-whether values are character or numeric. The second method provides more
-control over how cells are colored since we provide an explicit color
-function and thus other requirements such as bin counts, cut points, or a
-numeric domain. Finally, we can choose whether to apply the cell-specific
-colors to either the cell background or the cell text." />
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-    <h1>Set data cell colors using a palette or a color function</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/data_color.R'><code>R/data_color.R</code></a></small>
-    <div class="hidden name"><code>data_color.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>It's possible to add color to data cells according to their values. The
-<code>data_color()</code> function colors all rows of any <code>columns</code> supplied. There are
-two ways to define how cells are colored: (1) through the use of a supplied
-color palette, and (2) through use of a color mapping function available from
-the <strong>scales</strong> package. The first method colorizes cell data according to
-whether values are character or numeric. The second method provides more
-control over how cells are colored since we provide an explicit color
-function and thus other requirements such as bin counts, cut points, or a
-numeric domain. Finally, we can choose whether to apply the cell-specific
-colors to either the cell background or the cell text.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>data_color</span>(
-  <span class='no'>data</span>,
-  <span class='no'>columns</span>,
-  <span class='no'>colors</span>,
-  <span class='kw'>alpha</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>apply_to</span> <span class='kw'>=</span> <span class='st'>"fill"</span>,
-  <span class='kw'>autocolor_text</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns wherein changes to cell data colors should occur.</p></td>
-    </tr>
-    <tr>
-      <th>colors</th>
-      <td><p>Either a color mapping function from the <strong>scales</strong> package or
-a vector of colors to use for each distinct value or level in each of the
-provided <code>columns</code>. The color mapping functions are:
-<code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_quantile()</a></code>, <code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_bin()</a></code>, <code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_numeric()</a></code>, and
-<code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_factor()</a></code>. If providing a vector of colors as a palette, each
-color value provided must either be a color name (in the set of colors
-provided by <code><a href='https://rdrr.io/r/grDevices/colors.html'>grDevices::colors()</a></code>) or a hexadecimal string in the form of
-"#RRGGBB" or "#RRGGBBAA".</p></td>
-    </tr>
-    <tr>
-      <th>alpha</th>
-      <td><p>An optional, fixed alpha transparency value that will be applied
-to all of the <code>colors</code> provided (regardless of whether a color palette was
-directly supplied or generated through a color mapping function).</p></td>
-    </tr>
-    <tr>
-      <th>apply_to</th>
-      <td><p>Which style element should the colors be applied to? Options
-include the cell background (the default, given as <code>fill</code>) or the cell
-text (<code>text</code>).</p></td>
-    </tr>
-    <tr>
-      <th>autocolor_text</th>
-      <td><p>An option to let <strong>gt</strong> modify the coloring of text
-within cells undergoing background coloring. This will in some cases yield
-more optimal text-to-background color contrast. By default, this is set to
-<code>TRUE</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The <code>col_*()</code> color mapping functions from the scales package can be used in
-the <code>colors</code> argument. These functions map data values (<code>numeric</code> or
-<code>factor</code>/<code>character</code>) to colors according to the provided palette.</p>
-<ul>
-<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_numeric()</a></code>: provides a simple linear mapping from
-continuous numeric data to an interpolated palette.</p></li>
-<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_bin()</a></code>: provides a mapping of continuous numeric data to
-value-based bins. This internally uses the <code><a href='https://rdrr.io/r/base/cut.html'>base::cut()</a></code> function.</p></li>
-<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_quantile()</a></code>: provides a mapping of continuous
-numeric data to quantiles. This internally uses the
-<code><a href='https://rdrr.io/r/stats/quantile.html'>stats::quantile()</a></code> function.</p></li>
-<li><p><code><a href='https://scales.r-lib.org//reference/col_numeric.html'>scales::col_factor()</a></code>: provides a mapping of factors to colors. If the
-palette is discrete and has a different number of colors than the number of
-factors, interpolation is used.</p></li>
-</ul>
-
-<p>By default, <strong>gt</strong> will choose the ideal text color (for maximal contrast)
-when colorizing the background of data cells. This option can be disabled by
-setting <code>autocolor_text</code> to <code>FALSE</code>.</p>
-<p>Choosing the right color palette can often be difficult because it's both
-hard to discover suitable palettes and then obtain the vector of colors. To
-make this process easier we can elect to use the <strong>paletteer</strong> package,
-which makes a wide range of palettes from various R packages readily
-available. The <code><a href='info_paletteer.html'>info_paletteer()</a></code> information table allows us to easily
-inspect all of the discrete color palettes available in <strong>paletteer</strong>. We
-only then need to specify the <code>package</code> and <code>palette</code> when calling the
-<code><a href='https://rdrr.io/pkg/paletteer/man/paletteer_d.html'>paletteer::paletteer_d()</a></code> function, and, we get the palette as a vector of
-hexadecimal colors.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_data_color_1.png' width=100% /></p>
-<p><img src='figures/man_data_color_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-13</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># library(paletteer)</span>
-
-<span class='co'># Use `countrypops` to create a gt table;</span>
-<span class='co'># Apply a color scale to the `population`</span>
-<span class='co'># column with `scales::col_numeric`,</span>
-<span class='co'># four supplied colors, and a domain</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>country_name</span> <span class='kw'>==</span> <span class='st'>"Mongolia"</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"code"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/utils/head.html'>tail</a></span>(<span class='fl'>10</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>data_color</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>population</span>),
-    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
-      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(
-        <span class='st'>"red"</span>, <span class='st'>"orange"</span>, <span class='st'>"green"</span>, <span class='st'>"blue"</span>),
-      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>0.2E7</span>, <span class='fl'>0.4E7</span>))
-  )
-
-<span class='co'># Use `pizzaplace` to create a gt table;</span>
-<span class='co'># Apply colors from the `red_material`</span>
-<span class='co'># palette (in the `ggsci` pkg but</span>
-<span class='co'># more easily gotten from the `paletteer`</span>
-<span class='co'># package, info at `info_paletteer()`) to</span>
-<span class='co'># to `sold` and `income` columns; setting</span>
-<span class='co'># the `domain` of `scales::col_numeric()`</span>
-<span class='co'># to `NULL` will use the bounds of the</span>
-<span class='co'># available data as the domain</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>type</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"chicken"</span>, <span class='st'>"supreme"</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>type</span>, <span class='no'>size</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(
-    <span class='kw'>sold</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/context.html'>n</a></span>(),
-    <span class='kw'>income</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>price</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"size"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>data_color</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sold</span>, <span class='no'>income</span>),
-    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
-      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='kw pkg'>paletteer</span><span class='kw ns'>::</span><span class='fu'><a href='https://rdrr.io/pkg/paletteer/man/paletteer_d.html'>paletteer_d</a></span>(
-        <span class='kw'>palette</span> <span class='kw'>=</span> <span class='st'>"ggsci::red_material"</span>
-        ) <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://rdrr.io/r/base/character.html'>as.character</a></span>(),
-      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-      )
-  )</div></pre>
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-    <h1>Perform LaTeX escaping</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>escape_latex.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Text may contain several characters with special meanings in LaTeX. This
-function will transform a character vector so that it is safe to use within
-LaTeX tables.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>escape_latex</span>(<span class='no'>text</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>text</th>
-      <td><p>a character vector containing the text that is to be
-LaTeX-escaped.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character vector.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-20</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
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-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/exibble.html b/docs/reference/exibble.html
deleted file mode 100644
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-well-suited for quick experimentation with the functions in this package. It
-contains only eight rows with numeric, character, and factor columns. The
-last 4 rows contain NA values in the majority of this tibble's columns (1
-missing value per column). The date, time, and datetime columns are
-character-based dates/times in the familiar ISO 8601 format. The row and
-group columns provide for unique rownames and two groups (grp_a and
-grp_b) for experimenting with the gt() function's rowname_col and
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-    <h1>A toy example tibble for testing with gt: exibble</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
-    <div class="hidden name"><code>exibble.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This tibble contains data of a few different classes, which makes it
-well-suited for quick experimentation with the functions in this package. It
-contains only eight rows with numeric, character, and factor columns. The
-last 4 rows contain <code>NA</code> values in the majority of this tibble's columns (1
-missing value per column). The <code>date</code>, <code>time</code>, and <code>datetime</code> columns are
-character-based dates/times in the familiar ISO 8601 format. The <code>row</code> and
-<code>group</code> columns provide for unique rownames and two groups (<code>grp_a</code> and
-<code>grp_b</code>) for experimenting with the <code><a href='gt.html'>gt()</a></code> function's <code>rowname_col</code> and
-<code>groupname_col</code> arguments.</p>
-    </div>
-
-    <pre class="usage"><span class='no'>exibble</span></pre>
-
-
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>A tibble with 8 rows and 9 variables:</p><dl'>
-<dt>num</dt><dd><p>a numeric column ordered with increasingly larger values</p></dd>
-<dt>char</dt><dd><p>a character column composed of names of fruits from <code>a</code> to
-<code>h</code></p></dd>
-<dt>fctr</dt><dd><p>a factor column with numbers from 1 to 8, written out</p></dd>
-<dt>date, time, datetime</dt><dd><p>character columns with dates, times, and
-datetimes</p></dd>
-<dt>currency</dt><dd><p>a numeric column that is useful for testing currency-based
-formatting</p></dd>
-<dt>row</dt><dd><p>a character column in the format <code>row_X</code> which can be
-useful for testing with row captions in a table stub</p></dd>
-<dt>group</dt><dd><p>a character column with four <code>grp_a</code> values and four
-<code>grp_b</code> values which can be useful for testing tables that contain
-row groups</p></dd>
-
-</dl>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>11-6</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Datasets: 
-<code><a href='countrypops.html'>countrypops</a></code>,
-<code><a href='gtcars.html'>gtcars</a></code>,
-<code><a href='pizzaplace.html'>pizzaplace</a></code>,
-<code><a href='sp500.html'>sp500</a></code>,
-<code><a href='sza.html'>sza</a></code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
-<span class='co'># available in `exibble`</span>
-<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>exibble</span>)</div><div class='output co'>#&gt; Rows: 8
-#&gt; Columns: 9
-#&gt; $ num      <span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 1.111e-01, 2.222e+00, 3.333e+01, 4.444e+02, 5.550e+03, NA, 7…
-#&gt; $ char     </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "apricot", "banana", "coconut", "durian", NA, "fig", "grapef…
-#&gt; $ fctr     </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span> one, two, three, four, five, six, seven, eight
-#&gt; $ date     </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2015-01-15", "2015-02-15", "2015-03-15", "2015-04-15", "201…
-#&gt; $ time     </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "13:35", "14:40", "15:45", "16:50", "17:55", NA, "19:10", "2…
-#&gt; $ datetime </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2018-01-01 02:22", "2018-02-02 14:33", "2018-03-03 03:44", …
-#&gt; $ currency </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 49.950, 17.950, 1.390, 65100.000, 1325.810, 13.255, NA, 0.440
-#&gt; $ row      </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "row_1", "row_2", "row_3", "row_4", "row_5", "row_6", "row_7…
-#&gt; $ group    </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "grp_a", "grp_a", "grp_a", "grp_a", "grp_b", "grp_b", "grp_b…</div><div class='input'>
-</div></span></pre>
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-<meta property="og:description" content="Get a list of summary row data frames from a gt_tbl object where summary
-rows were added via the summary_rows() function. The output data frames
-contain the groupname and rowname columns, whereby rowname contains
-descriptive stub labels for the summary rows." />
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-    <h1>Extract a summary list from a <strong>gt</strong> object</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
-    <div class="hidden name"><code>extract_summary.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Get a list of summary row data frames from a <code>gt_tbl</code> object where summary
-rows were added via the <code><a href='summary_rows.html'>summary_rows()</a></code> function. The output data frames
-contain the <code>groupname</code> and <code>rowname</code> columns, whereby <code>rowname</code> contains
-descriptive stub labels for the summary rows.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>extract_summary</span>(<span class='no'>data</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A list of data frames containing summary data.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_extract_summary_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>13-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Export Functions: 
-<code><a href='as_latex.html'>as_latex</a>()</code>,
-<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
-<code><a href='as_rtf.html'>as_rtf</a>()</code>,
-<code><a href='gtsave.html'>gtsave</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table with</span>
-<span class='co'># row groups; create summary rows by row</span>
-<span class='co'># group (`min`, `max`, `avg`) and then</span>
-<span class='co'># extract the summary rows as a list</span>
-<span class='co'># object</span>
-<span class='no'>summary_extracted</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
-      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-30"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='no'>date</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
-    <span class='kw'>week</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
-      <span class='st'>"W"</span>, <span class='fu'><a href='https://rdrr.io/r/base/strptime.html'>strftime</a></span>(<span class='no'>date</span>, <span class='kw'>format</span> <span class='kw'>=</span> <span class='st'>"%V"</span>))
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>adj_close</span>, -<span class='no'>volume</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(
-    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
-    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"week"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>high</span>, <span class='no'>low</span>, <span class='no'>close</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>),
-      <span class='kw'>avg</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/mean.html'>mean</a></span>(<span class='no'>.</span>)),
-    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>extract_summary</span>()
-
-<span class='co'># Use the summary list to make a new</span>
-<span class='co'># gt table; the key thing is to use</span>
-<span class='co'># `dplyr::bind_rows()` and then pass the</span>
-<span class='co'># tibble to `gt()` (the `groupname` and</span>
-<span class='co'># `rowname` magic column names create</span>
-<span class='co'># row groups and a stub)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>summary_extracted</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='https://rdrr.io/r/base/unlist.html'>unlist</a></span>(<span class='kw'>recursive</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/bind.html'>bind_rows</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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diff --git a/docs/reference/figures/gt-test-drive.svg b/docs/reference/figures/gt-test-drive.svg
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diff --git a/docs/reference/fmt.html b/docs/reference/fmt.html
deleted file mode 100644
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-<meta property="og:description" content="The fmt() function provides greater control in formatting raw data values
-than any of the specialized fmt_*() functions that are available in
-gt. Along with the columns and rows arguments that provide some
-precision in targeting data cells, the fns argument allows you to define
-one or more functions for manipulating the raw data.
-If providing a single function to fns, the recommended format is in the
-form: fns = function(x) .... This single function will format the targeted
-data cells the same way regardless of the output format (e.g., HTML, LaTeX,
-RTF).
-If you require formatting of x that depends on the output format, a list of
-functions can be provided for the html, latex, and default contexts.
-This can be in the form of fns = list(html = function(x) ..., latex = function(x) ..., default = function(x) ...). In this multiple-function case,
-we recommended including the default function as a fallback if all contexts
-aren't provided." />
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-    <div class="page-header">
-    <h1>Set a column format with a formatter function</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>fmt()</code> function provides greater control in formatting raw data values
-than any of the specialized <code>fmt_*()</code> functions that are available in
-<strong>gt</strong>. Along with the <code>columns</code> and <code>rows</code> arguments that provide some
-precision in targeting data cells, the <code>fns</code> argument allows you to define
-one or more functions for manipulating the raw data.
-If providing a single function to <code>fns</code>, the recommended format is in the
-form: <code>fns = function(x) ...</code>. This single function will format the targeted
-data cells the same way regardless of the output format (e.g., HTML, LaTeX,
-RTF).
-If you require formatting of <code>x</code> that depends on the output format, a list of
-functions can be provided for the <code>html</code>, <code>latex</code>, and <code>default</code> contexts.
-This can be in the form of <code>fns = list(html = function(x) ..., latex = function(x) ..., default = function(x) ...)</code>. In this multiple-function case,
-we recommended including the <code>default</code> function as a fallback if all contexts
-aren't provided.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt</span>(<span class='no'>data</span>, <span class='kw'>columns</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='no'>fns</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>fns</th>
-      <td><p>Either a single formatting function or a named list of functions.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>As with all of the <code>fmt_*()</code> functions, targeting of values is done through
-<code>columns</code> and additionally by <code>rows</code> (if nothing is provided for <code>rows</code> then
-entire columns are selected). A number of helper functions exist to make
-targeting more effective. Conditional formatting is possible by providing a
-conditional expression to the <code>rows</code> argument. See the Arguments section for
-more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-11</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># format the numeric values in the `num`</span>
-<span class='co'># column with a function supplied to</span>
-<span class='co'># the `fns` argument</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>row</span>, -<span class='no'>group</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
-      <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='st'>"'"</span>, <span class='no'>x</span> * <span class='fl'>1000</span>, <span class='st'>"'"</span>)
-    }
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/fmt_currency.html b/docs/reference/fmt_currency.html
deleted file mode 100644
index 81c0a204d..000000000
--- a/docs/reference/fmt_currency.html
+++ /dev/null
@@ -1,440 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<title>Format values as currencies — fmt_currency • gt</title>
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-<meta property="og:title" content="Format values as currencies — fmt_currency" />
-<meta property="og:description" content="With numeric values in a gt table, we can perform currency-based
-formatting. This function supports both automatic formatting with a
-three-letter or numeric currency code. We can also specify a custom currency
-that is formatted according to the output context with the currency()
-helper function. Numeric formatting facilitated through the use of a locale
-ID. We have fine control over the conversion from numeric values to currency
-values, where we could take advantage of the following options:
-the currency: providing a currency code or common currency name will
-procure the correct currency symbol and number of currency subunits; we could
-also use the currency() helper function to specify a custom currency
-currency symbol placement: the currency symbol can be placed before
-or after the values
-decimals/subunits: choice of the number of decimal places, and a
-choice of the decimal symbol, and an option on whether to include or exclude
-the currency subunits (decimal portion)
-negative values: choice of a negative sign or parentheses for values
-less than zero
-digit grouping separators: options to enable/disable digit separators
-and provide a choice of separator symbol
-scaling: we can choose to scale targeted values by a multiplier value
-large-number suffixing: larger figures (thousands, millions, etc.) can
-be autoscaled and decorated with the appropriate suffixes
-pattern: option to use a text pattern for decoration of the formatted
-currency values
-locale-based formatting: providing a locale ID will result in
-currency formatting specific to the chosen locale
-We can use the info_currencies() function for a useful reference on all of
-the possible inputs to the currency argument." />
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-    <div class="page-header">
-    <h1>Format values as currencies</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_currency.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>With numeric values in a <strong>gt</strong> table, we can perform currency-based
-formatting. This function supports both automatic formatting with a
-three-letter or numeric currency code. We can also specify a custom currency
-that is formatted according to the output context with the <code><a href='currency.html'>currency()</a></code>
-helper function. Numeric formatting facilitated through the use of a locale
-ID. We have fine control over the conversion from numeric values to currency
-values, where we could take advantage of the following options:</p><ul>
-<li><p>the currency: providing a currency code or common currency name will
-procure the correct currency symbol and number of currency subunits; we could
-also use the <code><a href='currency.html'>currency()</a></code> helper function to specify a custom currency</p></li>
-<li><p>currency symbol placement: the currency symbol can be placed before
-or after the values</p></li>
-<li><p>decimals/subunits: choice of the number of decimal places, and a
-choice of the decimal symbol, and an option on whether to include or exclude
-the currency subunits (decimal portion)</p></li>
-<li><p>negative values: choice of a negative sign or parentheses for values
-less than zero</p></li>
-<li><p>digit grouping separators: options to enable/disable digit separators
-and provide a choice of separator symbol</p></li>
-<li><p>scaling: we can choose to scale targeted values by a multiplier value</p></li>
-<li><p>large-number suffixing: larger figures (thousands, millions, etc.) can
-be autoscaled and decorated with the appropriate suffixes</p></li>
-<li><p>pattern: option to use a text pattern for decoration of the formatted
-currency values</p></li>
-<li><p>locale-based formatting: providing a locale ID will result in
-currency formatting specific to the chosen locale</p></li>
-</ul><p>We can use the <code><a href='info_currencies.html'>info_currencies()</a></code> function for a useful reference on all of
-the possible inputs to the <code>currency</code> argument.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_currency</span>(
-  <span class='no'>data</span>,
-  <span class='no'>columns</span>,
-  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"USD"</span>,
-  <span class='kw'>use_subunits</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>accounting</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>,
-  <span class='kw'>suffixing</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
-  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
-  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
-  <span class='kw'>placement</span> <span class='kw'>=</span> <span class='st'>"left"</span>,
-  <span class='kw'>incl_space</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>currency</th>
-      <td><p>The currency to use for the numeric value. This input can be
-supplied as a 3-letter currency code (e.g., <code>"USD"</code> for U.S. Dollars,
-<code>"EUR"</code> for the Euro currency). Use <code><a href='info_currencies.html'>info_currencies()</a></code> to get an
-information table with all of the valid currency codes and examples of
-each. Alternatively, we can provide a common currency name (e.g.,
-<code>"dollar"</code>, <code>"pound"</code>, <code>"yen"</code>, etc.) to simplify the process. Use
-<code><a href='info_currencies.html'>info_currencies()</a></code> with the <code>type == "symbol"</code> option to view an
-information table with all of the supported currency symbol names along
-with examples.</p>
-<p>We can also use the <code><a href='currency.html'>currency()</a></code> helper function to specify a custom
-currency, where the string could vary across output contexts. For example,
-using <code><a href='currency.html'>currency(html = "&amp;fnof;", default = "f")</a></code> would give us a suitable
-glyph for the Dutch guilder in an HTML output table, and it would simply be
-the letter "f" in all other output contexts). Please note that <code>decimals</code>
-will default to <code>2</code> when using the <code><a href='currency.html'>currency()</a></code> helper function.</p>
-<p>If nothing is provided to <code>currency</code> then <code>"USD"</code> (U.S. dollars) will be
-used.</p></td>
-    </tr>
-    <tr>
-      <th>use_subunits</th>
-      <td><p>An option for whether the subunits portion of a currency
-value should be displayed. By default, this is <code>TRUE</code>.</p></td>
-    </tr>
-    <tr>
-      <th>accounting</th>
-      <td><p>An option to use accounting style for currency values. With
-<code>FALSE</code> (the default), negative values will be shown with a minus sign.
-Using <code>accounting = TRUE</code> will put negative values in parentheses.</p></td>
-    </tr>
-    <tr>
-      <th>decimals</th>
-      <td><p>An option to specify the exact number of decimal places to
-use. The default number of decimal places is <code>2</code>.</p></td>
-    </tr>
-    <tr>
-      <th>use_seps</th>
-      <td><p>An option to use digit group separators. The type of digit
-group separator is set by <code>sep_mark</code> and overridden if a locale ID is
-provided to <code>locale</code>. This setting is <code>TRUE</code> by default.</p></td>
-    </tr>
-    <tr>
-      <th>scale_by</th>
-      <td><p>A value to scale the input. The default is <code>1.0</code>. All numeric
-values will be multiplied by this value first before undergoing formatting.
-This value will be ignored if using any of the <code>suffixing</code> options (i.e.,
-where <code>suffixing</code> is not set to <code>FALSE</code>).</p></td>
-    </tr>
-    <tr>
-      <th>suffixing</th>
-      <td><p>An option to scale and apply suffixes to larger numbers
-(e.g., <code>1924000</code> can be transformed to <code>1.92M</code>). This option can accept a
-logical value, where <code>FALSE</code> (the default) will not perform this
-transformation and <code>TRUE</code> will apply thousands (<code>K</code>), millions (<code>M</code>),
-billions (<code>B</code>), and trillions (<code>T</code>) suffixes after automatic value scaling.
-We can also specify which symbols to use for each of the value ranges by
-using a character vector of the preferred symbols to replace the defaults
-(e.g., <code><a href='https://rdrr.io/r/base/c.html'>c("k", "Ml", "Bn", "Tr")</a></code>).</p>
-<p>Including <code>NA</code> values in the vector will ensure that the particular range
-will either not be included in the transformation (e.g, <code><a href='https://rdrr.io/r/base/c.html'>c(NA, "M", "B", "T")</a></code> won't modify numbers in the thousands range) or the range will
-inherit a previous suffix (e.g., with <code><a href='https://rdrr.io/r/base/c.html'>c("K", "M", NA, "T")</a></code>, all numbers
-in the range of millions and billions will be in terms of millions).</p>
-<p>Any use of <code>suffixing</code> (where it is not set expressly as <code>FALSE</code>) means
-that any value provided to <code>scale_by</code> will be ignored.</p></td>
-    </tr>
-    <tr>
-      <th>pattern</th>
-      <td><p>A formatting pattern that allows for decoration of the
-formatted value. The value itself is represented by <code>{x}</code> and all other
-characters are taken to be string literals.</p></td>
-    </tr>
-    <tr>
-      <th>sep_mark</th>
-      <td><p>The mark to use as a separator between groups of digits
-(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
-of <code>1,000</code>).</p></td>
-    </tr>
-    <tr>
-      <th>dec_mark</th>
-      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
-    </tr>
-    <tr>
-      <th>placement</th>
-      <td><p>The placement of the currency symbol. This can be either be
-<code>left</code> (the default) or <code>right</code>.</p></td>
-    </tr>
-    <tr>
-      <th>incl_space</th>
-      <td><p>An option for whether to include a space between the value
-and the currency symbol. The default is to not introduce a space character.</p></td>
-    </tr>
-    <tr>
-      <th>locale</th>
-      <td><p>An optional locale ID that can be used for formatting the value
-according the locale's rules. Examples include <code>"en_US"</code> for English
-(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
-locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
-We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
-the locales that are supported.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_currency_1.png' width=100% /></p>
-<p><img src='figures/man_fmt_currency_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># format the `currency` column to have</span>
-<span class='co'># currency values in euros (EUR)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_currency</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"EUR"</span>
-  )
-
-<span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># Keep only the `num` and `currency`,</span>
-<span class='co'># columns, then, format those columns</span>
-<span class='co'># using the "CNY" and "GBP" currencies</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_currency</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"CNY"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_currency</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>currency</span> <span class='kw'>=</span> <span class='st'>"GBP"</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
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-<meta property="og:description" content="Format input date values that are either of the Date type, or, are
-character-based and expressed according to the ISO 8601 date format
-(YYYY-MM-DD). Once the appropriate data cells are targeted with columns
-(and, optionally, rows), we can simply apply a preset date style to format
-the dates. The following date styles are available for simpler formatting of
-ISO dates (all using the input date of 2000-02-29 in the example output
-dates):
-iso: 2000-02-29
-wday_month_day_year: Tuesday, February 29, 2000
-wd_m_day_year: Tue, Feb 29, 2000
-wday_day_month_year: Tuesday 29 February 2000
-month_day_year: February 29, 2000
-m_day_year: Feb 29, 2000
-day_m_year: 29 Feb 2000
-day_month_year: 29 February 2000
-day_month: 29 February
-year: 2000
-month: February
-day: 29
-year.mn.day: 2000/02/29
-y.mn.day: 0/02/29
-We can use the info_date_style() function for a useful reference on all of
-the possible inputs to date_style." />
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-    <h1>Format values as dates</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_date.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Format input date values that are either of the <code>Date</code> type, or, are
-character-based and expressed according to the ISO 8601 date format
-(<code>YYYY-MM-DD</code>). Once the appropriate data cells are targeted with <code>columns</code>
-(and, optionally, <code>rows</code>), we can simply apply a preset date style to format
-the dates. The following date styles are available for simpler formatting of
-ISO dates (all using the input date of <code>2000-02-29</code> in the example output
-dates):</p><ol>
-<li><p>iso: <code>2000-02-29</code></p></li>
-<li><p>wday_month_day_year: <code>Tuesday, February 29, 2000</code></p></li>
-<li><p>wd_m_day_year: <code>Tue, Feb 29, 2000</code></p></li>
-<li><p>wday_day_month_year: <code>Tuesday 29 February 2000</code></p></li>
-<li><p>month_day_year: <code>February 29, 2000</code></p></li>
-<li><p>m_day_year: <code>Feb 29, 2000</code></p></li>
-<li><p>day_m_year: <code>29 Feb 2000</code></p></li>
-<li><p>day_month_year: <code>29 February 2000</code></p></li>
-<li><p>day_month: <code>29 February</code></p></li>
-<li><p>year: <code>2000</code></p></li>
-<li><p>month: <code>February</code></p></li>
-<li><p>day: <code>29</code></p></li>
-<li><p>year.mn.day: <code>2000/02/29</code></p></li>
-<li><p>y.mn.day: <code>0/02/29</code></p></li>
-</ol><p>We can use the <code><a href='info_date_style.html'>info_date_style()</a></code> function for a useful reference on all of
-the possible inputs to <code>date_style</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_date</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>2</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>date_style</th>
-      <td><p>The date style to use. Supply a number (from <code>1</code> to <code>14</code>)
-that corresponds to the preferred date style. Use <code><a href='info_date_style.html'>info_date_style()</a></code> to
-see the different numbered and named date presets.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_date_1.png' width=100% /></p>
-<p><img src='figures/man_fmt_date_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># keep only the `date` and `time` columns;</span>
-<span class='co'># format the `date` column to have</span>
-<span class='co'># dates formatted as `month_day_year`</span>
-<span class='co'># (date style `5`)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_date</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>),
-    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>5</span>
-  )
-
-<span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># keep only the `date` and `time` columns;</span>
-<span class='co'># format the `date` column to have mixed</span>
-<span class='co'># date formats (dates after April will</span>
-<span class='co'># be different than the others)</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_date</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span>
-      <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='no'>date</span>) <span class='kw'>&gt;</span> <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2015-04-01"</span>),
-    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>6</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_date</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>date</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span>
-      <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='no'>date</span>) <span class='kw'>&lt;=</span> <span class='fu'><a href='https://rdrr.io/r/base/as.Date.html'>as.Date</a></span>(<span class='st'>"2015-04-01"</span>),
-    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>7</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
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-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/fmt_datetime.html b/docs/reference/fmt_datetime.html
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-<meta property="og:description" content="Format input date-time values that are character-based and expressed
-according to the ISO 8601 date-time format (YYYY-MM-DD HH:MM:SS). Once the
-appropriate data cells are targeted with columns (and, optionally, rows),
-we can simply apply preset date and time styles to format the date-time
-values. The following date styles are available for simpler formatting of the
-date portion (all using the input date of 2000-02-29 in the example output
-dates):
-iso: 2000-02-29
-wday_month_day_year: Tuesday, February 29, 2000
-wd_m_day_year: Tue, Feb 29, 2000
-wday_day_month_year: Tuesday 29 February 2000
-month_day_year: February 29, 2000
-m_day_year: Feb 29, 2000
-day_m_year: 29 Feb 2000
-day_month_year: 29 February 2000
-day_month: 29 February
-year: 2000
-month: February
-day: 29
-year.mn.day: 2000/02/29
-y.mn.day: 0/02/29
-The following time styles are available for simpler formatting of the time
-portion (all using the input time of 14:35:00 in the example output times):
-hms: 14:35:00
-hm: 14:35
-hms_p: 2:35:00 PM
-hm_p: 2:35 PM
-h_p: 2 PM
-We can use the info_date_style() and info_time_style() functions as
-useful references for all of the possible inputs to date_style and
-time_style." />
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-    <h1>Format values as date-times</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_datetime.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Format input date-time values that are character-based and expressed
-according to the ISO 8601 date-time format (<code>YYYY-MM-DD HH:MM:SS</code>). Once the
-appropriate data cells are targeted with <code>columns</code> (and, optionally, <code>rows</code>),
-we can simply apply preset date and time styles to format the date-time
-values. The following date styles are available for simpler formatting of the
-date portion (all using the input date of <code>2000-02-29</code> in the example output
-dates):</p><ol>
-<li><p>iso: <code>2000-02-29</code></p></li>
-<li><p>wday_month_day_year: <code>Tuesday, February 29, 2000</code></p></li>
-<li><p>wd_m_day_year: <code>Tue, Feb 29, 2000</code></p></li>
-<li><p>wday_day_month_year: <code>Tuesday 29 February 2000</code></p></li>
-<li><p>month_day_year: <code>February 29, 2000</code></p></li>
-<li><p>m_day_year: <code>Feb 29, 2000</code></p></li>
-<li><p>day_m_year: <code>29 Feb 2000</code></p></li>
-<li><p>day_month_year: <code>29 February 2000</code></p></li>
-<li><p>day_month: <code>29 February</code></p></li>
-<li><p>year: <code>2000</code></p></li>
-<li><p>month: <code>February</code></p></li>
-<li><p>day: <code>29</code></p></li>
-<li><p>year.mn.day: <code>2000/02/29</code></p></li>
-<li><p>y.mn.day: <code>0/02/29</code></p></li>
-</ol><p>The following time styles are available for simpler formatting of the time
-portion (all using the input time of <code>14:35:00</code> in the example output times):</p><ol>
-<li><p>hms: <code>14:35:00</code></p></li>
-<li><p>hm: <code>14:35</code></p></li>
-<li><p>hms_p: <code>2:35:00 PM</code></p></li>
-<li><p>hm_p: <code>2:35 PM</code></p></li>
-<li><p>h_p: <code>2 PM</code></p></li>
-</ol><p>We can use the <code><a href='info_date_style.html'>info_date_style()</a></code> and <code><a href='info_time_style.html'>info_time_style()</a></code> functions as
-useful references for all of the possible inputs to <code>date_style</code> and
-<code>time_style</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_datetime</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>2</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>date_style</th>
-      <td><p>The date style to use. Supply a number (from <code>1</code> to <code>14</code>)
-that corresponds to the preferred date style. Use <code><a href='info_date_style.html'>info_date_style()</a></code> to
-see the different numbered and named date presets.</p></td>
-    </tr>
-    <tr>
-      <th>time_style</th>
-      <td><p>The time style to use. Supply a number (from <code>1</code> to <code>5</code>)
-that corresponds to the preferred time style. Use <code><a href='info_time_style.html'>info_time_style()</a></code> to
-see the different numbered and named time presets.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_datetime_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-7</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># keep only the `datetime` column;</span>
-<span class='co'># format the column to have dates</span>
-<span class='co'># formatted as `month_day_year` and</span>
-<span class='co'># times to be `hms_p`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>datetime</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_datetime</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>datetime</span>),
-    <span class='kw'>date_style</span> <span class='kw'>=</span> <span class='fl'>5</span>,
-    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>3</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-    <div class="page-header">
-    <h1>Format Markdown text</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_markdown.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Any Markdown-formatted text in the incoming cells will be transformed to the
-appropriate output type during render when using <code>fmt_markdown()</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_markdown</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_markdown_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-8</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Create a few Markdown-based</span>
-<span class='co'># text snippets</span>
-<span class='no'>text_1a</span> <span class='kw'>&lt;-</span> <span class='st'>"
-### This is Markdown.
-
-Markdown’s syntax is comprised entirely of
-punctuation characters, which punctuation
-characters have been carefully chosen so as
-to look like what they mean... assuming
-you’ve ever used email.
-"</span>
-
-<span class='no'>text_1b</span> <span class='kw'>&lt;-</span> <span class='st'>"
-Info on Markdown syntax can be found
-[here](https://daringfireball.net/projects/markdown/).
-"</span>
-
-<span class='no'>text_2a</span> <span class='kw'>&lt;-</span> <span class='st'>"
-The **gt** package has these datasets:
-
- - `countrypops`
- - `sza`
- - `gtcars`
- - `sp500`
- - `pizzaplace`
- - `exibble`
-"</span>
-
-<span class='no'>text_2b</span> <span class='kw'>&lt;-</span> <span class='st'>"
-There's a quick reference [here](https://commonmark.org/help/).
-"</span>
-
-<span class='co'># Arrange the text snippets as a tibble</span>
-<span class='co'># using the `dplyr::tribble()` function;</span>
-<span class='co'># then, create a gt table and format</span>
-<span class='co'># all columns with `fmt_markdown()`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tribble</a></span>(
-    ~<span class='no'>Markdown</span>, ~<span class='no'>md</span>,
-    <span class='no'>text_1a</span>,   <span class='no'>text_2a</span>,
-    <span class='no'>text_1b</span>,   <span class='no'>text_2b</span>,
-  ) <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-    <span class='fu'>fmt_markdown</span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='tab_options.html'>tab_options</a></span>(<span class='kw'>table.width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>400</span>))</div></pre>
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-</div>
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diff --git a/docs/reference/fmt_missing.html b/docs/reference/fmt_missing.html
deleted file mode 100644
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-<meta property="og:description" content="Wherever there is missing data (i.e., NA values) a customizable mark may
-present better than the standard NA text that would otherwise appear. The
-fmt_missing() function allows for this replacement through its
-missing_text argument (where an em dash serves as the default)." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <div class="page-header">
-    <h1>Format missing values</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_missing.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Wherever there is missing data (i.e., <code>NA</code> values) a customizable mark may
-present better than the standard <code>NA</code> text that would otherwise appear. The
-<code>fmt_missing()</code> function allows for this replacement through its
-<code>missing_text</code> argument (where an em dash serves as the default).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_missing</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"---"</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>missing_text</th>
-      <td><p>The text to be used in place of <code>NA</code> values in the
-rendered table.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_missing_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-10</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># NA values in different columns will</span>
-<span class='co'># be given replacement text</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>row</span>, -<span class='no'>group</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_missing</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>:<span class='fl'>2</span>,
-    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"missing"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_missing</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>4</span>:<span class='fl'>7</span>,
-    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"nothing"</span>
-  )</div></pre>
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-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
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-<meta property="og:title" content="Format numeric values — fmt_number" />
-<meta property="og:description" content="With numeric values in a gt table, we can perform number-based
-formatting so that the targeted values are rendered with a higher
-consideration for tabular presentation. Furthermore, there is finer control
-over numeric formatting with the following options:
-decimals: choice of the number of decimal places, option to drop
-trailing zeros, and a choice of the decimal symbol
-digit grouping separators: options to enable/disable digit separators
-and provide a choice of separator symbol
-scaling: we can choose to scale targeted values by a multiplier value
-large-number suffixing: larger figures (thousands, millions, etc.) can
-be autoscaled and decorated with the appropriate suffixes
-pattern: option to use a text pattern for decoration of the formatted
-values
-locale-based formatting: providing a locale ID will result in number
-formatting specific to the chosen locale
-
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-    <h1>Format numeric values</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_number.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>With numeric values in a <strong>gt</strong> table, we can perform number-based
-formatting so that the targeted values are rendered with a higher
-consideration for tabular presentation. Furthermore, there is finer control
-over numeric formatting with the following options:</p><ul>
-<li><p>decimals: choice of the number of decimal places, option to drop
-trailing zeros, and a choice of the decimal symbol</p></li>
-<li><p>digit grouping separators: options to enable/disable digit separators
-and provide a choice of separator symbol</p></li>
-<li><p>scaling: we can choose to scale targeted values by a multiplier value</p></li>
-<li><p>large-number suffixing: larger figures (thousands, millions, etc.) can
-be autoscaled and decorated with the appropriate suffixes</p></li>
-<li><p>pattern: option to use a text pattern for decoration of the formatted
-values</p></li>
-<li><p>locale-based formatting: providing a locale ID will result in number
-formatting specific to the chosen locale</p></li>
-</ul>
-
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_number</span>(
-  <span class='no'>data</span>,
-  <span class='no'>columns</span>,
-  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
-  <span class='kw'>drop_trailing_zeros</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>,
-  <span class='kw'>suffixing</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
-  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
-  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
-  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>decimals</th>
-      <td><p>An option to specify the exact number of decimal places to
-use. The default number of decimal places is <code>2</code>.</p></td>
-    </tr>
-    <tr>
-      <th>drop_trailing_zeros</th>
-      <td><p>A logical value that allows for removal of
-trailing zeros (those redundant zeros after the decimal mark).</p></td>
-    </tr>
-    <tr>
-      <th>use_seps</th>
-      <td><p>An option to use digit group separators. The type of digit
-group separator is set by <code>sep_mark</code> and overridden if a locale ID is
-provided to <code>locale</code>. This setting is <code>TRUE</code> by default.</p></td>
-    </tr>
-    <tr>
-      <th>scale_by</th>
-      <td><p>A value to scale the input. The default is <code>1.0</code>. All numeric
-values will be multiplied by this value first before undergoing formatting.
-This value will be ignored if using any of the <code>suffixing</code> options (i.e.,
-where <code>suffixing</code> is not set to <code>FALSE</code>).</p></td>
-    </tr>
-    <tr>
-      <th>suffixing</th>
-      <td><p>An option to scale and apply suffixes to larger numbers
-(e.g., <code>1924000</code> can be transformed to <code>1.92M</code>). This option can accept a
-logical value, where <code>FALSE</code> (the default) will not perform this
-transformation and <code>TRUE</code> will apply thousands (<code>K</code>), millions (<code>M</code>),
-billions (<code>B</code>), and trillions (<code>T</code>) suffixes after automatic value scaling.
-We can also specify which symbols to use for each of the value ranges by
-using a character vector of the preferred symbols to replace the defaults
-(e.g., <code><a href='https://rdrr.io/r/base/c.html'>c("k", "Ml", "Bn", "Tr")</a></code>).</p>
-<p>Including <code>NA</code> values in the vector will ensure that the particular range
-will either not be included in the transformation (e.g, <code><a href='https://rdrr.io/r/base/c.html'>c(NA, "M", "B", "T")</a></code> won't modify numbers in the thousands range) or the range will
-inherit a previous suffix (e.g., with <code><a href='https://rdrr.io/r/base/c.html'>c("K", "M", NA, "T")</a></code>, all numbers
-in the range of millions and billions will be in terms of millions).</p>
-<p>Any use of <code>suffixing</code> (where it is not set expressly as <code>FALSE</code>) means
-that any value provided to <code>scale_by</code> will be ignored.</p></td>
-    </tr>
-    <tr>
-      <th>pattern</th>
-      <td><p>A formatting pattern that allows for decoration of the
-formatted value. The value itself is represented by <code>{x}</code> and all other
-characters are taken to be string literals.</p></td>
-    </tr>
-    <tr>
-      <th>sep_mark</th>
-      <td><p>The mark to use as a separator between groups of digits
-(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
-of <code>1,000</code>).</p></td>
-    </tr>
-    <tr>
-      <th>dec_mark</th>
-      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
-    </tr>
-    <tr>
-      <th>locale</th>
-      <td><p>An optional locale ID that can be used for formatting the value
-according the locale's rules. Examples include <code>"en_US"</code> for English
-(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
-locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
-We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
-the locales that are supported.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_number_1.png' width=100% /></p>
-<p><img src='figures/man_fmt_number_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>tidyr</span>)
-
-<span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># format the `num` column as numeric</span>
-<span class='co'># with three decimal places and with no</span>
-<span class='co'># use of digit separators</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_number</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>3</span>,
-    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
-  )
-
-<span class='co'># Use `countrypops` to create a gt</span>
-<span class='co'># table; format all numeric columns</span>
-<span class='co'># to use large-number suffixing</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>countrypops</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>country_code_3</span>, <span class='no'>year</span>, <span class='no'>population</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>country_code_3</span> <span class='kw'>%in%</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(
-      <span class='st'>"CHN"</span>, <span class='st'>"IND"</span>, <span class='st'>"USA"</span>, <span class='st'>"PAK"</span>, <span class='st'>"IDN"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>year</span> <span class='kw'>&gt;</span> <span class='fl'>1975</span> <span class='kw'>&amp;</span> <span class='no'>year</span> <span class='kw'>%%</span> <span class='fl'>5</span> <span class='kw'>==</span> <span class='fl'>0</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>tidyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://tidyr.tidyverse.org/reference/spread.html'>spread</a></span>(<span class='no'>year</span>, <span class='no'>population</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='fu'>desc</span>(<span class='no'>`2015`</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"country_code_3"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_number</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>2</span>:<span class='fl'>9</span>,
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
-    <span class='kw'>suffixing</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>
-  )</div></pre>
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-text via the pattern argument (the default is to apply nothing). All of
-this is useful when don't want to modify the input data other than to
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-    <h1>Format by simply passing data through</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_passthrough.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Format by passing data through no other transformation other than: (1)
-coercing to <code>character</code> (as all the <code>fmt_*()</code> functions do), and (2) applying
-text via the <code>pattern</code> argument (the default is to apply nothing). All of
-this is useful when don't want to modify the input data other than to
-decorate it within a pattern. Also, this function is useful when used as the
-<code>formatter</code> function in the <code><a href='summary_rows.html'>summary_rows()</a></code> function, where the output may
-be text or useful as is.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_passthrough</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>escape</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>escape</th>
-      <td><p>An option to escape text according to the final output format
-of the table. For example, if a LaTeX table is to be generated then LaTeX
-escaping would be performed during rendering. By default this is set to
-<code>TRUE</code> and setting to <code>FALSE</code> is useful in the case where LaTeX-formatted
-text should be passed through to the output LaTeX table unchanged.</p></td>
-    </tr>
-    <tr>
-      <th>pattern</th>
-      <td><p>A formatting pattern that allows for decoration of the
-formatted value. The value itself is represented by <code>{x}</code> and all other
-characters are taken to be string literals.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_passthrough_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-9</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># keep only the `char` column;</span>
-<span class='co'># pass the data in that column through</span>
-<span class='co'># but apply a simple pattern that adds</span>
-<span class='co'># an 's' to the non-NA values</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>char</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_passthrough</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>char</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span> !<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>char</span>),
-    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}s"</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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diff --git a/docs/reference/fmt_percent.html b/docs/reference/fmt_percent.html
deleted file mode 100644
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--- a/docs/reference/fmt_percent.html
+++ /dev/null
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-<meta property="og:description" content="With numeric values in a gt table, we can perform percentage-based
-formatting. It is assumed the input numeric values are in a fractional format
-since the numbers will be automatically multiplied by 100 before decorating
-with a percent sign. For more control over percentage formatting, we can use
-the following options:
-percent sign placement: the percent sign can be placed after or
-before the values and a space can be inserted between the symbol and the
-value.
-decimals: choice of the number of decimal places, option to drop
-trailing zeros, and a choice of the decimal symbol
-digit grouping separators: options to enable/disable digit separators
-and provide a choice of separator symbol
-pattern: option to use a text pattern for decoration of the formatted
-values
-locale-based formatting: providing a locale ID will result in number
-formatting specific to the chosen locale
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-    <div class="page-header">
-    <h1>Format values as a percentage</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_percent.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>With numeric values in a <strong>gt</strong> table, we can perform percentage-based
-formatting. It is assumed the input numeric values are in a fractional format
-since the numbers will be automatically multiplied by <code>100</code> before decorating
-with a percent sign. For more control over percentage formatting, we can use
-the following options:</p><ul>
-<li><p>percent sign placement: the percent sign can be placed after or
-before the values and a space can be inserted between the symbol and the
-value.</p></li>
-<li><p>decimals: choice of the number of decimal places, option to drop
-trailing zeros, and a choice of the decimal symbol</p></li>
-<li><p>digit grouping separators: options to enable/disable digit separators
-and provide a choice of separator symbol</p></li>
-<li><p>pattern: option to use a text pattern for decoration of the formatted
-values</p></li>
-<li><p>locale-based formatting: providing a locale ID will result in number
-formatting specific to the chosen locale</p></li>
-</ul>
-
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_percent</span>(
-  <span class='no'>data</span>,
-  <span class='no'>columns</span>,
-  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
-  <span class='kw'>drop_trailing_zeros</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
-  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
-  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
-  <span class='kw'>incl_space</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>placement</span> <span class='kw'>=</span> <span class='st'>"right"</span>,
-  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>decimals</th>
-      <td><p>An option to specify the exact number of decimal places to
-use. The default number of decimal places is <code>2</code>.</p></td>
-    </tr>
-    <tr>
-      <th>drop_trailing_zeros</th>
-      <td><p>A logical value that allows for removal of
-trailing zeros (those redundant zeros after the decimal mark).</p></td>
-    </tr>
-    <tr>
-      <th>use_seps</th>
-      <td><p>An option to use digit group separators. The type of digit
-group separator is set by <code>sep_mark</code> and overridden if a locale ID is
-provided to <code>locale</code>. This setting is <code>TRUE</code> by default.</p></td>
-    </tr>
-    <tr>
-      <th>pattern</th>
-      <td><p>A formatting pattern that allows for decoration of the
-formatted value. The value itself is represented by <code>{x}</code> and all other
-characters are taken to be string literals.</p></td>
-    </tr>
-    <tr>
-      <th>sep_mark</th>
-      <td><p>The mark to use as a separator between groups of digits
-(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
-of <code>1,000</code>).</p></td>
-    </tr>
-    <tr>
-      <th>dec_mark</th>
-      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
-    </tr>
-    <tr>
-      <th>incl_space</th>
-      <td><p>An option for whether to include a space between the value
-and the percent sign. The default is to not introduce a space character.</p></td>
-    </tr>
-    <tr>
-      <th>placement</th>
-      <td><p>The placement of the percent sign. This can be either be
-<code>right</code> (the default) or <code>left</code>.</p></td>
-    </tr>
-    <tr>
-      <th>locale</th>
-      <td><p>An optional locale ID that can be used for formatting the value
-according the locale's rules. Examples include <code>"en_US"</code> for English
-(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
-locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
-We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
-the locales that are supported.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_percent_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `pizzaplace` to create a gt table;</span>
-<span class='co'># format the `frac_of_quota` column to</span>
-<span class='co'># display values as percentages</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>pizzaplace</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>month</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/substr.html'>substr</a></span>(<span class='no'>date</span>, <span class='fl'>6</span>, <span class='fl'>7</span>))) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>month</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(<span class='kw'>pizzas_sold</span> <span class='kw'>=</span> <span class='fu'>n</span>()) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>ungroup</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>frac_of_quota</span> <span class='kw'>=</span> <span class='no'>pizzas_sold</span> / <span class='fl'>4000</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"month"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_percent</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>frac_of_quota</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
-  )</div><div class='output co'>#&gt; <span class='error'>Error: `summarise()` argument `pizzas_sold` errored.</span>
-#&gt; <span class='error'><span style='color: #0000BB;'>ℹ</span><span> `pizzas_sold` is `n()`.</span>
-#&gt; <span class='error'></span><span style='color: #0000BB;'>ℹ</span><span> The error occured in group 1: month = 1.</span>
-#&gt; <span class='error'></span><span style='color: #BB0000;'>x</span><span> could not find function "n"</span></div><div class='input'>
-</div></span></pre>
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diff --git a/docs/reference/fmt_scientific.html b/docs/reference/fmt_scientific.html
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-<meta property="og:description" content="With numeric values in a gt table, we can perform formatting so that the
-targeted values are rendered in scientific notation. Furthermore, there is
-fine control with the following options:
-decimals: choice of the number of decimal places, option to drop
-trailing zeros, and a choice of the decimal symbol
-scaling: we can choose to scale targeted values by a multiplier value
-pattern: option to use a text pattern for decoration of the formatted
-values
-locale-based formatting: providing a locale ID will result in
-formatting specific to the chosen locale
-
-" />
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-    <h1>Format values to scientific notation</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_scientific.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>With numeric values in a <strong>gt</strong> table, we can perform formatting so that the
-targeted values are rendered in scientific notation. Furthermore, there is
-fine control with the following options:</p><ul>
-<li><p>decimals: choice of the number of decimal places, option to drop
-trailing zeros, and a choice of the decimal symbol</p></li>
-<li><p>scaling: we can choose to scale targeted values by a multiplier value</p></li>
-<li><p>pattern: option to use a text pattern for decoration of the formatted
-values</p></li>
-<li><p>locale-based formatting: providing a locale ID will result in
-formatting specific to the chosen locale</p></li>
-</ul>
-
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_scientific</span>(
-  <span class='no'>data</span>,
-  <span class='no'>columns</span>,
-  <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>,
-  <span class='kw'>drop_trailing_zeros</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>,
-  <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}"</span>,
-  <span class='kw'>sep_mark</span> <span class='kw'>=</span> <span class='st'>","</span>,
-  <span class='kw'>dec_mark</span> <span class='kw'>=</span> <span class='st'>"."</span>,
-  <span class='kw'>locale</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>decimals</th>
-      <td><p>An option to specify the exact number of decimal places to
-use. The default number of decimal places is <code>2</code>.</p></td>
-    </tr>
-    <tr>
-      <th>drop_trailing_zeros</th>
-      <td><p>A logical value that allows for removal of
-trailing zeros (those redundant zeros after the decimal mark).</p></td>
-    </tr>
-    <tr>
-      <th>scale_by</th>
-      <td><p>A value to scale the input. The default is <code>1.0</code>. All numeric
-values will be multiplied by this value first before undergoing formatting.
-This value will be ignored if using any of the <code>suffixing</code> options (i.e.,
-where <code>suffixing</code> is not set to <code>FALSE</code>).</p></td>
-    </tr>
-    <tr>
-      <th>pattern</th>
-      <td><p>A formatting pattern that allows for decoration of the
-formatted value. The value itself is represented by <code>{x}</code> and all other
-characters are taken to be string literals.</p></td>
-    </tr>
-    <tr>
-      <th>sep_mark</th>
-      <td><p>The mark to use as a separator between groups of digits
-(e.g., using <code>sep_mark = ","</code> with <code>1000</code> would result in a formatted value
-of <code>1,000</code>).</p></td>
-    </tr>
-    <tr>
-      <th>dec_mark</th>
-      <td><p>The character to use as a decimal mark (e.g., using <code>dec_mark = ","</code> with <code>0.152</code> would result in a formatted value of <code>0,152</code>).</p></td>
-    </tr>
-    <tr>
-      <th>locale</th>
-      <td><p>An optional locale ID that can be used for formatting the value
-according the locale's rules. Examples include <code>"en_US"</code> for English
-(United States) and <code>"fr_FR"</code> for French (France). The use of a valid
-locale ID will override any values provided in <code>sep_mark</code> and <code>dec_mark</code>.
-We can use the <code><a href='info_locales.html'>info_locales()</a></code> function as a useful reference for all of
-the locales that are supported.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_scientific_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># format the `num` column as partially</span>
-<span class='co'># numeric and partially in scientific</span>
-<span class='co'># notation</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;</span> <span class='fl'>500</span>,
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>,
-    <span class='kw'>scale_by</span> <span class='kw'>=</span> <span class='fl'>1</span>/<span class='fl'>1000</span>,
-    <span class='kw'>pattern</span> <span class='kw'>=</span> <span class='st'>"{x}K"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_scientific</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&lt;=</span> <span class='fl'>500</span>,
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
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-<meta property="og:description" content="Format input time values that are character-based and expressed according to
-the ISO 8601 time format (HH:MM:SS). Once the appropriate data cells are
-targeted with columns (and, optionally, rows), we can simply apply a
-preset time style to format the times. The following time styles are
-available for simpler formatting of ISO times (all using the input time of
-14:35:00 in the example output times):
-hms: 14:35:00
-hm: 14:35
-hms_p: 2:35:00 PM
-hm_p: 2:35 PM
-h_p: 2 PM
-We can use the info_time_style() function for a useful reference on all of
-the possible inputs to time_style." />
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-    <div class="page-header">
-    <h1>Format values as times</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/format_data.R'><code>R/format_data.R</code></a></small>
-    <div class="hidden name"><code>fmt_time.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Format input time values that are character-based and expressed according to
-the ISO 8601 time format (<code>HH:MM:SS</code>). Once the appropriate data cells are
-targeted with <code>columns</code> (and, optionally, <code>rows</code>), we can simply apply a
-preset time style to format the times. The following time styles are
-available for simpler formatting of ISO times (all using the input time of
-<code>14:35:00</code> in the example output times):</p><ol>
-<li><p>hms: <code>14:35:00</code></p></li>
-<li><p>hm: <code>14:35</code></p></li>
-<li><p>hms_p: <code>2:35:00 PM</code></p></li>
-<li><p>hm_p: <code>2:35 PM</code></p></li>
-<li><p>h_p: <code>2 PM</code></p></li>
-</ol><p>We can use the <code><a href='info_time_style.html'>info_time_style()</a></code> function for a useful reference on all of
-the possible inputs to <code>time_style</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>fmt_time</span>(<span class='no'>data</span>, <span class='no'>columns</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>2</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to format. Can either be a series of column names
-provided in <code><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars()</a></code>, a vector of column indices, or a helper function
-focused on selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>Optional rows to format. Not providing any value results in all
-rows in <code>columns</code> being formatted. Can either be a vector of row captions
-provided <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a helper function focused on
-selections. The select helper functions are: <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>,
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.
-We can also use expressions to filter down to the rows we need (e.g.,
-<code>[colname_1] &gt; 100 &amp; [colname_2] &lt; 50</code>).</p></td>
-    </tr>
-    <tr>
-      <th>time_style</th>
-      <td><p>The time style to use. Supply a number (from <code>1</code> to <code>5</code>)
-that corresponds to the preferred time style. Use <code><a href='info_time_style.html'>info_time_style()</a></code> to
-see the different numbered and named time presets.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Targeting of values is done through <code>columns</code> and additionally by <code>rows</code> (if
-nothing is provided for <code>rows</code> then entire columns are selected). A number of
-helper functions exist to make targeting more effective. Conditional
-formatting is possible by providing a conditional expression to the <code>rows</code>
-argument. See the Arguments section for more information on this.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_fmt_time_1.png' width=100% /></p>
-<p><img src='figures/man_fmt_time_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-6</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code>,
-<code><a href='text_transform.html'>text_transform</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># keep only the `date` and `time` columns;</span>
-<span class='co'># format the `time` column to have</span>
-<span class='co'># times formatted as `hms_p`</span>
-<span class='co'># (time style `3`)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_time</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>time</span>),
-    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>3</span>
-  )
-
-<span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># keep only the `date` and `time` columns;</span>
-<span class='co'># format the `time` column to have mixed</span>
-<span class='co'># time formats (times after 16:00 will</span>
-<span class='co'># be different than the others)</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>date</span>, <span class='no'>time</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_time</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>time</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span>
-      <span class='no'>time</span> <span class='kw'>&gt;</span> <span class='st'>"16:00"</span>,
-    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>3</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>fmt_time</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>time</span>),
-    <span class='kw'>rows</span> <span class='kw'>=</span>
-      <span class='no'>time</span> <span class='kw'>&lt;=</span> <span class='st'>"16:00"</span>,
-    <span class='kw'>time_style</span> <span class='kw'>=</span> <span class='fl'>4</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/ggplot_image.html b/docs/reference/ggplot_image.html
deleted file mode 100644
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--- a/docs/reference/ggplot_image.html
+++ /dev/null
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-<meta property="og:description" content="We can add a ggplot2 plot inside of a table with the help of the
-ggplot_image() function. The function provides a convenient way to generate
-an HTML fragment with a ggplot object. Because this function is currently
-HTML-based, it is only useful for HTML table output. To use this function
-inside of data cells, it is recommended that the text_transform() function
-is used. With that function, we can specify which data cells to target and
-then include a call to ggplot_image() within the required user-defined
-function (for the fn argument). If we want to include a plot in other
-places (e.g., in the header, within footnote text, etc.) we need to use
-ggplot_image() within the html() helper function." />
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-    <div class="page-header">
-    <h1>Helper function for adding a ggplot</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
-    <div class="hidden name"><code>ggplot_image.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>We can add a <strong>ggplot2</strong> plot inside of a table with the help of the
-<code>ggplot_image()</code> function. The function provides a convenient way to generate
-an HTML fragment with a <code>ggplot</code> object. Because this function is currently
-HTML-based, it is only useful for HTML table output. To use this function
-inside of data cells, it is recommended that the <code><a href='text_transform.html'>text_transform()</a></code> function
-is used. With that function, we can specify which data cells to target and
-then include a call to <code>ggplot_image()</code> within the required user-defined
-function (for the <code>fn</code> argument). If we want to include a plot in other
-places (e.g., in the header, within footnote text, etc.) we need to use
-<code>ggplot_image()</code> within the <code><a href='html.html'>html()</a></code> helper function.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>ggplot_image</span>(<span class='no'>plot_object</span>, <span class='kw'>height</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>aspect_ratio</span> <span class='kw'>=</span> <span class='fl'>1</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>plot_object</th>
-      <td><p>A ggplot plot object.</p></td>
-    </tr>
-    <tr>
-      <th>height</th>
-      <td><p>The absolute height (px) of the image in the table cell.</p></td>
-    </tr>
-    <tr>
-      <th>aspect_ratio</th>
-      <td><p>The plot's final aspect ratio. Where the height of the
-plot is fixed using the <code>height</code> argument, the <code>aspect_ratio</code>
-will either compress (<code>aspect_ratio</code> &lt; <code>1.0</code>) or expand
-(<code>aspect_ratio</code> &gt; <code>1.0</code>) the plot horizontally. The default value
-of <code>1.0</code> will neither compress nor expand the plot.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character object with an HTML fragment that can be placed inside of
-a cell.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>By itself, the function creates an HTML image tag with an image URI embedded
-within (a 100 dpi PNG). We can easily experiment with any <code>ggplot2</code> plot
-object, and using it within <code>ggplot_image(plot_object = &lt;plot object&gt;</code>
-evaluates to:</p>
-<p><code>&lt;img cid=&lt;random CID&gt; src=&lt;data URI&gt; style=\"height:100px;\"&gt;</code></p>
-<p>where a height of <code>100px</code> is a default height chosen to work well within the
-heights of most table rows. There is the option to modify the aspect ratio of
-the plot (the default <code>aspect_ratio</code> is <code>1.0</code>) and this is useful for
-elongating any given plot to fit better within the table construct.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_ggplot_image_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>8-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Image Addition Functions: 
-<code><a href='local_image.html'>local_image</a>()</code>,
-<code><a href='test_image.html'>test_image</a>()</code>,
-<code><a href='web_image.html'>web_image</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>ggplot2</span>)
-
-<span class='co'># Create a ggplot plot</span>
-<span class='no'>plot_object</span> <span class='kw'>&lt;-</span>
-  <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(
-    <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>gtcars</span>,
-    <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>hp</span>, <span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>trq</span>,
-        <span class='kw'>size</span> <span class='kw'>=</span> <span class='no'>msrp</span>)) +
-  <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_point.html'>geom_point</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"blue"</span>) +
-  <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/theme.html'>theme</a></span>(<span class='kw'>legend.position</span> <span class='kw'>=</span> <span class='st'>"none"</span>)
-
-<span class='co'># Create a tibble that contains two</span>
-<span class='co'># cells (where one is a placeholder for</span>
-<span class='co'># an image), then, create a gt table;</span>
-<span class='co'># use the `text_transform()` function</span>
-<span class='co'># to insert the plot using by calling</span>
-<span class='co'># `ggplot_object()` within the user-</span>
-<span class='co'># defined function</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
-    <span class='kw'>text</span> <span class='kw'>=</span> <span class='st'>"Here is a ggplot:"</span>,
-    <span class='kw'>ggplot</span> <span class='kw'>=</span> <span class='fl'>NA</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='text_transform.html'>text_transform</a></span>(
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>ggplot</span>)),
-    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
-      <span class='no'>plot_object</span> <span class='kw'>%&gt;%</span>
-        <span class='fu'>ggplot_image</span>(<span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>200</span>))
-    }
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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diff --git a/docs/reference/grand_summary_rows.html b/docs/reference/grand_summary_rows.html
deleted file mode 100644
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+++ /dev/null
@@ -1,289 +0,0 @@
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-<meta property="og:description" content="Add grand summary rows to the gt table by using applying aggregation
-functions to the table data. The summary rows incorporate all of the
-available data, regardless of whether some of the data are part of row
-groups. You choose how to format the values in the resulting summary cells by
-use of a formatter function (e.g, fmt_number) and any relevant options." />
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-    <h1>Add grand summary rows using aggregation functions</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/summary_rows.R'><code>R/summary_rows.R</code></a></small>
-    <div class="hidden name"><code>grand_summary_rows.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Add grand summary rows to the <strong>gt</strong> table by using applying aggregation
-functions to the table data. The summary rows incorporate all of the
-available data, regardless of whether some of the data are part of row
-groups. You choose how to format the values in the resulting summary cells by
-use of a <code>formatter</code> function (e.g, <code>fmt_number</code>) and any relevant options.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>grand_summary_rows</span>(
-  <span class='no'>data</span>,
-  <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='no'>fns</span>,
-  <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"---"</span>,
-  <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-  <span class='no'>...</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns for which the summaries should be calculated.</p></td>
-    </tr>
-    <tr>
-      <th>fns</th>
-      <td><p>Functions used for aggregations. This can include base functions
-like <code>mean</code>, <code>min</code>, <code>max</code>, <code>median</code>, <code>sd</code>, or <code>sum</code> or any other
-user-defined aggregation function. The function(s) should be supplied
-within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. Within that list, we can specify the functions by use of
-function names in quotes (e.g., <code>"sum"</code>), as bare functions (e.g., <code>sum</code>),
-or as one-sided R formulas using a leading <code>~</code>. In the formula
-representation, a <code>.</code> serves as the data to be summarized (e.g., <code><a href='https://rdrr.io/r/base/sum.html'>sum(., na.rm = TRUE)</a></code>). The use of named arguments is recommended as the names
-will serve as summary row labels for the corresponding summary rows data
-(the labels can derived from the function names but only when not providing
-bare function names).</p></td>
-    </tr>
-    <tr>
-      <th>missing_text</th>
-      <td><p>The text to be used in place of <code>NA</code> values in summary
-cells with no data outputs.</p></td>
-    </tr>
-    <tr>
-      <th>formatter</th>
-      <td><p>A formatter function name. These can be any of the <code>fmt_*()</code>
-functions available in the package (e.g., <code><a href='fmt_number.html'>fmt_number()</a></code>, <code><a href='fmt_percent.html'>fmt_percent()</a></code>,
-etc.), or a custom function using <code><a href='fmt.html'>fmt()</a></code>. The default function is
-<code><a href='fmt_number.html'>fmt_number()</a></code> and its options can be accessed through <code>...</code>.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>Values passed to the <code>formatter</code> function, where the provided
-values are to be in the form of named vectors. For example, when using the
-default <code>formatter</code> function, <code><a href='fmt_number.html'>fmt_number()</a></code>, options such as <code>decimals</code>,
-<code>use_seps</code>, and <code>locale</code> can be used.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Should we need to obtain the summary data for external purposes, the
-<code><a href='extract_summary.html'>extract_summary()</a></code> function can be used with a <code>gt_tbl</code> object where grand
-summary rows were added via <code>grand_summary_rows()</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_grand_summary_rows_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>6-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Add Rows: 
-<code><a href='summary_rows.html'>summary_rows</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table with</span>
-<span class='co'># row groups; create grand summary rows</span>
-<span class='co'># (`min`, `max`, `avg`) for the table</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
-      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-16"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='no'>date</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
-    <span class='kw'>week</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
-      <span class='st'>"W"</span>, <span class='fu'><a href='https://rdrr.io/r/base/strptime.html'>strftime</a></span>(<span class='no'>date</span>, <span class='kw'>format</span> <span class='kw'>=</span> <span class='st'>"%V"</span>))
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>adj_close</span>, -<span class='no'>volume</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(
-    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
-    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"week"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>grand_summary_rows</span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>high</span>, <span class='no'>low</span>, <span class='no'>close</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>),
-      <span class='kw'>avg</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/mean.html'>mean</a></span>(<span class='no'>.</span>)),
-    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
-  )</div></pre>
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/zzz.R'><code>R/zzz.R</code></a></small>
-    <div class="hidden name"><code>gt-options.Rd</code></div>
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-    <p><strong>gt</strong> package options</p>
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-
-    
-
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-<p><strong>gt</strong> uses the following <code><a href='https://rdrr.io/r/base/options.html'>options()</a></code> to configure behavior:</p><ul>
-<li><p><code>gt.row_group.sep</code>: a separator between groups for the row group
-label.</p></li>
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/gt-package.R'><code>R/gt-package.R</code></a></small>
-    <div class="hidden name"><code>gt-package.Rd</code></div>
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-    <p>Build display tables from tabular data using with an easy-to-use
-    API. With its progressive approach, we can construct display tables with a
-    clear separation of concerns: you don't have to decide how the tabular data
-    gets transformed and structured whilst also worrying about aesthetics.</p>
-    </div>
-
-
-
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Useful links:</p><ul>
-<li><p><a href='https://github.com/rstudio/gt'>https://github.com/rstudio/gt</a></p></li>
-<li><p>Report bugs at <a href='https://github.com/rstudio/gt/issues'>https://github.com/rstudio/gt/issues</a></p></li>
-</ul>
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-      <a href="../articles/gt-datasets.html">gt Datasets</a>
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-      <a href="../articles/creating-summary-lines.html">Summary Lines</a>
-    </li>
-    <li class="dropdown-header">Case Studies</li>
-    <li>
-      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
-    </li>
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-  <a href="../news/index.html">News</a>
-</li>
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-    <div class="page-header">
-    <h1>Create a <strong>gt</strong> table object</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/gt.R'><code>R/gt.R</code></a></small>
-    <div class="hidden name"><code>gt.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>gt()</code> function creates a <strong>gt</strong> table object when provided with table
-data. Using this function is the first step in a typical <strong>gt</strong> workflow.
-Once we have the <strong>gt</strong> table object, we can perform styling transformations
-before rendering to a display table of various formats.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>gt</span>(
-  <span class='no'>data</span>,
-  <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"rowname"</span>,
-  <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_data.html'>group_vars</a></span>(<span class='no'>data</span>),
-  <span class='kw'>rownames_to_stub</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>auto_align</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.sep</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span>(<span class='st'>"gt.row_group.sep"</span>, <span class='st'>" - "</span>)
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A <code>data.frame</code> object or a tibble.</p></td>
-    </tr>
-    <tr>
-      <th>rowname_col</th>
-      <td><p>The column name in the input <code>data</code> table to use as row
-captions to be placed in the display table stub. If the <code>rownames_to_stub</code>
-option is <code>TRUE</code> then any column name provided to <code>rowname_col</code> will be
-ignored.</p></td>
-    </tr>
-    <tr>
-      <th>groupname_col</th>
-      <td><p>The column name in the input <code>data</code> table to use as
-group labels for generation of stub row groups. If the input <code>data</code> table
-has the <code>grouped_df</code> class (through use of the <code><a href='https://dplyr.tidyverse.org/reference/group_by.html'>dplyr::group_by()</a></code> function
-or associated <code>group_by*()</code> functions) then any input here is ignored.</p></td>
-    </tr>
-    <tr>
-      <th>rownames_to_stub</th>
-      <td><p>An option to take rownames from the input <code>data</code>
-table as row captions in the display table stub.</p></td>
-    </tr>
-    <tr>
-      <th>auto_align</th>
-      <td><p>Optionally have column data be aligned depending on the
-content contained in each column of the input <code>data</code>. Internally, this
-calls <code><a href='cols_align.html'>cols_align(align = "auto")</a></code> for all columns.</p></td>
-    </tr>
-    <tr>
-      <th>id</th>
-      <td><p>The table ID. By default, with <code>NULL</code>, this will be a random,
-ten-letter ID as generated by using the <code><a href='random_id.html'>random_id()</a></code> function. A custom
-table ID can be used with any single-length character vector.</p></td>
-    </tr>
-    <tr>
-      <th>row_group.sep</th>
-      <td><p>The separator to use between consecutive group names (a
-possibility when providing <code>data</code> as a <code>grouped_df</code> with multiple groups)
-in the displayed stub row group label.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>There are a few data ingest options we can consider at this stage. We can
-choose to create a table stub with rowname captions using the <code>rowname_col</code>
-argument. Further to this, stub row groups can be created with the
-<code>groupname_col</code>. Both arguments take the name of a column in the input table
-data. Typically, the data in the <code>groupname_col</code> will consist of categories
-of data in a table and the data in the <code>rowname_col</code> are unique labels
-(perhaps unique across the entire table or unique within groups).</p>
-<p>Row groups can also be created by passing a <code>grouped_df</code> to <code>gt()</code> by using
-the <code><a href='https://dplyr.tidyverse.org/reference/group_by.html'>dplyr::group_by()</a></code> function on the table data. In this way, two or more
-columns of categorical data can be used to make row groups. The
-<code>row_group.sep</code> argument allows for control in how the row group label will
-appear in the display table.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_gt_1.png' width=100% /></p>
-<p><img src='figures/man_gt_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>1-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create Table: 
-<code><a href='gt_preview.html'>gt_preview</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Create a table object using the</span>
-<span class='co'># `exibble` dataset; use the `row`</span>
-<span class='co'># and `group` columns to add a stub</span>
-<span class='co'># and row groups</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>gt</span>(
-    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>,
-    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>
-  )
-
-<span class='co'># The resulting object can be used</span>
-<span class='co'># in transformations (with `tab_*()`,</span>
-<span class='co'># `fmt_*()`, `cols_*()` functions)</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"Table Title"</span>,
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"Subtitle"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>2</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='cols_label.html'>cols_label</a></span>(<span class='kw'>num</span> <span class='kw'>=</span> <span class='st'>"number"</span>)</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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diff --git a/docs/reference/gt_latex_dependencies.html b/docs/reference/gt_latex_dependencies.html
deleted file mode 100644
index 96f0e3559..000000000
--- a/docs/reference/gt_latex_dependencies.html
+++ /dev/null
@@ -1,249 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
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-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
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-<title>Get the LaTeX dependencies required for a <strong>gt</strong> table — gt_latex_dependencies • gt</title>
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-<meta property="og:description" content="When working with Rnw (Sweave) files or otherwise writing LaTeX code,
-including a gt table can be problematic if we don't have knowledge
-of the LaTeX dependencies. For the most part, these dependencies are the
-LaTeX packages that are required for rendering a gt table. The
-gt_latex_dependencies() function provides an object that can be
-used to provide the LaTeX in an Rnw file, allowing gt tables to work
-and not yield errors due to missing packages." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
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-
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-      <ul class="nav navbar-nav">
-        <li>
-  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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-</li>
-<li class="dropdown">
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-    Articles
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-    <li class="dropdown-header">How to Use</li>
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-      <a href="../articles/gt-datasets.html">gt Datasets</a>
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-    </li>
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-</li>
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-        <li>
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-      
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-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Get the LaTeX dependencies required for a <strong>gt</strong> table</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>gt_latex_dependencies.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>When working with Rnw (Sweave) files or otherwise writing LaTeX code,
-including a <strong>gt</strong> table can be problematic if we don't have knowledge
-of the LaTeX dependencies. For the most part, these dependencies are the
-LaTeX packages that are required for rendering a <strong>gt</strong> table. The
-<code>gt_latex_dependencies()</code> function provides an object that can be
-used to provide the LaTeX in an Rnw file, allowing <strong>gt</strong> tables to work
-and not yield errors due to missing packages.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>gt_latex_dependencies</span>()</pre>
-
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>knit_asis</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Here is an example Rnw document that shows how the
-<code>gt_latex_dependencies()</code> can be used in conjunction with a <strong>gt</strong>
-table:</p>
-<pre>
-%!sweave=knitr
-
-\documentclass{article}
-
-&lt;&lt;echo=FALSE&gt;&gt;=
-library(gt)
- @
-
-&lt;&lt;results='asis', echo=FALSE&gt;&gt;=
-gt_latex_dependencies()
- @
-
-\begin{document}
-
-&lt;&lt;results='asis', echo=FALSE&gt;&gt;=
-exibble <!-- %&gt;% gt() -->
- @
-
-\end{document}
-</pre>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-21</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
-
-<div class="pkgdown">
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diff --git a/docs/reference/gt_output.html b/docs/reference/gt_output.html
deleted file mode 100644
index 25f3e0331..000000000
--- a/docs/reference/gt_output.html
+++ /dev/null
@@ -1,251 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
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-<title>Create a <strong>gt</strong> display table output element for Shiny — gt_output • gt</title>
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-<meta property="og:description" content="Using gt_output() we can render a reactive gt table, a process
-initiated by using the render_gt() function in the server component of a
-Shiny app. The gt_output() call is to be used in the Shiny ui component,
-the position and context wherein this call is made determines the where the
-gt table is rendered on the app page. It's important to note that the
-ID given during the render_gt() call is needed as the outputId in
-gt_output() (e.g., server: output$&amp;lt;id&amp;gt; &amp;lt;- render_gt(...); ui:
-gt_output(outputId = &quot;&amp;lt;id&amp;gt;&quot;)." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
-
-
-
-<!-- mathjax -->
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script>
-
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-<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
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-    <div class="page-header">
-    <h1>Create a <strong>gt</strong> display table output element for Shiny</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/shiny.R'><code>R/shiny.R</code></a></small>
-    <div class="hidden name"><code>gt_output.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Using <code>gt_output()</code> we can render a reactive <strong>gt</strong> table, a process
-initiated by using the <code><a href='render_gt.html'>render_gt()</a></code> function in the <code>server</code> component of a
-Shiny app. The <code>gt_output()</code> call is to be used in the Shiny <code>ui</code> component,
-the position and context wherein this call is made determines the where the
-<strong>gt</strong> table is rendered on the app page. It's important to note that the
-ID given during the <code><a href='render_gt.html'>render_gt()</a></code> call is needed as the <code>outputId</code> in
-<code>gt_output()</code> (e.g., <strong>server</strong>: <code>output$&lt;id&gt; &lt;- render_gt(...)</code>; <strong>ui</strong>:
-<code>gt_output(outputId = "&lt;id&gt;"</code>).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>gt_output</span>(<span class='no'>outputId</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>outputId</th>
-      <td><p>An output variable from which to read the table.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>We need to ensure that we have the <strong>shiny</strong> package installed first. This
-is easily by using <code><a href='https://rdrr.io/r/utils/install.packages.html'>install.packages("shiny")</a></code>. More information on creating
-Shiny apps can be found at the <a href='https://shiny.rstudio.com'>Shiny Site</a>.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>12-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Shiny functions: 
-<code><a href='render_gt.html'>render_gt</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>shiny</span>)
-
-<span class='co'># Here is a Shiny app (contained within</span>
-<span class='co'># a single file) that (1) prepares a</span>
-<span class='co'># gt table, (2) sets up the `ui` with</span>
-<span class='co'># `gt_output()`, and (3) sets up the</span>
-<span class='co'># `server` with a `render_gt()` that</span>
-<span class='co'># uses the `gt_tbl` object as the input</span>
-<span class='co'># expression</span>
-
-<span class='no'>gt_tbl</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='cols_hide.html'>cols_hide</a></span>(<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"_"</span>))
-
-<span class='no'>ui</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/fluidPage.html'>fluidPage</a></span>(
-
-  <span class='fu'>gt_output</span>(<span class='kw'>outputId</span> <span class='kw'>=</span> <span class='st'>"table"</span>)
-)
-
-<span class='no'>server</span> <span class='kw'>&lt;-</span> <span class='kw'>function</span>(<span class='no'>input</span>,
-                   <span class='no'>output</span>,
-                   <span class='no'>session</span>) {
-
-  <span class='no'>output</span>$<span class='no'>table</span> <span class='kw'>&lt;-</span>
-    <span class='fu'><a href='render_gt.html'>render_gt</a></span>(
-      <span class='kw'>expr</span> <span class='kw'>=</span> <span class='no'>gt_tbl</span>,
-      <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>),
-      <span class='kw'>width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>)
-    )
-}
-
-<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span>()) {
-  <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/shinyApp.html'>shinyApp</a></span>(<span class='no'>ui</span>, <span class='no'>server</span>)
-}</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/gt_preview.html b/docs/reference/gt_preview.html
deleted file mode 100644
index 3f8ded0aa..000000000
--- a/docs/reference/gt_preview.html
+++ /dev/null
@@ -1,247 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<meta property="og:description" content="Sometimes you may want to see just a small portion of your input data. We can
-use gt_preview() in place of gt() to get the first x rows of data and the
-last y rows of data (which can be set by the top_n and bottom_n
-arguments). It's not advised to use additional gt functions to further
-modify the output of gt_preview(). Furthermore, you cannot pass a gt
-object to gt_preview()." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
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-      <ul class="nav navbar-nav">
-        <li>
-  <a href="../articles/intro-creating-gt-tables.html">Intro</a>
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-      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Preview a <strong>gt</strong> table object</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/gt_preview.R'><code>R/gt_preview.R</code></a></small>
-    <div class="hidden name"><code>gt_preview.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Sometimes you may want to see just a small portion of your input data. We can
-use <code>gt_preview()</code> in place of <code><a href='gt.html'>gt()</a></code> to get the first x rows of data and the
-last y rows of data (which can be set by the <code>top_n</code> and <code>bottom_n</code>
-arguments). It's not advised to use additional <strong>gt</strong> functions to further
-modify the output of <code>gt_preview()</code>. Furthermore, you cannot pass a <strong>gt</strong>
-object to <code>gt_preview()</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>gt_preview</span>(<span class='no'>data</span>, <span class='kw'>top_n</span> <span class='kw'>=</span> <span class='fl'>5</span>, <span class='kw'>bottom_n</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>incl_rownums</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A <code>data.frame</code> object or a tibble.</p></td>
-    </tr>
-    <tr>
-      <th>top_n</th>
-      <td><p>This value will be used as the number of rows from the top of
-the table to display. The default, <code>5</code>, will show the first five rows of
-the table.</p></td>
-    </tr>
-    <tr>
-      <th>bottom_n</th>
-      <td><p>The value will be used as the number of rows from the bottom
-of the table to display. The default, <code>1</code>, will show the final row of the
-table.</p></td>
-    </tr>
-    <tr>
-      <th>incl_rownums</th>
-      <td><p>An option to include the row numbers for <code>data</code> in the
-table stub. By default, this is <code>TRUE</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Any grouped data or magic columns such as <code>rowname</code> and <code>groupname</code> will be
-ignored by <code>gt_preview()</code> and, as such, one cannot add a stub or group rows
-in the output table. By default, the output table will include row numbers in
-a stub (including a range of row numbers for the omitted rows). This row
-numbering option can be deactivated by setting <code>incl_rownums</code> to <code>FALSE</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_gt_preview_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>1-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create Table: 
-<code><a href='gt.html'>gt</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table</span>
-<span class='co'># preview (with only a few of its</span>
-<span class='co'># columns); you'll see the first five</span>
-<span class='co'># rows and the last row</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>year</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>gt_preview</span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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diff --git a/docs/reference/gtcars.html b/docs/reference/gtcars.html
deleted file mode 100644
index da24b700a..000000000
--- a/docs/reference/gtcars.html
+++ /dev/null
@@ -1,254 +0,0 @@
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<meta property="og:title" content="Deluxe automobiles from the 2014-2017 period — gtcars" />
-<meta property="og:description" content="Expensive and fast cars. Not your father's mtcars. Each row describes a car
-of a certain make, model, year, and trim. Basic specifications such as
-horsepower, torque, EPA MPG ratings, type of drivetrain, and transmission
-characteristics are provided. The country of origin for the car manufacturer
-is also given." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-
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-
-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Deluxe automobiles from the 2014-2017 period</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
-    <div class="hidden name"><code>gtcars.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Expensive and fast cars. Not your father's <code>mtcars</code>. Each row describes a car
-of a certain make, model, year, and trim. Basic specifications such as
-horsepower, torque, EPA MPG ratings, type of drivetrain, and transmission
-characteristics are provided. The country of origin for the car manufacturer
-is also given.</p>
-    </div>
-
-    <pre class="usage"><span class='no'>gtcars</span></pre>
-
-
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>A tibble with 47 rows and 15 variables:</p><dl'>
-<dt>mfr</dt><dd><p>The name of the car manufacturer</p></dd>
-<dt>model</dt><dd><p>The car's model name</p></dd>
-<dt>year</dt><dd><p>The car's model year</p></dd>
-<dt>trim</dt><dd><p>A short description of the car model's trim</p></dd>
-<dt>bdy_style</dt><dd><p>An identifier of the car's body style, which is either
-<code>coupe</code>, <code>convertible</code>, <code>sedan</code>, or <code>hatchback</code></p></dd>
-<dt>hp, hp_rpm</dt><dd><p>The car's horsepower and the associated RPM level</p></dd>
-<dt>trq, trq_rpm</dt><dd><p>The car's torque and the associated RPM level</p></dd>
-<dt>mpg_c, mpg_h</dt><dd><p>The miles per gallon fuel efficiency rating for city
-and highway driving</p></dd>
-<dt>drivetrain</dt><dd><p>The car's drivetrain which, for this dataset is either
-<code>rwd</code> (Rear Wheel Drive) or <code>awd</code> (All Wheel Drive)</p></dd>
-<dt>trsmn</dt><dd><p>The codified transmission type, where the number part is
-the number of gears; the car could have automatic transmission
-(<code>a</code>), manual transmission (<code>m</code>), an option to switch between
-both types (<code>am</code>), or, direct drive (<code>dd</code>)</p></dd>
-<dt>ctry_origin</dt><dd><p>The country name for where the vehicle manufacturer
-is headquartered</p></dd>
-
-</dl>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>All of the <code>gtcars</code> have something else in common (aside from the high asking
-prices): they are all grand tourer vehicles. These are proper GT cars that
-blend pure driving thrills with a level of comfort that is more expected from
-a fine limousine (e.g., a Rolls-Royce Phantom EWB). You'll find that, with
-these cars, comfort is emphasized over all-out performance. Nevertheless, the
-driving experience should also mean motoring at speed, doing so in style and
-safety.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>11-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Datasets: 
-<code><a href='countrypops.html'>countrypops</a></code>,
-<code><a href='exibble.html'>exibble</a></code>,
-<code><a href='pizzaplace.html'>pizzaplace</a></code>,
-<code><a href='sp500.html'>sp500</a></code>,
-<code><a href='sza.html'>sza</a></code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
-<span class='co'># available in `gtcars`</span>
-<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>gtcars</span>)</div><div class='output co'>#&gt; Rows: 47
-#&gt; Columns: 15
-#&gt; $ mfr         <span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "Ford", "Ferrari", "Ferrari", "Ferrari", "Ferrari", "Ferr…
-#&gt; $ model       </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "GT", "458 Speciale", "458 Spider", "458 Italia", "488 GT…
-#&gt; $ year        </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2017, 2015, 2015, 2014, 2016, 2015, 2017, 2015, 2015, 201…
-#&gt; $ trim        </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "Base Coupe", "Base Coupe", "Base", "Base Coupe", "Base C…
-#&gt; $ bdy_style   </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "coupe", "coupe", "convertible", "coupe", "coupe", "conve…
-#&gt; $ hp          </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 647, 597, 562, 562, 661, 553, 680, 652, 731, 949, 573, 54…
-#&gt; $ hp_rpm      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 6250, 9000, 9000, 9000, 8000, 7500, 8250, 8000, 8250, 900…
-#&gt; $ trq         </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 550, 398, 398, 398, 561, 557, 514, 504, 509, 664, 476, 43…
-#&gt; $ trq_rpm     </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 5900, 6000, 6000, 6000, 3000, 4750, 5750, 6000, 6000, 675…
-#&gt; $ mpg_c       </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 11, 13, 13, 13, 15, 16, 12, 11, 11, 12, 21, 16, 11, 16, 1…
-#&gt; $ mpg_h       </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 18, 17, 17, 17, 22, 23, 17, 16, 16, 16, 22, 22, 18, 20, 2…
-#&gt; $ drivetrain  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "rwd", "rwd", "rwd", "rwd", "rwd", "rwd", "awd", "awd", "…
-#&gt; $ trsmn       </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a", "7a…
-#&gt; $ ctry_origin </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "United States", "Italy", "Italy", "Italy", "Italy", "Ita…
-#&gt; $ msrp        </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 447000, 291744, 263553, 233509, 245400, 198973, 298000, 2…</div><div class='input'>
-</div></span></pre>
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-    <h1>Save a <strong>gt</strong> table as a file</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/export.R'><code>R/export.R</code></a></small>
-    <div class="hidden name"><code>gtsave.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>gtsave()</code> function makes it easy to save a <strong>gt</strong> table to a file. The
-function guesses the file type by the extension provided in the output
-filename, producing either an HTML, PDF, PNG, LaTeX, or RTF file.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>gtsave</span>(<span class='no'>data</span>, <span class='no'>filename</span>, <span class='kw'>path</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='no'>...</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>filename</th>
-      <td><p>The file name to create on disk. Ensure that an extension
-compatible with the output types is provided (<code>.html</code>, <code>.tex</code>, <code>.ltx</code>,
-<code>.rtf</code>). If a custom save function is provided then the file extension is
-disregarded.</p></td>
-    </tr>
-    <tr>
-      <th>path</th>
-      <td><p>An optional path to which the file should be saved (combined with
-filename).</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>All other options passed to the appropriate internal saving
-function.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Output filenames with either the <code>.html</code> or <code>.htm</code> extensions will produce an
-HTML document. In this case, we can pass a <code>TRUE</code> or <code>FALSE</code> value to the
-<code>inline_css</code> option to obtain an HTML document with inlined CSS styles (the
-default is <code>FALSE</code>). More details on CSS inlining are available at
-<code><a href='as_raw_html.html'>as_raw_html()</a></code>. We can pass values to arguments in <code><a href='https://rdrr.io/pkg/htmltools/man/save_html.html'>htmltools::save_html()</a></code>
-through the <code>...</code>. Those arguments are either <code>background</code> or <code>libdir</code>,
-please refer to the <strong>htmltools</strong> documentation for more details on the use
-of these arguments.</p>
-<p>We can create an image file based on the HTML version of the <code>gt</code> table. With
-the filename extension <code>.png</code>, we get a PNG image file. A PDF document can be
-generated by using the <code>.pdf</code> extension. This process is facilitated by the
-<strong>webshot</strong> package, so, this package needs to be installed before
-attempting to save any table as an image file. There is the option of passing
-values to the underlying <code><a href='https://rdrr.io/pkg/webshot/man/webshot.html'>webshot::webshot()</a></code> function though <code>...</code>. Some of
-the more useful arguments for PNG saving are <code>zoom</code> (defaults to a scale
-level of <code>2</code>) and <code>expand</code> (adds whitespace pixels around the cropped table
-image, and has a default value of <code>5</code>). There are several more options
-available so have a look at the <strong>webshot</strong> documentation for further
-details.</p>
-<p>If the output filename extension is either of <code>.tex</code>, <code>.ltx</code>, or <code>.rnw</code>, a
-LaTeX document is produced. An output filename of <code>.rtf</code> will generate an RTF
-document. The LaTeX and RTF saving functions don't have any options to pass
-to <code>...</code>.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>13-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Export Functions: 
-<code><a href='as_latex.html'>as_latex</a>()</code>,
-<code><a href='as_raw_html.html'>as_raw_html</a>()</code>,
-<code><a href='as_rtf.html'>as_rtf</a>()</code>,
-<code><a href='extract_summary.html'>extract_summary</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table; add</span>
-<span class='co'># a stubhead label to describe what is</span>
-<span class='co'># in the stub</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_stubhead.html'>tab_stubhead</a></span>(<span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"car"</span>)
-
-<span class='co'># Get an HTML file with inlined CSS</span>
-<span class='co'># (which is necessary for including the</span>
-<span class='co'># table as part of an HTML email)</span>
-<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>gtsave</span>(
-    <span class='st'>"tab_1.html"</span>, <span class='kw'>inline_css</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-    <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>()
-  )
-
-<span class='co'># By leaving out the `inline_css` option,</span>
-<span class='co'># we get a more conventional HTML file</span>
-<span class='co'># with embedded CSS styles</span>
-<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>gtsave</span>(<span class='st'>"tab_1.html"</span>, <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>())
-
-<span class='co'># Saving as PNG file results in a cropped</span>
-<span class='co'># image of an HTML table; the amount of</span>
-<span class='co'># whitespace can be set</span>
-<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>gtsave</span>(
-    <span class='st'>"tab_1.png"</span>, <span class='kw'>expand</span> <span class='kw'>=</span> <span class='fl'>10</span>,
-    <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>()
-  )
-
-<span class='co'># Any use of the `.tex`, `.ltx`, or `.rnw`</span>
-<span class='co'># will result in the output of a LaTeX</span>
-<span class='co'># document</span>
-<span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>gtsave</span>(<span class='st'>"tab_1.tex"</span>, <span class='kw'>path</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/tempfile.html'>tempdir</a></span>())</div></pre>
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diff --git a/docs/reference/html.html b/docs/reference/html.html
deleted file mode 100644
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-<meta property="og:description" content="For certain pieces of text (like in column labels or table headings) we may
-want to express them as raw HTML. In fact, with HTML, anything goes so it can
-be much more than just text. The html() function will guard the input HTML
-against escaping, so, your HTML tags will come through as HTML when
-rendered... to HTML." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <h1>Interpret input text as HTML-formatted text</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>html.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>For certain pieces of text (like in column labels or table headings) we may
-want to express them as raw HTML. In fact, with HTML, anything goes so it can
-be much more than just text. The <code>html()</code> function will guard the input HTML
-against escaping, so, your HTML tags will come through as HTML when
-rendered... to HTML.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>html</span>(<span class='no'>text</span>, <span class='no'>...</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>text, ...</th>
-      <td><p>The text that is understood to be HTML text, which is to be
-preserved.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character object of class <code>html</code>. It's tagged as an HTML fragment
-that is not to be sanitized.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_html_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># when adding a title, use the `html()`</span>
-<span class='co'># helper to use html formatting</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>currency</span>, <span class='no'>char</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'>html</span>(<span class='st'>"&lt;em&gt;HTML&lt;/em&gt;"</span>))</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
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-
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-    <li>
-      <a href="../articles/case-study-gtcars.html">Case Study: gtcars</a>
-    </li>
-  </ul>
-</li>
-<li>
-  <a href="../news/index.html">News</a>
-</li>
-      </ul>
-      <ul class="nav navbar-nav navbar-right">
-        <li>
-  <a href="https://github.com/rstudio/gt">
-    <span class="fa fa-github fa-lg"></span>
-     
-  </a>
-</li>
-      </ul>
-      
-    </div><!--/.nav-collapse -->
-  </div><!--/.container -->
-</div><!--/.navbar -->
-
-      
-
-      </header>
-
-<div class="row">
-  <div class="contents col-md-9">
-    <div class="page-header">
-      <h1>Reference</h1>
-    </div>
-
-    <table class="ref-index">
-
-    <colgroup>
-      
-      <col class="alias" />
-      <col class="title" />
-    </colgroup>
-
-    <tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-create-table" class="hasAnchor"><a href="#section-create-table" class="anchor"></a>Create Table</h2>
-          <p class="section-desc"><p>All <strong>gt</strong> tables begin with a call to <code><a href="../reference/gt.html">gt()</a></code>, where we would supply the input data table (data frame or tibble) and some basic options for creating a stub (<code>rowname_col</code>) and row groups (<code>groupname_col</code>). We can also introduce a grouped tibble (via <strong>dplyr</strong>’s <code>group_by()</code>) for more precise divisions of rows into row groups. The <code><a href="../reference/gt_preview.html">gt_preview()</a></code> function is great for getting a nicely-formatted preview of a data table (defaulting to the first 5 rows and the last row).</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="gt.html">gt()</a></code> </p>
-        </td>
-        <td><p>Create a <strong>gt</strong> table object</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="gt_preview.html">gt_preview()</a></code> </p>
-        </td>
-        <td><p>Preview a <strong>gt</strong> table object</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-create-or-modify-parts" class="hasAnchor"><a href="#section-create-or-modify-parts" class="anchor"></a>Create or Modify Parts</h2>
-          <p class="section-desc"><p>A <strong>gt</strong> table can contain a few useful parts for conveying additional information. These include a header (with a titles and subtitle), a footer (with footnotes and source notes), and additional areas for labels (row group labels, column spanner labels, the stubhead label). We can modify the look of table parts more generally with <code><a href="../reference/tab_options.html">tab_options()</a></code> and perform styling on targeted table locations with <code><a href="../reference/tab_style.html">tab_style()</a></code>.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="tab_header.html">tab_header()</a></code> </p>
-        </td>
-        <td><p>Add a table header</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_spanner.html">tab_spanner()</a></code> </p>
-        </td>
-        <td><p>Add a spanner column label</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_spanner_delim.html">tab_spanner_delim()</a></code> </p>
-        </td>
-        <td><p>Create column labels and spanners via delimited names</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_row_group.html">tab_row_group()</a></code> </p>
-        </td>
-        <td><p>Add a row group to a <strong>gt</strong> table</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_stubhead.html">tab_stubhead()</a></code> </p>
-        </td>
-        <td><p>Add label text to the stubhead</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_footnote.html">tab_footnote()</a></code> </p>
-        </td>
-        <td><p>Add a table footnote</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_source_note.html">tab_source_note()</a></code> </p>
-        </td>
-        <td><p>Add a source note citation</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_style.html">tab_style()</a></code> </p>
-        </td>
-        <td><p>Add custom styles to one or more cells</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="tab_options.html">tab_options()</a></code> </p>
-        </td>
-        <td><p>Modify the table output options</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-format-data" class="hasAnchor"><a href="#section-format-data" class="anchor"></a>Format Data</h2>
-          <p class="section-desc"><p>Columns of data can be formatted with the <code>fmt_*()</code> functions. We can specify the rows of these columns quite precisely with the <code>rows</code> argument. We get to apply these functions exactly once to each data cell (last call wins). Need to do custom formatting? Use the <code><a href="../reference/fmt.html">fmt()</a></code> function and define your own formatter within (or, create a wrapper with <code><a href="../reference/fmt.html">fmt()</a></code> if you prefer). The <code><a href="../reference/text_transform.html">text_transform()</a></code> function allows for post-processing of any data, and we provide a function for that transformation.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="fmt_number.html">fmt_number()</a></code> </p>
-        </td>
-        <td><p>Format numeric values</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_scientific.html">fmt_scientific()</a></code> </p>
-        </td>
-        <td><p>Format values to scientific notation</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_percent.html">fmt_percent()</a></code> </p>
-        </td>
-        <td><p>Format values as a percentage</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_currency.html">fmt_currency()</a></code> </p>
-        </td>
-        <td><p>Format values as currencies</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_date.html">fmt_date()</a></code> </p>
-        </td>
-        <td><p>Format values as dates</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_time.html">fmt_time()</a></code> </p>
-        </td>
-        <td><p>Format values as times</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_datetime.html">fmt_datetime()</a></code> </p>
-        </td>
-        <td><p>Format values as date-times</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_markdown.html">fmt_markdown()</a></code> </p>
-        </td>
-        <td><p>Format Markdown text</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_passthrough.html">fmt_passthrough()</a></code> </p>
-        </td>
-        <td><p>Format by simply passing data through</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt_missing.html">fmt_missing()</a></code> </p>
-        </td>
-        <td><p>Format missing values</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="fmt.html">fmt()</a></code> </p>
-        </td>
-        <td><p>Set a column format with a formatter function</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="text_transform.html">text_transform()</a></code> </p>
-        </td>
-        <td><p>Perform targeted text transformation with a function</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="data_color.html">data_color()</a></code> </p>
-        </td>
-        <td><p>Set data cell colors using a palette or a color function</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-modify-columns" class="hasAnchor"><a href="#section-modify-columns" class="anchor"></a>Modify Columns</h2>
-          <p class="section-desc"><p>The <code>cols_*()</code> functions allow for modifications that act on entire columns. This includes alignment of the data in columns (<code><a href="../reference/cols_align.html">cols_align()</a></code>), hiding columns from view (<code><a href="../reference/cols_hide.html">cols_hide()</a></code>), re-labeling the column labels (<code><a href="../reference/cols_label.html">cols_label()</a></code>), merging two columns together (<code>cols_merge*()</code>), moving columns around (<code>cols_move*()</code>)</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="cols_align.html">cols_align()</a></code> </p>
-        </td>
-        <td><p>Set the alignment of columns</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_width.html">cols_width()</a></code> </p>
-        </td>
-        <td><p>Set the widths of columns</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_label.html">cols_label()</a></code> </p>
-        </td>
-        <td><p>Relabel one or more columns</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_move_to_start.html">cols_move_to_start()</a></code> </p>
-        </td>
-        <td><p>Move one or more columns to the start</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_move_to_end.html">cols_move_to_end()</a></code> </p>
-        </td>
-        <td><p>Move one or more columns to the end</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_move.html">cols_move()</a></code> </p>
-        </td>
-        <td><p>Move one or more columns</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_hide.html">cols_hide()</a></code> </p>
-        </td>
-        <td><p>Hide one or more columns</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_merge_range.html">cols_merge_range()</a></code> </p>
-        </td>
-        <td><p>Merge two columns to a value range column</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_merge_uncert.html">cols_merge_uncert()</a></code> </p>
-        </td>
-        <td><p>Merge two columns to a value &amp; uncertainty column</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cols_merge.html">cols_merge()</a></code> </p>
-        </td>
-        <td><p>Merge data from two or more columns to a single column</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-modify-rows" class="hasAnchor"><a href="#section-modify-rows" class="anchor"></a>Modify Rows</h2>
-          <p class="section-desc"><p>The only function currently that modifies entire rows is the <code><a href="../reference/row_group_order.html">row_group_order()</a></code> function. It lets us modify the ordering of any row groups in the table.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="row_group_order.html">row_group_order()</a></code> </p>
-        </td>
-        <td><p>Modify the ordering of any row groups</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-add-rows" class="hasAnchor"><a href="#section-add-rows" class="anchor"></a>Add Rows</h2>
-          <p class="section-desc"><p>There are two functions that will add rows to a <strong>gt</strong> table: <code><a href="../reference/summary_rows.html">summary_rows()</a></code> and <code><a href="../reference/grand_summary_rows.html">grand_summary_rows()</a></code>. These functions will both add summary rows but one will do it in a groupwise fashion while the other will create grand summary rows.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="summary_rows.html">summary_rows()</a></code> </p>
-        </td>
-        <td><p>Add groupwise summary rows using aggregation functions</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="grand_summary_rows.html">grand_summary_rows()</a></code> </p>
-        </td>
-        <td><p>Add grand summary rows using aggregation functions</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-helper-functions" class="hasAnchor"><a href="#section-helper-functions" class="anchor"></a>Helper Functions</h2>
-          <p class="section-desc"><p>A small assortment of helper functions is available in the <strong>gt</strong> package. The various <code>cells_*()</code> functions are used for targeting cells with the <code>locations</code> argument in the <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code>, <code><a href="../reference/tab_style.html">tab_style()</a></code>, and <code><a href="../reference/text_transform.html">text_transform()</a></code> functions. The <code>cells_styles()</code> function is used exclusively with <code><a href="../reference/tab_style.html">tab_style()</a></code>’s <code>style</code> argument (and the <code><a href="../reference/px.html">px()</a></code> &amp; <code><a href="../reference/pct.html">pct()</a></code> functions may be useful there for specifying units in pixels or percentages). The <code><a href="../reference/md.html">md()</a></code> and <code><a href="../reference/html.html">html()</a></code> helpers can used be during label creation with the <code><a href="../reference/tab_header.html">tab_header()</a></code>, <code><a href="../reference/tab_footnote.html">tab_footnote()</a></code>, <code><a href="../reference/tab_spanner.html">tab_spanner()</a></code>, <code>tab_stubhead_label()</code>, and <code><a href="../reference/tab_source_note.html">tab_source_note()</a></code> functions.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="md.html">md()</a></code> </p>
-        </td>
-        <td><p>Interpret input text as Markdown-formatted text</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="html.html">html()</a></code> </p>
-        </td>
-        <td><p>Interpret input text as HTML-formatted text</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="px.html">px()</a></code> </p>
-        </td>
-        <td><p>Helper for providing a numeric value as pixels value</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="pct.html">pct()</a></code> </p>
-        </td>
-        <td><p>Helper for providing a numeric value as percentage</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_title.html">cells_title()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting the table title and subtitle</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_stubhead.html">cells_stubhead()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting the table stubhead cell</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_column_spanners.html">cells_column_spanners()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting the column spanners</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_column_labels.html">cells_column_labels()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting the column labels</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_row_groups.html">cells_row_groups()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting row groups</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_stub.html">cells_stub()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting cells in the table stub</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_body.html">cells_body()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting data cells in the table body</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_summary.html">cells_summary()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting group summary cells</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cells_grand_summary.html">cells_grand_summary()</a></code> </p>
-        </td>
-        <td><p>Location helper for targeting cells in a grand summary</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="currency.html">currency()</a></code> </p>
-        </td>
-        <td><p>Supply a custom currency symbol to <code>fmt_currency()</code></p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cell_text.html">cell_text()</a></code> </p>
-        </td>
-        <td><p>Helper for defining custom text styles for table cells</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cell_fill.html">cell_fill()</a></code> </p>
-        </td>
-        <td><p>Helper for defining custom fills for table cells</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="cell_borders.html">cell_borders()</a></code> </p>
-        </td>
-        <td><p>Helper for defining custom borders for table cells</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="adjust_luminance.html">adjust_luminance()</a></code> </p>
-        </td>
-        <td><p>Adjust the luminance for a palette of colors</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="random_id.html">random_id()</a></code> </p>
-        </td>
-        <td><p>Helper for creating a random <code>id</code> for a <strong>gt</strong> table</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="escape_latex.html">escape_latex()</a></code> </p>
-        </td>
-        <td><p>Perform LaTeX escaping</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="gt_latex_dependencies.html">gt_latex_dependencies()</a></code> </p>
-        </td>
-        <td><p>Get the LaTeX dependencies required for a <strong>gt</strong> table</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-image-addition-functions" class="hasAnchor"><a href="#section-image-addition-functions" class="anchor"></a>Image Addition Functions</h2>
-          <p class="section-desc"><p>We can add images into a <strong>gt</strong> table with the help of the <code>*_image()</code> functions. Two common ways to do this: (1) use <code><a href="../reference/text_transform.html">text_transform()</a></code> to insert images into data cells, (2) use any function that creates new labels (e.g., <code><a href="../reference/tab_header.html">tab_header()</a></code>) and use a <code>*_image()</code> function within the <code><a href="../reference/html.html">html()</a></code> helper.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="web_image.html">web_image()</a></code> </p>
-        </td>
-        <td><p>Helper function for adding an image from the web</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="local_image.html">local_image()</a></code> </p>
-        </td>
-        <td><p>Helper function for adding a local image</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="ggplot_image.html">ggplot_image()</a></code> </p>
-        </td>
-        <td><p>Helper function for adding a ggplot</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="test_image.html">test_image()</a></code> </p>
-        </td>
-        <td><p>Generate a path to a test image</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-table-option-functions" class="hasAnchor"><a href="#section-table-option-functions" class="anchor"></a>Table Option Functions</h2>
-          <p class="section-desc"><p>With the <code>opt_*()</code> functions, we have an easy way to set commonly-used table options without having to use <code><a href="../reference/tab_options.html">tab_options()</a></code> directly. For instance, we can modify the set of marks to use with footnotes, turn on row striping, change the alignment of the table header, and much more.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="opt_footnote_marks.html">opt_footnote_marks()</a></code> </p>
-        </td>
-        <td><p>Option to modify the set of footnote marks</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="opt_row_striping.html">opt_row_striping()</a></code> </p>
-        </td>
-        <td><p>Option to add or remove row striping</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="opt_align_table_header.html">opt_align_table_header()</a></code> </p>
-        </td>
-        <td><p>Option to align the table header</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="opt_all_caps.html">opt_all_caps()</a></code> </p>
-        </td>
-        <td><p>Option to use all caps in select table locations</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="opt_table_lines.html">opt_table_lines()</a></code> </p>
-        </td>
-        <td><p>Option to set table lines to different extents</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="opt_table_outline.html">opt_table_outline()</a></code> </p>
-        </td>
-        <td><p>Option to wrap an outline around the entire table</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-information-functions" class="hasAnchor"><a href="#section-information-functions" class="anchor"></a>Information Functions</h2>
-          <p class="section-desc"><p>These <code>info_*()</code> functions present us with <strong>gt</strong> tables containing useful information. So far, we can get reference information on date styles (<code><a href="../reference/info_date_style.html">info_date_style()</a></code>), on time styles (<code><a href="../reference/info_time_style.html">info_time_style()</a></code>), on a huge number of color palettes (<code><a href="../reference/info_paletteer.html">info_paletteer()</a></code>), on currencies (<code><a href="../reference/info_currencies.html">info_currencies()</a></code>), and, on all of the different locales supported in the formatter functions (<code><a href="../reference/info_locales.html">info_locales()</a></code>).</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="info_date_style.html">info_date_style()</a></code> </p>
-        </td>
-        <td><p>View a table with info on date styles</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="info_time_style.html">info_time_style()</a></code> </p>
-        </td>
-        <td><p>View a table with info on time styles</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="info_currencies.html">info_currencies()</a></code> </p>
-        </td>
-        <td><p>View a table with info on supported currencies</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="info_locales.html">info_locales()</a></code> </p>
-        </td>
-        <td><p>View a table with info on supported locales</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="info_paletteer.html">info_paletteer()</a></code> </p>
-        </td>
-        <td><p>View a table with info on color palettes</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-datasets" class="hasAnchor"><a href="#section-datasets" class="anchor"></a>Datasets</h2>
-          <p class="section-desc"><p>The <strong>gt</strong> package is equipped with six datasets that come in all shapes and sizes. Use them to experiment with the package. Many examples in the internal help documents use these datasets to quickly demonstrate the key features of <strong>gt</strong>.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="countrypops.html">countrypops</a></code> </p>
-        </td>
-        <td><p>Yearly populations of countries from 1960 to 2017</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="sza.html">sza</a></code> </p>
-        </td>
-        <td><p>Twice hourly solar zenith angles by month &amp; latitude</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="gtcars.html">gtcars</a></code> </p>
-        </td>
-        <td><p>Deluxe automobiles from the 2014-2017 period</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="sp500.html">sp500</a></code> </p>
-        </td>
-        <td><p>Daily S&amp;P 500 Index data from 1950 to 2015</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="pizzaplace.html">pizzaplace</a></code> </p>
-        </td>
-        <td><p>A year of pizza sales from a pizza place</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="exibble.html">exibble</a></code> </p>
-        </td>
-        <td><p>A toy example tibble for testing with gt: exibble</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-shiny-functions" class="hasAnchor"><a href="#section-shiny-functions" class="anchor"></a>Shiny Functions</h2>
-          <p class="section-desc"><p>Shiny is great for building interactive web apps with R. There’s really nothing quite like it. The <strong>gt</strong> package includes two functions that work nicely with Shiny: a table render function <code><a href="../reference/render_gt.html">render_gt()</a></code> (for the <code>server</code>) and a table output element <code><a href="../reference/gt_output.html">gt_output()</a></code> (for the <code>ui</code>).</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="render_gt.html">render_gt()</a></code> </p>
-        </td>
-        <td><p>A <strong>gt</strong> display table render function for use in Shiny</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="gt_output.html">gt_output()</a></code> </p>
-        </td>
-        <td><p>Create a <strong>gt</strong> display table output element for Shiny</p></td>
-      </tr>
-    </tbody><tbody>
-      <tr>
-        <th colspan="2">
-          <h2 id="section-export-functions" class="hasAnchor"><a href="#section-export-functions" class="anchor"></a>Export Functions</h2>
-          <p class="section-desc"><p>There may come a day when you need to export a <strong>gt</strong> table to some specific format. A great function for that is <code><a href="../reference/gtsave.html">gtsave()</a></code>, which allows us to save as an HTML file or an image file. Some other functions give us table code as a character vector (e.g., <code><a href="../reference/as_raw_html.html">as_raw_html()</a></code>). Did you use the <code><a href="../reference/summary_rows.html">summary_rows()</a></code> function and wish you had that summary data in a tibble? You can get it out with <code><a href="../reference/extract_summary.html">extract_summary()</a></code>.</p></p>
-        </th>
-      </tr>
-      
-      
-    </tbody><tbody>
-      
-      
-      <tr>
-        
-        <td>
-          <p><code><a href="gtsave.html">gtsave()</a></code> </p>
-        </td>
-        <td><p>Save a <strong>gt</strong> table as a file</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="as_raw_html.html">as_raw_html()</a></code> </p>
-        </td>
-        <td><p>Get the HTML content of a <strong>gt</strong> table</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="as_latex.html">as_latex()</a></code> </p>
-        </td>
-        <td><p>Output a gt object as LaTeX</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="as_rtf.html">as_rtf()</a></code> </p>
-        </td>
-        <td><p>Output a <strong>gt</strong> object as RTF</p></td>
-      </tr><tr>
-        
-        <td>
-          <p><code><a href="extract_summary.html">extract_summary()</a></code> </p>
-        </td>
-        <td><p>Extract a summary list from a <strong>gt</strong> object</p></td>
-      </tr>
-    </tbody>
-    </table>
-  </div>
-
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diff --git a/docs/reference/info_currencies.html b/docs/reference/info_currencies.html
deleted file mode 100644
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+++ /dev/null
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-<meta property="og:description" content="The fmt_currency() function lets us format numeric values as currencies.
-The table generated by the info_currencies() function provides a quick
-reference to all the available currencies. The currency identifiers are
-provided (name, 3-letter currency code, and 3-digit currency code) along with
-the each currency's exponent value (number of digits of the currency
-subunits). A formatted example is provided (based on the value of 49.95) to
-demonstrate the default formatting of each currency." />
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-    <h1>View a table with info on supported currencies</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
-    <div class="hidden name"><code>info_currencies.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code><a href='fmt_currency.html'>fmt_currency()</a></code> function lets us format numeric values as currencies.
-The table generated by the <code>info_currencies()</code> function provides a quick
-reference to all the available currencies. The currency identifiers are
-provided (name, 3-letter currency code, and 3-digit currency code) along with
-the each currency's exponent value (number of digits of the currency
-subunits). A formatted example is provided (based on the value of <code>49.95</code>) to
-demonstrate the default formatting of each currency.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>info_currencies</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"code"</span>, <span class='st'>"symbol"</span>), <span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>type</th>
-      <td><p>The type of currency information provided. Can either be <code>code</code>
-where currency information corresponding to 3-letter currency codes is
-provided, or <code>symbol</code> where currency info for common currency names (e.g.,
-dollar, pound, yen, etc.) is returned.</p></td>
-    </tr>
-    <tr>
-      <th>begins_with</th>
-      <td><p>Providing a single letter will filter currencies to only
-those that begin with that letter in their currency code. The default
-(<code>NULL</code>) will produce a table with all currencies displayed. This option
-only constrains the information table where <code>type == "code"</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>There are 172 currencies, which can lead to a verbose display table. To make
-this presentation more focused on retrieval, we can provide an initial letter
-corresponding to the 3-letter currency code to <code>begins_with</code>. This will
-filter currencies in the info table to just the set beginning with the
-supplied letter.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_info_currencies_1.png' width=100% /></p>
-<p><img src='figures/man_info_currencies_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>10-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Information Functions: 
-<code><a href='info_date_style.html'>info_date_style</a>()</code>,
-<code><a href='info_locales.html'>info_locales</a>()</code>,
-<code><a href='info_paletteer.html'>info_paletteer</a>()</code>,
-<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get a table of info on all of</span>
-<span class='co'># the currencies where the three-</span>
-<span class='co'># letter code begins with a "h"</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_currencies</span>(<span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='st'>"h"</span>)
-
-<span class='co'># Get a table of info on all of the</span>
-<span class='co'># common currency name/symbols that</span>
-<span class='co'># can be used with `fmt_currency()`</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span> <span class='fu'>info_currencies</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"symbol"</span>)</div></pre>
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-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/info_date_style.html b/docs/reference/info_date_style.html
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-    <h1>View a table with info on date styles</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
-    <div class="hidden name"><code>info_date_style.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code><a href='fmt_date.html'>fmt_date()</a></code> function lets us format date-based values in a convenient
-manner using preset styles. The table generated by the <code>info_date_style()</code>
-function provides a quick reference to all 14 styles, with associated number
-codes, the format names, and example outputs using a fixed date
-(<code>2000-02-29</code>).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>info_date_style</span>()</pre>
-
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_info_date_style_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>10-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Information Functions: 
-<code><a href='info_currencies.html'>info_currencies</a>()</code>,
-<code><a href='info_locales.html'>info_locales</a>()</code>,
-<code><a href='info_paletteer.html'>info_paletteer</a>()</code>,
-<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get a table of info on the different</span>
-<span class='co'># date-formatting styles (which are used</span>
-<span class='co'># by supplying a number code to the</span>
-<span class='co'># `fmt_date()` function)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_date_style</span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-</div>
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diff --git a/docs/reference/info_locales.html b/docs/reference/info_locales.html
deleted file mode 100644
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--- a/docs/reference/info_locales.html
+++ /dev/null
@@ -1,225 +0,0 @@
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-<meta property="og:description" content="Many of the fmt_*() functions have a locale argument that makes
-locale-based formatting easier. The table generated by the info_locales()
-function provides a quick reference to all the available locales. The locale
-identifiers are provided (base locale ID, common display name) along with the
-each locale's group and decimal separator marks. A formatted numeric example
-is provided (based on the value of 11027) to demonstrate the default
-formatting of each locale." />
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-    <h1>View a table with info on supported locales</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
-    <div class="hidden name"><code>info_locales.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Many of the <code>fmt_*()</code> functions have a <code>locale</code> argument that makes
-locale-based formatting easier. The table generated by the <code>info_locales()</code>
-function provides a quick reference to all the available locales. The locale
-identifiers are provided (base locale ID, common display name) along with the
-each locale's group and decimal separator marks. A formatted numeric example
-is provided (based on the value of <code>11027</code>) to demonstrate the default
-formatting of each locale.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>info_locales</span>(<span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>begins_with</th>
-      <td><p>Providing a single letter will filter locales to only
-those that begin with that letter in their base locale ID. The default
-(<code>NULL</code>) will produce a table with all locales displayed.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>There are 712 locales, which means that a very long display table is provided
-by default. To trim down the output table size, we can provide an initial
-letter corresponding to the base locale ID to <code>begins_with</code>. This will filter
-locales in the info table to just the set that begins with the supplied
-letter.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>10-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Information Functions: 
-<code><a href='info_currencies.html'>info_currencies</a>()</code>,
-<code><a href='info_date_style.html'>info_date_style</a>()</code>,
-<code><a href='info_paletteer.html'>info_paletteer</a>()</code>,
-<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get a table of info on all of</span>
-<span class='co'># the locales where the base</span>
-<span class='co'># locale ID begins with a "v"</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_locales</span>(<span class='kw'>begins_with</span> <span class='kw'>=</span> <span class='st'>"v"</span>)</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
-
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-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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diff --git a/docs/reference/info_paletteer.html b/docs/reference/info_paletteer.html
deleted file mode 100644
index c66f8508c..000000000
--- a/docs/reference/info_paletteer.html
+++ /dev/null
@@ -1,263 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-
-<title>View a table with info on color palettes — info_paletteer • gt</title>
-
-<!-- favicons -->
-<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
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-<meta property="og:title" content="View a table with info on color palettes — info_paletteer" />
-<meta property="og:description" content="While the data_color() function allows us to flexibly color data cells in
-our gt table, the harder part of this process is discovering and
-choosing color palettes that are suitable for the table output. We can make
-this process much easier in two ways: (1) by using the paletteer
-package, which makes a wide range of palettes from various R packages readily
-available, and (2) calling the info_paletteer() function to give us an
-information table that serves as a quick reference for all of the discrete
-color palettes available in paletteer." />
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-    <h1>View a table with info on color palettes</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
-    <div class="hidden name"><code>info_paletteer.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>While the <code><a href='data_color.html'>data_color()</a></code> function allows us to flexibly color data cells in
-our <strong>gt</strong> table, the harder part of this process is discovering and
-choosing color palettes that are suitable for the table output. We can make
-this process much easier in two ways: (1) by using the <strong>paletteer</strong>
-package, which makes a wide range of palettes from various R packages readily
-available, and (2) calling the <code>info_paletteer()</code> function to give us an
-information table that serves as a quick reference for all of the discrete
-color palettes available in <strong>paletteer</strong>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>info_paletteer</span>(<span class='kw'>color_pkgs</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>color_pkgs</th>
-      <td><p>A vector of color packages that determines which sets of
-palettes should be displayed in the information table. If this is
-<code>NULL</code> (the default) then all of the discrete palettes from all of the
-color packages represented in <strong>paletteer</strong> will be displayed.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The palettes displayed are organized by package and by palette name. These
-values are required when obtaining a palette (as a vector of hexadecimal
-colors), from the the <code><a href='https://rdrr.io/pkg/paletteer/man/paletteer_d.html'>paletteer::paletteer_d()</a></code> function. Once we are
-familiar with the names of the color palette packages (e.g.,
-<strong>RColorBrewer</strong>, <strong>ggthemes</strong>, <strong>wesanderson</strong>), we can narrow down
-the content of this information table by supplying a vector of such package
-names to <code>color_pkgs</code>.</p>
-<p>Colors from the following color packages (all supported by <strong>paletteer</strong>)
-are shown by default with <code>info_paletteer()</code>:</p><ul>
-<li><p><strong>awtools</strong>, 5 palettes</p></li>
-<li><p><strong>dichromat</strong>, 17 palettes</p></li>
-<li><p><strong>dutchmasters</strong>, 6 palettes</p></li>
-<li><p><strong>ggpomological</strong>, 2 palettes</p></li>
-<li><p><strong>ggsci</strong>, 42 palettes</p></li>
-<li><p><strong>ggthemes</strong>, 31 palettes</p></li>
-<li><p><strong>ghibli</strong>, 27 palettes</p></li>
-<li><p><strong>grDevices</strong>, 1 palette</p></li>
-<li><p><strong>jcolors</strong>, 13 palettes</p></li>
-<li><p><strong>LaCroixColoR</strong>, 21 palettes</p></li>
-<li><p><strong>NineteenEightyR</strong>, 12 palettes</p></li>
-<li><p><strong>nord</strong>, 16 palettes</p></li>
-<li><p><strong>ochRe</strong>, 16 palettes</p></li>
-<li><p><strong>palettetown</strong>, 389 palettes</p></li>
-<li><p><strong>pals</strong>, 8 palettes</p></li>
-<li><p><strong>Polychrome</strong>, 7 palettes</p></li>
-<li><p><strong>quickpalette</strong>, 17 palettes</p></li>
-<li><p><strong>rcartocolor</strong>, 34 palettes</p></li>
-<li><p><strong>RColorBrewer</strong>, 35 palettes</p></li>
-<li><p><strong>Redmonder</strong>, 41 palettes</p></li>
-<li><p><strong>wesanderson</strong>, 19 palettes</p></li>
-<li><p><strong>yarrr</strong>, 21 palettes</p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_info_paletteer_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>10-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Information Functions: 
-<code><a href='info_currencies.html'>info_currencies</a>()</code>,
-<code><a href='info_date_style.html'>info_date_style</a>()</code>,
-<code><a href='info_locales.html'>info_locales</a>()</code>,
-<code><a href='info_time_style.html'>info_time_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get a table of info on just the</span>
-<span class='co'># `ggthemes` color palette (easily</span>
-<span class='co'># accessible from the paletteer pkg)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='fu'>info_paletteer</span>(
-    <span class='kw'>color_pkgs</span> <span class='kw'>=</span> <span class='st'>"ggthemes"</span>)</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
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diff --git a/docs/reference/info_time_style.html b/docs/reference/info_time_style.html
deleted file mode 100644
index d8e64a40d..000000000
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+++ /dev/null
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-<meta property="og:description" content="The fmt_time() function lets us format time-based values in a convenient
-manner using preset styles. The table generated by the info_time_style()
-function provides a quick reference to all five styles, with associated
-number codes, the format names, and example outputs using a fixed time
-(14:35)." />
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-    <h1>View a table with info on time styles</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/info_tables.R'><code>R/info_tables.R</code></a></small>
-    <div class="hidden name"><code>info_time_style.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code><a href='fmt_time.html'>fmt_time()</a></code> function lets us format time-based values in a convenient
-manner using preset styles. The table generated by the <code>info_time_style()</code>
-function provides a quick reference to all five styles, with associated
-number codes, the format names, and example outputs using a fixed time
-(<code>14:35</code>).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>info_time_style</span>()</pre>
-
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_info_time_style_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>10-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Information Functions: 
-<code><a href='info_currencies.html'>info_currencies</a>()</code>,
-<code><a href='info_date_style.html'>info_date_style</a>()</code>,
-<code><a href='info_locales.html'>info_locales</a>()</code>,
-<code><a href='info_paletteer.html'>info_paletteer</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get a table of info on the different</span>
-<span class='co'># time-formatting styles (which are used</span>
-<span class='co'># by supplying a number code to the</span>
-<span class='co'># `fmt_time()` function)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span> <span class='fu'>info_time_style</span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
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-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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diff --git a/docs/reference/local_image.html b/docs/reference/local_image.html
deleted file mode 100644
index fb3d465a4..000000000
--- a/docs/reference/local_image.html
+++ /dev/null
@@ -1,261 +0,0 @@
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<title>Helper function for adding a local image — local_image • gt</title>
-
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-a table with local_image() function. The function provides a convenient way
-to generate an HTML fragment using an on-disk PNG or SVG. Because this
-function is currently HTML-based, it is only useful for HTML table output. To
-use this function inside of data cells, it is recommended that the
-text_transform() function is used. With that function, we can specify which
-data cells to target and then include a local_image() call within the
-required user-defined function (for the fn argument). If we want to include
-an image in other places (e.g., in the header, within footnote text, etc.) we
-need to use local_image() within the html() helper function." />
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-    <h1>Helper function for adding a local image</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
-    <div class="hidden name"><code>local_image.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>We can flexibly add a local image (i.e., an image residing on disk) inside of
-a table with <code>local_image()</code> function. The function provides a convenient way
-to generate an HTML fragment using an on-disk PNG or SVG. Because this
-function is currently HTML-based, it is only useful for HTML table output. To
-use this function inside of data cells, it is recommended that the
-<code><a href='text_transform.html'>text_transform()</a></code> function is used. With that function, we can specify which
-data cells to target and then include a <code>local_image()</code> call within the
-required user-defined function (for the <code>fn</code> argument). If we want to include
-an image in other places (e.g., in the header, within footnote text, etc.) we
-need to use <code>local_image()</code> within the <code><a href='html.html'>html()</a></code> helper function.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>local_image</span>(<span class='no'>filename</span>, <span class='kw'>height</span> <span class='kw'>=</span> <span class='fl'>30</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>filename</th>
-      <td><p>A path to an image file.</p></td>
-    </tr>
-    <tr>
-      <th>height</th>
-      <td><p>The absolute height (px) of the image in the table cell.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character object with an HTML fragment that can be placed inside of
-a cell.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>By itself, the function creates an HTML image tag with an image URI embedded
-within. We can easily experiment with a local PNG or SVG image that's
-available in the <strong>gt</strong> package using the <code><a href='test_image.html'>test_image()</a></code> function. Using
-that, the call <code>local_image(file = test_image(type = "png"))</code> evaluates to:</p>
-<p><code>&lt;img cid=&lt;random CID&gt; src=&lt;data URI&gt; style=\"height:30px;\"&gt;</code></p>
-<p>where a height of <code>30px</code> is a default height chosen to work well within the
-heights of most table rows.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_local_image_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>8-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Image Addition Functions: 
-<code><a href='ggplot_image.html'>ggplot_image</a>()</code>,
-<code><a href='test_image.html'>test_image</a>()</code>,
-<code><a href='web_image.html'>web_image</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Create a tibble that contains heights</span>
-<span class='co'># of an image in pixels (one column as a</span>
-<span class='co'># string, the other as numerical values),</span>
-<span class='co'># then, create a gt table; use the</span>
-<span class='co'># `text_transform()` function to insert</span>
-<span class='co'># a local test image (PNG) image with the</span>
-<span class='co'># various sizes</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
-    <span class='kw'>pixels</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)),
-    <span class='kw'>image</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='text_transform.html'>text_transform</a></span>(
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>image</span>)),
-    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
-      <span class='fu'>local_image</span>(
-        <span class='kw'>filename</span> <span class='kw'>=</span> <span class='fu'><a href='test_image.html'>test_image</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"png"</span>),
-        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='no'>x</span>)
-      )
-    }
-  )</div></pre>
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-footnotes, source notes, the table title, etc.) and expect it to render to
-HTML as Markdown does. There is the html() helper that allows you to ferry
-in HTML but this function md()... it's almost like a two-for-one deal (you
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-    <h1>Interpret input text as Markdown-formatted text</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>md.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Markdown! It's a wonderful thing. We can use it in certain places (e.g.,
-footnotes, source notes, the table title, etc.) and expect it to render to
-HTML as Markdown does. There is the <code><a href='html.html'>html()</a></code> helper that allows you to ferry
-in HTML but this function <code>md()</code>... it's almost like a two-for-one deal (you
-get to use Markdown plus any HTML fragments <em>at the same time</em>).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>md</span>(<span class='no'>text</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>text</th>
-      <td><p>The text that is understood to contain Markdown formatting.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character object of class <code>from_markdown</code>. It's tagged as being
-Markdown text and it will undergo conversion to HTML.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_md_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># when adding a title, use the `md()`</span>
-<span class='co'># helper to use Markdown formatting</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>currency</span>, <span class='no'>char</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'>md</span>(<span class='st'>"Using *Markdown*"</span>))</div></pre>
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diff --git a/docs/reference/opt_align_table_header.html b/docs/reference/opt_align_table_header.html
deleted file mode 100644
index a40762de4..000000000
--- a/docs/reference/opt_align_table_header.html
+++ /dev/null
@@ -1,252 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta property="og:description" content="By default, a table header added to a gt table has center alignment
-for both the title and the subtitle elements. This function allows us to
-easily set the horizontal alignment of the title and subtitle to the left
-or right by using the &quot;align&quot; argument. This function serves as a
-convenient shortcut for &amp;lt;gt_tbl&amp;gt; %&amp;gt;% tab_options(heading.align = &amp;lt;align&amp;gt;)." />
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-    <h1>Option to align the table header</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
-    <div class="hidden name"><code>opt_align_table_header.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>By default, a table header added to a <strong>gt</strong> table has center alignment
-for both the title and the subtitle elements. This function allows us to
-easily set the horizontal alignment of the title and subtitle to the left
-or right by using the <code>"align"</code> argument. This function serves as a
-convenient shortcut for <code>&lt;gt_tbl&gt; %&gt;% tab_options(heading.align = &lt;align&gt;)</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>opt_align_table_header</span>(<span class='no'>data</span>, <span class='kw'>align</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"left"</span>, <span class='st'>"center"</span>, <span class='st'>"right"</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>align</th>
-      <td><p>The alignment of the title and subtitle elements in the table
-header. Options are <code>"left"</code> (the default), <code>"center"</code>, or <code>"right"</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_opt_align_table_header_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>9-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Table Option Functions: 
-<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
-<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
-<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
-<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
-<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
-<span class='co'># a number of table parts added; the header</span>
-<span class='co'># (consisting of the title and the subtitle)</span>
-<span class='co'># are to be aligned to the left with the</span>
-<span class='co'># `opt_align_table_header()` function</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_align_table_header</span>(<span class='kw'>align</span> <span class='kw'>=</span> <span class='st'>"left"</span>)</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/opt_all_caps.html b/docs/reference/opt_all_caps.html
deleted file mode 100644
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@@ -1,264 +0,0 @@
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-<meta property="og:description" content="Sometimes an all-capitalized look is suitable for a table. With the
-opt_all_caps() function, we can transform characters in the column labels,
-the stub, and in all row groups in this way (and there's control over which
-of these locations are transformed)." />
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Option to use all caps in select table locations</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
-    <div class="hidden name"><code>opt_all_caps.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Sometimes an all-capitalized look is suitable for a table. With the
-<code>opt_all_caps()</code> function, we can transform characters in the column labels,
-the stub, and in all row groups in this way (and there's control over which
-of these locations are transformed).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>opt_all_caps</span>(
-  <span class='no'>data</span>,
-  <span class='kw'>all_caps</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"column_labels"</span>, <span class='st'>"stub"</span>, <span class='st'>"row_group"</span>)
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>all_caps</th>
-      <td><p>A logical value to indicate whether the text transformation
-to all caps should be performed (<code>TRUE</code>, the default) or reset to default
-values (<code>FALSE</code>) for the <code>locations</code> targeted.</p></td>
-    </tr>
-    <tr>
-      <th>locations</th>
-      <td><p>Which locations should undergo this text transformation? By
-default it includes all of the <code>"column_labels"</code>, the <code>"stub"</code>, and the
-<code>"row_group"</code> locations. However, we could just choose one or two of those.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>This function serves as a convenient shortcut for <code>&lt;gt_tbl&gt; %&gt;% tab_options(&lt;location&gt;.text_transform = "uppercase", &lt;location&gt;.font.size = pct(80), &lt;location&gt;.font.weight = "bolder")</code> (for all <code>locations</code> selected).</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_opt_all_caps_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>9-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Table Option Functions: 
-<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
-<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
-<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
-<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
-<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
-<span class='co'># a number of table parts added; all text</span>
-<span class='co'># in the column labels, the stub, and in</span>
-<span class='co'># all row groups is to be transformed to</span>
-<span class='co'># all caps using `opt_all_caps()`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_all_caps</span>()</div></pre>
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diff --git a/docs/reference/opt_footnote_marks.html b/docs/reference/opt_footnote_marks.html
deleted file mode 100644
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-<meta property="og:description" content="Alter the footnote marks for any footnotes that may be present in the table.
-Either a vector of marks can be provided (including Unicode characters), or,
-a specific keyword could be used to signify a preset sequence. This function
-serves as a shortcut for using tab_options(footnotes.marks = {marks})" />
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-    <div class="page-header">
-    <h1>Option to modify the set of footnote marks</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
-    <div class="hidden name"><code>opt_footnote_marks.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Alter the footnote marks for any footnotes that may be present in the table.
-Either a vector of marks can be provided (including Unicode characters), or,
-a specific keyword could be used to signify a preset sequence. This function
-serves as a shortcut for using <code><a href='tab_options.html'>tab_options(footnotes.marks = {marks})</a></code></p>
-    </div>
-
-    <pre class="usage"><span class='fu'>opt_footnote_marks</span>(<span class='no'>data</span>, <span class='no'>marks</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>marks</th>
-      <td><p>Either a character vector of length greater than 1 (that will
-represent the series of marks) or a single keyword that represents a preset
-sequence of marks. The valid keywords are: <code>"numbers"</code> (for numeric marks),
-<code>"letters"</code> and <code>"LETTERS"</code> (for lowercase and uppercase alphabetic marks),
-<code>"standard"</code> (for a traditional set of four symbol marks), and <code>"extended"</code>
-(which adds two more symbols to the standard set).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>We can supply a vector of that will represent the series of marks.
-The series of footnote marks is recycled when its usage goes beyond the
-length of the set. At each cycle, the marks are simply doubled, tripled, and
-so on (e.g., <code>*</code> -&gt; <code>**</code> -&gt; <code>***</code>). The option exists for providing keywords
-for certain types of footnote marks. The keywords are:</p>
-<ul>
-<li><p><code>"numbers"</code>: numeric marks, they begin from 1 and these marks are not
-subject to recycling behavior</p></li>
-<li><p><code>"letters"</code>: miniscule alphabetic marks, internally uses the <code>letters</code>
-vector
-which contains 26 lowercase letters of the Roman alphabet</p></li>
-<li><p><code>"LETTERS"</code>: majuscule alphabetic marks, using the <code>LETTERS</code> vector
-which has 26 uppercase letters of the Roman alphabet</p></li>
-<li><p><code>"standard"</code>: symbolic marks, four symbols in total</p></li>
-<li><p><code>"extended"</code>: symbolic marks, extends the standard set by adding two
-more symbols, making six</p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_opt_footnote_marks_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>9-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Table Option Functions: 
-<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
-<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
-<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
-<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
-<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sza` to create a gt table,</span>
-<span class='co'># adding three footnotes; call</span>
-<span class='co'># `opt_footnote_marks()` to specify</span>
-<span class='co'># which footnote marks to use</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>latitude</span>, <span class='no'>tst</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarize</a></span>(
-    <span class='kw'>SZA.Max</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>sza</span>),
-    <span class='kw'>SZA.Min</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>sza</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>ungroup</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>30</span>, !<span class='fu'><a href='https://rdrr.io/r/base/is.finite.html'>is.infinite</a></span>(<span class='no'>SZA.Min</span>)) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"tst"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_spanner_delim.html'>tab_spanner_delim</a></span>(<span class='kw'>delim</span> <span class='kw'>=</span> <span class='st'>"."</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_missing.html'>fmt_missing</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything</a></span>(),
-    <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"90+"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_stubhead.html'>tab_stubhead</a></span>(<span class='st'>"TST"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"True solar time."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_stubhead.html'>cells_stubhead</a></span>()
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Solar zenith angle."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_spanners.html'>cells_column_spanners</a></span>(<span class='kw'>spanners</span> <span class='kw'>=</span> <span class='st'>"SZA"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"The Lowest SZA."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_stub.html'>cells_stub</a></span>(<span class='kw'>rows</span> <span class='kw'>=</span> <span class='st'>"1200"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_footnote_marks</span>(<span class='kw'>marks</span> <span class='kw'>=</span> <span class='st'>"standard"</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='output co'>#&gt; <span class='warning'>Warning: no non-missing arguments to min; returning Inf</span></div><div class='input'>
-</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
-    </nav>
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diff --git a/docs/reference/opt_row_striping.html b/docs/reference/opt_row_striping.html
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-&amp;lt;gt_tbl&amp;gt; %&amp;gt;% tab_options(row.striping.include_table_body = TRUE|FALSE)." />
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-    <h1>Option to add or remove row striping</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
-    <div class="hidden name"><code>opt_row_striping.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>By default, a <strong>gt</strong> table does not have row striping enabled. However, this
-function allows us to easily enable or disable striped rows in the table
-body. This function serves as a convenient shortcut for
-<code>&lt;gt_tbl&gt; %&gt;% tab_options(row.striping.include_table_body = TRUE|FALSE)</code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>opt_row_striping</span>(<span class='no'>data</span>, <span class='kw'>row_striping</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>row_striping</th>
-      <td><p>A logical value to indicate whether row striping should
-be added or removed.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_opt_row_striping_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>9-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Table Option Functions: 
-<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
-<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
-<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
-<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code>,
-<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
-<span class='co'># a number of table parts added; next, we</span>
-<span class='co'># add row striping to every second row with</span>
-<span class='co'># the `opt_row_striping()` function</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_row_striping</span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-
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-</div>
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-</html>
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diff --git a/docs/reference/opt_table_lines.html b/docs/reference/opt_table_lines.html
deleted file mode 100644
index a072b240f..000000000
--- a/docs/reference/opt_table_lines.html
+++ /dev/null
@@ -1,254 +0,0 @@
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-<meta property="og:description" content="The opt_table_lines() function sets table lines in one of three possible
-ways: (1) all possible table lines drawn (&quot;all&quot;), (2) no table lines at all
-(&quot;none&quot;), and (3) resetting to the default line styles (&quot;default&quot;). This
-is great if you want to start off with lots of lines and subtract just a few
-of them with tab_options() or tab_style(). Or, use it to start with a
-completely lineless table, adding individual lines as needed." />
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-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Option to set table lines to different extents</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
-    <div class="hidden name"><code>opt_table_lines.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>opt_table_lines()</code> function sets table lines in one of three possible
-ways: (1) all possible table lines drawn (<code>"all"</code>), (2) no table lines at all
-(<code>"none"</code>), and (3) resetting to the default line styles (<code>"default"</code>). This
-is great if you want to start off with lots of lines and subtract just a few
-of them with <code><a href='tab_options.html'>tab_options()</a></code> or <code><a href='tab_style.html'>tab_style()</a></code>. Or, use it to start with a
-completely lineless table, adding individual lines as needed.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>opt_table_lines</span>(<span class='no'>data</span>, <span class='kw'>extent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"all"</span>, <span class='st'>"none"</span>, <span class='st'>"default"</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>extent</th>
-      <td><p>The extent to which lines will be visible in the table. Options
-are <code>"all"</code>, <code>"none"</code>, or <code>"default"</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_opt_table_lines_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>9-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Table Option Functions: 
-<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
-<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
-<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
-<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
-<code><a href='opt_table_outline.html'>opt_table_outline</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
-<span class='co'># a number of table parts added; then, use</span>
-<span class='co'># the `opt_table_lines()` function to</span>
-<span class='co'># haves lines everywhere there can possibly</span>
-<span class='co'># be lines</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_table_lines</span>()</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/opt_table_outline.html b/docs/reference/opt_table_outline.html
deleted file mode 100644
index 65753f80b..000000000
--- a/docs/reference/opt_table_outline.html
+++ /dev/null
@@ -1,260 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
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-<meta property="og:description" content="This function puts an outline of consistent style, width, and color
-around the entire table. It'll write over any existing outside lines so long
-as the width is larger that of the existing lines. The default value of
-style (&quot;solid&quot;) will draw a solid outline, whereas a value of &quot;none&quot;
-will remove any present outline." />
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-    <div class="page-header">
-    <h1>Option to wrap an outline around the entire table</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/opts.R'><code>R/opts.R</code></a></small>
-    <div class="hidden name"><code>opt_table_outline.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This function puts an outline of consistent <code>style</code>, <code>width</code>, and <code>color</code>
-around the entire table. It'll write over any existing outside lines so long
-as the <code>width</code> is larger that of the existing lines. The default value of
-<code>style</code> (<code>"solid"</code>) will draw a solid outline, whereas a value of <code>"none"</code>
-will remove any present outline.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>opt_table_outline</span>(<span class='no'>data</span>, <span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"solid"</span>, <span class='kw'>width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>3</span>), <span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#D3D3D3"</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>style, width, color</th>
-      <td><p>The style, width, and color properties for the table
-outline. By default, these are <code>"solid"</code>, <code><a href='px.html'>px(3)</a></code> (or, <code>"3px"</code>), and
-<code>"#D3D3D3"</code>. If <code>"none"</code> is used then the outline is removed and any values
-provided for <code>width</code> and <code>color</code> will be ignored (i.e., not set).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_opt_table_outline_1.png' width=100% /></p>
-<p><img src='figures/man_opt_table_outline_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>9-6</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Table Option Functions: 
-<code><a href='opt_align_table_header.html'>opt_align_table_header</a>()</code>,
-<code><a href='opt_all_caps.html'>opt_all_caps</a>()</code>,
-<code><a href='opt_footnote_marks.html'>opt_footnote_marks</a>()</code>,
-<code><a href='opt_row_striping.html'>opt_row_striping</a>()</code>,
-<code><a href='opt_table_lines.html'>opt_table_lines</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
-<span class='co'># a number of table parts added; have an</span>
-<span class='co'># outline wrap around the entire table by</span>
-<span class='co'># using `opt_table_outline()`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>, <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='summary_rows.html'>summary_rows</a></span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='st'>"grp_a"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='grand_summary_rows.html'>grand_summary_rows</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>total</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span>(<span class='no'>.</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-    )) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_source_note.html'>tab_source_note</a></span>(<span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"This is a source note."</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"This is a footnote."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fl'>1</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"The title of the table"</span>,
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"The table's subtitle"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_table_outline</span>()
-
-<span class='co'># Remove the table outline with the</span>
-<span class='co'># `style = "none"` option</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>opt_table_outline</span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"none"</span>)</div></pre>
-  </div>
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diff --git a/docs/reference/pct.html b/docs/reference/pct.html
deleted file mode 100644
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-<meta property="og:description" content="A percentage value acts as a length value that is relative to an initial
-state. For instance an 80 percent value for something will size the target
-to 80 percent the size of its 'previous' value. This type of sizing is
-useful for sizing up or down a length value with an intuitive measure. This
-helper function can be used for the setting of font sizes (e.g., in
-cell_text()) and altering the thicknesses of lines (e.g., in
-cell_borders()). Should a more exact definition of size be required, the
-analogous helper function pct() will be more useful." />
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-    <h1>Helper for providing a numeric value as percentage</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>pct.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>A percentage value acts as a length value that is relative to an initial
-state. For instance an 80 percent value for something will size the target
-to 80 percent the size of its 'previous' value. This type of sizing is
-useful for sizing up or down a length value with an intuitive measure. This
-helper function can be used for the setting of font sizes (e.g., in
-<code><a href='cell_text.html'>cell_text()</a></code>) and altering the thicknesses of lines (e.g., in
-<code><a href='cell_borders.html'>cell_borders()</a></code>). Should a more exact definition of size be required, the
-analogous helper function <code>pct()</code> will be more useful.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>pct</span>(<span class='no'>x</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>the numeric value to format as a string percentage for some
-<code><a href='tab_options.html'>tab_options()</a></code> arguments that can take percentage values
-(e.g., <code>table.width</code>).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character vector with a single value in percentage units.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_pct_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='px.html'>px</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># use the `pct()` helper to define the</span>
-<span class='co'># font size for the column labels</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>size</span> <span class='kw'>=</span> <span class='fu'>pct</span>(<span class='fl'>75</span>)),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/pipe.html b/docs/reference/pipe.html
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-<meta property="og:description" content="A synthetic dataset that describes pizza sales for a pizza place somewhere in
-the US. While the contents are artificial, the ingredients used to make the
-pizzas are far from it. There are 32 different pizzas that fall into 4
-different categories: classic (classic pizzas: 'You probably had one like
-it before, but never like this!'), chicken (pizzas with chicken as a major
-ingredient: 'Try the Southwest Chicken Pizza! You'll love it!'), supreme
-(pizzas that try a little harder: 'My Soppressata pizza uses only the finest
-salami from my personal salumist!'), and, veggie (pizzas without any meats
-whatsoever: 'My Five Cheese pizza has so many cheeses, I can only offer it in
-Large Size!')." />
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-    <h1>A year of pizza sales from a pizza place</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
-    <div class="hidden name"><code>pizzaplace.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>A synthetic dataset that describes pizza sales for a pizza place somewhere in
-the US. While the contents are artificial, the ingredients used to make the
-pizzas are far from it. There are 32 different pizzas that fall into 4
-different categories: <code>classic</code> (classic pizzas: 'You probably had one like
-it before, but never like this!'), <code>chicken</code> (pizzas with chicken as a major
-ingredient: 'Try the Southwest Chicken Pizza! You'll love it!'), <code>supreme</code>
-(pizzas that try a little harder: 'My Soppressata pizza uses only the finest
-salami from my personal salumist!'), and, <code>veggie</code> (pizzas without any meats
-whatsoever: 'My Five Cheese pizza has so many cheeses, I can only offer it in
-Large Size!').</p>
-    </div>
-
-    <pre class="usage"><span class='no'>pizzaplace</span></pre>
-
-
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>A tibble with 49574 rows and 7 variables:</p><dl'>
-<dt>id</dt><dd><p>The ID for the order, which consists of one or more pizzas
-at a give <code>date</code> and <code>time</code></p></dd>
-<dt>date</dt><dd><p>A character representation of the <code>order</code> date,
-expressed in the ISO 8601 date format (YYYY-MM-DD)</p></dd>
-<dt>time</dt><dd><p>A character representation of the <code>order</code> time,
-expressed as a 24-hour time the ISO 8601 extended time format
-(hh:mm:ss)</p></dd>
-<dt>name</dt><dd><p>The short name for the pizza</p></dd>
-<dt>size</dt><dd><p>The size of the pizza, which can either be <code>S</code>,
-<code>M</code>, <code>L</code>, <code>XL</code> (rare!), or <code>XXL</code> (even rarer!);
-most pizzas are available in the <code>S</code>, <code>M</code>, and <code>L</code> sizes
-but exceptions apply</p></dd>
-<dt>type</dt><dd><p>The category or type of pizza, which can either be
-<code>classic</code>, <code>chicken</code>, <code>supreme</code>, or <code>veggie</code></p></dd>
-<dt>price</dt><dd><p>The price of the pizza and the amount that it sold for
-(in USD)</p></dd>
-
-</dl>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Each pizza in the dataset is identified by a short <code>name</code>. The following
-listings provide the full names of each pizza and their main ingredients.</p>
-<p>Classic Pizzas:</p><ul>
-<li><p><code>classic_dlx</code>: The Classic Deluxe Pizza (Pepperoni, Mushrooms, Red
-Onions, Red Peppers, Bacon)</p></li>
-<li><p><code>big_meat</code>: The Big Meat Pizza (Bacon, Pepperoni, Italian Sausage,
-Chorizo Sausage)</p></li>
-<li><p><code>pepperoni</code>: The Pepperoni Pizza (Mozzarella Cheese, Pepperoni)</p></li>
-<li><p><code>hawaiian</code>: The Hawaiian Pizza (Sliced Ham, Pineapple, Mozzarella
-Cheese)</p></li>
-<li><p><code>pep_msh_pep</code>: The Pepperoni, Mushroom, and Peppers Pizza
-(Pepperoni, Mushrooms, and Green Peppers)</p></li>
-<li><p><code>ital_cpcllo</code>: The Italian Capocollo Pizza (Capocollo, Red
-Peppers, Tomatoes, Goat Cheese, Garlic, Oregano)</p></li>
-<li><p><code>napolitana</code>: The Napolitana Pizza (Tomatoes, Anchovies, Green
-Olives, Red Onions, Garlic)</p></li>
-<li><p><code>the_greek</code>: The Greek Pizza (Kalamata Olives, Feta Cheese,
-Tomatoes, Garlic, Beef Chuck Roast, Red Onions)</p></li>
-</ul>
-
-<p>Chicken Pizzas:</p><ul>
-<li><p><code>thai_ckn</code>: The Thai Chicken Pizza (Chicken, Pineapple, Tomatoes,
-Red Peppers, Thai Sweet Chilli Sauce)</p></li>
-<li><p><code>bbq_ckn</code>: The Barbecue Chicken Pizza (Barbecued Chicken, Red
-Peppers, Green Peppers, Tomatoes, Red Onions, Barbecue Sauce)</p></li>
-<li><p><code>southw_ckn</code>: The Southwest Chicken Pizza (Chicken, Tomatoes, Red
-Peppers, Red Onions, Jalapeno Peppers, Corn, Cilantro, Chipotle Sauce)</p></li>
-<li><p><code>cali_ckn</code>: The California Chicken Pizza (Chicken, Artichoke,
-Spinach, Garlic, Jalapeno Peppers, Fontina Cheese, Gouda Cheese)</p></li>
-<li><p><code>ckn_pesto</code>: The Chicken Pesto Pizza (Chicken, Tomatoes, Red
-Peppers, Spinach, Garlic, Pesto Sauce)</p></li>
-<li><p><code>ckn_alfredo</code>: The Chicken Alfredo Pizza (Chicken, Red Onions,
-Red Peppers, Mushrooms, Asiago Cheese, Alfredo Sauce)</p></li>
-</ul>
-
-<p>Supreme Pizzas:</p><ul>
-<li><p><code>brie_carre</code>: The Brie Carre Pizza (Brie Carre Cheese, Prosciutto,
-Caramelized Onions, Pears, Thyme, Garlic)</p></li>
-<li><p><code>calabrese</code>: The Calabrese Pizza (‘Nduja Salami, Pancetta,
-Tomatoes, Red Onions, Friggitello Peppers, Garlic)</p></li>
-<li><p><code>soppressata</code>: The Soppressata Pizza (Soppressata Salami, Fontina
-Cheese, Mozzarella Cheese, Mushrooms, Garlic)</p></li>
-<li><p><code>sicilian</code>: The Sicilian Pizza (Coarse Sicilian Salami, Tomatoes,
-Green Olives, Luganega Sausage, Onions, Garlic)</p></li>
-<li><p><code>ital_supr</code>: The Italian Supreme Pizza (Calabrese Salami,
-Capocollo, Tomatoes, Red Onions, Green Olives, Garlic)</p></li>
-<li><p><code>peppr_salami</code>: The Pepper Salami Pizza (Genoa Salami, Capocollo,
-Pepperoni, Tomatoes, Asiago Cheese, Garlic)</p></li>
-<li><p><code>prsc_argla</code>: The Prosciutto and Arugula Pizza (Prosciutto di San
-Daniele, Arugula, Mozzarella Cheese)</p></li>
-<li><p><code>spinach_supr</code>: The Spinach Supreme Pizza (Spinach, Red Onions,
-Pepperoni, Tomatoes, Artichokes, Kalamata Olives, Garlic, Asiago Cheese)</p></li>
-<li><p><code>spicy_ital</code>: The Spicy Italian Pizza (Capocollo, Tomatoes, Goat
-Cheese, Artichokes, Peperoncini verdi, Garlic)</p></li>
-</ul>
-
-<p>Vegetable Pizzas</p><ul>
-<li><p><code>mexicana</code>: The Mexicana Pizza (Tomatoes, Red Peppers, Jalapeno
-Peppers, Red Onions, Cilantro, Corn, Chipotle Sauce, Garlic)</p></li>
-<li><p><code>four_cheese</code>: The Four Cheese Pizza (Ricotta Cheese, Gorgonzola
-Piccante Cheese, Mozzarella Cheese, Parmigiano Reggiano Cheese, Garlic)</p></li>
-<li><p><code>five_cheese</code>: The Five Cheese Pizza (Mozzarella Cheese, Provolone
-Cheese, Smoked Gouda Cheese, Romano Cheese, Blue Cheese, Garlic)</p></li>
-<li><p><code>spin_pesto</code>: The Spinach Pesto Pizza (Spinach, Artichokes,
-Tomatoes, Sun-dried Tomatoes, Garlic, Pesto Sauce)</p></li>
-<li><p><code>veggie_veg</code>: The Vegetables + Vegetables Pizza (Mushrooms,
-Tomatoes, Red Peppers, Green Peppers, Red Onions, Zucchini, Spinach, Garlic)</p></li>
-<li><p><code>green_garden</code>: The Green Garden Pizza (Spinach, Mushrooms,
-Tomatoes, Green Olives, Feta Cheese)</p></li>
-<li><p><code>mediterraneo</code>: The Mediterranean Pizza (Spinach, Artichokes,
-Kalamata Olives, Sun-dried Tomatoes, Feta Cheese, Plum Tomatoes, Red Onions)</p></li>
-<li><p><code>spinach_fet</code>: The Spinach and Feta Pizza (Spinach, Mushrooms,
-Red Onions, Feta Cheese, Garlic)</p></li>
-<li><p><code>ital_veggie</code>: The Italian Vegetables Pizza (Eggplant, Artichokes,
-Tomatoes, Zucchini, Red Peppers, Garlic, Pesto Sauce)</p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>11-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Datasets: 
-<code><a href='countrypops.html'>countrypops</a></code>,
-<code><a href='exibble.html'>exibble</a></code>,
-<code><a href='gtcars.html'>gtcars</a></code>,
-<code><a href='sp500.html'>sp500</a></code>,
-<code><a href='sza.html'>sza</a></code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
-<span class='co'># available in `pizzaplace`</span>
-<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>pizzaplace</span>)</div><div class='output co'>#&gt; Rows: 49,574
-#&gt; Columns: 7
-#&gt; $ id    <span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2015-000001", "2015-000002", "2015-000002", "2015-000002", "20…
-#&gt; $ date  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "2015-01-01", "2015-01-01", "2015-01-01", "2015-01-01", "2015-0…
-#&gt; $ time  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "11:38:36", "11:57:40", "11:57:40", "11:57:40", "11:57:40", "11…
-#&gt; $ name  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "hawaiian", "classic_dlx", "mexicana", "thai_ckn", "five_cheese…
-#&gt; $ size  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "M", "M", "M", "L", "L", "L", "L", "M", "M", "M", "S", "S", "S"…
-#&gt; $ type  </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "classic", "classic", "veggie", "chicken", "veggie", "supreme",…
-#&gt; $ price </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 13.25, 16.00, 16.00, 20.75, 18.50, 20.75, 20.75, 16.50, 16.50, …</div><div class='input'>
-</div></span></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/print.gt_tbl.html b/docs/reference/print.gt_tbl.html
deleted file mode 100644
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+++ /dev/null
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-    <div class="hidden name"><code>print.gt_tbl.Rd</code></div>
-    </div>
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-    <p>This facilitates printing of the HTML table to the R console.</p>
-    </div>
-
-    <pre class="usage"><span class='co'># S3 method for gt_tbl</span>
-<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='kw'>view</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span>())</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>An object of class <code>gt_tbl</code>.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>Any additional parameters.</p></td>
-    </tr>
-    <tr>
-      <th>view</th>
-      <td><p>The value for <code><a href='https://rdrr.io/r/base/print.html'>print()</a></code>s <code>browse</code> argument.</p></td>
-    </tr>
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diff --git a/docs/reference/px.html b/docs/reference/px.html
deleted file mode 100644
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@@ -1,244 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-setting of font sizes (e.g., in cell_text()) and thicknesses of lines
-(e.g., in cell_borders()). Setting a length in pixels with px() allows
-for an absolute definition of size as opposed to the analogous helper
-function pct()." />
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>px.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>For certain parameters, a length value is required. Examples include the
-setting of font sizes (e.g., in <code><a href='cell_text.html'>cell_text()</a></code>) and thicknesses of lines
-(e.g., in <code><a href='cell_borders.html'>cell_borders()</a></code>). Setting a length in pixels with <code>px()</code> allows
-for an absolute definition of size as opposed to the analogous helper
-function <code><a href='pct.html'>pct()</a></code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>px</span>(<span class='no'>x</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>x</th>
-      <td><p>the numeric value to format as a string (e.g., <code>"12px"</code>) for
-some <code><a href='tab_options.html'>tab_options()</a></code> arguments that can take values as units of
-pixels (e.g., <code>table.font.size</code>).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character vector with a single value in pixel units.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_px_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
-<code><a href='cell_borders.html'>cell_borders</a>()</code>,
-<code><a href='cell_fill.html'>cell_fill</a>()</code>,
-<code><a href='cell_text.html'>cell_text</a>()</code>,
-<code><a href='cells_body.html'>cells_body</a>()</code>,
-<code><a href='cells_column_labels.html'>cells_column_labels</a>()</code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners</a>()</code>,
-<code><a href='cells_grand_summary.html'>cells_grand_summary</a>()</code>,
-<code><a href='cells_row_groups.html'>cells_row_groups</a>()</code>,
-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
-<code><a href='cells_stub.html'>cells_stub</a>()</code>,
-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
-<code><a href='cells_title.html'>cells_title</a>()</code>,
-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='random_id.html'>random_id</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># use the `px()` helper to define the</span>
-<span class='co'># font size for the column labels</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_style.html'>tab_style</a></span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>size</span> <span class='kw'>=</span> <span class='fu'>px</span>(<span class='fl'>20</span>)),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/random_id.html b/docs/reference/random_id.html
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/helpers.R'><code>R/helpers.R</code></a></small>
-    <div class="hidden name"><code>random_id.Rd</code></div>
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-    <p>This helper function can be used to create a random, character-based ID
-value argument of variable length (the default is 10 letters).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>random_id</span>(<span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>10</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>n</th>
-      <td><p>The number of lowercase letters to use for the random ID.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character vector containing a single, random ID.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>7-19</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Helper Functions: 
-<code><a href='adjust_luminance.html'>adjust_luminance</a>()</code>,
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-<code><a href='cells_stubhead.html'>cells_stubhead</a>()</code>,
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-<code><a href='cells_summary.html'>cells_summary</a>()</code>,
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-<code><a href='currency.html'>currency</a>()</code>,
-<code><a href='escape_latex.html'>escape_latex</a>()</code>,
-<code><a href='gt_latex_dependencies.html'>gt_latex_dependencies</a>()</code>,
-<code><a href='html.html'>html</a>()</code>,
-<code><a href='md.html'>md</a>()</code>,
-<code><a href='pct.html'>pct</a>()</code>,
-<code><a href='px.html'>px</a>()</code></p></div>
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-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>A <strong>gt</strong> display table render function for use in Shiny</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/shiny.R'><code>R/shiny.R</code></a></small>
-    <div class="hidden name"><code>render_gt.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>With <code>render_gt()</code> we can create a reactive <strong>gt</strong> table that works
-wonderfully once assigned to an output slot (with <code><a href='gt_output.html'>gt_output()</a></code>). This
-function is to be used within Shiny's <code>server()</code> component. We have some
-options for controlling the size of the container holding the <strong>gt</strong> table.
-The <code>width</code> and <code>height</code> arguments allow for sizing the container, and the
-<code>align</code> argument allows us to align the table within the container (some
-other fine-grained options for positioning are available in the
-<code><a href='tab_options.html'>tab_options()</a></code> function).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>render_gt</span>(
-  <span class='no'>expr</span>,
-  <span class='kw'>width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>height</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>env</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/sys.parent.html'>parent.frame</a></span>(),
-  <span class='kw'>quoted</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
-  <span class='kw'>outputArgs</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>()
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>expr</th>
-      <td><p>An expression that creates a <strong>gt</strong> table object. For sake of
-convenience, a data frame or tibble can be used here (it will be
-automatically introduced to <code><a href='gt.html'>gt()</a></code> with its default options).</p></td>
-    </tr>
-    <tr>
-      <th>width, height</th>
-      <td><p>The width and height of the table's container. Either can
-be specified as a single-length character with units of pixels or as a
-percentage. If provided as a single-length numeric vector, it is assumed
-that the value is given in units of pixels. The <code><a href='px.html'>px()</a></code> and <code><a href='pct.html'>pct()</a></code> helper
-functions can also be used to pass in numeric values and obtain values as
-pixel or percent units.</p></td>
-    </tr>
-    <tr>
-      <th>align</th>
-      <td><p>The alignment of the table in its container. By default, this is
-<code>"center"</code>. Other options are <code>"left"</code> and <code>"right"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>env</th>
-      <td><p>The environment in which to evaluate the <code>expr</code>.</p></td>
-    </tr>
-    <tr>
-      <th>quoted</th>
-      <td><p>Is <code>expr</code> a quoted expression (with <code><a href='https://rdrr.io/r/base/substitute.html'>quote()</a></code>)? This is useful
-if you want to save an expression in a variable.</p></td>
-    </tr>
-    <tr>
-      <th>outputArgs</th>
-      <td><p>A list of arguments to be passed through to the implicit
-call to <code><a href='gt_output.html'>gt_output()</a></code> when <code>render_gt</code> is used in an interactive R Markdown
-document.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>We need to ensure that we have the <strong>shiny</strong> package installed first. This
-is easily by using <code><a href='https://rdrr.io/r/utils/install.packages.html'>install.packages("shiny")</a></code>. More information on creating
-Shiny apps can be found at the <a href='https://shiny.rstudio.com'>Shiny Site</a>.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>12-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Shiny functions: 
-<code><a href='gt_output.html'>gt_output</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>shiny</span>)
-
-<span class='co'># Here is a Shiny app (contained within</span>
-<span class='co'># a single file) that (1) prepares a</span>
-<span class='co'># gt table, (2) sets up the `ui` with</span>
-<span class='co'># `gt_output()`, and (3) sets up the</span>
-<span class='co'># `server` with a `render_gt()` that</span>
-<span class='co'># uses the `gt_tbl` object as the input</span>
-<span class='co'># expression</span>
-
-<span class='no'>gt_tbl</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='cols_hide.html'>cols_hide</a></span>(<span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains</a></span>(<span class='st'>"_"</span>))
-
-<span class='no'>ui</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/fluidPage.html'>fluidPage</a></span>(
-
-  <span class='fu'><a href='gt_output.html'>gt_output</a></span>(<span class='kw'>outputId</span> <span class='kw'>=</span> <span class='st'>"table"</span>)
-)
-
-<span class='no'>server</span> <span class='kw'>&lt;-</span> <span class='kw'>function</span>(<span class='no'>input</span>,
-                   <span class='no'>output</span>,
-                   <span class='no'>session</span>) {
-
-  <span class='no'>output</span>$<span class='no'>table</span> <span class='kw'>&lt;-</span>
-    <span class='fu'>render_gt</span>(
-      <span class='kw'>expr</span> <span class='kw'>=</span> <span class='no'>gt_tbl</span>,
-      <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>),
-      <span class='kw'>width</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>600</span>)
-    )
-}
-
-<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/interactive.html'>interactive</a></span>()) {
-  <span class='fu'><a href='https://rdrr.io/pkg/shiny/man/shinyApp.html'>shinyApp</a></span>(<span class='no'>ui</span>, <span class='no'>server</span>)
-}</div></pre>
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diff --git a/docs/reference/row_group_order.html b/docs/reference/row_group_order.html
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-<meta property="og:description" content="We can modify the display order of any row groups in a gt object with
-the row_group_order() function. The groups argument can either take a
-vector of row group names or a numeric vector of row group indices; whichever
-is provided, the row groups will adhere to this revised ordering. It isn't
-necessary to provide all row group names in groups, rather, what is
-provided will assume the specified ordering at the top of the table and the
-remaining row groups will follow in their original ordering." />
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Modify the ordering of any row groups</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/modify_rows.R'><code>R/modify_rows.R</code></a></small>
-    <div class="hidden name"><code>row_group_order.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>We can modify the display order of any row groups in a <strong>gt</strong> object with
-the <code>row_group_order()</code> function. The <code>groups</code> argument can either take a
-vector of row group names or a numeric vector of row group indices; whichever
-is provided, the row groups will adhere to this revised ordering. It isn't
-necessary to provide all row group names in <code>groups</code>, rather, what is
-provided will assume the specified ordering at the top of the table and the
-remaining row groups will follow in their original ordering.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>row_group_order</span>(<span class='no'>data</span>, <span class='no'>groups</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>groups</th>
-      <td><p>A vector of row group names, or, a numeric vector of indices
-corresponding to the new ordering. Either vector must correspond to
-assigned group names or the index positions. Also, either type of vector is
-not required to have all of the row group names or available index
-positions within it; any omitted values will be added to the end while
-preserving the original ordering.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_row_group_order_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>5-1</p>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table</span>
-<span class='co'># with a stub and with row groups;</span>
-<span class='co'># modify the order of the row groups</span>
-<span class='co'># with `row_group_order()`, specifying</span>
-<span class='co'># the new ordering in `groups`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>char</span>, <span class='no'>currency</span>, <span class='no'>row</span>, <span class='no'>group</span>) <span class='kw'>%&gt;%</span>
-    <span class='fu'><a href='gt.html'>gt</a></span>(
-      <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>,
-      <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>
-    ) <span class='kw'>%&gt;%</span>
-    <span class='fu'>row_group_order</span>(
-      <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"grp_b"</span>, <span class='st'>"grp_a"</span>)
-    )</div></pre>
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diff --git a/docs/reference/sp500.html b/docs/reference/sp500.html
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-beginning of 1950 to the end of 2015. The index includes 500 leading
-companies and captures about 80\" />
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-    <div class="page-header">
-    <h1>Daily S&amp;P 500 Index data from 1950 to 2015</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
-    <div class="hidden name"><code>sp500.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This dataset provides daily price indicators for the S&amp;P 500 index from the
-beginning of 1950 to the end of 2015. The index includes 500 leading
-companies and captures about 80\<!-- % coverage of available market capitalization. --></p>
-    </div>
-
-    <pre class="usage"><span class='no'>sp500</span></pre>
-
-
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>A tibble with 16607 rows and 7 variables:</p><dl'>
-<dt>date</dt><dd><p>The date expressed as <code>Date</code> values</p></dd>
-<dt>open, high, low, close</dt><dd><p>The day's opening, high, low, and closing
-prices in USD; the <code>close</code> price is adjusted for splits</p></dd>
-<dt>volume</dt><dd><p>the number of trades for the given <code>date</code></p></dd>
-<dt>adj_close</dt><dd><p>The close price adjusted for both dividends and splits</p></dd>
-
-</dl>
-
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>11-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Datasets: 
-<code><a href='countrypops.html'>countrypops</a></code>,
-<code><a href='exibble.html'>exibble</a></code>,
-<code><a href='gtcars.html'>gtcars</a></code>,
-<code><a href='pizzaplace.html'>pizzaplace</a></code>,
-<code><a href='sza.html'>sza</a></code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
-<span class='co'># available in `sp500`</span>
-<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>sp500</span>)</div><div class='output co'>#&gt; Rows: 16,607
-#&gt; Columns: 7
-#&gt; $ date      <span style='color: #555555;font-style: italic;'>&lt;date&gt;</span><span> 2015-12-31, 2015-12-30, 2015-12-29, 2015-12-28, 2015-12-24…
-#&gt; $ open      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2060.59, 2077.34, 2060.54, 2057.77, 2063.52, 2042.20, 2023.…
-#&gt; $ high      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2062.54, 2077.34, 2081.56, 2057.77, 2067.36, 2064.73, 2042.…
-#&gt; $ low       </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2043.62, 2061.97, 2060.54, 2044.20, 2058.73, 2042.20, 2020.…
-#&gt; $ close     </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2043.94, 2063.36, 2078.36, 2056.50, 2060.99, 2064.29, 2038.…
-#&gt; $ volume    </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2655330000, 2367430000, 2542000000, 2492510000, 1411860000,…
-#&gt; $ adj_close </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 2043.94, 2063.36, 2078.36, 2056.50, 2060.99, 2064.29, 2038.…</div><div class='input'>
-</div></span></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
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diff --git a/docs/reference/summary_rows.html b/docs/reference/summary_rows.html
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-<meta property="og:description" content="Add summary rows to one or more row groups by using the table data and any
-suitable aggregation functions. You choose how to format the values in the
-resulting summary cells by use of a formatter function (e.g, fmt_number,
-etc.) and any relevant options." />
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-    <h1>Add groupwise summary rows using aggregation functions</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/summary_rows.R'><code>R/summary_rows.R</code></a></small>
-    <div class="hidden name"><code>summary_rows.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Add summary rows to one or more row groups by using the table data and any
-suitable aggregation functions. You choose how to format the values in the
-resulting summary cells by use of a <code>formatter</code> function (e.g, <code>fmt_number</code>,
-etc.) and any relevant options.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>summary_rows</span>(
-  <span class='no'>data</span>,
-  <span class='kw'>groups</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='no'>fns</span>,
-  <span class='kw'>missing_text</span> <span class='kw'>=</span> <span class='st'>"---"</span>,
-  <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-  <span class='no'>...</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>groups</th>
-      <td><p>The groups to consider for generation of groupwise summary
-rows. By default this is set to <code>NULL</code>, which results in the formation of
-grand summary rows (a grand summary operates on all table data). Providing
-the names of row groups in <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code> will create a groupwise summary and
-generate summary rows for the specified groups. Setting this to <code>TRUE</code>
-indicates that all available groups will receive groupwise summary rows.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns for which the summaries should be calculated.</p></td>
-    </tr>
-    <tr>
-      <th>fns</th>
-      <td><p>Functions used for aggregations. This can include base functions
-like <code>mean</code>, <code>min</code>, <code>max</code>, <code>median</code>, <code>sd</code>, or <code>sum</code> or any other
-user-defined aggregation function. The function(s) should be supplied
-within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>. Within that list, we can specify the functions by use of
-function names in quotes (e.g., <code>"sum"</code>), as bare functions (e.g., <code>sum</code>),
-or as one-sided R formulas using a leading <code>~</code>. In the formula
-representation, a <code>.</code> serves as the data to be summarized (e.g., <code><a href='https://rdrr.io/r/base/sum.html'>sum(., na.rm = TRUE)</a></code>). The use of named arguments is recommended as the names
-will serve as summary row labels for the corresponding summary rows data
-(the labels can derived from the function names but only when not providing
-bare function names).</p></td>
-    </tr>
-    <tr>
-      <th>missing_text</th>
-      <td><p>The text to be used in place of <code>NA</code> values in summary
-cells with no data outputs.</p></td>
-    </tr>
-    <tr>
-      <th>formatter</th>
-      <td><p>A formatter function name. These can be any of the <code>fmt_*()</code>
-functions available in the package (e.g., <code><a href='fmt_number.html'>fmt_number()</a></code>, <code><a href='fmt_percent.html'>fmt_percent()</a></code>,
-etc.), or a custom function using <code><a href='fmt.html'>fmt()</a></code>. The default function is
-<code><a href='fmt_number.html'>fmt_number()</a></code> and its options can be accessed through <code>...</code>.</p></td>
-    </tr>
-    <tr>
-      <th>...</th>
-      <td><p>Values passed to the <code>formatter</code> function, where the provided
-values are to be in the form of named vectors. For example, when using the
-default <code>formatter</code> function, <code><a href='fmt_number.html'>fmt_number()</a></code>, options such as <code>decimals</code>,
-<code>use_seps</code>, and <code>locale</code> can be used.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>Should we need to obtain the summary data for external purposes, the
-<code><a href='extract_summary.html'>extract_summary()</a></code> function can be used with a <code>gt_tbl</code> object where summary
-rows were added via <code>summary_rows()</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_summary_rows_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>6-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Add Rows: 
-<code><a href='grand_summary_rows.html'>grand_summary_rows</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sp500` to create a gt table with</span>
-<span class='co'># row groups; create summary rows (`min`,</span>
-<span class='co'># `max`, `avg`) by row group, where each</span>
-<span class='co'># each row group is a week number</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-01-05"</span> <span class='kw'>&amp;</span>
-      <span class='no'>date</span> <span class='kw'>&lt;=</span><span class='st'>"2015-01-16"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/arrange.html'>arrange</a></span>(<span class='no'>date</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
-    <span class='kw'>week</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
-      <span class='st'>"W"</span>, <span class='fu'><a href='https://rdrr.io/r/base/strptime.html'>strftime</a></span>(<span class='no'>date</span>, <span class='kw'>format</span> <span class='kw'>=</span> <span class='st'>"%V"</span>))
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>adj_close</span>, -<span class='no'>volume</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(
-    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
-    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"week"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>summary_rows</span>(
-    <span class='kw'>groups</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>open</span>, <span class='no'>high</span>, <span class='no'>low</span>, <span class='no'>close</span>),
-    <span class='kw'>fns</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='kw'>min</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>min</a></span>(<span class='no'>.</span>),
-      <span class='kw'>max</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span>(<span class='no'>.</span>),
-      <span class='kw'>avg</span> <span class='kw'>=</span> ~<span class='fu'><a href='https://rdrr.io/r/base/mean.html'>mean</a></span>(<span class='no'>.</span>)),
-    <span class='kw'>formatter</span> <span class='kw'>=</span> <span class='no'>fmt_number</span>,
-    <span class='kw'>use_seps</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-<meta property="og:description" content="This dataset contains solar zenith angles (in degrees, with the range of
-0-90) every half hour from 04:00 to 12:00, true solar time. This set of
-values is calculated on the first of every month for 4 different northern
-hemisphere latitudes. For determination of afternoon values, the presented
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-    <h1>Twice hourly solar zenith angles by month &amp; latitude</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/datasets.R'><code>R/datasets.R</code></a></small>
-    <div class="hidden name"><code>sza.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This dataset contains solar zenith angles (in degrees, with the range of
-0-90) every half hour from 04:00 to 12:00, true solar time. This set of
-values is calculated on the first of every month for 4 different northern
-hemisphere latitudes. For determination of afternoon values, the presented
-tabulated values are symmetric about noon.</p>
-    </div>
-
-    <pre class="usage"><span class='no'>sza</span></pre>
-
-
-    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
-
-    <p>A tibble with 816 rows and 4 variables:</p><dl'>
-<dt>latitude</dt><dd><p>The latitude in decimal degrees for the observations</p></dd>
-<dt>month</dt><dd><p>The measurement month; all calculations where conducted
-for the first day of each month</p></dd>
-<dt>tst</dt><dd><p>The true solar time at the given <code>latitude</code> and date
-(first of <code>month</code>) for which the solar zenith angle is calculated</p></dd>
-<dt>sza</dt><dd><p>The solar zenith angle in degrees, where <code>NA</code>s
-indicate that sunrise hadn't yet occurred by the <code>tst</code> value</p></dd>
-
-</dl>
-
-    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
-
-    <p>Calculated Actinic Fluxes (290 - 700 nm) for Air Pollution
-Photochemistry Applications (Peterson, 1976), available at:
-<a href='https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=9100JA26.txt'>https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=9100JA26.txt</a>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The solar zenith angle (SZA) is one measure that helps to describe the sun's
-path across the sky. It's defined as the angle of the sun relative to a line
-perpendicular to the earth's surface. It is useful to calculate the SZA in
-relation to the true solar time. True solar time relates to the position of
-the sun with respect to the observer, which is different depending on the
-exact longitude. For example, two hours before the sun crosses the meridian
-(the highest point it would reach that day) corresponds to a true solar time
-of 10 a.m. The SZA has a strong dependence on the observer's latitude. For
-example, at a latitude of 50 degrees N at the start of January, the noontime
-SZA is 73.0 but a different observer at 20 degrees N would measure the
-noontime SZA to be 43.0 degrees.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>11-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Datasets: 
-<code><a href='countrypops.html'>countrypops</a></code>,
-<code><a href='exibble.html'>exibble</a></code>,
-<code><a href='gtcars.html'>gtcars</a></code>,
-<code><a href='pizzaplace.html'>pizzaplace</a></code>,
-<code><a href='sp500.html'>sp500</a></code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Here is a glimpse at the data</span>
-<span class='co'># available in `sza`</span>
-<span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>glimpse</a></span>(<span class='no'>sza</span>)</div><div class='output co'>#&gt; Rows: 816
-#&gt; Columns: 4
-#&gt; $ latitude <span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, …
-#&gt; $ month    </span><span style='color: #555555;font-style: italic;'>&lt;fct&gt;</span><span> jan, jan, jan, jan, jan, jan, jan, jan, jan, jan, jan, jan, …
-#&gt; $ tst      </span><span style='color: #555555;font-style: italic;'>&lt;chr&gt;</span><span> "0400", "0430", "0500", "0530", "0600", "0630", "0700", "073…
-#&gt; $ sza      </span><span style='color: #555555;font-style: italic;'>&lt;dbl&gt;</span><span> NA, NA, NA, NA, NA, NA, 84.9, 78.7, 72.7, 66.1, 61.5, 56.5, …</div><div class='input'>
-</div></span></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/tab_footnote.html b/docs/reference/tab_footnote.html
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-<meta property="og:description" content="The tab_footnote() function can make it a painless process to add a
-footnote to a gt table. There are two components to a footnote: (1) a
-footnote mark that is attached to the targeted cell text, and (2) the
-footnote text (that starts with the corresponding footnote mark) that is
-placed in the table's footer area. Each call of tab_footnote() will add a
-different note, and one or more cells can be targeted via the location helper
-functions (e.g., cells_body(), cells_column_labels(), etc.)." />
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-    <h1>Add a table footnote</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_footnote.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>The <code>tab_footnote()</code> function can make it a painless process to add a
-footnote to a <strong>gt</strong> table. There are two components to a footnote: (1) a
-footnote mark that is attached to the targeted cell text, and (2) the
-footnote text (that starts with the corresponding footnote mark) that is
-placed in the table's footer area. Each call of <code>tab_footnote()</code> will add a
-different note, and one or more cells can be targeted via the location helper
-functions (e.g., <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_column_labels.html'>cells_column_labels()</a></code>, etc.).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_footnote</span>(<span class='no'>data</span>, <span class='no'>footnote</span>, <span class='no'>locations</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>footnote</th>
-      <td><p>The text to be used in the footnote. We can optionally use
-the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> functions to style the text as Markdown or to
-retain HTML elements in the footnote text.</p></td>
-    </tr>
-    <tr>
-      <th>locations</th>
-      <td><p>The cell or set of cells to be associated with the footnote.
-Supplying any of the <code>cells_*()</code> helper functions is a useful way to target
-the location cells that are associated with the footnote text. These helper
-functions are: <code><a href='cells_title.html'>cells_title()</a></code>, <code><a href='cells_stubhead.html'>cells_stubhead()</a></code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>, <code><a href='cells_column_labels.html'>cells_column_labels()</a></code>, <code><a href='cells_row_groups.html'>cells_row_groups()</a></code>,
-<code><a href='cells_stub.html'>cells_stub()</a></code>, <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_summary.html'>cells_summary()</a></code>, and
-<code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>. Additionally, we can enclose several <code>cells_*()</code>
-calls within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code> if we wish to link the footnote text to different
-types of locations (e.g., body cells, row group labels, the table title,
-etc.).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>The formatting of the footnotes can be controlled through the use of various
-parameters in the <code><a href='tab_options.html'>tab_options()</a></code> function:</p>
-<ul>
-<li><p><code>footnotes.sep</code>: allows for a choice of the separator between
-consecutive footnotes in the table footer. By default, this is set to a
-linebreak.</p></li>
-<li><p><code>footnotes.marks</code>: the set of sequential characters or numbers used
-to identify the footnotes.</p></li>
-<li><p><code>footnotes.font.size</code>: the size of the font used in the footnote
-section.</p></li>
-<li><p><code>footnotes.padding</code>: the amount of padding to apply between the
-footnote and source note sections in the table footer.</p></li>
-</ul>
-
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_footnote_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-6</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `sza` to create a gt table; color</span>
-<span class='co'># the `sza` column using the `data_color()`</span>
-<span class='co'># function, then, add a footnote to the</span>
-<span class='co'># `sza` column label explaining what the</span>
-<span class='co'># color scale signifies</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sza</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>latitude</span> <span class='kw'>==</span> <span class='fl'>20</span> <span class='kw'>&amp;</span>
-      <span class='no'>month</span> <span class='kw'>==</span> <span class='st'>"jan"</span> <span class='kw'>&amp;</span>
-      !<span class='fu'><a href='https://rdrr.io/r/base/NA.html'>is.na</a></span>(<span class='no'>sza</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>latitude</span>, -<span class='no'>month</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='data_color.html'>data_color</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sza</span>),
-    <span class='kw'>colors</span> <span class='kw'>=</span> <span class='kw pkg'>scales</span><span class='kw ns'>::</span><span class='fu'><a href='https://scales.r-lib.org//reference/col_numeric.html'>col_numeric</a></span>(
-      <span class='kw'>palette</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"white"</span>, <span class='st'>"yellow"</span>, <span class='st'>"navyblue"</span>),
-      <span class='kw'>domain</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>0</span>, <span class='fl'>90</span>))
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_footnote</span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Color indicates height of sun."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>sza</span>))
-  )</div></pre>
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diff --git a/docs/reference/tab_header.html b/docs/reference/tab_header.html
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-subtitle. A table header is an optional table part that is positioned above
-the column labels. We have the flexibility to use Markdown formatting for the
-header's title and subtitle. Furthermore, if the table is intended for HTML
-output, we can use HTML in either of the title or subtitle." />
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_header.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>We can add a table header to the <strong>gt</strong> table with a title and even a
-subtitle. A table header is an optional table part that is positioned above
-the column labels. We have the flexibility to use Markdown formatting for the
-header's title and subtitle. Furthermore, if the table is intended for HTML
-output, we can use HTML in either of the title or subtitle.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_header</span>(<span class='no'>data</span>, <span class='no'>title</span>, <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>title, subtitle</th>
-      <td><p>Text to be used in the table title and, optionally, for
-the table subtitle. We can elect to use the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> helper
-functions to style the text as Markdown or to retain HTML elements in the
-text.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_header_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># add a header part to contain a title</span>
-<span class='co'># and subtitle</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_header</span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **gtcars**"</span>),
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`gtcars` is an R dataset"</span>)
-  )</div></pre>
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diff --git a/docs/reference/tab_options.html b/docs/reference/tab_options.html
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-<meta property="og:description" content="Modify the options available in a table. These options are named by the
-components, the subcomponents, and the element that can adjusted." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
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-    <div class="page-header">
-    <h1>Modify the table output options</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_options.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Modify the options available in a table. These options are named by the
-components, the subcomponents, and the element that can adjusted.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_options</span>(
-  <span class='no'>data</span>,
-  <span class='kw'>container.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>container.height</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>container.overflow.x</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>container.overflow.y</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.margin.left</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.margin.right</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.font.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.font.color.light</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.right.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.right.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.right.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.left.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.left.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table.border.left.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.align</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.title.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.title.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.subtitle.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.subtitle.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>heading.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.vlines.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.vlines.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.vlines.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>column_labels.hidden</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.left.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.left.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.left.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.right.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.right.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row_group.border.right.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.hlines.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.hlines.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.hlines.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.vlines.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.vlines.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.vlines.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.border.top.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.border.top.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.border.top.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>table_body.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.font.weight</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.border.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.border.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>stub.border.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>data_row.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>summary_row.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>summary_row.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>summary_row.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>summary_row.border.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>summary_row.border.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>summary_row.border.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>grand_summary_row.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>grand_summary_row.text_transform</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>grand_summary_row.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>grand_summary_row.border.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>grand_summary_row.border.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>grand_summary_row.border.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.sep</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>footnotes.marks</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.background.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.font.size</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.padding</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.border.bottom.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.border.bottom.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.border.bottom.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.border.lr.style</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.border.lr.width</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>source_notes.border.lr.color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row.striping.background_color</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row.striping.include_stub</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
-  <span class='kw'>row.striping.include_table_body</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
-)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>container.width, container.height</th>
-      <td><p>The width and height of the table's
-container. Can be specified as a single-length character with units of
-pixels or as a percentage. If provided as a single-length numeric vector,
-it is assumed that the value is given in units of pixels. The <code><a href='px.html'>px()</a></code> and
-<code><a href='pct.html'>pct()</a></code> helper functions can also be used to pass in numeric values and
-obtain values as pixel or percent units.</p></td>
-    </tr>
-    <tr>
-      <th>container.overflow.x, container.overflow.y</th>
-      <td><p>Options to enable scrolling
-in the horizontal and vertical directions when the table content overflows
-the container dimensions. Using <code>TRUE</code> (the default for both) means that
-horizontal or vertical scrolling is enabled to view the entire table in
-those directions. With <code>FALSE</code>, the table may be clipped if the table width
-or height exceeds the <code>container.width</code> or <code>container.height</code>.</p></td>
-    </tr>
-    <tr>
-      <th>table.width</th>
-      <td><p>The width of the table. Can be specified as a
-single-length character with units of pixels or as a percentage. If
-provided as a single-length numeric vector, it is assumed that the value is
-given in units of pixels. The <code><a href='px.html'>px()</a></code> and <code><a href='pct.html'>pct()</a></code> helper functions can also
-be used to pass in numeric values and obtain values as pixel or percent
-units.</p></td>
-    </tr>
-    <tr>
-      <th>table.align</th>
-      <td><p>The horizontal alignment of the table in its container. By
-default, this is <code>"center"</code>. Other options are <code>"left"</code> and <code>"right"</code>. This
-will automatically set <code>table.margin.left</code> and <code>table.margin.right</code> to the
-appropriate values.</p></td>
-    </tr>
-    <tr>
-      <th>table.margin.left, table.margin.right</th>
-      <td><p>The size of the margins on the
-left and right of the table within the container. Can be specified as a
-single-length character with units of pixels or as a percentage. If
-provided as a single-length numeric vector, it is assumed that the value is
-given in units of pixels. The <code><a href='px.html'>px()</a></code> and <code><a href='pct.html'>pct()</a></code> helper functions can also
-be used to pass in numeric values and obtain values as pixel or percent
-units. Using <code>table.margin.left</code> or <code>table.margin.right</code> will overwrite any
-values set by <code>table.align</code>.</p></td>
-    </tr>
-    <tr>
-      <th>table.background.color, heading.background.color, column_labels.background.color, row_group.background.color, stub.background.color, summary_row.background.color, grand_summary_row.background.color, footnotes.background.color, source_notes.background.color</th>
-      <td><p>Background colors for the parent element <code>table</code> and the following child
-elements: <code>heading</code>, <code>column_labels</code>, <code>row_group</code>, <code>stub</code>, <code>summary_row</code>,
-<code>grand_summary_row</code>, <code>footnotes</code>, and <code>source_notes</code>. A color name or a
-hexadecimal color code should be provided.</p></td>
-    </tr>
-    <tr>
-      <th>table.font.color, table.font.color.light</th>
-      <td><p>The text color used throughout the table. There are two variants:
-<code>table.font.color</code> is for text overlaid on lighter background colors, and
-<code>table.font.color.light</code> is automatically used when text needs to be
-overlaid on darker background colors. A color name or a hexadecimal color
-code should be provided.</p></td>
-    </tr>
-    <tr>
-      <th>table.font.size, heading.title.font.size, heading.subtitle.font.size, column_labels.font.size, row_group.font.size, stub.font.size, footnotes.font.size, source_notes.font.size</th>
-      <td><p>The font sizes for the parent text element <code>table</code> and the following child
-elements: <code>heading.title</code>, <code>heading.subtitle</code>, <code>column_labels</code>,
-<code>row_group</code>, <code>footnotes</code>, and <code>source_notes</code>. Can be specified as a
-single-length character vector with units of pixels (e.g., <code>12px</code>) or as a
-percentage (e.g., <code>80\%</code>). If provided as a single-length numeric vector,
-it is assumed that the value is given in units of pixels. The <code><a href='px.html'>px()</a></code> and
-<code><a href='pct.html'>pct()</a></code> helper functions can also be used to pass in numeric values and
-obtain values as pixel or percentage units.</p></td>
-    </tr>
-    <tr>
-      <th>table.border.top.style, table.border.top.width, table.border.top.color, table.border.right.style, table.border.right.width, table.border.right.color, table.border.bottom.style, table.border.bottom.width, table.border.bottom.color, table.border.left.style, table.border.left.width, table.border.left.color</th>
-      <td><p>The style, width, and color properties of the table's absolute top and
-absolute bottom borders.</p></td>
-    </tr>
-    <tr>
-      <th>heading.align</th>
-      <td><p>Controls the horizontal alignment of the heading title
-and subtitle. We can either use <code>"center"</code>, <code>"left"</code>, or <code>"right"</code>.</p></td>
-    </tr>
-    <tr>
-      <th>heading.title.font.weight, heading.subtitle.font.weight, column_labels.font.weight, row_group.font.weight, stub.font.weight</th>
-      <td><p>The font weights of the <code>heading.title</code>, <code>heading.subtitle</code>,
-<code>column_labels</code>, <code>row_group</code>, and <code>stub</code> text elements. Can be a text-based
-keyword such as <code>"normal"</code>, <code>"bold"</code>, <code>"lighter"</code>, <code>"bolder"</code>, or, a
-numeric value between <code>1</code> and <code>1000</code>, inclusive. Note that only variable
-fonts may support the numeric mapping of weight.</p></td>
-    </tr>
-    <tr>
-      <th>heading.border.bottom.style, heading.border.bottom.width, heading.border.bottom.color</th>
-      <td><p>The style, width, and color properties of the header's bottom border. This
-border shares space with that of the <code>column_labels</code> location. If the
-<code>width</code> of this border is larger, then it will be the visible border.</p></td>
-    </tr>
-    <tr>
-      <th>heading.border.lr.style, heading.border.lr.width, heading.border.lr.color</th>
-      <td><p>The style, width, and color properties for the left and right borders of
-the <code>heading</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>column_labels.text_transform, row_group.text_transform, stub.text_transform, summary_row.text_transform, grand_summary_row.text_transform</th>
-      <td><p>Options to apply text transformations to the <code>column_labels</code>, <code>row_group</code>,
-<code>stub</code>, <code>summary_row</code>, and <code>grand_summary_row</code> text elements. Either of the
-<code>"uppercase"</code>, <code>"lowercase"</code>, or <code>"capitalize"</code> keywords can be used.</p></td>
-    </tr>
-    <tr>
-      <th>column_labels.vlines.style, column_labels.vlines.width, column_labels.vlines.color</th>
-      <td><p>The style, width, and color properties for all vertical lines ('vlines')
-of the the <code>column_labels</code>.</p></td>
-    </tr>
-    <tr>
-      <th>column_labels.border.top.style, column_labels.border.top.width, column_labels.border.top.color</th>
-      <td><p>The style, width, and color properties for the top border of the
-<code>column_labels</code> location. This border shares space with that of the
-<code>heading</code> location. If dthe <code>width</code> of this border is larger, then it will
-be the visible border.</p></td>
-    </tr>
-    <tr>
-      <th>column_labels.border.bottom.style, column_labels.border.bottom.width, column_labels.border.bottom.color</th>
-      <td><p>The style, width, and color properties for the bottom border of the
-<code>column_labels</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>column_labels.border.lr.style, column_labels.border.lr.width, column_labels.border.lr.color</th>
-      <td><p>The style, width, and color properties for the left and right borders of
-the <code>column_labels</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>column_labels.hidden</th>
-      <td><p>An option to hide the column labels. If providing
-<code>TRUE</code> then the entire <code>column_labels</code> location won't be seen and the table
-header (if present) will collapse downward.</p></td>
-    </tr>
-    <tr>
-      <th>row_group.border.top.style, row_group.border.top.width, row_group.border.top.color, row_group.border.bottom.style, row_group.border.bottom.width, row_group.border.bottom.color, row_group.border.left.style, row_group.border.left.width, row_group.border.left.color, row_group.border.right.style, row_group.border.right.width, row_group.border.right.color</th>
-      <td><p>The style, width, and color properties for all top, bottom, left, and right
-borders of the <code>row_group</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>table_body.hlines.style, table_body.hlines.width, table_body.hlines.color, table_body.vlines.style, table_body.vlines.width, table_body.vlines.color</th>
-      <td><p>The style, width, and color properties for all horizontal lines ('hlines')
-and vertical lines ('vlines') in the <code>table_body</code>.</p></td>
-    </tr>
-    <tr>
-      <th>table_body.border.top.style, table_body.border.top.width, table_body.border.top.color, table_body.border.bottom.style, table_body.border.bottom.width, table_body.border.bottom.color</th>
-      <td><p>The style, width, and color properties for all top and bottom borders of
-the <code>table_body</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>stub.border.style, stub.border.width, stub.border.color</th>
-      <td><p>The style, width, and color properties for the vertical border of the table
-stub.</p></td>
-    </tr>
-    <tr>
-      <th>data_row.padding, row_group.padding, summary_row.padding, grand_summary_row.padding, footnotes.padding, source_notes.padding</th>
-      <td><p>The amount of vertical padding to incorporate in the <code>data_row</code>,
-<code>row_group</code>, <code>summary_row</code>, <code>grand_summary_row</code>, <code>footnotes</code>, and
-<code>source_notes</code> locations.</p></td>
-    </tr>
-    <tr>
-      <th>summary_row.border.style, summary_row.border.width, summary_row.border.color</th>
-      <td><p>The style, width, and color properties for all horizontal borders of the
-<code>summary_row</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>grand_summary_row.border.style, grand_summary_row.border.width, grand_summary_row.border.color</th>
-      <td><p>The style, width, and color properties for the top borders of the
-<code>grand_summary_row</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>footnotes.border.bottom.style, footnotes.border.bottom.width, footnotes.border.bottom.color</th>
-      <td><p>The style, width, and color properties for the bottom border of the
-<code>footnotes</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>footnotes.border.lr.style, footnotes.border.lr.width, footnotes.border.lr.color</th>
-      <td><p>The style, width, and color properties for the left and right borders of
-the <code>footnotes</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>footnotes.sep</th>
-      <td><p>The separating characters between adjacent footnotes in
-the footnotes section. The default value produces a linebreak.</p></td>
-    </tr>
-    <tr>
-      <th>footnotes.marks</th>
-      <td><p>The set of sequential marks used to reference and
-identify each of the footnotes (same input as the <code><a href='opt_footnote_marks.html'>opt_footnote_marks()</a></code>
-function. We can supply a vector that represents the series of footnote
-marks. This vector is recycled when its usage goes beyond the length of the
-set. At each cycle, the marks are simply combined (e.g., <code>*</code> -&gt; <code>**</code> -&gt;
-<code>***</code>). The option exists for providing keywords for certain types of
-footnote marks. The keyword <code>"numbers"</code> (the default, indicating that we
-want to use numeric marks). We can use lowercase <code>"letters"</code> or uppercase
-<code>"LETTERS"</code>. There is the option for using a traditional symbol set where
-<code>"standard"</code> provides four symbols, and, <code>"extended"</code> adds two more
-symbols, making six.</p></td>
-    </tr>
-    <tr>
-      <th>source_notes.border.bottom.style, source_notes.border.bottom.width, source_notes.border.bottom.color</th>
-      <td><p>The style, width, and color properties for the bottom border of the
-<code>source_notes</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>source_notes.border.lr.style, source_notes.border.lr.width, source_notes.border.lr.color</th>
-      <td><p>The style, width, and color properties for the left and right borders of
-the <code>source_notes</code> location.</p></td>
-    </tr>
-    <tr>
-      <th>row.striping.background_color</th>
-      <td><p>The background color for striped table
-body rows. A color name or a hexadecimal color code should be provided.</p></td>
-    </tr>
-    <tr>
-      <th>row.striping.include_stub</th>
-      <td><p>An option for whether to include the stub
-when striping rows.</p></td>
-    </tr>
-    <tr>
-      <th>row.striping.include_table_body</th>
-      <td><p>An option for whether to include the
-table body when striping rows.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_options_1.png' width=100% /></p>
-<p><img src='figures/man_tab_options_2.png' width=100% /></p>
-<p><img src='figures/man_tab_options_3.png' width=100% /></p>
-<p><img src='figures/man_tab_options_4.png' width=100% /></p>
-<p><img src='figures/man_tab_options_5.png' width=100% /></p>
-<p><img src='figures/man_tab_options_6.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-9</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table with</span>
-<span class='co'># all the main parts added; we can use this</span>
-<span class='co'># going forward to demo some `tab_options()`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
-    -<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='no'>fctr</span>, <span class='no'>date</span>, <span class='no'>time</span>, <span class='no'>datetime</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(
-    <span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"row"</span>,
-    <span class='kw'>groupname_col</span> <span class='kw'>=</span> <span class='st'>"group"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"Data listing from **exibble**"</span>),
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='md.html'>md</a></span>(<span class='st'>"`exibble` is an R dataset"</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_currency.html'>fmt_currency</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Using commas for separators."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;</span> <span class='fl'>1000</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Using commas for separators."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&gt;</span> <span class='fl'>1000</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_footnote.html'>tab_footnote</a></span>(
-    <span class='kw'>footnote</span> <span class='kw'>=</span> <span class='st'>"Alphabetical fruit."</span>,
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_column_labels.html'>cells_column_labels</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>char</span>))
-  )
-
-<span class='co'># Modify the table width to 100% (which</span>
-<span class='co'># spans the entire content width area)</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_options</span>(
-    <span class='kw'>table.width</span> <span class='kw'>=</span> <span class='fu'><a href='pct.html'>pct</a></span>(<span class='fl'>100</span>)
-  )
-
-<span class='co'># Modify the table's background color</span>
-<span class='co'># to be "lightcyan"</span>
-<span class='no'>tab_3</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_options</span>(
-    <span class='kw'>table.background.color</span> <span class='kw'>=</span> <span class='st'>"lightcyan"</span>
-  )
-
-<span class='co'># Use letters as the marks for footnote</span>
-<span class='co'># references; also, separate footnotes in</span>
-<span class='co'># the footer by spaces instead of newlines</span>
-<span class='no'>tab_4</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_options</span>(
-    <span class='kw'>footnotes.sep</span> <span class='kw'>=</span> <span class='st'>" "</span>,
-    <span class='kw'>footnotes.marks</span> <span class='kw'>=</span> <span class='no'>letters</span>
-  )
-
-<span class='co'># Change the padding of data rows to 5px</span>
-<span class='no'>tab_5</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_options</span>(
-    <span class='kw'>data_row.padding</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>5</span>)
-  )
-
-<span class='co'># Reduce the size of the title and the</span>
-<span class='co'># subtitle text</span>
-<span class='no'>tab_6</span> <span class='kw'>&lt;-</span>
-  <span class='no'>tab_1</span> <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_options</span>(
-    <span class='kw'>heading.title.font.size</span> <span class='kw'>=</span> <span class='st'>"small"</span>,
-    <span class='kw'>heading.subtitle.font.size</span> <span class='kw'>=</span> <span class='st'>"small"</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/tab_row_group.html b/docs/reference/tab_row_group.html
deleted file mode 100644
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--- a/docs/reference/tab_row_group.html
+++ /dev/null
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-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta property="og:description" content="Create a row group with a collection of rows. This requires specification of
-the rows to be included, either by supplying row labels, row indices, or
-through use of a select helper function like starts_with()." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
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-    <div class="page-header">
-    <h1>Add a row group to a <strong>gt</strong> table</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_row_group.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Create a row group with a collection of rows. This requires specification of
-the rows to be included, either by supplying row labels, row indices, or
-through use of a select helper function like <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_row_group</span>(<span class='no'>data</span>, <span class='kw'>group</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>rows</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>others</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>group</th>
-      <td><p>The name of the row group. This text will also serve as the row
-group label.</p></td>
-    </tr>
-    <tr>
-      <th>rows</th>
-      <td><p>The rows to be made components of the row group. Can either be a
-vector of row captions provided in <code><a href='https://rdrr.io/r/base/c.html'>c()</a></code>, a vector of row indices, or a
-helper function focused on selections. The select helper functions are:
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>starts_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>ends_with()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>contains()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches()</a></code>, <code><a href='https://tidyselect.r-lib.org/reference/one_of.html'>one_of()</a></code>, and
-<code><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>everything()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>others</th>
-      <td><p>An option to set a default row group label for any rows not
-formally placed in a row group named by <code>group</code> in any call of
-<code>tab_row_group()</code>. A separate call to <code>tab_row_group()</code> with only a value
-to <code>others</code> is possible and makes explicit that the call is meant to
-provide a default row group label. If this is not set and there are rows
-that haven't been placed into a row group (where one or more row groups
-already exist), those rows will be automatically placed into a row group
-without a label.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_row_group_1.png' width=100% /></p>
-<p><img src='figures/man_tab_row_group_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table and</span>
-<span class='co'># add two row groups with the labels:</span>
-<span class='co'># `numbered` and `NA` (a group without</span>
-<span class='co'># a title, or, the rest)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_row_group</span>(
-    <span class='kw'>group</span> <span class='kw'>=</span> <span class='st'>"numbered"</span>,
-    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='fu'><a href='https://tidyselect.r-lib.org/reference/select_helpers.html'>matches</a></span>(<span class='st'>"^[0-9]"</span>)
-  )
-
-<span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># add two row groups with the labels</span>
-<span class='co'># `powerful` and `super powerful`: the</span>
-<span class='co'># distinction being `hp` lesser or</span>
-<span class='co'># greater than `600`</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_row_group</span>(
-    <span class='kw'>group</span> <span class='kw'>=</span> <span class='st'>"powerful"</span>,
-    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>hp</span> <span class='kw'>&lt;=</span> <span class='fl'>600</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_row_group</span>(
-    <span class='kw'>group</span> <span class='kw'>=</span> <span class='st'>"super powerful"</span>,
-    <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>hp</span> <span class='kw'>&gt;</span> <span class='fl'>600</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
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-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
-</div>
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diff --git a/docs/reference/tab_source_note.html b/docs/reference/tab_source_note.html
deleted file mode 100644
index 14f3fc6cc..000000000
--- a/docs/reference/tab_source_note.html
+++ /dev/null
@@ -1,237 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
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-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-<meta property="og:description" content="Add a source note to the footer part of the gt table. A source note is
-useful for citing the data included in the table. Several can be added to the
-footer, simply use multiple calls of tab_source_note() and they will be
-inserted in the order provided. We can use Markdown formatting for the note,
-or, if the table is intended for HTML output, we can include HTML formatting." />
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-    <li class="dropdown-header">Case Studies</li>
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-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Add a source note citation</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_source_note.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Add a source note to the footer part of the <strong>gt</strong> table. A source note is
-useful for citing the data included in the table. Several can be added to the
-footer, simply use multiple calls of <code>tab_source_note()</code> and they will be
-inserted in the order provided. We can use Markdown formatting for the note,
-or, if the table is intended for HTML output, we can include HTML formatting.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_source_note</span>(<span class='no'>data</span>, <span class='no'>source_note</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>source_note</th>
-      <td><p>Text to be used in the source note. We can optionally use
-the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> functions to style the text as Markdown or to
-retain HTML elements in the text.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_source_note_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-7</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># add a source note to the table</span>
-<span class='co'># footer that cites the data source</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mfr</span>, <span class='no'>model</span>, <span class='no'>msrp</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_source_note</span>(
-    <span class='kw'>source_note</span> <span class='kw'>=</span> <span class='st'>"From edmunds.com"</span>
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
-
-<div class="pkgdown">
-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
-</div>
-
-      </footer>
-   </div>
-
-  
-
-
-  </body>
-</html>
-
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diff --git a/docs/reference/tab_spanner.html b/docs/reference/tab_spanner.html
deleted file mode 100644
index 57ba4af1e..000000000
--- a/docs/reference/tab_spanner.html
+++ /dev/null
@@ -1,248 +0,0 @@
-<!-- Generated by pkgdown: do not edit by hand -->
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-  <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
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-
-<title>Add a spanner column label — tab_spanner • gt</title>
-
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-<!-- Bootstrap -->
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-
-<!-- headroom.js -->
-<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
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-<script src="../pkgdown.js"></script>
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-<meta property="og:title" content="Add a spanner column label — tab_spanner" />
-<meta property="og:description" content="Set a spanner column label by mapping it to columns already in the table.
-This label is placed above one or more column labels, spanning the width of
-those columns and column labels." />
-<meta property="og:image" content="https://gt.rstudio.com/logo.svg" />
-
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-        <li>
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-</li>
-<li class="dropdown">
-  <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">
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-<div class="row">
-  <div class="col-md-9 contents">
-    <div class="page-header">
-    <h1>Add a spanner column label</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_spanner.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Set a spanner column label by mapping it to columns already in the table.
-This label is placed above one or more column labels, spanning the width of
-those columns and column labels.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_spanner</span>(<span class='no'>data</span>, <span class='no'>label</span>, <span class='no'>columns</span>, <span class='kw'>gather</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>label</th>
-      <td><p>The text to use for the spanner column label.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>The columns to be components of the spanner heading.</p></td>
-    </tr>
-    <tr>
-      <th>gather</th>
-      <td><p>An option to move the specified <code>columns</code> such that they are
-unified under the spanner column label. Ordering of the moved-into-place
-columns will be preserved in all cases.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_spanner_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-2</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table;</span>
-<span class='co'># Group several columns related to car</span>
-<span class='co'># performance under a spanner column</span>
-<span class='co'># with the label `performance`</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(
-    -<span class='no'>mfr</span>, -<span class='no'>trim</span>, <span class='no'>bdy_style</span>, <span class='no'>drivetrain</span>,
-    -<span class='no'>drivetrain</span>, -<span class='no'>trsmn</span>, -<span class='no'>ctry_origin</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>8</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_spanner</span>(
-    <span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"performance"</span>,
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(
-      <span class='no'>hp</span>, <span class='no'>hp_rpm</span>, <span class='no'>trq</span>, <span class='no'>trq_rpm</span>,
-      <span class='no'>mpg_c</span>, <span class='no'>mpg_h</span>)
-  )</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
-</div>
-
-
-      <footer>
-      <div class="copyright">
-  <p>Developed by Richard Iannone, Joe Cheng, Barret Schloerke, <a href='https://www.rstudio.com'><img src='https://www.tidyverse.org/rstudio-logo.svg' alt='RStudio' height='24' /></a>.</p>
-</div>
-
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-  <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.0.9000.</p>
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diff --git a/docs/reference/tab_spanner_delim.html b/docs/reference/tab_spanner_delim.html
deleted file mode 100644
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-components (LHS) are promoted to being spanner column labels, and the
-secondary components (RHS) will become the column labels. Please note that
-reference to individual columns must continue to be the column names from the
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_spanner_delim.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>This function will split selected delimited column names such that the first
-components (LHS) are promoted to being spanner column labels, and the
-secondary components (RHS) will become the column labels. Please note that
-reference to individual columns must continue to be the column names from the
-input table data (which are unique by necessity).</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_spanner_delim</span>(<span class='no'>data</span>, <span class='no'>delim</span>, <span class='kw'>columns</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>gather</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>delim</th>
-      <td><p>The delimiter to use to split an input column name. The
-delimiter supplied will be autoescaped for the internal splitting
-procedure. The first component of the split will become the group name and
-the second component will be the column label.</p></td>
-    </tr>
-    <tr>
-      <th>columns</th>
-      <td><p>An optional vector of column names that this operation should
-be limited to. The default is to consider all columns in the table.</p></td>
-    </tr>
-    <tr>
-      <th>gather</th>
-      <td><p>An option to move the specified <code>columns</code> such that they are
-unified under the spanner column label. Ordering of the moved-into-place
-columns will be preserved in all cases.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>If we look to the column names in the <code>iris</code> dataset as an example of how
-<code>tab_spanner_delim()</code> might be useful, we find the names <code>Sepal.Length</code>,
-<code>Sepal.Width</code>, <code>Petal.Length</code>, <code>Petal.Width</code>. From this naming system, it's
-easy to see that the <code>Sepal</code> and <code>Petal</code> can group together the repeated
-common <code>Length</code> and <code>Width</code> values. In your own datasets, we can avoid a
-lengthy relabeling with <code><a href='cols_label.html'>cols_label()</a></code> if column names can be fashioned
-beforehand to contain both the spanner column label and the column label. An
-additional advantage is that the column names in the input table data remain
-unique even though there may eventually be repeated column labels in the
-rendered output table).</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_spanner_delim_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-3</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `iris` to create a gt table; split</span>
-<span class='co'># any columns that are dot-separated</span>
-<span class='co'># between column spanner labels (first</span>
-<span class='co'># part) and column labels (second part)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>iris</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>Species</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>4</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_spanner_delim</span>(<span class='kw'>delim</span> <span class='kw'>=</span> <span class='st'>"."</span>)</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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diff --git a/docs/reference/tab_stubhead.html b/docs/reference/tab_stubhead.html
deleted file mode 100644
index 29000bd03..000000000
--- a/docs/reference/tab_stubhead.html
+++ /dev/null
@@ -1,237 +0,0 @@
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-element that is positioned left of the column labels, and above the stub. If
-a stub does not exist, then there is no stubhead (so no change will be made
-when using this function in that case). We have the flexibility to use
-Markdown formatting for the stubhead label. Furthermore, if the table is
-intended for HTML output, we can use HTML for the stubhead label." />
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-    <h1>Add label text to the stubhead</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_stubhead.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Add a label to the stubhead of a <strong>gt</strong> table. The stubhead is the lone
-element that is positioned left of the column labels, and above the stub. If
-a stub does not exist, then there is no stubhead (so no change will be made
-when using this function in that case). We have the flexibility to use
-Markdown formatting for the stubhead label. Furthermore, if the table is
-intended for HTML output, we can use HTML for the stubhead label.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_stubhead</span>(<span class='no'>data</span>, <span class='no'>label</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>label</th>
-      <td><p>The text to be used as the stubhead label We can optionally use
-the <code><a href='md.html'>md()</a></code> and <code><a href='html.html'>html()</a></code> functions to style the text as Markdown or to
-retain HTML elements in the text.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_stubhead_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-5</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_style.html'>tab_style</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `gtcars` to create a gt table; add</span>
-<span class='co'># a stubhead label to describe what is</span>
-<span class='co'># in the stub</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>gtcars</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>model</span>, <span class='no'>year</span>, <span class='no'>hp</span>, <span class='no'>trq</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>5</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>(<span class='kw'>rowname_col</span> <span class='kw'>=</span> <span class='st'>"model"</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_stubhead</span>(<span class='kw'>label</span> <span class='kw'>=</span> <span class='st'>"car"</span>)</div></pre>
-  </div>
-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
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-      <h2 data-toc-skip>Contents</h2>
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diff --git a/docs/reference/tab_style.html b/docs/reference/tab_style.html
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-<meta property="og:title" content="Add custom styles to one or more cells — tab_style" />
-<meta property="og:description" content="With the tab_style() function we can target specific cells and apply styles
-to them. This is best done in conjunction with the helper functions
-cell_text(), cell_fill(), and cell_borders(). At present this function
-is focused on the application of styles for HTML output only (as such, other
-output formats will ignore all tab_style() calls). Using the aforementioned
-helper functions, here are some of the styles we can apply:
-the background color of the cell (cell_fill(): color)
-the cell's text color, font, and size (cell_text(): color, font,
-size)
-the text style (cell_text(): style), enabling the use of italics or
-oblique text.
-the text weight (cell_text(): weight), allowing the use of thin to
-bold text (the degree of choice is greater with variable fonts)
-the alignment and indentation of text (cell_text(): align and
-indent)
-the cell borders (cell_borders())
-
-" />
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-    <div class="page-header">
-    <h1>Add custom styles to one or more cells</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/tab_create_modify.R'><code>R/tab_create_modify.R</code></a></small>
-    <div class="hidden name"><code>tab_style.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>With the <code>tab_style()</code> function we can target specific cells and apply styles
-to them. This is best done in conjunction with the helper functions
-<code><a href='cell_text.html'>cell_text()</a></code>, <code><a href='cell_fill.html'>cell_fill()</a></code>, and <code><a href='cell_borders.html'>cell_borders()</a></code>. At present this function
-is focused on the application of styles for HTML output only (as such, other
-output formats will ignore all <code>tab_style()</code> calls). Using the aforementioned
-helper functions, here are some of the styles we can apply:</p><ul>
-<li><p>the background color of the cell (<code><a href='cell_fill.html'>cell_fill()</a></code>: <code>color</code>)</p></li>
-<li><p>the cell's text color, font, and size (<code><a href='cell_text.html'>cell_text()</a></code>: <code>color</code>, <code>font</code>,
-<code>size</code>)</p></li>
-<li><p>the text style (<code><a href='cell_text.html'>cell_text()</a></code>: <code>style</code>), enabling the use of italics or
-oblique text.</p></li>
-<li><p>the text weight (<code><a href='cell_text.html'>cell_text()</a></code>: <code>weight</code>), allowing the use of thin to
-bold text (the degree of choice is greater with variable fonts)</p></li>
-<li><p>the alignment and indentation of text (<code><a href='cell_text.html'>cell_text()</a></code>: <code>align</code> and
-<code>indent</code>)</p></li>
-<li><p>the cell borders (<code><a href='cell_borders.html'>cell_borders()</a></code>)</p></li>
-</ul>
-
-    </div>
-
-    <pre class="usage"><span class='fu'>tab_style</span>(<span class='no'>data</span>, <span class='no'>style</span>, <span class='no'>locations</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>style</th>
-      <td><p>a vector of styles to use. The <code><a href='cell_text.html'>cell_text()</a></code>, <code><a href='cell_fill.html'>cell_fill()</a></code>, and
-<code><a href='cell_borders.html'>cell_borders()</a></code> helper functions can be used here to more easily generate
-valid styles. If using more than one helper function to define styles, all
-calls must be enclosed in a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code>.</p></td>
-    </tr>
-    <tr>
-      <th>locations</th>
-      <td><p>the cell or set of cells to be associated with the style.
-Supplying any of the <code>cells_*()</code> helper functions is a useful way to target
-the location cells that are associated with the styling. These helper
-functions are: <code><a href='cells_title.html'>cells_title()</a></code>, <code><a href='cells_stubhead.html'>cells_stubhead()</a></code>,
-<code><a href='cells_column_spanners.html'>cells_column_spanners()</a></code>, <code><a href='cells_column_labels.html'>cells_column_labels()</a></code>, <code><a href='cells_row_groups.html'>cells_row_groups()</a></code>,
-<code><a href='cells_stub.html'>cells_stub()</a></code>, <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_summary.html'>cells_summary()</a></code>, and
-<code><a href='cells_grand_summary.html'>cells_grand_summary()</a></code>. Additionally, we can enclose several <code>cells_*()</code>
-calls within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code> if we wish to apply styling to different types of
-locations (e.g., body cells, row group labels, the table title, etc.).</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_tab_style_1.png' width=100% /></p>
-<p><img src='figures/man_tab_style_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>2-8</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p><code><a href='cell_text.html'>cell_text()</a></code>, <code><a href='cell_fill.html'>cell_fill()</a></code>, and <code><a href='cell_borders.html'>cell_borders()</a></code> as helpers for
-defining custom styles and <code><a href='cells_body.html'>cells_body()</a></code> as one of many useful helper
-functions for targeting the locations to be styled.</p>
-<p>Other Create or Modify Parts: 
-<code><a href='tab_footnote.html'>tab_footnote</a>()</code>,
-<code><a href='tab_header.html'>tab_header</a>()</code>,
-<code><a href='tab_options.html'>tab_options</a>()</code>,
-<code><a href='tab_row_group.html'>tab_row_group</a>()</code>,
-<code><a href='tab_source_note.html'>tab_source_note</a>()</code>,
-<code><a href='tab_spanner_delim.html'>tab_spanner_delim</a>()</code>,
-<code><a href='tab_spanner.html'>tab_spanner</a>()</code>,
-<code><a href='tab_stubhead.html'>tab_stubhead</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># add styles that are to be applied</span>
-<span class='co'># to data cells that satisfy a</span>
-<span class='co'># condition (using `tab_style()`)</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(
-    <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>, <span class='no'>currency</span>),
-    <span class='kw'>decimals</span> <span class='kw'>=</span> <span class='fl'>1</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_style</span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightcyan"</span>),
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>weight</span> <span class='kw'>=</span> <span class='st'>"bold"</span>)
-      ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>num</span> <span class='kw'>&gt;=</span> <span class='fl'>5000</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_style</span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"#F9E3D6"</span>),
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>style</span> <span class='kw'>=</span> <span class='st'>"italic"</span>)
-      ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>),
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>currency</span> <span class='kw'>&lt;</span> <span class='fl'>100</span>)
-  )
-
-<span class='co'># Use `sp500` to create a gt table;</span>
-<span class='co'># color entire rows of cells based</span>
-<span class='co'># on values in a particular column</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='no'>sp500</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(
-    <span class='no'>date</span> <span class='kw'>&gt;=</span> <span class='st'>"2015-12-01"</span> <span class='kw'>&amp;</span>
-    <span class='no'>date</span> <span class='kw'>&lt;=</span> <span class='st'>"2015-12-15"</span>
-  ) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='no'>adj_close</span>, <span class='no'>volume</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_style</span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"lightgreen"</span>),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>close</span> <span class='kw'>&gt;</span> <span class='no'>open</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'>tab_style</span>(
-    <span class='kw'>style</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(
-      <span class='fu'><a href='cell_fill.html'>cell_fill</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"red"</span>),
-      <span class='fu'><a href='cell_text.html'>cell_text</a></span>(<span class='kw'>color</span> <span class='kw'>=</span> <span class='st'>"white"</span>)
-      ),
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>rows</span> <span class='kw'>=</span> <span class='no'>open</span> <span class='kw'>&gt;</span> <span class='no'>close</span>)
-  )</div></pre>
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diff --git a/docs/reference/test_image.html b/docs/reference/test_image.html
deleted file mode 100644
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+++ /dev/null
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-    <h1>Generate a path to a test image</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
-    <div class="hidden name"><code>test_image.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>Two test images are available within the <strong>gt</strong> package. Both contain the
-same imagery (sized at 200px by 200px) but one is a PNG file while the other
-is an SVG file. This function is most useful when paired with <code><a href='local_image.html'>local_image()</a></code>
-since we test various sizes of the test image within that function.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>test_image</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"png"</span>, <span class='st'>"svg"</span>))</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>type</th>
-      <td><p>The type of the image, which can either be <code>png</code> (the default) or
-<code>svg</code>.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character vector with a single path to an image file.</p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>8-4</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Image Addition Functions: 
-<code><a href='ggplot_image.html'>ggplot_image</a>()</code>,
-<code><a href='local_image.html'>local_image</a>()</code>,
-<code><a href='web_image.html'>web_image</a>()</code></p></div>
-
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-  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
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diff --git a/docs/reference/text_transform.html b/docs/reference/text_transform.html
deleted file mode 100644
index 6b8e1b7fe..000000000
--- a/docs/reference/text_transform.html
+++ /dev/null
@@ -1,253 +0,0 @@
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-<!DOCTYPE html>
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-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/text_transform.R'><code>R/text_transform.R</code></a></small>
-    <div class="hidden name"><code>text_transform.Rd</code></div>
-    </div>
-
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-    <p>Perform targeted text transformation with a function</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>text_transform</span>(<span class='no'>data</span>, <span class='no'>locations</span>, <span class='no'>fn</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>data</th>
-      <td><p>A table object that is created using the <code><a href='gt.html'>gt()</a></code> function.</p></td>
-    </tr>
-    <tr>
-      <th>locations</th>
-      <td><p>The cell or set of cells to be associated with the text
-transformation. Only the <code><a href='cells_body.html'>cells_body()</a></code>, <code><a href='cells_stub.html'>cells_stub()</a></code>, and
-<code><a href='cells_column_labels.html'>cells_column_labels()</a></code> helper functions can be used here. We can enclose
-several of these calls within a <code><a href='https://rdrr.io/r/base/list.html'>list()</a></code> if we wish to make the
-transformation happen at different locations.</p></td>
-    </tr>
-    <tr>
-      <th>fn</th>
-      <td><p>The function to use for text transformation.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>An object of class <code>gt_tbl</code>.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_text_transform_1.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>3-12</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Format Data: 
-<code><a href='data_color.html'>data_color</a>()</code>,
-<code><a href='fmt_currency.html'>fmt_currency</a>()</code>,
-<code><a href='fmt_datetime.html'>fmt_datetime</a>()</code>,
-<code><a href='fmt_date.html'>fmt_date</a>()</code>,
-<code><a href='fmt_markdown.html'>fmt_markdown</a>()</code>,
-<code><a href='fmt_missing.html'>fmt_missing</a>()</code>,
-<code><a href='fmt_number.html'>fmt_number</a>()</code>,
-<code><a href='fmt_passthrough.html'>fmt_passthrough</a>()</code>,
-<code><a href='fmt_percent.html'>fmt_percent</a>()</code>,
-<code><a href='fmt_scientific.html'>fmt_scientific</a>()</code>,
-<code><a href='fmt_time.html'>fmt_time</a>()</code>,
-<code><a href='fmt.html'>fmt</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Use `exibble` to create a gt table;</span>
-<span class='co'># transform the formatted text in the</span>
-<span class='co'># `num` and `currency` columns using</span>
-<span class='co'># a function within `text_transform()`,</span>
-<span class='co'># where `x` is a formatted vector of</span>
-<span class='co'># column values</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='no'>exibble</span> <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>num</span>, <span class='no'>char</span>, <span class='no'>currency</span>) <span class='kw'>%&gt;%</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/slice.html'>slice</a></span>(<span class='fl'>1</span>:<span class='fl'>4</span>) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_number.html'>fmt_number</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='fmt_currency.html'>fmt_currency</a></span>(<span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>currency</span>)) <span class='kw'>%&gt;%</span>
-  <span class='fu'>text_transform</span>(
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(
-      <span class='kw'>columns</span> <span class='kw'>=</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>num</span>)),
-    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
-      <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(
-        <span class='no'>x</span>, <span class='st'>" ("</span>,
-        <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/case_when.html'>case_when</a></span>(
-          <span class='no'>x</span> <span class='kw'>&gt;</span> <span class='fl'>20</span>   ~ <span class='st'>"large"</span>,
-          <span class='no'>x</span> <span class='kw'>&lt;=</span> <span class='fl'>20</span>  ~ <span class='st'>"small"</span>),
-        <span class='st'>")"</span>)
-    }
-  )</div></pre>
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diff --git a/docs/reference/web_image.html b/docs/reference/web_image.html
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-<meta property="og:description" content="We can flexibly add a web image inside of a table with web_image()
-function. The function provides a convenient way to generate an HTML fragment
-with an image URL. Because this function is currently HTML-based, it is only
-useful for HTML table output. To use this function inside of data cells, it
-is recommended that the text_transform() function is used. With that
-function, we can specify which data cells to target and then include a
-web_image() call within the required user-defined function (for the fn
-argument). If we want to include an image in other places (e.g., in the
-header, within footnote text, etc.) we need to use web_image() within the
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-    <h1>Helper function for adding an image from the web</h1>
-    <small class="dont-index">Source: <a href='https://github.com/rstudio/gt/blob/master/R/image.R'><code>R/image.R</code></a></small>
-    <div class="hidden name"><code>web_image.Rd</code></div>
-    </div>
-
-    <div class="ref-description">
-    <p>We can flexibly add a web image inside of a table with <code>web_image()</code>
-function. The function provides a convenient way to generate an HTML fragment
-with an image URL. Because this function is currently HTML-based, it is only
-useful for HTML table output. To use this function inside of data cells, it
-is recommended that the <code><a href='text_transform.html'>text_transform()</a></code> function is used. With that
-function, we can specify which data cells to target and then include a
-<code>web_image()</code> call within the required user-defined function (for the <code>fn</code>
-argument). If we want to include an image in other places (e.g., in the
-header, within footnote text, etc.) we need to use <code>web_image()</code> within the
-<code><a href='html.html'>html()</a></code> helper function.</p>
-    </div>
-
-    <pre class="usage"><span class='fu'>web_image</span>(<span class='no'>url</span>, <span class='kw'>height</span> <span class='kw'>=</span> <span class='fl'>30</span>)</pre>
-
-    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
-    <table class="ref-arguments">
-    <colgroup><col class="name" /><col class="desc" /></colgroup>
-    <tr>
-      <th>url</th>
-      <td><p>A url that resolves to an image file.</p></td>
-    </tr>
-    <tr>
-      <th>height</th>
-      <td><p>The absolute height (px) of the image in the table cell.</p></td>
-    </tr>
-    </table>
-
-    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
-
-    <p>A character object with an HTML fragment that can be placed inside of
-a cell.</p>
-    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
-
-    <p>By itself, the function creates an HTML image tag, so, the call
-<code>web_image("http://some.web.site/image.png")</code> evaluates to:</p>
-<p><code>&lt;img src=\"http://some.web.site/image.png\" style=\"height:30px;\"&gt;</code></p>
-<p>where a height of <code>30px</code> is a default height chosen to work well within the
-heights of most table rows.</p>
-    <h2 class="hasAnchor" id="figures"><a class="anchor" href="#figures"></a>Figures</h2>
-
-    
-
-<p><img src='figures/man_web_image_1.png' width=100% /></p>
-<p><img src='figures/man_web_image_2.png' width=100% /></p>
-    <h2 class="hasAnchor" id="function-id"><a class="anchor" href="#function-id"></a>Function ID</h2>
-
-    
-
-<p>8-1</p>
-    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
-
-    <div class='dont-index'><p>Other Image Addition Functions: 
-<code><a href='ggplot_image.html'>ggplot_image</a>()</code>,
-<code><a href='local_image.html'>local_image</a>()</code>,
-<code><a href='test_image.html'>test_image</a>()</code></p></div>
-
-    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
-    <pre class="examples"><div class='input'><span class='co'># Get the PNG-based logo for the R</span>
-<span class='co'># Project from an image URL</span>
-<span class='no'>r_png_url</span> <span class='kw'>&lt;-</span>
-  <span class='st'>"https://www.r-project.org/logo/Rlogo.png"</span>
-
-<span class='co'># Create a tibble that contains heights</span>
-<span class='co'># of an image in pixels (one column as a</span>
-<span class='co'># string, the other as numerical values),</span>
-<span class='co'># then, create a gt table; use the</span>
-<span class='co'># `text_transform()` function to insert</span>
-<span class='co'># the R logo PNG image with the various</span>
-<span class='co'># sizes</span>
-<span class='no'>tab_1</span> <span class='kw'>&lt;-</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
-    <span class='kw'>pixels</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)),
-    <span class='kw'>image</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='text_transform.html'>text_transform</a></span>(
-    <span class='kw'>locations</span> <span class='kw'>=</span> <span class='fu'><a href='cells_body.html'>cells_body</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/vars.html'>vars</a></span>(<span class='no'>image</span>)),
-    <span class='kw'>fn</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) {
-      <span class='fu'>web_image</span>(
-        <span class='kw'>url</span> <span class='kw'>=</span> <span class='no'>r_png_url</span>,
-        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/numeric.html'>as.numeric</a></span>(<span class='no'>x</span>)
-      )
-    }
-  )
-
-<span class='co'># Get the SVG-based logo for the R</span>
-<span class='co'># Project from an image URL</span>
-<span class='no'>r_svg_url</span> <span class='kw'>&lt;-</span>
-  <span class='st'>"https://www.r-project.org/logo/Rlogo.svg"</span>
-
-<span class='co'># Create a tibble that contains heights</span>
-<span class='co'># of an image in pixels (one column as a</span>
-<span class='co'># string, the other as numerical values),</span>
-<span class='co'># then, create a gt table; use the</span>
-<span class='co'># `tab_header()` function to insert</span>
-<span class='co'># the R logo SVG image once in the title</span>
-<span class='co'># and five times in the subtitle</span>
-<span class='no'>tab_2</span> <span class='kw'>&lt;-</span>
-  <span class='kw pkg'>dplyr</span><span class='kw ns'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(
-    <span class='kw'>pixels</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)),
-    <span class='kw'>image</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>10</span>, <span class='fl'>35</span>, <span class='fl'>5</span>)
-  ) <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='gt.html'>gt</a></span>() <span class='kw'>%&gt;%</span>
-  <span class='fu'><a href='tab_header.html'>tab_header</a></span>(
-    <span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='html.html'>html</a></span>(
-      <span class='st'>"&lt;strong&gt;R Logo&lt;/strong&gt;"</span>,
-      <span class='fu'>web_image</span>(
-        <span class='kw'>url</span> <span class='kw'>=</span> <span class='no'>r_svg_url</span>,
-        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>50</span>)
-      )
-    ),
-    <span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='fu'><a href='html.html'>html</a></span>(
-      <span class='fu'>web_image</span>(
-        <span class='kw'>url</span> <span class='kw'>=</span> <span class='no'>r_svg_url</span>,
-        <span class='kw'>height</span> <span class='kw'>=</span> <span class='fu'><a href='px.html'>px</a></span>(<span class='fl'>12</span>)
-      ) <span class='kw'>%&gt;%</span>
-        <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='fl'>5</span>)
-    )
-  )</div></pre>
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-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_align.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_hide.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_label.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_merge.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_merge_range.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_merge_uncert.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_move.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_move_to_end.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_move_to_start.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/cols_width.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/countrypops.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/currency.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/data_color.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/escape_latex.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/exibble.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/extract_summary.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_currency.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_date.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_datetime.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_markdown.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_missing.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_number.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_passthrough.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_percent.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_scientific.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/fmt_time.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/ggplot_image.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/grand_summary_rows.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gt-options.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gt-package.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gt.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gt_latex_dependencies.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gt_output.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gt_preview.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gtcars.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/gtsave.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/html.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/info_currencies.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/info_date_style.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/info_locales.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/info_paletteer.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/info_time_style.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/local_image.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/md.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/opt_align_table_header.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/opt_all_caps.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/opt_footnote_marks.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/opt_row_striping.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/opt_table_lines.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/opt_table_outline.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/pct.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/pipe.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/pizzaplace.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/print.gt_tbl.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/px.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/random_id.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/reexports.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/render_gt.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/row_group_order.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/sp500.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/summary_rows.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/sza.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_footnote.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_header.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_options.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_row_group.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_source_note.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_spanner.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_spanner_delim.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_stubhead.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/tab_style.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/test_image.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/text_transform.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/reference/web_image.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/articles/case-study-gtcars.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/articles/creating-summary-lines.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/articles/gt-datasets.html</loc>
-  </url>
-  <url>
-    <loc>https://gt.rstudio.com/articles/intro-creating-gt-tables.html</loc>
-  </url>
-</urlset>
diff --git a/vignettes/images/countrypops.png b/man/figures/countrypops.png
similarity index 100%
rename from vignettes/images/countrypops.png
rename to man/figures/countrypops.png
diff --git a/vignettes/images/exibble.svg b/man/figures/exibble.svg
similarity index 100%
rename from vignettes/images/exibble.svg
rename to man/figures/exibble.svg
diff --git a/vignettes/images/gtcars.svg b/man/figures/gtcars.svg
similarity index 100%
rename from vignettes/images/gtcars.svg
rename to man/figures/gtcars.svg
diff --git a/vignettes/images/pizzaplace.svg b/man/figures/pizzaplace.svg
similarity index 100%
rename from vignettes/images/pizzaplace.svg
rename to man/figures/pizzaplace.svg
diff --git a/vignettes/images/sp500.svg b/man/figures/sp500.svg
similarity index 100%
rename from vignettes/images/sp500.svg
rename to man/figures/sp500.svg
diff --git a/vignettes/images/sza.svg b/man/figures/sza.svg
similarity index 100%
rename from vignettes/images/sza.svg
rename to man/figures/sza.svg
diff --git a/vignettes/images/tables_from_the_web.png b/man/figures/tables_from_the_web.png
similarity index 100%
rename from vignettes/images/tables_from_the_web.png
rename to man/figures/tables_from_the_web.png
diff --git a/vignettes/case-study-gtcars.Rmd b/vignettes/case-study-gtcars.Rmd
index 958101a89..f18eade0d 100644
--- a/vignettes/case-study-gtcars.Rmd
+++ b/vignettes/case-study-gtcars.Rmd
@@ -17,7 +17,7 @@ library(dplyr)
 library(tibble)
 ```
 
-<p align="center"><img src="images/gtcars.svg" width=50%></p>
+<p align="center"><img src="../reference/figures/gtcars.svg" width=50%></p>
 
 Let's make a display table using the `gtcars` dataset. We all know `mtcars`... what is `gtcars`? It's basically a modernized `mtcars` for the **gt** age. It's part of the **gt** package, and here is a preview of the tibble:
 
diff --git a/vignettes/gt-datasets.Rmd b/vignettes/gt-datasets.Rmd
index 048b56e45..108a5b901 100644
--- a/vignettes/gt-datasets.Rmd
+++ b/vignettes/gt-datasets.Rmd
@@ -19,9 +19,9 @@ library(tidyr)
 
 The **gt** package comes with six built-in datasets for experimenting with the **gt** API: `countrypops`, `sza`, `gtcars`, `sp500`, `pizzaplace`, and `exibble`. While each dataset has different subject matter, all of them will be used to develop **gt** examples with consistent syntax.
 
-<img src="images/countrypops.png" width=30%><img src="images/sza.svg" width=30%><img src="images/gtcars.svg" width=30%>
+<img src="../reference/figures/countrypops.png" width=30%><img src="../reference/figures/sza.svg" width=30%><img src="../reference/figures/gtcars.svg" width=30%>
 
-<img src="images/sp500.svg" width=30%><img src="images/pizzaplace.svg" width=30%><img src="images/exibble.svg" width=30%>
+<img src="../reference/figures/sp500.svg" width=30%><img src="../reference/figures/pizzaplace.svg" width=30%><img src="../reference/figures/exibble.svg" width=30%>
 
 Each dataset is stored as a tibble, ranging from very small (like `exibble`, an example tibble of 8 rows) to quite large in size (e.g., at nearly 50,000 rows: `pizzaplace`). Larger datasets are typically impractical as **gt output tables** but they provide opportunities for demonstrating preprocessing using tidyverse tools like **dplyr** and **tidyr** (upstream of **gt**'s `gt()` entry point). 
 
diff --git a/vignettes/intro-creating-gt-tables.Rmd b/vignettes/intro-creating-gt-tables.Rmd
index 2ded095ae..7a6f502b3 100644
--- a/vignettes/intro-creating-gt-tables.Rmd
+++ b/vignettes/intro-creating-gt-tables.Rmd
@@ -1,6 +1,8 @@
 ---
 title: "Introduction to Creating gt Tables"
-output: rmarkdown::html_vignette
+output: 
+  rmarkdown::html_vignette:
+    self_contained: true
 vignette: >
   %\VignetteIndexEntry{Intro to Creating gt Tables}
   %\VignetteEngine{knitr::rmarkdown}
@@ -18,7 +20,7 @@ library(dplyr)
 
 The **gt** package is all about making it simple to produce nice-looking display tables. Display tables? Well yes, we are trying to distinguish between data tables (e.g., tibbles, `data.frame`s, etc.) and those tables you'd find in a web page, a journal article, or in a magazine. Such tables can likewise be called presentation tables, summary tables, or just tables really. Here are some examples, ripped straight from the web:
 
-<img src="images/tables_from_the_web.png" width=100%>
+<img src="../reference/figures/tables_from_the_web.png" width=100%>
 
 We can think of display tables as output only, where we'd not want to use them as input ever again. Other features include annotations, table element styling, and text transformations that serve to communicate the subject matter more clearly.
 
@@ -63,7 +65,7 @@ The **gt** package makes it relatively easy to add parts so that the resulting *
 
 This is the way the main parts of a table (and their subparts) fit together:
 
-<p align="center"><img src="../man/figures/gt_parts_of_a_table.svg" width=100%></p>
+<p align="center"><img src="../reference/figures/gt_parts_of_a_table.svg" width=100%></p>
 
 The parts (roughly from top to bottom) are:
 

From 4aa4d44dd8c865797976a179a9eaee3b6726f2d5 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 4 May 2020 15:05:15 -0400
Subject: [PATCH 11/30] Update Description of package to be less confusing
 (#569)

* Update DESCRIPTION

* Make further changes to text
---
 DESCRIPTION | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 64d3c7203..da4e312a8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -2,10 +2,13 @@ Type: Package
 Package: gt
 Version: 0.2.0.9000
 Title: Easily Create Presentation-Ready Display Tables
-Description: Build display tables from tabular data using with an easy-to-use
-    API. With its progressive approach, we can construct display tables with a
-    clear separation of concerns: you don't have to decide how the tabular data
-    gets transformed and structured whilst also worrying about aesthetics.
+Description: Build display tables from tabular data with an easy-to-use set of
+    functions. With its progressive approach, we can construct display tables
+    with a cohesive set of table parts. Table values can be formatted using any
+    of the included formatter functions. Footnotes and cell styles can be 
+    precisely added through gt's location targeting system. The way in which gt
+    handles things for you means that you don't often have to worry about the
+    fine details.
 Authors@R: c(
     person("Richard", "Iannone", , "rich@rstudio.com", c("aut", "cre"),
            comment = c(ORCID = "0000-0003-3925-190X")),

From 9f7297a474b94f4cda57ca05488e5309c18c1079 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 4 May 2020 15:47:02 -0400
Subject: [PATCH 12/30] Update GH Actions workflow for R CMD check (#568)

* Revise GH workflow YAML file; add covr to Suggests

* Add more R versions for R CMD check
---
 .github/workflows/R-CMD-check.yaml | 6 +++++-
 DESCRIPTION                        | 1 +
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
index a619c788b..f79888ceb 100644
--- a/.github/workflows/R-CMD-check.yaml
+++ b/.github/workflows/R-CMD-check.yaml
@@ -18,11 +18,15 @@ jobs:
       fail-fast: false
       matrix:
         config:
+          - {os: windows-latest, r: '3.5'}
           - {os: windows-latest, r: '3.6'}
+          - {os: windows-latest, r: '4.0'}
+          - {os: macOS-latest, r: '3.5'}
           - {os: macOS-latest, r: '3.6'}
-          - {os: ubuntu-16.04, r: '3.4', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
+          - {os: macOS-latest, r: '4.0'}
           - {os: ubuntu-16.04, r: '3.5', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
           - {os: ubuntu-16.04, r: '3.6', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04, r: '4.0', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
 
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
diff --git a/DESCRIPTION b/DESCRIPTION
index da4e312a8..a94280435 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -42,6 +42,7 @@ Imports:
     tibble (>= 3.0.0),
     tidyselect (>= 1.0.0)
 Suggests:
+    covr,
     knitr,
     paletteer,
     testthat (>= 2.1.0),

From 91259d1a054c4326c551b5557fe188093b186421 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 4 May 2020 17:03:20 -0400
Subject: [PATCH 13/30] Bump cache on pkgdown.yaml for GH workflow (#570)

---
 .github/workflows/pkgdown.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml
index 0ec9d2862..4b573f6ac 100644
--- a/.github/workflows/pkgdown.yaml
+++ b/.github/workflows/pkgdown.yaml
@@ -24,8 +24,8 @@ jobs:
         uses: actions/cache@v1
         with:
           path: ${{ env.R_LIBS_USER }}
-          key: macOS-r-3.6-${{ hashFiles('depends.Rds') }}
-          restore-keys: macOS-r-3.6-
+          key: macOS-r-3.6-1-${{ hashFiles('depends.Rds') }}
+          restore-keys: macOS-r-3.6-1
 
       - name: Install dependencies
         run: |

From 26f699a8fdca9a14109e9ddaa901776400149049 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 4 May 2020 19:41:35 -0400
Subject: [PATCH 14/30] Squelch warnings from tibble 3.0.0/3.0.1 (#557)

* Avoid subsetting with OOB values

The change is identical in tibble 3.0.0 and we avoid a tibble warning. See https://cran.r-project.org/web/packages/tibble/vignettes/invariants.html for details (example is `df[10, ]`).

* Update min version requirement for tibble

* Modify creation of 0-row tibble

And roll back the requirement for the latest version of tibble.

* Use `if (interactive()) {` around examples that write files

This solution looks pretty nice in the internal help docs and in the pkgdown site (i.e., doesn't add cleanup lines in-between the example calls). Plus it shouldn't be flagged by a CRAN reviewer.

* Update NEWS.md
---
 NEWS.md       |  2 ++
 R/dt_styles.R | 14 +++++++-------
 R/export.R    |  4 +++-
 man/gtsave.Rd |  4 +++-
 4 files changed, 15 insertions(+), 9 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index 6085e16ec..ab765bb65 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,7 @@
 # gt 0.2.0.9000 (in development)
 
+* Ensure compatibility with **tibble** 3.0.0. PR: [#557](https://github.com/rstudio/gt/pull/557).
+
 # gt 0.2.0.5
 
 * New package with 80 exported functions for building display tables
diff --git a/R/dt_styles.R b/R/dt_styles.R
index 1f111657e..cb081c846 100644
--- a/R/dt_styles.R
+++ b/R/dt_styles.R
@@ -13,14 +13,14 @@ dt_styles_set <- function(data, styles) {
 dt_styles_init <- function(data) {
 
   dplyr::tibble(
-    locname = NA_character_,
-    grpname = NA_character_,
-    colname = NA_character_,
-    locnum = NA_real_,
-    rownum = NA_integer_,
-    colnum = NA_integer_,
+    locname = character(0),
+    grpname = character(0),
+    colname = character(0),
+    locnum = numeric(0),
+    rownum = integer(0),
+    colnum = integer(0),
     styles = list()
-  )[-1, ] %>%
+  ) %>%
     dt_styles_set(styles = ., data = data)
 }
 
diff --git a/R/export.R b/R/export.R
index f218e7b76..3c1a6ee76 100644
--- a/R/export.R
+++ b/R/export.R
@@ -41,7 +41,8 @@
 #'   function.
 #'
 #' @examples
-#' \donttest{
+#' if (interactive()) {
+#'
 #' # Use `gtcars` to create a gt table; add
 #' # a stubhead label to describe what is
 #' # in the stub
@@ -81,6 +82,7 @@
 #' # document
 #' tab_1 %>%
 #'   gtsave("tab_1.tex", path = tempdir())
+#'
 #' }
 #'
 #' @family Export Functions
diff --git a/man/gtsave.Rd b/man/gtsave.Rd
index c125530db..ed60a338a 100644
--- a/man/gtsave.Rd
+++ b/man/gtsave.Rd
@@ -58,7 +58,8 @@ to \code{...}.
 }
 
 \examples{
-\dontrun{
+if (interactive()) {
+
 # Use `gtcars` to create a gt table; add
 # a stubhead label to describe what is
 # in the stub
@@ -98,6 +99,7 @@ tab_1 \%>\%
 # document
 tab_1 \%>\%
   gtsave("tab_1.tex", path = tempdir())
+
 }
 
 }

From b2ee76bf93522624b6d216425ee2fa9a3896a88e Mon Sep 17 00:00:00 2001
From: Hadley Wickham <h.wickham@gmail.com>
Date: Thu, 7 May 2020 16:14:37 -0500
Subject: [PATCH 15/30] Remove test of scales behaviour

---
 tests/testthat/test-data_color.R | 12 ------------
 1 file changed, 12 deletions(-)

diff --git a/tests/testthat/test-data_color.R b/tests/testthat/test-data_color.R
index e02049bcc..ab191c3e7 100644
--- a/tests/testthat/test-data_color.R
+++ b/tests/testthat/test-data_color.R
@@ -625,18 +625,6 @@ test_that("the correct color values are obtained when defining a palette", {
       )
   )
 
-  # Expect an error when providing an `NA` along
-  # with valid color names to `colors`
-  expect_error(
-    test_tbl %>%
-      gt() %>%
-      data_color(
-        columns = vars(min_sza),
-        colors = c("green", "blue", NA),
-        autocolor_text = TRUE
-      )
-  )
-
   # Expect an error when providing a numeric vector
   # to `colors`
   expect_error(

From a33ed2845674876db5103311ace03ef95b475e05 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 15 May 2020 15:13:50 -0400
Subject: [PATCH 16/30] Update failing example (#586)

---
 R/format_data.R    |  2 +-
 man/fmt_percent.Rd |  2 +-
 man/gt-package.Rd  | 11 +++++++----
 3 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/R/format_data.R b/R/format_data.R
index 5f426fc37..5615ff306 100644
--- a/R/format_data.R
+++ b/R/format_data.R
@@ -501,7 +501,7 @@ fmt_symbol <- function(data,
 #'   pizzaplace %>%
 #'   dplyr::mutate(month = as.numeric(substr(date, 6, 7))) %>%
 #'   dplyr::group_by(month) %>%
-#'   dplyr::summarize(pizzas_sold = n()) %>%
+#'   dplyr::summarize(pizzas_sold = dplyr::n()) %>%
 #'   dplyr::ungroup() %>%
 #'   dplyr::mutate(frac_of_quota = pizzas_sold / 4000) %>%
 #'   gt(rowname_col = "month") %>%
diff --git a/man/fmt_percent.Rd b/man/fmt_percent.Rd
index 8ae32f000..8ac5ea231 100644
--- a/man/fmt_percent.Rd
+++ b/man/fmt_percent.Rd
@@ -116,7 +116,7 @@ tab_1 <-
   pizzaplace \%>\%
   dplyr::mutate(month = as.numeric(substr(date, 6, 7))) \%>\%
   dplyr::group_by(month) \%>\%
-  dplyr::summarize(pizzas_sold = n()) \%>\%
+  dplyr::summarize(pizzas_sold = dplyr::n()) \%>\%
   dplyr::ungroup() \%>\%
   dplyr::mutate(frac_of_quota = pizzas_sold / 4000) \%>\%
   gt(rowname_col = "month") \%>\%
diff --git a/man/gt-package.Rd b/man/gt-package.Rd
index 005863cfb..1a3850743 100644
--- a/man/gt-package.Rd
+++ b/man/gt-package.Rd
@@ -6,10 +6,13 @@
 \alias{_PACKAGE}
 \title{gt: Easily Create Presentation-Ready Display Tables}
 \description{
-Build display tables from tabular data using with an easy-to-use
-    API. With its progressive approach, we can construct display tables with a
-    clear separation of concerns: you don't have to decide how the tabular data
-    gets transformed and structured whilst also worrying about aesthetics.
+Build display tables from tabular data with an easy-to-use set of
+    functions. With its progressive approach, we can construct display tables
+    with a cohesive set of table parts. Table values can be formatted using any
+    of the included formatter functions. Footnotes and cell styles can be 
+    precisely added through gt's location targeting system. The way in which gt
+    handles things for you means that you don't often have to worry about the
+    fine details.
 }
 \seealso{
 Useful links:

From 1e42417c3be55a675d6da9274f1ef21884db9bdf Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Thu, 21 May 2020 18:40:43 -0400
Subject: [PATCH 17/30] Ensure that row ordering doesn't affect summary row
 calculations (#556)

* Update @examples section of `gtsave()`

Strangely, changes to `export.R` were not checked in as part of https://github.com/rstudio/gt/pull/527 (the roxygenized .Rd was, however). This change ensures that the source doc is now in sync.

* Update example in `fmt_percent()` fcn

* Ensure that row ordering doesn't affect summary calcs

* Make changes based on code review comments

* Add one more testthat test

* Update NEWS.md

* Update NEWS.md
---
 NEWS.md                            |   4 +-
 R/dt_summary.R                     |  22 ++--
 R/export.R                         |   1 -
 tests/testthat/test-summary_rows.R | 159 +++++++++++++++++++++++++++++
 4 files changed, 173 insertions(+), 13 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index ab765bb65..a03ecb286 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,8 @@
 # gt 0.2.0.9000 (in development)
 
-* Ensure compatibility with **tibble** 3.0.0. PR: [#557](https://github.com/rstudio/gt/pull/557).
+* `summary_rows()` and `grand_summary_rows()` no longer incorrectly calculate summary values in cases where rows aren't already sorted by group (#556).
+
+* Ensure compatibility with **tibble** 3.0.0 (#557).
 
 # gt 0.2.0.5
 
diff --git a/R/dt_summary.R b/R/dt_summary.R
index 040d0582b..7c71f206a 100644
--- a/R/dt_summary.R
+++ b/R/dt_summary.R
@@ -70,6 +70,7 @@ dt_summary_build <- function(data,
   body <- dt_body_get(data = data)
   data_tbl <- dt_data_get(data = data)
   stub_df <- dt_stub_df_get(data = data)
+  boxh_df <- dt_boxhead_get(data = data)
 
   # If the `summary_list` object is an empty list,
   # return an empty list as the `list_of_summaries`
@@ -170,21 +171,20 @@ dt_summary_build <- function(data,
     if (identical(groups, grand_summary_col)) {
 
       select_data_tbl <-
-        cbind(
-          stub_df[c("groupname", "rowname")],
-          data_tbl
-        )[, -2] %>%
-        dplyr::mutate(groupname = grand_summary_col) %>%
-        dplyr::select(groupname, columns)
+        data_tbl %>%
+        dplyr::select(!!columns) %>%
+        dplyr::mutate(groupname = !!grand_summary_col) %>%
+        dplyr::select(groupname, !!columns) %>%
+        as.data.frame(stringsAsFactors = FALSE)
 
     } else {
 
       select_data_tbl <-
-        cbind(
-          stub_df[c("groupname", "rowname")],
-          data_tbl
-        )[, -2] %>%
-        dplyr::select(groupname, columns)
+        dplyr::bind_cols(
+          stub_df %>% dplyr::select(groupname),
+          data_tbl[stub_df$rownum_i, columns]
+        ) %>%
+        as.data.frame(stringsAsFactors = FALSE)
     }
 
     # Get the registered function calls
diff --git a/R/export.R b/R/export.R
index 3c1a6ee76..8313ea30f 100644
--- a/R/export.R
+++ b/R/export.R
@@ -82,7 +82,6 @@
 #' # document
 #' tab_1 %>%
 #'   gtsave("tab_1.tex", path = tempdir())
-#'
 #' }
 #'
 #' @family Export Functions
diff --git a/tests/testthat/test-summary_rows.R b/tests/testthat/test-summary_rows.R
index 11be6ef71..ad61876a1 100644
--- a/tests/testthat/test-summary_rows.R
+++ b/tests/testthat/test-summary_rows.R
@@ -20,6 +20,14 @@ tbl <-
     groupname_col = "week"
   )
 
+# Gets the inner HTML text from a single value
+selection_text <- function(html, selection) {
+
+  html %>%
+    rvest::html_nodes(selection) %>%
+    rvest::html_text()
+}
+
 test_that("the `summary_rows()` can make groupwise summaries", {
 
   # Create a table with summary rows for
@@ -819,6 +827,157 @@ test_that("`groups = FALSE` returns data unchanged", {
   )
 })
 
+test_that("the ordering of groups shouldn't affect group/grand summary calcs", {
+
+  # Create tibbles with rows in different orders
+  tbl_1 <-
+    tibble::tibble(
+      id = c("1", "2", "3", "4", "5", "6"),
+      value = c(1, 10, 1, 10, 99, 1),
+      group = c("b", "a", "b", "a", "c", "b")
+    )
+
+  tbl_2 <-
+    tbl_1 %>%
+    dplyr::slice(6, 3, 5, 1, 4, 2)
+
+  tbl_3 <-
+    tbl_2 %>%
+    dplyr::arrange(group, id)
+
+  # Prepare a set gt tables with summary rows (using the same
+  # `summary_rows()` call each time)
+  gt_tbl_1 <-
+    tbl_1 %>%
+    dplyr::group_by(group) %>%
+    gt(rowname_col = "id") %>%
+    summary_rows(groups = TRUE, columns = vars(value), fns = list("sum"))
+
+  gt_tbl_1b <-
+    tbl_1 %>%
+    gt(rowname_col = "id", groupname_col = "group") %>%
+    summary_rows(groups = TRUE, columns = vars(value), fns = list("sum"))
+
+  gt_tbl_2 <-
+    tbl_2 %>%
+    gt(rowname_col = "id", groupname_col = "group") %>%
+    summary_rows(groups = TRUE, columns = vars(value), fns = list("sum"))
+
+  gt_tbl_3 <-
+    tbl_3 %>%
+    gt(rowname_col = "id", groupname_col = "group") %>%
+    summary_rows(groups = TRUE, columns = vars(value), fns = list("sum"))
+
+  # Expect the correct values in summary rows of `gt_tbl`
+  gt_tbl_1 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_summary_row gt_first_summary_row']") %>%
+    expect_equal(c("3.00", "20.00", "99.00"))
+
+  # Expect the HTML output tables of `gt_tbl_1` and `gt_tbl_1b` to be the same
+  expect_identical(
+    gt_tbl_1 %>% render_as_html(),
+    gt_tbl_1b %>% render_as_html()
+  )
+
+  # Expect the correct values in summary rows of `gt_tbl_2`
+  gt_tbl_2 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_summary_row gt_first_summary_row']") %>%
+    expect_equal(c("3.00", "99.00", "20.00"))
+
+  # Expect the correct values in summary rows of `gt_tbl_3`
+  gt_tbl_3 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_summary_row gt_first_summary_row']") %>%
+    expect_equal(c("20.00", "3.00", "99.00"))
+
+  # Prepare a set gt tables with a grand summary (using the same
+  # `grand_summary_rows()` call each time)
+  gt_tbl_1_gs <-
+    tbl_1 %>%
+    dplyr::group_by(group) %>%
+    gt(rowname_col = "id") %>%
+    grand_summary_rows(columns = vars(value), fns = list("sum"))
+
+  gt_tbl_1b_gs <-
+    tbl_1 %>%
+    gt(rowname_col = "id", groupname_col = "group") %>%
+    grand_summary_rows(columns = vars(value), fns = list("sum"))
+
+  gt_tbl_2_gs <-
+    tbl_2 %>%
+    gt(rowname_col = "id", groupname_col = "group") %>%
+    grand_summary_rows(columns = vars(value), fns = list("sum"))
+
+  gt_tbl_3_gs <-
+    tbl_3 %>%
+    gt(rowname_col = "id", groupname_col = "group") %>%
+    grand_summary_rows(columns = vars(value), fns = list("sum"))
+
+  # Expect the correct value in the grand summary row of `gt_tbl_gs`
+  gt_tbl_1_gs %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row']") %>%
+    expect_equal(c("122.00"))
+
+  # Expect the HTML output tables of `gt_tbl_gs` and `gt_tbl_1b_gs` to be the same
+  expect_identical(
+    gt_tbl_1_gs %>% render_as_html(),
+    gt_tbl_1b_gs %>% render_as_html()
+  )
+
+  # Expect the correct value in the grand summary row of `gt_tbl_2_gs`
+  gt_tbl_2_gs %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row']") %>%
+    expect_equal(c("122.00"))
+
+  # Expect the correct value in the grand summary row of `gt_tbl_3_gs`
+  gt_tbl_3_gs %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row']") %>%
+    expect_equal(c("122.00"))
+
+  # Example where a columns is named `columns`
+  tbl_4 <-
+    tibble::tibble(
+      id = c("1", "2", "3", "4", "5", "6"),
+      value = c(1, 10, 1, 10, 99, 1),
+      columns = c(2, 20, 2, 20, 198, 2),
+      group = c("b", "a", "b", "a", "c", "b")
+    )
+
+  gt_tbl_4 <-
+    tbl_4 %>%
+    dplyr::group_by(group) %>%
+    gt(rowname_col = "id") %>%
+    summary_rows(groups = TRUE, columns = vars(value, columns), fns = list("sum")) %>%
+    grand_summary_rows(columns = vars(value, columns), fns = list("sum"))
+
+  # Expect the correct values in summary rows of `gt_tbl_4`
+  gt_tbl_4 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_summary_row gt_first_summary_row']") %>%
+    expect_equal(c("3.00", "6.00", "20.00", "40.00", "99.00", "198.00"))
+
+  # Expect the correct values in the grand summary row of `gt_tbl_4`
+  gt_tbl_4 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row']") %>%
+    expect_equal(c("122.00", "244.00"))
+
+  gt_tbl_5 <-
+    tbl_4 %>%
+    dplyr::rename(grand_summary_col = columns) %>%
+    dplyr::group_by(group) %>%
+    gt(rowname_col = "id") %>%
+    summary_rows(groups = TRUE, columns = vars(value, grand_summary_col), fns = list("sum")) %>%
+    grand_summary_rows(columns = vars(value, grand_summary_col), fns = list("sum"))
+
+  # Expect the correct values in summary rows of `gt_tbl_4`
+  gt_tbl_5 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_summary_row gt_first_summary_row']") %>%
+    expect_equal(c("3.00", "6.00", "20.00", "40.00", "99.00", "198.00"))
+
+  # Expect the correct values in the grand summary row of `gt_tbl_4`
+  gt_tbl_5 %>% render_as_html() %>% xml2::read_html() %>%
+    selection_text("[class='gt_row gt_right gt_grand_summary_row gt_first_grand_summary_row']") %>%
+    expect_equal(c("122.00", "244.00"))
+})
+
 test_that("summary rows can be created when there is no stub", {
 
   # Create a table based on `sp500`, with

From 20f99d6068e2d707cf4a09b593af30ecb506df52 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Tue, 26 May 2020 15:54:23 -0400
Subject: [PATCH 18/30] Release gt 0.2.1 (#588)

* Update DESCRIPTION and NEWS.md

* Update NEWS.md

* Merge branch 'master' into v0.2.1-rc

* master:
  Ensure that row ordering doesn't affect summary row calculations (#556)

* Update NEWS.md

* Update DESCRIPTION
---
 DESCRIPTION | 6 +++---
 NEWS.md     | 6 ++++--
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index a94280435..aef13b476 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,12 +1,12 @@
 Type: Package
 Package: gt
-Version: 0.2.0.9000
+Version: 0.2.1
 Title: Easily Create Presentation-Ready Display Tables
 Description: Build display tables from tabular data with an easy-to-use set of
     functions. With its progressive approach, we can construct display tables
     with a cohesive set of table parts. Table values can be formatted using any
-    of the included formatter functions. Footnotes and cell styles can be 
-    precisely added through gt's location targeting system. The way in which gt
+    of the included formatting functions. Footnotes and cell styles can be 
+    precisely added through a location targeting system. The way in which 'gt'
     handles things for you means that you don't often have to worry about the
     fine details.
 Authors@R: c(
diff --git a/NEWS.md b/NEWS.md
index a03ecb286..d2261c5c9 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,10 +1,12 @@
-# gt 0.2.0.9000 (in development)
+# gt 0.2.1
 
 * `summary_rows()` and `grand_summary_rows()` no longer incorrectly calculate summary values in cases where rows aren't already sorted by group (#556).
 
 * Ensure compatibility with **tibble** 3.0.0 (#557).
 
-# gt 0.2.0.5
+* Adapt tests to changes in dependent packages (#575)
+
+# gt 0.2.0.5 (2020-03-31)
 
 * New package with 80 exported functions for building display tables
 

From c13b00aae92ae487b3c68d5be7932b35a4291f4f Mon Sep 17 00:00:00 2001
From: Barret Schloerke <barret@rstudio.com>
Date: Fri, 29 May 2020 15:26:03 -0400
Subject: [PATCH 19/30] Update R-CMD-check.yaml (#599)

* Update R-CMD-check.yaml

* Use new cache key

* Add process. Install on all platforms

* Don't use cache

* Use cache with new key. Install pillar
---
 .github/workflows/R-CMD-check.yaml | 47 ++++++++++++++++++------------
 1 file changed, 29 insertions(+), 18 deletions(-)

diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
index f79888ceb..b650973d5 100644
--- a/.github/workflows/R-CMD-check.yaml
+++ b/.github/workflows/R-CMD-check.yaml
@@ -12,33 +12,32 @@ jobs:
   R-CMD-check:
     runs-on: ${{ matrix.config.os }}
 
-    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+    name: ${{ matrix.config.os }} (${{ matrix.r }})
 
     strategy:
       fail-fast: false
       matrix:
+        r: 
+          - '3.5'
+          - '3.6'
+          - '4.0'
         config:
-          - {os: windows-latest, r: '3.5'}
-          - {os: windows-latest, r: '3.6'}
-          - {os: windows-latest, r: '4.0'}
-          - {os: macOS-latest, r: '3.5'}
-          - {os: macOS-latest, r: '3.6'}
-          - {os: macOS-latest, r: '4.0'}
-          - {os: ubuntu-16.04, r: '3.5', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04, r: '3.6', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
-          - {os: ubuntu-16.04, r: '4.0', rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
+          - {os: windows-latest}
+          - {os: macOS-latest}
+          - {os: ubuntu-16.04, rspm: "https://demo.rstudiopm.com/all/__linux__/xenial/latest"}
 
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
       _R_CHECK_FORCE_SUGGESTS_: false
       RSPM: ${{ matrix.config.rspm }}
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
 
     steps:
       - uses: actions/checkout@v2
 
       - uses: r-lib/actions/setup-r@master
         with:
-          r-version: ${{ matrix.config.r }}
+          r-version: ${{ matrix.r }}
 
       - uses: r-lib/actions/setup-pandoc@master
 
@@ -53,8 +52,16 @@ jobs:
         uses: actions/cache@v1
         with:
           path: ${{ env.R_LIBS_USER }}
-          key: ${{ runner.os }}-r-${{ matrix.config.r }}-${{ hashFiles('depends.Rds') }}
-          restore-keys: ${{ runner.os }}-r-${{ matrix.config.r }}-
+          key: ${{ runner.os }}-r-${{ matrix.r }}-2-${{ hashFiles('depends.Rds') }}
+          restore-keys: ${{ runner.os }}-r-${{ matrix.r }}-2-
+      
+      - name: Problematic Pkgs
+        shell: Rscript {0}
+        run: |
+          remotes::install_cran("ellipsis")
+          remotes::install_cran("pillar")
+          remotes::install_cran("ps")
+          remotes::install_cran("processx")
 
       - name: Install system dependencies
         if: runner.os == 'Linux'
@@ -66,23 +73,27 @@ jobs:
           sudo -s eval "$sysreqs"
 
       - name: Install dependencies
+        shell: Rscript {0}
         run: |
           remotes::install_deps(dependencies = TRUE)
-          remotes::install_cran("rcmdcheck")
+
+      - name: Install rcmdcheck
         shell: Rscript {0}
+        run: |
+          remotes::install_cran("rcmdcheck")
 
       - name: Check
-        run: rcmdcheck::rcmdcheck(args = "--no-manual", error_on = "warning", check_dir = "check")
         shell: Rscript {0}
+        run: rcmdcheck::rcmdcheck(args = "--no-manual", error_on = "warning", check_dir = "check")
 
       - name: Upload check results
         if: failure()
         uses: actions/upload-artifact@master
         with:
-          name: ${{ runner.os }}-r${{ matrix.config.r }}-results
+          name: ${{ runner.os }}-r${{ matrix.r }}-results
           path: check
 
       - name: Test coverage
-        if: matrix.config.os == 'macOS-latest' && matrix.config.r == '3.6'
-        run: covr::codecov()
+        if: matrix.config.os == 'macOS-latest' && matrix.r == '3.6'
         shell: Rscript {0}
+        run: covr::codecov()

From 321bfb93f1910c458cb7e57e9de406b31c50b228 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 22 Jun 2020 14:44:42 -0400
Subject: [PATCH 20/30] Refactor `data_color()` so that it executes faster
 (#576)

* Refactor `data_color()` so that it executes faster

* Make changes based on code review
---
 R/data_color.R    | 191 ++++++++++++++++++----------------------------
 man/data_color.Rd |   6 +-
 2 files changed, 76 insertions(+), 121 deletions(-)

diff --git a/R/data_color.R b/R/data_color.R
index 2fea048aa..9d94fcf76 100644
--- a/R/data_color.R
+++ b/R/data_color.R
@@ -56,8 +56,8 @@
 #'   to all of the `colors` provided (regardless of whether a color palette was
 #'   directly supplied or generated through a color mapping function).
 #' @param apply_to Which style element should the colors be applied to? Options
-#'   include the cell background (the default, given as `fill`) or the cell
-#'   text (`text`).
+#'   include the cell background (the default, given as `"fill"`) or the cell
+#'   text (`"text"`).
 #' @param autocolor_text An option to let **gt** modify the coloring of text
 #'   within cells undergoing background coloring. This will in some cases yield
 #'   more optimal text-to-background color contrast. By default, this is set to
@@ -130,15 +130,23 @@ data_color <- function(data,
                        columns,
                        colors,
                        alpha = NULL,
-                       apply_to = "fill",
+                       apply_to = c("fill", "text"),
                        autocolor_text = TRUE) {
 
   # Perform input object validation
   stop_if_not_gt(data = data)
 
+  # Get the correct `apply_to` value
+  apply_to <- match.arg(apply_to)
+
+  colors <- rlang::enquo(colors)
+
   # Get the internal data table
   data_tbl <- dt_data_get(data = data)
 
+  # Evaluate `colors` with `eval_tidy()` (supports quosures)
+  colors <- rlang::eval_tidy(colors, data_tbl)
+
   # Collect the column names from `data_tbl`
   colnames <- names(data_tbl)
 
@@ -147,20 +155,25 @@ data_color <- function(data,
   columns <- rlang::enquo(columns)
   resolved_columns <- resolve_vars(var_expr = !!columns, data = data)
 
+  # Get the sequence of row indices for the table
+  rows <- seq_len(nrow(data_tbl))
+
+  data_color_styles_tbl <-
+    dplyr::tibble(
+      locname = character(0), grpname = character(0), colname = character(0),
+      locnum = numeric(0), rownum = integer(0), colnum = integer(0), styles = list()
+    )
+
   for (column in resolved_columns) {
 
-    data_vals <- data_tbl[[column]]
+    data_vals <- data_tbl[[column]][rows]
 
     if (inherits(colors, "character")) {
 
       if (is.numeric(data_vals)) {
 
-        color_fn <-
-          scales::col_numeric(
-            palette = colors,
-            domain = data_vals,
-            alpha = TRUE
-          )
+        # Create a color function based on `scales::col_numeric()`
+        color_fn <- scales::col_numeric(palette = colors, domain = data_vals, alpha = TRUE)
 
       } else if (is.character(data_vals) || is.factor(data_vals)) {
 
@@ -170,22 +183,20 @@ data_color <- function(data,
         # of levels. Instead, colors should be subsetted. scales does the right
         # thing for palette names though, so we need to screen those cases out.
         if (length(colors) > 1) {
-          nlvl <- if (is.factor(data_vals)) {
-            nlevels(data_vals)
-          } else {
-            nlevels(factor(data_vals))
-          }
+          nlvl <-
+            if (is.factor(data_vals)) {
+              nlevels(data_vals)
+            } else {
+              nlevels(factor(data_vals))
+            }
           if (length(colors) > nlvl) {
             colors <- colors[seq_len(nlvl)]
           }
         }
 
-        color_fn <-
-          scales::col_factor(
-            palette = colors,
-            domain = data_vals,
-            alpha = TRUE
-          )
+        # Create a color function based on `scales::col_factor()`
+        color_fn <- scales::col_factor(palette = colors, domain = data_vals, alpha = TRUE)
+
       } else {
 
         stop("Don't know how to map colors to a column of class ", class(data_vals)[1], ".",
@@ -193,13 +204,17 @@ data_color <- function(data,
       }
 
     } else if (inherits(colors, "function")) {
+
+      # If a color function is directly provided, use as is
       color_fn <- colors
 
     } else {
-      stop("The `colors` arg must be either a character vector of colors or a function", call. = FALSE)
+
+      stop("The `colors` arg must be either a character vector of colors or a function",
+           call. = FALSE)
     }
 
-    color_fn <- rlang::enquo(color_fn)
+    # Evaluate `color_fn` with `eval_tidy()` (supports quosures)
     color_fn <- rlang::eval_tidy(color_fn, data_tbl)
 
     # Evaluate the color function with the data values
@@ -209,112 +224,52 @@ data_color <- function(data,
     # fixed alpha value if necessary
     color_vals <- html_color(colors = color_vals, alpha = alpha)
 
-    for (i in seq_along(data_vals)) {
-
-      color <- color_vals[i]
-
-      if (apply_to == "fill") {
+    color_styles <-
+      switch(
+        apply_to,
+        fill = lapply(color_vals, FUN = function(x) cell_fill(color = x)),
+        text = lapply(color_vals, FUN = function(x) cell_text(color = x))
+      )
+
+    data_color_styles_tbl <-
+      dplyr::bind_rows(
+        data_color_styles_tbl,
+        generate_data_color_styles_tbl(
+          column = column, rows = rows,
+          color_styles = color_styles
+        )
+      )
 
-        # Apply color value to the background of the cell
-        data <-
-          scale_apply_styles(
-            data,
-            column = column,
-            apply_to = apply_to,
-            styles = list(list(color = color)),
-            rows_i = i
-          )
+    if (apply_to == "fill" && autocolor_text) {
 
-      } else if (apply_to == "text") {
+      color_vals <- ideal_fgnd_color(bgnd_color = color_vals)
 
-        # Apply color value to the text within the cell
-        data <-
-          scale_apply_styles(
-            data,
-            column = column,
-            apply_to = apply_to,
-            styles = list(list(color = color)),
-            rows_i = i
-          )
-      }
+      color_styles <- lapply(color_vals, FUN = function(x) cell_text(color = x))
 
-      # If the `autocolor_text` option is TRUE then the coloring
-      # of text will be modified to achieve the highest contrast
-      # possible
-      if (apply_to == "fill" & autocolor_text) {
-
-        # Apply the `ideal_fgnd_color()` function to
-        # the background color value to obtain a suitable
-        # text color
-        color_text <- ideal_fgnd_color(bgnd_color = color)
-
-        # Apply color value to the text of the cell
-        data <-
-          scale_apply_styles(
-            data,
-            column = column,
-            apply_to = "text",
-            styles = list(list(color = color_text)),
-            rows_i = i
+      data_color_styles_tbl <-
+        dplyr::bind_rows(
+          data_color_styles_tbl,
+          generate_data_color_styles_tbl(
+            column = column, rows = rows,
+            color_styles = color_styles
           )
-      }
+        )
     }
   }
 
-  data
+  dt_styles_set(
+    data = data,
+    styles = dplyr::bind_rows(dt_styles_get(data = data), data_color_styles_tbl)
+  )
 }
 
-#' Apply color scale styles to the gt table data
-#'
-#' @noRd
-scale_apply_styles <- function(data,
-                               column,
-                               apply_to,
-                               styles,
-                               rows_i = NULL) {
-
-  data_tbl <- dt_data_get(data = data)
-
-  if (is.null(rows_i)) {
-    rows_i <- seq(nrow(data_tbl))
-  }
-
-  if (length(styles) != length(rows_i)) {
-
-    stop("The lengths of `styles` (", length(styles),
-         ") and of `rows_i` (", length(rows_i), ") must be equal.",
-         call. = FALSE)
-  }
-
-  for (i in seq_along(rows_i)) {
-
-    if (apply_to == "fill") {
-
-      data <-
-        data %>%
-        tab_style(
-          do.call(cell_fill, styles[[i]]),
-          cells_body(
-            columns = column,
-            rows = rows_i[[i]]
-          )
-        )
-
-    } else if (apply_to == "text") {
-
-      data <-
-        data %>%
-        tab_style(
-          do.call(cell_text, styles[[i]]),
-          cells_body(
-            columns = column,
-            rows = rows_i[[i]]
-          )
-        )
-    }
-  }
+generate_data_color_styles_tbl <- function(column, rows, color_styles) {
 
-  data
+  dplyr::tibble(
+    locname = "data", grpname = NA_character_,
+    colname = column, locnum = 5, rownum = rows,
+    styles = color_styles
+  )
 }
 
 #' Are color values in rgba() format?
diff --git a/man/data_color.Rd b/man/data_color.Rd
index 0aae5d01c..f666771ed 100644
--- a/man/data_color.Rd
+++ b/man/data_color.Rd
@@ -9,7 +9,7 @@ data_color(
   columns,
   colors,
   alpha = NULL,
-  apply_to = "fill",
+  apply_to = c("fill", "text"),
   autocolor_text = TRUE
 )
 }
@@ -32,8 +32,8 @@ to all of the \code{colors} provided (regardless of whether a color palette was
 directly supplied or generated through a color mapping function).}
 
 \item{apply_to}{Which style element should the colors be applied to? Options
-include the cell background (the default, given as \code{fill}) or the cell
-text (\code{text}).}
+include the cell background (the default, given as \code{"fill"}) or the cell
+text (\code{"text"}).}
 
 \item{autocolor_text}{An option to let \strong{gt} modify the coloring of text
 within cells undergoing background coloring. This will in some cases yield

From fa66dd98921fe155bab3132915150f610648cded Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 22 Jun 2020 15:08:42 -0400
Subject: [PATCH 21/30] Restore row striping option in stub cells
 (`row.striping.include_stub = TRUE`) (#564)

* Restore row striping in stub

* Update NEWS.md

* Update roxygen documentation
---
 DESCRIPTION                     |  2 +-
 NEWS.md                         |  4 ++++
 inst/css/gt_styles_default.scss |  8 ++++----
 man/data_color.Rd               | 10 +++++-----
 man/gt-package.Rd               |  4 ++--
 man/gtsave.Rd                   |  1 -
 man/reexports.Rd                |  2 +-
 7 files changed, 17 insertions(+), 14 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index aef13b476..656ce97c7 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -23,7 +23,7 @@ BugReports: https://github.com/rstudio/gt/issues
 Encoding: UTF-8
 LazyData: true
 ByteCompile: true
-RoxygenNote: 7.1.0
+RoxygenNote: 7.1.0.9000
 Depends:
     R (>= 3.2.0)
 Imports: 
diff --git a/NEWS.md b/NEWS.md
index d2261c5c9..c11288ad5 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,7 @@
+# gt 0.2.1.9000 (unreleased)
+
+* Restore the ability to have row striping in stub cells (with `tab_option()`'s `row.striping.include_stub = TRUE`). Thanks @gergness for creating the PR that prompted this final fix (#537). PR: #564.
+
 # gt 0.2.1
 
 * `summary_rows()` and `grand_summary_rows()` no longer incorrectly calculate summary values in cases where rows aren't already sorted by group (#556).
diff --git a/inst/css/gt_styles_default.scss b/inst/css/gt_styles_default.scss
index cc9703618..64c71e6fc 100644
--- a/inst/css/gt_styles_default.scss
+++ b/inst/css/gt_styles_default.scss
@@ -163,10 +163,6 @@
     vertical-align: middle;
   }
 
-  .gt_striped {
-     background-color: $row_striping_background_color; // row.striping.background_color
-  }
-
   .gt_from_md > :first-child {
     margin-top: 0;
   }
@@ -246,6 +242,10 @@
     border-top-color: $grand_summary_row_border_color; // grand_summary_row.border.color
   }
 
+  .gt_striped {
+     background-color: $row_striping_background_color; // row.striping.background_color
+  }
+
   .gt_table_body {
     border-top-style: $table_body_border_top_style; // table_body.border.top.style
     border-top-width: $table_body_border_top_width; // table_body.border.top.width
diff --git a/man/data_color.Rd b/man/data_color.Rd
index f666771ed..95c2521b2 100644
--- a/man/data_color.Rd
+++ b/man/data_color.Rd
@@ -21,8 +21,8 @@ data_color(
 \item{colors}{Either a color mapping function from the \strong{scales} package or
 a vector of colors to use for each distinct value or level in each of the
 provided \code{columns}. The color mapping functions are:
-\code{\link[scales:col_quantile]{scales::col_quantile()}}, \code{\link[scales:col_bin]{scales::col_bin()}}, \code{\link[scales:col_numeric]{scales::col_numeric()}}, and
-\code{\link[scales:col_factor]{scales::col_factor()}}. If providing a vector of colors as a palette, each
+\code{\link[scales:col_numeric]{scales::col_quantile()}}, \code{\link[scales:col_numeric]{scales::col_bin()}}, \code{\link[scales:col_numeric]{scales::col_numeric()}}, and
+\code{\link[scales:col_numeric]{scales::col_factor()}}. If providing a vector of colors as a palette, each
 color value provided must either be a color name (in the set of colors
 provided by \code{\link[grDevices:colors]{grDevices::colors()}}) or a hexadecimal string in the form of
 "#RRGGBB" or "#RRGGBBAA".}
@@ -63,12 +63,12 @@ the \code{colors} argument. These functions map data values (\code{numeric} or
 \itemize{
 \item \code{\link[scales:col_numeric]{scales::col_numeric()}}: provides a simple linear mapping from
 continuous numeric data to an interpolated palette.
-\item \code{\link[scales:col_bin]{scales::col_bin()}}: provides a mapping of continuous numeric data to
+\item \code{\link[scales:col_numeric]{scales::col_bin()}}: provides a mapping of continuous numeric data to
 value-based bins. This internally uses the \code{\link[base:cut]{base::cut()}} function.
-\item \code{\link[scales:col_quantile]{scales::col_quantile()}}: provides a mapping of continuous
+\item \code{\link[scales:col_numeric]{scales::col_quantile()}}: provides a mapping of continuous
 numeric data to quantiles. This internally uses the
 \code{\link[stats:quantile]{stats::quantile()}} function.
-\item \code{\link[scales:col_factor]{scales::col_factor()}}: provides a mapping of factors to colors. If the
+\item \code{\link[scales:col_numeric]{scales::col_factor()}}: provides a mapping of factors to colors. If the
 palette is discrete and has a different number of colors than the number of
 factors, interpolation is used.
 }
diff --git a/man/gt-package.Rd b/man/gt-package.Rd
index 1a3850743..2631f6801 100644
--- a/man/gt-package.Rd
+++ b/man/gt-package.Rd
@@ -9,8 +9,8 @@
 Build display tables from tabular data with an easy-to-use set of
     functions. With its progressive approach, we can construct display tables
     with a cohesive set of table parts. Table values can be formatted using any
-    of the included formatter functions. Footnotes and cell styles can be 
-    precisely added through gt's location targeting system. The way in which gt
+    of the included formatting functions. Footnotes and cell styles can be 
+    precisely added through a location targeting system. The way in which 'gt'
     handles things for you means that you don't often have to worry about the
     fine details.
 }
diff --git a/man/gtsave.Rd b/man/gtsave.Rd
index ed60a338a..a371d748b 100644
--- a/man/gtsave.Rd
+++ b/man/gtsave.Rd
@@ -99,7 +99,6 @@ tab_1 \%>\%
 # document
 tab_1 \%>\%
   gtsave("tab_1.tex", path = tempdir())
-
 }
 
 }
diff --git a/man/reexports.Rd b/man/reexports.Rd
index 2502a2e43..1105bf771 100644
--- a/man/reexports.Rd
+++ b/man/reexports.Rd
@@ -19,6 +19,6 @@ below to see their documentation.
 \describe{
   \item{dplyr}{\code{\link[dplyr]{vars}}}
 
-  \item{tidyselect}{\code{\link[tidyselect]{contains}}, \code{\link[tidyselect]{ends_with}}, \code{\link[tidyselect]{everything}}, \code{\link[tidyselect]{matches}}, \code{\link[tidyselect]{one_of}}, \code{\link[tidyselect]{starts_with}}}
+  \item{tidyselect}{\code{\link[tidyselect:starts_with]{contains}}, \code{\link[tidyselect:starts_with]{ends_with}}, \code{\link[tidyselect]{everything}}, \code{\link[tidyselect:starts_with]{matches}}, \code{\link[tidyselect]{one_of}}, \code{\link[tidyselect]{starts_with}}}
 }}
 

From 92597d8c651fe42f37bf5e89e1ee6d333f919d5b Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 22 Jun 2020 15:31:41 -0400
Subject: [PATCH 22/30] Add `scale_values` arg to `fmt_percent()` (#565)

* Add `scale_values` arg to `fmt_percent()`

* Update NEWS.md

* Update NEWS.md
---
 NEWS.md                           | 10 ++++++----
 R/format_data.R                   | 22 +++++++++++++++++-----
 man/fmt_percent.Rd                | 15 +++++++++++----
 tests/testthat/test-fmt_percent.R | 11 +++++++++++
 4 files changed, 45 insertions(+), 13 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index c11288ad5..a6795ccfe 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,14 +1,16 @@
-# gt 0.2.1.9000 (unreleased)
+# gt (unreleased)
 
-* Restore the ability to have row striping in stub cells (with `tab_option()`'s `row.striping.include_stub = TRUE`). Thanks @gergness for creating the PR that prompted this final fix (#537). PR: #564.
+* The new `scale_values` argument for `fmt_percent()` makes it easy to use values that are already scaled (and just require the percent mark). Thank you @djohn215 for the suggestion in #559. (#565)
+
+* Restore the ability to have row striping in stub cells (with `tab_option()`'s `row.striping.include_stub = TRUE`). Thanks @gergness for creating PR #537, which prompted this final fix. (#564)
 
 # gt 0.2.1
 
 * `summary_rows()` and `grand_summary_rows()` no longer incorrectly calculate summary values in cases where rows aren't already sorted by group (#556).
 
-* Ensure compatibility with **tibble** 3.0.0 (#557).
+* Ensure compatibility with **tibble** 3.0.0. (#557)
 
-* Adapt tests to changes in dependent packages (#575)
+* Adapt tests to changes in dependent packages. (#575)
 
 # gt 0.2.0.5 (2020-03-31)
 
diff --git a/R/format_data.R b/R/format_data.R
index 5615ff306..3b78967af 100644
--- a/R/format_data.R
+++ b/R/format_data.R
@@ -461,10 +461,11 @@ fmt_symbol <- function(data,
 #' Format values as a percentage
 #'
 #' With numeric values in a **gt** table, we can perform percentage-based
-#' formatting. It is assumed the input numeric values are in a fractional format
-#' since the numbers will be automatically multiplied by `100` before decorating
-#' with a percent sign. For more control over percentage formatting, we can use
-#' the following options:
+#' formatting. It is assumed the input numeric values are proportional values
+#' and, in this case, the values will be automatically multiplied by `100`
+#' before decorating with a percent sign (the other case is accommodated though
+#' setting the `scale_values` to `FALSE`) For more control over percentage
+#' formatting, we can use the following options:
 #' \itemize{
 #' \item percent sign placement: the percent sign can be placed after or
 #' before the values and a space can be inserted between the symbol and the
@@ -486,6 +487,10 @@ fmt_symbol <- function(data,
 #' argument. See the Arguments section for more information on this.
 #'
 #' @inheritParams fmt_number
+#' @param scale_values Should the values be scaled through multiplication by
+#'   100? By default this is `TRUE` since the expectation is that normally
+#'   values are proportions. Setting to `FALSE` signifies that the values are
+#'   already scaled and require only the percent sign when formatted.
 #' @param incl_space An option for whether to include a space between the value
 #'   and the percent sign. The default is to not introduce a space character.
 #' @param placement The placement of the percent sign. This can be either be
@@ -524,6 +529,7 @@ fmt_percent <- function(data,
                         rows = NULL,
                         decimals = 2,
                         drop_trailing_zeros = FALSE,
+                        scale_values = TRUE,
                         use_seps = TRUE,
                         pattern = "{x}",
                         sep_mark = ",",
@@ -546,6 +552,12 @@ fmt_percent <- function(data,
          call. = FALSE)
   }
 
+  if (scale_values) {
+    scale_by <- 100
+  } else {
+    scale_by <- 1.0
+  }
+
   fmt_symbol(
     data = data,
     columns = !!columns,
@@ -555,7 +567,7 @@ fmt_percent <- function(data,
     decimals = decimals,
     drop_trailing_zeros = drop_trailing_zeros,
     use_seps = use_seps,
-    scale_by = 100,
+    scale_by = scale_by,
     suffixing = FALSE,
     pattern = pattern,
     sep_mark = sep_mark,
diff --git a/man/fmt_percent.Rd b/man/fmt_percent.Rd
index 8ac5ea231..139a0ea85 100644
--- a/man/fmt_percent.Rd
+++ b/man/fmt_percent.Rd
@@ -10,6 +10,7 @@ fmt_percent(
   rows = NULL,
   decimals = 2,
   drop_trailing_zeros = FALSE,
+  scale_values = TRUE,
   use_seps = TRUE,
   pattern = "{x}",
   sep_mark = ",",
@@ -41,6 +42,11 @@ use. The default number of decimal places is \code{2}.}
 \item{drop_trailing_zeros}{A logical value that allows for removal of
 trailing zeros (those redundant zeros after the decimal mark).}
 
+\item{scale_values}{Should the values be scaled through multiplication by
+100? By default this is \code{TRUE} since the expectation is that normally
+values are proportions. Setting to \code{FALSE} signifies that the values are
+already scaled and require only the percent sign when formatted.}
+
 \item{use_seps}{An option to use digit group separators. The type of digit
 group separator is set by \code{sep_mark} and overridden if a locale ID is
 provided to \code{locale}. This setting is \code{TRUE} by default.}
@@ -73,10 +79,11 @@ An object of class \code{gt_tbl}.
 }
 \description{
 With numeric values in a \strong{gt} table, we can perform percentage-based
-formatting. It is assumed the input numeric values are in a fractional format
-since the numbers will be automatically multiplied by \code{100} before decorating
-with a percent sign. For more control over percentage formatting, we can use
-the following options:
+formatting. It is assumed the input numeric values are proportional values
+and, in this case, the values will be automatically multiplied by \code{100}
+before decorating with a percent sign (the other case is accommodated though
+setting the \code{scale_values} to \code{FALSE}) For more control over percentage
+formatting, we can use the following options:
 \itemize{
 \item percent sign placement: the percent sign can be placed after or
 before the values and a space can be inserted between the symbol and the
diff --git a/tests/testthat/test-fmt_percent.R b/tests/testthat/test-fmt_percent.R
index 1264b17e2..32f65773b 100644
--- a/tests/testthat/test-fmt_percent.R
+++ b/tests/testthat/test-fmt_percent.R
@@ -201,4 +201,15 @@ test_that("the `fmt_percent()` function works correctly", {
       "64.300,00&percnt;", "21.223,20&percnt;", "0,00&percnt;",
       "&minus;2.324,00&percnt;")
   )
+
+  # Format the `num_2` column to 2 decimal places, expect that these
+  # values are prescaled and just require a percent mark; extract
+  # `output_df` and compare to expected values
+  expect_equal(
+    (tab %>%
+       fmt_percent(columns = "num_2", decimals = 2, scale_values = FALSE) %>%
+       render_formats_test("html"))[["num_2"]],
+    c("34.00&percnt;", "74.00&percnt;", "23.00&percnt;", "93.00&percnt;",
+      "35.00&percnt;", "76.00&percnt;", "57.00&percnt;")
+  )
 })

From 34540d68088e63e9bdf8404f29b87b74cb4a0aa9 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 22 Jun 2020 15:35:41 -0400
Subject: [PATCH 23/30] Fix issues with defining column widths in
 `cols_width()` (#561)

* Add fixes for specifying column widths

* Update implementation of `cols_width()`

* Update test-cols_width.R

* Rewrite implementation of column sizing

* Update R/utils_render_html.R

Co-authored-by: Joe Cheng <joe@rstudio.com>

* Update utils_render_html.R

* Update utils_render_html.R

* Create html-17-table_width_specifications.R

* Make changes based on code review discussions

* Make changes based on a code review

* Treat html_fragment_within pattern as regex literal

Co-authored-by: Joe Cheng <joe@rstudio.com>
---
 R/dt_options.R                                |   1 +
 R/modify_columns.R                            |  49 +--
 R/tab_create_modify.R                         |   4 +
 R/utils.R                                     |  20 ++
 R/utils_render_html.R                         |  69 ++--
 man/cols_width.Rd                             |  23 +-
 man/tab_options.Rd                            |   5 +
 .../html-17-table_width_specifications.R      | 319 ++++++++++++++++++
 tests/testthat/helper-gt_attr_expectations.R  |   2 +-
 tests/testthat/test-cols_width.R              | 258 ++++++++------
 10 files changed, 588 insertions(+), 162 deletions(-)
 create mode 100644 tests/gt-examples/01-html-script/html-17-table_width_specifications.R

diff --git a/R/dt_options.R b/R/dt_options.R
index 04ed7c117..dcf3a0064 100644
--- a/R/dt_options.R
+++ b/R/dt_options.R
@@ -46,6 +46,7 @@ dt_options_tbl <-
     "container_overflow_y",              FALSE,  "container",        "overflow","auto",
     "table_id",                          FALSE,  "table",            "value",   NA_character_,
     "table_width",                        TRUE,  "table",            "px",      "auto",
+    "table_layout",                       TRUE,  "table",            "value",   "fixed",
     "table_margin_left",                  TRUE,  "table",            "px",      "auto",
     "table_margin_right",                 TRUE,  "table",            "px",      "auto",
     "table_background_color",             TRUE,  "table",            "value",   "#FFFFFF",
diff --git a/R/modify_columns.R b/R/modify_columns.R
index dad4b3fdb..574bffdb6 100644
--- a/R/modify_columns.R
+++ b/R/modify_columns.R
@@ -103,17 +103,20 @@ cols_align <- function(data,
 #' Set the widths of columns
 #'
 #' Manual specifications of column widths can be performed using the
-#' `cols_width()` function. We choose which columns get specific widths (in
-#' pixels, usually by use of the [px()] helper function). Width assignments are
-#' supplied in `...` through two-sided formulas, where the left-hand side
-#' defines the target columns and the right-hand side is a single width value in
-#' pixels.
-#'
-#' Normally, column widths are automatically set to span across the width of the
-#' container (both table and container widths can be individually modified with
-#' the `table.width` and `container.width` options within [tab_options()]). When
-#' using `cols_width()` though, the `table.width` option is disregarded in
-#' favor of the pixel values set for each column.
+#' `cols_width()` function. We choose which columns get specific widths. This
+#' can be in units of pixels (easily set by use of the [px()] helper function),
+#' or, as percentages (where the [pct()] helper function is useful). Width
+#' assignments are supplied in `...` through two-sided formulas, where the
+#' left-hand side defines the target columns and the right-hand side is a single
+#' dimension.
+#'
+#' Column widths can be set as absolute or relative values (with px and
+#' percentage values). Those columns not specified are treated as having
+#' variable width. The sizing behavior for column widths depends on the
+#' combination of value types, and, whether a table width has been set (which
+#' could, itself, be expressed as an absolute or relative value). Widths for the
+#' table and its container can be individually modified with the `table.width`
+#' and `container.width` arguments within [tab_options()]).
 #'
 #' @inheritParams cols_align
 #' @param ... Expressions for the assignment of column widths for the table
@@ -200,10 +203,13 @@ cols_width <- function(data,
     cols <- width_item %>% rlang::f_lhs()
 
     columns <-
-      resolve_vars(
-        var_expr = !!cols,
-        data = data
-      ) %>%
+      dt_boxhead_get_vars(data)[
+        resolve_data_vals_idx(
+          var_expr = !!cols,
+          data_tbl = NULL,
+          vals = dt_boxhead_get_vars(data)
+        )
+      ] %>%
       base::setdiff(columns_used)
 
     columns_used <- c(columns_used, columns)
@@ -213,6 +219,9 @@ cols_width <- function(data,
       rlang::f_rhs() %>%
       rlang::eval_tidy()
 
+    # If a bare numeric value is provided, give that the `px` dimension
+    if (is.numeric(width)) width <- paste_right(as.character(width), "px")
+
     for (column in columns) {
       data <- data %>% dt_boxhead_edit(var = column, column_width = list(width))
     }
@@ -229,15 +238,9 @@ cols_width <- function(data,
 
     columns_unset <- (data %>% dt_boxhead_get_vars())[unset_widths]
 
-    warning("Unset column widths found, setting them to `100px`:\n",
-            " * columns: ",
-            str_catalog(columns_unset),
-            ".\n",
-            " * Set any remaining column widths in `cols_width()` with `everything() ~ px(100)`.",
-            call. = FALSE)
-
     for (column in columns_unset) {
-      data <- data %>% dt_boxhead_edit(var = column, column_width = list("100px"))
+
+      data <- data %>% dt_boxhead_edit(var = column, column_width = list(""))
     }
   }
 
diff --git a/R/tab_create_modify.R b/R/tab_create_modify.R
index a2bedb716..029488240 100644
--- a/R/tab_create_modify.R
+++ b/R/tab_create_modify.R
@@ -1148,6 +1148,9 @@ set_style.cells_grand_summary <- function(loc, data, style) {
 #'   given in units of pixels. The [px()] and [pct()] helper functions can also
 #'   be used to pass in numeric values and obtain values as pixel or percent
 #'   units.
+#' @param table.layout The value for the `table-layout` CSS style in the HTML
+#'   output context. By default, this is `"fixed"` but another valid option is
+#'   `"auto"`.
 #' @param table.align The horizontal alignment of the table in its container. By
 #'   default, this is `"center"`. Other options are `"left"` and `"right"`. This
 #'   will automatically set `table.margin.left` and `table.margin.right` to the
@@ -1378,6 +1381,7 @@ tab_options <- function(data,
                         container.overflow.x = NULL,
                         container.overflow.y = NULL,
                         table.width = NULL,
+                        table.layout = NULL,
                         table.align = NULL,
                         table.margin.left = NULL,
                         table.margin.right = NULL,
diff --git a/R/utils.R b/R/utils.R
index 7a4557c86..84ef53535 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -1019,6 +1019,26 @@ validate_table_id <- function(id) {
   }
 }
 
+validate_css_lengths <- function(x) {
+
+  # Don't include empty strings in the validation; these lengths
+  # should be handled downstream (i.e., using `htmltools::css()`,
+  # where empty strings and NULL values don't create rules at all)
+  x_units_non_empty <- x[!(x == "")]
+
+  # While this returns a vector of corrected CSS units, we
+  # primarily want to verify that the vector of provided values
+  # don't contain any invalid suffixes; this throws if that's the
+  # case and returns `TRUE` otherwise
+  vapply(
+    x_units_non_empty,
+    FUN = htmltools::validateCssUnit,
+    FUN.VALUE = character(1),
+    USE.NAMES = FALSE
+  ) %>%
+    is.character()
+}
+
 column_classes_are_valid <- function(data, columns, valid_classes) {
 
   dt_data_get(data = data) %>%
diff --git a/R/utils_render_html.R b/R/utils_render_html.R
index fe9b58cf0..57ca4b0a5 100644
--- a/R/utils_render_html.R
+++ b/R/utils_render_html.R
@@ -67,38 +67,53 @@ get_table_defs <- function(data) {
 
   boxh <- dt_boxhead_get(data = data)
 
-  if (boxh$column_width %>% unlist() %>% length() > 0) {
+  # Get the `table-layout` value, which is set in `_options`
+  table_style <-
+    paste0("table-layout: ", dt_options_get_value(data, option = "table_layout"), ";")
+
+  # In the case that column widths are not set for any columns,
+  # there should not be a `<colgroup>` tag requirement
+  if (boxh$column_width %>% unlist() %>% length() < 1) {
+    return(list(table_style = NULL, table_colgroups = NULL))
+  }
 
-    widths <-
-      boxh %>%
-      dplyr::filter(type == "default") %>%
-      .$column_width %>%
-      unlist()
+  # Get the table's width (which or may not have been set)
+  table_width <- dt_options_get_value(data, option = "table_width")
 
-    # Assumption is that all width values are `px` values
-    total_width <-
-      widths %>%
-      tidy_gsub("px", "") %>%
-      as.numeric() %>%
-      sum(na.rm = TRUE) %>%
-      as.character() %>%
-      paste_right("px")
-
-    table_style <-
-      paste("table-layout: fixed", paste0("width: ", total_width), sep = "; ")
-
-    table_colgroups <-
-      htmltools::tags$colgroup(
-        lapply(widths, function(width) {
-          htmltools::tags$col(style = paste0("width: ", width))
-        })
-      )
+  widths <-
+    boxh %>%
+    dplyr::filter(type %in% c("default", "stub")) %>%
+    dplyr::arrange(dplyr::desc(type)) %>% # This ensures that the `stub` is first
+    .$column_width %>%
+    unlist()
+
+  # Stop function if all length dimensions (where provided)
+  # don't conform to accepted CSS length definitions
+  validate_css_lengths(widths)
+
+  # If all of the widths are defined as px values for all columns,
+  # then ensure that the width values are strictly respected as
+  # absolute width values (even if a table width has already been set)
+  if (all(grepl("px", widths)) && table_width == "auto") {
+    table_width <- "0px"
+  }
 
-  } else {
-    table_style <- NULL
-    table_colgroups <- NULL
+  if (all(grepl("%", widths)) && table_width == "auto") {
+    table_width <- "100%"
+  }
+
+  if (table_width != "auto") {
+    table_style <- paste(table_style, paste0("width: ", table_width), sep = "; ")
   }
 
+  # Create the `<colgroup>` tag
+  table_colgroups <-
+    htmltools::tags$colgroup(
+      lapply(widths, function(width) {
+        htmltools::tags$col(style = htmltools::css(width = width))
+      })
+    )
+
   list(
     table_style = table_style,
     table_colgroups = table_colgroups
diff --git a/man/cols_width.Rd b/man/cols_width.Rd
index 3af30a837..75d47d2ae 100644
--- a/man/cols_width.Rd
+++ b/man/cols_width.Rd
@@ -30,18 +30,21 @@ An object of class \code{gt_tbl}.
 }
 \description{
 Manual specifications of column widths can be performed using the
-\code{cols_width()} function. We choose which columns get specific widths (in
-pixels, usually by use of the \code{\link[=px]{px()}} helper function). Width assignments are
-supplied in \code{...} through two-sided formulas, where the left-hand side
-defines the target columns and the right-hand side is a single width value in
-pixels.
+\code{cols_width()} function. We choose which columns get specific widths. This
+can be in units of pixels (easily set by use of the \code{\link[=px]{px()}} helper function),
+or, as percentages (where the \code{\link[=pct]{pct()}} helper function is useful). Width
+assignments are supplied in \code{...} through two-sided formulas, where the
+left-hand side defines the target columns and the right-hand side is a single
+dimension.
 }
 \details{
-Normally, column widths are automatically set to span across the width of the
-container (both table and container widths can be individually modified with
-the \code{table.width} and \code{container.width} options within \code{\link[=tab_options]{tab_options()}}). When
-using \code{cols_width()} though, the \code{table.width} option is disregarded in
-favor of the pixel values set for each column.
+Column widths can be set as absolute or relative values (with px and
+percentage values). Those columns not specified are treated as having
+variable width. The sizing behavior for column widths depends on the
+combination of value types, and, whether a table width has been set (which
+could, itself, be expressed as an absolute or relative value). Widths for the
+table and its container can be individually modified with the \code{table.width}
+and \code{container.width} arguments within \code{\link[=tab_options]{tab_options()}}).
 }
 \section{Figures}{
 
diff --git a/man/tab_options.Rd b/man/tab_options.Rd
index 55c61b6bb..76675eb10 100644
--- a/man/tab_options.Rd
+++ b/man/tab_options.Rd
@@ -11,6 +11,7 @@ tab_options(
   container.overflow.x = NULL,
   container.overflow.y = NULL,
   table.width = NULL,
+  table.layout = NULL,
   table.align = NULL,
   table.margin.left = NULL,
   table.margin.right = NULL,
@@ -157,6 +158,10 @@ given in units of pixels. The \code{\link[=px]{px()}} and \code{\link[=pct]{pct(
 be used to pass in numeric values and obtain values as pixel or percent
 units.}
 
+\item{table.layout}{The value for the \code{table-layout} CSS style in the HTML
+output context. By default, this is \code{"fixed"} but another valid option is
+\code{"auto"}.}
+
 \item{table.align}{The horizontal alignment of the table in its container. By
 default, this is \code{"center"}. Other options are \code{"left"} and \code{"right"}. This
 will automatically set \code{table.margin.left} and \code{table.margin.right} to the
diff --git a/tests/gt-examples/01-html-script/html-17-table_width_specifications.R b/tests/gt-examples/01-html-script/html-17-table_width_specifications.R
new file mode 100644
index 000000000..35b70a863
--- /dev/null
+++ b/tests/gt-examples/01-html-script/html-17-table_width_specifications.R
@@ -0,0 +1,319 @@
+library(gt)
+library(tidyverse)
+
+# Test matrix for setting of column widths; broadly there are 21 cases with
+# different combinations of setting dimensions (or not) on table columns with
+# px and %, and, setting the table width (or not) in px and %
+
+gt_tbl <-
+  exibble %>%
+  dplyr::select(num, char, datetime, row) %>%
+  gt(rowname_col = "row")
+
+
+#
+# I. Defining an absolute table width in pixels
+#
+
+# (1) UNDEF
+# All columns are variable (equal widths unless
+# content in some columns causes width expansion)
+gt_tbl %>%
+  tab_options(table.width = px(800))
+
+
+# (2) PX
+# Define all columns in terms of px values;
+# the overall table width of 800px is respected
+# (of px values will act as proportions of width,
+# as long as their sum isn't greater than the
+# overall table width)
+gt_tbl %>%
+  cols_width(
+    everything() ~ px(20)
+  ) %>%
+  tab_options(table.width = px(800))
+
+
+# (3) PX + UNDEF
+# Define some columns in terms of px values;
+# undefined widths will be variable (based on content,
+# filling the remaining width)
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(120),
+    vars(char) ~ px(140)
+  ) %>%
+  tab_options(table.width = px(800))
+
+
+# (4) PCT
+# If everything is in terms of percentages, the
+# proportional widths are normalized, overall
+# table width is honored
+gt_tbl %>%
+  cols_width(
+    everything() ~ pct(30)
+  ) %>%
+  tab_options(table.width = px(800))
+
+
+# (5) PCT + UNDEF
+# Define some columns in terms of % values;
+# undefined widths will be variable (based on content,
+# filling the remaining width)
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ pct(5), # this is the stub column
+    vars(char) ~ pct(10)
+  ) %>%
+  tab_options(table.width = px(800))
+
+
+# (6) PX + PCT
+# Define all columns in terms of either px or %;
+# these are all converted to proportions but the
+# exact routine is not intuitive; table.width seems
+# to be constant no matter what values are given
+# for the column widths
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ px(100),
+    vars(num) ~ px(100),
+    vars(char) ~ pct(10),
+    vars(datetime) ~ pct(10)
+  ) %>%
+  tab_options(table.width = px(800))
+
+
+# (7) PX + PCT + UNDEF
+# Define some columns in terms of px and % values;
+# looks as though % columns are scaled and fixed, px
+# columns are fixed, other columns take up the remaining
+# space (if any); table.width seems to be constant no
+# matter what values are given for the column widths
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(100),
+    vars(char) ~ pct(50)
+  ) %>%
+  tab_options(table.width = px(800))
+
+
+
+#
+# II. Defining an absolute table width as a percentage
+#
+
+# (1) UNDEF
+# All columns are variable (equal widths unless
+# content in some columns causes width expansion)
+gt_tbl %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  tab_options(table.width = pct(60))
+
+
+# (2) PX
+# Define all columns in terms of px values;
+# the overall table width of 800px is respected
+# (of px values will act as proportions of width,
+# as long as their sum isn't greater than the
+# overall table width)
+gt_tbl %>%
+  cols_width(
+    everything() ~ px(20)
+  ) %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  cols_width(
+    everything() ~ px(20)
+  ) %>%
+  tab_options(table.width = pct(80))
+
+
+# (3) PX + UNDEF
+# Define some columns in terms of px values;
+# undefined widths will be variable (based on content,
+# filling the remaining width)
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(120),
+    vars(char) ~ px(140)
+  ) %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(120),
+    vars(char) ~ px(140)
+  ) %>%
+  tab_options(table.width = pct(80))
+
+
+# (4) PCT
+# If everything is in terms of percentages, the
+# proportional widths are normalized, overall
+# table width is honored
+gt_tbl %>%
+  cols_width(
+    everything() ~ pct(30)
+  ) %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  cols_width(
+    everything() ~ pct(30)
+  ) %>%
+  tab_options(table.width = pct(80))
+
+
+# (5) PCT + UNDEF
+# Define some columns in terms of % values;
+# undefined widths will be variable (based on content,
+# filling the remaining width)
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ pct(5), # this is the stub column
+    vars(char) ~ pct(10)
+  ) %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ pct(5), # this is the stub column
+    vars(char) ~ pct(10)
+  ) %>%
+  tab_options(table.width = pct(80))
+
+
+# (6) PX + PCT
+# Define all columns in terms of either px or %;
+# these are all converted to proportions but the
+# exact routine is not intuitive; table.width seems
+# to be constant no matter what values are given
+# for the column widths
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ px(100),
+    vars(num) ~ px(100),
+    vars(char) ~ pct(10),
+    vars(datetime) ~ pct(10)
+  ) %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ px(100),
+    vars(num) ~ px(100),
+    vars(char) ~ pct(10),
+    vars(datetime) ~ pct(10)
+  ) %>%
+  tab_options(table.width = pct(80))
+
+
+# (7) PX + PCT + UNDEF
+# Define some columns in terms of px and % values;
+# looks as though % columns are scaled and fixed, px
+# columns are fixed, other columns take up the remaining
+# space (if any); table.width seems to be constant no
+# matter what values are given for the column widths
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(100),
+    vars(char) ~ pct(50)
+  ) %>%
+  tab_options(table.width = pct(100))
+
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(100),
+    vars(char) ~ pct(50)
+  ) %>%
+  tab_options(table.width = pct(80))
+
+
+
+#
+# III. No definition of the table width
+#
+
+# (1) UNDEF
+# All columns are variable (equal widths unless
+# content in some columns causes width expansion)
+gt_tbl
+
+
+# (2) PX
+# Define all columns in terms of px values;
+# each px is exactly as specified
+# NOTE: we intervene and set the table width to 0px
+gt_tbl %>%
+  cols_width(
+    everything() ~ px(20)
+  )
+
+
+# (3) PX + UNDEF
+# Define some columns in terms of px values;
+# undefined widths will be variable (based on content,
+# filling the remaining width)
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(120),
+    vars(char) ~ px(140)
+  )
+
+
+# (4) PCT
+# If everything is in terms of percentages, the
+# proportional widths are normalized
+# NOTE: we intervene and set the table width to 100%
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ pct(30),
+    vars(num) ~ pct(30),
+    vars(char) ~ pct(10),
+    vars(datetime) ~ pct(10)
+  )
+
+
+# (5) PCT + UNDEF
+# Define some columns in terms of % values;
+# undefined widths will be variable (based on content,
+# filling the remaining width); automatically, w/o
+# intervention, the table width goes to 100%
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ pct(10), # this is the stub column
+    vars(char) ~ pct(10)
+  )
+
+
+# (6) PX + PCT
+# Define all columns in terms of either px or %;
+# these are all converted to proportions but the
+# exact routine is not intuitive; automatically, w/o
+# intervention, the table width goes to 100%
+gt_tbl %>%
+  cols_width(
+    vars(row) ~ px(100),
+    vars(num) ~ px(100),
+    vars(char) ~ pct(10),
+    vars(datetime) ~ pct(10)
+  )
+
+
+# (7) PX + PCT + UNDEF
+# Define some columns in terms of px and % values;
+# looks as though % columns are scaled and fixed, px
+# columns are fixed, other columns expand to fit their
+# content
+gt_tbl %>%
+  cols_width(
+    vars(num) ~ px(100),
+    vars(char) ~ pct(50)
+  )
+
diff --git a/tests/testthat/helper-gt_attr_expectations.R b/tests/testthat/helper-gt_attr_expectations.R
index 88bd84c95..e64e3b6b0 100644
--- a/tests/testthat/helper-gt_attr_expectations.R
+++ b/tests/testthat/helper-gt_attr_expectations.R
@@ -102,7 +102,7 @@ expect_tab <- function(tab,
 
   dt_options_get(data = tab) %>%
     dim() %>%
-    expect_equal(c(128, 5))
+    expect_equal(c(129, 5))
 
   dt_transforms_get(data = tab) %>%
     length() %>%
diff --git a/tests/testthat/test-cols_width.R b/tests/testthat/test-cols_width.R
index b389645b1..6bb97cf4e 100644
--- a/tests/testthat/test-cols_width.R
+++ b/tests/testthat/test-cols_width.R
@@ -13,7 +13,8 @@ tbl <-
     349.7,  307.1,  566.7,  542.9,
     63.7,  504.3,  152.0,  724.5,
     105.4,  729.8,  962.4,  336.4,
-    924.2,  424.6,  740.8,  104.2)
+    924.2,  424.6,  740.8,  104.2
+  )
 
 # Function to skip tests if Suggested packages not available on system
 check_suggests <- function() {
@@ -39,6 +40,11 @@ selection_text <- function(html, selection) {
     rvest::html_text()
 }
 
+# Helper function to compare a contiguous set of HTML fragments with raw html
+html_fragment_within <- function(raw_html, ...) {
+  grepl(paste0("\\Q", c(...), "\\E", "[\\n\\s]*?", collapse = ""), raw_html, perl = TRUE)
+}
+
 test_that("the function `cols_width()` works correctly", {
 
   # Check that specific suggested packages are available
@@ -56,14 +62,14 @@ test_that("the function `cols_width()` works correctly", {
     )
 
   # Expect that the all column widths are set to `100px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-      "<colgroup>\n\\s*?<col style=\"width: 100px\"/>\n\\s*?",
-      "<col style=\"width: 100px\"/>\n\\s*?<col style",
-      "=\"width: 100px\"/>\\s*?<col style=\"width: 100px\"/>\\s*?",
-      "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -80,42 +86,86 @@ test_that("the function `cols_width()` works correctly", {
 
   # Expect that the first two column widths are
   # set to `100px`, and the rest are `70px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 100px\"/>\n\\s*?",
-        "<col style=\"width: 100px\"/>\n\\s*?<col style",
-        "=\"width: 70px\"/>\\s*?<col style=\"width: 70px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:70px;\"/>",
+      "<col style=\"width:70px;\"/>",
+      "</colgroup>"
+    ) %>%
+    expect_true()
+
+  # Create a `tbl_html` object with `gt()` and make
+  # every column variable width
+  tbl_html <-
+    gt(tbl) %>%
+    cols_width(
+      vars(col_1) ~ "",
+      vars(col_2) ~ "",
+      vars(col_3) ~ "",
+      vars(col_4) ~ ""
+    )
+
+  # Expect that the all column widths are unset
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"\"/>",
+      "<col style=\"\"/>",
+      "<col style=\"\"/>",
+      "<col style=\"\"/>",
+      "</colgroup>"
+    ) %>%
+    expect_true()
+
+  # Create a `tbl_html` object with `gt()` and a
+  # combination of different, allowable length
+  # dimensions
+  tbl_html <-
+    gt(tbl) %>%
+    cols_width(
+      vars(col_1) ~ px(100),
+      vars(col_2) ~ 200,
+      vars(col_3) ~ pct(20),
+      vars(col_4) ~ ""
+    )
+
+  # Expect that the first three column widths are
+  # all set and the fourth is not
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:200px;\"/>",
+      "<col style=\"width:20%;\"/>",
+      "<col style=\"\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
   # Create a `tbl_html` object with `gt()` and size the
-  # first two columns to `100px`; the uncaptured columns
-  # will get default width of `100px` (a warning will be
-  # given)
+  # first two columns to `100px`; the unset columns
+  # will be variable widths
   tbl_html <-
-    suppressWarnings(
-      gt(tbl) %>%
-        cols_width(
-          vars(col_1) ~ px(150),
-          vars(col_2) ~ px(150)
-        )
+    gt(tbl) %>%
+    cols_width(
+      vars(col_1) ~ px(150),
+      vars(col_2) ~ px(150)
     )
 
   # Expect that the first two column widths are
-  # set to `150px`, and the rest are `100px`
-  suppressWarnings(
-    tbl_html %>%
-      render_as_html() %>%
-      tidy_grepl(
-        paste0(
-          "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-          "<col style=\"width: 150px\"/>\n\\s*?<col style",
-          "=\"width: 100px\"/>\\s*?<col style=\"width: 100px\"/>\\s*?",
-          "</colgroup>")
-      )) %>%
+  # set to `150px`, and the rest are blank (variable width)
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"\"/>",
+      "<col style=\"\"/>",
+      "</colgroup>"
+    ) %>%
     expect_true()
 
   # Create a `tbl_html` object with `gt()` and assign
@@ -128,14 +178,14 @@ test_that("the function `cols_width()` works correctly", {
     )
 
   # Expect that the all column widths are set to `150px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-        "<col style=\"width: 150px\"/>\n\\s*?<col style",
-        "=\"width: 150px\"/>\\s*?<col style=\"width: 150px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -149,14 +199,14 @@ test_that("the function `cols_width()` works correctly", {
     )
 
   # Expect that the all column widths are set to `150px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-        "<col style=\"width: 150px\"/>\n\\s*?<col style",
-        "=\"width: 150px\"/>\\s*?<col style=\"width: 150px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -172,14 +222,14 @@ test_that("the function `cols_width()` works correctly", {
 
   # Expect that the first column width is set to
   # `150px`, and the rest are `100px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-        "<col style=\"width: 100px\"/>\n\\s*?<col style",
-        "=\"width: 100px\"/>\\s*?<col style=\"width: 100px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -193,14 +243,14 @@ test_that("the function `cols_width()` works correctly", {
     )
 
   # Expect that the all column widths are set to `150px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-        "<col style=\"width: 150px\"/>\n\\s*?<col style",
-        "=\"width: 150px\"/>\\s*?<col style=\"width: 150px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -214,14 +264,14 @@ test_that("the function `cols_width()` works correctly", {
     )
 
   # Expect that the all column widths are set to `150px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-        "<col style=\"width: 150px\"/>\n\\s*?<col style",
-        "=\"width: 150px\"/>\\s*?<col style=\"width: 150px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -237,14 +287,14 @@ test_that("the function `cols_width()` works correctly", {
 
   # Expect that the first two column widths are set to
   # `150px`, and the rest are `100px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 150px\"/>\n\\s*?",
-        "<col style=\"width: 150px\"/>\n\\s*?<col style",
-        "=\"width: 100px\"/>\\s*?<col style=\"width: 100px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:150px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "<col style=\"width:100px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -264,14 +314,14 @@ test_that("the function `cols_width()` works correctly", {
 
   # Expect that the first column width is set to
   # `175px`, and the rest are `75px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 175px\"/>\n\\s*?",
-        "<col style=\"width: 75px\"/>\n\\s*?<col style",
-        "=\"width: 75px\"/>\\s*?<col style=\"width: 75px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:175px;\"/>",
+      "<col style=\"width:75px;\"/>",
+      "<col style=\"width:75px;\"/>",
+      "<col style=\"width:75px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -293,14 +343,14 @@ test_that("the function `cols_width()` works correctly", {
 
   # Expect that the first column width is set to
   # `250px`, and the rest are `75px`
-  tbl_html %>%
-    render_as_html() %>%
-    tidy_grepl(
-      paste0(
-        "<colgroup>\n\\s*?<col style=\"width: 250px\"/>\n\\s*?",
-        "<col style=\"width: 75px\"/>\n\\s*?<col style",
-        "=\"width: 75px\"/>\\s*?<col style=\"width: 75px\"/>\\s*?",
-        "</colgroup>")
+  tbl_html %>% render_as_html() %>%
+    html_fragment_within(
+      "<colgroup>",
+      "<col style=\"width:250px;\"/>",
+      "<col style=\"width:75px;\"/>",
+      "<col style=\"width:75px;\"/>",
+      "<col style=\"width:75px;\"/>",
+      "</colgroup>"
     ) %>%
     expect_true()
 
@@ -319,4 +369,10 @@ test_that("the function `cols_width()` works correctly", {
     gt(tbl) %>%
       cols_width()
   )
+
+  # Expect an error if an incorrect unit is present
+  # in any vector element of CSS length values
+  expect_error(
+    validate_css_lengths(c("", "3", "3em", "3rem", "3dem"))
+  )
 })

From 721c9a5253202ca11c552290c11fbf4f5db427ed Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 22 Jun 2020 16:32:14 -0400
Subject: [PATCH 24/30] Add options for sig figs / inclusion of trailing dec
 marks (#546)

* Add options for sig figs / inclusion of trailing dec marks

* Add validation for `n_sigfig` values

* Add several testthat tests

* Fix bug in fn call; set mode to "double" for format "e"

Also, update tests for significant figures formatting.

* Update NEWS.md

* Correct tests for htmltools v0.5
---
 DESCRIPTION                      |   2 +-
 NEWS.md                          |   2 +
 R/format_data.R                  |  52 ++++++-
 R/utils.R                        |  16 ++
 R/utils_formatters.R             |  46 +++++-
 man/fmt_currency.Rd              |   6 +
 man/fmt_number.Rd                |  14 ++
 man/fmt_percent.Rd               |   6 +
 tests/testthat/test-cols_width.R |  14 +-
 tests/testthat/test-fmt_number.R | 250 +++++++++++++++++++++++++++++++
 10 files changed, 386 insertions(+), 22 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 656ce97c7..eecbd6a18 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -33,7 +33,7 @@ Imports:
     fs (>= 1.3.2),
     ggplot2 (>= 3.3.0),
     glue (>= 1.3.2),
-    htmltools (>= 0.4.0),
+    htmltools (>= 0.5.0),
     magrittr (>= 1.5),
     rlang (>= 0.4.5),
     sass (>= 0.1.1),
diff --git a/NEWS.md b/NEWS.md
index a6795ccfe..827c1599e 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,7 @@
 # gt (unreleased)
 
+* There are new options for numeric formatting: (1) using significant figures (with `n_sigfig` in `fmt_number`), and (2) the ability to retain/drop trailing decimal marks (with `drop_trailing_dec_mark` in `fmt_number()`, `fmt_percent()`, and `fmt_currency()`). Thank you @drolejoel for the suggestion in #535! (#546).
+
 * The new `scale_values` argument for `fmt_percent()` makes it easy to use values that are already scaled (and just require the percent mark). Thank you @djohn215 for the suggestion in #559. (#565)
 
 * Restore the ability to have row striping in stub cells (with `tab_option()`'s `row.striping.include_stub = TRUE`). Thanks @gergness for creating PR #537, which prompted this final fix. (#564)
diff --git a/R/format_data.R b/R/format_data.R
index 3b78967af..d98471d5a 100644
--- a/R/format_data.R
+++ b/R/format_data.R
@@ -38,8 +38,18 @@
 #'   `[colname_1] > 100 & [colname_2] < 50`).
 #' @param decimals An option to specify the exact number of decimal places to
 #'   use. The default number of decimal places is `2`.
+#' @param n_sigfig A option to format numbers to *n* significant figures. By
+#'   default, this is `NULL` and thus number values will be formatted according
+#'   to the number of decimal places set via `decimals`. If opting to format
+#'   according to the rules of significant figures, `n_sigfig` must be a number
+#'   greater than or equal to `1`. Any values passed to the `decimals` and
+#'   `drop_trailing_zeros` arguments will be ignored.
 #' @param drop_trailing_zeros A logical value that allows for removal of
 #'   trailing zeros (those redundant zeros after the decimal mark).
+#' @param drop_trailing_dec_mark A logical value that determines whether decimal
+#'   marks should always appear even if there are no decimal digits to display
+#'   after formatting (e.g, `23` becomes `23.`). The default for this is `TRUE`,
+#'   which means that trailing decimal marks are not shown.
 #' @param use_seps An option to use digit group separators. The type of digit
 #'   group separator is set by `sep_mark` and overridden if a locale ID is
 #'   provided to `locale`. This setting is `TRUE` by default.
@@ -132,7 +142,9 @@ fmt_number <- function(data,
                        columns,
                        rows = NULL,
                        decimals = 2,
+                       n_sigfig = NULL,
                        drop_trailing_zeros = FALSE,
+                       drop_trailing_dec_mark = TRUE,
                        use_seps = TRUE,
                        scale_by = 1.0,
                        suffixing = FALSE,
@@ -166,6 +178,18 @@ fmt_number <- function(data,
          call. = FALSE)
   }
 
+  # Set the `formatC_format` option according to whether number
+  # formatting with significant figures is to be performed
+  if (!is.null(n_sigfig)) {
+
+    # Stop function if `n_sigfig` does not have a valid value
+    validate_n_sigfig(n_sigfig)
+
+    formatC_format <- "fg"
+  } else {
+    formatC_format <- "f"
+  }
+
   # Pass `data`, `columns`, `rows`, and the formatting
   # functions as a function list to `fmt()`
   fmt(
@@ -184,8 +208,11 @@ fmt_number <- function(data,
           scale_x_values(suffix_df$scale_by) %>%
           # Format numeric values to character-based numbers
           format_num_to_str(
-            context = context, decimals = decimals, sep_mark = sep_mark,
-            dec_mark = dec_mark, drop_trailing_zeros = drop_trailing_zeros
+            context = context, decimals = decimals, n_sigfig = n_sigfig,
+            sep_mark = sep_mark, dec_mark = dec_mark,
+            drop_trailing_zeros = drop_trailing_zeros,
+            drop_trailing_dec_mark = drop_trailing_dec_mark,
+            format = formatC_format
           ) %>%
           # With large-number suffixing support, we paste the
           # vector of suffixes to the right of the values
@@ -317,11 +344,13 @@ fmt_scientific <- function(data,
 
         x_str <-
           x %>%
-          # Format numeric values to character-based numbers
           format_num_to_str(
-            context = context, decimals = decimals, sep_mark = sep_mark,
-            dec_mark = dec_mark, drop_trailing_zeros = drop_trailing_zeros,
-            format = "e", replace_minus_mark = FALSE
+            context = context, decimals = decimals, n_sigfig = NULL,
+            sep_mark = sep_mark, dec_mark = dec_mark,
+            drop_trailing_zeros = drop_trailing_zeros,
+            drop_trailing_dec_mark = FALSE,
+            format = "e",
+            replace_minus_mark = FALSE
           )
 
         # # Determine which values don't require the (x 10^n)
@@ -365,6 +394,7 @@ fmt_symbol <- function(data,
                        accounting = FALSE,
                        decimals = NULL,
                        drop_trailing_zeros = FALSE,
+                       drop_trailing_dec_mark = TRUE,
                        use_seps = TRUE,
                        scale_by = 1.0,
                        suffixing = FALSE,
@@ -419,7 +449,8 @@ fmt_symbol <- function(data,
             # Format numeric values to character-based numbers
             format_num_to_str_c(
               context = context, decimals = decimals, sep_mark = sep_mark,
-              dec_mark = dec_mark, drop_trailing_zeros = drop_trailing_zeros
+              dec_mark = dec_mark, drop_trailing_zeros = drop_trailing_zeros,
+              drop_trailing_dec_mark = drop_trailing_dec_mark
             )
         }
 
@@ -433,7 +464,8 @@ fmt_symbol <- function(data,
             # Format numeric values to character-based numbers
             format_num_to_str_c(
               context = context, decimals = decimals, sep_mark = sep_mark,
-              dec_mark = dec_mark, drop_trailing_zeros = drop_trailing_zeros
+              dec_mark = dec_mark, drop_trailing_zeros = drop_trailing_zeros,
+              drop_trailing_dec_mark = drop_trailing_dec_mark
             )
         }
 
@@ -529,6 +561,7 @@ fmt_percent <- function(data,
                         rows = NULL,
                         decimals = 2,
                         drop_trailing_zeros = FALSE,
+                        drop_trailing_dec_mark = TRUE,
                         scale_values = TRUE,
                         use_seps = TRUE,
                         pattern = "{x}",
@@ -566,6 +599,7 @@ fmt_percent <- function(data,
     accounting = FALSE,
     decimals = decimals,
     drop_trailing_zeros = drop_trailing_zeros,
+    drop_trailing_dec_mark = drop_trailing_dec_mark,
     use_seps = use_seps,
     scale_by = scale_by,
     suffixing = FALSE,
@@ -696,6 +730,7 @@ fmt_currency <- function(data,
                          use_subunits = TRUE,
                          accounting = FALSE,
                          decimals = NULL,
+                         drop_trailing_dec_mark = TRUE,
                          use_seps = TRUE,
                          scale_by = 1.0,
                          suffixing = FALSE,
@@ -739,6 +774,7 @@ fmt_currency <- function(data,
     accounting = accounting,
     decimals = decimals,
     drop_trailing_zeros = FALSE,
+    drop_trailing_dec_mark = drop_trailing_dec_mark,
     use_seps = use_seps,
     scale_by = scale_by,
     suffixing = suffixing,
diff --git a/R/utils.R b/R/utils.R
index 84ef53535..57251fcd4 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -1019,6 +1019,22 @@ validate_table_id <- function(id) {
   }
 }
 
+validate_n_sigfig <- function(n_sigfig) {
+
+  if (length(n_sigfig) != 1) {
+    stop("The length of `n_sigfig` must be 1.", call. = FALSE)
+  }
+  if (is.na(n_sigfig)) {
+    stop("The value for `n_sigfig` must not be `NA`.", call. = FALSE)
+  }
+  if (!is.numeric(n_sigfig)) {
+    stop("Any input for `n_sigfig` must be numeric.", call. = FALSE)
+  }
+  if (n_sigfig < 1) {
+    stop("The value for `n_sigfig` must be greater than or equal to 1.", call. = FALSE)
+  }
+}
+
 validate_css_lengths <- function(x) {
 
   # Don't include empty strings in the validation; these lengths
diff --git a/R/utils_formatters.R b/R/utils_formatters.R
index 868d8ffa0..d618bd580 100644
--- a/R/utils_formatters.R
+++ b/R/utils_formatters.R
@@ -225,23 +225,55 @@ scale_x_values <- function(x,
 format_num_to_str <- function(x,
                               context,
                               decimals,
+                              n_sigfig,
                               sep_mark,
                               dec_mark,
                               drop_trailing_zeros,
+                              drop_trailing_dec_mark,
                               format = "f",
                               replace_minus_mark = TRUE) {
 
+  if (format == "fg") {
+    x <- signif(x, digits = n_sigfig)
+    mode <- NULL
+    digits <- n_sigfig
+    flag <- "#"
+    drop0trailing <- FALSE
+  } else if (format == "f") {
+    mode <- "double"
+    digits <- decimals
+    flag <- ""
+    drop0trailing <- drop_trailing_zeros
+  } else if (format == "e") {
+    mode <- "double"
+    digits <- decimals
+    flag <- ""
+    drop0trailing <- drop_trailing_zeros
+  } else {
+    stop("The format provided isn't recognized.")
+  }
+
   x_str <-
     formatC(
       x = x,
-      digits = decimals,
-      mode = "double",
-      big.mark = sep_mark,
-      decimal.mark = dec_mark,
       format = format,
-      drop0trailing = drop_trailing_zeros
+      mode = mode,
+      digits = digits,
+      flag = flag,
+      drop0trailing = drop0trailing,
+      big.mark = sep_mark,
+      decimal.mark = dec_mark
     )
 
+  # If a trailing decimal mark is to be retained (not the
+  # default option but sometimes desirable), affix the `dec_mark`
+  # to the right of those figures that are missing this mark
+  if (!drop_trailing_dec_mark) {
+    x_str_no_dec <- !grepl(dec_mark, x_str, fixed = TRUE)
+    x_str[x_str_no_dec] <- paste_right(x_str[x_str_no_dec], dec_mark)
+  }
+
+  # Replace the minus mark (a hyphen) with a context-specific minus sign
   if (replace_minus_mark) {
     x_str <- format_minus(x_str = x_str, x = x, context = context)
   }
@@ -258,7 +290,8 @@ format_num_to_str_c <- function(x,
                                 decimals,
                                 sep_mark,
                                 dec_mark,
-                                drop_trailing_zeros = FALSE) {
+                                drop_trailing_zeros = FALSE,
+                                drop_trailing_dec_mark) {
 
   format_num_to_str(
     x = x,
@@ -267,6 +300,7 @@ format_num_to_str_c <- function(x,
     sep_mark = sep_mark,
     dec_mark = dec_mark,
     drop_trailing_zeros = drop_trailing_zeros,
+    drop_trailing_dec_mark = drop_trailing_dec_mark,
     format = "f"
   )
 }
diff --git a/man/fmt_currency.Rd b/man/fmt_currency.Rd
index 9c36583f9..db22837e8 100644
--- a/man/fmt_currency.Rd
+++ b/man/fmt_currency.Rd
@@ -12,6 +12,7 @@ fmt_currency(
   use_subunits = TRUE,
   accounting = FALSE,
   decimals = NULL,
+  drop_trailing_dec_mark = TRUE,
   use_seps = TRUE,
   scale_by = 1,
   suffixing = FALSE,
@@ -69,6 +70,11 @@ Using \code{accounting = TRUE} will put negative values in parentheses.}
 \item{decimals}{An option to specify the exact number of decimal places to
 use. The default number of decimal places is \code{2}.}
 
+\item{drop_trailing_dec_mark}{A logical value that determines whether decimal
+marks should always appear even if there are no decimal digits to display
+after formatting (e.g, \code{23} becomes \code{23.}). The default for this is \code{TRUE},
+which means that trailing decimal marks are not shown.}
+
 \item{use_seps}{An option to use digit group separators. The type of digit
 group separator is set by \code{sep_mark} and overridden if a locale ID is
 provided to \code{locale}. This setting is \code{TRUE} by default.}
diff --git a/man/fmt_number.Rd b/man/fmt_number.Rd
index af7b75e75..66b85758a 100644
--- a/man/fmt_number.Rd
+++ b/man/fmt_number.Rd
@@ -9,7 +9,9 @@ fmt_number(
   columns,
   rows = NULL,
   decimals = 2,
+  n_sigfig = NULL,
   drop_trailing_zeros = FALSE,
+  drop_trailing_dec_mark = TRUE,
   use_seps = TRUE,
   scale_by = 1,
   suffixing = FALSE,
@@ -38,9 +40,21 @@ We can also use expressions to filter down to the rows we need (e.g.,
 \item{decimals}{An option to specify the exact number of decimal places to
 use. The default number of decimal places is \code{2}.}
 
+\item{n_sigfig}{A option to format numbers to \emph{n} significant figures. By
+default, this is \code{NULL} and thus number values will be formatted according
+to the number of decimal places set via \code{decimals}. If opting to format
+according to the rules of significant figures, \code{n_sigfig} must be a number
+greater than or equal to \code{1}. Any values passed to the \code{decimals} and
+\code{drop_trailing_zeros} arguments will be ignored.}
+
 \item{drop_trailing_zeros}{A logical value that allows for removal of
 trailing zeros (those redundant zeros after the decimal mark).}
 
+\item{drop_trailing_dec_mark}{A logical value that determines whether decimal
+marks should always appear even if there are no decimal digits to display
+after formatting (e.g, \code{23} becomes \code{23.}). The default for this is \code{TRUE},
+which means that trailing decimal marks are not shown.}
+
 \item{use_seps}{An option to use digit group separators. The type of digit
 group separator is set by \code{sep_mark} and overridden if a locale ID is
 provided to \code{locale}. This setting is \code{TRUE} by default.}
diff --git a/man/fmt_percent.Rd b/man/fmt_percent.Rd
index 139a0ea85..993004607 100644
--- a/man/fmt_percent.Rd
+++ b/man/fmt_percent.Rd
@@ -10,6 +10,7 @@ fmt_percent(
   rows = NULL,
   decimals = 2,
   drop_trailing_zeros = FALSE,
+  drop_trailing_dec_mark = TRUE,
   scale_values = TRUE,
   use_seps = TRUE,
   pattern = "{x}",
@@ -42,6 +43,11 @@ use. The default number of decimal places is \code{2}.}
 \item{drop_trailing_zeros}{A logical value that allows for removal of
 trailing zeros (those redundant zeros after the decimal mark).}
 
+\item{drop_trailing_dec_mark}{A logical value that determines whether decimal
+marks should always appear even if there are no decimal digits to display
+after formatting (e.g, \code{23} becomes \code{23.}). The default for this is \code{TRUE},
+which means that trailing decimal marks are not shown.}
+
 \item{scale_values}{Should the values be scaled through multiplication by
 100? By default this is \code{TRUE} since the expectation is that normally
 values are proportions. Setting to \code{FALSE} signifies that the values are
diff --git a/tests/testthat/test-cols_width.R b/tests/testthat/test-cols_width.R
index 6bb97cf4e..62f1bb884 100644
--- a/tests/testthat/test-cols_width.R
+++ b/tests/testthat/test-cols_width.R
@@ -112,10 +112,10 @@ test_that("the function `cols_width()` works correctly", {
   tbl_html %>% render_as_html() %>%
     html_fragment_within(
       "<colgroup>",
-      "<col style=\"\"/>",
-      "<col style=\"\"/>",
-      "<col style=\"\"/>",
-      "<col style=\"\"/>",
+      "<col/>",
+      "<col/>",
+      "<col/>",
+      "<col/>",
       "</colgroup>"
     ) %>%
     expect_true()
@@ -140,7 +140,7 @@ test_that("the function `cols_width()` works correctly", {
       "<col style=\"width:100px;\"/>",
       "<col style=\"width:200px;\"/>",
       "<col style=\"width:20%;\"/>",
-      "<col style=\"\"/>",
+      "<col/>",
       "</colgroup>"
     ) %>%
     expect_true()
@@ -162,8 +162,8 @@ test_that("the function `cols_width()` works correctly", {
       "<colgroup>",
       "<col style=\"width:150px;\"/>",
       "<col style=\"width:150px;\"/>",
-      "<col style=\"\"/>",
-      "<col style=\"\"/>",
+      "<col/>",
+      "<col/>",
       "</colgroup>"
     ) %>%
     expect_true()
diff --git a/tests/testthat/test-fmt_number.R b/tests/testthat/test-fmt_number.R
index 748546337..96580367a 100644
--- a/tests/testthat/test-fmt_number.R
+++ b/tests/testthat/test-fmt_number.R
@@ -384,6 +384,256 @@ test_that("the `fmt_number()` function can scale/suffix larger numbers", {
     "999.99990")
 })
 
+test_that("the `fmt_number()` function format to specified significant figures", {
+
+  # These numbers will be used in tests of formatting
+  # correctly to n significant figures
+  numbers <-
+    c(
+      50000.01,        #1
+      1000.001,        #2
+      10.00001,        #3
+      12345,           #4
+      1234.5,          #5
+      123.45,          #6
+      1.2345,          #7
+      0.12345,         #8
+      0.0000123456,    #9
+      -50000.01,      #10
+      -1000.001,      #11
+      -10.00001,      #12
+      -12345,         #13
+      -1234.5,        #14
+      -123.45,        #15
+      -1.2345,        #16
+      -0.12345,       #17
+      -0.0000123456   #18
+    )
+
+  # Create a single-column tibble with these values in `num`
+  numbers_tbl <- dplyr::tibble(num = numbers)
+
+  # Create a `gt_tbl` object with `gt()` and the
+  # `numbers_tbl` dataset
+  tab <- gt(data = numbers_tbl)
+
+  # Format the `num` column to 5 significant figures
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", n_sigfig = 5) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c("50,000", "1,000.0", "10.000", "12,345", "1,234.5", "123.45",
+      "1.2345", "0.12345", "0.000012346", "&minus;50,000", "&minus;1,000.0",
+      "&minus;10.000", "&minus;12,345", "&minus;1,234.5", "&minus;123.45",
+      "&minus;1.2345", "&minus;0.12345", "&minus;0.000012346"
+    )
+  )
+
+  # Format the `num` column to 4 significant figures
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", n_sigfig = 4) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c("50,000", "1,000", "10.00", "12,340", "1,234", "123.4", "1.234",
+      "0.1234", "0.00001235", "&minus;50,000", "&minus;1,000", "&minus;10.00",
+      "&minus;12,340", "&minus;1,234", "&minus;123.4", "&minus;1.234",
+      "&minus;0.1234", "&minus;0.00001235"
+    )
+  )
+
+  # Format the `num` column to 3 significant figures
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", n_sigfig = 3) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c("50,000", "1,000", "10.0", "12,300", "1,230", "123", "1.23",
+      "0.123", "0.0000123", "&minus;50,000", "&minus;1,000", "&minus;10.0",
+      "&minus;12,300", "&minus;1,230", "&minus;123", "&minus;1.23",
+      "&minus;0.123", "&minus;0.0000123"
+    )
+  )
+
+  # Format the `num` column to 2 significant figures
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", n_sigfig = 2) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c("50,000", "1,000", "10", "12,000", "1,200", "120", "1.2", "0.12",
+      "0.000012", "&minus;50,000", "&minus;1,000", "&minus;10", "&minus;12,000",
+      "&minus;1,200", "&minus;120", "&minus;1.2", "&minus;0.12", "&minus;0.000012"
+    )
+  )
+
+  # Format the `num` column to 1 significant figure
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", n_sigfig = 1) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c("50,000", "1,000", "10", "10,000", "1,000", "100", "1", "0.1",
+      "0.00001", "&minus;50,000", "&minus;1,000", "&minus;10", "&minus;10,000",
+      "&minus;1,000", "&minus;100", "&minus;1", "&minus;0.1", "&minus;0.00001"
+    )
+  )
+
+  # Expect an error if the length of `n_sigfig` is not 1
+  expect_error(fmt_number(columns = "num", n_sigfig = c(1, 2)))
+
+  # Expect an error if `n_sigfig` is NA
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = NA))
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = NA_integer_))
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = NA_real_))
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = NA_integer_))
+
+  # Expect an error if `n_sigfig` is not numeric
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = "3"))
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = TRUE))
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = factor(3)))
+
+  # Don't expect errors when using integers or doubles
+  expect_error(regexp = NA, tab %>% fmt_number(columns = "num", n_sigfig = 2L))
+  expect_error(regexp = NA, tab %>% fmt_number(columns = "num", n_sigfig = 2))
+
+  # Expect an error if `n_sigfig` is less than 1
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = 0L))
+  expect_error(tab %>% fmt_number(columns = "num", n_sigfig = -1L))
+})
+
+
+test_that("the `drop_trailing_dec_mark` option works in select `fmt_*()` functions", {
+
+  # These numbers will be used in tests with `drop_trailing_dec_mark = FALSE`
+  numbers <- c(0.001, 0.01, 0.1, 0, 1, 1.1, 1.12, 50000, -1.5, -5, -500.1)
+
+  # Create a single-column tibble with these values in `num`
+  numbers_tbl <- dplyr::tibble(num = numbers)
+
+  # Create a `gt_tbl` object with `gt()` and the
+  # `numbers_tbl` dataset
+  tab <- gt(data = numbers_tbl)
+
+  # Format the `num` column using `fmt_number()` with default options
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", drop_trailing_dec_mark = TRUE) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0.00", "0.01", "0.10", "0.00", "1.00", "1.10", "1.12", "50,000.00",
+      "&minus;1.50", "&minus;5.00", "&minus;500.10"
+    )
+  )
+
+  # Format the `num` column using `fmt_number()` with `decimals = 0`
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", decimals = 0) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0", "0", "0", "0", "1", "1", "1", "50,000", "&minus;2", "&minus;5",
+      "&minus;500"
+    )
+  )
+
+  # Format the `num` column using `fmt_number()` with `decimals = 0` and
+  # `drop_trailing_dec_mark = FALSE`
+  expect_equal(
+    (tab %>%
+       fmt_number(columns = "num", decimals = 0, drop_trailing_dec_mark = FALSE) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0.", "0.", "0.", "0.", "1.", "1.", "1.", "50,000.", "&minus;2.",
+      "&minus;5.", "&minus;500."
+    )
+  )
+
+  # Format the `num` column using `fmt_percent()` with default options
+  expect_equal(
+    (tab %>%
+       fmt_percent(columns = "num", drop_trailing_dec_mark = TRUE) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0.10&percnt;", "1.00&percnt;", "10.00&percnt;", "0.00&percnt;",
+      "100.00&percnt;", "110.00&percnt;", "112.00&percnt;", "5,000,000.00&percnt;",
+      "&minus;150.00&percnt;", "&minus;500.00&percnt;", "&minus;50,010.00&percnt;"
+    )
+  )
+
+  # Format the `num` column using `fmt_percent()` with `decimals = 0`
+  expect_equal(
+    (tab %>%
+       fmt_percent(columns = "num", decimals = 0) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0&percnt;", "1&percnt;", "10&percnt;", "0&percnt;", "100&percnt;",
+      "110&percnt;", "112&percnt;", "5,000,000&percnt;", "&minus;150&percnt;",
+      "&minus;500&percnt;", "&minus;50,010&percnt;"
+    )
+  )
+
+  # Format the `num` column using `fmt_percent()` with `decimals = 0` and
+  # `drop_trailing_dec_mark = FALSE`
+  expect_equal(
+    (tab %>%
+       fmt_percent(columns = "num", decimals = 0, drop_trailing_dec_mark = FALSE) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0.&percnt;", "1.&percnt;", "10.&percnt;", "0.&percnt;", "100.&percnt;",
+      "110.&percnt;", "112.&percnt;", "5,000,000.&percnt;", "&minus;150.&percnt;",
+      "&minus;500.&percnt;", "&minus;50,010.&percnt;"
+    )
+  )
+
+  # Format the `num` column using `fmt_currency()` with default options
+  expect_equal(
+    (tab %>%
+       fmt_currency(columns = "num", drop_trailing_dec_mark = TRUE) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "$0.00", "$0.01", "$0.10", "$0.00", "$1.00", "$1.10", "$1.12",
+      "$50,000.00", "&minus;$1.50", "&minus;$5.00", "&minus;$500.10"
+    )
+  )
+
+  # Format the `num` column using `fmt_currency()` with `decimals = 0`
+  expect_equal(
+    (tab %>%
+       fmt_currency(columns = "num", decimals = 0) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "$0", "$0", "$0", "$0", "$1", "$1", "$1", "$50,000", "&minus;$2",
+      "&minus;$5", "&minus;$500"
+    )
+  )
+
+  # Format the `num` column using `fmt_currency()` with `decimals = 0` and
+  # `drop_trailing_dec_mark = FALSE`
+  expect_equal(
+    (tab %>%
+       fmt_currency(columns = "num", decimals = 0, drop_trailing_dec_mark = FALSE) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "$0.", "$0.", "$0.", "$0.", "$1.", "$1.", "$1.", "$50,000.",
+      "&minus;$2.", "&minus;$5.", "&minus;$500."
+    )
+  )
+
+  # Format the `num` column using `fmt_currency()` with `decimals = 0`,
+  # `drop_trailing_dec_mark = FALSE`, and placement of the currency
+  # symbol ("EUR") to the right-hand side of the figure
+  expect_equal(
+    (tab %>%
+       fmt_currency(
+         columns = "num", currency = "EUR", decimals = 0,
+         placement = "right", drop_trailing_dec_mark = FALSE
+       ) %>%
+       render_formats_test(context = "html"))[["num"]],
+    c(
+      "0.&#8364;", "0.&#8364;", "0.&#8364;", "0.&#8364;", "1.&#8364;",
+      "1.&#8364;", "1.&#8364;", "50,000.&#8364;", "&minus;2.&#8364;",
+      "&minus;5.&#8364;", "&minus;500.&#8364;"
+    )
+  )
+})
+
 test_that("`fmt_number()` with `suffixing = TRUE` works with small numbers", {
 
   # Create an input data frame with a single column

From 6058358fe2f56901f2ef175fb74fa655e0b9793b Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Mon, 13 Jul 2020 16:28:24 -0400
Subject: [PATCH 25/30] Settable font options (#591)

* Add parital implementation of custom font support

* Add partial implementation of better font support

* Add the `add` option to `opt_font()`

* Make further refinements on expanded font support

* Update google_fonts_process.R

* Update google_fonts_process.R

* Make modifications based on code review

* Add `info_google_fonts()` information fcn

* Change fcn name and add some testthat tests

* Add more testthat tests

* Update test-opt_functions.R

* Put Google Fonts processing in sysdata pipeline

* Add CSS builder functions and docs

* Add documentation assets

* Make changes based on code review

* Reexport `css()` and update documentation

* Update DESCRIPTION

* Use correct dimension values in testthat test
---
 DESCRIPTION                                   |    2 +-
 NAMESPACE                                     |    7 +
 R/compile_scss.R                              |   21 +-
 R/dt_options.R                                |   13 +-
 R/helpers.R                                   |  202 +-
 R/info_tables.R                               |  205 +-
 R/opts.R                                      |  242 ++
 R/reexports.R                                 |    4 +
 R/sysdata.rda                                 |  Bin 117513 -> 191478 bytes
 R/tab_create_modify.R                         |   91 +-
 R/utils.R                                     |   12 +-
 R/utils_render_html.R                         |   42 +-
 R/zzz.R                                       |   10 +
 _pkgdown.yml                                  |    8 +-
 data-raw/X04-palettes_strips.R                |    5 +
 data-raw/X05-google_fonts.R                   |  140 +
 data-raw/zz_process_datasets_ext.R            |    2 +
 inst/css/external.css                         |   11 +
 inst/css/gt_styles_default.scss               |    2 +
 inst/extdata/google_axes_tbl.csv              |   59 +
 inst/extdata/google_font_tbl.csv              | 1008 +++++++
 inst/extdata/google_styles_tbl.csv            | 2683 +++++++++++++++++
 man/adjust_luminance.Rd                       |    4 +-
 man/cell_borders.Rd                           |    2 +
 man/cell_fill.Rd                              |    2 +
 man/cell_text.Rd                              |    6 +-
 man/cells_body.Rd                             |    2 +
 man/cells_column_labels.Rd                    |    2 +
 man/cells_column_spanners.Rd                  |    2 +
 man/cells_grand_summary.Rd                    |    2 +
 man/cells_row_groups.Rd                       |    2 +
 man/cells_stub.Rd                             |    2 +
 man/cells_stubhead.Rd                         |    2 +
 man/cells_summary.Rd                          |    2 +
 man/cells_title.Rd                            |    2 +
 man/currency.Rd                               |    2 +
 man/default_fonts.Rd                          |   81 +
 man/escape_latex.Rd                           |    4 +-
 man/figures/man_cols_width_1.png              |  Bin 36577 -> 36577 bytes
 man/figures/man_default_fonts_1.png           |  Bin 0 -> 16127 bytes
 man/figures/man_google_font_1.png             |  Bin 0 -> 14827 bytes
 man/figures/man_google_font_2.png             |  Bin 0 -> 85656 bytes
 man/figures/man_info_google_fonts_1.png       |  Bin 0 -> 188535 bytes
 man/figures/man_opt_css_1.png                 |  Bin 0 -> 25815 bytes
 man/figures/man_opt_table_font_1.png          |  Bin 0 -> 45023 bytes
 man/figures/man_opt_table_font_2.png          |  Bin 0 -> 18357 bytes
 man/figures/man_tab_style_3.png               |  Bin 0 -> 15895 bytes
 man/google_font.Rd                            |  113 +
 man/gt_latex_dependencies.Rd                  |    4 +-
 man/html.Rd                                   |    2 +
 man/info_currencies.Rd                        |    8 +-
 man/info_date_style.Rd                        |    6 +-
 man/info_google_fonts.Rd                      |   43 +
 man/info_locales.Rd                           |    4 +
 man/info_paletteer.Rd                         |    4 +
 man/info_time_style.Rd                        |    6 +-
 man/md.Rd                                     |    2 +
 man/opt_align_table_header.Rd                 |    2 +
 man/opt_all_caps.Rd                           |    2 +
 man/opt_css.Rd                                |   86 +
 man/opt_footnote_marks.Rd                     |    2 +
 man/opt_row_striping.Rd                       |    2 +
 man/opt_table_font.Rd                         |  120 +
 man/opt_table_lines.Rd                        |    2 +
 man/opt_table_outline.Rd                      |    2 +
 man/pct.Rd                                    |    2 +
 man/px.Rd                                     |    2 +
 man/random_id.Rd                              |    4 +-
 man/reexports.Rd                              |    3 +
 man/tab_options.Rd                            |   39 +-
 man/tab_style.Rd                              |   26 +-
 .../html-16-table_options_everywhere.R        |    4 +-
 tests/testthat/helper-gt_attr_expectations.R  |    2 +-
 tests/testthat/test-info_tables.R             |   17 +
 tests/testthat/test-opt_functions.R           |  111 +
 tests/testthat/test-tab_style.R               |   40 +
 tests/testthat/test-util_functions.R          |    5 +-
 77 files changed, 5467 insertions(+), 86 deletions(-)
 create mode 100644 data-raw/X05-google_fonts.R
 create mode 100644 inst/css/external.css
 create mode 100644 inst/extdata/google_axes_tbl.csv
 create mode 100644 inst/extdata/google_font_tbl.csv
 create mode 100644 inst/extdata/google_styles_tbl.csv
 create mode 100644 man/default_fonts.Rd
 create mode 100644 man/figures/man_default_fonts_1.png
 create mode 100644 man/figures/man_google_font_1.png
 create mode 100644 man/figures/man_google_font_2.png
 create mode 100644 man/figures/man_info_google_fonts_1.png
 create mode 100644 man/figures/man_opt_css_1.png
 create mode 100644 man/figures/man_opt_table_font_1.png
 create mode 100644 man/figures/man_opt_table_font_2.png
 create mode 100644 man/figures/man_tab_style_3.png
 create mode 100644 man/google_font.Rd
 create mode 100644 man/info_google_fonts.Rd
 create mode 100644 man/opt_css.Rd
 create mode 100644 man/opt_table_font.Rd

diff --git a/DESCRIPTION b/DESCRIPTION
index eecbd6a18..59157168f 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -23,7 +23,7 @@ BugReports: https://github.com/rstudio/gt/issues
 Encoding: UTF-8
 LazyData: true
 ByteCompile: true
-RoxygenNote: 7.1.0.9000
+RoxygenNote: 7.1.1
 Depends:
     R (>= 3.2.0)
 Imports: 
diff --git a/NAMESPACE b/NAMESPACE
index 854f0bbfa..067929eb0 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -32,8 +32,10 @@ export(cols_move_to_end)
 export(cols_move_to_start)
 export(cols_width)
 export(contains)
+export(css)
 export(currency)
 export(data_color)
+export(default_fonts)
 export(ends_with)
 export(escape_latex)
 export(everything)
@@ -50,6 +52,7 @@ export(fmt_percent)
 export(fmt_scientific)
 export(fmt_time)
 export(ggplot_image)
+export(google_font)
 export(grand_summary_rows)
 export(gt)
 export(gt_latex_dependencies)
@@ -59,6 +62,7 @@ export(gtsave)
 export(html)
 export(info_currencies)
 export(info_date_style)
+export(info_google_fonts)
 export(info_locales)
 export(info_paletteer)
 export(info_time_style)
@@ -68,8 +72,10 @@ export(md)
 export(one_of)
 export(opt_align_table_header)
 export(opt_all_caps)
+export(opt_css)
 export(opt_footnote_marks)
 export(opt_row_striping)
+export(opt_table_font)
 export(opt_table_lines)
 export(opt_table_outline)
 export(pct)
@@ -96,6 +102,7 @@ import(rlang)
 import(tidyselect)
 importFrom(dplyr,vars)
 importFrom(ggplot2,ggsave)
+importFrom(htmltools,css)
 importFrom(magrittr,"%>%")
 importFrom(tidyselect,contains)
 importFrom(tidyselect,ends_with)
diff --git a/R/compile_scss.R b/R/compile_scss.R
index 5be69212a..0499ddf48 100644
--- a/R/compile_scss.R
+++ b/R/compile_scss.R
@@ -9,6 +9,21 @@ compile_scss <- function(data, id = NULL) {
 
   has_id <- !is.null(id)
 
+  # Get the vector of fonts and transform to a `font-family` string
+  font_vec <- unique(dt_options_get_value(data = data, option = "table_font_names"))
+  font_family_attr <- as_css_font_family_attr(font_vec = font_vec)
+
+  # Get any additional CSS statements
+  additional_css <- dt_options_get_value(data = data, option = "table_additional_css")
+
+  # Determine if there are any additional CSS statements
+  has_additional_css <- any(nchar(additional_css) > 0)
+
+  # Combine any additional CSS statements and separate with `\n`
+  if (has_additional_css) {
+    table_additional_css <- paste(additional_css, collapse = "\n") %>% paste_right("\n")
+  }
+
   sass::sass(
     list(
       list(element_id = id),
@@ -19,14 +34,14 @@ compile_scss <- function(data, id = NULL) {
         .open = "<<", .close = ">>",
         "
         <<ifelse(has_id, 'html', '.gt_table')>> {
-          font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto,
-            Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans',
-            Arial, sans-serif;
+          <<font_family_attr>>
         }
 
         <<ifelse(has_id, '##{$element_id} {', '')>>
         @include gt_styles();
         <<ifelse(has_id, '}', '')>>
+
+        <<ifelse(has_additional_css, table_additional_css, '')>>
         ")
     )
   )
diff --git a/R/dt_options.R b/R/dt_options.R
index dcf3a0064..8be9d5e31 100644
--- a/R/dt_options.R
+++ b/R/dt_options.R
@@ -36,6 +36,13 @@ dt_options_get_value <- function(data, option) {
   dt_options$value[[which(dt_options$parameter == option)]]
 }
 
+default_fonts_vec <-
+  c(
+    "-apple-system", "BlinkMacSystemFont", "Segoe UI", "Roboto",
+    "Oxygen", "Ubuntu", "Cantarell", "Helvetica Neue", "Fira Sans",
+    "Droid Sans", "Arial", "sans-serif"
+  )
+
 dt_options_tbl <-
   dplyr::tribble(
     ~parameter,                          ~scss,  ~category,          ~type,     ~value,
@@ -50,9 +57,13 @@ dt_options_tbl <-
     "table_margin_left",                  TRUE,  "table",            "px",      "auto",
     "table_margin_right",                 TRUE,  "table",            "px",      "auto",
     "table_background_color",             TRUE,  "table",            "value",   "#FFFFFF",
+    "table_additional_css",              FALSE,  "table",            "values",  character(0),
+    "table_font_names",                  FALSE,  "table",            "values",  default_fonts_vec,
+    "table_font_size",                    TRUE,  "table",            "px",      "16px",
+    "table_font_weight",                  TRUE,  "table",            "value",   "normal",
+    "table_font_style",                   TRUE,   "table",           "value",   "normal",
     "table_font_color",                   TRUE,  "table",            "value",   "#333333",
     "table_font_color_light",             TRUE,  "table",            "value",   "#FFFFFF",
-    "table_font_size",                    TRUE,  "table",            "px",      "16px",
     "table_border_top_include",          FALSE,  "table",            "logical", TRUE,
     "table_border_top_style",             TRUE,  "table",            "value",   "solid",
     "table_border_top_width",             TRUE,  "table",            "px",      "2px",
diff --git a/R/helpers.R b/R/helpers.R
index 20ed61ca7..47dcbdfa1 100644
--- a/R/helpers.R
+++ b/R/helpers.R
@@ -1128,8 +1128,8 @@ currency <- function(...,
 #'   function. We can also use one of the following absolute size keywords:
 #'   `"xx-small"`, `"x-small"`, `"small"`, `"medium"`, `"large"`, `"x-large"`,
 #'   or `"xx-large"`.
-#' @param style The text style. Can be one of either `"center"`, `"normal"`,
-#'   `"italic"`, or `"oblique"`.
+#' @param style The text style. Can be one of either `"normal"`, `"italic"`, or
+#'   `"oblique"`.
 #' @param weight The weight of the font. Can be a text-based keyword such as
 #'   `"normal"`, `"bold"`, `"lighter"`, `"bolder"`, or, a numeric value between
 #'   `1` and `1000`, inclusive. Note that only variable fonts may support the
@@ -1219,43 +1219,52 @@ cell_text <- function(color = NULL,
   #
 
   validate_style_in(
-    style_vals, style_names, "align",
-    c("center", "left", "right", "justify")
+    style_vals, style_names,
+    arg_name = "align",
+    in_vector = c("center", "left", "right", "justify")
   )
 
   validate_style_in(
-    style_vals, style_names, "v_align",
-    c("middle", "top", "bottom")
+    style_vals, style_names,
+    arg_name = "v_align",
+    in_vector = c("middle", "top", "bottom")
   )
 
   validate_style_in(
-    style_vals, style_names, "style",
-    c("normal", "italic", "oblique")
+    style_vals, style_names,
+    arg_name = "style",
+    in_vector = c("normal", "italic", "oblique")
   )
 
   validate_style_in(
-    style_vals, style_names, "weight",
-    c("normal", "bold", "lighter", "bolder")
+    style_vals, style_names,
+    arg_name = "weight",
+    in_vector = c("normal", "bold", "lighter", "bolder"),
+    with_pattern = "[1-9][0-9][0-9]"
   )
 
   validate_style_in(
-    style_vals, style_names, "stretch",
-    c("ultra-condensed", "extra-condensed", "condensed",
+    style_vals, style_names, arg_name = "stretch",
+    in_vector = c(
+      "ultra-condensed", "extra-condensed", "condensed",
       "semi-condensed", "normal", "semi-expanded", "expanded",
-      "extra-expanded", "ultra-expanded")
+      "extra-expanded", "ultra-expanded"
+    )
   )
 
   validate_style_in(
-    style_vals, style_names, "decorate",
-    c("overline", "line-through", "underline", "underline overline")
+    style_vals, style_names,
+    arg_name = "decorate",
+    in_vector = c("overline", "line-through", "underline", "underline overline")
   )
 
   validate_style_in(
-    style_vals, style_names, "transform",
-    c("uppercase", "lowercase", "capitalize")
+    style_vals, style_names,
+    arg_name = "transform",
+    in_vector = c("uppercase", "lowercase", "capitalize")
   )
 
-  cell_style_structure("cell_text", style_vals)
+  cell_style_structure(name = "cell_text", obj = style_vals)
 }
 
 cell_style_to_html.cell_text <- function(style) {
@@ -1544,6 +1553,155 @@ cell_style_structure <- function(name, obj, subclass = name) {
   style_obj
 }
 
+#' Helper function for specifying a font from the Google Fonts service
+#'
+#' The `google_font()` helper function can be used wherever a font name should
+#' be specified. There are two instances where this helper can be used: the
+#' `name` argument in [opt_table_font()] (for setting a table font) and in that
+#' of [cell_text()] (used with [tab_style()]). To get a helpful listing of fonts
+#' that work well in tables, use the [info_google_fonts()] function.
+#'
+#' @param name The complete name of a font available in Google Fonts.
+#'
+#' @return An object of class `font_css`.
+#'
+#' @examples
+#' if (interactive()) {
+#'
+#' # Use `exibble` to create a gt table of
+#' # eight rows, replace missing values with
+#' # em dashes; for text in the `time` column,
+#' # we use the Google font 'IBM Plex Mono'
+#' # and set up the `default_fonts()` as
+#' # fallbacks (just in case the webfont is
+#' # not accessible)
+#' tab_1 <-
+#'   exibble %>%
+#'   dplyr::select(char, time) %>%
+#'   gt() %>%
+#'   fmt_missing(columns = everything()) %>%
+#'   tab_style(
+#'     style = cell_text(
+#'       font = c(
+#'         google_font(name = "IBM Plex Mono"),
+#'         default_fonts()
+#'       )
+#'     ),
+#'     locations = cells_body(columns = vars(time))
+#'   )
+#'
+#' # Use `sp500` to create a small gt table,
+#' # using `fmt_currency()` to provide a
+#' # dollar sign for the first row of monetary
+#' # values; then, set a larger font size for
+#' # the table and use the 'Merriweather' font
+#' # using the `google_font()` function (with
+#' # two font fallbacks: 'Cochin' and the
+#' # catchall 'Serif' group)
+#' tab_2 <-
+#'   sp500 %>%
+#'   dplyr::slice(1:10) %>%
+#'   dplyr::select(-volume, -adj_close) %>%
+#'   gt() %>%
+#'   fmt_currency(
+#'     columns = 2:5,
+#'     rows = 1,
+#'     currency = "USD",
+#'     use_seps = FALSE
+#'   ) %>%
+#'   tab_options(table.font.size = px(20)) %>%
+#'   opt_table_font(
+#'     font = list(
+#'       google_font(name = "Merriweather"),
+#'       "Cochin", "Serif"
+#'     )
+#'   )
+#' }
+#'
+#' @section Figures:
+#' \if{html}{\figure{man_google_font_1.png}{options: width=100\%}}
+#'
+#' \if{html}{\figure{man_google_font_2.png}{options: width=100\%}}
+#'
+#' @family Helper Functions
+#' @section Function ID:
+#' 7-18
+#'
+#' @export
+google_font <- function(name) {
+
+  import_stmt <-
+    name %>% tidy_gsub(" ", "+") %>%
+    paste_between(
+      c(
+        "@import url('https://fonts.googleapis.com/css2?family=",
+        ":ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap');"
+      )
+    )
+
+  font_list <-
+    list(
+      name = name,
+      import_stmt = import_stmt
+    )
+
+  class(font_list) <- "font_css"
+  font_list
+}
+
+#' A vector of default fonts for use with **gt** tables
+#'
+#' The vector of fonts given by `default_fonts()` should be used with a **gt**
+#' table that is rendered to HTML. We can specify additional fonts to use but
+#' this default set should be placed after that to act as fallbacks. This is
+#' useful when specifying `font` values in the [cell_text()] function (itself
+#' used in the [tab_style()] function). If using [opt_table_font()] (which also
+#' has a `font` argument) we probably don't need to specify this vector of fonts
+#' since it is handled by its `add` option (which is `TRUE` by default).
+#'
+#' @return A character vector of font names.
+#'
+#' @examples
+#' # Use `exibble` to create a gt table;
+#' # attempting to modify the fonts used
+#' # for the `time` column is much safer
+#' # if `default_fonts()` is appended to
+#' # the end of the `font` listing in the
+#' # `cell_text()` call (the "Comic Sansa"
+#' # and "Menloa" fonts don't exist, but,
+#' # we'll get the first available font
+#' # from the `default_fonts()` set)
+#' tab_1 <-
+#'   exibble %>%
+#'   dplyr::select(char, time) %>%
+#'   gt() %>%
+#'   tab_style(
+#'     style = cell_text(
+#'       font = c(
+#'         "Comic Sansa", "Menloa",
+#'         default_fonts()
+#'       )
+#'     ),
+#'     locations = cells_body(columns = vars(time))
+#'   )
+#'
+#' @section Figures:
+#' \if{html}{\figure{man_default_fonts_1.png}{options: width=100\%}}
+#'
+#' @family Helper Functions
+#'
+#' @section Function ID:
+#' 7-19
+#'
+#' @export
+default_fonts <- function() {
+  c(
+    "-apple-system", "BlinkMacSystemFont", "Segoe UI", "Roboto",
+    "Oxygen", "Ubuntu", "Cantarell", "Helvetica Neue", "Fira Sans",
+    "Droid Sans", "Arial", "sans-serif"
+  )
+}
+
 #' Adjust the luminance for a palette of colors
 #'
 #' This function can brighten or darken a palette of colors by an arbitrary
@@ -1611,7 +1769,7 @@ cell_style_structure <- function(name, obj, subclass = name) {
 #'
 #' @family Helper Functions
 #' @section Function ID:
-#' 7-18
+#' 7-20
 #'
 #' @export
 adjust_luminance <- function(colors,
@@ -1664,7 +1822,7 @@ adjust_luminance <- function(colors,
 #'
 #' @family Helper Functions
 #' @section Function ID:
-#' 7-19
+#' 7-21
 #'
 #' @export
 random_id <- function(n = 10) {
@@ -1685,7 +1843,7 @@ random_id <- function(n = 10) {
 #'
 #' @family Helper Functions
 #' @section Function ID:
-#' 7-20
+#' 7-22
 #'
 #' @export
 escape_latex <- function(text) {
@@ -1737,7 +1895,7 @@ escape_latex <- function(text) {
 #'
 #' @family Helper Functions
 #' @section Function ID:
-#' 7-21
+#' 7-23
 #'
 #' @export
 gt_latex_dependencies <- function() {
diff --git a/R/info_tables.R b/R/info_tables.R
index 6a422bdfd..6dfef8687 100644
--- a/R/info_tables.R
+++ b/R/info_tables.R
@@ -1,11 +1,13 @@
 #' View a table with info on date styles
 #'
-#' The `fmt_date()` function lets us format date-based values in a convenient
+#' The [fmt_date()] function lets us format date-based values in a convenient
 #' manner using preset styles. The table generated by the `info_date_style()`
 #' function provides a quick reference to all 14 styles, with associated number
 #' codes, the format names, and example outputs using a fixed date
 #' (`2000-02-29`).
 #'
+#' @return An object of class `gt_tbl`.
+#'
 #' @examples
 #' # Get a table of info on the different
 #' # date-formatting styles (which are used
@@ -62,12 +64,14 @@ info_date_style <- function() {
 
 #' View a table with info on time styles
 #'
-#' The `fmt_time()` function lets us format time-based values in a convenient
+#' The [fmt_time()] function lets us format time-based values in a convenient
 #' manner using preset styles. The table generated by the `info_time_style()`
 #' function provides a quick reference to all five styles, with associated
 #' number codes, the format names, and example outputs using a fixed time
 #' (`14:35`).
 #'
+#' @return An object of class `gt_tbl`.
+#'
 #' @examples
 #' # Get a table of info on the different
 #' # time-formatting styles (which are used
@@ -112,8 +116,8 @@ info_time_style <- function() {
 
 #' View a table with info on supported currencies
 #'
-#' The `fmt_currency()` function lets us format numeric values as currencies.
-#' The table generated by the `info_currencies()` function provides a quick
+#' The [fmt_currency()] function lets us format numeric values as currencies.
+#' The table generated by the [info_currencies()] function provides a quick
 #' reference to all the available currencies. The currency identifiers are
 #' provided (name, 3-letter currency code, and 3-digit currency code) along with
 #' the each currency's exponent value (number of digits of the currency
@@ -135,6 +139,8 @@ info_time_style <- function() {
 #'   (`NULL`) will produce a table with all currencies displayed. This option
 #'   only constrains the information table where `type == "code"`.
 #'
+#' @return An object of class `gt_tbl`.
+#'
 #' @examples
 #' # Get a table of info on all of
 #' # the currencies where the three-
@@ -284,6 +290,8 @@ info_currencies <- function(type = c("code", "symbol"),
 #'   those that begin with that letter in their base locale ID. The default
 #'   (`NULL`) will produce a table with all locales displayed.
 #'
+#' @return An object of class `gt_tbl`.
+#'
 #' @examples
 #' # Get a table of info on all of
 #' # the locales where the base
@@ -416,6 +424,9 @@ info_locales <- function(begins_with = NULL) {
 #'   palettes should be displayed in the information table. If this is
 #'   `NULL` (the default) then all of the discrete palettes from all of the
 #'   color packages represented in **paletteer** will be displayed.
+#'
+#' @return An object of class `gt_tbl`.
+#'
 #' @examples
 #' # Get a table of info on just the
 #' # `ggthemes` color palette (easily
@@ -505,3 +516,189 @@ info_paletteer <- function(color_pkgs = NULL) {
       )
     )
 }
+
+
+#' View a table on recommended Google Fonts
+#'
+#' The [google_font()] helper function can be used wherever a font name should
+#' be specified. There are two instances where this helper can be used: the
+#' `name` argument in [opt_table_font()] (for setting a table font) and in that
+#' of [cell_text()] (used with [tab_style()]). Because there is an overwhelming
+#' number of fonts available in the *Google Fonts* catalog, the
+#' `info_google_fonts()` provides a table with a set of helpful font
+#' recommendations. These fonts look great in the different parts of a **gt**
+#' table. Why? For the most part they are suitable for body text, having large
+#' counters, large x-height, reasonably low contrast, and open apertures. These
+#' font features all make for high legibility at smaller sizes.
+#'
+#' @return An object of class `gt_tbl`.
+#'
+#' @examples
+#' # Get a table of info on some of the
+#' # recommended Google Fonts for tables
+#' tab_1 <- info_google_fonts()
+#'
+#' @family Information Functions
+#' @section Function ID:
+#' 10-6
+#'
+#' @export
+info_google_fonts <- function() {
+
+  # Recommended Fonts
+  recommended <-
+    c(
+      "Space Mono",
+      "Work Sans",
+      "Inter",
+      "Rubik",
+      "Libre Franklin",
+      "Comorant",
+      "Fira Sans",
+      "Fira Code",
+      "Eczar",
+      "Chivo",
+      "Inknut",
+      "Source Sans Pro",
+      "Source Serif Pro",
+      "Roboto",
+      "Roboto Slab",
+      "BioRhyme",
+      "Poppins",
+      "Archivo Narrow",
+      "Libre Baskerville",
+      "Playfair Display",
+      "Karla",
+      "Encode Sans",
+      "Lora",
+      "Proza Libre",
+      "Spectral",
+      "IBM Plex Sans",
+      "IBM Plex Mono",
+      "Crimson Text",
+      "Montserrat",
+      "PT Sans",
+      "PT Serif",
+      "Lato",
+      "Cardo",
+      "Open Sans",
+      "Inconsolata",
+      "Cabin",
+      "Raleway",
+      "Anonymous Pro",
+      "Merriweather",
+      "Exo 2",
+      "Public Sans",
+      "Muli"
+    )
+
+  styles_summary <-
+    google_styles_tbl %>%
+    dplyr::mutate(weight = as.integer(weight)) %>%
+    dplyr::filter(name %in% recommended) %>%
+    dplyr::group_by(name, style) %>%
+    dplyr::summarize(min_weight = min(weight), max_weight = max(weight)) %>%
+    dplyr::ungroup() %>%
+    dplyr::arrange(name, dplyr::desc(style)) %>%
+    dplyr::mutate(weight_range = dplyr::case_when(
+      style == "normal" & min_weight != max_weight ~ paste0("n&nbsp;", min_weight, "&#8209;", max_weight),
+      style == "normal" & min_weight == max_weight ~ paste0("n&nbsp;", min_weight),
+      style == "italic" & min_weight != max_weight ~ paste0("*i*&nbsp;", min_weight, "&#8209;", max_weight),
+      style == "italic" & min_weight == max_weight ~ paste0("*i*&nbsp;", min_weight)
+    )) %>%
+    dplyr::group_by(name) %>%
+    dplyr::summarize(weight_ranges = paste(weight_range, collapse = "<br>"))
+
+  source_notes <-
+    google_styles_tbl %>%
+    dplyr::filter(name %in% recommended) %>%
+    dplyr::select(name, copyright) %>%
+    dplyr::distinct() %>%
+    dplyr::mutate(name = paste0("**", name, "** ")) %>%
+    dplyr::mutate(name_copy = paste0(name, copyright)) %>%
+    dplyr::pull(name_copy) %>%
+    paste(collapse = ". ") %>%
+    gsub("..", ".", ., fixed = TRUE) %>%
+    paste_right(".")
+
+  google_font_tbl_int <-
+    google_font_tbl %>%
+    dplyr::filter(name %in% recommended) %>%
+    dplyr::left_join(styles_summary, by = "name") %>%
+    dplyr::mutate(
+      category = stringr::str_to_title(category) %>%
+        tidy_gsub("_", " ") %>%
+        tidy_gsub("serif", "Serif")
+    ) %>%
+    dplyr::select(-license, -date_added, -designer) %>%
+    dplyr::mutate(samp = paste0(LETTERS[1:13], letters[1:13], collapse = ""))
+
+  google_font_tbl_gt <-
+    google_font_tbl_int %>%
+    dplyr::arrange(category) %>%
+    gt(rowname_col = "name", groupname_col = "category") %>%
+    fmt_markdown(columns = vars(weight_ranges)) %>%
+    tab_style(
+      style = list(
+        cell_text(size = px(8), font = "Courier"),
+        cell_fill(color = "#F7F7F7")
+      ),
+      locations = cells_body(columns = vars(weight_ranges))
+    ) %>%
+    tab_style(
+      style = cell_text(size = px(24)),
+      locations = cells_title(groups = "title")
+    ) %>%
+    tab_style(
+      style = cell_text(size = px(18)),
+      locations = cells_title(groups = "subtitle")
+    ) %>%
+    tab_style(
+      style = cell_text(size = px(28), indent = px(5)),
+      locations = cells_body(columns = vars(samp))
+    ) %>%
+    tab_style(
+      style = cell_text(size = px(14)),
+      locations = cells_stub()
+    ) %>%
+    tab_style(
+      style = cell_text(size = px(18), weight = "600"),
+      locations = cells_row_groups()
+    ) %>%
+    tab_header(
+      title = md("Recommended *Google Fonts* for **gt**"),
+      subtitle = md("Fonts like these can be accessed using the `google_font()` function.<br><br>")
+    ) %>%
+    opt_align_table_header("left") %>%
+    opt_table_lines("none") %>%
+    tab_options(
+      table.width = px(800),
+      column_labels.hidden = TRUE,
+      row_group.padding = px(12),
+      data_row.padding = px(4),
+      table_body.hlines.style = "solid",
+      table_body.hlines.width = px(1),
+      table_body.hlines.color = "#F7F7F7",
+      row_group.border.top.style = "solid",
+      row_group.border.top.width = px(1),
+      row_group.border.bottom.width = px(1),
+      table.border.bottom.style = "solid",
+      table.border.bottom.width = px(1),
+      table.border.bottom.color = "#F7F7F7",
+      source_notes.font.size = px(10),
+      source_notes.padding = px(6)
+    ) %>%
+    tab_source_note(md(source_notes))
+
+  for (i in seq(nrow(google_font_tbl_int))) {
+
+    google_font_tbl_gt <-
+      google_font_tbl_gt %>%
+      tab_style(
+        style = cell_text(font = google_font(name = google_font_tbl_int$name[i])),
+        locations = cells_body(columns = vars(samp), rows = google_font_tbl_int$name[i])
+      )
+  }
+
+  google_font_tbl_gt
+}
diff --git a/R/opts.R b/R/opts.R
index 41b75bda1..79cb80776 100644
--- a/R/opts.R
+++ b/R/opts.R
@@ -497,6 +497,248 @@ opt_table_outline <- function(data,
   tab_options_multi(data, option_value_list)
 }
 
+
+#' Option to define a custom font for the table
+#'
+#' @description
+#' The `opt_table_font()` function makes it possible to define a custom font for
+#' the entire **gt** table. The standard fallback fonts are still set by default
+#' but the font defined here will take precedence. You could still have
+#' different fonts in select locations in the table, and for that you would need
+#' to use [tab_style()] in conjunction with the [cell_text()] helper function.
+#'
+#' We have the option to supply either a system font for the `font_name`, or, a
+#' font available at the Google Fonts service by use of the [google_font()]
+#' helper function.
+#'
+#' @inheritParams fmt_number
+#' @param font Either the name of a font available in the user system or a call
+#'   to [google_font()], which has a large selection of typefaces.
+#' @param style The text style. Can be one of either `"normal"`, `"italic"`, or
+#'   `"oblique"`.
+#' @param weight The weight of the font. Can be a text-based keyword such as
+#'   `"normal"`, `"bold"`, `"lighter"`, `"bolder"`, or, a numeric value between
+#'   `1` and `1000`, inclusive. Note that only variable fonts may support the
+#'   numeric mapping of weight.
+#' @param add Should this font be added to the front of the already-defined
+#'   fonts for the table? By default, this is `TRUE` and is recommended since
+#'   the list serves as fallbacks when certain fonts are not available.
+#'
+#' @return An object of class `gt_tbl`.
+#'
+#' @examples
+#' if (interactive()) {
+#'
+#' # Use `sp500` to create a small gt table,
+#' # using `fmt_currency()` to provide a
+#' # dollar sign for the first row of monetary
+#' # values; then, set a larger font size for
+#' # the table and use the 'Merriweather' font
+#' # (from Google Fonts, via `google_font()`)
+#' # with two font fallbacks ('Cochin' and the
+#' # catchall 'Serif' group)
+#' tab_1 <-
+#'   sp500 %>%
+#'   dplyr::slice(1:10) %>%
+#'   dplyr::select(-volume, -adj_close) %>%
+#'   gt() %>%
+#'   fmt_currency(
+#'     columns = 2:5,
+#'     rows = 1,
+#'     currency = "USD",
+#'     use_seps = FALSE
+#'   ) %>%
+#'   tab_options(table.font.size = px(18)) %>%
+#'   opt_table_font(
+#'     font = list(
+#'       google_font(name = "Merriweather"),
+#'       "Cochin", "Serif"
+#'     )
+#'   )
+#'
+#' # Use `sza` to create an eleven-row table;
+#' # within `opt_table_font()`, set up a
+#' # preferred list of sans-serif fonts that
+#' # are commonly available in macOS (using
+#' # part of the `default_fonts()` vector as
+#' # a fallback)
+#' # and Windows 10
+#' tab_2 <-
+#'   sza %>%
+#'   dplyr::filter(
+#'     latitude == 20 &
+#'       month == "jan" &
+#'       !is.na(sza)
+#'   ) %>%
+#'   dplyr::select(-latitude, -month) %>%
+#'   gt() %>%
+#'   opt_table_font(
+#'     font = c(
+#'       "Helvetica Neue", "Segoe UI",
+#'       default_fonts()[-c(1:3)]
+#'     )
+#'   ) %>%
+#'   opt_all_caps()
+#'
+#' }
+#'
+#' @section Figures:
+#' \if{html}{\figure{man_opt_table_font_1.png}{options: width=100\%}}
+#'
+#' \if{html}{\figure{man_opt_table_font_2.png}{options: width=100\%}}
+#'
+#' @family Table Option Functions
+#' @section Function ID:
+#' 9-7
+#'
+#' @export
+opt_table_font <- function(data,
+                           font,
+                           weight = NULL,
+                           style = NULL,
+                           add = TRUE) {
+
+  existing_fonts <- dt_options_get_value(data = data, option = "table_font_names")
+  existing_additional_css <- dt_options_get_value(data = data, option = "table_additional_css")
+
+  font <- normalize_font_input(font_input = font)
+
+  additional_css <- c(font$import_stmt, existing_additional_css)
+
+  data <- tab_options(data = data, table.font.names = c(font$name, if (add) existing_fonts))
+  data <- tab_options(data = data, table.additional_css = additional_css)
+
+  if (!is.null(weight)) {
+
+    if (is.numeric(weight)) weight <- as.character(weight)
+
+    data <- tab_options(data = data, table.font.weight = weight)
+    data <- tab_options(data = data, column_labels.font.weight = weight)
+  }
+
+  if (!is.null(style)) {
+    data <- tab_options(data = data, table.font.style = style)
+  }
+
+  data
+}
+
+#' Option to add custom CSS for the table
+#'
+#' The `opt_css()` function makes it possible to add CSS to a **gt** table. This
+#' CSS will be added after the compiled CSS that **gt** generates automatically
+#' when the object is transformed to an HTML output table. You can supply `css`
+#' as a vector of lines or as a single string.
+#'
+#' @inheritParams fmt_number
+#' @param css The CSS to include as part of the rendered table's `<style>`
+#'   element.
+#' @param add If `TRUE`, the default, the CSS is added to any already-defined
+#'   CSS (typically from previous calls of [opt_table_font()], `opt_css()`, or,
+#'   directly setting CSS the `table.additional_css` value in [tab_options()]).
+#'   If this is set to `FALSE`, the CSS provided here will replace any
+#'   previously-stored CSS.
+#' @param allow_duplicates When this is `FALSE` (the default), the CSS provided
+#'   here won't be added (provided that `add = TRUE`) if it is seen in the
+#'   already-defined CSS.
+#'
+#' @return An object of class `gt_tbl`.
+#'
+#' @examples
+#' # Use `exibble` to create a gt table and
+#' # format the data in both columns; with
+#' # `opt_css()` insert CSS rulesets as
+#' # as string and be sure to set the table
+#' # ID explicitly (here as "one")
+#' tab_1 <-
+#'   exibble %>%
+#'   dplyr::select(num, currency) %>%
+#'   gt(id = "one") %>%
+#'   fmt_currency(
+#'     columns = vars(currency),
+#'     currency = "HKD"
+#'   ) %>%
+#'   fmt_scientific(
+#'     columns = vars(num)
+#'   ) %>%
+#'   opt_css(
+#'     css = "
+#'     #one .gt_table {
+#'       background-color: skyblue;
+#'     }
+#'     #one .gt_row {
+#'       padding: 20px 30px;
+#'     }
+#'     #one .gt_col_heading {
+#'       text-align: center !important;
+#'     }
+#'     "
+#'   )
+#'
+#' @section Figures:
+#' \if{html}{\figure{man_opt_css_1.png}{options: width=100\%}}
+#'
+#' @family Table Option Functions
+#' @section Function ID:
+#' 9-8
+#'
+#' @export
+opt_css <- function(data,
+                    css,
+                    add = TRUE,
+                    allow_duplicates = FALSE) {
+
+  existing_additional_css <-
+    dt_options_get_value(data = data, option = "table_additional_css")
+
+  css <- paste(css, collapse = "\n")
+
+  if (!add && !allow_duplicates && css %in% existing_additional_css) {
+    return(data)
+  }
+
+  additional_css <- c(existing_additional_css, css)
+
+  tab_options(data = data, table.additional_css = additional_css)
+}
+
+normalize_font_input <- function(font_input) {
+
+  if (!inherits(font_input, "character") &&
+      !inherits(font_input, "list") &&
+      !inherits(font_input, "font_css")) {
+    stop("Values provided to `font` must either be a list or a character vector.",
+         call. = FALSE)
+  }
+
+  if (inherits(font_input, "character")) {
+    font_input <- list(font_input)
+  }
+
+  # Unlist a list of lists; this normalizes the value for `font_input`
+  # in the cases where multiple fonts were provided in `c()` and `list()`
+  if (any(vapply(font_input, is.list, FUN.VALUE = logical(1)))) {
+    font_input <- unlist(font_input, recursive = FALSE)
+  }
+
+  if (is.null(names(font_input))) {
+    font_names <- unlist(font_input)
+    import_stmts <- ""
+  } else {
+    font_names <- unique(unname(unlist(font_input[names(font_input) %in% c("name", "")])))
+    import_stmts <- unique(unname(unlist(font_input[names(font_input) %in% "import_stmt"])))
+  }
+
+  font_list <-
+    list(
+      name = font_names,
+      import_stmt = import_stmts
+    )
+
+  class(font_list) <- "font_css"
+  font_list
+}
+
 # Create an option-value list with a vector of arg names from the
 # `tab_options()` function and either one value or n-length values
 # corresponding to those options
diff --git a/R/reexports.R b/R/reexports.R
index 79204a9e8..72bec624a 100644
--- a/R/reexports.R
+++ b/R/reexports.R
@@ -25,3 +25,7 @@ tidyselect::one_of
 #' @importFrom tidyselect everything
 #' @export
 tidyselect::everything
+
+#' @importFrom htmltools css
+#' @export
+htmltools::css
diff --git a/R/sysdata.rda b/R/sysdata.rda
index dbdb2d8de315cb4aa6ce3e0a7f847b926d9f1bd4..7486e496f5e91bad1c833b0b29de1b35a5cb4721 100644
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diff --git a/R/tab_create_modify.R b/R/tab_create_modify.R
index 029488240..5f6009632 100644
--- a/R/tab_create_modify.R
+++ b/R/tab_create_modify.R
@@ -784,8 +784,9 @@ tab_source_note <- function(data,
 #' @inheritParams fmt_number
 #' @param style a vector of styles to use. The [cell_text()], [cell_fill()], and
 #'   [cell_borders()] helper functions can be used here to more easily generate
-#'   valid styles. If using more than one helper function to define styles, all
-#'   calls must be enclosed in a [list()].
+#'   valid styles.  If using more than one helper function to define styles, all
+#'   calls must be enclosed in a [list()]. Custom CSS declarations can be used
+#'   for HTML output by including a [css()]-based statement as a list item.
 #' @param locations the cell or set of cells to be associated with the style.
 #'   Supplying any of the `cells_*()` helper functions is a useful way to target
 #'   the location cells that are associated with the styling. These helper
@@ -855,11 +856,32 @@ tab_source_note <- function(data,
 #'       rows = open > close)
 #'   )
 #'
+#' # Use `exibble` to create a gt table;
+#' # replace missing values with the
+#' # `fmt_missing()` function and then
+#' # add styling to the `char` column
+#' # with `cell_fill()` and with a
+#' # CSS style declaration
+#' tab_3 <-
+#'   exibble %>%
+#'   dplyr::select(char, fctr) %>%
+#'   gt() %>%
+#'   fmt_missing(everything()) %>%
+#'   tab_style(
+#'     style = list(
+#'       cell_fill(color = "lightcyan"),
+#'       "font-variant: small-caps;"
+#'     ),
+#'     locations = cells_body(columns = vars(char))
+#'   )
+#'
 #' @section Figures:
 #' \if{html}{\figure{man_tab_style_1.png}{options: width=100\%}}
 #'
 #' \if{html}{\figure{man_tab_style_2.png}{options: width=100\%}}
 #'
+#' \if{html}{\figure{man_tab_style_3.png}{options: width=100\%}}
+#'
 #' @family Create or Modify Parts
 #' @section Function ID:
 #' 2-8
@@ -876,10 +898,30 @@ tab_style <- function(data,
   # Perform input object validation
   stop_if_not_gt(data = data)
 
+  # Intercept font styles that require registration
+  if ("cell_text" %in% names(style)) {
+
+    if ("font" %in% names(style[["cell_text"]])) {
+
+      font <- style[["cell_text"]][["font"]]
+      font <- normalize_font_input(font_input = font)
+
+      existing_additional_css <- dt_options_get_value(data = data, option = "table_additional_css")
+      additional_css <- c(font$import_stmt, existing_additional_css)
+
+      data <- tab_options(data = data, table.additional_css = additional_css)
+
+      font_names <- font$name
+
+      style[["cell_text"]][["font"]] <-
+        as_css_font_family_attr(font_vec = font_names, value_only = TRUE)
+    }
+  }
+
   # Resolve into a list of locations
   locations <- as_locations(locations)
 
-  style <- as_style(style)
+  style <- as_style(style = style)
 
   # Resolve the locations of the targeted data cells and append
   # the format directives
@@ -901,14 +943,14 @@ as_style <- function(style) {
   # components together
   if (!inherits(style, "cell_styles")) {
 
-    if (!inherits(style, "list")) {
-      stop("Styles should be provided exclusively by the stylizing ",
-           "helper functions:",
-           " * `cell_text()\n",
-           " * `cell_fill()\n",
-           " * `cell_borders()`",
-           call. = FALSE)
-    }
+    # if (!inherits(style, "list")) {
+    #   stop("Styles should be provided exclusively by the stylizing ",
+    #        "helper functions:\n",
+    #        " * `cell_text()\n",
+    #        " * `cell_fill()\n",
+    #        " * `cell_borders()`",
+    #        call. = FALSE)
+    # }
 
     # Initialize an empty list that will be
     # populated with normalized style declarations
@@ -918,7 +960,11 @@ as_style <- function(style) {
 
       style_item <- style[[i]]
 
-      if (!inherits(style_item, "cell_styles")) {
+      if (inherits(style_item, "character")) {
+
+        style_item <- list(cell_style = style_item)
+
+      } else if (!inherits(style_item, "cell_styles")) {
 
         stop("All provided styles should be generated by stylizing ",
              "helper functions. Style with index `", i, "` is invalid.",
@@ -933,9 +979,6 @@ as_style <- function(style) {
     style <- final_style
   }
 
-  # Check for class of `cell_style` in upgraded `style` list
-  lapply(style, function(x) checkmate::assert_class(x = x, classes = "cell_style"))
-
   style
 }
 
@@ -1168,6 +1211,14 @@ set_style.cells_grand_summary <- function(loc, data, style) {
 #'   elements: `heading`, `column_labels`, `row_group`, `stub`, `summary_row`,
 #'   `grand_summary_row`, `footnotes`, and `source_notes`. A color name or a
 #'   hexadecimal color code should be provided.
+#' @param table.additional_css This option can be used to supply an additional
+#'   block of CSS rules to be applied after the automatically generated table
+#'   CSS.
+#' @param table.font.names The names of the fonts used for the table. This is
+#'   a vector of several font names. If the first font isn't available, then
+#'   the next font is tried (and so on).
+#' @param table.font.style The font style for the table. Can be one of either
+#'   `"normal"`, `"italic"`, or `"oblique"`.
 #' @param table.font.color,table.font.color.light
 #'   The text color used throughout the table. There are two variants:
 #'   `table.font.color` is for text overlaid on lighter background colors, and
@@ -1185,8 +1236,8 @@ set_style.cells_grand_summary <- function(loc, data, style) {
 #'   obtain values as pixel or percentage units.
 #' @param heading.align Controls the horizontal alignment of the heading title
 #'   and subtitle. We can either use `"center"`, `"left"`, or `"right"`.
-#' @param heading.title.font.weight,heading.subtitle.font.weight,column_labels.font.weight,row_group.font.weight,stub.font.weight
-#'   The font weights of the `heading.title`, `heading.subtitle`,
+#' @param table.font.weight,heading.title.font.weight,heading.subtitle.font.weight,column_labels.font.weight,row_group.font.weight,stub.font.weight
+#'   The font weights of the table, `heading.title`, `heading.subtitle`,
 #'   `column_labels`, `row_group`, and `stub` text elements. Can be a text-based
 #'   keyword such as `"normal"`, `"bold"`, `"lighter"`, `"bolder"`, or, a
 #'   numeric value between `1` and `1000`, inclusive. Note that only variable
@@ -1386,9 +1437,13 @@ tab_options <- function(data,
                         table.margin.left = NULL,
                         table.margin.right = NULL,
                         table.background.color = NULL,
+                        table.additional_css = NULL,
+                        table.font.names = NULL,
+                        table.font.size = NULL,
+                        table.font.weight = NULL,
+                        table.font.style = NULL,
                         table.font.color = NULL,
                         table.font.color.light = NULL,
-                        table.font.size = NULL,
                         table.border.top.style = NULL,
                         table.border.top.width = NULL,
                         table.border.top.color = NULL,
diff --git a/R/utils.R b/R/utils.R
index 57251fcd4..d56edf8fd 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -957,12 +957,22 @@ validate_marks <- function(marks) {
   }
 }
 
-validate_style_in <- function(style_vals, style_names, arg_name, in_vector) {
+validate_style_in <- function(style_vals,
+                              style_names,
+                              arg_name,
+                              in_vector,
+                              with_pattern = NULL) {
 
   if (arg_name %in% style_names) {
 
     arg_value <- style_vals[[arg_name]]
 
+    # There is positive validation if a regex pattern is specified
+    # in `with_pattern` and the pattern matches
+    if (!is.null(with_pattern) && grepl(with_pattern, arg_value)) {
+        return()
+    }
+
     if (!(arg_value %in% in_vector)) {
       stop("The provided `", arg_name, "` value cannot be `",
            arg_value, "`; it can only be either of the following:\n",
diff --git a/R/utils_render_html.R b/R/utils_render_html.R
index 57ca4b0a5..22a205013 100644
--- a/R/utils_render_html.R
+++ b/R/utils_render_html.R
@@ -9,12 +9,32 @@ footnote_mark_to_html <- function(mark) {
 
 styles_to_html <- function(styles) {
 
-  style_list <-
-    lapply(styles, function(x) cell_style_to_html(x)) %>%
-    unname() %>%
-    unlist(recursive = FALSE)
+  vapply(
+    styles,
+    FUN.VALUE = character(1), USE.NAMES = FALSE,
+    FUN = function(x) {
 
-  paste0(names(style_list), ": ", style_list, ";", collapse = " ")
+      if (any(is.null(names(x)))) {
+
+        style <- gsub(":", ": ", x, fixed = TRUE)
+
+      } else if (all(names(x) != "")) {
+
+        x <- cell_style_to_html(x)
+
+        style <-
+          paste0(names(x), ": ", x, ";", collapse = " ") %>%
+          tidy_gsub(";;", ";")
+
+      } else {
+        style <- as.character(x)
+      }
+
+      style
+    }
+  ) %>%
+    paste(collapse = " ") %>%
+    tidy_gsub("\n", " ")
 }
 
 cell_style_to_html <- function(style) {
@@ -1108,3 +1128,15 @@ build_row_styles <- function(styles_resolved_row,
 
   row_styles
 }
+
+as_css_font_family_attr <- function(font_vec, value_only = FALSE) {
+
+  fonts_spaces <- grepl(" ", font_vec)
+  font_vec[fonts_spaces] <- paste_between(x = font_vec[fonts_spaces], x_2 = c("'", "'"))
+
+  value <- paste(font_vec, collapse = ", ")
+
+  if (value_only) return(value)
+
+  paste_between(value, x_2 = c("font-family: ", ";"))
+}
diff --git a/R/zzz.R b/R/zzz.R
index f28ffb02c..df5c85944 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -31,6 +31,7 @@ globalVariables(
     "b",
     "blue",
     "boxhead",
+    "category",
     "colname",
     "colnames_start",
     "colnum",
@@ -38,9 +39,12 @@ globalVariables(
     "column_align",
     "column_label",
     "colors",
+    "copyright",
     "curr_code",
     "curr_name",
     "data_attr",
+    "date_added",
+    "designer",
     "display_name",
     "footnotes",
     "footnotes_to_list",
@@ -58,6 +62,8 @@ globalVariables(
     "missing_text",
     "n",
     "n_cols",
+    "name",
+    "name_copy",
     "obtain_group_ordering",
     "package",
     "palette",
@@ -80,6 +86,7 @@ globalVariables(
     "r",
     "rgba",
     "rowname",
+    "samp",
     "scss",
     "selector",
     "style",
@@ -88,6 +95,9 @@ globalVariables(
     "type",
     "value",
     "var",
+    "weight",
+    "weight_range",
+    "weight_ranges",
     "yiq"
     )
   )
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 2d6941e8d..f2b6636bf 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -133,6 +133,8 @@ reference:
     - random_id
     - escape_latex
     - gt_latex_dependencies
+    - default_fonts
+    - google_font
 
   - title: Image Addition Functions
     desc: >
@@ -167,15 +169,17 @@ reference:
       useful information. So far, we can get reference information on
       date styles (`info_date_style()`), on time styles
       (`info_time_style()`), on a huge number of color palettes
-      (`info_paletteer()`), on currencies (`info_currencies()`), and, on
+      (`info_paletteer()`), on currencies (`info_currencies()`), on
       all of the different locales supported in the formatter functions
-      (`info_locales()`).
+      (`info_locales()`), and on our recommendations for which Google Fonts
+      to try in your tables.
     contents:
     - info_date_style
     - info_time_style
     - info_currencies
     - info_locales
     - info_paletteer
+    - info_google_fonts
 
   - title: Datasets
     desc: >
diff --git a/data-raw/X04-palettes_strips.R b/data-raw/X04-palettes_strips.R
index 3a54e078c..4a5c4d126 100644
--- a/data-raw/X04-palettes_strips.R
+++ b/data-raw/X04-palettes_strips.R
@@ -69,3 +69,8 @@ get_d_palettes <- function(color_packages = c(
 }
 
 palettes_strips <- get_d_palettes()
+
+rm(get_d_palettes)
+rm(make_color_strip_svg)
+rm(make_rects)
+
diff --git a/data-raw/X05-google_fonts.R b/data-raw/X05-google_fonts.R
new file mode 100644
index 000000000..3c574af42
--- /dev/null
+++ b/data-raw/X05-google_fonts.R
@@ -0,0 +1,140 @@
+library(tidyverse)
+library(here)
+library(downloader)
+library(fs)
+
+# Set up a working directory for Google Font data processing
+work_dir <- here("data-raw", "google_fonts_metadata")
+fs::dir_create(work_dir)
+
+# Download and extract the tarball for the google/font repository
+downloader::download(
+  "https://github.com/google/fonts/tarball/master",
+  destfile = file.path(work_dir, "google_fonts.tar.gz")
+)
+utils::untar(file.path(work_dir, "google_fonts.tar.gz"), exdir = work_dir)
+
+# Get the directory names for each of the OFL fonts
+file_list <- fs::dir_ls(path = fs::path_expand(work_dir)) %>% as.character()
+ofl_dirs <- fs::dir_ls(file.path(file_list[!grepl("tar.gz", file_list)], "ofl"))
+
+# Copy all .pb files to the root of the work directory
+for (dr in ofl_dirs) {
+
+  font_name <- dr %>% fs::path_split() %>% unlist() %>% rev() %>% .[1]
+
+  if (fs::file_exists(file.path(dr, "METADATA.pb"))) {
+
+    fs::file_copy(
+      path = file.path(dr, "METADATA.pb"),
+      new_path = file.path(work_dir, paste0(font_name, "__METADATA.pb"))
+    )
+  }
+
+  rm(font_name)
+}
+
+# Get paths for all .pb files in the work directory
+ofl_files <- fs::dir_ls(work_dir, glob = "*.pb")
+
+# Initialize tibbles
+google_font_tbl <-
+  dplyr::tibble(
+    name = character(0), designer = character(0), license = character(0),
+    category = character(0), date_added = character(0)
+  )
+google_styles_tbl <-
+  dplyr::tibble(
+    name = character(0), style = character(0), weight = character(0),
+    filename = character(0), post_script_name = character(0),
+    full_name = character(0), copyright = character(0)
+  )
+google_axes_tbl <-
+  dplyr::tibble(
+    name = character(0), tag = character(0), min_value = character(0),
+    max_value = character(0),
+  )
+
+# For every font file, read the `.pb` metadata file and extract
+# font metrics and other items of information
+for (file in ofl_files) {
+
+  pb <-
+    readr::read_file(file) %>%
+    gt:::tidy_gsub("#.*?\n", "\n")
+
+  font_variants <-
+    stringr::str_extract_all(pb, pattern = "fonts \\{(\\n|.)*?\\}") %>%
+    unlist() %>%
+    gt:::tidy_gsub("(fonts \\{\n  |\\}$|\"|$)", "") %>%
+    gt:::tidy_gsub("\n  ", "\n") %>%
+    gt:::tidy_gsub("\n$", "") %>%
+    stringr::str_split("\n")
+
+  font_info <-
+    pb %>%
+    stringr::str_replace_all(pattern = "fonts \\{(\\n|.)*?\\}", "") %>%
+    gt:::tidy_gsub("axes \\{.*", "") %>%
+    gt:::tidy_gsub("subsets:.*", "") %>%
+    gt:::tidy_gsub("\n{2,}", "\n") %>%
+    gt:::tidy_gsub("\n$", "") %>%
+    gt:::tidy_gsub("\"", "") %>%
+    stringr::str_split("\n") %>%
+    unlist()
+
+  font_name <- read.dcf(textConnection(font_info))[1, 1] %>% unname()
+
+  google_font_tbl <-
+    dplyr::bind_rows(
+      google_font_tbl,
+      read.dcf(textConnection(font_info)) %>%
+        dplyr::as_tibble()
+    )
+
+  for (i in seq_len(length(font_variants))) {
+    google_styles_tbl <-
+      dplyr::bind_rows(
+        google_styles_tbl,
+        read.dcf(textConnection(font_variants[[i]])) %>% dplyr::as_tibble()
+      )
+  }
+
+  if (str_detect(pb, "axes \\{")) {
+
+    axes <-
+      stringr::str_extract_all(pb, pattern = "axes(\\n|.)*?\\}") %>%
+      unlist() %>%
+      gt:::tidy_gsub("(axes \\{\n  |\\}$|\"|$)", "") %>%
+      gt:::tidy_gsub("\n  ", "\n") %>%
+      gt:::tidy_gsub("\n$", "") %>%
+      stringr::str_split("\n")
+
+
+    for (i in seq_len(length(axes))) {
+      google_axes_tbl <-
+        dplyr::bind_rows(
+          google_axes_tbl,
+          read.dcf(textConnection(axes[[i]])) %>%
+            dplyr::as_tibble() %>%
+            dplyr::mutate(name = font_name) %>%
+            dplyr::select(name, dplyr::everything())
+        )
+    }
+  }
+}
+
+# Remove the work directory
+unlink(work_dir, recursive = TRUE)
+
+rm(dr)
+rm(file)
+rm(file_list)
+rm(font_info)
+rm(font_name)
+rm(i)
+rm(ofl_dirs)
+rm(ofl_files)
+rm(pb)
+rm(work_dir)
+rm(font_variants)
+rm(axes)
diff --git a/data-raw/zz_process_datasets_ext.R b/data-raw/zz_process_datasets_ext.R
index cf6064b9b..76de11a30 100644
--- a/data-raw/zz_process_datasets_ext.R
+++ b/data-raw/zz_process_datasets_ext.R
@@ -4,9 +4,11 @@ source("data-raw/X01-currencies.R")
 source("data-raw/X02-currency_symbols.R")
 source("data-raw/X03-locales.R")
 source("data-raw/X04-palettes_strips.R")
+source("data-raw/X05-google_fonts.R")
 
 # Create internal datasets (`sysdata.rda`)
 usethis::use_data(
   currencies, currency_symbols, locales, palettes_strips,
+  google_font_tbl, google_styles_tbl, google_axes_tbl,
   internal = TRUE, overwrite = TRUE
 )
diff --git a/inst/css/external.css b/inst/css/external.css
new file mode 100644
index 000000000..a34a2a9de
--- /dev/null
+++ b/inst/css/external.css
@@ -0,0 +1,11 @@
+.gt_table {
+  background-color: skyblue;
+}
+
+.gt_row {
+  padding: 20px 30px;
+}
+
+.gt_col_heading {
+  text-align: center !important;
+}
diff --git a/inst/css/gt_styles_default.scss b/inst/css/gt_styles_default.scss
index 64c71e6fc..382cc42f4 100644
--- a/inst/css/gt_styles_default.scss
+++ b/inst/css/gt_styles_default.scss
@@ -7,6 +7,8 @@
     margin-right: $table_margin_right; // table.margin.right
     color: font-color($table_background_color);
     font-size: $table_font_size; // table.font.size
+    font-weight: $table_font_weight; // table.font.weight
+    font-style: $table_font_style; // table.font.style
     background-color: $table_background_color; // table.background.color
     width: $table_width; // table.width
     border-top-style: $table_border_top_style; // table.border.top.style
diff --git a/inst/extdata/google_axes_tbl.csv b/inst/extdata/google_axes_tbl.csv
new file mode 100644
index 000000000..0cea9b5b9
--- /dev/null
+++ b/inst/extdata/google_axes_tbl.csv
@@ -0,0 +1,59 @@
+name,tag,min_value,max_value
+Archivo Narrow,wght,400.0,700.0
+Changa,wght,200.0,800.0
+Comfortaa,wght,300.0,700.0
+Crimson Pro,wght,200.0,900.0
+Dancing Script,wght,400.0,700.0
+Dosis,wght,200.0,800.0
+EB Garamond,wght,400.0,800.0
+El Messiri,wght,400.0,700.0
+Encode Sans,wdth,75.0,125.0
+Encode Sans,wght,100.0,900.0
+Exo 2,wght,100.0,900.0
+Exo,wght,100.0,900.0
+Faustina,wght,400.0,700.0
+Fira Code,wght,300.0,700.0
+Grenze Gotisch,wght,100.0,900.0
+Heebo,wght,100.0,900.0
+Hepta Slab,wght,1.0,900.0
+Inconsolata,wdth,50.0,200.0
+Inconsolata,wght,200.0,900.0
+Inter,slnt,-10.0,0.0
+Inter,wght,100.0,900.0
+Josefin Sans,wght,100.0,700.0
+Jost,wght,100.0,900.0
+Jura,wght,300.0,700.0
+Karla,wght,200.0,800.0
+Kreon,wght,300.0,700.0
+League Gothic,slnt,-12.0,0.0
+League Gothic,wdth,75.0,112.5
+Lemonada,wght,300.0,700.0
+Literata,wght,400.0,700.0
+Lora,wght,400.0,700.0
+Manrope,wght,200.0,800.0
+Manuale,wght,400.0,700.0
+Markazi Text,wght,400.0,700.0
+Maven Pro,wght,400.0,900.0
+Mohave,wght,300.0,700.0
+Muli,wght,200.0,900.0
+MuseoModerno,wght,100.0,900.0
+Orbitron,wght,400.0,900.0
+Oswald,wght,200.0,700.0
+Playfair Display,wght,400.0,900.0
+Podkova,wght,400.0,800.0
+Public Sans,wght,100.0,900.0
+Quicksand,wght,300.0,700.0
+Recursive,CASL,0.0,1.0
+Recursive,MONO,0.0,1.0
+Recursive,CRSV,0.0,1.0
+Recursive,slnt,-15.0,0
+Recursive,wght,300.0,1000.0
+Roboto,wdth,75.0,100.0
+Roboto,wght,100.0,900.0
+Rokkitt,wght,100.0,900.0
+Rosario,wght,300.0,700.0
+Ruda,wght,400.0,900.0
+Spartan,wght,100.0,900.0
+Vollkorn,wght,400.0,900.0
+Work Sans,wght,100.0,900.0
+Yanone Kaffeesatz,wght,200.0,700.0
diff --git a/inst/extdata/google_font_tbl.csv b/inst/extdata/google_font_tbl.csv
new file mode 100644
index 000000000..838f93aee
--- /dev/null
+++ b/inst/extdata/google_font_tbl.csv
@@ -0,0 +1,1008 @@
+name,designer,license,category,date_added
+ABeeZee,Anja Meiners,OFL,SANS_SERIF,2012-09-30
+Abel,MADType,OFL,SANS_SERIF,2011-08-03
+Abhaya Libre,Mooniak,OFL,SERIF,2016-08-30
+Abril Fatface,TypeTogether,OFL,DISPLAY,2011-08-31
+Abyssinica SIL,SIL International,OFL,SERIF,2016-01-20
+Acme,Huerta Tipográfica,OFL,SANS_SERIF,2011-12-19
+Actor,Thomas Junold,OFL,SANS_SERIF,2011-08-03
+Adamina,Cyreal,OFL,SERIF,2011-09-07
+Adobe Blank,Dr. Ken Lunde,OFL,MONOSPACE,2016-03-23
+Advent Pro,Andreas Kalpakidis,OFL,SANS_SERIF,2012-02-29
+Aguafina Script,Sudtipos,OFL,HANDWRITING,2011-11-30
+Akronim,Grzegorz Klimczewski,OFL,DISPLAY,2012-09-23
+Aladin,Sudtipos,OFL,HANDWRITING,2011-11-30
+Alata,"Spyros Zevelakis, Eben Sorkin",OFL,SANS_SERIF,2019-11-08
+Alatsi,"Spyros Zevelakis, Eben Sorkin",OFL,SANS_SERIF,2019-11-07
+Aldrich,MADType,OFL,SANS_SERIF,2011-08-17
+Alef,"Hagilda, Mushon Zer-Aviv",OFL,SANS_SERIF,2013-05-21
+Alegreya,Huerta Tipogr\303\241fica,OFL,SERIF,2011-12-19
+Alegreya Sans,Juan Pablo del Peral,OFL,SANS_SERIF,2013-12-04
+Alegreya Sans SC,Juan Pablo del Peral,OFL,SANS_SERIF,2013-12-04
+Alegreya SC,Huerta Tipogr\303\241fica,OFL,SERIF,2011-12-19
+Aleo,"Alessio Laiso, Kevin Conroy",OFL,SERIF,2018-12-05
+Alex Brush,TypeSETit,OFL,HANDWRITING,2011-12-19
+Alfa Slab One,JM Solé,OFL,DISPLAY,2011-12-19
+Alice,Cyreal,OFL,SERIF,2011-08-10
+Alike,Cyreal,OFL,SERIF,2011-08-24
+Alike Angular,Cyreal,OFL,SERIF,2011-09-28
+Allan,Anton Koovit,OFL,DISPLAY,2012-09-06
+Allerta,Matt McInerney,OFL,SANS_SERIF,2010-11-30
+Allerta Stencil,Matt McInerney,OFL,SANS_SERIF,2010-11-30
+Allura,TypeSETit,OFL,HANDWRITING,2012-02-08
+Almarai,Boutros Fonts,OFL,SANS_SERIF,2019-06-04
+Almendra,Ana Sanfelippo,OFL,SERIF,2011-12-19
+Almendra Display,Ana Sanfelippo,OFL,DISPLAY,2012-11-12
+Almendra SC,Ana Sanfelippo,OFL,SERIF,2011-12-19
+Amarante,Karolina Lach,OFL,DISPLAY,2012-07-10
+Amaranth,Gesine Todt,OFL,SANS_SERIF,2011-05-04
+Amatica SC,Multiple Designers,OFL,DISPLAY,2016-06-20
+Amatic SC,"Vernon Adams, Ben Nathan, Thomas Jockin",OFL,HANDWRITING,2011-10-12
+Amethysta,Cyreal,OFL,SERIF,2012-01-18
+Amiko,Impallari Type,OFL,SANS_SERIF,2016-06-20
+Amiri,"Khaled Hosny, Sebastian Kosch",OFL,SERIF,2012-07-30
+Amita,Multiple Designers,OFL,HANDWRITING,2015-05-20
+Anaheim,Vernon Adams,OFL,SANS_SERIF,2012-10-31
+Andada,Huerta Tipográfica,OFL,SERIF,2011-10-05
+Andada SC,Huerta Tipográfica,OFL,SERIF,2012-11-12
+Andika,SIL International,OFL,SANS_SERIF,2011-08-10
+Angkor,Danh Hong,OFL,DISPLAY,2011-03-02
+Annie Use Your Telescope,Kimberly Geswein,OFL,HANDWRITING,2011-04-14
+Anonymous Pro,Mark Simonson,OFL,MONOSPACE,2010-12-15
+Antic,Santiago Orozco,OFL,SANS_SERIF,2011-08-31
+Antic Didone,Santiago Orozco,OFL,SERIF,2012-03-14
+Antic Slab,Santiago Orozco,OFL,SERIF,2012-03-14
+Anton,Vernon Adams,OFL,SANS_SERIF,2011-02-23
+Antonio,Vernon Adams,OFL,SANS_SERIF,2013-03-06
+Arapey,Eduardo Tunni,OFL,SERIF,2011-11-02
+Arbutus,Karolina Lach,OFL,DISPLAY,2011-12-07
+Arbutus Slab,Karolina Lach,OFL,SERIF,2012-09-18
+Architects Daughter,Kimberly Geswein,OFL,HANDWRITING,2011-03-09
+Archivo,Omnibus-Type,OFL,SANS_SERIF,2016-12-03
+Archivo Black,Omnibus-Type,OFL,SANS_SERIF,2012-09-18
+Archivo Narrow,Omnibus-Type,OFL,SANS_SERIF,2012-09-18
+Aref Ruqaa,"Abdullah Aref, Khaled Hosny, Hermann Zapf",OFL,SERIF,2016-06-20
+Arima Madurai,Multiple Designers,OFL,DISPLAY,2016-08-22
+Arizonia,TypeSETit,OFL,HANDWRITING,2011-12-19
+Armata,Viktoriya Grabowska,OFL,SANS_SERIF,2011-12-19
+Arsenal,Andrij Shevchenko,OFL,SANS_SERIF,2016-12-06
+Artifika,Cyreal,OFL,SERIF,2011-06-01
+Arvo,Anton Koovit,OFL,SERIF,2010-11-17
+Arya,Multiple Designers,OFL,SANS_SERIF,2015-05-20
+Asap,Omnibus-Type,OFL,SANS_SERIF,2012-01-25
+Asap Condensed,Omnibus-Type,OFL,SANS_SERIF,2016-12-07
+Asar,Sorkin Type,OFL,SERIF,2015-06-17
+Asset,Riccardo De Franceschi,OFL,DISPLAY,2011-06-29
+Assistant,Multiple Designers,OFL,SANS_SERIF,2016-06-20
+Astloch,Dan Rhatigan,OFL,DISPLAY,2011-02-16
+Asul,Mariela Monsalve,OFL,SANS_SERIF,2011-12-19
+Athiti,Cadson Demak,OFL,SANS_SERIF,2016-06-20
+Atma,Black Foundry,OFL,DISPLAY,2017-05-09
+Atomic Age,James Grieshaber,OFL,DISPLAY,2011-10-26
+Aubrey,Cyreal,OFL,DISPLAY,2011-07-27
+Audiowide,Astigmatic,OFL,DISPLAY,2012-04-04
+Autour One,Sorkin Type,OFL,DISPLAY,2012-05-15
+Average,Eduardo Tunni,OFL,SERIF,2012-03-14
+Average Sans,Eduardo Tunni,OFL,SANS_SERIF,2012-10-26
+Averia Gruesa Libre,Dan Sayers,OFL,DISPLAY,2012-03-14
+Averia Libre,Dan Sayers,OFL,DISPLAY,2012-03-14
+Averia Sans Libre,Dan Sayers,OFL,DISPLAY,2012-03-14
+Averia Serif Libre,Dan Sayers,OFL,DISPLAY,2012-03-14
+B612,"Nicolas Chauveau, Thomas Paillot, Jonathan Favre-Lamarine, Jean-Luc Vinot",OFL,SANS_SERIF,2018-11-21
+B612 Mono,"Nicolas Chauveau, Thomas Paillot, Jonathan Favre-Lamarine, Jean-Luc Vinot",OFL,MONOSPACE,2018-11-21
+Bad Script,Gaslight,OFL,HANDWRITING,2011-12-13
+Bahiana,Omnibus-Type,OFL,DISPLAY,2016-12-02
+Bahianita,Omnibus-Type,OFL,DISPLAY,2019-06-12
+Bai Jamjuree,Cadson Demak,OFL,SANS_SERIF,2018-08-24
+Baloo 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Bhai 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Bhai,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Bhaijaan,Ek Type,OFL,DISPLAY,2017-06-16
+Baloo Bhaina 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Bhaina,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Chettan 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Chettan,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Da 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Da,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Paaji 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Paaji,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Tamma 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Tamma,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Tammudu 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Tammudu,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Thambi 2,Ek Type,OFL,DISPLAY,2016-01-20
+Baloo Thambi,Ek Type,OFL,DISPLAY,2016-01-20
+Balsamiq Sans,Michael Angeles,OFL,DISPLAY,2020-04-09
+Balthazar,Dario Manuel Muhafara,OFL,SERIF,2011-12-13
+Bangers,Vernon Adams,OFL,DISPLAY,2011-02-09
+Barlow,Jeremy Tribby,OFL,SANS_SERIF,2017-10-26
+Barlow Condensed,Jeremy Tribby,OFL,SANS_SERIF,2017-10-26
+Barlow Semi Condensed,Jeremy Tribby,OFL,SANS_SERIF,2017-10-26
+Barriecito,Omnibus-Type,OFL,DISPLAY,2019-06-12
+Barrio,Omnibus-Type,OFL,DISPLAY,2016-12-02
+Basic,Magnus Gaarde,OFL,SANS_SERIF,2011-12-15
+Baskervville,ANRT (Atelier National de Recherche typographique),OFL,SERIF,2019-10-04
+Battambang,Danh Hong,OFL,DISPLAY,2011-03-02
+Baumans,Cyreal,OFL,DISPLAY,2011-12-07
+Bayon,Danh Hong,OFL,DISPLAY,2011-03-02
+Bebas Neue,Ryoichi Tsunekawa,OFL,DISPLAY,2019-10-16
+Belgrano,LatinoType,OFL,SERIF,2011-12-19
+Bellefair,"Nick Shinn, Liron Lavi Turkenic",OFL,SERIF,2017-06-28
+Belleza,Eduardo Tunni,OFL,SANS_SERIF,2012-03-29
+Bellota,Kemie Guaida,OFL,DISPLAY,2020-01-16
+Bellota Text,Kemie Guaida,OFL,DISPLAY,2020-01-16
+BenchNine,Vernon Adams,OFL,SANS_SERIF,2012-09-24
+Bentham,Ben Weiner,OFL,SERIF,2010-11-30
+Berkshire Swash,Astigmatic,OFL,HANDWRITING,2012-03-14
+Beth Ellen,Rob Jelinski,OFL,HANDWRITING,2019-05-10
+Bevan,Vernon Adams,OFL,DISPLAY,2011-02-23
+Be Vietnam,"Gabriel Lam, Tony Le, Vietanh Nguyen, beGroup Vietnam",OFL,SANS_SERIF,2019-08-05
+Bhavuka,Multiple Designers,OFL,DISPLAY,2014-10-31
+Bigelow Rules,Astigmatic,OFL,DISPLAY,2012-11-02
+Bigshot One,Gesine Todt,OFL,DISPLAY,2011-05-04
+Big Shoulders Display,Patric King,OFL,DISPLAY,2019-09-11
+Big Shoulders Text,Patric King,OFL,DISPLAY,2019-09-11
+Bilbo,TypeSETit,OFL,HANDWRITING,2011-12-07
+Bilbo Swash Caps,TypeSETit,OFL,HANDWRITING,2011-12-13
+Bio Rhyme,Aoife Mooney,OFL,SERIF,2016-06-20
+Bio Rhyme Expanded,Aoife Mooney,OFL,SERIF,2016-06-20
+Biryani,"Dan Reynolds, Mathieu Réguer",OFL,SANS_SERIF,2015-04-22
+Bitter,Huerta Tipográfica,OFL,SERIF,2011-12-19
+Black And White Picture,AsiaSoft Inc.,OFL,SANS_SERIF,2018-02-27
+Black Han Sans,Zess Type,OFL,SANS_SERIF,2018-02-23
+Black Ops One,James Grieshaber,OFL,DISPLAY,2011-07-27
+Blinker,Juergen Huber,OFL,SANS_SERIF,2019-06-24
+Bokor,Danh Hong,OFL,DISPLAY,2011-03-02
+Bonbon,Cyreal,OFL,HANDWRITING,2011-12-07
+Boogaloo,John Vargas Beltrán,OFL,DISPLAY,2011-12-19
+Bowlby One,Vernon Adams,OFL,DISPLAY,2011-07-13
+Bowlby One SC,Vernon Adams,OFL,DISPLAY,2011-07-06
+Brawler,Cyreal,OFL,SERIF,2011-05-18
+Bree Serif,TypeTogether,OFL,SERIF,2011-12-19
+Bruno Ace,Astigmatic,OFL,SANS_SERIF,2012-11-16
+Bruno Ace SC,Astigmatic,OFL,SANS_SERIF,2012-11-16
+Bubblegum Sans,Sudtipos,OFL,DISPLAY,2011-11-23
+Bubbler One,Brenda Gallo,OFL,SANS_SERIF,2012-05-09
+Buda,Adèle Antignac,OFL,DISPLAY,2010-12-20
+Buenard,FontFuror,OFL,SERIF,2011-12-19
+Bungee,David Jonathan Ross,OFL,DISPLAY,2016-06-20
+Bungee Hairline,David Jonathan Ross,OFL,DISPLAY,2016-06-20
+Bungee Inline,David Jonathan Ross,OFL,DISPLAY,2016-06-20
+Bungee Outline,David Jonathan Ross,OFL,DISPLAY,2016-06-20
+Bungee Shade,David Jonathan Ross,OFL,DISPLAY,2016-06-20
+Butcherman,Typomondo,OFL,DISPLAY,2011-12-19
+Butcherman Caps,Typomondo,OFL,DISPLAY,2011-10-24
+Butterfly Kids,Tart Workshop,OFL,HANDWRITING,2012-02-15
+Cabin,Impallari Type,OFL,SANS_SERIF,2011-03-23
+Cabin Condensed,Impallari Type,OFL,SANS_SERIF,2011-11-30
+Cabin Sketch,Impallari Type,OFL,DISPLAY,2011-03-16
+Caesar Dressing,Open Window,OFL,DISPLAY,2011-12-19
+Cagliostro,MADType,OFL,SANS_SERIF,2011-11-30
+Cairo,"Mohamed Gaber, Multiple Designers",OFL,SANS_SERIF,2016-06-20
+Caladea,"Andrés Torresi, Carolina Giovagnoli",OFL,SERIF,2020-02-11
+Calistoga,"Yvonne Schuttler, Eben Sorkin",OFL,DISPLAY,2019-11-04
+Cambay,Pooja Saxena,OFL,SANS_SERIF,2015-01-28
+Cambo,Huerta Tipográfica,OFL,SERIF,2011-12-19
+Candal,Vernon Adams,OFL,SANS_SERIF,2011-03-09
+Cantarell,Dave Crossland,OFL,SANS_SERIF,2010-05-10
+Cantata One,Joana Correia,OFL,SERIF,2012-02-29
+Cantora One,Impallari Type,OFL,SANS_SERIF,2012-07-30
+Capriola,Viktoriya Grabowska,OFL,SANS_SERIF,2012-07-10
+Cardo,David Perry,OFL,SERIF,2011-09-07
+Carme,Rubén Prol,OFL,SANS_SERIF,2011-07-27
+Carrois Gothic,Carrois Apostrophe,OFL,SANS_SERIF,2012-09-30
+Carrois Gothic SC,Carrois Apostrophe,OFL,SANS_SERIF,2012-09-30
+Carter One,Vernon Adams,OFL,DISPLAY,2011-05-04
+Catamaran,Pria Ravichandran,OFL,SANS_SERIF,2015-07-08
+Caudex,Nidud,OFL,SERIF,2011-05-18
+Caveat,Impallari Type,OFL,HANDWRITING,2015-09-23
+Caveat Brush,Impallari Type,OFL,HANDWRITING,2015-09-23
+Cedarville Cursive,Kimberly Geswein,OFL,HANDWRITING,2011-06-08
+Ceviche One,Miguel Hernandez,OFL,DISPLAY,2011-12-07
+Chakra Petch,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+Changa,Eduardo Tunni,OFL,SANS_SERIF,2012-10-31
+Changa One,Eduardo Tunni,OFL,DISPLAY,2011-11-30
+Chango,Fontstage,OFL,DISPLAY,2011-12-13
+Charm,Cadson Demak,OFL,HANDWRITING,2018-08-23
+Charmonman,Cadson Demak,OFL,HANDWRITING,2018-08-22
+Chathura,Multiple Designers,OFL,SANS_SERIF,2017-05-09
+Chau Philomene One,Vicente Lamónaca,OFL,SANS_SERIF,2012-04-04
+Chela One,Miguel Hernandez,OFL,DISPLAY,2012-10-05
+Chelsea Market,Tart Workshop,OFL,DISPLAY,2012-01-04
+Chenla,Danh Hong,OFL,DISPLAY,2011-03-02
+Cherry Bomb,Satsuyako,OFL,DISPLAY,2019-12-02
+Cherry Swash,Nataliya Kasatkina,OFL,DISPLAY,2012-10-05
+Chicle,Sudtipos,OFL,DISPLAY,2011-11-30
+Chilanka,SMC,OFL,HANDWRITING,2019-06-10
+Chivo,Omnibus-Type,OFL,SANS_SERIF,2011-12-07
+Chonburi,Cadson Demak,OFL,DISPLAY,2015-07-08
+Cinzel,Natanael Gama,OFL,SERIF,2012-10-24
+Cinzel Decorative,Natanael Gama,OFL,DISPLAY,2012-10-05
+Clicker Script,Astigmatic,OFL,HANDWRITING,2012-11-11
+Coda,Vernon Adams,OFL,DISPLAY,2010-12-07
+Coda Caption,Vernon Adams,OFL,SANS_SERIF,2011-02-09
+Codystar,Neapolitan,OFL,DISPLAY,2012-03-14
+Coiny,Marcelo Magalhães,OFL,DISPLAY,2016-06-20
+Combo,Eduardo Tunni,OFL,DISPLAY,2012-09-23
+Comfortaa,Johan Aakerlund,OFL,DISPLAY,2011-08-10
+Comic Neue,Craig Rozynski,OFL,HANDWRITING,2020-03-12
+Concert One,Multiple Designers,OFL,DISPLAY,2011-11-23
+Condiment,Sudtipos,OFL,HANDWRITING,2012-01-25
+Content,Danh Hong,OFL,DISPLAY,2011-03-02
+Contrail One,Riccardo De Franceschi,OFL,DISPLAY,2011-10-26
+Convergence,Multiple Designers,OFL,SANS_SERIF,2011-11-09
+Cookie,Ania Kruk,OFL,HANDWRITING,2011-10-12
+Copse,Dan Rhatigan,OFL,SERIF,2010-12-15
+Corben,Vernon Adams,OFL,DISPLAY,2010-12-20
+Cormorant,Christian Thalmann,OFL,SERIF,2017-01-18
+Cormorant Garamond,Christian Thalmann,OFL,SERIF,2017-01-18
+Cormorant Infant,Christian Thalmann,OFL,SERIF,2017-01-18
+Cormorant SC,Christian Thalmann,OFL,SERIF,2017-01-18
+Cormorant Unicase,Christian Thalmann,OFL,SERIF,2017-01-18
+Cormorant Upright,Christian Thalmann,OFL,SERIF,2017-01-18
+Courgette,Karolina Lach,OFL,HANDWRITING,2012-07-10
+Courier Prime,Alan Dague-Greene,OFL,MONOSPACE,2019-12-05
+Coustard,Vernon Adams,OFL,SERIF,2011-08-10
+Covered By Your Grace,Kimberly Geswein,OFL,HANDWRITING,2010-12-07
+Creepster,Sideshow,OFL,DISPLAY,2011-12-19
+Crete Round,TypeTogether,OFL,SERIF,2011-12-19
+Crimson Pro,Jacques Le Bailly,OFL,SERIF,2018-12-05
+Crimson Text,Sebastian Kosch,OFL,SERIF,2011-01-26
+Croissant One,Eduardo Tunni,OFL,DISPLAY,2012-11-12
+Cuprum,Jovanny Lemonad,OFL,SANS_SERIF,2012-04-04
+Cute Font,TypoDesign Lab. Inc,OFL,DISPLAY,2018-02-23
+Cutive,Vernon Adams,OFL,SERIF,2012-02-29
+Cutive Mono,Vernon Adams,OFL,MONOSPACE,2012-10-26
+Damion,Vernon Adams,OFL,HANDWRITING,2011-04-27
+Dancing Script,Impallari Type,OFL,HANDWRITING,2011-05-18
+Dangrek,Danh Hong,OFL,DISPLAY,2011-03-02
+Darker Grotesque,"Gabriel Lam, Vietanh Nguyen",OFL,SANS_SERIF,2019-06-19
+Dawning of a New Day,Kimberly Geswein,OFL,HANDWRITING,2011-04-14
+Days One,Jovanny Lemonad,OFL,SANS_SERIF,2011-08-17
+Dekko,Sorkin Type,OFL,HANDWRITING,2015-01-28
+Delius,Natalia Raices,OFL,HANDWRITING,2011-07-27
+Delius Swash Caps,Natalia Raices,OFL,HANDWRITING,2011-08-03
+Delius Unicase,Natalia Raices,OFL,HANDWRITING,2011-10-12
+Della Respira,Nathan Willis,OFL,SERIF,2012-04-04
+Denk One,Sorkin Type,OFL,SANS_SERIF,2012-11-26
+Devonshire,Astigmatic,OFL,HANDWRITING,2011-11-16
+Dhurjati,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Dhyana,Vernon Adams,OFL,SERIF,2011-12-15
+Didact Gothic,"Daniel Johnson, Cyreal",OFL,SANS_SERIF,2011-05-04
+Digital Numbers,Stephan Ahlf,OFL,MONOSPACE,2015-06-24
+Diplomata,Eduardo Tunni,OFL,DISPLAY,2012-01-25
+Diplomata SC,Eduardo Tunni,OFL,DISPLAY,2012-01-25
+DM Mono,Colophon Foundry,OFL,MONOSPACE,2020-04-15
+DM Sans,"Colophon Foundry, Jonny Pinhorn",OFL,SANS_SERIF,2019-06-12
+DM Serif Display,"Colophon Foundry, Frank Grießhammer",OFL,SERIF,2019-06-12
+DM Serif Text,"Colophon Foundry, Frank Grießhammer",OFL,SERIF,2019-06-12
+Do Hyeon,Woowahan Brothers,OFL,SANS_SERIF,2018-02-24
+Dokdo,FONTRIX,OFL,HANDWRITING,2018-02-23
+Domine,Impallari Type,OFL,SERIF,2012-11-30
+Donegal One,Gary Lonergan,OFL,SERIF,2012-11-26
+Doppio One,Szymon Celej,OFL,SANS_SERIF,2012-02-22
+Dorsa,Santiago Orozco,OFL,SANS_SERIF,2011-08-31
+Dosis,Impallari Type,OFL,SANS_SERIF,2019-01-23
+Dr Sugiyama,Sudtipos,OFL,HANDWRITING,2011-11-30
+Duru Sans,Onur Yazıcıgil,OFL,SANS_SERIF,2011-12-19
+Dynalight,Astigmatic,OFL,DISPLAY,2011-12-19
+Eagle Lake,Astigmatic,OFL,HANDWRITING,2012-07-11
+East Sea Dokdo,YoonDesign Inc,OFL,HANDWRITING,2018-03-12
+Eater,Typomondo,OFL,DISPLAY,2011-12-19
+Eater Caps,Typomondo,OFL,DISPLAY,2011-10-24
+EB Garamond,"Georg Duffner, Octavio Pardo",OFL,SERIF,2011-03-23
+Economica,Vicente Lamónaca,OFL,SANS_SERIF,2012-02-29
+Eczar,Rosetta,OFL,SERIF,2015-06-03
+Ek Mukta,Ek Type,OFL,SANS_SERIF,2014-05-12
+Electrolize,Gaslight,OFL,SANS_SERIF,2011-12-07
+El Messiri,"Mohamed Gaber, Jovanny Lemonad",OFL,SANS_SERIF,2016-06-20
+Elsie,Alejandro Inler,OFL,DISPLAY,2012-11-12
+Elsie Swash Caps,Alejandro Inler,OFL,DISPLAY,2012-11-12
+Emblema One,Riccardo De Franceschi,OFL,DISPLAY,2012-01-18
+Emilys Candy,Neapolitan,OFL,DISPLAY,2012-02-29
+Encode Sans,"Impallari Type, Andres Torresi, Jacques Le Bailly",OFL,SANS_SERIF,2020-05-07
+Encode Sans Condensed,"Impallari Type, Andres Torresi, Jacques Le Bailly",OFL,SANS_SERIF,2017-02-08
+Encode Sans Expanded,"Impallari Type, Andres Torresi, Jacques Le Bailly",OFL,SANS_SERIF,2017-02-08
+Encode Sans Semi Condensed,"Impallari Type, Andres Torresi, Jacques Le Bailly",OFL,SANS_SERIF,2017-02-08
+Encode Sans Semi Expanded,"Impallari Type, Andres Torresi, Jacques Le Bailly",OFL,SANS_SERIF,2017-02-08
+Engagement,Astigmatic,OFL,HANDWRITING,2011-12-07
+Englebert,Astigmatic,OFL,SANS_SERIF,2012-11-02
+Enriqueta,FontFuror,OFL,SERIF,2011-12-13
+Erica One,Miguel Hernandez,OFL,DISPLAY,2012-01-18
+Esteban,Angélica Díaz,OFL,SERIF,2012-01-11
+Euphoria Script,Sabrina Mariela Lopez,OFL,HANDWRITING,2012-02-08
+Ewert,Multiple Designers,OFL,DISPLAY,2012-02-08
+Exo 2,Natanael Gama,OFL,SANS_SERIF,2013-12-04
+Exo,"Natanael Gama, Robin Mientjes",OFL,SANS_SERIF,2012-02-08
+Expletus Sans,Designtown,OFL,DISPLAY,2011-05-04
+Fahkwang,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+Fanwood Text,Barry Schwartz,OFL,SERIF,2011-08-31
+Farro,Grayscale,OFL,SANS_SERIF,2019-07-17
+Farsan,Pooja Saxena,OFL,DISPLAY,2016-06-20
+Fascinate,Astigmatic,OFL,DISPLAY,2011-12-07
+Fascinate Inline,Astigmatic,OFL,DISPLAY,2011-12-07
+Faster One,Eduardo Tunni,OFL,DISPLAY,2012-10-26
+Fasthand,Danh Hong,OFL,SERIF,2012-05-24
+Fauna One,Eduardo Tunni,OFL,SERIF,2013-06-05
+Faustina,Omnibus-Type,OFL,SERIF,2016-12-03
+Federant,Cyreal,OFL,DISPLAY,2011-10-05
+Federo,Cyreal,OFL,SANS_SERIF,2011-07-27
+Felipa,Fontstage,OFL,HANDWRITING,2012-02-08
+Fenix,Fernando Díaz,OFL,SERIF,2012-09-24
+Finger Paint,Carrois Apostrophe,OFL,DISPLAY,2012-09-30
+Fira Code,Multiple Designers,OFL,MONOSPACE,2019-03-25
+Fira Mono,Carrois Apostrophe,OFL,MONOSPACE,2014-06-18
+Fira Sans,Carrois Apostrophe,OFL,SANS_SERIF,2014-06-18
+Fira Sans Condensed,Carrois Apostrophe,OFL,SANS_SERIF,2016-12-02
+Fira Sans Extra Condensed,Carrois Apostrophe,OFL,SANS_SERIF,2016-12-06
+Fjalla One,Sorkin Type,OFL,SANS_SERIF,2012-10-27
+Fjord One,Viktoriya Grabowska,OFL,SERIF,2011-11-02
+Flamenco,LatinoType,OFL,DISPLAY,2011-12-19
+Flavors,Sideshow,OFL,DISPLAY,2011-12-19
+Fondamento,Astigmatic,OFL,HANDWRITING,2011-11-16
+Forum,Denis Masharov,OFL,DISPLAY,2011-07-06
+Francois One,Vernon Adams,OFL,SANS_SERIF,2011-05-04
+Frank Ruhl Libre,Yanek Iontef,OFL,SERIF,2016-06-20
+Freckle Face,Astigmatic,OFL,DISPLAY,2012-11-26
+Fredericka the Great,Tart Workshop,OFL,DISPLAY,2011-12-19
+Fredoka One,Milena Brandao,OFL,DISPLAY,2012-03-14
+Freehand,Danh Hong,OFL,DISPLAY,2011-03-02
+Fresca,Fontstage,OFL,SANS_SERIF,2011-12-07
+Frijole,Sideshow,OFL,DISPLAY,2011-12-19
+Fruktur,Viktoriya Grabowska,OFL,DISPLAY,2013-01-16
+Fugaz One,LatinoType,OFL,DISPLAY,2011-12-19
+Gabriela,Eduardo Tunni,OFL,SERIF,2013-03-06
+Gaegu,JIKJI SOFT,OFL,HANDWRITING,2018-02-28
+Gafata,Lautaro Hourcade,OFL,SANS_SERIF,2012-10-31
+Galada,Multiple Designers,OFL,DISPLAY,2016-06-20
+Galdeano,Dario Manuel Muhafara,OFL,SANS_SERIF,2011-12-07
+Galindo,Astigmatic,OFL,DISPLAY,2012-08-13
+Gamja Flower,YoonDesign Inc,OFL,HANDWRITING,2018-02-23
+Gayathri,SMC,OFL,SANS_SERIF,2019-06-10
+Gelasio,Eben Sorkin,OFL,SERIF,2019-12-03
+Gemunu Libre,Mooniak,OFL,SANS_SERIF,2017-05-29
+Gentium Basic,Victor Gaultney,OFL,SERIF,2011-07-20
+Gentium Book Basic,Victor Gaultney,OFL,SERIF,2011-08-17
+Geo,Ben Weiner,OFL,SANS_SERIF,2010-11-30
+Geostar,Joe Prince,OFL,DISPLAY,2011-08-10
+Geostar Fill,Joe Prince,OFL,DISPLAY,2011-08-10
+Germania One,John Vargas Beltrán,OFL,DISPLAY,2012-01-18
+GFS Didot,Greek Font Society,OFL,SERIF,2010-09-21
+GFS Neohellenic,Greek Font Society,OFL,SANS_SERIF,2010-09-21
+Gidugu,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Gilda Display,Eduardo Tunni,OFL,SERIF,2012-10-31
+Girassol,Liam Spradlin,OFL,DISPLAY,2019-12-05
+Give You Glory,Kimberly Geswein,OFL,HANDWRITING,2011-07-13
+Glass Antiqua,Denis Masharov,OFL,DISPLAY,2012-02-22
+Glegoo,Eduardo Tunni,OFL,SERIF,2012-01-25
+Gloria Hallelujah,Kimberly Geswein,OFL,HANDWRITING,2011-07-27
+Goblin One,Riccardo De Franceschi,OFL,DISPLAY,2011-06-29
+Gochi Hand,Huerta Tipográfica,OFL,HANDWRITING,2011-10-05
+Gorditas,Gustavo Dipre,OFL,DISPLAY,2012-03-14
+Gothic A1,HanYang I&C Co,OFL,SANS_SERIF,2018-02-24
+Gotu,Ek Type,OFL,SANS_SERIF,2020-01-10
+Goudy Bookletter 1911,Barry Schwartz,OFL,SERIF,2011-02-09
+Graduate,Eduardo Tunni,OFL,DISPLAY,2012-03-14
+Grand Hotel,Astigmatic,OFL,HANDWRITING,2012-11-30
+Gravitas One,Riccardo De Franceschi,OFL,DISPLAY,2011-06-29
+Great Vibes,TypeSETit,OFL,HANDWRITING,2012-03-29
+Grenze,Omnibus-Type,OFL,SERIF,2018-09-19
+Grenze Gotisch,Omnibus-Type,OFL,DISPLAY,2020-05-18
+Griffy,Neapolitan,OFL,DISPLAY,2012-09-06
+Gruppo,Vernon Adams,OFL,DISPLAY,2010-12-20
+Gudea,Agustina Mingote,OFL,SANS_SERIF,2012-01-18
+Gugi,TAE System & Typefaces Co.,OFL,DISPLAY,2018-02-23
+Gupter,Octavio Pardo,OFL,SERIF,2019-11-13
+Gurajada,Purushoth Kumar Guttula,OFL,SERIF,2015-01-08
+Habibi,Magnus Gaarde,OFL,SERIF,2011-12-19
+Halant,Indian Type Foundry,OFL,SERIF,2014-08-27
+Hammersmith One,Nicole Fally,OFL,SANS_SERIF,2011-06-29
+Hanalei,Astigmatic,OFL,DISPLAY,2012-11-26
+Hanalei Fill,Astigmatic,OFL,DISPLAY,2012-11-26
+Handlee,Joe Prince,OFL,HANDWRITING,2011-12-13
+Hanuman,Danh Hong,OFL,SERIF,2010-09-21
+Happy Monkey,Brenda Gallo,OFL,DISPLAY,2012-03-14
+Harmattan,SIL International,OFL,SANS_SERIF,2016-06-20
+Headland One,Gary Lonergan,OFL,SERIF,2012-05-09
+Heebo,Multiple Designers,OFL,SANS_SERIF,2016-06-20
+Henny Penny,Brownfox,OFL,DISPLAY,2012-02-22
+Hepta Slab,Mike LaGattuta,OFL,SERIF,2018-09-19
+Hermeneus One,Impallari Type,OFL,SANS_SERIF,2012-05-01
+Herr Von Muellerhoff,Sudtipos,OFL,HANDWRITING,2011-11-30
+Hi Melody,YoonDesign Inc,OFL,HANDWRITING,2018-02-23
+Hind,Indian Type Foundry,OFL,SANS_SERIF,2014-06-25
+Hind Colombo,Indian Type Foundry,OFL,SANS_SERIF,2016-01-20
+Hind Guntur,Indian Type Foundry,OFL,SANS_SERIF,2016-01-20
+Hind Jalandhar,Indian Type Foundry,OFL,SANS_SERIF,2016-01-20
+Hind Kochi,Indian Type Foundry,OFL,SANS_SERIF,2016-01-20
+Hind Madurai,Indian Type Foundry,OFL,SANS_SERIF,2016-01-20
+Hind Mysuru,Indian Type Foundry,OFL,SANS_SERIF,2016-01-20
+Hind Siliguri,Indian Type Foundry,OFL,SANS_SERIF,2015-09-09
+Hind Vadodara,Indian Type Foundry,OFL,SANS_SERIF,2015-09-09
+Holtwood One SC,Vernon Adams,OFL,SERIF,2011-05-04
+Homenaje,Multiple Designers,OFL,SANS_SERIF,2012-01-18
+Ibarra Real Nova,"Jos\303\251 Mar\303\255a Ribagorda, Octavio Pardo",OFL,SERIF,2019-11-04
+IBM Plex Mono,"Mike Abbink, Bold Monday",OFL,MONOSPACE,2018-03-12
+IBM Plex Sans,"Mike Abbink, Bold Monday",OFL,SANS_SERIF,2018-03-12
+IBM Plex Sans Condensed,"Mike Abbink, Bold Monday",OFL,SANS_SERIF,2018-03-12
+IBM Plex Serif,"Mike Abbink, Bold Monday",OFL,SERIF,2018-03-12
+Iceberg,Cyreal,OFL,DISPLAY,2012-01-25
+Iceland,Cyreal,OFL,DISPLAY,2011-11-23
+IM Fell Double Pica,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell Double Pica SC,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell DW Pica,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell DW Pica SC,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell English,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell English SC,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell French Canon,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell French Canon SC,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell Great Primer,Igino Marini,OFL,SERIF,2010-05-17
+IM Fell Great Primer SC,Igino Marini,OFL,SERIF,2010-05-17
+Imprima,Eduardo Tunni,OFL,SANS_SERIF,2012-03-14
+Inconsolata,Raph Levien,OFL,MONOSPACE,2010-02-19
+Inder,Sorkin Type,OFL,SANS_SERIF,2011-12-19
+Indie Flower,Kimberly Geswein,OFL,HANDWRITING,2011-03-09
+Inika,Constanza Artigas,OFL,SERIF,2012-01-11
+Inknut Antiqua,Claus Eggers Sørensen,OFL,SERIF,2015-05-20
+Inria Sans,"Grégori Vincens, Jérémie Hornus",OFL,SANS_SERIF,2019-12-05
+Inria Serif,"Grégori Vincens, Jérémie Hornus",OFL,SERIF,2019-12-05
+Inter,Rasmus Andersson,OFL,SANS_SERIF,2020-01-24
+Istok Web,Andrey V. Panov,OFL,SANS_SERIF,2011-07-13
+Italiana,Santiago Orozco,OFL,SERIF,2012-03-14
+Italianno,TypeSETit,OFL,HANDWRITING,2011-12-19
+Itim,Cadson Demak,OFL,HANDWRITING,2015-07-01
+Jacques Francois,Cyreal,OFL,SERIF,2012-09-07
+Jacques Francois Shadow,Cyreal,OFL,DISPLAY,2012-09-07
+Jaldi,Omnibus-Type,OFL,SANS_SERIF,2015-04-22
+Jim Nightshade,Astigmatic,OFL,HANDWRITING,2012-01-04
+Jockey One,TypeTogether,OFL,SANS_SERIF,2011-10-26
+Jolly Lodger,Font Diner,OFL,DISPLAY,2012-03-14
+Jomhuria,KB Studio,OFL,DISPLAY,2016-06-20
+Jomolhari,Christopher J. Fynn,OFL,SERIF,2019-09-10
+Josefin Sans,Santiago Orozco,OFL,SANS_SERIF,2010-11-17
+Josefin Sans Std Light,hidden,OFL,SANS_SERIF,2010-05-18
+Josefin Slab,Santiago Orozco,OFL,SERIF,2010-11-17
+Jost,Owen Earl,OFL,SANS_SERIF,2020-02-11
+Joti One,Eduardo Tunni,OFL,DISPLAY,2012-10-31
+Jua,Woowahan Brothers,OFL,SANS_SERIF,2018-02-24
+Judson,Daniel Johnson,OFL,SERIF,2011-05-04
+Julee,Julian Tunni,OFL,HANDWRITING,2011-09-07
+Julius Sans One,Luciano Vergara,OFL,SANS_SERIF,2012-10-05
+Junge,Cyreal,OFL,SERIF,2012-01-18
+Jura,"Daniel Johnson, Cyreal",OFL,SANS_SERIF,2011-05-18
+Just Me Again Down Here,Kimberly Geswein,OFL,HANDWRITING,2010-12-07
+K2D,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+Kadwa,Sol Matas,OFL,SERIF,2015-06-17
+Kalam,Indian Type Foundry,OFL,HANDWRITING,2014-10-17
+Kameron,Vernon Adams,OFL,SERIF,2011-06-08
+Kanit,Cadson Demak,OFL,SANS_SERIF,2015-12-07
+Kantumruy,Tep Sovichet,OFL,SANS_SERIF,2013-06-24
+Karla,Jonny Pinhorn,OFL,SANS_SERIF,2012-03-14
+Karla Tamil Inclined,Jonathan Pinhorn,OFL,SANS_SERIF,2012-09-29
+Karla Tamil Upright,Jonathan Pinhorn,OFL,SANS_SERIF,2012-09-29
+Karma,Indian Type Foundry,OFL,SERIF,2014-06-25
+Katibeh,KB Studio,OFL,DISPLAY,2016-06-20
+Kaushan Script,Impallari Type,OFL,HANDWRITING,2012-01-25
+Kavivanar,Tharique Azeez,OFL,HANDWRITING,2016-06-20
+Kavoon,Viktoriya Grabowska,OFL,DISPLAY,2013-01-23
+Kdam Thmor,Tep Sovichet,OFL,DISPLAY,2013-12-04
+Keania One,Julia Petretta,OFL,DISPLAY,2012-10-31
+Kelly Slab,Denis Masharov,OFL,DISPLAY,2011-07-27
+Kenia,Julia Petretta,OFL,DISPLAY,2010-12-15
+Khand,Indian Type Foundry,OFL,SANS_SERIF,2014-07-14
+Khmer,Danh Hong,OFL,DISPLAY,2011-03-02
+Khula,Erin McLaughlin,OFL,SANS_SERIF,2015-01-28
+Kirang Haerang,Woowahan Brothers,OFL,DISPLAY,2018-02-24
+Kite One,Eduardo Tunni,OFL,SANS_SERIF,2012-10-26
+Knewave,Tyler Finck,OFL,DISPLAY,2011-11-23
+Kodchasan,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+KoHo,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+Kotta One,Ania Kruk,OFL,SERIF,2012-01-25
+Koulen,Danh Hong,OFL,DISPLAY,2011-03-02
+Kreon,Julia Petretta,OFL,SERIF,2011-02-02
+Kristi,Birgit Pulk,OFL,HANDWRITING,2010-12-20
+Krona One,Yvonne Schüttler,OFL,SANS_SERIF,2012-02-22
+Krub,Cadson Demak,OFL,SANS_SERIF,2018-08-24
+Kulim Park,Dale Sattler,OFL,SANS_SERIF,2019-09-25
+Kumar One,Indian Type Foundry,OFL,DISPLAY,2016-06-20
+Kurale,Eduardo Tunni,OFL,SERIF,2015-05-14
+La Belle Aurore,Kimberly Geswein,OFL,HANDWRITING,2011-06-08
+Lacquer,"Niki Polyocan, Eli Block",OFL,DISPLAY,2019-07-04
+Laila,Indian Type Foundry,OFL,SERIF,2014-08-27
+Lakki Reddy,Appaji Ambarisha Darbha,OFL,HANDWRITING,2015-01-12
+Lalezar,Borna Izadpanah,OFL,SANS_SERIF,2017-02-28
+Lancelot,Marion Kadi,OFL,DISPLAY,2011-11-02
+Lateef,SIL International,OFL,SERIF,2012-01-18
+Lato,Łukasz Dziedzic,OFL,SANS_SERIF,2010-12-15
+League Gothic,"League Of Movable Type, Mirko Velimirovic",OFL,SANS_SERIF,2020-01-30
+League Script,Haley Fiege,OFL,HANDWRITING,2011-03-09
+Leckerli One,Gesine Todt,OFL,HANDWRITING,2011-07-20
+Ledger,Denis Masharov,OFL,SERIF,2012-02-22
+Lekton,Multiple Designers,OFL,SANS_SERIF,2010-12-20
+Lemon,Eduardo Tunni,OFL,DISPLAY,2011-11-30
+Lemonada,"Mohamed Gaber, Eduardo Tunni",OFL,DISPLAY,2016-06-20
+Lexend Deca,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Lexend Exa,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Lexend Giga,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Lexend Mega,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Lexend Peta,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Lexend Tera,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Lexend Zetta,Thomas Jockin,OFL,SANS_SERIF,2019-08-01
+Libre Barcode 128,Lasse Fister,OFL,DISPLAY,2017-07-31
+Libre Barcode 128 Text,Lasse Fister,OFL,DISPLAY,2017-07-31
+Libre Barcode 39,Lasse Fister,OFL,DISPLAY,2017-07-31
+Libre Barcode 39 Extended,Lasse Fister,OFL,DISPLAY,2017-08-21
+Libre Barcode 39 Extended Text,Lasse Fister,OFL,DISPLAY,2017-08-21
+Libre Barcode 39 Text,Lasse Fister,OFL,DISPLAY,2017-07-31
+Libre Baskerville,Impallari Type,OFL,SERIF,2012-11-30
+Libre Caslon Display,Impallari Type,OFL,SERIF,2017-11-30
+Libre Caslon Text,Impallari Type,OFL,SERIF,2013-03-15
+Libre Franklin,Impallari Type,OFL,SANS_SERIF,2016-06-20
+Life Savers,Impallari Type,OFL,DISPLAY,2012-08-13
+Lilita One,Juan Montoreano,OFL,DISPLAY,2012-01-11
+Lily Script One,Julia Petretta,OFL,DISPLAY,2013-06-05
+Limelight,Nicole Fally,OFL,DISPLAY,2011-05-25
+Linden Hill,Barry Schwartz,OFL,SERIF,2011-10-19
+Literata,TypeTogether,OFL,SERIF,2018-12-06
+Liu Jian Mao Cao,Liu Zhengjiang,OFL,HANDWRITING,2019-03-18
+Livvic,"LV=, Jacques Le Bailly",OFL,SANS_SERIF,2019-06-21
+Lobster,Impallari Type,OFL,DISPLAY,2010-05-17
+Lobster Two,Impallari Type,OFL,DISPLAY,2011-06-21
+Lohit Bengali,Multiple Designers,OFL,SERIF,2012-05-09
+Lohit Tamil,Multiple Designers,OFL,SERIF,2011-12-12
+Londrina Outline,Marcelo Magalhães,OFL,DISPLAY,2012-03-14
+Londrina Shadow,Marcelo Magalhães,OFL,DISPLAY,2012-03-14
+Londrina Sketch,Marcelo Magalhães,OFL,DISPLAY,2012-03-14
+Londrina Solid,Marcelo Magalhães,OFL,DISPLAY,2012-03-14
+Long Cang,Chen Xiaomin,OFL,HANDWRITING,2019-03-18
+Lora,Cyreal,OFL,SERIF,2011-07-06
+Loved by the King,Kimberly Geswein,OFL,HANDWRITING,2011-07-06
+Lovers Quarrel,TypeSETit,OFL,HANDWRITING,2012-03-29
+Love Ya Like A Sister,Kimberly Geswein,OFL,DISPLAY,2011-07-06
+Lusitana,Ana Paula Megda,OFL,SERIF,2012-01-11
+Lustria,MADType,OFL,SERIF,2012-01-18
+Macondo,John Vargas Beltrán,OFL,DISPLAY,2012-01-18
+Macondo Swash Caps,John Vargas Beltrán,OFL,DISPLAY,2012-01-18
+Mada,"Khaled Hosny, Paul D. Hunt",OFL,SANS_SERIF,2017-05-08
+Magra,FontFuror,OFL,SANS_SERIF,2012-01-11
+Maitree,Cadson Demak,OFL,SERIF,2016-06-20
+Major Mono Display,Emre Parlak,OFL,MONOSPACE,2018-12-05
+Mako,Vernon Adams,OFL,SANS_SERIF,2011-05-11
+Mali,Cadson Demak,OFL,HANDWRITING,2018-08-22
+Mallanna,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Mandali,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Manjari,Santhosh Thottingal,OFL,SANS_SERIF,2018-11-21
+Manrope,Mikhail Sharanda,OFL,SANS_SERIF,2019-10-03
+Mansalva,Carolina Short,OFL,HANDWRITING,2019-08-29
+Manuale,Omnibus-Type,OFL,SERIF,2016-12-03
+Marcellus,Astigmatic,OFL,SERIF,2012-05-09
+Marcellus SC,Astigmatic,OFL,SERIF,2012-05-09
+Marck Script,Denis Masharov,OFL,HANDWRITING,2011-10-12
+Margarine,Astigmatic,OFL,DISPLAY,2012-11-16
+Markazi Text,"Borna Izadpanah, Fiona Ross, Florian Runge",OFL,SERIF,2018-06-06
+Marko One,Cyreal,OFL,SERIF,2011-12-13
+Marmelad,Cyreal,OFL,SANS_SERIF,2011-12-07
+Martel,Dan Reynolds,OFL,SERIF,2015-04-20
+Martel Sans,"Dan Reynolds, Mathieu Réguer",OFL,SANS_SERIF,2015-03-04
+Marvel,Carolina Trebol,OFL,SANS_SERIF,2011-08-03
+Ma Shan Zheng,Ma ShanZheng,OFL,HANDWRITING,2019-03-18
+Mate,Eduardo Tunni,OFL,SERIF,2011-11-02
+Mate SC,Eduardo Tunni,OFL,SERIF,2011-11-02
+Maven Pro,Joe Prince,OFL,SANS_SERIF,2011-05-25
+McLaren,Astigmatic,OFL,DISPLAY,2012-08-13
+Meddon,Vernon Adams,OFL,HANDWRITING,2011-02-02
+MedievalSharp,Wojciech Kalinowski,OFL,DISPLAY,2011-03-02
+Medula One,LatinoType,OFL,DISPLAY,2011-12-19
+Meera Inimai,SMC,OFL,SANS_SERIF,2016-06-20
+Megrim,Daniel Johnson,OFL,DISPLAY,2011-05-04
+Meie Script,Multiple Designers,OFL,HANDWRITING,2012-08-21
+Merge One,Kosal Sen,OFL,SANS_SERIF,2012-10-05
+Merienda,Eduardo Tunni,OFL,HANDWRITING,2012-10-31
+Merienda One,Eduardo Tunni,OFL,HANDWRITING,2011-09-07
+Merriweather,Sorkin Type,OFL,SERIF,2011-05-11
+Merriweather Sans,Sorkin Type,OFL,SANS_SERIF,2013-03-06
+Mervale Script,Astigmatic,OFL,HANDWRITING,2012-11-12
+Metal,Danh Hong,OFL,DISPLAY,2011-03-02
+Metal Mania,Open Window,OFL,DISPLAY,2012-07-11
+Metamorphous,James Grieshaber,OFL,DISPLAY,2011-12-07
+Metrophobic,Vernon Adams,OFL,SANS_SERIF,2011-05-11
+Miama,Linus Romer,OFL,HANDWRITING,2012-05-09
+Michroma,Vernon Adams,OFL,SANS_SERIF,2011-03-30
+Milonga,Impallari Type,OFL,DISPLAY,2012-11-30
+Miltonian,Impallari Type,OFL,DISPLAY,2011-04-06
+Miltonian Tattoo,Impallari Type,OFL,DISPLAY,2011-04-06
+Mina,"Suman Bhandary, Natanael Gama, Mooniak",OFL,SANS_SERIF,2017-02-20
+Miniver,Open Window,OFL,DISPLAY,2011-12-19
+Miriam Libre,Michal Sahar,OFL,SANS_SERIF,2016-06-20
+Mirza,KB Studio,OFL,DISPLAY,2016-06-20
+Miss Fajardose,Sudtipos,OFL,HANDWRITING,2011-11-30
+Miss Saint Delafield,Sudtipos,OFL,HANDWRITING,2011-11-30
+Mitr,Cadson Demak,OFL,SANS_SERIF,2016-06-20
+Modak,Ek Type,OFL,DISPLAY,2015-02-18
+Modern Antiqua,Wojciech Kalinowski,OFL,DISPLAY,2011-07-13
+Mogra,Lipi Raval,OFL,DISPLAY,2017-05-09
+Mohave,Gumpita Rahayu,OFL,SANS_SERIF,2020-01-23
+Molengo,Denis Jacquerye,OFL,SANS_SERIF,2010-04-19
+Molle,Elena Albertoni,OFL,HANDWRITING,2012-09-18
+Monda,Vernon Adams,OFL,SANS_SERIF,2012-11-30
+Monofett,Vernon Adams,OFL,DISPLAY,2011-05-04
+Monoton,Vernon Adams,OFL,DISPLAY,2011-08-24
+Monsieur La Doulaise,Sudtipos,OFL,HANDWRITING,2011-11-30
+Montaga,Alejandra Rodriguez,OFL,SERIF,2012-01-18
+Montserrat,"Julieta Ulanovsky, Sol Matas, Juan Pablo del Peral, Jacques Le Bailly",OFL,SANS_SERIF,2011-12-13
+Montserrat Alternates,"Julieta Ulanovsky, Sol Matas, Juan Pablo del Peral, Jacques Le Bailly",OFL,SANS_SERIF,2012-10-01
+Montserrat Subrayada,Julieta Ulanovsky,OFL,SANS_SERIF,2012-10-01
+Moul,Danh Hong,OFL,DISPLAY,2011-03-02
+Moulpali,Danh Hong,OFL,DISPLAY,2011-03-02
+Mouse Memoirs,Astigmatic,OFL,SANS_SERIF,2012-11-02
+Mr Bedford,Sudtipos,OFL,HANDWRITING,2011-11-30
+Mr Bedfort,Sudtipos,OFL,HANDWRITING,2012-01-11
+Mr Dafoe,Sudtipos,OFL,HANDWRITING,2011-11-30
+Mr De Haviland,Sudtipos,OFL,HANDWRITING,2011-11-30
+Mrs Saint Delafield,Sudtipos,OFL,HANDWRITING,2012-01-11
+Mrs Sheppards,Sudtipos,OFL,HANDWRITING,2011-11-30
+Mukta,Ek Type,OFL,SANS_SERIF,2017-01-26
+Mukta Mahee,Ek Type,OFL,SANS_SERIF,2017-05-19
+Mukta Malar,Ek Type,OFL,SANS_SERIF,2017-02-13
+Mukta Vaani,Ek Type,OFL,SANS_SERIF,2016-06-15
+Muli,Vernon Adams,OFL,SANS_SERIF,2011-05-25
+MuseoModerno,Omnibus-Type,OFL,DISPLAY,2020-05-18
+Mystery Quest,Sideshow,OFL,DISPLAY,2012-02-29
+Nanum Brush Script,Sandoll Communication,OFL,HANDWRITING,2012-05-09
+Nanum Gothic,Sandoll Communication,OFL,HANDWRITING,2012-05-09
+Nanum Gothic Coding,Sandoll Communication,OFL,HANDWRITING,2012-05-09
+Nanum Myeongjo,Sandoll Communication,OFL,HANDWRITING,2012-05-09
+Nanum Pen Script,Sandoll Communication,OFL,HANDWRITING,2012-05-09
+NATS,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Neucha,Jovanny Lemonad,OFL,HANDWRITING,2010-09-21
+Neuton,Brian Zick,OFL,SERIF,2011-02-09
+New Rocker,Impallari Type,OFL,DISPLAY,2012-11-30
+News Cycle,Nathan Willis,OFL,SANS_SERIF,2011-04-27
+Niconne,Vernon Adams,OFL,HANDWRITING,2011-11-23
+Niramit,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+Nixie One,Jovanny Lemonad,OFL,DISPLAY,2011-06-21
+Nobile,Vernon Adams,OFL,SANS_SERIF,2010-05-10
+Norican,Vernon Adams,OFL,HANDWRITING,2012-02-08
+Nosifer,Typomondo,OFL,DISPLAY,2011-12-19
+Nosifer Caps,Typomondo,OFL,DISPLAY,2011-10-24
+Notable,"Eli Block, Hana Tanimura, Noemie Le Coz",OFL,SANS_SERIF,2018-08-03
+Nothing You Could Do,Kimberly Geswein,OFL,HANDWRITING,2011-05-11
+Noticia Text,JM Solé,OFL,SERIF,2012-02-08
+Noto Sans,Google,OFL,SANS_SERIF,2013-02-27
+Noto Serif,Google,OFL,SERIF,2013-02-27
+Nova Cut,Wojciech Kalinowski,OFL,DISPLAY,2011-03-23
+Nova Flat,Wojciech Kalinowski,OFL,DISPLAY,2011-03-23
+Nova Mono,Wojciech Kalinowski,OFL,MONOSPACE,2011-03-23
+Nova Oval,Wojciech Kalinowski,OFL,DISPLAY,2011-03-23
+Nova Round,Wojciech Kalinowski,OFL,DISPLAY,2011-03-23
+Nova Script,Wojciech Kalinowski,OFL,DISPLAY,2011-03-23
+Nova Slim,Wojciech Kalinowski,OFL,DISPLAY,2011-03-23
+Nova Square,Wojciech Kalinowski,OFL,DISPLAY,2011-04-14
+NTR,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Numans,Jovanny Lemonad,OFL,SANS_SERIF,2011-08-17
+Nunito,Vernon Adams,OFL,SANS_SERIF,2012-08-12
+Nunito Sans,Multiple Designers,OFL,SANS_SERIF,2016-10-06
+Odibee Sans,James Barnard,OFL,DISPLAY,2019-11-08
+Odor Mean Chey,Danh Hong,OFL,DISPLAY,2011-03-02
+Offside,Eduardo Tunni,OFL,DISPLAY,2012-10-26
+OFL Sorts Mill Goudy TT,Barry Schwartz,OFL,SERIF,2010-05-18
+Oldenburg,Nicole Fally,OFL,DISPLAY,2011-12-19
+Old Standard TT,Alexey Kryukov,OFL,SERIF,2010-05-18
+Oleo Script,soytutype fonts,OFL,DISPLAY,2012-03-29
+Oleo Script Swash Caps,soytutype fonts,OFL,DISPLAY,2012-11-12
+Oranienbaum,Multiple Designers,OFL,SERIF,2012-08-20
+Orbitron,Matt McInerney,OFL,SANS_SERIF,2010-12-15
+Oregano,Astigmatic,OFL,DISPLAY,2012-08-13
+Orienta,Eduardo Tunni,OFL,SANS_SERIF,2012-09-07
+Original Surfer,Astigmatic,OFL,DISPLAY,2011-12-07
+Oswald,"Vernon Adams, Kalapi Gajjar, Cyreal",OFL,SANS_SERIF,2012-02-29
+Overlock,Dario Manuel Muhafara,OFL,DISPLAY,2011-12-19
+Overlock SC,Dario Manuel Muhafara,OFL,DISPLAY,2011-12-19
+Overpass,Delve Withrington,OFL,SANS_SERIF,2016-12-02
+Overpass Mono,Delve Withrington,OFL,MONOSPACE,2016-12-02
+Over the Rainbow,Kimberly Geswein,OFL,HANDWRITING,2011-04-27
+Ovo,Nicole Fally,OFL,SERIF,2011-07-20
+Oxanium,Severin Meyer,OFL,DISPLAY,2020-01-30
+Oxygen,Vernon Adams,OFL,SANS_SERIF,2012-03-29
+Oxygen Mono,Vernon Adams,OFL,MONOSPACE,2012-09-08
+Pacifico,"Vernon Adams, Jacques Le Bailly, Botjo Nikoltchev, Ani Petrova",OFL,HANDWRITING,2011-03-09
+Padauk,SIL International,OFL,SANS_SERIF,2016-11-08
+Palanquin,Pria Ravichandran,OFL,SANS_SERIF,2015-01-28
+Palanquin Dark,Pria Ravichandran,OFL,SANS_SERIF,2015-01-28
+Pangolin,Kevin Burke,OFL,HANDWRITING,2017-02-12
+Paprika,Eduardo Tunni,OFL,DISPLAY,2012-10-26
+Parisienne,Astigmatic,OFL,HANDWRITING,2012-01-25
+Passero One,Viktoriya Grabowska,OFL,DISPLAY,2011-08-31
+Passion One,Fontstage,OFL,DISPLAY,2011-12-13
+Pathway Gothic One,Eduardo Tunni,OFL,SANS_SERIF,2013-06-05
+Patrick Hand,Patrick Wagesreiter,OFL,HANDWRITING,2011-07-06
+Patrick Hand SC,Patrick Wagesreiter,OFL,HANDWRITING,2013-02-27
+Pattaya,Multiple Designers,OFL,SANS_SERIF,2016-06-20
+Patua One,LatinoType,OFL,DISPLAY,2011-12-19
+Pavanam,Multiple Designers,OFL,SANS_SERIF,2016-06-20
+Paytone One,Vernon Adams,OFL,SANS_SERIF,2011-05-04
+Pecita,Phillipe Cochy,OFL,HANDWRITING,2012-05-09
+Peddana,Appaji Ambarisha Darbha,OFL,SERIF,2014-12-10
+Peralta,Astigmatic,OFL,DISPLAY,2012-07-11
+Petit Formal Script,Impallari Type,OFL,HANDWRITING,2012-09-07
+Petrona,Ringo Romei,OFL,SERIF,2011-11-02
+Phetsarath,Danh Hong,OFL,SERIF,2012-05-18
+Philosopher,Jovanny Lemonad,OFL,SANS_SERIF,2011-08-31
+Piedra,Sudtipos,OFL,DISPLAY,2011-11-30
+Pinyon Script,Nicole Fally,OFL,HANDWRITING,2011-10-12
+Pirata One,Multiple Designers,OFL,DISPLAY,2012-10-31
+Plaster,Sorkin Type,OFL,DISPLAY,2011-12-13
+Play,Jonas Hecksher,OFL,SANS_SERIF,2011-05-04
+Playball,TypeSETit,OFL,DISPLAY,2011-12-19
+Playfair Display,Claus Eggers Sørensen,OFL,SERIF,2011-11-16
+Playfair Display SC,Claus Eggers Sørensen,OFL,SERIF,2012-10-26
+Podkova,Cyreal,OFL,SERIF,2011-05-18
+Poetsen One,"Rodrigo Fuenzalida, Pablo Impallari",OFL,DISPLAY,2012-09-07
+Poiret One,Denis Masharov,OFL,DISPLAY,2012-02-29
+Poller One,Yvonne Schüttler,OFL,DISPLAY,2011-09-28
+Poly,Nicolás Silva,OFL,SERIF,2011-11-02
+Pompiere,Karolina Lach,OFL,DISPLAY,2011-07-20
+Ponnala,Appaji Ambarisha Darbha,OFL,DISPLAY,2014-12-10
+Pontano Sans,Vernon Adams,OFL,SANS_SERIF,2012-03-14
+Poor Story,Yoon Design,OFL,DISPLAY,2018-02-23
+Poppins,Indian Type Foundry,OFL,SANS_SERIF,2015-06-03
+Porter Sans Block,Tyler Finck,OFL,DISPLAY,2013-12-03
+Port Lligat Sans,Tipo,OFL,SANS_SERIF,2012-01-18
+Port Lligat Slab,Tipo,OFL,SERIF,2012-01-18
+Post No Bills Colombo,Mooniak,OFL,DISPLAY,2017-02-20
+Post No Bills Jaffna,Mooniak,OFL,DISPLAY,2017-02-20
+Pragati Narrow,Omnibus-Type,OFL,SANS_SERIF,2015-04-22
+Prata,Cyreal,OFL,SERIF,2011-09-07
+Preahvihear,Danh Hong,OFL,DISPLAY,2011-03-02
+Press Start 2P,CodeMan38,OFL,DISPLAY,2012-04-04
+Pridi,Cadson Demak,OFL,SERIF,2016-06-20
+Princess Sofia,Tart Workshop,OFL,HANDWRITING,2012-02-15
+Prociono,Barry Schwartz,OFL,SERIF,2011-08-31
+Prompt,Cadson Demak,OFL,SANS_SERIF,2016-06-20
+Prosto One,Multiple Designers,OFL,DISPLAY,2012-02-29
+Proza Libre,Jasper de Waard,OFL,SANS_SERIF,2016-06-20
+PT Mono,ParaType,OFL,MONOSPACE,2012-02-29
+PT Sans,ParaType,OFL,SANS_SERIF,2010-09-21
+PT Sans Caption,ParaType,OFL,SANS_SERIF,2010-09-21
+PT Sans Narrow,ParaType,OFL,SANS_SERIF,2010-09-21
+PT Serif,ParaType,OFL,SERIF,2011-02-09
+PT Serif Caption,ParaType,OFL,SERIF,2011-02-09
+Public Sans,Multiple Designers,OFL,SANS_SERIF,2019-06-07
+Puritan,Ben Weiner,OFL,SANS_SERIF,2010-11-30
+Purple Purse,Astigmatic,OFL,DISPLAY,2012-11-16
+Pushster,Andyj,OFL,DISPLAY,2019-04-01
+Quando,Joana Correia,OFL,SERIF,2012-07-10
+Quantico,MADType,OFL,SANS_SERIF,2011-12-19
+Quattrocento,Impallari Type,OFL,SERIF,2012-03-20
+Quattrocento Sans,Impallari Type,OFL,SANS_SERIF,2012-02-15
+Questrial,Joe Prince,OFL,SANS_SERIF,2011-08-10
+Quicksand,Andrew Paglinawan,OFL,SANS_SERIF,2011-10-19
+Quintessential,Astigmatic,OFL,HANDWRITING,2012-11-02
+Qwigley,TypeSETit,OFL,HANDWRITING,2011-12-19
+Racing Sans One,Impallari Type,OFL,DISPLAY,2012-08-13
+Radley,Vernon Adams,OFL,SERIF,2011-12-13
+Rajdhani,Indian Type Foundry,OFL,SANS_SERIF,2014-07-09
+Rakkas,Zeynep Akay,OFL,DISPLAY,2016-06-20
+Raleway,Multiple Designers,OFL,SANS_SERIF,2012-09-07
+Raleway Dots,Multiple Designers,OFL,DISPLAY,2012-09-07
+Ramabhadra,Purushoth Kumar Guttula,OFL,SANS_SERIF,2014-12-10
+Ramaraja,Appaji Ambarisha Darbha,OFL,SERIF,2015-01-08
+Rambla,Martin Sommaruga,OFL,SANS_SERIF,2012-10-31
+Rammetto One,Vernon Adams,OFL,DISPLAY,2011-11-02
+Ranchers,Impallari Type,OFL,DISPLAY,2012-09-07
+Ranga,TipTopTyp,OFL,DISPLAY,2015-01-28
+Rasa,Rosetta,OFL,SERIF,2016-06-20
+Rationale,Cyreal,OFL,SANS_SERIF,2011-08-03
+Ravi Prakash,Appaji Ambarisha Darbha,OFL,DISPLAY,2015-01-12
+Recursive,"Arrow Type, Stephen Nixon",OFL,SANS_SERIF,2020-05-01
+Redacted,Christian Naths,OFL,DISPLAY,2013-09-18
+Redacted Script,Christian Naths,OFL,HANDWRITING,2013-09-18
+Red Hat Display,MCKL,OFL,SANS_SERIF,2019-04-10
+Red Hat Text,MCKL,OFL,SANS_SERIF,2019-04-10
+Reem Kufi,"Khaled Hosny, Santiago Orozco",OFL,SANS_SERIF,2016-05-31
+Reenie Beanie,James Grieshaber,OFL,HANDWRITING,2010-05-10
+Revalia,Multiple Designers,OFL,DISPLAY,2012-03-14
+Rhodium Libre,James Puckett,OFL,SERIF,2015-06-03
+Ribeye,Astigmatic,OFL,DISPLAY,2011-11-23
+Ribeye Marrow,Astigmatic,OFL,DISPLAY,2011-11-23
+Righteous,Astigmatic,OFL,DISPLAY,2011-11-23
+Risque,Astigmatic,OFL,DISPLAY,2012-11-11
+Roboto,"Christian Robertson, Paratype, Font Bureau",OFL,SANS_SERIF,2013-01-09
+Rokkitt,Vernon Adams,OFL,SERIF,2011-07-27
+Romanesco,Astigmatic,OFL,HANDWRITING,2012-08-13
+Ropa Sans,Botjo Nikoltchev,OFL,SANS_SERIF,2012-01-25
+Rosario,Omnibus-Type,OFL,SANS_SERIF,2011-09-07
+Rosarivo,Pablo Ugerman,OFL,SERIF,2012-03-29
+Rouge Script,Sabrina Mariela Lopez,OFL,HANDWRITING,2012-01-11
+Rowdies,Jaikishan Patel,OFL,DISPLAY,2019-10-10
+Rozha One,Indian Type Foundry,OFL,SERIF,2014-08-13
+Rubik,"Hubert and Fischer, Meir Sadan, Cyreal",OFL,SANS_SERIF,2015-07-22
+Rubik Mono One,Hubert and Fischer,OFL,SANS_SERIF,2014-05-05
+Rubik One,Hubert and Fischer,OFL,SANS_SERIF,2014-05-05
+Ruda,Multiple Designers,OFL,SANS_SERIF,2012-01-11
+Rufina,Martin Sommaruga,OFL,SERIF,2012-10-31
+Ruge Boogie,TypeSETit,OFL,HANDWRITING,2011-12-19
+Ruluko,Multiple Designers,OFL,SANS_SERIF,2012-01-11
+Rum Raisin,Astigmatic,OFL,SANS_SERIF,2012-11-02
+Ruslan Display,Denis Masharov,OFL,DISPLAY,2011-05-18
+Russo One,Jovanny Lemonad,OFL,SANS_SERIF,2012-04-04
+Ruthie,TypeSETit,OFL,HANDWRITING,2011-12-19
+Rye,Nicole Fally,OFL,DISPLAY,2012-08-21
+Sacramento,Astigmatic,OFL,HANDWRITING,2012-11-01
+Sahitya,Juan Pablo del Peral,OFL,SERIF,2015-06-17
+Sail,Miguel Hernandez,OFL,DISPLAY,2011-12-19
+Saira,Omnibus-Type,OFL,SANS_SERIF,2016-12-03
+Saira Condensed,Omnibus-Type,OFL,SANS_SERIF,2016-12-03
+Saira Extra Condensed,Omnibus-Type,OFL,SANS_SERIF,2016-12-03
+Saira Semi Condensed,Omnibus-Type,OFL,SANS_SERIF,2016-12-03
+Saira Stencil One,"Hector Gatti, Omnibus-Type",OFL,DISPLAY,2019-06-19
+Salsa,John Vargas Beltrán,OFL,DISPLAY,2011-10-12
+Sanchez,Daniel Hernandez,OFL,SERIF,2012-10-31
+Sancreek,Vernon Adams,OFL,DISPLAY,2011-10-12
+Sansation,Bernd Montag,OFL,SANS_SERIF,2012-10-18
+Sansita,Omnibus-Type,OFL,SANS_SERIF,2016-12-04
+Sansita One,Omnibus-Type,OFL,DISPLAY,2011-09-28
+Sarabun,Suppakit Chalermlarp,OFL,SANS_SERIF,2013-10-28
+Sarala,Andres Torresi,OFL,SANS_SERIF,2015-06-17
+Sarina,James Grieshaber,OFL,DISPLAY,2011-12-19
+Sarpanch,Indian Type Foundry,OFL,SANS_SERIF,2014-09-03
+Scada,Jovanny Lemonad,OFL,SANS_SERIF,2012-07-30
+Scheherazade,SIL International,OFL,SERIF,2012-01-18
+Scope One,Dalton Maag,OFL,SERIF,2016-06-20
+Seaweed Script,Neapolitan,OFL,DISPLAY,2012-02-29
+Secular One,Michal Sahar,OFL,SANS_SERIF,2016-06-20
+Sedan,Sebastian Salazar,OFL,SERIF,2012-10-31
+Sedan SC,Sebastian Salazar,OFL,SERIF,2012-10-31
+Sedgwick Ave,Multiple Designers,OFL,HANDWRITING,2017-08-01
+Sedgwick Ave Display,Multiple Designers,OFL,HANDWRITING,2017-08-01
+Sen,Kosal Sen,OFL,SANS_SERIF,2020-01-17
+Sevillana,Brownfox,OFL,DISPLAY,2012-02-22
+Seymour One,Vernon Adams,OFL,SANS_SERIF,2012-10-10
+Shadows Into Light,Kimberly Geswein,OFL,HANDWRITING,2011-06-08
+Shadows Into Light Two,Kimberly Geswein,OFL,HANDWRITING,2012-02-22
+Shanti,Vernon Adams,OFL,SANS_SERIF,2011-05-11
+Share,Carrois Apostrophe,OFL,DISPLAY,2012-02-08
+Share Tech,Carrois Apostrophe,OFL,SANS_SERIF,2012-10-31
+Share Tech Mono,Carrois Apostrophe,OFL,MONOSPACE,2012-10-31
+Shojumaru,Astigmatic,OFL,DISPLAY,2012-01-25
+Short Stack,James Grieshaber,OFL,HANDWRITING,2011-08-17
+Shrikhand,Jonny Pinhorn,OFL,DISPLAY,2016-06-20
+Siamreap,Danh Hong,OFL,DISPLAY,2011-03-02
+Siemreap,Danh Hong,OFL,DISPLAY,2011-04-20
+Sigmar One,Vernon Adams,OFL,DISPLAY,2011-05-04
+Signika,Anna Giedryś,OFL,SANS_SERIF,2011-11-23
+Signika Negative,Anna Giedryś,OFL,SANS_SERIF,2011-11-23
+Simonetta,Brownfox,OFL,DISPLAY,2012-04-04
+Single Day,DXKorea Inc,OFL,DISPLAY,2018-02-23
+Sintony,Eduardo Rodriguez Tunni,OFL,SANS_SERIF,2013-02-27
+Sirin Stencil,Cyreal,OFL,DISPLAY,2012-01-18
+Sitara,Neelakash Kshetrimayum,OFL,SERIF,2015-06-10
+Six Caps,Vernon Adams,OFL,SANS_SERIF,2011-02-16
+Skranji,Neapolitan,OFL,DISPLAY,2012-08-21
+Slabo 13px,John Hudson,OFL,SERIF,2014-05-30
+Slabo 27px,John Hudson,OFL,SERIF,2014-05-30
+Smythe,Vernon Adams,OFL,DISPLAY,2011-04-20
+Sniglet,Multiple Designers,OFL,DISPLAY,2010-12-15
+Snippet,Gesine Todt,OFL,SANS_SERIF,2011-07-20
+Snowburst One,Annet Stirling,OFL,DISPLAY,2012-11-26
+Sofadi One,Botjo Nikoltchev,OFL,DISPLAY,2012-09-30
+Sofia,LatinoType,OFL,HANDWRITING,2011-12-19
+Solway,"Mariya V. Pigoulevskaya, The Northern Block",OFL,SERIF,2018-08-06
+Sometype Mono,Ryoichi Tsunekawa,OFL,MONOSPACE,2019-09-26
+Song Myung,JIKJI,OFL,SERIF,2018-02-23
+Sonsie One,Riccardo De Franceschi,OFL,DISPLAY,2012-01-18
+Sorts Mill Goudy,Barry Schwartz,OFL,SERIF,2011-09-07
+Source Code Pro,Paul D. Hunt,OFL,MONOSPACE,2012-09-20
+Source Sans Pro,Paul D. Hunt,OFL,SANS_SERIF,2012-07-31
+Source Serif Pro,Frank Grießhammer,OFL,SERIF,2014-05-30
+Space Mono,Colophon,OFL,MONOSPACE,2016-06-20
+Spartan,"Matt Bailey, Mirko Velimirovic",OFL,SANS_SERIF,2020-01-30
+Spectral,Production Type,OFL,SERIF,2017-10-10
+Spectral SC,Production Type,OFL,SERIF,2017-10-10
+Spicy Rice,Astigmatic,OFL,DISPLAY,2011-12-13
+Spinnaker,Elena Albertoni,OFL,SANS_SERIF,2011-09-28
+Spirax,Brenda Gallo,OFL,DISPLAY,2011-11-23
+Squada One,Joe Prince,OFL,DISPLAY,2011-12-15
+Sree Krushnadevaraya,Purushoth Kumar Guttula,OFL,SERIF,2015-01-12
+Sriracha,Cadson Demak,OFL,HANDWRITING,2015-07-01
+Srisakdi,Cadson Demak,OFL,DISPLAY,2018-08-22
+Staatliches,"Brian LaRossa, Erica Carras",OFL,DISPLAY,2018-12-10
+Stalemate,Astigmatic,OFL,HANDWRITING,2012-11-03
+Stalinist One,Multiple Designers,OFL,DISPLAY,2012-08-20
+Stalin One,Multiple Designers,OFL,DISPLAY,2012-08-20
+Stardos Stencil,Vernon Adams,OFL,DISPLAY,2011-07-06
+Stint Ultra Condensed,Astigmatic,OFL,DISPLAY,2011-12-07
+Stint Ultra Expanded,Astigmatic,OFL,DISPLAY,2012-02-15
+Stoke,Nicole Fally,OFL,SERIF,2012-08-03
+Strait,Eduardo Tunni,OFL,SANS_SERIF,2012-10-26
+Strong,Gaslight,OFL,SANS_SERIF,2012-05-09
+Stylish,AsiaSoft Inc,OFL,SANS_SERIF,2018-02-27
+Sue Ellen Francisco,Kimberly Geswein,OFL,HANDWRITING,2011-04-14
+Suez One,Michal Sahar,OFL,SERIF,2016-06-20
+Sulphur Point,Dale Sattler,OFL,SANS_SERIF,2019-09-25
+Sumana,Cyreal,OFL,SERIF,2015-04-29
+Sunflower,JIKJISOFT,OFL,SANS_SERIF,2018-02-27
+Supermercado One,James Grieshaber,OFL,DISPLAY,2011-11-02
+Sura,Carolina Giovagnoli,OFL,SERIF,2015-06-17
+Suranna,Purushoth Kumar Guttula,OFL,SERIF,2015-01-12
+Suravaram,Purushoth Kumar Guttula,OFL,SERIF,2015-01-12
+Suwannaphum,Danh Hong,OFL,DISPLAY,2011-03-02
+Swanky and Moo Moo,Kimberly Geswein,OFL,HANDWRITING,2011-04-27
+Tajawal,Boutros Fonts,OFL,SANS_SERIF,2018-04-04
+Tangerine,Toshi Omagari,OFL,HANDWRITING,2010-06-08
+Taprom,Danh Hong,OFL,DISPLAY,2011-03-02
+Tauri,Yvonne Schüttler,OFL,SANS_SERIF,2013-02-27
+Taviraj,Cadson Demak,OFL,SERIF,2016-06-20
+Teko,Indian Type Foundry,OFL,SANS_SERIF,2014-06-25
+Telex,Huerta Tipográfica,OFL,SANS_SERIF,2012-01-18
+Tenali Ramakrishna,Appaji Ambarisha Darbha,OFL,SANS_SERIF,2014-12-10
+Tenor Sans,Denis Masharov,OFL,SANS_SERIF,2011-05-25
+Terminal Dosis,Impallari Type,OFL,SANS_SERIF,2011-09-28
+Terminal Dosis Light,multiple designers,OFL,SANS_SERIF,2011-03-30
+Text Me One,Julia Petretta,OFL,SANS_SERIF,2012-10-31
+Thabit,Khaled Hosny,OFL,SERIF,2010-09-21
+Thasadith,Cadson Demak,OFL,SANS_SERIF,2018-08-22
+The Girl Next Door,Kimberly Geswein,OFL,HANDWRITING,2011-04-20
+Tienne,Vernon Adams,OFL,SERIF,2011-07-27
+Tillana,Indian Type Foundry,OFL,HANDWRITING,2015-06-03
+Timmana,Appaji Ambarisha Darbha,OFL,SANS_SERIF,2015-01-12
+Titan One,Rodrigo Fuenzalida,OFL,DISPLAY,2012-01-11
+Titillium Web,Multiple Designers,OFL,SANS_SERIF,2012-10-01
+Tomorrow,"Tony de Marco, Monica Rizzolli",OFL,SANS_SERIF,2019-10-02
+Trade Winds,Sideshow,OFL,DISPLAY,2011-12-19
+Trirong,Cadson Demak,OFL,SERIF,2016-06-20
+Trocchi,Vernon Adams,OFL,SERIF,2012-04-04
+Trochut,Andreu Balius,OFL,DISPLAY,2012-01-18
+Trykker,Magnus Gaarde,OFL,SERIF,2011-12-19
+Tuffy,Thatcher Ulrich,OFL,SANS_SERIF,2012-05-09
+Tulpen One,Naima Ben Ayed,OFL,DISPLAY,2011-08-03
+Turret Road,Dale Sattler,OFL,DISPLAY,2019-09-03
+Uchen,Christopher J. Fynn,OFL,SERIF,2019-12-07
+Uncial Antiqua,Astigmatic,OFL,DISPLAY,2011-12-19
+Underdog,Multiple Designers,OFL,DISPLAY,2012-09-23
+Unica One,Eduardo Tunni,OFL,DISPLAY,2012-10-26
+UnifrakturCook,j. 'mach' wust,OFL,DISPLAY,2010-12-07
+UnifrakturMaguntia,j. 'mach' wust,OFL,DISPLAY,2010-11-30
+Unlock,Eduardo Tunni,OFL,DISPLAY,2011-11-30
+Unna,Omnibus-Type,OFL,SERIF,2011-07-20
+Vampiro One,Riccardo De Franceschi,OFL,DISPLAY,2012-11-26
+Varela,Joe Prince,OFL,SANS_SERIF,2011-06-29
+Varela Round,Joe Prince,OFL,SANS_SERIF,2011-07-13
+Varta,Sorkin Type Co,OFL,SANS_SERIF,2015-05-13
+Vast Shadow,Nicole Fally,OFL,DISPLAY,2011-10-12
+Vesper Libre,Mota Italic,OFL,SERIF,2014-07-14
+Viaoda Libre,"Gydient, Vietanh Nguyen",OFL,DISPLAY,2019-11-05
+Vibes,AbdElmomen Kadhim (blueMix),OFL,DISPLAY,2019-04-23
+Vibur,Johan Kallas,OFL,HANDWRITING,2010-12-15
+Vidaloka,Cyreal,OFL,SERIF,2011-08-17
+Viga,Fontstage,OFL,SANS_SERIF,2011-12-07
+Voces,Multiple Designers,OFL,DISPLAY,2012-02-22
+Volkhov,Cyreal,OFL,SERIF,2011-08-17
+Vollkorn,Friedrich Althausen,OFL,SERIF,2010-09-08
+Vollkorn SC,Friedrich Althausen,OFL,SERIF,2017-09-08
+Voltaire,Yvonne Schüttler,OFL,SANS_SERIF,2011-08-17
+VT323,Peter Hull,OFL,MONOSPACE,2011-03-02
+Waiting for the Sunrise,Kimberly Geswein,OFL,HANDWRITING,2011-04-14
+Wallpoet,Lars Berggren,OFL,DISPLAY,2011-04-27
+Warnes,Eduardo Tunni,OFL,DISPLAY,2012-09-07
+Wellfleet,Riccardo De Franceschi,OFL,DISPLAY,2012-01-11
+Wendy One,Alejandro Inler,OFL,SANS_SERIF,2012-12-05
+Wire One,Cyreal,OFL,SANS_SERIF,2011-05-18
+Work Sans,Wei Huang,OFL,SANS_SERIF,2015-07-08
+Yaldevi Colombo,Mooniak,OFL,SANS_SERIF,2017-02-20
+Yanone Kaffeesatz,"Yanone, Cyreal",OFL,SANS_SERIF,2010-05-11
+Yantramanav,Erin McLaughlin,OFL,SANS_SERIF,2015-06-03
+Yatra One,Catherine Leigh Schmidt,OFL,DISPLAY,2016-06-20
+Yeon Sung,Woowahan brothers,OFL,DISPLAY,2018-02-23
+Yeseva One,Jovanny Lemonad,OFL,DISPLAY,2011-07-13
+Yesteryear,Astigmatic,OFL,HANDWRITING,2011-12-19
+Yinmar,Danh Hong,OFL,DISPLAY,2016-02-03
+Yrsa,Rosetta,OFL,SERIF,2016-06-20
+ZCOOL KuaiLe,"Liu Bingke, Yang Kang, Wu Shaojie",OFL,SANS_SERIF,2018-12-05
+ZCOOL QingKe HuangYou,Zheng Qingke,OFL,SANS_SERIF,2018-12-05
+ZCOOL XiaoWei,Li Dawei,OFL,SANS_SERIF,2018-12-05
+Zeyada,Kimberly Geswein,OFL,HANDWRITING,2011-06-08
+Zhi Mang Xing,Wei Zhimang,OFL,HANDWRITING,2019-03-18
+Zilla Slab,Typotheque,OFL,SERIF,2017-06-28
+Zilla Slab Highlight,Typotheque,OFL,DISPLAY,2017-07-26
diff --git a/inst/extdata/google_styles_tbl.csv b/inst/extdata/google_styles_tbl.csv
new file mode 100644
index 000000000..b381bd714
--- /dev/null
+++ b/inst/extdata/google_styles_tbl.csv
@@ -0,0 +1,2683 @@
+name,style,weight,filename,post_script_name,full_name,copyright
+ABeeZee,normal,400,ABeeZee-Regular.ttf,ABeeZee-Regular,ABeeZee Regular,"Copyright (c) 2011 by Anja Meiners, with Reserved Font Name \'ABeeZee\'"
+ABeeZee,italic,400,ABeeZee-Italic.ttf,ABeeZee-Italic,ABeeZee Italic,"Copyright (c) 2011 by Anja Meiners, with Reserved Font Name \'ABeeZee\'"
+Abel,normal,400,Abel-Regular.ttf,Abel-Regular,Abel Regular,"Copyright (c) 2011, Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name Abel."
+Abhaya Libre,normal,400,AbhayaLibre-Regular.ttf,AbhayaLibre-Regular,Abhaya Libre Regular,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Abhaya Libre,normal,500,AbhayaLibre-Medium.ttf,AbhayaLibre-Medium,Abhaya Libre Medium,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Abhaya Libre,normal,600,AbhayaLibre-SemiBold.ttf,AbhayaLibre-SemiBold,Abhaya Libre SemiBold,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Abhaya Libre,normal,700,AbhayaLibre-Bold.ttf,AbhayaLibre-Bold,Abhaya Libre Bold,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Abhaya Libre,normal,800,AbhayaLibre-ExtraBold.ttf,AbhayaLibre-ExtraBold,Abhaya Libre ExtraBold,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Abril Fatface,normal,400,AbrilFatface-Regular.ttf,AbrilFatface-Regular,Abril Fatface,"Copyright (c) 2011, Copyright (c) 2011, TypeTogether (www.type-together.com info@type-together.com), with Reserved Font Names \Abril\ and \Abril Fatface\"
+Abyssinica SIL,normal,400,AbyssinicaSIL-Regular.ttf,AbyssinicaSIL,Abyssinica SIL Regular,Copyright (c) 2000-2013 by SIL International. All rights reserved.
+Acme,normal,400,Acme-Regular.ttf,Acme-Regular,Acme Regular,"Copyright (c) 2011 by Juan Pablo del Peral (info@huertatipografica.com.ar), with Reserved Font Name \Acme\"
+Actor,normal,400,Actor-Regular.ttf,Actor-Regular,Actor Regular,"Copyright (c) 2011, Thomas Junold <hallo@buerofueraufmerksamkeit.de>, with Reserved Font Name \Actor\."
+Adamina,normal,400,Adamina-Regular.ttf,Adamina-Regular,Adamina Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name \'Adamina\'"
+Adobe Blank,normal,400,AdobeBlank-Regular.ttf,AdobeBlank-Regular,Adobe Blank,"Copyright  2013, 2015 Adobe Systems Incorporated (http://www.adobe.com/)."
+Advent Pro,normal,100,AdventPro-Thin.ttf,AdventPro-Thin,Advent Pro Thin,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Advent Pro,normal,200,AdventPro-ExtraLight.ttf,AdventPro-ExtraLight,Advent Pro ExtraLight,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Advent Pro,normal,300,AdventPro-Light.ttf,AdventPro-Light,Advent Pro Light,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Advent Pro,normal,400,AdventPro-Regular.ttf,AdventPro-Regular,Advent Pro Regular,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Advent Pro,normal,500,AdventPro-Medium.ttf,AdventPro-Medium,Advent Pro Medium,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Advent Pro,normal,600,AdventPro-SemiBold.ttf,AdventPro-SemiBold,Advent Pro SemiBold,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Advent Pro,normal,700,AdventPro-Bold.ttf,AdventPro-Bold,Advent Pro Bold,"Copyright (c) 2008 Andreas Kalpakidis (hello@inderesting.com), with Reserved Font Name \Advent Pro\"
+Aguafina Script,normal,400,AguafinaScript-Regular.ttf,AguafinaScript-Regular,Aguafina Script Regular,"Copyright (c) 2007 Angel Koziupa (sudtipos@sudtipos.com), Copyright (c) 2007 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Aguafina Script\"
+Akronim,normal,400,Akronim-Regular.ttf,Akronim-Regular,Akronim Regular,"Copyright (c) 2012 Grzegorz Klimczewski, Fonty.PL (www.fonty.pl), with Reserved Font Name \'Akronim\'"
+Aladin,normal,400,Aladin-Regular.ttf,Aladin-Regular,Aladin Regular,"Copyright (c) 2009 Angel Koziupa (sudtipos@sudtipos.com), Copyright (c) 2009 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Aladin\"
+Alata,normal,400,Alata-Regular.ttf,Alata-Regular,Alata Regular,Copyright 2019 The Alata Project Authors (https://github.com/SorkinType/Alata)
+Alatsi,normal,400,Alatsi-Regular.ttf,Alatsi-Regular,Alatsi Regular,Copyright 2019 The Alatsi Project Authors (https://github.com/SorkinType/Alatsi)
+Aldrich,normal,400,Aldrich-Regular.ttf,Aldrich-Regular,Aldrich Regular,"Copyright (c) Matthew Desmond, 2011. All rights reserved."
+Alef,normal,400,Alef-Regular.ttf,Alef-Regular,Alef Regular,Copyright (c) 2012 by Hagilda. All rights reserved.
+Alef,normal,700,Alef-Bold.ttf,Alef-Bold,Alef Bold,Copyright (c) 2012 by Hagilda. All rights reserved.
+Alegreya,normal,400,Alegreya-Regular.ttf,Alegreya-Regular,Alegreya Regular,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,italic,400,Alegreya-Italic.ttf,Alegreya-Italic,Alegreya Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,normal,500,Alegreya-Medium.ttf,Alegreya-Medium,Alegreya Medium,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,italic,500,Alegreya-MediumItalic.ttf,Alegreya-MediumItalic,Alegreya Medium Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,normal,700,Alegreya-Bold.ttf,Alegreya-Bold,Alegreya Bold,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,italic,700,Alegreya-BoldItalic.ttf,Alegreya-BoldItalic,Alegreya Bold Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,normal,800,Alegreya-ExtraBold.ttf,Alegreya-ExtraBold,Alegreya ExtraBold,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,italic,800,Alegreya-ExtraBoldItalic.ttf,Alegreya-ExtraBoldItalic,Alegreya ExtraBold Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,normal,900,Alegreya-Black.ttf,Alegreya-Black,Alegreya Black,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya,italic,900,Alegreya-BlackItalic.ttf,Alegreya-BlackItalic,Alegreya Black Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya Sans,normal,100,AlegreyaSans-Thin.ttf,AlegreyaSans-Thin,Alegreya Sans Thin,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,100,AlegreyaSans-ThinItalic.ttf,AlegreyaSans-ThinItalic,Alegreya Sans Thin Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,normal,300,AlegreyaSans-Light.ttf,AlegreyaSans-Light,Alegreya Sans Light,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,300,AlegreyaSans-LightItalic.ttf,AlegreyaSans-LightItalic,Alegreya Sans Light Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,normal,400,AlegreyaSans-Regular.ttf,AlegreyaSans-Regular,Alegreya Sans Regular,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,400,AlegreyaSans-Italic.ttf,AlegreyaSans-Italic,Alegreya Sans Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,normal,500,AlegreyaSans-Medium.ttf,AlegreyaSans-Medium,Alegreya Sans Medium,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,500,AlegreyaSans-MediumItalic.ttf,AlegreyaSans-MediumItalic,Alegreya Sans Medium Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,normal,700,AlegreyaSans-Bold.ttf,AlegreyaSans-Bold,Alegreya Sans Bold,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,700,AlegreyaSans-BoldItalic.ttf,AlegreyaSans-BoldItalic,Alegreya Sans Bold Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,normal,800,AlegreyaSans-ExtraBold.ttf,AlegreyaSans-ExtraBold,Alegreya Sans ExtraBold,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,800,AlegreyaSans-ExtraBoldItalic.ttf,AlegreyaSans-ExtraBoldItalic,Alegreya Sans ExtraBold Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,normal,900,AlegreyaSans-Black.ttf,AlegreyaSans-Black,Alegreya Sans Black,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans,italic,900,AlegreyaSans-BlackItalic.ttf,AlegreyaSans-BlackItalic,Alegreya Sans Black Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,100,AlegreyaSansSC-Thin.ttf,AlegreyaSansSC-Thin,Alegreya Sans SC Thin,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,100,AlegreyaSansSC-ThinItalic.ttf,AlegreyaSansSC-ThinItalic,Alegreya Sans SC Thin Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,300,AlegreyaSansSC-Light.ttf,AlegreyaSansSC-Light,Alegreya Sans SC Light,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,300,AlegreyaSansSC-LightItalic.ttf,AlegreyaSansSC-LightItalic,Alegreya Sans SC Light Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,400,AlegreyaSansSC-Regular.ttf,AlegreyaSansSC-Regular,Alegreya Sans SC Regular,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,400,AlegreyaSansSC-Italic.ttf,AlegreyaSansSC-Italic,Alegreya Sans SC Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,500,AlegreyaSansSC-Medium.ttf,AlegreyaSansSC-Medium,Alegreya Sans SC Medium,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,500,AlegreyaSansSC-MediumItalic.ttf,AlegreyaSansSC-MediumItalic,Alegreya Sans SC Medium Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,700,AlegreyaSansSC-Bold.ttf,AlegreyaSansSC-Bold,Alegreya Sans SC Bold,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,700,AlegreyaSansSC-BoldItalic.ttf,AlegreyaSansSC-BoldItalic,Alegreya Sans SC Bold Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,800,AlegreyaSansSC-ExtraBold.ttf,AlegreyaSansSC-ExtraBold,Alegreya Sans SC ExtraBold,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,800,AlegreyaSansSC-ExtraBoldItalic.ttf,AlegreyaSansSC-ExtraBoldItalic,Alegreya Sans SC ExtraBold Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,normal,900,AlegreyaSansSC-Black.ttf,AlegreyaSansSC-Black,Alegreya Sans SC Black,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya Sans SC,italic,900,AlegreyaSansSC-BlackItalic.ttf,AlegreyaSansSC-BlackItalic,Alegreya Sans SC Black Italic,Copyright 2013 The Alegreya Sans Project Authors (https://github.com/huertatipografica/Alegreya-Sans)
+Alegreya SC,normal,400,AlegreyaSC-Regular.ttf,AlegreyaSC-Regular,Alegreya SC Regular,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,italic,400,AlegreyaSC-Italic.ttf,AlegreyaSC-Italic,Alegreya SC Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,normal,500,AlegreyaSC-Medium.ttf,AlegreyaSC-Medium,Alegreya SC Medium,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,italic,500,AlegreyaSC-MediumItalic.ttf,AlegreyaSC-MediumItalic,Alegreya SC Medium Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,normal,700,AlegreyaSC-Bold.ttf,AlegreyaSC-Bold,Alegreya SC Bold,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,italic,700,AlegreyaSC-BoldItalic.ttf,AlegreyaSC-BoldItalic,Alegreya SC Bold Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,normal,800,AlegreyaSC-ExtraBold.ttf,AlegreyaSC-ExtraBold,Alegreya SC ExtraBold,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,italic,800,AlegreyaSC-ExtraBoldItalic.ttf,AlegreyaSC-ExtraBoldItalic,Alegreya SC ExtraBold Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,normal,900,AlegreyaSC-Black.ttf,AlegreyaSC-Black,Alegreya SC Black,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Alegreya SC,italic,900,AlegreyaSC-BlackItalic.ttf,AlegreyaSC-BlackItalic,Alegreya SC Black Italic,Copyright 2011 The Alegreya Project Authors (https://github.com/huertatipografica/Alegreya)
+Aleo,normal,300,Aleo-Light.ttf,Aleo-Light,Aleo Light,Copyright 2018 The Aleo Project Authors (https://github.com/AlessioLaiso/aleo)
+Aleo,italic,300,Aleo-LightItalic.ttf,Aleo-LightItalic,Aleo Light Italic,Copyright 2018 The Aleo Project Authors (https://github.com/AlessioLaiso/aleo)
+Aleo,normal,400,Aleo-Regular.ttf,Aleo-Regular,Aleo Regular,Copyright 2018 The Aleo Project Authors (https://github.com/AlessioLaiso/aleo)
+Aleo,italic,400,Aleo-Italic.ttf,Aleo-Italic,Aleo Italic,Copyright 2018 The Aleo Project Authors (https://github.com/AlessioLaiso/aleo)
+Aleo,normal,700,Aleo-Bold.ttf,Aleo-Bold,Aleo Bold,Copyright 2018 The Aleo Project Authors (https://github.com/AlessioLaiso/aleo)
+Aleo,italic,700,Aleo-BoldItalic.ttf,Aleo-BoldItalic,Aleo Bold Italic,Copyright 2018 The Aleo Project Authors (https://github.com/AlessioLaiso/aleo)
+Alex Brush,normal,400,AlexBrush-Regular.ttf,AlexBrush-Regular,Alex Brush Regular,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Alex Brush\"
+Alfa Slab One,normal,400,AlfaSlabOne-Regular.ttf,AlfaSlabOne-Regular,Alfa Slab One Regular,"Copyright 2016 The Alfa Slab One Project Authors (http://www.jmsole.cl | info@jmsole.cl), with Reserved Font Name \Alfa Slab\."
+Alice,normal,400,Alice-Regular.ttf,Alice-Regular,Alice Regular,Copyright 2011 The Alice Project Authors (contact@cyreal.org) with Reserved Font Name \Alice\
+Alike,normal,400,Alike-Regular.ttf,Alike-Regular,Alike Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name \'Alike\'."
+Alike Angular,normal,400,AlikeAngular-Regular.ttf,AlikeAngular-Regular,Alike Angular Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name \Alike\ and \Alike Angular\."
+Allan,normal,400,Allan-Regular.ttf,Allan-Regular,Allan Regular,"Copyright (c) 2010-2012, Anton Koovit (anton@fatype.com), with Reserved Font Name \'Allan\'"
+Allan,normal,700,Allan-Bold.ttf,Allan-Bold,Allan Bold,"Copyright (c) 2010-2012, Anton Koovit (anton@fatype.com), with Reserved Font Name \'Allan\'"
+Allerta,normal,400,Allerta-Regular.ttf,Allerta-Regular,Allerta Regular,"Copyright (c) 2009, Matt McInerney <matt@pixelspread.com>"
+Allerta Stencil,normal,400,AllertaStencil-Regular.ttf,AllertaStencil-Regular,Allerta Stencil Regular,"Copyright (c) 2009, Matt McInerney <matt@pixelspread.com> with Reserved Font Name Allerta."
+Allura,normal,400,Allura-Regular.ttf,Allura-Regular,Allura Regular,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Allura\"
+Almarai,normal,300,Almarai-Light.ttf,Almarai-Light,Almarai Light,Copyright (c) 2019 by Almarai. All rights reserved.
+Almarai,normal,400,Almarai-Regular.ttf,Almarai-Regular,Almarai,Copyright (c) 2019 by Almarai. All rights reserved.
+Almarai,normal,700,Almarai-Bold.ttf,Almarai-Bold,Almarai Bold,Copyright (c) 2019 by Almarai. All rights reserved.
+Almarai,normal,800,Almarai-ExtraBold.ttf,Almarai-ExtraBold,Almarai ExtraBold,Copyright (c) 2019 by Almarai. All rights reserved.
+Almendra,normal,400,Almendra-Regular.ttf,Almendra-Regular,Almendra Regular,"Copyright (c) 2011-2012, Ana Sanfelippo (anasanfe@gmail.com), with Reserved Font Name \'Almendra\'"
+Almendra,italic,400,Almendra-Italic.ttf,Almendra-Italic,Almendra Italic,"Copyright (c) 2011-2012, Ana Sanfelippo (anasanfe@gmail.com), with Reserved Font Name \'Almendra\'"
+Almendra,normal,700,Almendra-Bold.ttf,Almendra-Bold,Almendra Bold,"Copyright (c) 2011-2012, Ana Sanfelippo (anasanfe@gmail.com), with Reserved Font Name \'Almendra\'"
+Almendra,italic,700,Almendra-BoldItalic.ttf,Almendra-BoldItalic,Almendra Bold Italic,"Copyright (c) 2011-2012, Ana Sanfelippo (anasanfe@gmail.com), with Reserved Font Name \'Almendra\'"
+Almendra Display,normal,400,AlmendraDisplay-Regular.ttf,AlmendraDisplay-Regular,Almendra Display Regular,"Copyright (c) 2011-2012, Ana Sanfelippo (anasanfe@gmail.com), with Reserved Font Name \'Almendra\'"
+Almendra SC,normal,400,AlmendraSC-Regular.ttf,AlmendraSC-Regular,Almendra SC Regular,Copyright (c) 2011 by Ana Sanfelippo (anasanfe@gmail.com). Reserved Font Names \Almendra\ \Almendra SC\
+Amarante,normal,400,Amarante-Regular.ttf,Amarante-Regular,Amarante Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Amarante\."
+Amaranth,normal,400,Amaranth-Regular.ttf,Amaranth-Regular,Amaranth Regular,Copyright 2016 The Amaranth Project Authors (https://github.com/googlefonts/amaranth)
+Amaranth,italic,400,Amaranth-Italic.ttf,Amaranth-Italic,Amaranth Italic,Copyright 2016 The Amaranth Project Authors (https://github.com/googlefonts/amaranth)
+Amaranth,normal,700,Amaranth-Bold.ttf,Amaranth-Bold,Amaranth Bold,Copyright 2016 The Amaranth Project Authors (https://github.com/googlefonts/amaranth)
+Amaranth,italic,700,Amaranth-BoldItalic.ttf,Amaranth-BoldItalic,Amaranth Bold Italic,Copyright 2016 The Amaranth Project Authors (https://github.com/googlefonts/amaranth)
+Amatica SC,normal,400,AmaticaSC-Regular.ttf,AmaticaSC-Regular,Amatica SC Regular,Copyright 2011 The Amatic Project Authors.
+Amatica SC,normal,700,AmaticaSC-Bold.ttf,AmaticaSC-Bold,Amatica SC Bold,Copyright 2011 The Amatic Project Authors.
+Amatic SC,normal,400,AmaticSC-Regular.ttf,AmaticSC-Regular,Amatic SC Regular,Copyright 2015 The Amatic SC Project Authors (https://github.com/googlefonts/AmaticSC)
+Amatic SC,normal,700,AmaticSC-Bold.ttf,AmaticSC-Bold,Amatic SC Bold,Copyright 2015 The Amatic SC Project Authors (https://github.com/googlefonts/AmaticSC)
+Amethysta,normal,400,Amethysta-Regular.ttf,Amethysta-Regular,Amethysta Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name \Amethysta\.  This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Amiko,normal,400,Amiko-Regular.ttf,Amiko-Regular,Amiko Regular,"Copyright (c) 2014, Impallari Type (www.impallari.com)."
+Amiko,normal,600,Amiko-SemiBold.ttf,Amiko-SemiBold,Amiko SemiBold,"Copyright (c) 2014, Impallari Type (www.impallari.com)."
+Amiko,normal,700,Amiko-Bold.ttf,Amiko-Bold,Amiko Bold,"Copyright (c) 2014, Impallari Type (www.impallari.com)."
+Amiri,normal,400,Amiri-Regular.ttf,Amiri-Regular,Amiri Regular,"Copyright (c) 2010-2016, Khaled Hosny <khaledhosny@eglug.org>. Portions copyright (c) 2010, Sebastian Kosch <sebastian@aldusleaf.org>."
+Amiri,italic,400,Amiri-Italic.ttf,Amiri-Italic,Amiri Italic,"Copyright (c) 2010-2016, Khaled Hosny <khaledhosny@eglug.org>. Portions copyright (c) 2010, Sebastian Kosch <sebastian@aldusleaf.org>."
+Amiri,normal,700,Amiri-Bold.ttf,Amiri-Bold,Amiri Bold,"Copyright (c) 2010-2016, Khaled Hosny <khaledhosny@eglug.org>. Portions copyright (c) 2010, Sebastian Kosch <sebastian@aldusleaf.org>."
+Amiri,italic,700,Amiri-BoldItalic.ttf,Amiri-BoldItalic,Amiri Bold Italic,"Copyright (c) 2010-2016, Khaled Hosny <khaledhosny@eglug.org>. Portions copyright (c) 2010, Sebastian Kosch <sebastian@aldusleaf.org>."
+Amita,normal,400,Amita-Regular.ttf,Amita-Regular,Amita Regular,"Copyright (c) 2014, Eduardo Rodriguez Tunni. Copyright (c) 2000, Modular Infotech, Pune, INDIA. All rights reserved. Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com). All rights reserved."
+Amita,normal,700,Amita-Bold.ttf,Amita-Bold,Amita Bold,"Copyright (c) 2014, Eduardo Rodriguez Tunni. Copyright (c) 2000, Modular Infotech, Pune, INDIA. All rights reserved. Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com). All rights reserved."
+Anaheim,normal,400,Anaheim-Regular.ttf,Anaheim-Regular,Anaheim Regular,Copyright 2012 The Anaheim Project Authors
+Andada,normal,400,Andada-Regular.ttf,Andada-Regular,Andada Regular,"Copyright (c) 2011, Huerta Tipografica (www.huertatipografica.com.ar), with Reserved Font Names \Andada\, \Andada Pro\ and \Andada HT\"
+Andada SC,normal,400,AndadaSC-Regular.ttf,AndadaSC-Regular,Andada SC,"Copyright (c) 2011-2012, Carolina Giovagnoli (huertatipografica.com.ar info@huertatipografica.com.ar), with Reserved Font Name 'Andada'"
+Andada SC,italic,400,AndadaSC-Italic.ttf,AndadaSC-Italic,Andada SC Italic,"Copyright (c) 2011-2012, Carolina Giovagnoli (huertatipografica.com.ar info@huertatipografica.com.ar), with Reserved Font Name 'Andada'"
+Andada SC,normal,700,AndadaSC-Bold.ttf,AndadaSC-Bold,Andada SC Bold,"Copyright (c) 2011-2012, Carolina Giovagnoli (huertatipografica.com.ar info@huertatipografica.com.ar), with Reserved Font Name 'Andada'"
+Andada SC,italic,700,AndadaSC-BoldItalic.ttf,AndadaSC-BoldItalic,Andada SC Bold Italic,"Copyright (c) 2011-2012, Carolina Giovagnoli (huertatipografica.com.ar info@huertatipografica.com.ar), with Reserved Font Name 'Andada'"
+Andika,normal,400,Andika-Regular.ttf,Andika-Regular,Andika Regular,"Copyright (c) 2004-2011, SIL International (http://www.sil.org/). Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL), with Reserved Font Names \Andika\ and \SIL\."
+Angkor,normal,400,Angkor-Regular.ttf,Angkor-Regular,Angkor Regular,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com), with Reserved Font Name Angkor. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Annie Use Your Telescope,normal,400,AnnieUseYourTelescope-Regular.ttf,AnnieUseYourTelescope-Regular,Annie Use Your Telescope Regular,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com)"
+Anonymous Pro,normal,400,AnonymousPro-Regular.ttf,AnonymousPro-Regular,Anonymous Pro Regular,Copyright (c) Mark Simonson 2009-2010. All rights reserved.
+Anonymous Pro,italic,400,AnonymousPro-Italic.ttf,AnonymousPro-Italic,Anonymous Pro Italic,Copyright (c) Mark Simonson 2009-2010. All rights reserved.
+Anonymous Pro,normal,700,AnonymousPro-Bold.ttf,AnonymousPro-Bold,Anonymous Pro Bold,Copyright (c) Mark Simonson 2009-2010. All rights reserved.
+Anonymous Pro,italic,700,AnonymousPro-BoldItalic.ttf,AnonymousPro-BoldItalic,Anonymous Pro Bold Italic,Copyright (c) Mark Simonson 2009-2010. All rights reserved.
+Antic,normal,400,Antic-Regular.ttf,Antic-Regular,Antic Regular,"Copyright (c) 2010, 2011, Santiago Orozco <hi@typemade.mx>, with Reserved Font Name \Antic\"
+Antic Didone,normal,400,AnticDidone-Regular.ttf,AnticDidone-Regular,Antic Didone Regular,"Copyright (c) 2011, Santiago Orozco (hi@typemade.mx), with Reserved Font Name Antic Didone."
+Antic Slab,normal,400,AnticSlab-Regular.ttf,AnticSlab-Regular,Antic Slab Regular,Copyright (c) 2011 by Santiago Orozco(hi@typemade.mx) with reserved name Antic Slab
+Anton,normal,400,Anton-Regular.ttf,Anton-Regular,Anton Regular,Copyright 2011 The Anton Project Authors
+Antonio,normal,300,Antonio-Light.ttf,Antonio-Light,Antonio Light,"Copyright (c) 2011-12, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Antonio'"
+Antonio,normal,400,Antonio-Regular.ttf,Antonio-Regular,Antonio Regular,"Copyright (c) 2011-12, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Antonio'"
+Antonio,normal,700,Antonio-Bold.ttf,Antonio-Bold,Antonio Bold,"Copyright (c) 2011-12, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Antonio'"
+Arapey,normal,400,Arapey-Regular.ttf,Arapey-Regular,Arapey Regular,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Arapey\"
+Arapey,italic,400,Arapey-Italic.ttf,Arapey-Italic,Arapey Italic,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Arapey\"
+Arbutus,normal,400,Arbutus-Regular.ttf,Arbutus-Regular,Arbutus Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \Arbutus\.  This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Arbutus Slab,normal,400,ArbutusSlab-Regular.ttf,ArbutusSlab-Regular,Arbutus Slab Regular,Copyright (c) 2012 by Sorkin Type Co.. All rights reserved.
+Architects Daughter,normal,400,ArchitectsDaughter-Regular.ttf,ArchitectsDaughter-Regular,Architects Daughter Regular,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com)"
+Archivo,normal,400,Archivo-Regular.ttf,Archivo-Regular,Archivo Regular,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,italic,400,Archivo-Italic.ttf,Archivo-Italic,Archivo Italic,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,normal,500,Archivo-Medium.ttf,Archivo-Medium,Archivo Medium,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,italic,500,Archivo-MediumItalic.ttf,Archivo-MediumItalic,Archivo Medium Italic,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,normal,600,Archivo-SemiBold.ttf,Archivo-SemiBold,Archivo SemiBold,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,italic,600,Archivo-SemiBoldItalic.ttf,Archivo-SemiBoldItalic,Archivo SemiBold Italic,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,normal,700,Archivo-Bold.ttf,Archivo-Bold,Archivo Bold,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo,italic,700,Archivo-BoldItalic.ttf,Archivo-BoldItalic,Archivo Bold Italic,Copyright 2019 The Archivo Project Authors (https://github.com/Omnibus-Type/Archivo)
+Archivo Black,normal,400,ArchivoBlack-Regular.ttf,ArchivoBlack-Regular,Archivo Black Regular,Copyright 2017 The Archivo Black Project Authors (https://github.com/Omnibus-Type/ArchivoBlack)
+Archivo Narrow,normal,400,ArchivoNarrow[wght].ttf,ArchivoNarrow-Regular,Archivo Narrow Regular,Copyright 2019 The Archivo Narrow Project Authors (https://github.com/Omnibus-Type/ArchivoNarrow)
+Archivo Narrow,italic,400,ArchivoNarrow-Italic[wght].ttf,ArchivoNarrow-Italic,Archivo Narrow Italic,Copyright 2019 The Archivo Narrow Project Authors (https://github.com/Omnibus-Type/ArchivoNarrow)
+Aref Ruqaa,normal,400,ArefRuqaa-Regular.ttf,ArefRuqaa-Regular,Aref Ruqaa Regular,"Portions copyright  2015, Khaled Hosny (<khaledhosny@eglug.org>). Portions copyright  1997, 2009, 2011 American Mathematical Society (<http://www.ams.org>), with Reserved Font Name EURM10."
+Aref Ruqaa,normal,700,ArefRuqaa-Bold.ttf,ArefRuqaa-Bold,Aref Ruqaa Bold,"Portions copyright  2015, Khaled Hosny (<khaledhosny@eglug.org>). Portions copyright  1997, 2009, 2011 American Mathematical Society (<http://www.ams.org>), with Reserved Font Name EURB10."
+Arima Madurai,normal,100,ArimaMadurai-Thin.ttf,ArimaMadurai-Thin,Arima Madurai Thin,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,200,ArimaMadurai-ExtraLight.ttf,ArimaMadurai-ExtraLight,Arima Madurai ExtraLight,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,300,ArimaMadurai-Light.ttf,ArimaMadurai-Light,Arima Madurai Light,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,400,ArimaMadurai-Regular.ttf,ArimaMadurai-Regular,Arima Madurai Regular,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,500,ArimaMadurai-Medium.ttf,ArimaMadurai-Medium,Arima Madurai Medium,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,700,ArimaMadurai-Bold.ttf,ArimaMadurai-Bold,Arima Madurai Bold,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,800,ArimaMadurai-ExtraBold.ttf,ArimaMadurai-ExtraBold,Arima Madurai ExtraBold,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arima Madurai,normal,900,ArimaMadurai-Black.ttf,ArimaMadurai-Black,Arima Madurai Black,Copyright 2015 The Arima Project Authors (info@ndiscovered.com)
+Arizonia,normal,400,Arizonia-Regular.ttf,Arizonia-Regular,Arizonia Regular,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Arizonia\"
+Armata,normal,400,Armata-Regular.ttf,Armata-Regular,Armata Regular,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \Armata\  This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: http://scripts.sil.org/OFL"
+Arsenal,normal,400,Arsenal-Regular.ttf,Arsenal-Regular,Arsenal Regular,Copyright 2012 The Arsenal Project Authors (andrij.design@gmail.com)
+Arsenal,italic,400,Arsenal-Italic.ttf,Arsenal-Italic,Arsenal Italic,Copyright 2012 The Arsenal Project Authors (andrij.design@gmail.com)
+Arsenal,normal,700,Arsenal-Bold.ttf,Arsenal-Bold,Arsenal Bold,Copyright 2012 The Arsenal Project Authors (andrij.design@gmail.com)
+Arsenal,italic,700,Arsenal-BoldItalic.ttf,Arsenal-BoldItalic,Arsenal Bold Italic,Copyright 2012 The Arsenal Project Authors (andrij.design@gmail.com)
+Artifika,normal,400,Artifika-Regular.ttf,Artifika-Regular,Artifika Regular,Copyright (c) 2011 by Yulya Zhdanova | Cyreal. All rights reserved.
+Arvo,normal,400,Arvo-Regular.ttf,Arvo,Arvo,Copyright 2010 Anton Koovit.
+Arvo,italic,400,Arvo-Italic.ttf,Arvo-Italic,Arvo-Italic,"Copyright 2010 Anton Koovit, Yassin Baggar."
+Arvo,normal,700,Arvo-Bold.ttf,Arvo-Bold,Arvo Bold,Copyright (c) 2010 by Anton Koovit.
+Arvo,italic,700,Arvo-BoldItalic.ttf,Arvo-BoldItalic,Arvo Bold Italic,"Copyright 2010 Anton Koovit, Yassin Baggar."
+Arya,normal,400,Arya-Regular.ttf,Arya-Regular,Arya Regular,"Copyright (c) 2014, Eduardo Rodriguez Tunni. Copyright (c) 2000, Modular Infotech, Pune, INDIA. All rights reserved."
+Arya,normal,700,Arya-Bold.ttf,Arya-Bold,Arya Bold,"Copyright (c) 2014, Eduardo Rodriguez Tunni. Copyright (c) 2000, Modular Infotech, Pune, INDIA. All rights reserved."
+Asap,normal,400,Asap-Regular.ttf,Asap-Regular,Asap Regular,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,italic,400,Asap-Italic.ttf,Asap-Italic,Asap Italic,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,normal,500,Asap-Medium.ttf,Asap-Medium,Asap Medium,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,italic,500,Asap-MediumItalic.ttf,Asap-MediumItalic,Asap Medium Italic,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,normal,600,Asap-SemiBold.ttf,Asap-SemiBold,Asap SemiBold,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,italic,600,Asap-SemiBoldItalic.ttf,Asap-SemiBoldItalic,Asap SemiBold Italic,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,normal,700,Asap-Bold.ttf,Asap-Bold,Asap Bold,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap,italic,700,Asap-BoldItalic.ttf,Asap-BoldItalic,Asap Bold Italic,Copyright 2018 The Asap Project Authors (https://github.com/Omnibus-Type/Asap) with Reserved Font Name \Asap\.
+Asap Condensed,normal,400,AsapCondensed-Regular.ttf,AsapCondensed-Regular,Asap Condensed Regular,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,italic,400,AsapCondensed-Italic.ttf,AsapCondensed-Italic,Asap Condensed Italic,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,normal,500,AsapCondensed-Medium.ttf,AsapCondensed-Medium,Asap Condensed Medium,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,italic,500,AsapCondensed-MediumItalic.ttf,AsapCondensed-MediumItalic,Asap Condensed Medium Italic,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,normal,600,AsapCondensed-SemiBold.ttf,AsapCondensed-SemiBold,Asap Condensed SemiBold,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,italic,600,AsapCondensed-SemiBoldItalic.ttf,AsapCondensed-SemiBoldItalic,Asap Condensed SemiBold Italic,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,normal,700,AsapCondensed-Bold.ttf,AsapCondensed-Bold,Asap Condensed Bold,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asap Condensed,italic,700,AsapCondensed-BoldItalic.ttf,AsapCondensed-BoldItalic,Asap Condensed Bold Italic,"Copyright 2018 The Asap Condensed Project Authors (https://github.com/Omnibus-Type/AsapCondensed), with Reserved Font Name \(Asap Condensed)\."
+Asar,normal,400,Asar-Regular.ttf,Asar-Regular,Asar Regular,"Copyright (c) 2014-2015, Sorkin Type Co (sorkintype.com | sorkintype@gmail.com). Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)"
+Asset,normal,400,Asset-Regular.ttf,Asset-Regular,Asset Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \Asset\.  This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Assistant,normal,200,Assistant-ExtraLight.ttf,Assistant-ExtraLight,Assistant ExtraLight,"Copyright 2010 The Amirim Project Authors, with Reserved Font Name \'Source\'. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Assistant,normal,300,Assistant-Light.ttf,Assistant-Light,Assistant Light,"Copyright 2010 The Amirim Project Authors, with Reserved Font Name \'Source\'. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Assistant,normal,400,Assistant-Regular.ttf,Assistant-Regular,Assistant Regular,"Copyright 2010 The Amirim Project Authors, with Reserved Font Name \'Source\'. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Assistant,normal,600,Assistant-SemiBold.ttf,Assistant-SemiBold,Assistant SemiBold,"Copyright 2010 The Amirim Project Authors, with Reserved Font Name \'Source\'. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Assistant,normal,700,Assistant-Bold.ttf,Assistant-Bold,Assistant Bold,"Copyright 2010 The Amirim Project Authors, with Reserved Font Name \'Source\'. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Assistant,normal,800,Assistant-ExtraBold.ttf,Assistant-ExtraBold,Assistant ExtraBold,"Copyright 2010 The Amirim Project Authors, with Reserved Font Name \'Source\'. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Astloch,normal,400,Astloch-Regular.ttf,Astloch-Regular,Astloch Regular,Copyright 2011 The Astloch Project Authors
+Astloch,normal,700,Astloch-Bold.ttf,Astloch-Bold,Astloch Bold,
+Asul,normal,400,Asul-Regular.ttf,Asul-Regular,Asul Regular,"Copyright (c) 2011, Mariela Monsalve (marmonsalve@gmail.com), with Reserved Font Name \Asul\"
+Asul,normal,700,Asul-Bold.ttf,Asul-Bold,Asul Bold,"Copyright (c) 2011, Mariela Monsalve (marmonsalve@gmail.com), with Reserved Font Name \Asul\"
+Athiti,normal,200,Athiti-ExtraLight.ttf,Athiti-ExtraLight,Athiti ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Athiti,normal,300,Athiti-Light.ttf,Athiti-Light,Athiti Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Athiti,normal,400,Athiti-Regular.ttf,Athiti-Regular,Athiti Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Athiti,normal,500,Athiti-Medium.ttf,Athiti-Medium,Athiti Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Athiti,normal,600,Athiti-SemiBold.ttf,Athiti-SemiBold,Athiti SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Athiti,normal,700,Athiti-Bold.ttf,Athiti-Bold,Athiti Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Atma,normal,300,Atma-Light.ttf,Atma-Light,Atma Light,Copyright 2015 The Atma Project Authors (www.black-foundry.com)
+Atma,normal,400,Atma-Regular.ttf,Atma-Regular,Atma Regular,Copyright 2015 The Atma Project Authors (www.black-foundry.com)
+Atma,normal,500,Atma-Medium.ttf,Atma-Medium,Atma Medium,Copyright 2015 The Atma Project Authors (www.black-foundry.com)
+Atma,normal,600,Atma-SemiBold.ttf,Atma-SemiBold,Atma SemiBold,Copyright 2015 The Atma Project Authors (www.black-foundry.com)
+Atma,normal,700,Atma-Bold.ttf,Atma-Bold,Atma Bold,Copyright 2015 The Atma Project Authors (www.black-foundry.com)
+Atomic Age,normal,400,AtomicAge-Regular.ttf,AtomicAge-Regular,Atomic Age Regular,"Copyright (c) 2013 - 2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Atomic Age\'."
+Aubrey,normal,400,Aubrey-Regular.ttf,Aubrey-Regular,Aubrey Regular,Copyright (c) 2011 by Gayaneh Bagdasaryan | Cyreal.org. All rights reserved.
+Audiowide,normal,400,Audiowide-Regular.ttf,Audiowide-Regular,Audiowide Regular,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Audiowide\"
+Autour One,normal,400,AutourOne-Regular.ttf,AutourOne-Regular,Autour One Regular,"Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Autour\'"
+Average,normal,400,Average-Regular.ttf,Average-Regular,Average Regular,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar), with Reserved Font Name \Average\"
+Average Sans,normal,400,AverageSans-Regular.ttf,AverageSans-Regular,Average Sans Regular,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar), with Reserved Font Name \'Average\'"
+Averia Gruesa Libre,normal,400,AveriaGruesaLibre-Regular.ttf,AveriaGruesaLibre-Regular,Averia Gruesa Libre Regular,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Libre,normal,300,AveriaLibre-Light.ttf,AveriaLibre-Light,Averia Libre Light,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Libre,italic,300,AveriaLibre-LightItalic.ttf,AveriaLibre-LightItalic,Averia Libre Light Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Libre,normal,400,AveriaLibre-Regular.ttf,AveriaLibre-Regular,Averia Libre Regular,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Libre,italic,400,AveriaLibre-Italic.ttf,AveriaLibre-Italic,Averia Libre Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Libre,normal,700,AveriaLibre-Bold.ttf,AveriaLibre-Bold,Averia Libre Bold,"2011, Dan Sayers (i@iotic.com"
+Averia Libre,italic,700,AveriaLibre-BoldItalic.ttf,AveriaLibre-BoldItalic,Averia Libre Bold Italic,"2011, Dan Sayers (i@iotic.com"
+Averia Sans Libre,normal,300,AveriaSansLibre-Light.ttf,AveriaSansLibre-Light,Averia Sans Libre Light,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Sans Libre,italic,300,AveriaSansLibre-LightItalic.ttf,AveriaSansLibre-LightItalic,Averia Sans Libre Light Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Sans Libre,normal,400,AveriaSansLibre-Regular.ttf,AveriaSansLibre-Regular,Averia Sans Libre Regular,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Sans Libre,italic,400,AveriaSansLibre-Italic.ttf,AveriaSansLibre-Italic,Averia Sans Libre Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Sans Libre,normal,700,AveriaSansLibre-Bold.ttf,AveriaSansLibre-Bold,Averia Sans Libre Bold,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Sans Libre,italic,700,AveriaSansLibre-BoldItalic.ttf,AveriaSansLibre-BoldItalic,Averia Sans Libre Bold Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Serif Libre,normal,300,AveriaSerifLibre-Light.ttf,AveriaSerifLibre-Light,Averia Serif Libre Light,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Serif Libre,italic,300,AveriaSerifLibre-LightItalic.ttf,AveriaSerifLibre-LightItalic,Averia Serif Libre Light Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Serif Libre,normal,400,AveriaSerifLibre-Regular.ttf,AveriaSerifLibre-Regular,Averia Serif Libre Regular,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Serif Libre,italic,400,AveriaSerifLibre-Italic.ttf,AveriaSerifLibre-Italic,Averia Serif Libre Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Serif Libre,normal,700,AveriaSerifLibre-Bold.ttf,AveriaSerifLibre-Bold,Averia Serif Libre Bold,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+Averia Serif Libre,italic,700,AveriaSerifLibre-BoldItalic.ttf,AveriaSerifLibre-BoldItalic,Averia Serif Libre Bold Italic,"Copyright (c) 2011, Dan Sayers (i@iotic.com), with Reserved Font Name \'Averia\' and \'Averia Libre\'."
+B612,normal,400,B612-Regular.ttf,B612-Regular,B612 Regular,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612,italic,400,B612-Italic.ttf,B612-Italic,B612 Italic,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612,normal,700,B612-Bold.ttf,B612-Bold,B612 Bold,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612,italic,700,B612-BoldItalic.ttf,B612-BoldItalic,B612 Bold Italic,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612 Mono,normal,400,B612Mono-Regular.ttf,B612Mono-Regular,B612 Mono Regular,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612 Mono,italic,400,B612Mono-Italic.ttf,B612Mono-Italic,B612 Mono Italic,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612 Mono,normal,700,B612Mono-Bold.ttf,B612Mono-Bold,B612 Mono Bold,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+B612 Mono,italic,700,B612Mono-BoldItalic.ttf,B612Mono-BoldItalic,B612 Mono Bold Italic,Copyright 2012 The B612 Project Authors (https://github.com/polarsys/b612)
+Bad Script,normal,400,BadScript-Regular.ttf,BadScript-Regular,Bad Script Regular,Copyright 2011 The Bad Script Project Authors (gaslighttypefoundry@gmail.com)
+Bahiana,normal,400,Bahiana-Regular.ttf,Bahiana-Regular,Bahiana Regular,Copyright 2016 The Bahiana Project Authors (omnibus.type@gmail.com)
+Bahianita,normal,400,Bahianita-Regular.ttf,Bahianita-Regular,Bahianita Regular,Copyright 2018 The Bahianita Project Authors (https://github.com/Omnibus-Type/Bahiana/tree/master/Bahianita)
+Bai Jamjuree,normal,200,BaiJamjuree-ExtraLight.ttf,BaiJamjuree-ExtraLight,Bai Jamjuree ExtraLight,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,italic,200,BaiJamjuree-ExtraLightItalic.ttf,BaiJamjuree-ExtraLightItalic,Bai Jamjuree ExtraLight Italic,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,normal,300,BaiJamjuree-Light.ttf,BaiJamjuree-Light,Bai Jamjuree Light,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,italic,300,BaiJamjuree-LightItalic.ttf,BaiJamjuree-LightItalic,Bai Jamjuree Light Italic,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,normal,400,BaiJamjuree-Regular.ttf,BaiJamjuree-Regular,Bai Jamjuree Regular,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,italic,400,BaiJamjuree-Italic.ttf,BaiJamjuree-Italic,Bai Jamjuree Italic,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,normal,500,BaiJamjuree-Medium.ttf,BaiJamjuree-Medium,Bai Jamjuree Medium,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,italic,500,BaiJamjuree-MediumItalic.ttf,BaiJamjuree-MediumItalic,Bai Jamjuree Medium Italic,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,normal,600,BaiJamjuree-SemiBold.ttf,BaiJamjuree-SemiBold,Bai Jamjuree SemiBold,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,italic,600,BaiJamjuree-SemiBoldItalic.ttf,BaiJamjuree-SemiBoldItalic,Bai Jamjuree SemiBold Italic,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,normal,700,BaiJamjuree-Bold.ttf,BaiJamjuree-Bold,Bai Jamjuree Bold,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Bai Jamjuree,italic,700,BaiJamjuree-BoldItalic.ttf,BaiJamjuree-BoldItalic,Bai Jamjuree Bold Italic,Copyright 2018 Bai Jamjuree (https://github.com/cadsondemak/Bai-Jamjuree)
+Baloo 2,normal,400,Baloo2-Regular.ttf,Baloo2-Regular,Baloo 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo 2,normal,500,Baloo2-Medium.ttf,Baloo2-Medium,Baloo 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo 2,normal,600,Baloo2-SemiBold.ttf,Baloo2-SemiBold,Baloo 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo 2,normal,700,Baloo2-Bold.ttf,Baloo2-Bold,Baloo 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo 2,normal,800,Baloo2-ExtraBold.ttf,Baloo2-ExtraBold,Baloo 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo,normal,400,Baloo-Regular.ttf,Baloo-Regular,Baloo Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Bhai 2,normal,400,BalooBhai2-Regular.ttf,BalooBhai2-Regular,Baloo Bhai 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhai 2,normal,500,BalooBhai2-Medium.ttf,BalooBhai2-Medium,Baloo Bhai 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhai 2,normal,600,BalooBhai2-SemiBold.ttf,BalooBhai2-SemiBold,Baloo Bhai 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhai 2,normal,700,BalooBhai2-Bold.ttf,BalooBhai2-Bold,Baloo Bhai 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhai 2,normal,800,BalooBhai2-ExtraBold.ttf,BalooBhai2-ExtraBold,Baloo Bhai 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhai,normal,400,BalooBhai-Regular.ttf,BalooBhai-Regular,Baloo Bhai Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Bhaijaan,normal,400,BalooBhaijaan-Regular.ttf,BalooBhaijaan-Regular,Baloo Bhaijaan Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Bhaina 2,normal,400,BalooBhaina2-Regular.ttf,BalooBhaina2-Regular,Baloo Bhaina 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhaina 2,normal,500,BalooBhaina2-Medium.ttf,BalooBhaina2-Medium,Baloo Bhaina 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhaina 2,normal,600,BalooBhaina2-SemiBold.ttf,BalooBhaina2-SemiBold,Baloo Bhaina 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhaina 2,normal,700,BalooBhaina2-Bold.ttf,BalooBhaina2-Bold,Baloo Bhaina 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhaina 2,normal,800,BalooBhaina2-ExtraBold.ttf,BalooBhaina2-ExtraBold,Baloo Bhaina 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Bhaina,normal,400,BalooBhaina-Regular.ttf,BalooBhaina-Regular,Baloo Bhaina Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Chettan 2,normal,400,BalooChettan2-Regular.ttf,BalooChettan2-Regular,Baloo Chettan 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Chettan 2,normal,500,BalooChettan2-Medium.ttf,BalooChettan2-Medium,Baloo Chettan 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Chettan 2,normal,600,BalooChettan2-SemiBold.ttf,BalooChettan2-SemiBold,Baloo Chettan 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Chettan 2,normal,700,BalooChettan2-Bold.ttf,BalooChettan2-Bold,Baloo Chettan 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Chettan 2,normal,800,BalooChettan2-ExtraBold.ttf,BalooChettan2-ExtraBold,Baloo Chettan 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Chettan,normal,400,BalooChettan-Regular.ttf,BalooChettan-Regular,Baloo Chettan Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Da 2,normal,400,BalooDa2-Regular.ttf,BalooDa2-Regular,Baloo Da 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Da 2,normal,500,BalooDa2-Medium.ttf,BalooDa2-Medium,Baloo Da 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Da 2,normal,600,BalooDa2-SemiBold.ttf,BalooDa2-SemiBold,Baloo Da 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Da 2,normal,700,BalooDa2-Bold.ttf,BalooDa2-Bold,Baloo Da 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Da 2,normal,800,BalooDa2-ExtraBold.ttf,BalooDa2-ExtraBold,Baloo Da 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Da,normal,400,BalooDa-Regular.ttf,BalooDa-Regular,Baloo Da Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Paaji 2,normal,400,BalooPaaji2-Regular.ttf,BalooPaaji2-Regular,Baloo Paaji 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Paaji 2,normal,500,BalooPaaji2-Medium.ttf,BalooPaaji2-Medium,Baloo Paaji 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Paaji 2,normal,600,BalooPaaji2-SemiBold.ttf,BalooPaaji2-SemiBold,Baloo Paaji 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Paaji 2,normal,700,BalooPaaji2-Bold.ttf,BalooPaaji2-Bold,Baloo Paaji 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Paaji 2,normal,800,BalooPaaji2-ExtraBold.ttf,BalooPaaji2-ExtraBold,Baloo Paaji 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Paaji,normal,400,BalooPaaji-Regular.ttf,BalooPaaji-Regular,Baloo Paaji Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Tamma 2,normal,400,BalooTamma2-Regular.ttf,BalooTamma2-Regular,Baloo Tamma 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tamma 2,normal,500,BalooTamma2-Medium.ttf,BalooTamma2-Medium,Baloo Tamma 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tamma 2,normal,600,BalooTamma2-SemiBold.ttf,BalooTamma2-SemiBold,Baloo Tamma 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tamma 2,normal,700,BalooTamma2-Bold.ttf,BalooTamma2-Bold,Baloo Tamma 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tamma 2,normal,800,BalooTamma2-ExtraBold.ttf,BalooTamma2-ExtraBold,Baloo Tamma 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tamma,normal,400,BalooTamma-Regular.ttf,BalooTamma-Regular,Baloo Tamma Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Tammudu 2,normal,400,BalooTammudu2-Regular.ttf,BalooTammudu2-Regular,Baloo Tammudu 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tammudu 2,normal,500,BalooTammudu2-Medium.ttf,BalooTammudu2-Medium,Baloo Tammudu 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tammudu 2,normal,600,BalooTammudu2-SemiBold.ttf,BalooTammudu2-SemiBold,Baloo Tammudu 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tammudu 2,normal,700,BalooTammudu2-Bold.ttf,BalooTammudu2-Bold,Baloo Tammudu 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tammudu 2,normal,800,BalooTammudu2-ExtraBold.ttf,BalooTammudu2-ExtraBold,Baloo Tammudu 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Tammudu,normal,400,BalooTammudu-Regular.ttf,BalooTammudu-Regular,Baloo Tammudu Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Baloo Thambi 2,normal,400,BalooThambi2-Regular.ttf,BalooThambi2-Regular,Baloo Thambi 2 Regular,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Thambi 2,normal,500,BalooThambi2-Medium.ttf,BalooThambi2-Medium,Baloo Thambi 2 Medium,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Thambi 2,normal,600,BalooThambi2-SemiBold.ttf,BalooThambi2-SemiBold,Baloo Thambi 2 SemiBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Thambi 2,normal,700,BalooThambi2-Bold.ttf,BalooThambi2-Bold,Baloo Thambi 2 Bold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Thambi 2,normal,800,BalooThambi2-ExtraBold.ttf,BalooThambi2-ExtraBold,Baloo Thambi 2 ExtraBold,Copyright 2019 The Baloo 2 Project Authors (https://github.com/EkType/Baloo2)
+Baloo Thambi,normal,400,BalooThambi-Regular.ttf,BalooThambi-Regular,Baloo Thambi Regular,Copyright (c) 2015 Ek Type (www.ektype.in)
+Balsamiq Sans,normal,400,BalsamiqSans-Regular.ttf,BalsamiqSans-Regular,Balsamiq Sans Regular,Copyright 2011 The Balsamiq Sans Project Authors (https://github.com/balsamiq/balsamiqsans)
+Balsamiq Sans,italic,400,BalsamiqSans-Italic.ttf,BalsamiqSans-Italic,Balsamiq Sans Italic,Copyright 2011 The Balsamiq Sans Project Authors (https://github.com/balsamiq/balsamiqsans)
+Balsamiq Sans,normal,700,BalsamiqSans-Bold.ttf,BalsamiqSans-Bold,Balsamiq Sans Bold,Copyright 2011 The Balsamiq Sans Project Authors (https://github.com/balsamiq/balsamiqsans)
+Balsamiq Sans,italic,700,BalsamiqSans-BoldItalic.ttf,BalsamiqSans-BoldItalic,Balsamiq Sans Bold Italic,Copyright 2011 The Balsamiq Sans Project Authors (https://github.com/balsamiq/balsamiqsans)
+Balthazar,normal,400,Balthazar-Regular.ttf,Balthazar-Regular,Balthazar Regular,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar dario@tipo.net.ar), with Reserved Font Name \Balthazar\."
+Bangers,normal,400,Bangers-Regular.ttf,Bangers-Regular,Bangers Regular,Copyright 2010 The Bangers Project Authors (contact@sansoxygen.com)
+Barlow,normal,100,Barlow-Thin.ttf,Barlow-Thin,Barlow Thin,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,100,Barlow-ThinItalic.ttf,Barlow-ThinItalic,Barlow Thin Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,200,Barlow-ExtraLight.ttf,Barlow-ExtraLight,Barlow ExtraLight,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,200,Barlow-ExtraLightItalic.ttf,Barlow-ExtraLightItalic,Barlow ExtraLight Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,300,Barlow-Light.ttf,Barlow-Light,Barlow Light,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,300,Barlow-LightItalic.ttf,Barlow-LightItalic,Barlow Light Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,400,Barlow-Regular.ttf,Barlow-Regular,Barlow Regular,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,400,Barlow-Italic.ttf,Barlow-Italic,Barlow Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,500,Barlow-Medium.ttf,Barlow-Medium,Barlow Medium,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,500,Barlow-MediumItalic.ttf,Barlow-MediumItalic,Barlow Medium Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,600,Barlow-SemiBold.ttf,Barlow-SemiBold,Barlow SemiBold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,600,Barlow-SemiBoldItalic.ttf,Barlow-SemiBoldItalic,Barlow SemiBold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,700,Barlow-Bold.ttf,Barlow-Bold,Barlow Bold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,700,Barlow-BoldItalic.ttf,Barlow-BoldItalic,Barlow Bold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,800,Barlow-ExtraBold.ttf,Barlow-ExtraBold,Barlow ExtraBold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,800,Barlow-ExtraBoldItalic.ttf,Barlow-ExtraBoldItalic,Barlow ExtraBold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,normal,900,Barlow-Black.ttf,Barlow-Black,Barlow Black,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow,italic,900,Barlow-BlackItalic.ttf,Barlow-BlackItalic,Barlow Black Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,100,BarlowCondensed-Thin.ttf,BarlowCondensed-Thin,Barlow Condensed Thin,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,100,BarlowCondensed-ThinItalic.ttf,BarlowCondensed-ThinItalic,Barlow Condensed Thin Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,200,BarlowCondensed-ExtraLight.ttf,BarlowCondensed-ExtraLight,Barlow Condensed ExtraLight,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,200,BarlowCondensed-ExtraLightItalic.ttf,BarlowCondensed-ExtraLightItalic,Barlow Condensed ExtraLight Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,300,BarlowCondensed-Light.ttf,BarlowCondensed-Light,Barlow Condensed Light,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,300,BarlowCondensed-LightItalic.ttf,BarlowCondensed-LightItalic,Barlow Condensed Light Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,400,BarlowCondensed-Regular.ttf,BarlowCondensed-Regular,Barlow Condensed Regular,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,400,BarlowCondensed-Italic.ttf,BarlowCondensed-Italic,Barlow Condensed Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,500,BarlowCondensed-Medium.ttf,BarlowCondensed-Medium,Barlow Condensed Medium,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,500,BarlowCondensed-MediumItalic.ttf,BarlowCondensed-MediumItalic,Barlow Condensed Medium Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,600,BarlowCondensed-SemiBold.ttf,BarlowCondensed-SemiBold,Barlow Condensed SemiBold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,600,BarlowCondensed-SemiBoldItalic.ttf,BarlowCondensed-SemiBoldItalic,Barlow Condensed SemiBold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,700,BarlowCondensed-Bold.ttf,BarlowCondensed-Bold,Barlow Condensed Bold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,700,BarlowCondensed-BoldItalic.ttf,BarlowCondensed-BoldItalic,Barlow Condensed Bold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,800,BarlowCondensed-ExtraBold.ttf,BarlowCondensed-ExtraBold,Barlow Condensed ExtraBold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,800,BarlowCondensed-ExtraBoldItalic.ttf,BarlowCondensed-ExtraBoldItalic,Barlow Condensed ExtraBold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,normal,900,BarlowCondensed-Black.ttf,BarlowCondensed-Black,Barlow Condensed Black,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Condensed,italic,900,BarlowCondensed-BlackItalic.ttf,BarlowCondensed-BlackItalic,Barlow Condensed Black Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,100,BarlowSemiCondensed-Thin.ttf,BarlowSemiCondensed-Thin,Barlow Semi Condensed Thin,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,100,BarlowSemiCondensed-ThinItalic.ttf,BarlowSemiCondensed-ThinItalic,Barlow Semi Condensed Thin Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,200,BarlowSemiCondensed-ExtraLight.ttf,BarlowSemiCondensed-ExtraLight,Barlow Semi Condensed ExtraLight,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,200,BarlowSemiCondensed-ExtraLightItalic.ttf,BarlowSemiCondensed-ExtraLightItalic,Barlow Semi Condensed ExtraLight Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,300,BarlowSemiCondensed-Light.ttf,BarlowSemiCondensed-Light,Barlow Semi Condensed Light,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,300,BarlowSemiCondensed-LightItalic.ttf,BarlowSemiCondensed-LightItalic,Barlow Semi Condensed Light Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,400,BarlowSemiCondensed-Regular.ttf,BarlowSemiCondensed-Regular,Barlow Semi Condensed Regular,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,400,BarlowSemiCondensed-Italic.ttf,BarlowSemiCondensed-Italic,Barlow Semi Condensed Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,500,BarlowSemiCondensed-Medium.ttf,BarlowSemiCondensed-Medium,Barlow Semi Condensed Medium,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,500,BarlowSemiCondensed-MediumItalic.ttf,BarlowSemiCondensed-MediumItalic,Barlow Semi Condensed Medium Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,600,BarlowSemiCondensed-SemiBold.ttf,BarlowSemiCondensed-SemiBold,Barlow Semi Condensed SemiBold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,600,BarlowSemiCondensed-SemiBoldItalic.ttf,BarlowSemiCondensed-SemiBoldItalic,Barlow Semi Condensed SemiBold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,700,BarlowSemiCondensed-Bold.ttf,BarlowSemiCondensed-Bold,Barlow Semi Condensed Bold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,700,BarlowSemiCondensed-BoldItalic.ttf,BarlowSemiCondensed-BoldItalic,Barlow Semi Condensed Bold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,800,BarlowSemiCondensed-ExtraBold.ttf,BarlowSemiCondensed-ExtraBold,Barlow Semi Condensed ExtraBold,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,800,BarlowSemiCondensed-ExtraBoldItalic.ttf,BarlowSemiCondensed-ExtraBoldItalic,Barlow Semi Condensed ExtraBold Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,normal,900,BarlowSemiCondensed-Black.ttf,BarlowSemiCondensed-Black,Barlow Semi Condensed Black,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barlow Semi Condensed,italic,900,BarlowSemiCondensed-BlackItalic.ttf,BarlowSemiCondensed-BlackItalic,Barlow Semi Condensed Black Italic,Copyright 2017 The Barlow Project Authors (https://github.com/jpt/barlow)
+Barriecito,normal,400,Barriecito-Regular.ttf,Barriecito-Regular,Barriecito Regular,Copyright 2018 The Barriecito Project Authors (https://github.com/Omnibus-Type/Barrio/Barriecito)
+Barrio,normal,400,Barrio-Regular.ttf,Barrio-Regular,Barrio Regular,Copyright 2016 The Barrio Project Authors (omnibus.type@gmail.com)
+Basic,normal,400,Basic-Regular.ttf,Basic-Regular,Basic Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Basic\."
+Baskervville,normal,400,Baskervville-Regular.ttf,Baskervville-Regular,Baskervville Regular,Copyright 2018 The Baskervville Project Authors (https://github.com/anrt-type/ANRT-Baskervville)
+Baskervville,italic,400,Baskervville-Italic.ttf,Baskervville-Italic,Baskervville Italic,Copyright 2018 The Baskervville Project Authors (https://github.com/anrt-type/ANRT-Baskervville)
+Battambang,normal,400,Battambang-Regular.ttf,Battambang-Regular,Battambang Regular,"Copyright (c) 2013, Danh Hong (khmertype.org)"
+Battambang,normal,700,Battambang-Bold.ttf,Battambang-Bold,Battambang Bold,"Copyright (c) 2013, Danh Hong (khmertype.org)"
+Baumans,normal,400,Baumans-Regular.ttf,Baumans-Regular,Baumans Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name \Baumans\.  This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Bayon,normal,400,Bayon-Regular.ttf,Bayon-Regular,Bayon Regular,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com), with Reserved Font Name Bayon. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Bebas Neue,normal,400,BebasNeue-Regular.ttf,BebasNeue-Regular,Bebas Neue Regular,Copyright 2019 The Bebas Neue Project Authors (https://github.com/dharmatype/Bebas-Neue)
+Belgrano,normal,400,Belgrano-Regular.ttf,Belgrano-Regular,Belgrano Regular,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com),  with Reserved Font Names \Belgrano\"
+Bellefair,normal,400,Bellefair-Regular.ttf,Bellefair-Regular,Bellefair Regular,Copyright 2015 The Bellefair Project Authors (https://github.com/shinntype/bellefair)
+Belleza,normal,400,Belleza-Regular.ttf,Belleza-Regular,Belleza Regular,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar), with Reserved Font Name \Belleza\"
+Bellota,normal,300,Bellota-Light.ttf,Bellota-Light,Bellota Light,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota,italic,300,Bellota-LightItalic.ttf,Bellota-LightItalic,Bellota Light Italic,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota,normal,400,Bellota-Regular.ttf,Bellota-Regular,Bellota Regular,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota,italic,400,Bellota-Italic.ttf,Bellota-Italic,Bellota Italic,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota,normal,700,Bellota-Bold.ttf,Bellota-Bold,Bellota Bold,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota,italic,700,Bellota-BoldItalic.ttf,Bellota-BoldItalic,Bellota Bold Italic,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota Text,normal,300,BellotaText-Light.ttf,BellotaText-Light,Bellota Text Light,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota Text,italic,300,BellotaText-LightItalic.ttf,BellotaText-LightItalic,Bellota Text Light Italic,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota Text,normal,400,BellotaText-Regular.ttf,BellotaText-Regular,Bellota Text Regular,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota Text,italic,400,BellotaText-Italic.ttf,BellotaText-Italic,Bellota Text Italic,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota Text,normal,700,BellotaText-Bold.ttf,BellotaText-Bold,Bellota Text Bold,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+Bellota Text,italic,700,BellotaText-BoldItalic.ttf,BellotaText-BoldItalic,Bellota Text Bold Italic,Copyright 2019 The Bellota Project Authors (https://github.com/kemie/Bellota-Font)
+BenchNine,normal,300,BenchNine-Light.ttf,BenchNine-Light,BenchNine Light,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Name \'BenchNine\'"
+BenchNine,normal,400,BenchNine-Regular.ttf,BenchNine-Regular,BenchNine Regular,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Name \'BenchNine\'"
+BenchNine,normal,700,BenchNine-Bold.ttf,BenchNine-Bold,BenchNine Bold,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Name \'BenchNine\'"
+Bentham,normal,400,Bentham-Regular.ttf,Bentham-Regular,Bentham Regular,"Copyright (c) 1999-2010, Ben Weiner (ben@readingtype.org.uk), with Reserved Font Name Bentham."
+Berkshire Swash,normal,400,BerkshireSwash-Regular.ttf,BerkshireSwash-Regular,Berkshire Swash Regular,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Berkshire Swash\"
+Beth Ellen,normal,400,BethEllen-Regular.ttf,BethEllen-Regular,Beth Ellen Regular,Copyright 2019 The Beth Ellen Project Authors (https://github.com/googlefonts/BethEllen)
+Bevan,normal,400,Bevan-Regular.ttf,Bevan-Regular,Bevan Regular,Copyright 2016 The Bevan Project Authors (www.sansoxygen.com)
+Be Vietnam,normal,100,BeVietnam-Thin.ttf,BeVietnam-Thin,Be Vietnam Thin,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,100,BeVietnam-ThinItalic.ttf,BeVietnam-ThinItalic,Be Vietnam Thin Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,normal,300,BeVietnam-Light.ttf,BeVietnam-Light,Be Vietnam Light,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,300,BeVietnam-LightItalic.ttf,BeVietnam-LightItalic,Be Vietnam Light Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,normal,400,BeVietnam-Regular.ttf,BeVietnam-Regular,Be Vietnam Regular,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,400,BeVietnam-Italic.ttf,BeVietnam-Italic,Be Vietnam Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,normal,500,BeVietnam-Medium.ttf,BeVietnam-Medium,Be Vietnam Medium,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,500,BeVietnam-MediumItalic.ttf,BeVietnam-MediumItalic,Be Vietnam Medium Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,normal,600,BeVietnam-SemiBold.ttf,BeVietnam-SemiBold,Be Vietnam SemiBold,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,600,BeVietnam-SemiBoldItalic.ttf,BeVietnam-SemiBoldItalic,Be Vietnam SemiBold Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,normal,700,BeVietnam-Bold.ttf,BeVietnam-Bold,Be Vietnam Bold,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,700,BeVietnam-BoldItalic.ttf,BeVietnam-BoldItalic,Be Vietnam Bold Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,normal,800,BeVietnam-ExtraBold.ttf,BeVietnam-ExtraBold,Be Vietnam ExtraBold,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Be Vietnam,italic,800,BeVietnam-ExtraBoldItalic.ttf,BeVietnam-ExtraBoldItalic,Be Vietnam ExtraBold Italic,Copyright 2019 The Bevietnam Project Authors (https://github.com/bettergui/beVietnam)
+Bhavuka,normal,400,Bhavuka-Regular.ttf,Bhavuka-Regular,Bhavuka Regular,"Copyright 2014 - Matt Heximer (www.10fourdesign.com)\nbased on Latin \Bellota\ by Kemie Guaida (www.pixilate.com), \nwhich is in turn based on \Snippet\ by Gesine Todt.\n\nLicensed under the SIL Open Font License 1.1 This license is available with a FAQ at: http://scripts.sil.org/OFL\n(see file OFL.txt)"
+Bigelow Rules,normal,400,BigelowRules-Regular.ttf,BigelowRules-Regular,Bigelow Rules Regular,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Bigelow Rules\"
+Bigshot One,normal,400,BigshotOne-Regular.ttf,BigshotOne-Regular,Bigshot One Regular,Copyright (c) 2011 by Gesine Todt. All rights reserved.
+Big Shoulders Display,normal,100,BigShouldersDisplay-Thin.ttf,BigShouldersDisplay-Thin,Big Shoulders Display Thin,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,300,BigShouldersDisplay-Light.ttf,BigShouldersDisplay-Light,Big Shoulders Display Light,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,400,BigShouldersDisplay-Regular.ttf,BigShouldersDisplay-Regular,Big Shoulders Display Regular,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,500,BigShouldersDisplay-Medium.ttf,BigShouldersDisplay-Medium,Big Shoulders Display Medium,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,600,BigShouldersDisplay-SemiBold.ttf,BigShouldersDisplay-SemiBold,Big Shoulders Display SemiBold,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,700,BigShouldersDisplay-Bold.ttf,BigShouldersDisplay-Bold,Big Shoulders Display Bold,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,800,BigShouldersDisplay-ExtraBold.ttf,BigShouldersDisplay-ExtraBold,Big Shoulders Display ExtraBold,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Display,normal,900,BigShouldersDisplay-Black.ttf,BigShouldersDisplay-Black,Big Shoulders Display Black,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,100,BigShouldersText-Thin.ttf,BigShouldersText-Thin,Big Shoulders Text Thin,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,300,BigShouldersText-Light.ttf,BigShouldersText-Light,Big Shoulders Text Light,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,400,BigShouldersText-Regular.ttf,BigShouldersText-Regular,Big Shoulders Text Regular,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,500,BigShouldersText-Medium.ttf,BigShouldersText-Medium,Big Shoulders Text Medium,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,600,BigShouldersText-SemiBold.ttf,BigShouldersText-SemiBold,Big Shoulders Text SemiBold,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,700,BigShouldersText-Bold.ttf,BigShouldersText-Bold,Big Shoulders Text Bold,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,800,BigShouldersText-ExtraBold.ttf,BigShouldersText-ExtraBold,Big Shoulders Text ExtraBold,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Big Shoulders Text,normal,900,BigShouldersText-Black.ttf,BigShouldersText-Black,Big Shoulders Text Black,Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders)
+Bilbo,normal,400,Bilbo-Regular.ttf,Bilbo-Regular,Bilbo Regular,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Bilbo\"
+Bilbo Swash Caps,normal,400,BilboSwashCaps-Regular.ttf,BilboSwashCaps-Regular,Bilbo Swash Caps Regular,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Names \Bilbo\ and \Bilbo Swash Caps\"
+Bio Rhyme,normal,200,BioRhyme-ExtraLight.ttf,BioRhyme-ExtraLight,BioRhyme ExtraLight,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme,normal,300,BioRhyme-Light.ttf,BioRhyme-Light,BioRhyme Light,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme,normal,400,BioRhyme-Regular.ttf,BioRhyme-Regular,BioRhyme Regular,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme,normal,700,BioRhyme-Bold.ttf,BioRhyme-Bold,BioRhyme Bold,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme,normal,800,BioRhyme-ExtraBold.ttf,BioRhyme-ExtraBold,BioRhyme ExtraBold,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme Expanded,normal,200,BioRhymeExpanded-ExtraLight.ttf,BioRhymeExpanded-ExtraLight,BioRhyme Expanded ExtraLight,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme Expanded,normal,300,BioRhymeExpanded-Light.ttf,BioRhymeExpanded-Light,BioRhyme Expanded Light,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme Expanded,normal,400,BioRhymeExpanded-Regular.ttf,BioRhymeExpanded-Regular,BioRhyme Expanded Regular,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme Expanded,normal,700,BioRhymeExpanded-Bold.ttf,BioRhymeExpanded-Bold,BioRhyme Expanded Bold,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Bio Rhyme Expanded,normal,800,BioRhymeExpanded-ExtraBold.ttf,BioRhymeExpanded-ExtraBold,BioRhyme Expanded ExtraBold,Copyright 2016 Aoife Mooney (aoifemooney@gmail.com www.aoifemooney.org)
+Biryani,normal,200,Biryani-ExtraLight.ttf,Biryani-ExtraLight,Biryani ExtraLight,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Biryani,normal,300,Biryani-Light.ttf,Biryani-Light,Biryani Light,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Biryani,normal,400,Biryani-Regular.ttf,Biryani-Regular,Biryani Regular,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Biryani,normal,600,Biryani-SemiBold.ttf,Biryani-SemiBold,Biryani SemiBold,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Biryani,normal,700,Biryani-Bold.ttf,Biryani-Bold,Biryani Bold,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Biryani,normal,800,Biryani-ExtraBold.ttf,Biryani-ExtraBold,Biryani ExtraBold,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Biryani,normal,900,Biryani-Black.ttf,Biryani-Black,Biryani Black,Copyright (c) 2015 Dan Reynolds. Copyright (c) 2015 Mathieu Réguer.
+Bitter,normal,400,Bitter-Regular.ttf,Bitter-Regular,Bitter Regular,"Copyright (c) 2011, Sol Matas (www.huertatipografica.com.ar), with Reserved Font Name \Bitter\"
+Bitter,italic,400,Bitter-Italic.ttf,Bitter-Italic,Bitter Italic,"Copyright (c) 2011, Sol Matas (www.huertatipografica.com.ar), with Reserved Font Name \Bitter\"
+Bitter,normal,700,Bitter-Bold.ttf,Bitter-Bold,Bitter Bold,"Copyright (c) 2011, Sol Matas (www.huertatipografica.com.ar), with Reserved Font Name \Bitter\"
+Black And White Picture,normal,400,BlackAndWhitePicture-Regular.ttf,BlackAndWhitePicture-Regular,Black And White Picture Regular,Copyright (c) 1992-2018 AsiaSoft Inc. Seoul Korea All Rights Reserved.
+Black Han Sans,normal,400,BlackHanSans-Regular.ttf,BlackHanSans-Regular,Black Han Sans Regular,Copyright 2015 The Black Han Sans Authors
+Black Ops One,normal,400,BlackOpsOne-Regular.ttf,BlackOpsOne-Regular,Black Ops One Regular,"Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com) with Reserved Font Names \Black Ops\ and \Black Ops One\."
+Blinker,normal,100,Blinker-Thin.ttf,Blinker-Thin,Blinker Thin,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,200,Blinker-ExtraLight.ttf,Blinker-ExtraLight,Blinker ExtraLight,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,300,Blinker-Light.ttf,Blinker-Light,Blinker Light,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,400,Blinker-Regular.ttf,Blinker-Regular,Blinker,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,600,Blinker-SemiBold.ttf,Blinker-SemiBold,Blinker SemiBold,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,700,Blinker-Bold.ttf,Blinker-Bold,Blinker Bold,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,800,Blinker-ExtraBold.ttf,Blinker-ExtraBold,Blinker ExtraBold,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Blinker,normal,900,Blinker-Black.ttf,Blinker-Black,Blinker Black,Copyright 2019 the Blinker project authors (https://github.com/supertype-de/Blinker)
+Bokor,normal,400,Bokor-Regular.ttf,Bokor-Regular,Bokor Regular,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com), with Reserved Font Name Bokor. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Bonbon,normal,400,Bonbon-Regular.ttf,Bonbon-Regular,Bonbon Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name \Bonbon\.  This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Boogaloo,normal,400,Boogaloo-Regular.ttf,Boogaloo-Regular,Boogaloo Regular,"Copyright (c) 2011, John Vargas Beltran (www.johnvargasbeltran.com|john.vargasbeltran@gmail.com), with Reserved Font Name \Boogaloo\."
+Bowlby One,normal,400,BowlbyOne-Regular.ttf,BowlbyOne-Regular,Bowlby One Regular,"Copyright (c) 2011 by vernon adams (vern@newtypography.co.uk), with Reserved Font Names \Bowlby\ \Bowlby One\ and \Bowlby One SC\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Bowlby One SC,normal,400,BowlbyOneSC-Regular.ttf,BowlbyOneSC-Regular,Bowlby One SC Regular,"Copyright (c) 2011, vernon adams (vern@newtypography.co.uk), with Reserved Font Names \Bowlby\"
+Brawler,normal,400,Brawler-Regular.ttf,Brawler-Regular,Brawler Regular,Copyright (c) 2011 by Oleg Frolov | Cyreal. All rights reserved.
+Bree Serif,normal,400,BreeSerif-Regular.ttf,BreeSerif-Regular,Bree Serif Regular,"Copyright (c) 2011, TypeTogether (www.type-together.com), with Reserved Font Names \Bree\ and \Bree Serif\"
+Bruno Ace,normal,400,BrunoAce-Regular.ttf,BrunoAce-Regular,Bruno Ace,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Bruno Ace\"
+Bruno Ace SC,normal,400,BrunoAceSC-Regular.ttf,BrunoAceSC-Regular,Bruno Ace SC,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Bruno Ace SC\"
+Bubblegum Sans,normal,400,BubblegumSans-Regular.ttf,BubblegumSans-Regular,Bubblegum Sans Regular,"Copyright (c) 2011 Angel Koziupa (sudtipos@sudtipos.com), Copyright (c) 2011 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Bubblegum Sans\"
+Bubbler One,normal,400,BubblerOne-Regular.ttf,BubblerOne-Regular,Bubbler One Regular,"Copyright (c) 2011 by Brenda Gallo (gbrenda1987@gmail.com), with Reserved Font Name \Bubbler\"
+Buda,normal,300,Buda-Light.ttf,Buda-Light,Buda Light,"Copyright (c) 2010, Adele Antignac (a.antignac@hotmail.fr). All rights reserved. Licenced under SIL OFL vl.1"
+Buenard,normal,400,Buenard-Regular.ttf,Buenard-Regular,Buenard Regular,"Copyright (c) 2011, FontFuror (info@fontfuror.com), with Reserved Font Names \Buenard\ and \Buenard Pro\."
+Buenard,normal,700,Buenard-Bold.ttf,Buenard-Bold,Buenard Bold,"Copyright (c) 2011, FontFuror (info@fontfuror.com), with Reserved Font Names \Buenard\ and \Buenard Pro\."
+Bungee,normal,400,Bungee-Regular.ttf,Bungee-Regular,Bungee Regular,Copyright 2008 The Bungee Project Authors (david@djr.com)
+Bungee Hairline,normal,400,BungeeHairline-Regular.ttf,BungeeHairline-Regular,Bungee Hairline Regular,Copyright 2008 The Bungee Project Authors (david@djr.com)
+Bungee Inline,normal,400,BungeeInline-Regular.ttf,BungeeInline-Regular,Bungee Inline Regular,Copyright 2008 The Bungee Project Authors (david@djr.com)
+Bungee Outline,normal,400,BungeeOutline-Regular.ttf,BungeeOutline-Regular,Bungee Outline Regular,Copyright 2008 The Bungee Project Authors (david@djr.com)
+Bungee Shade,normal,400,BungeeShade-Regular.ttf,BungeeShade-Regular,Bungee Shade Regular,Copyright 2008 The Bungee Project Authors (david@djr.com)
+Butcherman,normal,400,Butcherman-Regular.ttf,Butcherman-Regular,Butcherman Regular,"Copyright (c) 2011, Typomondo, with Reserved Font Name  \Butcherman\."
+Butcherman Caps,normal,400,ButchermanCaps-Regular.ttf,ButchermanCaps-Regular,Butcherman Caps Regular,"Copyright (c) 2011, Vernon Adams DBA Typomondo (vern@newtypography.co.uk), with Reserved Font Name \Butcherman\."
+Butterfly Kids,normal,400,ButterflyKids-Regular.ttf,ButterflyKids-Regular,Butterfly Kids Regular,"Copyright (c) 2012 by Font Diner, Inc DBA Tart Workshop (diner@fontdiner.com) with Reseved Font Name \Butterfly Kids\"
+Cabin,normal,400,Cabin-Regular.ttf,Cabin-Regular,Cabin,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,italic,400,Cabin-Italic.ttf,Cabin-Italic,Cabin Italic,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,normal,500,Cabin-Medium.ttf,Cabin-Medium,Cabin Medium,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,italic,500,Cabin-MediumItalic.ttf,Cabin-MediumItalic,Cabin Medium Italic,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,normal,600,Cabin-SemiBold.ttf,Cabin-SemiBold,Cabin SemiBold,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,italic,600,Cabin-SemiBoldItalic.ttf,Cabin-SemiBoldItalic,Cabin SemiBold Italic,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,normal,700,Cabin-Bold.ttf,Cabin-Bold,Cabin Bold,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin,italic,700,Cabin-BoldItalic.ttf,Cabin-BoldItalic,Cabin Bold Italic,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin Condensed,normal,400,CabinCondensed-Regular.ttf,CabinCondensed-Regular,Cabin Condensed,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin Condensed,normal,500,CabinCondensed-Medium.ttf,CabinCondensed-Medium,Cabin Condensed Medium,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin Condensed,normal,600,CabinCondensed-SemiBold.ttf,CabinCondensed-SemiBold,Cabin Condensed SemiBold,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin Condensed,normal,700,CabinCondensed-Bold.ttf,CabinCondensed-Bold,Cabin Condensed Bold,Copyright 2016 The Cabin Project Authors (impallari@gmail.com)
+Cabin Sketch,normal,400,CabinSketch-Regular.ttf,CabinSketch-Regular,Cabin Sketch Regular,"Copyright 2011 The Cabin Project Authors (impallari@gmail.com), with Reserved Font Name \Cabin\, \Cabin Sketch\."
+Cabin Sketch,normal,700,CabinSketch-Bold.ttf,CabinSketch-Bold,Cabin Sketch Bold,"Copyright 2011 The Cabin Project Authors (impallari@gmail.com), with Reserved Font Name \Cabin\, \Cabin Sketch\."
+Caesar Dressing,normal,400,CaesarDressing-Regular.ttf,CaesarDressing-Regular,Caesar Dressing,Copyright (c) 2011 by Open Window (dathanboardman@gmail.com) with Reseved Font Name \Caesar Dressing\
+Cagliostro,normal,400,Cagliostro-Regular.ttf,Cagliostro-Regular,Cagliostro Regular,"Copyright (c) 2011 Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name \Cagliostro\"
+Cairo,normal,200,Cairo-ExtraLight.ttf,Cairo-ExtraLight,Cairo ExtraLight,Copyright 2009 The Cairo Project Authors (gaber@gaberism.net)
+Cairo,normal,300,Cairo-Light.ttf,Cairo-Light,Cairo Light,Copyright 2009 The Cairo Project Authors (gaber@gaberism.net)
+Cairo,normal,400,Cairo-Regular.ttf,Cairo-Regular,Cairo Regular,Copyright 2009 The Cairo Project Authors (gaber@gaberism.net)
+Cairo,normal,600,Cairo-SemiBold.ttf,Cairo-SemiBold,Cairo SemiBold,Copyright 2009 The Cairo Project Authors (gaber@gaberism.net)
+Cairo,normal,700,Cairo-Bold.ttf,Cairo-Bold,Cairo Bold,Copyright 2009 The Cairo Project Authors (gaber@gaberism.net)
+Cairo,normal,900,Cairo-Black.ttf,Cairo-Black,Cairo Black,Copyright 2009 The Cairo Project Authors (gaber@gaberism.net)
+Caladea,normal,400,Caladea-Regular.ttf,Caladea-Regular,Caladea Regular,Copyright 2012 The Caladea Project Authors (https://github.com/huertatipografica/Caladea)
+Caladea,italic,400,Caladea-Italic.ttf,Caladea-Italic,Caladea Italic,Copyright 2012 The Caladea Project Authors (https://github.com/huertatipografica/Caladea)
+Caladea,normal,700,Caladea-Bold.ttf,Caladea-Bold,Caladea Bold,Copyright 2012 The Caladea Project Authors (https://github.com/huertatipografica/Caladea)
+Caladea,italic,700,Caladea-BoldItalic.ttf,Caladea-BoldItalic,Caladea Bold Italic,Copyright 2012 The Caladea Project Authors (https://github.com/huertatipografica/Caladea)
+Calistoga,normal,400,Calistoga-Regular.ttf,Calistoga-Regular,Calistoga Regular,Copyright 2019 The Calistoga Project Authors (https://github.com/SorkinType/Calistoga)
+Cambay,normal,400,Cambay-Regular.ttf,Cambay-Regular,Cambay Regular,Copyright (c) 2014 Pooja Saxena (www.poojasaxena.in)
+Cambay,italic,400,Cambay-Italic.ttf,Cambay-Italic,Cambay Italic,Copyright (c) 2014 Pooja Saxena (www.poojasaxena.in)
+Cambay,normal,700,Cambay-Bold.ttf,Cambay-Bold,Cambay Bold,Copyright (c) 2014 Pooja Saxena (www.poojasaxena.in)
+Cambay,italic,700,Cambay-BoldItalic.ttf,Cambay-BoldItalic,Cambay Bold Italic,Copyright (c) 2014 Pooja Saxena (www.poojasaxena.in)
+Cambo,normal,400,Cambo-Regular.ttf,Cambo-Regular,Cambo,"Copyright (c) 2011, Carolina Giovagnoli (caro@huertatipografica.com.ar), Copyright (c) 2011, Andres Torresi (andres@huertatipografica.com.ar), with Reserved Font Name Cambo."
+Candal,normal,400,Candal.ttf,Candal,Candal,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Candal'. All rights reserved."
+Cantarell,normal,400,Cantarell-Regular.ttf,Cantarell-Regular,Cantarell Regular,Copyright (c) 2009 Dave Crossland <dave@lab6.com>
+Cantarell,italic,400,Cantarell-Oblique.ttf,Cantarell-Oblique,Cantarell Oblique,Copyright (c) 2009 Dave Crossland <dave@lab6.com>
+Cantarell,normal,700,Cantarell-Bold.ttf,Cantarell-Bold,Cantarell Bold,Copyright (c) 2009 Dave Crossland <dave@lab6.com>
+Cantarell,italic,700,Cantarell-BoldOblique.ttf,Cantarell-BoldOblique,Cantarell Bold Oblique,Copyright (c) 2009 Dave Crossland <dave@lab6.com>
+Cantata One,normal,400,CantataOne-Regular.ttf,CantataOne-Regular,Cantata One,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name \Cantata\"
+Cantora One,normal,400,CantoraOne-Regular.ttf,CantoraOne-Regular,Cantora One,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com) with Reserved Font Name Cantora."
+Capriola,normal,400,Capriola-Regular.ttf,Capriola-Regular,Capriola Regular,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Capriola\."
+Cardo,normal,400,Cardo-Regular.ttf,Cardo-Regular,Cardo,"Copyright (c) 2002-2011, David J. Perry (hospes02@scholarsfonts.net)"
+Cardo,italic,400,Cardo-Italic.ttf,Cardo-Italic,Cardo Italic,"Copyright (c) 2002-2011, David J. Perry (hospes02@scholarsfonts.net)"
+Cardo,normal,700,Cardo-Bold.ttf,Cardo-Bold,Cardo Bold,"Copyright (c) 2002-2011, David J. Perry (hospes02@scholarsfonts.net)"
+Carme,normal,400,Carme-Regular.ttf,Carme,Carme Regular,"Copyright (c) 2010-2011, Ruben Prol (ipanemagrafica@gmail.com|www.ipanemagrafica.com), with Reserved Font Name Carme."
+Carrois Gothic,normal,400,CarroisGothic-Regular.ttf,CarroisGothic-Regular,Carrois Gothic Regular,"Copyright (c) 2011 by Ralph du Carrois, with Reserved Font Name \'Carrois\'"
+Carrois Gothic SC,normal,400,CarroisGothicSC-Regular.ttf,CarroisGothicSC-Regular,Carrois Gothic SC Regular,"Copyright (c) 2011 by Ralph du Carrois, with Reserved Font Name \'Carrois\'"
+Carter One,normal,400,CarterOne.ttf,CarterOne,Carter One,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Carter One'. All rights reserved."
+Catamaran,normal,100,Catamaran-Thin.ttf,Catamaran-Thin,Catamaran Thin,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,200,Catamaran-ExtraLight.ttf,Catamaran-ExtraLight,Catamaran ExtraLight,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,300,Catamaran-Light.ttf,Catamaran-Light,Catamaran Light,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,400,Catamaran-Regular.ttf,Catamaran-Regular,Catamaran Regular,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,500,Catamaran-Medium.ttf,Catamaran-Medium,Catamaran Medium,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,600,Catamaran-SemiBold.ttf,Catamaran-SemiBold,Catamaran SemiBold,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,700,Catamaran-Bold.ttf,Catamaran-Bold,Catamaran Bold,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,800,Catamaran-ExtraBold.ttf,Catamaran-ExtraBold,Catamaran ExtraBold,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Catamaran,normal,900,Catamaran-Black.ttf,Catamaran-Black,Catamaran Black,Copyright 2014 The Catamaran Authors (pria.ravichandran@gmail.com)
+Caudex,normal,400,Caudex-Regular.ttf,Caudex,Caudex,Copyright (c) 2011 Hjort Nidudsson (nidud@users.sourceforge.net)
+Caudex,italic,400,Caudex-Italic.ttf,Caudex-Italic,Caudex Italic,Copyright (c) 2011 Hjort Nidudsson (nidud@users.sourceforge.net)
+Caudex,normal,700,Caudex-Bold.ttf,Caudex-Bold,Caudex Bold,Copyright (c) 2011 Hjort Nidudsson (nidud@users.sourceforge.net)
+Caudex,italic,700,Caudex-BoldItalic.ttf,Caudex-BoldItalic,Caudex Bold Italic,Copyright (c) 2011 Hjort Nidudsson (nidud@users.sourceforge.net)
+Caveat,normal,400,Caveat-Regular.ttf,Caveat-Regular,Caveat Regular,Copyright 2014 The Caveat Project Authors (https://github.com/googlefonts/caveat)
+Caveat,normal,700,Caveat-Bold.ttf,Caveat-Bold,Caveat Bold,Copyright 2014 The Caveat Project Authors (https://github.com/googlefonts/caveat)
+Caveat Brush,normal,400,CaveatBrush-Regular.ttf,CaveatBrush-Regular,Caveat Brush,Copyright 2015 Google Inc. All Rights Reserved.
+Cedarville Cursive,normal,400,Cedarville-Cursive.ttf,Cedarville-Cursive,Cedarville Cursive,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Ceviche One,normal,400,CevicheOne-Regular.ttf,CevicheOne-Regular,Ceviche One,"Copyright (c) 2011 by LatinoType Limitada (luciano@latinotype.com), with Reserved Font Names \Cecivhe\ and \Ceviche One\"
+Chakra Petch,normal,300,ChakraPetch-Light.ttf,ChakraPetch-Light,Chakra Petch Light,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,italic,300,ChakraPetch-LightItalic.ttf,ChakraPetch-LightItalic,Chakra Petch Light Italic,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,normal,400,ChakraPetch-Regular.ttf,ChakraPetch-Regular,Chakra Petch Regular,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,italic,400,ChakraPetch-Italic.ttf,ChakraPetch-Italic,Chakra Petch Italic,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,normal,500,ChakraPetch-Medium.ttf,ChakraPetch-Medium,Chakra Petch Medium,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,italic,500,ChakraPetch-MediumItalic.ttf,ChakraPetch-MediumItalic,Chakra Petch Medium Italic,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,normal,600,ChakraPetch-SemiBold.ttf,ChakraPetch-SemiBold,Chakra Petch SemiBold,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,italic,600,ChakraPetch-SemiBoldItalic.ttf,ChakraPetch-SemiBoldItalic,Chakra Petch SemiBold Italic,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,normal,700,ChakraPetch-Bold.ttf,ChakraPetch-Bold,Chakra Petch Bold,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Chakra Petch,italic,700,ChakraPetch-BoldItalic.ttf,ChakraPetch-BoldItalic,Chakra Petch Bold Italic,Copyright 2018 The Chakra Petch Project Authors (https://github.com/m4rc1e/Chakra-Petch.git)
+Changa,normal,400,Changa[wght].ttf,Changa-ExtraLight,Changa ExtraLight,Copyright 2011 The Changa Project Authors (https://github.com/etunni/Changa)
+Changa One,normal,400,ChangaOne-Regular.ttf,ChangaOne,Changa One,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Changa\"
+Changa One,italic,400,ChangaOne-Italic.ttf,ChangaOne-Italic,Changa One Italic,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Changa\"
+Chango,normal,400,Chango-Regular.ttf,Chango-Regular,Chango Regular,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Chango\"
+Charm,normal,400,Charm-Regular.ttf,Charm-Regular,Charm Regular,Copyright 2018 The Charm Project Authors (https://github.com/cadsondemak/charm)
+Charm,normal,700,Charm-Bold.ttf,Charm-Bold,Charm Bold,Copyright 2018 The Charm Project Authors (https://github.com/cadsondemak/charm)
+Charmonman,normal,400,Charmonman-Regular.ttf,Charmonman-Regular,Charmonman Regular,Copyright 2018 The Charmonman Project Authors (https://github.com/cadsondemak/Charmonman)
+Charmonman,normal,700,Charmonman-Bold.ttf,Charmonman-Bold,Charmonman Bold,Copyright 2018 The Charmonman Project Authors (https://github.com/cadsondemak/Charmonman)
+Chathura,normal,100,Chathura-Thin.ttf,Chathura-Thin,Chathura Thin,Copyright 2009 The Chathura Project Authors.
+Chathura,normal,300,Chathura-Light.ttf,Chathura-Light,Chathura Light,Copyright 2009 The Chathura Project Authors.
+Chathura,normal,400,Chathura-Regular.ttf,Chathura-Regular,Chathura Regular,Copyright 2009 The Chathura Project Authors.
+Chathura,normal,700,Chathura-Bold.ttf,Chathura-Bold,Chathura Bold,Copyright 2009 The Chathura Project Authors.
+Chathura,normal,800,Chathura-ExtraBold.ttf,Chathura-ExtraBold,Chathura ExtraBold,Copyright 2009 The Chathura Project Authors.
+Chau Philomene One,normal,400,ChauPhilomeneOne-Regular.ttf,ChauPhilomeneOne-Regular,Chau Philomene One Regular,"Copyright (c) 2010-2012, TipoType (produccion.taller@gmail.com), with Reserved Font Name \Chau Philomene\"
+Chau Philomene One,italic,400,ChauPhilomeneOne-Italic.ttf,ChauPhilomeneOne-Italic,Chau Philomene One Italic,"Copyright (c) 2010-2012, TipoType (produccion.taller@gmail.com www.tipotype.com), with Reserved Font Name \Chau Philomene\"
+Chela One,normal,400,ChelaOne-Regular.ttf,ChelaOne-Regular,Chela One,"Copyright (c) 2012, LatinoType (luciano@latinotype.com), with Reserved Font Names 'Chela'"
+Chelsea Market,normal,400,ChelseaMarket-Regular.ttf,ChelseaMarket-Regular,Chelsea Market,"Copyright (c) 2011 by Font Diner, Inc DBA Tart Workshop (diner@fontdiner.com) with Reseved Font Name \Chelsea Market\"
+Chenla,normal,400,Chenla.ttf,Chenla,Chenla,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name NiDA Chenla. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Cherry Bomb,normal,400,CherryBomb-Regular.ttf,CherryBomb-Regular,Cherry Bomb Regular,Copyright 2019 The Cherry Bomb Project Authors (https://github.com/satsuyako/CherryBomb)
+Cherry Swash,normal,400,CherrySwash-Regular.ttf,CherrySwash-Regular,Cherry Swash,"Copyright (c) 2012, Natalia Kasatkina (kasatkinanataliya@gmail.com)"
+Cherry Swash,normal,700,CherrySwash-Bold.ttf,CherrySwash-Bold,Cherry Swash Bold,"Copyright (c) 2012, Natalia Kasatkina (kasatkinanataliya@gmail.com)"
+Chicle,normal,400,Chicle-Regular.ttf,Chicle-Regular,Chicle Regular,"Copyright (c) 2007 Angel Koziupa (sudtipos@sudtipos.com), Copyright (c) 2007 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Chicle\"
+Chilanka,normal,400,Chilanka-Regular.ttf,Chilanka-Regular,Chilanka Regular,Copyright 2019 The Chilanka Project Authors (https://gitlab.com/smc/fonts/chilanka)
+Chivo,normal,300,Chivo-Light.ttf,Chivo-Light,Chivo Light,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,italic,300,Chivo-LightItalic.ttf,Chivo-LightItalic,Chivo Light Italic,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,normal,400,Chivo-Regular.ttf,Chivo-Regular,Chivo Regular,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,italic,400,Chivo-Italic.ttf,Chivo-Italic,Chivo Italic,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,normal,700,Chivo-Bold.ttf,Chivo-Bold,Chivo Bold,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,italic,700,Chivo-BoldItalic.ttf,Chivo-BoldItalic,Chivo Bold Italic,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,normal,900,Chivo-Black.ttf,Chivo-Black,Chivo Black,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chivo,italic,900,Chivo-BlackItalic.ttf,Chivo-BlackItalic,Chivo Black Italic,Copyright 2016 The Chivo Project Authors (omnibus.type@gmail.com)
+Chonburi,normal,400,Chonburi-Regular.ttf,Chonburi-Regular,Chonburi,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Cinzel,normal,400,Cinzel-Regular.ttf,Cinzel-Regular,Cinzel Regular,"Copyright  2012 Natanael Gama (info@ndiscovered.com), with Reserved Font Name \'Cinzel\'"
+Cinzel,normal,700,Cinzel-Bold.ttf,Cinzel-Bold,Cinzel Bold,"Copyright  2012 Natanael Gama (info@ndiscovered.com), with Reserved Font Name \'Cinzel\'"
+Cinzel,normal,900,Cinzel-Black.ttf,Cinzel-Black,Cinzel Black,"Copyright  2012 Natanael Gama (info@ndiscovered.com), with Reserved Font Name \'Cinzel\'"
+Cinzel Decorative,normal,400,CinzelDecorative-Regular.ttf,CinzelDecorative-Regular,Cinzel Decorative Regular,"Copyright  2012 Natanael Gama (info@ndiscovered.com), with Reserved Font Name \'Cinzel\'"
+Cinzel Decorative,normal,700,CinzelDecorative-Bold.ttf,CinzelDecorative-Bold,Cinzel Decorative Bold,"Copyright  2012 Natanael Gama (info@ndiscovered.com), with Reserved Font Name \'Cinzel\'"
+Cinzel Decorative,normal,900,CinzelDecorative-Black.ttf,CinzelDecorative-Black,Cinzel Decorative Black,"Copyright  2012 Natanael Gama (info@ndiscovered.com), with Reserved Font Name \'Cinzel\'"
+Clicker Script,normal,400,ClickerScript-Regular.ttf,ClickerScript-Regular,Clicker Script,"Copyright (c) 2012 by Brian J. Bonislawsky and Jim Lyles for Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Clicker Script\"
+Coda,normal,400,Coda-Regular.ttf,Coda-Regular,Coda Regular,"Copyright (c) 2010-2012, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \Coda\"
+Coda,normal,800,Coda-ExtraBold.ttf,Coda-ExtraBold,Coda ExtraBold,"Copyright (c) 2010-2012, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \Coda\"
+Coda Caption,normal,800,CodaCaption-ExtraBold.ttf,CodaCaption-ExtraBold,Coda Caption ExtraBold,Copyright (c) 2009 by vernon adams. All rights reserved.
+Codystar,normal,300,Codystar-Light.ttf,Codystar-Light,Codystar Light,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Codystar Light\"
+Codystar,normal,400,Codystar-Regular.ttf,Codystar,Codystar,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Codystar\"
+Coiny,normal,400,Coiny-Regular.ttf,Coiny-Regular,Coiny Regular,Copyright 2015 Marcelo Magalhaes (marcelommp@gmail.com @marcelommp)
+Combo,normal,400,Combo-Regular.ttf,Combo-Regular,Combo,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Combo'"
+Comfortaa,normal,400,Comfortaa[wght].ttf,Comfortaa-Regular,Comfortaa Regular,"Copyright 2011 The Comfortaa Project Authors (https://github.com/alexeiva/comfortaa), with Reserved Font Name \Comfortaa\."
+Comic Neue,normal,300,ComicNeue-Light.ttf,ComicNeue-Light,Comic Neue Light,Copyright 2014 The Comic Neue Project Authors (https://github.com/crozynski/comicneue)
+Comic Neue,italic,300,ComicNeue-LightItalic.ttf,ComicNeue-LightItalic,Comic Neue Light Italic,Copyright 2014 The Comic Neue Project Authors (https://github.com/crozynski/comicneue)
+Comic Neue,normal,400,ComicNeue-Regular.ttf,ComicNeue-Regular,Comic Neue Regular,Copyright 2014 The Comic Neue Project Authors (https://github.com/crozynski/comicneue)
+Comic Neue,italic,400,ComicNeue-Italic.ttf,ComicNeue-Italic,Comic Neue Italic,Copyright 2014 The Comic Neue Project Authors (https://github.com/crozynski/comicneue)
+Comic Neue,normal,700,ComicNeue-Bold.ttf,ComicNeue-Bold,Comic Neue Bold,Copyright 2014 The Comic Neue Project Authors (https://github.com/crozynski/comicneue)
+Comic Neue,italic,700,ComicNeue-BoldItalic.ttf,ComicNeue-BoldItalic,Comic Neue Bold Italic,Copyright 2014 The Comic Neue Project Authors (https://github.com/crozynski/comicneue)
+Concert One,normal,400,ConcertOne-Regular.ttf,ConcertOne-Regular,Concert One,"Copyright (c) 2011, 2011 Johan Kallas (johankallas@gmail.com), Copyright (c) 2011, 2011 Mihkel Virkus (mihkelvirkus@gmail.com), with Reserved Font Name Concert."
+Condiment,normal,400,Condiment-Regular.ttf,Condiment-Regular,Condiment,"Copyright (c) 2010 Angel Koziupa (sudtipos@sudtipos.com), Copyright (c) 2010 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Condiment\"
+Content,normal,400,Content-Regular.ttf,Content,Content,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Content. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Content,normal,700,Content-Bold.ttf,Content-Bold,Content Bold,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Content. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Contrail One,normal,400,ContrailOne-Regular.ttf,ContrailOne-Regular,Contrail One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Names \Contrail\ and \Contrail One\."
+Convergence,normal,400,Convergence-Regular.ttf,Convergence-Regular,Convergence-Regular,"Copyright (c) 2010 by Jos Nicols Silva Schwarzenberg.<info@nsilva.com> and John Vargas Beltran <http://www.johnvargasbeltran.com/>, with Reserved Font Names \Convergence\."
+Cookie,normal,400,Cookie-Regular.ttf,Cookie-Regular,Cookie-Regular,"Copyright (c) 2011 by Ania Kruk (hello@aniakruk.com), with Reserved Font Name Cookie."
+Copse,normal,400,Copse-Regular.ttf,Copse,Copse,"\Copyright (c) 2010, Daniel Rhatigan (sparky@ultrasparky.org) with Reserved Font Name Copse\"
+Corben,normal,400,Corben-Regular.ttf,Corben-Regular,Corben Regular,"Copyright (c) 2010, 2011 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Corben'."
+Corben,normal,700,Corben-Bold.ttf,Corben,Corben,"Copyright (c) 2010, 2011 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Corben'. All rights reserved."
+Cormorant,normal,300,Cormorant-Light.ttf,Cormorant-Light,Cormorant Light,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,italic,300,Cormorant-LightItalic.ttf,Cormorant-LightItalic,Cormorant Light Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,normal,400,Cormorant-Regular.ttf,Cormorant-Regular,Cormorant Regular,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,italic,400,Cormorant-Italic.ttf,Cormorant-Italic,Cormorant Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,normal,500,Cormorant-Medium.ttf,Cormorant-Medium,Cormorant Medium,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,italic,500,Cormorant-MediumItalic.ttf,Cormorant-MediumItalic,Cormorant Medium Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,normal,600,Cormorant-SemiBold.ttf,Cormorant-SemiBold,Cormorant SemiBold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,italic,600,Cormorant-SemiBoldItalic.ttf,Cormorant-SemiBoldItalic,Cormorant SemiBold Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,normal,700,Cormorant-Bold.ttf,Cormorant-Bold,Cormorant Bold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant,italic,700,Cormorant-BoldItalic.ttf,Cormorant-BoldItalic,Cormorant Bold Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,normal,300,CormorantGaramond-Light.ttf,CormorantGaramond-Light,Cormorant Garamond Light,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,italic,300,CormorantGaramond-LightItalic.ttf,CormorantGaramond-LightItalic,Cormorant Garamond Light Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,normal,400,CormorantGaramond-Regular.ttf,CormorantGaramond-Regular,Cormorant Garamond Regular,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,italic,400,CormorantGaramond-Italic.ttf,CormorantGaramond-Italic,Cormorant Garamond Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,normal,500,CormorantGaramond-Medium.ttf,CormorantGaramond-Medium,Cormorant Garamond Medium,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,italic,500,CormorantGaramond-MediumItalic.ttf,CormorantGaramond-MediumItalic,Cormorant Garamond Medium Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,normal,600,CormorantGaramond-SemiBold.ttf,CormorantGaramond-SemiBold,Cormorant Garamond SemiBold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,italic,600,CormorantGaramond-SemiBoldItalic.ttf,CormorantGaramond-SemiBoldItalic,Cormorant Garamond SemiBold Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,normal,700,CormorantGaramond-Bold.ttf,CormorantGaramond-Bold,Cormorant Garamond Bold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Garamond,italic,700,CormorantGaramond-BoldItalic.ttf,CormorantGaramond-BoldItalic,Cormorant Garamond Bold Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,normal,300,CormorantInfant-Light.ttf,CormorantInfant-Light,Cormorant Infant Light,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,italic,300,CormorantInfant-LightItalic.ttf,CormorantInfant-LightItalic,Cormorant Infant Light Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,normal,400,CormorantInfant-Regular.ttf,CormorantInfant-Regular,Cormorant Infant Regular,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,italic,400,CormorantInfant-Italic.ttf,CormorantInfant-Italic,Cormorant Infant Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,normal,500,CormorantInfant-Medium.ttf,CormorantInfant-Medium,Cormorant Infant Medium,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,italic,500,CormorantInfant-MediumItalic.ttf,CormorantInfant-MediumItalic,Cormorant Infant Medium Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,normal,600,CormorantInfant-SemiBold.ttf,CormorantInfant-SemiBold,Cormorant Infant SemiBold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,italic,600,CormorantInfant-SemiBoldItalic.ttf,CormorantInfant-SemiBoldItalic,Cormorant Infant SemiBold Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,normal,700,CormorantInfant-Bold.ttf,CormorantInfant-Bold,Cormorant Infant Bold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Infant,italic,700,CormorantInfant-BoldItalic.ttf,CormorantInfant-BoldItalic,Cormorant Infant Bold Italic,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant SC,normal,300,CormorantSC-Light.ttf,CormorantSC-Light,Cormorant SC Light,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant SC,normal,400,CormorantSC-Regular.ttf,CormorantSC-Regular,Cormorant SC Regular,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant SC,normal,500,CormorantSC-Medium.ttf,CormorantSC-Medium,Cormorant SC Medium,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant SC,normal,600,CormorantSC-SemiBold.ttf,CormorantSC-SemiBold,Cormorant SC SemiBold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant SC,normal,700,CormorantSC-Bold.ttf,CormorantSC-Bold,Cormorant SC Bold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Unicase,normal,300,CormorantUnicase-Light.ttf,CormorantUnicase-Light,Cormorant Unicase Light,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Unicase,normal,400,CormorantUnicase-Regular.ttf,CormorantUnicase-Regular,Cormorant Unicase Regular,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Unicase,normal,500,CormorantUnicase-Medium.ttf,CormorantUnicase-Medium,Cormorant Unicase Medium,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Unicase,normal,600,CormorantUnicase-SemiBold.ttf,CormorantUnicase-SemiBold,Cormorant Unicase SemiBold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Unicase,normal,700,CormorantUnicase-Bold.ttf,CormorantUnicase-Bold,Cormorant Unicase Bold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Upright,normal,300,CormorantUpright-Light.ttf,CormorantUpright-Light,Cormorant Upright Light,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Upright,normal,400,CormorantUpright-Regular.ttf,CormorantUpright-Regular,Cormorant Upright Regular,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Upright,normal,500,CormorantUpright-Medium.ttf,CormorantUpright-Medium,Cormorant Upright Medium,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Upright,normal,600,CormorantUpright-SemiBold.ttf,CormorantUpright-SemiBold,Cormorant Upright SemiBold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Cormorant Upright,normal,700,CormorantUpright-Bold.ttf,CormorantUpright-Bold,Cormorant Upright Bold,Copyright 2015 The Cormorant Project Authors (github.com/CatharsisFonts/Cormorant)
+Courgette,normal,400,Courgette-Regular.ttf,Courgette-Regular,Courgette Regular,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Courgette\."
+Courier Prime,normal,400,CourierPrime-Regular.ttf,CourierPrime-Regular,Courier Prime Regular,Copyright 2015 The Courier Prime Project Authors (https://github.com/quoteunquoteapps/CourierPrime).
+Courier Prime,italic,400,CourierPrime-Italic.ttf,CourierPrime-Italic,Courier Prime Italic,Copyright 2015 The Courier Prime Project Authors (https://github.com/quoteunquoteapps/CourierPrime).
+Courier Prime,normal,700,CourierPrime-Bold.ttf,CourierPrime-Bold,Courier Prime Bold,Copyright 2015 The Courier Prime Project Authors (https://github.com/quoteunquoteapps/CourierPrime).
+Courier Prime,italic,700,CourierPrime-BoldItalic.ttf,CourierPrime-BoldItalic,Courier Prime Bold Italic,Copyright 2015 The Courier Prime Project Authors (https://github.com/quoteunquoteapps/CourierPrime).
+Coustard,normal,400,Coustard-Regular.ttf,Coustard-Regular,Coustard Regular,Copyright 2011 Vernon Adams (vern@newtypography.co.uk)
+Coustard,normal,900,Coustard-Black.ttf,Coustard-Black,Coustard Black,Copyright 2011 Vernon Adams (vern@newtypography.co.uk)
+Covered By Your Grace,normal,400,CoveredByYourGrace.ttf,CoveredByYourGrace,Covered By Your Grace,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Creepster,normal,400,Creepster-Regular.ttf,Creepster-Regular,Creepster,"Copyright (c) 2011, Font Diner, Inc DBA Sideshow (diner@fontdiner.com), with Reserved Font Names \Creepster\"
+Crete Round,normal,400,CreteRound-Regular.ttf,CreteRound-Regular,Crete Round,"Copyright (c) 2011, TypeTogether (www.type-together.com info@type-together.com), with Reserved Font Names \Crete\ and \Crete Round\"
+Crete Round,italic,400,CreteRound-Italic.ttf,CreteRound-Italic,Crete Round Italic,"Copyright (c) 2011, TypeTogether (www.type-together.com info@type-together.com), with Reserved Font Names \Crete\ and \Crete Round\"
+Crimson Pro,normal,200,CrimsonPro[wght].ttf,CrimsonPro-ExtraLight,Crimson Pro ExtraLight,Copyright 2018 The Crimson Pro Project Authors (https://github.com/Fonthausen/CrimsonPro)
+Crimson Pro,italic,200,CrimsonPro-Italic[wght].ttf,CrimsonPro-ExtraLightItalic,Crimson Pro ExtraLight Italic,Copyright 2018 The Crimson Pro Project Authors (https://github.com/Fonthausen/CrimsonPro)
+Crimson Text,normal,400,CrimsonText-Regular.ttf,CrimsonText-Regular,Crimson Text Regular,"Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name \Crimson\."
+Crimson Text,italic,400,CrimsonText-Italic.ttf,CrimsonText-Italic,Crimson Text Italic,"Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name \Crimson\."
+Crimson Text,normal,600,CrimsonText-SemiBold.ttf,CrimsonText-SemiBold,Crimson Text SemiBold,"Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name \Crimson\."
+Crimson Text,italic,600,CrimsonText-SemiBoldItalic.ttf,CrimsonText-SemiBoldItalic,Crimson Text SemiBold Italic,"Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name \Crimson\."
+Crimson Text,normal,700,CrimsonText-Bold.ttf,CrimsonText-Bold,Crimson Text Bold,"Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name \Crimson\."
+Crimson Text,italic,700,CrimsonText-BoldItalic.ttf,CrimsonText-BoldItalic,Crimson Text Bold Italic,"Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name \Crimson\."
+Croissant One,normal,400,CroissantOne-Regular.ttf,CroissantOne-Regular,Croissant One,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Croissant'"
+Cuprum,normal,400,Cuprum-Regular.ttf,Cuprum-Regular,Cuprum Regular,"Copyright 2010 The Cuprum Project Authors (lemonad@jovanny.ru), with Reserved Font Name \Cuprum\."
+Cuprum,italic,400,Cuprum-Italic.ttf,Cuprum-Italic,Cuprum Italic,"Copyright 2010 The Cuprum Project Authors (lemonad@jovanny.ru), with Reserved Font Name \Cuprum\."
+Cuprum,normal,700,Cuprum-Bold.ttf,Cuprum-Bold,Cuprum Bold,"Copyright 2010 The Cuprum Project Authors (lemonad@jovanny.ru), with Reserved Font Name \Cuprum\."
+Cuprum,italic,700,Cuprum-BoldItalic.ttf,Cuprum-BoldItalic,Cuprum Bold Italic,"Copyright 2010 The Cuprum Project Authors (lemonad@jovanny.ru), with Reserved Font Name \Cuprum\."
+Cute Font,normal,400,CuteFont-Regular.ttf,CuteFont-Regular,Cute Font Regular,COPYRIGHT  2004-2017 by TypoDesign Lab. Inc. All rights reserved. Font designed by TypoDesign Lab. Inc.
+Cutive,normal,400,Cutive-Regular.ttf,Cutive-Regular,Cutive,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Names \Cutive\"
+Cutive Mono,normal,400,CutiveMono-Regular.ttf,CutiveMono-Regular,Cutive Mono Regular,Copyright 2012 The Cutive Project Authors (vern@newtypography.co.uk)
+Damion,normal,400,Damion-Regular.ttf,Damion,Damion,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Damion'. All rights reserved."
+Dancing Script,normal,400,DancingScript[wght].ttf,DancingScript-Regular,Dancing Script Regular,"Copyright 2016 The Dancing Script Project Authors (impallari@gmail.com), with Reserved Font Name \'Dancing Script\'."
+Dangrek,normal,400,Dangrek.ttf,Dangrek,Dangrek,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Dangrek. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Darker Grotesque,normal,300,DarkerGrotesque-Light.ttf,DarkerGrotesque-Light,Darker Grotesque Light,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Darker Grotesque,normal,400,DarkerGrotesque-Regular.ttf,DarkerGrotesque-Regular,Darker Grotesque Regular,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Darker Grotesque,normal,500,DarkerGrotesque-Medium.ttf,DarkerGrotesque-Medium,Darker Grotesque Medium,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Darker Grotesque,normal,600,DarkerGrotesque-SemiBold.ttf,DarkerGrotesque-SemiBold,Darker Grotesque SemiBold,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Darker Grotesque,normal,700,DarkerGrotesque-Bold.ttf,DarkerGrotesque-Bold,Darker Grotesque Bold,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Darker Grotesque,normal,800,DarkerGrotesque-ExtraBold.ttf,DarkerGrotesque-ExtraBold,Darker Grotesque ExtraBold,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Darker Grotesque,normal,900,DarkerGrotesque-Black.ttf,DarkerGrotesque-Black,Darker Grotesque Black,Copyright 2019 The Darkergrotesque Project Authors (https://github.com/bettergui/DarkerGrotesque)
+Dawning of a New Day,normal,400,DawningofaNewDay.ttf,DawningofaNewDay,Dawning of a New Day,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Days One,normal,400,DaysOne-Regular.ttf,DaysOne-Regular,Days One,"Copyright (c) 2009 by Alexander Kalachev, Alexey Maslov, Jovanny Lemonad (lemonad@jovanny.ru). All rights reserved."
+Dekko,normal,400,Dekko-Regular.ttf,Dekko,Dekko,"Copyright (c) 2000, Modular Infotech, Pune, INDIA. Copyright (c) 2014, Sorkin Type Co, Boston, MA, USA (www.sorkintype.com)"
+Delius,normal,400,Delius-Regular.ttf,Delius-Regular,Delius-Regular,Copyright (c) 2010 by Natalia Raices (nraices@gmail.com). All rights reserved.
+Delius Swash Caps,normal,400,DeliusSwashCaps-Regular.ttf,DeliusSwashCaps-Regular,Delius Swash Caps,"Copyright (c) 2010, 2011, Natalia Raices <nraices@gmail.com>, with Reserved Font Name \Delius\ \Delius Unicase\ \Delius Swash Caps\."
+Delius Unicase,normal,400,DeliusUnicase-Regular.ttf,DeliusUnicase-Regular,Delius Unicase,"Copyright (c) 2010, 2011, Natalia Raices<nraices@gmail.com>, with Reserved Font Name \Delius\ \Delius Unicase\ \Delius Swash Caps\."
+Delius Unicase,normal,700,DeliusUnicase-Bold.ttf,DeliusUnicase-Bold,Delius Unicase Bold,"Copyright (c) 2010, 2011, Natalia Raices<nraices@gmail.com>, with Reserved Font Name \Delius\ \Delius Unicase\ \Delius Swash Caps\."
+Della Respira,normal,400,DellaRespira-Regular.ttf,DellaRespira-Regular,Della Respira,"Copyright (c) 2011-2012, Nathan Willis (nwillis@glyphography.com), with Reserved Font Names \Della Respira\"
+Denk One,normal,400,DenkOne-Regular.ttf,DenkOne-Regular,Denk One,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name 'Denk'"
+Devonshire,normal,400,Devonshire-Regular.ttf,Devonshire-Regular,Devonshire-Regular,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Devonshire\"
+Dhurjati,normal,400,Dhurjati-Regular.ttf,Dhurjati,Dhurjati,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 2014 Google, Inc."
+Dhyana,normal,400,Dhyana-Regular.ttf,Dhyana,Dhyana,"Copyright (c) 2010-12, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \Nobile\ and \Dhyana\"
+Dhyana,normal,700,Dhyana-Bold.ttf,Dhyana-Bold,Dhyana Bold,"Copyright (c) 2010-12, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \Nobile\ and \Dhyana\"
+Didact Gothic,normal,400,DidactGothic-Regular.ttf,DidactGothic-Regular,Didact Gothic Regular,Copyright 2016 The Didact Gothic Project Authors (il.basso.buffo@gmail.com)
+Digital Numbers,normal,400,DigitalNumbers-Regular.ttf,DigitalNumbers-Regular,Digital Numbers,"Copyright (c) 2015, Stephan Ahlf (https://github.com/s-a/digital-numbers-font stephan.ahlf@googlemail.com)"
+Diplomata,normal,400,Diplomata-Regular.ttf,Diplomata-Regular,Diplomata,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Diplomata\"
+Diplomata SC,normal,400,DiplomataSC-Regular.ttf,DiplomataSC-Regular,Diplomata SC,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Diplomata\"
+DM Mono,normal,300,DMMono-Light.ttf,DMMono-Light,DM Mono Light,Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono)
+DM Mono,italic,300,DMMono-LightItalic.ttf,DMMono-LightItalic,DM Mono Light Italic,Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono)
+DM Mono,normal,400,DMMono-Regular.ttf,DMMono-Regular,DM Mono Regular,Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono)
+DM Mono,italic,400,DMMono-Italic.ttf,DMMono-Italic,DM Mono Italic,Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono)
+DM Mono,normal,500,DMMono-Medium.ttf,DMMono-Medium,DM Mono Medium,Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono)
+DM Mono,italic,500,DMMono-MediumItalic.ttf,DMMono-MediumItalic,DM Mono Medium Italic,Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono)
+DM Sans,normal,400,DMSans-Regular.ttf,DMSans-Regular,DM Sans Regular,Copyright 2014-2017 Indian Type Foundry (info@indiantypefoundry.com) with Reserved Font Name \'Poppins\'. Copyright 2019 Google LLC.
+DM Sans,italic,400,DMSans-Italic.ttf,DMSans-Italic,DM Sans Italic,Copyright 2014-2017 Indian Type Foundry (info@indiantypefoundry.com) with Reserved Font Name \'Poppins\'. Copyright 2019 Google LLC.
+DM Sans,normal,500,DMSans-Medium.ttf,DMSans-Medium,DM Sans Medium,Copyright 2014-2017 Indian Type Foundry (info@indiantypefoundry.com) with Reserved Font Name \'Poppins\'. Copyright 2019 Google LLC.
+DM Sans,italic,500,DMSans-MediumItalic.ttf,DMSans-MediumItalic,DM Sans Medium Italic,Copyright 2014-2017 Indian Type Foundry (info@indiantypefoundry.com) with Reserved Font Name \'Poppins\'. Copyright 2019 Google LLC.
+DM Sans,normal,700,DMSans-Bold.ttf,DMSans-Bold,DM Sans Bold,Copyright 2014-2017 Indian Type Foundry (info@indiantypefoundry.com) with Reserved Font Name \'Poppins\'. Copyright 2019 Google LLC.
+DM Sans,italic,700,DMSans-BoldItalic.ttf,DMSans-BoldItalic,DM Sans Bold Italic,Copyright 2014-2017 Indian Type Foundry (info@indiantypefoundry.com) with Reserved Font Name \'Poppins\'. Copyright 2019 Google LLC.
+DM Serif Display,normal,400,DMSerifDisplay-Regular.ttf,DMSerifDisplay-Regular,DM Serif Display Regular,"Copyright 2014 - 2017 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'. Copyright 2019 Google LLC."
+DM Serif Display,italic,400,DMSerifDisplay-Italic.ttf,DMSerifDisplay-Italic,DM Serif Display Italic,"Copyright 2014 - 2017 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'. Copyright 2019 Google LLC."
+DM Serif Text,normal,400,DMSerifText-Regular.ttf,DMSerifText-Regular,DM Serif Text Regular,"Copyright 2014 - 2017 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'. Copyright 2019 Google LLC."
+DM Serif Text,italic,400,DMSerifText-Italic.ttf,DMSerifText-Italic,DM Serif Text Italic,"Copyright 2014 - 2017 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'. Copyright 2019 Google LLC."
+Do Hyeon,normal,400,DoHyeon-Regular.ttf,DoHyeon-Regular,Do Hyeon Regular,Copyright 2018 The Do Hyeon Project Authors
+Dokdo,normal,400,Dokdo-Regular.ttf,Dokdo-Regular,Dokdo Regular,Copyright (c) 2005-2017 FONTRIX. All Rights Reserved.
+Domine,normal,400,Domine-Regular.ttf,Domine-Regular,Domine,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), Copyright (c) 2012, Brenda Gallo (gbrenda1987@gmail.com), with Reserved Font Name Domine."
+Domine,normal,700,Domine-Bold.ttf,Domine-Bold,Domine Bold,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), Copyright (c) 2012, Brenda Gallo (gbrenda1987@gmail.com), with Reserved Font Name Domine."
+Donegal One,normal,400,DonegalOne-Regular.ttf,DonegalOne-Regular,Donegal One,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name 'Donegal'"
+Doppio One,normal,400,DoppioOne-Regular.ttf,DoppioOne-Regular,Doppio One Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name \Doppio\"
+Dorsa,normal,400,Dorsa-Regular.ttf,Dorsa-Regular,Dorsa,"Copyright (c) 2011, Santiago Orozco (hi@typemade.mx), with Reserved Font Name \Dorsa\"
+Dosis,normal,200,Dosis[wght].ttf,Dosis-ExtraLight,Dosis ExtraLight,Copyright 2011 The Dosis Project Authors (impallari@gmail.com)
+Dr Sugiyama,normal,400,DrSugiyama-Regular.ttf,DrSugiyama-Regular,Dr Sugiyama Regular,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Dr Sujiyama\"
+Duru Sans,normal,400,DuruSans-Regular.ttf,DuruSans-Regular,Duru Sans,Copyright (c) 2010 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name Duru.
+Dynalight,normal,400,Dynalight-Regular.ttf,Dynalight-Regular,Dynalight,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Dynalight\"
+Eagle Lake,normal,400,EagleLake-Regular.ttf,EagleLake-Regular,Eagle Lake,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Eagle Lake\"
+East Sea Dokdo,normal,400,EastSeaDokdo-Regular.ttf,EastSeaDokdo-Regular,East Sea Dokdo Regular,Copyright (c) YoonDesign Inc. All Rights Reserved.
+Eater,normal,400,Eater-Regular.ttf,Eater-Regular,Eater,"Copyright (c) 2011, Vernon Adams DBA Typomondo (vern@newtypography.co.uk), with Reserved Font Name \Eater\"
+Eater Caps,normal,400,EaterCaps-Regular.ttf,EaterCaps-Regular,Eater Caps Regular,"Copyright (c) 2011, Vernon Adams DBA Typomondo (vern@newtypography.co.uk), with Reserved Font Name \Eater\"
+EB Garamond,normal,400,EBGaramond[wght].ttf,EBGaramond-Regular,EB Garamond Regular,Copyright 2017 The EB Garamond Project Authors (https://github.com/octaviopardo/EBGaramond12)
+EB Garamond,italic,400,EBGaramond-Italic[wght].ttf,EBGaramond-Italic,EB Garamond Italic,Copyright 2017 The EB Garamond Project Authors (https://github.com/octaviopardo/EBGaramond12)
+Economica,normal,400,Economica-Regular.ttf,Economica-Regular,Economica,"Copyright (c) 2012, Vicente Lamonaca (produccion.taller@gmail.com www.tipografia-montevideo.info www.tipotype.com)"
+Economica,italic,400,Economica-Italic.ttf,Economica-Italic,Economica Italic,"Copyright (c) 2012, Vicente Lamonaca (produccion.taller@gmail.com www.tipografia-montevideo.info www.tipotype.com)"
+Economica,normal,700,Economica-Bold.ttf,Economica-Bold,Economica Bold,"Copyright (c) 2012, Vicente Lamonaca (produccion.taller@gmail.com www.tipografia-montevideo.info www.tipotype.com)"
+Economica,italic,700,Economica-BoldItalic.ttf,Economica-BoldItalic,Economica Bold Italic,"Copyright (c) 2012, Vicente Lamonaca (produccion.taller@gmail.com www.tipografia-montevideo.info www.tipotype.com)"
+Eczar,normal,400,Eczar-Regular.ttf,Eczar-Regular,Eczar Regular,"Copyright (c) 2014, Vaibhav Singh (design) and Rosetta Type Foundry s.r.o. (post-production)."
+Eczar,normal,500,Eczar-Medium.ttf,Eczar-Medium,Eczar Medium,"Copyright (c) 2014, Vaibhav Singh (design) and Rosetta Type Foundry s.r.o. (post-production)."
+Eczar,normal,600,Eczar-SemiBold.ttf,Eczar-SemiBold,Eczar SemiBold,"Copyright (c) 2014, Vaibhav Singh (design) and Rosetta Type Foundry s.r.o. (post-production)."
+Eczar,normal,700,Eczar-Bold.ttf,Eczar-Bold,Eczar Bold,"Copyright (c) 2014, Vaibhav Singh (design) and Rosetta Type Foundry s.r.o. (post-production)."
+Eczar,normal,800,Eczar-ExtraBold.ttf,Eczar-ExtraBold,Eczar ExtraBold,"Copyright (c) 2014, Vaibhav Singh (design) and Rosetta Type Foundry s.r.o. (post-production)."
+Ek Mukta,normal,200,EkMukta-ExtraLight.ttf,EkMukta-ExtraLight,Ek Mukta ExtraLight,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Ek Mukta,normal,300,EkMukta-Light.ttf,EkMukta-Light,Ek Mukta Light,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Ek Mukta,normal,400,EkMukta-Regular.ttf,EkMukta-Regular,Ek Mukta Regular,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Ek Mukta,normal,500,EkMukta-Medium.ttf,EkMukta-Medium,Ek Mukta Medium,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Ek Mukta,normal,600,EkMukta-SemiBold.ttf,EkMukta-SemiBold,Ek Mukta SemiBold,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Ek Mukta,normal,700,EkMukta-Bold.ttf,EkMukta-Bold,Ek Mukta Bold,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Ek Mukta,normal,800,EkMukta-ExtraBold.ttf,EkMukta-ExtraBold,Ek Mukta ExtraBold,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Electrolize,normal,400,Electrolize-Regular.ttf,Electrolize-Regular,Electrolize,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Electrolize\ This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+El Messiri,normal,400,ElMessiri[wght].ttf,ElMessiri-Regular,El Messiri Regular,Copyright 2015 The El Messiri Project Authors (https://github.com/Gue3bara/El-Messiri)
+Elsie,normal,400,Elsie-Regular.ttf,Elsie-Regular,Elsie Regular,"Copyright (c) 2010-2012, Alejandro Inler (alejandroinler@gmail.com), with Reserved Font Name \'Elsie\'"
+Elsie,normal,900,Elsie-Black.ttf,Elsie-Black,Elsie Black,"Copyright (c) 2010-2012, Alejandro Inler (alejandroinler@gmail.com), with Reserved Font Name \'Elsie\'"
+Elsie Swash Caps,normal,400,ElsieSwashCaps-Regular.ttf,ElsieSwashCaps-Regular,Elsie Swash Caps Regular,"Copyright (c) 2010-2012, Alejandro Inler (alejandroinler@gmail.com), with Reserved Font Name \'Elsie\'"
+Elsie Swash Caps,normal,900,ElsieSwashCaps-Black.ttf,ElsieSwashCaps-Black,Elsie Swash Caps Black,"Copyright (c) 2010-2012, Alejandro Inler (alejandroinler@gmail.com), with Reserved Font Name \'Elsie\'"
+Emblema One,normal,400,EmblemaOne-Regular.ttf,EmblemaOne-Regular,Emblema One,Copyright (c) 2011 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Names \Emblema\ and \Emblema One\
+Emilys Candy,normal,400,EmilysCandy-Regular.ttf,EmilysCandy-Regular,Emilys Candy,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Emilys Candy\"
+Encode Sans,normal,400,"EncodeSans[wdth,wght].ttf",EncodeSans-CondensedThin,Encode Sans Condensed Thin,"Copyright 2020 The Encode Project Authors (https://github.com/thundernixon/Encode-Sans), with Reserved Font Name \'Encode Sans\'."
+Encode Sans Condensed,normal,100,EncodeSansCondensed-Thin.ttf,EncodeSansCondensed-Thin,Encode Sans Condensed Thin,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,200,EncodeSansCondensed-ExtraLight.ttf,EncodeSansCondensed-ExtraLight,Encode Sans Condensed ExtraLight,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,300,EncodeSansCondensed-Light.ttf,EncodeSansCondensed-Light,Encode Sans Condensed Light,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,400,EncodeSansCondensed-Regular.ttf,EncodeSansCondensed-Regular,Encode Sans Condensed Regular,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,500,EncodeSansCondensed-Medium.ttf,EncodeSansCondensed-Medium,Encode Sans Condensed Medium,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,600,EncodeSansCondensed-SemiBold.ttf,EncodeSansCondensed-SemiBold,Encode Sans Condensed SemiBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,700,EncodeSansCondensed-Bold.ttf,EncodeSansCondensed-Bold,Encode Sans Condensed Bold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,800,EncodeSansCondensed-ExtraBold.ttf,EncodeSansCondensed-ExtraBold,Encode Sans Condensed ExtraBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Condensed,normal,900,EncodeSansCondensed-Black.ttf,EncodeSansCondensed-Black,Encode Sans Condensed Black,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,100,EncodeSansExpanded-Thin.ttf,EncodeSansExpanded-Thin,Encode Sans Expanded Thin,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,200,EncodeSansExpanded-ExtraLight.ttf,EncodeSansExpanded-ExtraLight,Encode Sans Expanded ExtraLight,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,300,EncodeSansExpanded-Light.ttf,EncodeSansExpanded-Light,Encode Sans Expanded Light,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,400,EncodeSansExpanded-Regular.ttf,EncodeSansExpanded-Regular,Encode Sans Expanded Regular,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,500,EncodeSansExpanded-Medium.ttf,EncodeSansExpanded-Medium,Encode Sans Expanded Medium,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,600,EncodeSansExpanded-SemiBold.ttf,EncodeSansExpanded-SemiBold,Encode Sans Expanded SemiBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,700,EncodeSansExpanded-Bold.ttf,EncodeSansExpanded-Bold,Encode Sans Expanded Bold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,800,EncodeSansExpanded-ExtraBold.ttf,EncodeSansExpanded-ExtraBold,Encode Sans Expanded ExtraBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Expanded,normal,900,EncodeSansExpanded-Black.ttf,EncodeSansExpanded-Black,Encode Sans Expanded Black,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,100,EncodeSansSemiCondensed-Thin.ttf,EncodeSansSemiCondensed-Thin,Encode Sans Semi Condensed Thin,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,200,EncodeSansSemiCondensed-ExtraLight.ttf,EncodeSansSemiCondensed-ExtraLight,Encode Sans Semi Condensed ExtraLight,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,300,EncodeSansSemiCondensed-Light.ttf,EncodeSansSemiCondensed-Light,Encode Sans Semi Condensed Light,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,400,EncodeSansSemiCondensed-Regular.ttf,EncodeSansSemiCondensed-Regular,Encode Sans Semi Condensed Regular,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,500,EncodeSansSemiCondensed-Medium.ttf,EncodeSansSemiCondensed-Medium,Encode Sans Semi Condensed Medium,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,600,EncodeSansSemiCondensed-SemiBold.ttf,EncodeSansSemiCondensed-SemiBold,Encode Sans Semi Condensed SemiBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,700,EncodeSansSemiCondensed-Bold.ttf,EncodeSansSemiCondensed-Bold,Encode Sans Semi Condensed Bold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,800,EncodeSansSemiCondensed-ExtraBold.ttf,EncodeSansSemiCondensed-ExtraBold,Encode Sans Semi Condensed ExtraBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Condensed,normal,900,EncodeSansSemiCondensed-Black.ttf,EncodeSansSemiCondensed-Black,Encode Sans Semi Condensed Black,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,100,EncodeSansSemiExpanded-Thin.ttf,EncodeSansSemiExpanded-Thin,Encode Sans Semi Expanded Thin,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,200,EncodeSansSemiExpanded-ExtraLight.ttf,EncodeSansSemiExpanded-ExtraLight,Encode Sans Semi Expanded ExtraLight,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,300,EncodeSansSemiExpanded-Light.ttf,EncodeSansSemiExpanded-Light,Encode Sans Semi Expanded Light,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,400,EncodeSansSemiExpanded-Regular.ttf,EncodeSansSemiExpanded-Regular,Encode Sans Semi Expanded Regular,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,500,EncodeSansSemiExpanded-Medium.ttf,EncodeSansSemiExpanded-Medium,Encode Sans Semi Expanded Medium,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,600,EncodeSansSemiExpanded-SemiBold.ttf,EncodeSansSemiExpanded-SemiBold,Encode Sans Semi Expanded SemiBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,700,EncodeSansSemiExpanded-Bold.ttf,EncodeSansSemiExpanded-Bold,Encode Sans Semi Expanded Bold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,800,EncodeSansSemiExpanded-ExtraBold.ttf,EncodeSansSemiExpanded-ExtraBold,Encode Sans Semi Expanded ExtraBold,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Encode Sans Semi Expanded,normal,900,EncodeSansSemiExpanded-Black.ttf,EncodeSansSemiExpanded-Black,Encode Sans Semi Expanded Black,"Copyright 2012 The Encode Project Authors (impallari@gmail.com), with Reserved Font Name \Encode Sans\."
+Engagement,normal,400,Engagement-Regular.ttf,Engagement-Regular,Engagement,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Engagement\"
+Englebert,normal,400,Englebert-Regular.ttf,Englebert-Regular,Englebert,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name 'Englebert'"
+Enriqueta,normal,400,Enriqueta-Regular.ttf,Enriqueta-Regular,Enriqueta Regular,Copyright 2018 The Enriqueta Project Authors (https://github.com/vv-monsalve/Enriqueta_2019)
+Enriqueta,normal,500,Enriqueta-Medium.ttf,Enriqueta-Medium,Enriqueta Medium,Copyright 2018 The Enriqueta Project Authors (https://github.com/vv-monsalve/Enriqueta_2019)
+Enriqueta,normal,600,Enriqueta-SemiBold.ttf,Enriqueta-SemiBold,Enriqueta SemiBold,Copyright 2018 The Enriqueta Project Authors (https://github.com/vv-monsalve/Enriqueta_2019)
+Enriqueta,normal,700,Enriqueta-Bold.ttf,Enriqueta-Bold,Enriqueta Bold,Copyright 2018 The Enriqueta Project Authors (https://github.com/vv-monsalve/Enriqueta_2019)
+Erica One,normal,400,EricaOne-Regular.ttf,EricaOne-Regular,Erica One,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com), with Reserved Font Names \Erica\ \Erica One\"
+Esteban,normal,400,Esteban-Regular.ttf,Esteban,Esteban,"Copyright (c) 2011, Angelica Diaz Rivera (www.typereview.wordpress.com angiecina@gmail.com), with Reserved Font Name \Esteban\"
+Euphoria Script,normal,400,EuphoriaScript-Regular.ttf,EuphoriaScript-Regular,Euphoria Script,"Copyright (c) 2012 Sabrina Mariela Lopez (typesenses@live.com.ar), with Reserved Font Name \Euphoria Script\"
+Ewert,normal,400,Ewert-Regular.ttf,Ewert-Regular,Ewert,"Copyright (c) 2011, Johan Kallas (johankallas@gmail.com), Copyright (c) 2011 Mihkel Virkus (mihkelvirkus@gmail.com) with Reserved Font Name Ewert."
+Exo 2,normal,400,Exo2[wght].ttf,Exo2-Regular,Exo 2 Regular,Copyright 2013 The Exo 2 Project Authors (https://github.com/NDISCOVER/Exo-2.0)
+Exo 2,italic,400,Exo2-Italic[wght].ttf,Exo2-Italic,Exo 2 Italic,Copyright 2013 The Exo 2 Project Authors (https://github.com/NDISCOVER/Exo-2.0)
+Exo,normal,400,Exo[wght].ttf,Exo-Thin,Exo Thin,Copyright 2017 The Exo Project Authors (https://github.com/NDISCOVER/Exo-1.0)
+Exo,italic,400,Exo-Italic[wght].ttf,Exo-ThinItalic,Exo Thin Italic,Copyright 2017 The Exo Project Authors (https://github.com/NDISCOVER/Exo-1.0)
+Expletus Sans,normal,400,ExpletusSans-Regular.ttf,ExpletusSans,Expletus Sans,Copyright (c) 2009 by Designtown (jasper@designtown.nl). All rights reserved.
+Expletus Sans,italic,400,ExpletusSans-Italic.ttf,ExpletusSans-Italic,Expletus Sans Italic,Copyright (c) 2009 by Designtown (jasper@designtown.nl). All rights reserved.
+Expletus Sans,normal,500,ExpletusSans-Medium.ttf,ExpletusSans-Medium,Expletus Sans Medium,Copyright (c) 2010 by Jasper de Waard (jasper@designtown.nl). All rights reserved.
+Expletus Sans,italic,500,ExpletusSans-MediumItalic.ttf,ExpletusSans-MediumItalic,Expletus Sans Medium Italic,Copyright (c) 2010 by Jasper de Waard (jasper@designtown.nl). All rights reserved.
+Expletus Sans,normal,600,ExpletusSans-SemiBold.ttf,ExpletusSans-SemiBold,Expletus Sans SemiBold,Copyright (c) 2010 by Jasper de Waard (jasper@designtown.nl). All rights reserved.
+Expletus Sans,italic,600,ExpletusSans-SemiBoldItalic.ttf,ExpletusSans-SemiBoldItalic,Expletus Sans SemiBold Italic,Copyright (c) 2010 by Jasper de Waard (jasper@designtown.nl). All rights reserved.
+Expletus Sans,normal,700,ExpletusSans-Bold.ttf,ExpletusSans-Bold,Expletus Sans Bold,Copyright (c) 2009 by Jasper de Waard (jasper@designtown.nl). All rights reserved.
+Expletus Sans,italic,700,ExpletusSans-BoldItalic.ttf,ExpletusSans-BoldItalic,Expletus Sans Bold Italic,Copyright (c) 2009 by Jasper de Waard (jasper@designtown.nl). All rights reserved.
+Fahkwang,normal,200,Fahkwang-ExtraLight.ttf,Fahkwang-ExtraLight,Fahkwang ExtraLight,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,italic,200,Fahkwang-ExtraLightItalic.ttf,Fahkwang-ExtraLightItalic,Fahkwang ExtraLight Italic,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,normal,300,Fahkwang-Light.ttf,Fahkwang-Light,Fahkwang Light,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,italic,300,Fahkwang-LightItalic.ttf,Fahkwang-LightItalic,Fahkwang Light Italic,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,normal,400,Fahkwang-Regular.ttf,Fahkwang-Regular,Fahkwang Regular,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,italic,400,Fahkwang-Italic.ttf,Fahkwang-Italic,Fahkwang Italic,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,normal,500,Fahkwang-Medium.ttf,Fahkwang-Medium,Fahkwang Medium,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,italic,500,Fahkwang-MediumItalic.ttf,Fahkwang-MediumItalic,Fahkwang Medium Italic,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,normal,600,Fahkwang-SemiBold.ttf,Fahkwang-SemiBold,Fahkwang SemiBold,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,italic,600,Fahkwang-SemiBoldItalic.ttf,Fahkwang-SemiBoldItalic,Fahkwang SemiBold Italic,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,normal,700,Fahkwang-Bold.ttf,Fahkwang-Bold,Fahkwang Bold,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fahkwang,italic,700,Fahkwang-BoldItalic.ttf,Fahkwang-BoldItalic,Fahkwang Bold Italic,Copyright 2018 The Fahkwang Project Authors (https://github.com/cadsondemak/Fah-Kwang)
+Fanwood Text,normal,400,FanwoodText-Regular.ttf,FanwoodText-Regular,Fanwood Text,"Copyright (c) 2011, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Fanwood Text,italic,400,FanwoodText-Italic.ttf,FanwoodText-Italic,Fanwood Text Italic,"Copyright (c) 2011, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Farro,normal,300,Farro-Light.ttf,Farro-Light,Farro Light,Copyright 2018 The Farro Project Authors (https://github.com/grayscaleltd/farro)
+Farro,normal,400,Farro-Regular.ttf,Farro-Regular,Farro Regular,Copyright 2018 The Farro Project Authors (https://github.com/grayscaleltd/farro)
+Farro,normal,500,Farro-Medium.ttf,Farro-Medium,Farro Medium,Copyright 2018 The Farro Project Authors (https://github.com/grayscaleltd/farro)
+Farro,normal,700,Farro-Bold.ttf,Farro-Bold,Farro Bold,Copyright 2018 The Farro Project Authors (https://github.com/grayscaleltd/farro)
+Farsan,normal,400,Farsan-Regular.ttf,Farsan-Regular,Farsan Regular,Copyright (c) 2014 Pooja Saxena (www.poojasaxena.in)
+Fascinate,normal,400,Fascinate-Regular.ttf,Fascinate-Regular,Fascinate,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Fascinate\"
+Fascinate Inline,normal,400,FascinateInline-Regular.ttf,FascinateInline-Regular,Fascinate Inline,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Fascinate Inline\"
+Faster One,normal,400,FasterOne-Regular.ttf,FasterOne-Regular,Faster One,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Faster'"
+Fasthand,normal,400,Fasthand-Regular.ttf,Fasthand-Regular,Fasthand,"Copyright (c) 2012, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Fasthand"
+Fauna One,normal,400,FaunaOne-Regular.ttf,FaunaOne-Regular,Fauna One,"Copyright (c) 2013, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Fauna'"
+Faustina,normal,400,Faustina[wght].ttf,Faustina-Regular,Faustina Regular,Copyright 2016 The Faustina Project Authors (https://github.com/Omnibus-Type/Faustina)
+Faustina,italic,400,Faustina-Italic[wght].ttf,Faustina-Italic,Faustina Italic,Copyright 2016 The Faustina Project Authors (https://github.com/Omnibus-Type/Faustina)
+Federant,normal,400,Federant-Regular.ttf,Federant-Regular,Federant,"Copyright (c) 2011, Cyreal (www.cyreal.org), with Reserved Font Name 'Federant'."
+Federo,normal,400,Federo-Regular.ttf,Federo-Regular,Federo,Copyright (c) 2011 by Olexa M. Volochay | Cyreal.org (a@cyreal.org). All rights reserved.
+Felipa,normal,400,Felipa-Regular.ttf,Felipa-Regular,Felipa,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Felipa\"
+Fenix,normal,400,Fenix-Regular.ttf,Fenix-Regular,Fenix,"Copyright (c) 2012, Fernando Diaz (www.ferfolio.com fer@ferfolio.com) with Reserved Font Name 'Fenix'"
+Finger Paint,normal,400,FingerPaint-Regular.ttf,FingerPaint-Regular,Finger Paint Regular,"Copyright (c) 2011 by Ralph du Carrois, with Reserved Font Name \'Finger Paint\'"
+Fira Code,normal,300,FiraCode[wght].ttf,FiraCode-Light,Fira Code Light,Copyright 2012-2015 The Fira Code Project Authors (https://github.com/tonsky/FiraCode)
+Fira Mono,normal,400,FiraMono-Regular.ttf,FiraMono-Regular,Fira Mono Regular,"Digitized data copyright  2012-2015, The Mozilla Foundation and Telefonica S.A."
+Fira Mono,normal,500,FiraMono-Medium.ttf,FiraMono-Medium,Fira Mono Medium,"Digitized data copyright  2012-2015, The Mozilla Foundation and Telefonica S.A."
+Fira Mono,normal,700,FiraMono-Bold.ttf,FiraMono-Bold,Fira Mono Bold,"Digitized data copyright  2012-2015, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,100,FiraSans-Thin.ttf,FiraSans-Thin,Fira Sans Thin,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,100,FiraSans-ThinItalic.ttf,FiraSans-ThinItalic,Fira Sans Thin Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,200,FiraSans-ExtraLight.ttf,FiraSans-ExtraLight,Fira Sans ExtraLight,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,200,FiraSans-ExtraLightItalic.ttf,FiraSans-ExtraLightItalic,Fira Sans ExtraLight Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,300,FiraSans-Light.ttf,FiraSans-Light,Fira Sans Light,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,300,FiraSans-LightItalic.ttf,FiraSans-LightItalic,Fira Sans Light Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,400,FiraSans-Regular.ttf,FiraSans-Regular,Fira Sans Regular,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,400,FiraSans-Italic.ttf,FiraSans-Italic,Fira Sans Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,500,FiraSans-Medium.ttf,FiraSans-Medium,Fira Sans Medium,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,500,FiraSans-MediumItalic.ttf,FiraSans-MediumItalic,Fira Sans Medium Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,600,FiraSans-SemiBold.ttf,FiraSans-SemiBold,Fira Sans SemiBold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,600,FiraSans-SemiBoldItalic.ttf,FiraSans-SemiBoldItalic,Fira Sans SemiBold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,700,FiraSans-Bold.ttf,FiraSans-Bold,Fira Sans Bold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,700,FiraSans-BoldItalic.ttf,FiraSans-BoldItalic,Fira Sans Bold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,800,FiraSans-ExtraBold.ttf,FiraSans-ExtraBold,Fira Sans ExtraBold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,800,FiraSans-ExtraBoldItalic.ttf,FiraSans-ExtraBoldItalic,Fira Sans ExtraBold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,normal,900,FiraSans-Black.ttf,FiraSans-Black,Fira Sans Black,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans,italic,900,FiraSans-BlackItalic.ttf,FiraSans-BlackItalic,Fira Sans Black Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,100,FiraSansCondensed-Thin.ttf,FiraSansCondensed-Thin,Fira Sans Condensed Thin,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,100,FiraSansCondensed-ThinItalic.ttf,FiraSansCondensed-ThinItalic,Fira Sans Condensed Thin Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,200,FiraSansCondensed-ExtraLight.ttf,FiraSansCondensed-ExtraLight,Fira Sans Condensed ExtraLight,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,200,FiraSansCondensed-ExtraLightItalic.ttf,FiraSansCondensed-ExtraLightItalic,Fira Sans Condensed ExtraLight Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,300,FiraSansCondensed-Light.ttf,FiraSansCondensed-Light,Fira Sans Condensed Light,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,300,FiraSansCondensed-LightItalic.ttf,FiraSansCondensed-LightItalic,Fira Sans Condensed Light Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,400,FiraSansCondensed-Regular.ttf,FiraSansCondensed-Regular,Fira Sans Condensed Regular,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,400,FiraSansCondensed-Italic.ttf,FiraSansCondensed-Italic,Fira Sans Condensed Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,500,FiraSansCondensed-Medium.ttf,FiraSansCondensed-Medium,Fira Sans Condensed Medium,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,500,FiraSansCondensed-MediumItalic.ttf,FiraSansCondensed-MediumItalic,Fira Sans Condensed Medium Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,600,FiraSansCondensed-SemiBold.ttf,FiraSansCondensed-SemiBold,Fira Sans Condensed SemiBold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,600,FiraSansCondensed-SemiBoldItalic.ttf,FiraSansCondensed-SemiBoldItalic,Fira Sans Condensed SemiBold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,700,FiraSansCondensed-Bold.ttf,FiraSansCondensed-Bold,Fira Sans Condensed Bold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,700,FiraSansCondensed-BoldItalic.ttf,FiraSansCondensed-BoldItalic,Fira Sans Condensed Bold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,800,FiraSansCondensed-ExtraBold.ttf,FiraSansCondensed-ExtraBold,Fira Sans Condensed ExtraBold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,800,FiraSansCondensed-ExtraBoldItalic.ttf,FiraSansCondensed-ExtraBoldItalic,Fira Sans Condensed ExtraBold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,normal,900,FiraSansCondensed-Black.ttf,FiraSansCondensed-Black,Fira Sans Condensed Black,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Condensed,italic,900,FiraSansCondensed-BlackItalic.ttf,FiraSansCondensed-BlackItalic,Fira Sans Condensed Black Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,100,FiraSansExtraCondensed-Thin.ttf,FiraSansExtraCondensed-Thin,Fira Sans Extra Condensed Thin,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,100,FiraSansExtraCondensed-ThinItalic.ttf,FiraSansExtraCondensed-ThinItalic,Fira Sans Extra Condensed Thin Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,200,FiraSansExtraCondensed-ExtraLight.ttf,FiraSansExtraCondensed-ExtraLight,Fira Sans Extra Condensed ExtraLight,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,200,FiraSansExtraCondensed-ExtraLightItalic.ttf,FiraSansExtraCondensed-ExtraLightItalic,Fira Sans Extra Condensed ExtraLight Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,300,FiraSansExtraCondensed-Light.ttf,FiraSansExtraCondensed-Light,Fira Sans Extra Condensed Light,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,300,FiraSansExtraCondensed-LightItalic.ttf,FiraSansExtraCondensed-LightItalic,Fira Sans Extra Condensed Light Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,400,FiraSansExtraCondensed-Regular.ttf,FiraSansExtraCondensed-Regular,Fira Sans Extra Condensed Regular,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,400,FiraSansExtraCondensed-Italic.ttf,FiraSansExtraCondensed-Italic,Fira Sans Extra Condensed Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,500,FiraSansExtraCondensed-Medium.ttf,FiraSansExtraCondensed-Medium,Fira Sans Extra Condensed Medium,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,500,FiraSansExtraCondensed-MediumItalic.ttf,FiraSansExtraCondensed-MediumItalic,Fira Sans Extra Condensed Medium Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,600,FiraSansExtraCondensed-SemiBold.ttf,FiraSansExtraCondensed-SemiBold,Fira Sans Extra Condensed SemiBold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,600,FiraSansExtraCondensed-SemiBoldItalic.ttf,FiraSansExtraCondensed-SemiBoldItalic,Fira Sans Extra Condensed SemiBold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,700,FiraSansExtraCondensed-Bold.ttf,FiraSansExtraCondensed-Bold,Fira Sans Extra Condensed Bold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,700,FiraSansExtraCondensed-BoldItalic.ttf,FiraSansExtraCondensed-BoldItalic,Fira Sans Extra Condensed Bold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,800,FiraSansExtraCondensed-ExtraBold.ttf,FiraSansExtraCondensed-ExtraBold,Fira Sans Extra Condensed ExtraBold,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,800,FiraSansExtraCondensed-ExtraBoldItalic.ttf,FiraSansExtraCondensed-ExtraBoldItalic,Fira Sans Extra Condensed ExtraBold Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,normal,900,FiraSansExtraCondensed-Black.ttf,FiraSansExtraCondensed-Black,Fira Sans Extra Condensed Black,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fira Sans Extra Condensed,italic,900,FiraSansExtraCondensed-BlackItalic.ttf,FiraSansExtraCondensed-BlackItalic,Fira Sans Extra Condensed Black Italic,"Digitized data copyright 2012-2016, The Mozilla Foundation and Telefonica S.A."
+Fjalla One,normal,400,FjallaOne-Regular.ttf,FjallaOne-Regular,Fjalla One,"Copyright (c) 2011 by Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name 'Fjalla'"
+Fjord One,normal,400,FjordOne-Regular.ttf,Fjord-One,Fjord One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Names \Fjord\ and \Fjord One\ This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: http://scripts.sil.org/OFL"
+Flamenco,normal,300,Flamenco-Light.ttf,Flamenco-Light,Flamenco Light,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com), with Reserved Font Names \Flamenco\"
+Flamenco,normal,400,Flamenco-Regular.ttf,Flamenco-Regular,Flamenco Regular,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com), with Reserved Font Names \Flamenco\"
+Flavors,normal,400,Flavors-Regular.ttf,Flavors-Regular,Flavors Regular,"Copyright (c) 2011 by Font Diner, Inc DBA Sideshow (diner@fontdiner.com) with Reserved Font Name \Flavors\"
+Fondamento,normal,400,Fondamento-Regular.ttf,Fondamento-Regular,Fondamento Regular,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Fondamento\"
+Fondamento,italic,400,Fondamento-Italic.ttf,Fondamento-Italic,Fondamento-Italic,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Fondamento Italic\"
+Forum,normal,400,Forum-Regular.ttf,Forum,Forum,"Copyright (c) 2011, Denis Masharov <denis.masharov@gmail.com>. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Francois One,normal,400,FrancoisOne-Regular.ttf,FrancoisOne-Regular,Francois One Regular,Copyright 2011 The Francois One Project Authors (contact@sansoxygen.com)
+Frank Ruhl Libre,normal,300,FrankRuhlLibre-Light.ttf,FrankRuhlLibre-Light,Frank Ruhl Libre Light,Copyright 2015 The Frank Ruhl Libre Project Authors.
+Frank Ruhl Libre,normal,400,FrankRuhlLibre-Regular.ttf,FrankRuhlLibre-Regular,Frank Ruhl Libre Regular,Copyright 2015 The Frank Ruhl Libre Project Authors.
+Frank Ruhl Libre,normal,500,FrankRuhlLibre-Medium.ttf,FrankRuhlLibre-Medium,Frank Ruhl Libre Medium,Copyright 2015 The Frank Ruhl Libre Project Authors.
+Frank Ruhl Libre,normal,700,FrankRuhlLibre-Bold.ttf,FrankRuhlLibre-Bold,Frank Ruhl Libre Bold,Copyright 2015 The Frank Ruhl Libre Project Authors.
+Frank Ruhl Libre,normal,900,FrankRuhlLibre-Black.ttf,FrankRuhlLibre-Black,Frank Ruhl Libre Black,Copyright 2015 by Yanek Iontef. All rights reserved.
+Freckle Face,normal,400,FreckleFace-Regular.ttf,FreckleFace-Regular,Freckle Face,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Freckle Face\"
+Fredericka the Great,normal,400,FrederickatheGreat-Regular.ttf,FrederickatheGreat,Fredericka the Great,"Copyright (c) 2011 by Font Diner, Inc DBA Tart Workshop (diner@fontdiner.com) with Reseved Font Name \Fredericka the Great\"
+Fredoka One,normal,400,FredokaOne-Regular.ttf,FredokaOne-Regular,Fredoka One,"Copyright (c) 2011 Milena B Brandao (milenabbrandao@gmail.com), with Reserved Font Name \Fredoka\"
+Freehand,normal,400,Freehand.ttf,Freehand,Freehand,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Freethand. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Fresca,normal,400,Fresca-Regular.ttf,Fresca-Regular,Fresca-Regular,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Fresca\"
+Frijole,normal,400,Frijole-Regular.ttf,Frijole,Frijole,"Copyright (c) 2011 by Font Diner, Inc DBA Sideshow (diner@fontdiner.com) with Reserved Font Name \Frijole\"
+Fruktur,normal,400,Fruktur-Regular.ttf,Fruktur-Regular,Fruktur,"Copyright (c) 2013, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name 'Fruktur'"
+Fugaz One,normal,400,FugazOne-Regular.ttf,FugazOne-Regular,Fugaz One,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com), with Reserved Font Names \Fugaz\ and \Fugaz One\"
+Gabriela,normal,400,Gabriela-Regular.ttf,Gabriela-Regular,Gabriela Regular,"Copyright 2013 The Gabriela Project Authors (edu@tipo.net.ar), with Reserved Font Name \Gabriela\."
+Gaegu,normal,300,Gaegu-Light.ttf,Gaegu-Light,Gaegu Light,Copyright 2018 The Gaegu Project Authors
+Gaegu,normal,400,Gaegu-Regular.ttf,Gaegu-Regular,Gaegu Regular,Copyright 2018 The Gaegu Project Authors
+Gaegu,normal,700,Gaegu-Bold.ttf,Gaegu-Bold,Gaegu Bold,Copyright 2018 The Gaegu Project Authors
+Gafata,normal,400,Gafata-Regular.ttf,Gafata-Regular,Gafata,"Copyright (c) 2010-2012, Lautaro Hourcade (lautaro.uy@gmail.com), with Reserved Font Name 'Gafata'"
+Galada,normal,400,Galada-Regular.ttf,Galada-Regular,Galada Regular,Copyright (c) 2010 by Pablo Impallari (www.impallari.com). Copyright (c) 2015 by black foundry (www.black-foundry.com)
+Galdeano,normal,400,Galdeano-Regular.ttf,Galdeano-Regular,Galdeano Regular,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar dario@tipo.net.ar), with Reserved Font Name \Galdeano\."
+Galindo,normal,400,Galindo-Regular.ttf,Galindo-Regular,Galindo,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Galindo\"
+Gamja Flower,normal,400,GamjaFlower-Regular.ttf,GamjaFlower-Regular,Gamja Flower Regular,Copyright (c) YoonDesign Inc. All Rights Reserved.
+Gayathri,normal,100,Gayathri-Thin.ttf,Gayathri-Thin,Gayathri Thin,Copyright 2019 The Gayathri Project Authors (https://gitlab.com/smc/fonts/gayathri)
+Gayathri,normal,400,Gayathri-Regular.ttf,Gayathri-Regular,Gayathri Regular,Copyright 2019 The Gayathri Project Authors (https://gitlab.com/smc/fonts/gayathri)
+Gayathri,normal,700,Gayathri-Bold.ttf,Gayathri-Bold,Gayathri Bold,Copyright 2019 The Gayathri Project Authors (https://gitlab.com/smc/fonts/gayathri)
+Gelasio,normal,400,Gelasio-Regular.ttf,Gelasio-Regular,Gelasio Regular,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,italic,400,Gelasio-Italic.ttf,Gelasio-Italic,Gelasio Italic,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,normal,500,Gelasio-Medium.ttf,Gelasio-Medium,Gelasio Medium,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,italic,500,Gelasio-MediumItalic.ttf,Gelasio-MediumItalic,Gelasio Medium Italic,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,normal,600,Gelasio-SemiBold.ttf,Gelasio-SemiBold,Gelasio SemiBold,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,italic,600,Gelasio-SemiBoldItalic.ttf,Gelasio-SemiBoldItalic,Gelasio SemiBold Italic,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,normal,700,Gelasio-Bold.ttf,Gelasio-Bold,Gelasio Bold,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gelasio,italic,700,Gelasio-BoldItalic.ttf,Gelasio-BoldItalic,Gelasio Bold Italic,Copyright 2019 The Gelasio Project Authors (https://github.com/SorkinType/Gelasio)
+Gemunu Libre,normal,200,GemunuLibre-ExtraLight.ttf,GemunuLibre-ExtraLight,Gemunu Libre ExtraLight,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gemunu Libre,normal,300,GemunuLibre-Light.ttf,GemunuLibre-Light,Gemunu Libre Light,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gemunu Libre,normal,400,GemunuLibre-Regular.ttf,GemunuLibre-Regular,Gemunu Libre Regular,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gemunu Libre,normal,500,GemunuLibre-Medium.ttf,GemunuLibre-Medium,Gemunu Libre Medium,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gemunu Libre,normal,600,GemunuLibre-SemiBold.ttf,GemunuLibre-SemiBold,Gemunu Libre SemiBold,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gemunu Libre,normal,700,GemunuLibre-Bold.ttf,GemunuLibre-Bold,Gemunu Libre Bold,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gemunu Libre,normal,800,GemunuLibre-ExtraBold.ttf,GemunuLibre-ExtraBold,Gemunu Libre ExtraBold,Copyright (c) 1996-2015 Pushpananda Ekanayake (pushpanandae@gmail.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar) Copyright (c) 2015 Mooniak (hello@mooniak.com)
+Gentium Basic,normal,400,GenBasR.ttf,GentiumBasic,Gentium Basic,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Basic,italic,400,GenBasI.ttf,GentiumBasic-Italic,Gentium Basic Italic,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Basic,normal,700,GenBasB.ttf,GentiumBasic-Bold,Gentium Basic Bold,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Basic,italic,700,GenBasBI.ttf,GentiumBasic-BoldItalic,Gentium Basic Bold Italic,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Book Basic,normal,400,GenBkBasR.ttf,GentiumBookBasic,Gentium Book Basic,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Book Basic,italic,400,GenBkBasI.ttf,GentiumBookBasic-Italic,Gentium Book Basic Italic,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Book Basic,normal,700,GenBkBasB.ttf,GentiumBookBasic-Bold,Gentium Book Basic Bold,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Gentium Book Basic,italic,700,GenBkBasBI.ttf,GentiumBookBasic-BoldItalic,Gentium Book Basic Bold Italic,"Copyright (c) 2003-2013, SIL International (http://www.sil.org/) with Reserved Font Names \Gentium\ and \SIL\"
+Geo,normal,400,Geo-Regular.ttf,Geo-Regular,Geo,"Copyright (c) 2000-2010, Ben Weiner (ben@readingtype.org.uk), with Reserved Font Name Geo."
+Geo,italic,400,Geo-Oblique.ttf,Geo-Oblique,Geo Oblique,"Copyright (c) 2000-2010, Ben Weiner (ben@readingtype.org.uk), with Reserved Font Name Geo."
+Geostar,normal,400,Geostar-Regular.ttf,Geostar-Regular,Geostar,"Copyright (c) 2011, Admix Designs (http://www.admixdesigns.com joe@admixdesigns.com) with Reserved Font Name Geostar."
+Geostar Fill,normal,400,GeostarFill-Regular.ttf,GeostarFill-Regular,Geostar Fill,"Copyright (c) 2011, Admix Designs (http://www.admixdesigns.com joe@admixdesigns.com) with Reserved Font Name Geostar."
+Germania One,normal,400,GermaniaOne-Regular.ttf,GermaniaOne-Regular,Germania One,"Copyright (c) 2011 by John Vargas Beltran (john.vargasbeltran@gmail.com), with Reserved Font Name \Germania One\"
+GFS Didot,normal,400,GFSDidot-Regular.ttf,GFSDidot-Regular,GFS Didot Regular,"Copyright (c) Takis Katsoulidis and George D. Matthiopoulos (gfs@greekfontsociety.gr), 2001. All rights reserved."
+GFS Neohellenic,normal,400,GFSNeohellenic.ttf,GFSNeohellenic-Regular,GFS Neohellenic Regular,"Copyright (c) Takis Katsoulidis and George D. Matthiopoulos (gfs@greekfontsociety.gr), 1993-2001. All rights reserved."
+GFS Neohellenic,italic,400,GFSNeohellenicItalic.ttf,GFSNeohellenic-Italic,GFS Neohellenic Italic,"Copyright (c) Takis Katsoulidis and George D. Matthiopoulos (gfs@greekfontsociety.gr) , 2001. All rights reserved."
+GFS Neohellenic,normal,700,GFSNeohellenicBold.ttf,GFSNeohellenic-Bold,GFS Neohellenic Bold,"Copyright (c) Designed by Takis Katsoulidis and George D. Matthiopoulos (gfs@greekfontsociety.gr)., 2001. All rights reserved."
+GFS Neohellenic,italic,700,GFSNeohellenicBoldItalic.ttf,GFSNeohellenic-BoldItalic,GFS Neohellenic Bold Italic,"Copyright (c) Designed by Takis Katsoulidis and George D. Matthiopoulos (gfs@greekfontsociety.gr)., 2001. All rights reserved."
+Gidugu,normal,400,Gidugu-Regular.ttf,Gidugu,Gidugu,Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2014 Eduardo Tunni (http://www.tipo.net.ar)
+Gilda Display,normal,400,GildaDisplay-Regular.ttf,GildaDisplay-Regular,Gilda Display,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Gilda'"
+Girassol,normal,400,Girassol-Regular.ttf,Girassol-Regular,Girassol Regular,Copyright 2019 The Girassol Project Authors (https://github.com/liamspradlin/Girassol-Display)
+Give You Glory,normal,400,GiveYouGlory.ttf,GiveYouGlory,Give You Glory,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com). This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Glass Antiqua,normal,400,GlassAntiqua-Regular.ttf,GlassAntiqua-Regular,Glass Antiqua,"Copyright (c) 2011, Denis Masharov <denis.masharov@gmail.com>."
+Glegoo,normal,400,Glegoo-Regular.ttf,Glegoo-Regular,Glegoo,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar), Copyright 2011-13 Lohit Fonts Project contributors (http://fedorahosted.org/lohit)"
+Glegoo,normal,700,Glegoo-Bold.ttf,Glegoo-Bold,Glegoo Bold,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar), Copyright 2011-13 Lohit Fonts Project contributors (http://fedorahosted.org/lohit)"
+Gloria Hallelujah,normal,400,GloriaHallelujah.ttf,GloriaHallelujah,Gloria Hallelujah,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Goblin One,normal,400,GoblinOne.ttf,GoblinOne,Goblin One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Goblin\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Gochi Hand,normal,400,GochiHand-Regular.ttf,GochiHand-Regular,Gochi Hand,"Copyright (c) 2011, Huerta Tipografica (www.huertatipografica.com.ar info@huertatipografica.com.ar), with Reserved Font Names \Gochi\ and \Gochi Hand\"
+Gorditas,normal,400,Gorditas-Regular.ttf,Gorditas-Regular,Gorditas,"Copyright (c) 2011, Gustavo Dipre (gbrenda1987@gmail.com), with Reserved Font Name \Gorditas\."
+Gorditas,normal,700,Gorditas-Bold.ttf,Gorditas-Bold,Gorditas Bold,"Copyright (c) 2011, Gustavo Dipre (gbrenda1987@gmail.com), with Reserved Font Name \Gorditas\."
+Gothic A1,normal,100,GothicA1-Thin.ttf,GothicA1-Thin,Gothic A1 Thin,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,200,GothicA1-ExtraLight.ttf,GothicA1-ExtraLight,Gothic A1 ExtraLight,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,300,GothicA1-Light.ttf,GothicA1-Light,Gothic A1 Light,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,400,GothicA1-Regular.ttf,GothicA1-Regular,Gothic A1 Regular,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,500,GothicA1-Medium.ttf,GothicA1-Medium,Gothic A1 Medium,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,600,GothicA1-SemiBold.ttf,GothicA1-SemiBold,Gothic A1 SemiBold,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,700,GothicA1-Bold.ttf,GothicA1-Bold,Gothic A1 Bold,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,800,GothicA1-ExtraBold.ttf,GothicA1-ExtraBold,Gothic A1 ExtraBold,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gothic A1,normal,900,GothicA1-Black.ttf,GothicA1-Black,Gothic A1 Black,"(C) Copyright HanYang I&C Co.,Ltd. All rights reserved."
+Gotu,normal,400,Gotu-Regular.ttf,Gotu-Regular,Gotu,"Copyright (c) 2016, Ek Type. All rights reserved."
+Goudy Bookletter 1911,normal,400,GoudyBookletter1911.ttf,GoudyBookletter1911,Goudy Bookletter 1911,"Copyright (c) 2010, Barry Schwartz (crudfactory.com chemoelectric@chemoelectric.org)"
+Graduate,normal,400,Graduate-Regular.ttf,Graduate-Regular,Graduate,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Graduate\"
+Grand Hotel,normal,400,GrandHotel-Regular.ttf,GrandHotel-Regular,Grand Hotel,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Grand Hotel\"
+Gravitas One,normal,400,GravitasOne.ttf,GravitasOne,Gravitas One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Gravitas\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Great Vibes,normal,400,GreatVibes-Regular.ttf,GreatVibes-Regular,Great Vibes,"Copyright (c) 2012 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Great Vibes\"
+Grenze,normal,100,Grenze-Thin.ttf,Grenze-Thin,Grenze Thin,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,100,Grenze-ThinItalic.ttf,Grenze-ThinItalic,Grenze Thin Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,200,Grenze-ExtraLight.ttf,Grenze-ExtraLight,Grenze ExtraLight,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,200,Grenze-ExtraLightItalic.ttf,Grenze-ExtraLightItalic,Grenze ExtraLight Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,300,Grenze-Light.ttf,Grenze-Light,Grenze Light,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,300,Grenze-LightItalic.ttf,Grenze-LightItalic,Grenze Light Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,400,Grenze-Regular.ttf,Grenze-Regular,Grenze Regular,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,400,Grenze-Italic.ttf,Grenze-Italic,Grenze Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,500,Grenze-Medium.ttf,Grenze-Medium,Grenze Medium,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,500,Grenze-MediumItalic.ttf,Grenze-MediumItalic,Grenze Medium Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,600,Grenze-SemiBold.ttf,Grenze-SemiBold,Grenze SemiBold,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,600,Grenze-SemiBoldItalic.ttf,Grenze-SemiBoldItalic,Grenze SemiBold Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,700,Grenze-Bold.ttf,Grenze-Bold,Grenze Bold,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,700,Grenze-BoldItalic.ttf,Grenze-BoldItalic,Grenze Bold Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,800,Grenze-ExtraBold.ttf,Grenze-ExtraBold,Grenze ExtraBold,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,800,Grenze-ExtraBoldItalic.ttf,Grenze-ExtraBoldItalic,Grenze ExtraBold Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,normal,900,Grenze-Black.ttf,Grenze-Black,Grenze Black,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze,italic,900,Grenze-BlackItalic.ttf,Grenze-BlackItalic,Grenze Black Italic,"Copyright 2018 The Grenze Project Authors (https://github.com/Omnibus-Type/Grenze), with Reserved Font Name \Grenze\."
+Grenze Gotisch,normal,400,GrenzeGotisch[wght].ttf,GrenzeGotisch-Regular,Grenze Gotisch Regular,Copyright 2020 The Grenze Gotisch Project Authors (https://github.com/Omnibus-Type/Grenze-Gotisch)
+Griffy,normal,400,Griffy-Regular.ttf,Griffy-Regular,Griffy,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Griffy\"
+Gruppo,normal,400,Gruppo-Regular.ttf,Gruppo,Gruppo,Copyright (c) 2010 Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Gruppo'. Available under the terms of the SIL OFL v1.1 from http://scripts.sil.org/OFL
+Gudea,normal,400,Gudea-Regular.ttf,Gudea,Gudea,"Copyright (c) 2012, Agustina Mingote (agustinamingote@gmail.com), with Reserved Font Names \Gudea\"
+Gudea,italic,400,Gudea-Italic.ttf,Gudea-Italic,Gudea Italic,"Copyright (c) 2012, Agustina Mingote (agustinamingote@gmail.com), with Reserved Font Names \Gudea\"
+Gudea,normal,700,Gudea-Bold.ttf,Gudea-Bold,Gudea Bold,"Copyright (c) 2012, Agustina Mingote (agustinamingote@gmail.com), with Reserved Font Names \Gudea\"
+Gugi,normal,400,Gugi-Regular.ttf,Gugi-Regular,Gugi Regular,Copyright (c) 2017 by TAE System & Typefaces Co.. All rights reserved.
+Gupter,normal,400,Gupter-Regular.ttf,Gupter-Regular,Gupter Regular,Copyright 2019 The Gupter Project Authors (https://github.com/octaviopardo/GUPTER)
+Gupter,normal,500,Gupter-Medium.ttf,Gupter-Medium,Gupter Medium,Copyright 2019 The Gupter Project Authors (https://github.com/octaviopardo/GUPTER)
+Gupter,normal,700,Gupter-Bold.ttf,Gupter-Bold,Gupter Bold,Copyright 2019 The Gupter Project Authors (https://github.com/octaviopardo/GUPTER)
+Gurajada,normal,400,Gurajada-Regular.ttf,Gurajada,Gurajada,Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org)
+Habibi,normal,400,Habibi-Regular.ttf,Habibi-Regular,Habibi,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Habibi\."
+Halant,normal,300,Halant-Light.ttf,Halant-Light,Halant Light,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Halant,normal,400,Halant-Regular.ttf,Halant-Regular,Halant Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Halant,normal,500,Halant-Medium.ttf,Halant-Medium,Halant Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Halant,normal,600,Halant-SemiBold.ttf,Halant-SemiBold,Halant SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Halant,normal,700,Halant-Bold.ttf,Halant-Bold,Halant Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Hammersmith One,normal,400,HammersmithOne-Regular.ttf,HammersmithOne,Hammersmith One,"Copyright (c) 2011, Sorkin Type Co. (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Hammersmith One\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Hanalei,normal,400,Hanalei-Regular.ttf,Hanalei-Regular,Hanalei,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Hanalei\"
+Hanalei Fill,normal,400,HanaleiFill-Regular.ttf,HanaleiFill-Regular,Hanalei Fill,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Hanalei Fill\"
+Handlee,normal,400,Handlee-Regular.ttf,Handlee-Regular,Handlee Regular,"Copyright (c) 2011, Admix Designs (http://www.admixdesigns.com joe@admixdesigns.com) with Reserved Font Name Handlee."
+Hanuman,normal,400,Hanuman-Regular.ttf,Hanuman-Regular,Hanuman Regular,Copyright 2011 Danh Hong (danhhong@gmail.com)
+Hanuman,normal,700,Hanuman-Bold.ttf,Hanuman-Bold,Hanuman Bold,Copyright 2011 Danh Hong (danhhong@gmail.com)
+Happy Monkey,normal,400,HappyMonkey-Regular.ttf,HappyMonkey-Regular,Happy Monkey,"Copyright (c) 2011 by Brenda Gallo (gbrenda1987@gmail.com), with Reserved Font Name \Happy Monkey\."
+Harmattan,normal,400,Harmattan-Regular.ttf,Harmattan-Regular,Harmattan Regular,"Copyright (c) 2007-2008, The C&MA Guinea Fulbe Team;\n\nCopyright renewed 2011-2012, George W. Nuss (http://www.fulbefouta.com),\nwith the Reserved Font Name \Fouta\.\n\nCopyright (c) 2004-2015, SIL International (http://scripts.sil.org), \nwith Reserved Font Names \'Andika\' and \'SIL\'.\n\nCopyright (c) 2014-2015, SIL International (http://www.sil.org/).\nwith Reserved Font Names \Harmattan\ and \SIL\."
+Headland One,normal,400,HeadlandOne-Regular.ttf,HeadlandOne-Regular,Headland One,"Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name \Headland\"
+Heebo,normal,400,Heebo[wght].ttf,Heebo-Regular,Heebo Regular,Copyright 2014 The Heebo Project Authors (https://github.com/OdedEzer/heebo)
+Henny Penny,normal,400,HennyPenny-Regular.ttf,HennyPenny-Regular,Henny Penny,"Copyright (c) 2012, Brownfox (gayaneh.b@gmail.com), with Reserved Font Name \Henny Penny\"
+Hepta Slab,normal,200,HeptaSlab[wght].ttf,HeptaSlab-ExtraLight,Hepta Slab ExtraLight,Copyright 2018 The Hepta Slab Project Authors (https://github.com/mjlagattuta/Hepta-Slab)
+Hermeneus One,normal,400,HermeneusOne-Regular.ttf,HermeneusOne-Regular,Hermeneus One,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com) and Rodrigo Fuenzalida (www.rfuenzalida.com), with Reserved Font Name Hermeneus."
+Herr Von Muellerhoff,normal,400,HerrVonMuellerhoff-Regular.ttf,HerrVonMuellerhoff-Regular,Herr Von Muellerhoff Regular,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Herr Von Mullerhoff\"
+Hi Melody,normal,400,HiMelody-Regular.ttf,HiMelody-Regular,Hi Melody Regular,Copyright (c) YoonDesign Inc. All Rights Reserved.
+Hind,normal,300,Hind-Light.ttf,Hind-Light,Hind Light,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Hind,normal,400,Hind-Regular.ttf,Hind-Regular,Hind Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Hind,normal,500,Hind-Medium.ttf,Hind-Medium,Hind Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Hind,normal,600,Hind-SemiBold.ttf,Hind-SemiBold,Hind SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Hind,normal,700,Hind-Bold.ttf,Hind-Bold,Hind Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Colombo,normal,300,HindColombo-Light.ttf,HindColombo-Light,Hind Colombo Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Colombo,normal,400,HindColombo-Regular.ttf,HindColombo-Regular,Hind Colombo,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Colombo,normal,500,HindColombo-Medium.ttf,HindColombo-Medium,Hind Colombo Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Colombo,normal,600,HindColombo-SemiBold.ttf,HindColombo-SemiBold,Hind Colombo SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Colombo,normal,700,HindColombo-Bold.ttf,HindColombo-Bold,Hind Colombo Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Guntur,normal,300,HindGuntur-Light.ttf,HindGuntur-Light,Hind Guntur Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Guntur,normal,400,HindGuntur-Regular.ttf,HindGuntur-Regular,Hind Guntur Regular,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Guntur,normal,500,HindGuntur-Medium.ttf,HindGuntur-Medium,Hind Guntur Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Guntur,normal,600,HindGuntur-SemiBold.ttf,HindGuntur-SemiBold,Hind Guntur SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Guntur,normal,700,HindGuntur-Bold.ttf,HindGuntur-Bold,Hind Guntur Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Jalandhar,normal,300,HindJalandhar-Light.ttf,HindJalandhar-Light,Hind Jalandhar Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Jalandhar,normal,400,HindJalandhar-Regular.ttf,HindJalandhar-Regular,Hind Jalandhar,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Jalandhar,normal,500,HindJalandhar-Medium.ttf,HindJalandhar-Medium,Hind Jalandhar Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Jalandhar,normal,600,HindJalandhar-SemiBold.ttf,HindJalandhar-SemiBold,Hind Jalandhar SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Jalandhar,normal,700,HindJalandhar-Bold.ttf,HindJalandhar-Bold,Hind Jalandhar Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Kochi,normal,300,HindKochi-Light.ttf,HindKochi-Light,Hind Kochi Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Kochi,normal,400,HindKochi-Regular.ttf,HindKochi-Regular,Hind Kochi,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Kochi,normal,500,HindKochi-Medium.ttf,HindKochi-Medium,Hind Kochi Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Kochi,normal,600,HindKochi-SemiBold.ttf,HindKochi-SemiBold,Hind Kochi SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Kochi,normal,700,HindKochi-Bold.ttf,HindKochi-Bold,Hind Kochi Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Madurai,normal,300,HindMadurai-Light.ttf,HindMadurai-Light,Hind Madurai Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Madurai,normal,400,HindMadurai-Regular.ttf,HindMadurai-Regular,Hind Madurai Regular,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Madurai,normal,500,HindMadurai-Medium.ttf,HindMadurai-Medium,Hind Madurai Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Madurai,normal,600,HindMadurai-SemiBold.ttf,HindMadurai-SemiBold,Hind Madurai SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Madurai,normal,700,HindMadurai-Bold.ttf,HindMadurai-Bold,Hind Madurai Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Mysuru,normal,300,HindMysuru-Light.ttf,HindMysuru-Light,Hind Mysuru Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Mysuru,normal,400,HindMysuru-Regular.ttf,HindMysuru-Regular,Hind Mysuru,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Mysuru,normal,500,HindMysuru-Medium.ttf,HindMysuru-Medium,Hind Mysuru Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Mysuru,normal,600,HindMysuru-SemiBold.ttf,HindMysuru-SemiBold,Hind Mysuru SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Mysuru,normal,700,HindMysuru-Bold.ttf,HindMysuru-Bold,Hind Mysuru Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Siliguri,normal,300,HindSiliguri-Light.ttf,HindSiliguri-Light,Hind Siliguri Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Siliguri,normal,400,HindSiliguri-Regular.ttf,HindSiliguri-Regular,Hind Siliguri Regular,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Siliguri,normal,500,HindSiliguri-Medium.ttf,HindSiliguri-Medium,Hind Siliguri Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Siliguri,normal,600,HindSiliguri-SemiBold.ttf,HindSiliguri-SemiBold,Hind Siliguri SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Siliguri,normal,700,HindSiliguri-Bold.ttf,HindSiliguri-Bold,Hind Siliguri Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Vadodara,normal,300,HindVadodara-Light.ttf,HindVadodara-Light,Hind Vadodara Light,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Vadodara,normal,400,HindVadodara-Regular.ttf,HindVadodara-Regular,Hind Vadodara Regular,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Vadodara,normal,500,HindVadodara-Medium.ttf,HindVadodara-Medium,Hind Vadodara Medium,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Vadodara,normal,600,HindVadodara-SemiBold.ttf,HindVadodara-SemiBold,Hind Vadodara SemiBold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Hind Vadodara,normal,700,HindVadodara-Bold.ttf,HindVadodara-Bold,Hind Vadodara Bold,Copyright (c) 2015 Indian Type Foundry (info@indiantypefoundry.com)
+Holtwood One SC,normal,400,HoltwoodOneSC.ttf,HoltwoodOneSC,Holtwood One SC,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Holtwood'. All rights reserved."
+Homenaje,normal,400,Homenaje-Regular.ttf,Homenaje-Regular,Homenaje Regular,"Copyright 2016 The Homenaje Project Authors (https://github.com/googlefonts/Homenaje), with Reserved Font Name \'Homenaje."
+Ibarra Real Nova,normal,400,IbarraRealNova-Regular.ttf,IbarraRealNova-Regular,Ibarra Real Nova Regular,Copyright 2007 The Ibarra Real Nova Project Authors (https://github.com/googlefonts/ibarrareal)
+Ibarra Real Nova,italic,400,IbarraRealNova-Italic.ttf,IbarraRealNova-Italic,Ibarra Real Nova Italic,Copyright 2007 The Ibarra Real Nova Project Authors (https://github.com/googlefonts/ibarrareal)
+Ibarra Real Nova,normal,600,IbarraRealNova-SemiBold.ttf,IbarraRealNova-SemiBold,Ibarra Real Nova SemiBold,Copyright 2007 The Ibarra Real Nova Project Authors (https://github.com/googlefonts/ibarrareal)
+Ibarra Real Nova,italic,600,IbarraRealNova-SemiBoldItalic.ttf,IbarraRealNova-SemiBoldItalic,Ibarra Real Nova SemiBold Italic,Copyright 2007 The Ibarra Real Nova Project Authors (https://github.com/googlefonts/ibarrareal)
+Ibarra Real Nova,normal,700,IbarraRealNova-Bold.ttf,IbarraRealNova-Bold,Ibarra Real Nova Bold,Copyright 2007 The Ibarra Real Nova Project Authors (https://github.com/googlefonts/ibarrareal)
+Ibarra Real Nova,italic,700,IbarraRealNova-BoldItalic.ttf,IbarraRealNova-BoldItalic,Ibarra Real Nova Bold Italic,Copyright 2007 The Ibarra Real Nova Project Authors (https://github.com/googlefonts/ibarrareal)
+IBM Plex Mono,normal,100,IBMPlexMono-Thin.ttf,IBMPlexMono-Thin,IBM Plex Mono Thin,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,100,IBMPlexMono-ThinItalic.ttf,IBMPlexMono-ThinItalic,IBM Plex Mono Thin Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,normal,200,IBMPlexMono-ExtraLight.ttf,IBMPlexMono-ExtraLight,IBM Plex Mono ExtraLight,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,200,IBMPlexMono-ExtraLightItalic.ttf,IBMPlexMono-ExtraLightItalic,IBM Plex Mono ExtraLight Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,normal,300,IBMPlexMono-Light.ttf,IBMPlexMono-Light,IBM Plex Mono Light,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,300,IBMPlexMono-LightItalic.ttf,IBMPlexMono-LightItalic,IBM Plex Mono Light Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,normal,400,IBMPlexMono-Regular.ttf,IBMPlexMono,IBM Plex Mono,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,400,IBMPlexMono-Italic.ttf,IBMPlexMono-Italic,IBM Plex Mono Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,normal,500,IBMPlexMono-Medium.ttf,IBMPlexMono-Medium,IBM Plex Mono Medium,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,500,IBMPlexMono-MediumItalic.ttf,IBMPlexMono-MediumItalic,IBM Plex Mono Medium Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,normal,600,IBMPlexMono-SemiBold.ttf,IBMPlexMono-SemiBold,IBM Plex Mono SemiBold,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,600,IBMPlexMono-SemiBoldItalic.ttf,IBMPlexMono-SemiBoldItalic,IBM Plex Mono SemiBold Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,normal,700,IBMPlexMono-Bold.ttf,IBMPlexMono-Bold,IBM Plex Mono Bold,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Mono,italic,700,IBMPlexMono-BoldItalic.ttf,IBMPlexMono-BoldItalic,IBM Plex Mono Bold Italic,Copyright 2017 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,100,IBMPlexSans-Thin.ttf,IBMPlexSans-Thin,IBM Plex Sans Thin,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,100,IBMPlexSans-ThinItalic.ttf,IBMPlexSans-ThinItalic,IBM Plex Sans Thin Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,200,IBMPlexSans-ExtraLight.ttf,IBMPlexSans-ExtraLight,IBM Plex Sans ExtraLight,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,200,IBMPlexSans-ExtraLightItalic.ttf,IBMPlexSans-ExtraLightItalic,IBM Plex Sans ExtraLight Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,300,IBMPlexSans-Light.ttf,IBMPlexSans-Light,IBM Plex Sans Light,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,300,IBMPlexSans-LightItalic.ttf,IBMPlexSans-LightItalic,IBM Plex Sans Light Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,400,IBMPlexSans-Regular.ttf,IBMPlexSans,IBM Plex Sans,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,400,IBMPlexSans-Italic.ttf,IBMPlexSans-Italic,IBM Plex Sans Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,500,IBMPlexSans-Medium.ttf,IBMPlexSans-Medium,IBM Plex Sans Medium,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,500,IBMPlexSans-MediumItalic.ttf,IBMPlexSans-MediumItalic,IBM Plex Sans Medium Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,600,IBMPlexSans-SemiBold.ttf,IBMPlexSans-SemiBold,IBM Plex Sans SemiBold,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,600,IBMPlexSans-SemiBoldItalic.ttf,IBMPlexSans-SemiBoldItalic,IBM Plex Sans SemiBold Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,normal,700,IBMPlexSans-Bold.ttf,IBMPlexSans-Bold,IBM Plex Sans Bold,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans,italic,700,IBMPlexSans-BoldItalic.ttf,IBMPlexSans-BoldItalic,IBM Plex Sans Bold Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,100,IBMPlexSansCondensed-Thin.ttf,IBMPlexSansCond-Thin,IBM Plex Sans Condensed Thin,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,100,IBMPlexSansCondensed-ThinItalic.ttf,IBMPlexSansCond-ThinItalic,IBM Plex Sans Condensed Thin Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,200,IBMPlexSansCondensed-ExtraLight.ttf,IBMPlexSansCond-ExtraLight,IBM Plex Sans Condensed ExtraLight,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,200,IBMPlexSansCondensed-ExtraLightItalic.ttf,IBMPlexSansCond-ExtraLightItalic,IBM Plex Sans Condensed ExtraLight Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,300,IBMPlexSansCondensed-Light.ttf,IBMPlexSansCond-Light,IBM Plex Sans Condensed Light,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,300,IBMPlexSansCondensed-LightItalic.ttf,IBMPlexSansCond-LightItalic,IBM Plex Sans Condensed Light Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,400,IBMPlexSansCondensed-Regular.ttf,IBMPlexSansCond,IBM Plex Sans Condensed,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,400,IBMPlexSansCondensed-Italic.ttf,IBMPlexSansCond-Italic,IBM Plex Sans Condensed Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,500,IBMPlexSansCondensed-Medium.ttf,IBMPlexSansCond-Medium,IBM Plex Sans Condensed Medium,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,500,IBMPlexSansCondensed-MediumItalic.ttf,IBMPlexSansCond-MediumItalic,IBM Plex Sans Condensed Medium Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,600,IBMPlexSansCondensed-SemiBold.ttf,IBMPlexSansCond-SemiBold,IBM Plex Sans Condensed SemiBold,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,600,IBMPlexSansCondensed-SemiBoldItalic.ttf,IBMPlexSansCond-SemiBoldItalic,IBM Plex Sans Condensed SemiBold Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,normal,700,IBMPlexSansCondensed-Bold.ttf,IBMPlexSansCond-Bold,IBM Plex Sans Condensed Bold,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Sans Condensed,italic,700,IBMPlexSansCondensed-BoldItalic.ttf,IBMPlexSansCond-BoldItalic,IBM Plex Sans Condensed Bold Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,100,IBMPlexSerif-Thin.ttf,IBMPlexSerif-Thin,IBM Plex Serif Thin,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,100,IBMPlexSerif-ThinItalic.ttf,IBMPlexSerif-ThinItalic,IBM Plex Serif Thin Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,200,IBMPlexSerif-ExtraLight.ttf,IBMPlexSerif-ExtraLight,IBM Plex Serif ExtraLight,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,200,IBMPlexSerif-ExtraLightItalic.ttf,IBMPlexSerif-ExtraLightItalic,IBM Plex Serif ExtraLight Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,300,IBMPlexSerif-Light.ttf,IBMPlexSerif-Light,IBM Plex Serif Light,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,300,IBMPlexSerif-LightItalic.ttf,IBMPlexSerif-LightItalic,IBM Plex Serif Light Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,400,IBMPlexSerif-Regular.ttf,IBMPlexSerif,IBM Plex Serif,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,400,IBMPlexSerif-Italic.ttf,IBMPlexSerif-Italic,IBM Plex Serif Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,500,IBMPlexSerif-Medium.ttf,IBMPlexSerif-Medium,IBM Plex Serif Medium,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,500,IBMPlexSerif-MediumItalic.ttf,IBMPlexSerif-MediumItalic,IBM Plex Serif Medium Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,600,IBMPlexSerif-SemiBold.ttf,IBMPlexSerif-SemiBold,IBM Plex Serif SemiBold,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,600,IBMPlexSerif-SemiBoldItalic.ttf,IBMPlexSerif-SemiBoldItalic,IBM Plex Serif SemiBold Italic,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,normal,700,IBMPlexSerif-Bold.ttf,IBMPlexSerif-Bold,IBM Plex Serif Bold,Copyright 2018 IBM Corp. All rights reserved.
+IBM Plex Serif,italic,700,IBMPlexSerif-BoldItalic.ttf,IBMPlexSerif-BoldItalic,IBM Plex Serif Bold Italic,Copyright 2018 IBM Corp. All rights reserved.
+Iceberg,normal,400,Iceberg-Regular.ttf,Iceberg-Regular,Iceberg,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org), with Reserved Font Name \Iceberg\."
+Iceland,normal,400,Iceland-Regular.ttf,Iceland-Regular,Iceland,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Iceland\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+IM Fell Double Pica,normal,400,IMFELLDoublePica-Regular.ttf,IM_FELL_Double_Pica_Roman,IM FELL Double Pica Roman,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL Double Pica Roman
+IM Fell Double Pica,italic,400,IMFELLDoublePica-Italic.ttf,IM_FELL_Double_Pica_Italic,IM FELL Double Pica Italic,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) with reserved name IM FELL Double Pica Italic
+IM Fell Double Pica SC,normal,400,IMFeDPsc28P.ttf,IM_FELL_Double_Pica_SC,IM FELL Double Pica SC,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL Double Pica SC
+IM Fell DW Pica,normal,400,IMFePIrm28P.ttf,IM_FELL_DW_Pica_Roman,IM FELL DW Pica Roman,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL DW Pica Roman
+IM Fell DW Pica,italic,400,IMFePIit28P.ttf,IM_FELL_DW_Pica_Italic,IM FELL DW Pica Italic,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL DW Pica Italic
+IM Fell DW Pica SC,normal,400,IMFePIsc28P.ttf,IM_FELL_DW_Pica_SC,IM FELL DW Pica SC,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL DW Pica SC
+IM Fell English,normal,400,IMFeENrm28P.ttf,IM_FELL_English_Roman,IM FELL English Roman,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL English Roman
+IM Fell English,italic,400,IMFeENit28P.ttf,IM_FELL_English_Italic,IM FELL English Italic,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL English Italic
+IM Fell English SC,normal,400,IMFeENsc28P.ttf,IM_FELL_English_SC,IM FELL English SC,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL English SC
+IM Fell French Canon,normal,400,IMFeFCrm28P.ttf,IM_FELL_French_Canon_Roman,IM FELL French Canon Roman,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL French Canon Roman
+IM Fell French Canon,italic,400,IMFeFCit28P.ttf,IM_FELL_French_Canon_Italic,IM FELL French Canon Italic,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL French Canon Italic
+IM Fell French Canon SC,normal,400,IMFeFCsc28P.ttf,IM_FELL_French_Canon_SC,IM FELL French Canon SC,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL French Canon SC
+IM Fell Great Primer,normal,400,IMFeGPrm28P.ttf,IM_FELL_Great_Primer_Roman,IM FELL Great Primer Roman,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL Great Primer Roman
+IM Fell Great Primer,italic,400,IMFeGPit28P.ttf,IM_FELL_Great_Primer_Italic,IM FELL Great Primer Italic,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL Great Primer Italic
+IM Fell Great Primer SC,normal,400,IMFeGPsc28P.ttf,IM_FELL_Great_Primer_SC,IM FELL Great Primer SC,© 2007 Igino Marini (www.iginomarini.com mail@iginomarini.com) With Reserved Font Name IM FELL Great Primer SC
+Imprima,normal,400,Imprima-Regular.ttf,Imprima-Regular,Imprima,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Imprima\"
+Inconsolata,normal,400,"Inconsolata[wdth,wght].ttf",Inconsolata-Regular,Inconsolata Regular,Copyright 2006 The Inconsolata Project Authors (https://github.com/cyrealtype/Inconsolata)
+Inder,normal,400,Inder-Regular.ttf,Inder-Regular,Inder,Copyright (c) 2010 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name Inder.
+Indie Flower,normal,400,IndieFlower-Regular.ttf,IndieFlower-Regular,Indie Flower Regular,Copyright 2010 The Indie Flower Authors (kimberlygeswein.com)
+Inika,normal,400,Inika-Regular.ttf,Inika,Inika,Copyright (c) 2011 by Constanza Artigas Preller (artigasconstanza@gmail.com). All rights reserved.
+Inika,normal,700,Inika-Bold.ttf,Inika-Bold,Inika Bold,Copyright (c) 2011 by Constanza Artigas Preller (artigasconstanza@gmail.com). All rights reserved.
+Inknut Antiqua,normal,300,InknutAntiqua-Light.ttf,InknutAntiqua-Light,Inknut Antiqua Light,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inknut Antiqua,normal,400,InknutAntiqua-Regular.ttf,InknutAntiqua-Regular,Inknut Antiqua Regular,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inknut Antiqua,normal,500,InknutAntiqua-Medium.ttf,InknutAntiqua-Medium,Inknut Antiqua Medium,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inknut Antiqua,normal,600,InknutAntiqua-SemiBold.ttf,InknutAntiqua-SemiBold,Inknut Antiqua SemiBold,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inknut Antiqua,normal,700,InknutAntiqua-Bold.ttf,InknutAntiqua-Bold,Inknut Antiqua Bold,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inknut Antiqua,normal,800,InknutAntiqua-ExtraBold.ttf,InknutAntiqua-ExtraBold,Inknut Antiqua ExtraBold,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inknut Antiqua,normal,900,InknutAntiqua-Black.ttf,InknutAntiqua-Black,Inknut Antiqua Black,Copyright (c) 2014 by Claus Eggers Srensen (es@forthehearts.net).
+Inria Sans,normal,300,InriaSans-Light.ttf,InriaSans-Light,Inria Sans Light,Copyright 2017 The Inria Sans Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Sans,italic,300,InriaSans-LightItalic.ttf,InriaSans-LightItalic,Inria Sans Light Italic,Copyright 2017 The Inria Sans Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Sans,normal,400,InriaSans-Regular.ttf,InriaSans-Regular,Inria Sans Regular,Copyright 2017 The Inria Sans Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Sans,italic,400,InriaSans-Italic.ttf,InriaSans-Italic,Inria Sans Italic,Copyright 2017 The Inria Sans Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Sans,normal,700,InriaSans-Bold.ttf,InriaSans-Bold,Inria Sans Bold,Copyright 2017 The Inria Sans Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Sans,italic,700,InriaSans-BoldItalic.ttf,InriaSans-BoldItalic,Inria Sans Bold Italic,Copyright 2017 The Inria Sans Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Serif,normal,300,InriaSerif-Light.ttf,InriaSerif-Light,Inria Serif Light,Copyright 2017 The Inria Serif Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Serif,italic,300,InriaSerif-LightItalic.ttf,InriaSerif-LightItalic,Inria Serif Light Italic,Copyright 2017 The Inria Serif Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Serif,normal,400,InriaSerif-Regular.ttf,InriaSerif-Regular,Inria Serif Regular,Copyright 2017 The Inria Serif Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Serif,italic,400,InriaSerif-Italic.ttf,InriaSerif-Italic,Inria Serif Italic,Copyright 2017 The Inria Serif Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Serif,normal,700,InriaSerif-Bold.ttf,InriaSerif-Bold,Inria Serif Bold,Copyright 2017 The Inria Serif Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inria Serif,italic,700,InriaSerif-BoldItalic.ttf,InriaSerif-BoldItalic,Inria Serif Bold Italic,Copyright 2017 The Inria Serif Project Authors (https://github.com/BlackFoundryCom/InriaFonts)
+Inter,normal,400,"Inter[slnt,wght].ttf",Inter-Regular,Inter-Regular,Copyright 2020 The Inter Project Authors (https://github.com/rsms/inter)
+Istok Web,normal,400,IstokWeb-Regular.ttf,IstokWeb-Regular,Istok Web Regular,"Copyright (c) 2008-2014, Andrey V. Panov (panov@canopus.iacp.dvo.ru), with Reserved Font Name Istok"
+Istok Web,italic,400,IstokWeb-Italic.ttf,IstokWeb-Italic,Istok Web Italic,"Copyright (c) 2008-2014, Andrey V. Panov (panov@canopus.iacp.dvo.ru), with Reserved Font Name Istok"
+Istok Web,normal,700,IstokWeb-Bold.ttf,IstokWeb-Bold,Istok Web Bold,"Copyright (c) 2008-2014, Andrey V. Panov (panov@canopus.iacp.dvo.ru), with Reserved Font Name Istok"
+Istok Web,italic,700,IstokWeb-BoldItalic.ttf,IstokWeb-BoldItalic,Istok Web Bold Italic,"Copyright (c) 2008-2014, Andrey V. Panov (panov@canopus.iacp.dvo.ru), with Reserved Font Name Istok"
+Italiana,normal,400,Italiana-Regular.ttf,Italiana-Regular,Italiana,Copyright (c) 2011 by Santiago Orozco (hi@typemade.mx) with reserved name Italiana
+Italianno,normal,400,Italianno-Regular.ttf,Italianno-Regular,Italianno,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Italianno\"
+Itim,normal,400,Itim-Regular.ttf,Itim-Regular,Itim,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com), Copyright (c) 2014, Pablo Impallari (www.impallari.com|impallari@gmail.com)"
+Jacques Francois,normal,400,JacquesFrancois-Regular.ttf,JacquesFrancois-Regular,Jacques Francois,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name 'Jacques Francois'"
+Jacques Francois Shadow,normal,400,JacquesFrancoisShadow-Regular.ttf,JacquesFrancoisShadow-Regular,Jacques Francois Shadow,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name 'Jacques Francois'"
+Jaldi,normal,400,Jaldi-Regular.ttf,Jaldi-Regular,Jaldi,"Copyright (c) 2011-2015, Omnibus-Type (www.omnibus-type.com omnibus.type@gmail.com) with Reserved Font Name 'Jaldi' and 'Asap'"
+Jaldi,normal,700,Jaldi-Bold.ttf,Jaldi-Bold,Jaldi Bold,"Copyright (c) 2011-2015, Omnibus-Type (www.omnibus-type.com omnibus.type@gmail.com) with Reserved Font Name 'Jaldi' and 'Asap'"
+Jim Nightshade,normal,400,JimNightshade-Regular.ttf,JimNightshade-Regular,Jim Nightshade,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Jim Nightshade\"
+Jockey One,normal,400,JockeyOne-Regular.ttf,JockeyOne-Regular,Jockey One,"Copyright (c) 2011, Copyright (c) 2011, TypeTogether (www.type-together.com info@type-together.com), with Reserved Font Names \Jockey\ and \Jockey One\"
+Jolly Lodger,normal,400,JollyLodger-Regular.ttf,JollyLodger,Jolly Lodger,"Copyright (c) 2012 by Font Diner, Inc (diner@fontdiner.com) with Reseved Font Name \Jolly Lodger\"
+Jomhuria,normal,400,Jomhuria-Regular.ttf,Jomhuria-Regular,Jomhuria Regular,Copyright 2015 KB-Studio (www.k-b-studio.com|tarobish@gmail.com). Copyright 2015 Lasse Fister (lasse@graphicore.de). Copyright 2015 Sorkin Type Co (www.sorkintype.com). Copyright 2010-2015 Khaled Hosny (khaledhosny@eglug.org).
+Jomolhari,normal,400,Jomolhari-Regular.ttf,Jomolhari-Regular,Jomolhari Regular,Copyright (c) 2006 by Christopher Fynn. All rights reserved.
+Josefin Sans,normal,400,JosefinSans[wght].ttf,JosefinSans-Thin,Josefin Sans Thin,"Copyright 2010 The Josefin Sans Project Authors (https://github.com/ThomasJockin/JosefinSansFont-master), with Reserved Font Name \Josefin Sans\."
+Josefin Sans,italic,400,JosefinSans-Italic[wght].ttf,JosefinSans-ThinItalic,Josefin Sans Thin Italic,"Copyright 2010 The Josefin Sans Project Authors (https://github.com/ThomasJockin/JosefinSansFont-master), with Reserved Font Name \Josefin Sans\."
+Josefin Sans Std Light,normal,400,JosefinSansStd-Light.ttf,JosefinSansStd-Light,Josefin Sans Std Light,Copyright (c) 2010 by Santiago Orozco (hi@typemade.mx). All rights reserved.
+Josefin Slab,normal,100,JosefinSlab-Thin.ttf,JosefinSlab-Thin,Josefin Slab Thin,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,italic,100,JosefinSlab-ThinItalic.ttf,JosefinSlab-ThinItalic,Josefin Slab Thin Italic,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,normal,300,JosefinSlab-Light.ttf,JosefinSlab-Light,Josefin Slab Light,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,italic,300,JosefinSlab-LightItalic.ttf,JosefinSlab-LightItalic,Josefin Slab Light Italic,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,normal,400,JosefinSlab-Regular.ttf,JosefinSlab-Regular,Josefin Slab Regular,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,italic,400,JosefinSlab-Italic.ttf,JosefinSlab-Italic,Josefin Slab Italic,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,normal,600,JosefinSlab-SemiBold.ttf,JosefinSlab-SemiBold,Josefin Slab SemiBold,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,italic,600,JosefinSlab-SemiBoldItalic.ttf,JosefinSlab-SemiBoldItalic,Josefin Slab SemiBold Italic,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,normal,700,JosefinSlab-Bold.ttf,JosefinSlab-Bold,Josefin Slab Bold,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Josefin Slab,italic,700,JosefinSlab-BoldItalic.ttf,JosefinSlab-BoldItalic,Josefin Slab Bold Italic,Copyright (c) 2010 by Typemade (hi@typemade.mx). All rights reserved.
+Jost,normal,400,Jost[wght].ttf,Jost-Regular,Jost Regular,Copyright 2020 The Jost Project Authors (https://github.com/indestructible-type)
+Jost,italic,400,Jost-Italic[wght].ttf,Jost-Italic,Jost Italic,Copyright 2020 The Jost Project Authors (https://github.com/indestructible-type)
+Joti One,normal,400,JotiOne-Regular.ttf,JotiOne-Regular,Joti One,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Joti'"
+Jua,normal,400,Jua-Regular.ttf,Jua-Regular,Jua Regular,Copyright 2018 The BM JUA Project Authors
+Judson,normal,400,Judson-Regular.ttf,Judson-Regular,Judson Regular,"Copyright (c) 2010, 2011 by Daniel Johnson (il.basso.buffo@gmail.com). Released under the terms of the SIL Open Font License v1.1."
+Judson,italic,400,Judson-Italic.ttf,Judson-Italic,Judson Italic,"Copyright (c) 2010, 2011 by Daniel Johnson (il.basso.buffo@gmail.com). Released under the terms of the SIL Open Font License v1.1."
+Judson,normal,700,Judson-Bold.ttf,Judson-Bold,Judson Bold,"Copyright (c) 2010, 2011 by Daniel Johnson (il.basso.buffo@gmail.com). Released under the terms of the SIL Open Font License v1.1."
+Julee,normal,400,Julee-Regular.ttf,Julee-Regular,Julee-Regular,"Copyright (c) 2011, Julian Tunni (jotadejulian@hotmail.com), with Reserved Font Name \Julee\"
+Julius Sans One,normal,400,JuliusSansOne-Regular.ttf,JuliusSansOne-Regular,Julius Sans One,"Copyright (c) 2012, LatinoType (luciano@latinotype.com), with Reserved Font Names 'Julius'"
+Junge,normal,400,Junge-Regular.ttf,Junge-Regular,Junge,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Junge\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Jura,normal,300,Jura[wght].ttf,Jura-Light,Jura Light,Copyright 2019 The Jura Project Authors (https://github.com/ossobuffo/jura)
+Just Me Again Down Here,normal,400,JustMeAgainDownHere.ttf,JustMeAgainDownHere,Just Me Again Down Here,Copyright (c) 2011 by Kimberly Geswein (kimberlygeswein@gmail.com). All rights reserved.
+K2D,normal,100,K2D-Thin.ttf,K2D-Thin,K2D Thin,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,100,K2D-ThinItalic.ttf,K2D-ThinItalic,K2D Thin Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,200,K2D-ExtraLight.ttf,K2D-ExtraLight,K2D ExtraLight,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,200,K2D-ExtraLightItalic.ttf,K2D-ExtraLightItalic,K2D ExtraLight Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,300,K2D-Light.ttf,K2D-Light,K2D Light,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,300,K2D-LightItalic.ttf,K2D-LightItalic,K2D Light Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,400,K2D-Regular.ttf,K2D-Regular,K2D Regular,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,400,K2D-Italic.ttf,K2D-Italic,K2D Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,500,K2D-Medium.ttf,K2D-Medium,K2D Medium,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,500,K2D-MediumItalic.ttf,K2D-MediumItalic,K2D Medium Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,600,K2D-SemiBold.ttf,K2D-SemiBold,K2D SemiBold,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,600,K2D-SemiBoldItalic.ttf,K2D-SemiBoldItalic,K2D SemiBold Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,700,K2D-Bold.ttf,K2D-Bold,K2D Bold,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,700,K2D-BoldItalic.ttf,K2D-BoldItalic,K2D Bold Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,normal,800,K2D-ExtraBold.ttf,K2D-ExtraBold,K2D ExtraBold,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+K2D,italic,800,K2D-ExtraBoldItalic.ttf,K2D-ExtraBoldItalic,K2D ExtraBold Italic,Copyright 2018 The K2D Project Authors (https://github.com/cadsondemak/K2D)
+Kadwa,normal,400,Kadwa-Regular.ttf,Kadwa-Regular,Kadwa,"Copyright (c) 2014-2015, Sol Matas (www.huertatipografica.com - sol@huertatipografica.com)"
+Kadwa,normal,700,Kadwa-Bold.ttf,Kadwa-Bold,Kadwa Bold,"Copyright (c) 2014-2015, Sol Matas (www.huertatipografica.com - sol@huertatipografica.com)"
+Kalam,normal,300,Kalam-Light.ttf,Kalam-Light,Kalam Light,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Kalam,normal,400,Kalam-Regular.ttf,Kalam-Regular,Kalam,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Kalam,normal,700,Kalam-Bold.ttf,Kalam-Bold,Kalam Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Kameron,normal,400,Kameron-Regular.ttf,Kameron,Kameron,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Kameron'. All rights reserved."
+Kameron,normal,700,Kameron-Bold.ttf,Kameron-Bold,Kameron Bold,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Kameron'. All rights reserved."
+Kanit,normal,100,Kanit-Thin.ttf,Kanit-Thin,Kanit Thin,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,100,Kanit-ThinItalic.ttf,Kanit-ThinItalic,Kanit Thin Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,200,Kanit-ExtraLight.ttf,Kanit-ExtraLight,Kanit ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,200,Kanit-ExtraLightItalic.ttf,Kanit-ExtraLightItalic,Kanit ExtraLight Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,300,Kanit-Light.ttf,Kanit-Light,Kanit Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,300,Kanit-LightItalic.ttf,Kanit-LightItalic,Kanit Light Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,400,Kanit-Regular.ttf,Kanit-Regular,Kanit Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,400,Kanit-Italic.ttf,Kanit-Italic,Kanit Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,500,Kanit-Medium.ttf,Kanit-Medium,Kanit Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,500,Kanit-MediumItalic.ttf,Kanit-MediumItalic,Kanit Medium Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,600,Kanit-SemiBold.ttf,Kanit-SemiBold,Kanit SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,600,Kanit-SemiBoldItalic.ttf,Kanit-SemiBoldItalic,Kanit SemiBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,700,Kanit-Bold.ttf,Kanit-Bold,Kanit Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,700,Kanit-BoldItalic.ttf,Kanit-BoldItalic,Kanit Bold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,800,Kanit-ExtraBold.ttf,Kanit-ExtraBold,Kanit ExtraBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,800,Kanit-ExtraBoldItalic.ttf,Kanit-ExtraBoldItalic,Kanit ExtraBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,normal,900,Kanit-Black.ttf,Kanit-Black,Kanit Black,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kanit,italic,900,Kanit-BlackItalic.ttf,Kanit-BlackItalic,Kanit Black Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Kantumruy,normal,300,Kantumruy-Light.ttf,KantumruyLight,Kantumruy Light,"Copyright (c) 2013, Tep Sovichet (it4ug.net sovichet.tep@gmail.com), with Reserved Font Name 'Kantumruy'"
+Kantumruy,normal,400,Kantumruy-Regular.ttf,Kantumruy,Kantumruy,"Copyright (c) 2013, Tep Sovichet (it4ug.net sovichet.tep@gmail.com), with Reserved Font Name 'Kantumruy'"
+Kantumruy,normal,700,Kantumruy-Bold.ttf,Kantumruy-Bold,Kantumruy Bold,"Copyright (c) 2013, Tep Sovichet (it4ug.net sovichet.tep@gmail.com), with Reserved Font Name 'Kantumruy'"
+Karla,normal,400,Karla[wght].ttf,Karla-ExtraLight,Karla ExtraLight,Copyright 2019 The Karla Project Authors (https://github.com/bghryct/karmilla)
+Karla,italic,400,Karla-Italic[wght].ttf,Karla-ExtraLightItalic,Karla ExtraLight Italic,Copyright 2019 The Karla Project Authors (https://github.com/bghryct/karmilla)
+Karla Tamil Inclined,normal,400,KarlaTamilInclined-Regular.ttf,KarlaTamilInclined-Regular,Karla Tamil Inclined,"Copyright (c) 2011-2012, Jonathan Pinhorn (jonpinhorn.typedesign@gmail.com), with Reserved Font Names 'Karla'"
+Karla Tamil Inclined,normal,700,KarlaTamilInclined-Bold.ttf,KarlaTamilInclined-Bold,Karla Tamil Inclined Bold,"Copyright (c) 2011-2012, Jonathan Pinhorn (jonpinhorn.typedesign@gmail.com), with Reserved Font Names 'Karla'"
+Karla Tamil Upright,normal,400,KarlaTamilUpright-Regular.ttf,KarlaTamilUpright-Regular,Karla Tamil Upright,"Copyright (c) 2011-2012, Jonathan Pinhorn (jonpinhorn.typedesign@gmail.com), with Reserved Font Names 'Karla'"
+Karla Tamil Upright,normal,700,KarlaTamilUpright-Bold.ttf,KarlaTamilUpright-Bold,Karla Tamil Upright Bold,"Copyright (c) 2011-2012, Jonathan Pinhorn (jonpinhorn.typedesign@gmail.com), with Reserved Font Names 'Karla'"
+Karma,normal,300,Karma-Light.ttf,Karma-Light,Karma Light,Copyright 2014 Indian Type Foundry. All rights reserved.
+Karma,normal,400,Karma-Regular.ttf,Karma-Regular,Karma Regular,Copyright 2014 Indian Type Foundry. All rights reserved.
+Karma,normal,500,Karma-Medium.ttf,Karma-Medium,Karma Medium,Copyright 2014 Indian Type Foundry. All rights reserved.
+Karma,normal,600,Karma-SemiBold.ttf,Karma-SemiBold,Karma SemiBold,Copyright 2014 Indian Type Foundry. All rights reserved.
+Karma,normal,700,Karma-Bold.ttf,Karma-Bold,Karma Bold,Copyright 2014 Indian Type Foundry. All rights reserved.
+Katibeh,normal,400,Katibeh-Regular.ttf,Katibeh-Regular,Katibeh Regular,"Copyright 2015, 2016 KB-Studio (www.k-b-studio.com|tarobish@gmail.com). Copyright 2015, 2016 Lasse Fister (lasse@graphicore.de). Copyright 2015, 2016 Eduardo Tunni(edu@tipo.net.ar)."
+Kaushan Script,normal,400,KaushanScript-Regular.ttf,KaushanScript-Regular,Kaushan Script,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), with Reserved Font Name Kaushan Script."
+Kavivanar,normal,400,Kavivanar-Regular.ttf,Kavivanar-Regular,Kavivanar Regular,"Copyright (c) 2015, Tharique Azeez (http://thariqueazeez.com|zeezat@gmail.com)"
+Kavoon,normal,400,Kavoon-Regular.ttf,Kavoon-Regular,Kavoon,"Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Kavoon'"
+Kdam Thmor,normal,400,KdamThmor-Regular.ttf,KdamThmor,Kdam Thmor,"Copyright (c) 2013 by Sovichet Tep with Reserved Font Name \Kdam Thmor\. Copyright (c) 2010-2011 by tyPoland Lukasz Dziedzic with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1."
+Keania One,normal,400,KeaniaOne-Regular.ttf,KeaniaOne-Regular,Keania One,"Copyright (c) 2012, Julia Petretta (julia.petretta@googlemail.com), with Reserved Font Name 'Keania'"
+Kelly Slab,normal,400,KellySlab-Regular.ttf,KellySlab-Regular,Kelly Slab,"Copyright (c) 2011, Denis Masharov <denis.masharov@gmail.com>, with Reserved Font Names \Kelly\, \Kelly Slab\."
+Kenia,normal,400,Kenia-Regular.ttf,Kenia-Regular,Kenia,"Copyright (c) 2010, Julia Petretta (julia.petretta@googlemail.com), with Reserved Font Name Kenia"
+Khand,normal,300,Khand-Light.ttf,Khand-Light,Khand Light,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Khand,normal,400,Khand-Regular.ttf,Khand-Regular,Khand Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Khand,normal,500,Khand-Medium.ttf,Khand-Medium,Khand Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Khand,normal,600,Khand-SemiBold.ttf,Khand-SemiBold,Khand SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Khand,normal,700,Khand-Bold.ttf,Khand-Bold,Khand Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Khmer,normal,400,Khmer.ttf,Khmer,Khmer,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Khula,normal,300,Khula-Light.ttf,Khula-Light,Khula Light,"Copyright (c) 2014, Erin McLaughlin (hello@erinmclaughlin.com). Digitized data copyright 2010, Google Corporation."
+Khula,normal,400,Khula-Regular.ttf,Khula-Regular,Khula Regular,"Copyright (c) 2014, Erin McLaughlin (hello@erinmclaughlin.com). Digitized data copyright 2010, Google Corporation."
+Khula,normal,600,Khula-SemiBold.ttf,Khula-SemiBold,Khula SemiBold,"Copyright (c) 2014, Erin McLaughlin (hello@erinmclaughlin.com). Digitized data copyright 2010, Google Corporation."
+Khula,normal,700,Khula-Bold.ttf,Khula-Bold,Khula Bold,"Copyright (c) 2014, Erin McLaughlin (hello@erinmclaughlin.com). Digitized data copyright 2010, Google Corporation."
+Khula,normal,800,Khula-ExtraBold.ttf,Khula-ExtraBold,Khula ExtraBold,"Copyright (c) 2014, Erin McLaughlin (hello@erinmclaughlin.com). Digitized data copyright 2010, Google Corporation."
+Kirang Haerang,normal,400,KirangHaerang-Regular.ttf,KirangHaerang-Regular,Kirang Haerang Regular,Copyright 2018 The Kirang Haerang Project Authors
+Kite One,normal,400,KiteOne-Regular.ttf,KiteOne-Regular,Kite One,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Kite'"
+Knewave,normal,400,Knewave-Regular.ttf,Knewave-Regular,Knewave,Copyright (c) 2011 by Tyler Finck (tylerfinck@gmail.com). All rights reserved.
+Kodchasan,normal,200,Kodchasan-ExtraLight.ttf,Kodchasan-ExtraLight,Kodchasan ExtraLight,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,italic,200,Kodchasan-ExtraLightItalic.ttf,Kodchasan-ExtraLightItalic,Kodchasan ExtraLight Italic,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,normal,300,Kodchasan-Light.ttf,Kodchasan-Light,Kodchasan Light,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,italic,300,Kodchasan-LightItalic.ttf,Kodchasan-LightItalic,Kodchasan Light Italic,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,normal,400,Kodchasan-Regular.ttf,Kodchasan-Regular,Kodchasan Regular,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,italic,400,Kodchasan-Italic.ttf,Kodchasan-Italic,Kodchasan Italic,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,normal,500,Kodchasan-Medium.ttf,Kodchasan-Medium,Kodchasan Medium,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,italic,500,Kodchasan-MediumItalic.ttf,Kodchasan-MediumItalic,Kodchasan Medium Italic,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,normal,600,Kodchasan-SemiBold.ttf,Kodchasan-SemiBold,Kodchasan SemiBold,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,italic,600,Kodchasan-SemiBoldItalic.ttf,Kodchasan-SemiBoldItalic,Kodchasan SemiBold Italic,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,normal,700,Kodchasan-Bold.ttf,Kodchasan-Bold,Kodchasan Bold,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+Kodchasan,italic,700,Kodchasan-BoldItalic.ttf,Kodchasan-BoldItalic,Kodchasan Bold Italic,Copyright 2018 The Kodchasan Project Authors (https://github.com/cadsondemak/Kodchasan)
+KoHo,normal,200,KoHo-ExtraLight.ttf,KoHo-ExtraLight,KoHo ExtraLight,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,italic,200,KoHo-ExtraLightItalic.ttf,KoHo-ExtraLightItalic,KoHo ExtraLight Italic,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,normal,300,KoHo-Light.ttf,KoHo-Light,KoHo Light,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,italic,300,KoHo-LightItalic.ttf,KoHo-LightItalic,KoHo Light Italic,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,normal,400,KoHo-Regular.ttf,KoHo-Regular,KoHo Regular,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,italic,400,KoHo-Italic.ttf,KoHo-Italic,KoHo Italic,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,normal,500,KoHo-Medium.ttf,KoHo-Medium,KoHo Medium,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,italic,500,KoHo-MediumItalic.ttf,KoHo-MediumItalic,KoHo Medium Italic,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,normal,600,KoHo-SemiBold.ttf,KoHo-SemiBold,KoHo SemiBold,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,italic,600,KoHo-SemiBoldItalic.ttf,KoHo-SemiBoldItalic,KoHo SemiBold Italic,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,normal,700,KoHo-Bold.ttf,KoHo-Bold,KoHo Bold,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+KoHo,italic,700,KoHo-BoldItalic.ttf,KoHo-BoldItalic,KoHo Bold Italic,Copyright 2018 The KoHo Project Authors (https://github.com/cadsondemak/Koho)
+Kotta One,normal,400,KottaOne-Regular.ttf,KottaOne-Regular,Kotta One,"Copyright (c) 2012 by Ania Kruk (hello@aniakruk.com), with Reserved Font Name \Kotta\"
+Koulen,normal,400,Koulen.ttf,Koulen,Koulen,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Koulen. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Kreon,normal,300,Kreon[wght].ttf,Kreon-Light,Kreon Light,Copyright 2018 The Kreon Project Authors (https://github.com/googlefonts/kreon)
+Kristi,normal,400,Kristi-Regular.ttf,Kristi-Regular,Kristi Regular,"Copyright (c) 2010, Birgit Pulk (birgitpulk@gmail.com). All rights reserved. Licenced under SIL OFL v1.1"
+Krona One,normal,400,KronaOne-Regular.ttf,KronaOne-Regular,Krona One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Krona\."
+Krub,normal,200,Krub-ExtraLight.ttf,Krub-ExtraLight,Krub ExtraLight,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,italic,200,Krub-ExtraLightItalic.ttf,Krub-ExtraLightItalic,Krub ExtraLight Italic,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,normal,300,Krub-Light.ttf,Krub-Light,Krub Light,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,italic,300,Krub-LightItalic.ttf,Krub-LightItalic,Krub Light Italic,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,normal,400,Krub-Regular.ttf,Krub-Regular,Krub Regular,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,italic,400,Krub-Italic.ttf,Krub-Italic,Krub Italic,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,normal,500,Krub-Medium.ttf,Krub-Medium,Krub Medium,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,italic,500,Krub-MediumItalic.ttf,Krub-MediumItalic,Krub Medium Italic,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,normal,600,Krub-SemiBold.ttf,Krub-SemiBold,Krub SemiBold,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,italic,600,Krub-SemiBoldItalic.ttf,Krub-SemiBoldItalic,Krub SemiBold Italic,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,normal,700,Krub-Bold.ttf,Krub-Bold,Krub Bold,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Krub,italic,700,Krub-BoldItalic.ttf,Krub-BoldItalic,Krub Bold Italic,Copyright 2018 The Krub Project Authors (https://github.com/cadsondemak/Krub)
+Kulim Park,normal,200,KulimPark-ExtraLight.ttf,KulimPark-ExtraLight,Kulim Park ExtraLight,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,italic,200,KulimPark-ExtraLightItalic.ttf,KulimPark-ExtraLightItalic,Kulim Park ExtraLight Italic,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,normal,300,KulimPark-Light.ttf,KulimPark-Light,Kulim Park Light,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,italic,300,KulimPark-LightItalic.ttf,KulimPark-LightItalic,Kulim Park Light Italic,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,normal,400,KulimPark-Regular.ttf,KulimPark-Regular,Kulim Park Regular,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,italic,400,KulimPark-Italic.ttf,KulimPark-Italic,Kulim Park Italic,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,normal,600,KulimPark-SemiBold.ttf,KulimPark-SemiBold,Kulim Park SemiBold,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,italic,600,KulimPark-SemiBoldItalic.ttf,KulimPark-SemiBoldItalic,Kulim Park SemiBold Italic,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,normal,700,KulimPark-Bold.ttf,KulimPark-Bold,Kulim Park Bold,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kulim Park,italic,700,KulimPark-BoldItalic.ttf,KulimPark-BoldItalic,Kulim Park Bold Italic,Copyright 2018 The Kulim Park Project Authors (https://github.com/noponies/Kulim-Park)
+Kumar One,normal,400,KumarOne-Regular.ttf,KumarOne-Regular,Kumar One Regular,Copyright (c) 2016 Indian Type Foundry (info@indiantypefoundry.com)
+Kurale,normal,400,Kurale-Regular.ttf,Kurale-Regular,Kurale Regular,Copyright 2013 The Kurale Project Authors (edu@tipo.net.ar)
+La Belle Aurore,normal,400,LaBelleAurore.ttf,LaBelleAurore,La Belle Aurore,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Lacquer,normal,400,Lacquer-Regular.ttf,Lacquer-Regular,Lacquer Regular,Copyright 2019 The Lacquer Project Authors (https://github.com/Lacquer-Font/Lacquer)
+Laila,normal,300,Laila-Light.ttf,Laila-Light,Laila Light,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Laila,normal,400,Laila-Regular.ttf,Laila-Regular,Laila Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Laila,normal,500,Laila-Medium.ttf,Laila-Medium,Laila Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Laila,normal,600,Laila-SemiBold.ttf,Laila-SemiBold,Laila SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Laila,normal,700,Laila-Bold.ttf,Laila-Bold,Laila Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Lakki Reddy,normal,400,LakkiReddy-Regular.ttf,LakkiReddy,Lakki Reddy,"Copyright (c) 2011 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2010 by Font Diner, Inc DBA Sideshow."
+Lalezar,normal,400,Lalezar-Regular.ttf,Lalezar-Regular,Lalezar Regular,Copyright 2015 The Lalezar Project Authors (https://github.com/BornaIz/Lalezar)
+Lancelot,normal,400,Lancelot-Regular.ttf,Lancelot,Lancelot,Copyright (c) 2011 by Marion Kadi (marionkadi@gmail.com). All rights reserved. Licenced under SIL OFL v1.1
+Lateef,normal,400,LateefRegOT.ttf,Lateef,Lateef,"Copyright (c) 2004-2008, SIL International (http://www.sil.org/), and released under the SIL Open Font License, with Reserved Font Names \Lateef\ and \SIL\."
+Lato,normal,100,Lato-Thin.ttf,Lato-Thin,Lato Thin,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,100,Lato-ThinItalic.ttf,Lato-ThinItalic,Lato Thin Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,200,Lato-ExtraLight.ttf,Lato-ExtraLight,Lato ExtraLight,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,200,Lato-ExtraLightItalic.ttf,Lato-ExtraLightItalic,Lato ExtraLight Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,300,Lato-Light.ttf,Lato-Light,Lato Light,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,300,Lato-LightItalic.ttf,Lato-LightItalic,Lato Light Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,400,Lato-Regular.ttf,Lato-Regular,Lato Regular,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,400,Lato-Italic.ttf,Lato-Italic,Lato Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,500,Lato-Medium.ttf,Lato-Medium,Lato Medium,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,500,Lato-MediumItalic.ttf,Lato-MediumItalic,Lato Medium Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,600,Lato-SemiBold.ttf,Lato-SemiBold,Lato SemiBold,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,600,Lato-SemiBoldItalic.ttf,Lato-SemiBoldItalic,Lato SemiBold Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,700,Lato-Bold.ttf,Lato-Bold,Lato Bold,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,700,Lato-BoldItalic.ttf,Lato-BoldItalic,Lato Bold Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,800,Lato-ExtraBold.ttf,Lato-ExtraBold,Lato ExtraBold,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,800,Lato-ExtraBoldItalic.ttf,Lato-ExtraBoldItalic,Lato ExtraBold Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,normal,900,Lato-Black.ttf,Lato-Black,Lato Black,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+Lato,italic,900,Lato-BlackItalic.ttf,Lato-BlackItalic,Lato Black Italic,"Copyright (c) 2011-2015 by tyPoland Lukasz Dziedzic (http://www.typoland.com/) with Reserved Font Name \Lato\. Licensed under the SIL Open Font License, Version 1.1 (http://scripts.sil.org/OFL)."
+League Gothic,normal,400,"LeagueGothic[slnt,wdth].ttf",LeagueGothic-Regular,League Gothic Regular,Copyright 2020 The League Gothic Project Authors (https://github.com/bghryct/league-gothic)
+League Script,normal,400,LeagueScript-Regular.ttf,LeagueScript,League Script,"Copyright (c) 2010, Haley Fiege (haley@kingdomofawesome.com"
+Leckerli One,normal,400,LeckerliOne-Regular.ttf,LeckerliOne-Regular,Leckerli One,"Copyright (c) 2011 Gesine Todt (www.gesine-todt.de hallo@gesine-todt.de), with Reserved Font Names \Leckerli\"
+Ledger,normal,400,Ledger-Regular.ttf,Ledger-Regular,Ledger,"Copyright (c) 2011, Denis Masharov <denis.masharov@gmail.com>."
+Lekton,normal,400,Lekton-Regular.ttf,Lekton-Regular,Lekton,"Copyright (c) 2008, 2009, 2010, Accademia di Belle Arti di Urbino (luciano.perondi@isiaurbino.net). Licensed under the SIL Open Font License, Version 1.1"
+Lekton,italic,400,Lekton-Italic.ttf,Lekton-Italic,Lekton-Italic,"Copyright (c) 2008, 2009, 2010, Accademia di Belle Arti di Urbino (luciano.perondi@isiaurbino.net). Licensed under the SIL Open Font License, Version 1.1"
+Lekton,normal,700,Lekton-Bold.ttf,Lekton-Bold,Lekton-Bold,"Copyright (c) 2008, 2009, 2010, Accademia di Belle Arti di Urbino (luciano.perondi@isiaurbino.net). Licensed under the SIL Open Font License, Version 1.1"
+Lemon,normal,400,Lemon-Regular.ttf,Lemon-Regular,Lemon Regular,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Lemon\"
+Lemonada,normal,400,Lemonada[wght].ttf,Lemonada-Regular,Lemonada Regular,Copyright 2011 The Lemonada Project Authors (https://github.com/Gue3bara/Lemonada)
+Lexend Deca,normal,400,LexendDeca-Regular.ttf,LexendDeca-Regular,Lexend Deca Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Lexend Exa,normal,400,LexendExa-Regular.ttf,LexendExa-Regular,Lexend Exa Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Lexend Giga,normal,400,LexendGiga-Regular.ttf,LexendGiga-Regular,Lexend Giga Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Lexend Mega,normal,400,LexendMega-Regular.ttf,LexendMega-Regular,Lexend Mega Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Lexend Peta,normal,400,LexendPeta-Regular.ttf,LexendPeta-Regular,Lexend Peta Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Lexend Tera,normal,400,LexendTera-Regular.ttf,LexendTera-Regular,Lexend Tera Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Lexend Zetta,normal,400,LexendZetta-Regular.ttf,LexendZetta-Regular,Lexend Zetta Regular,Copyright 2019 The Lexend Project Authors (https://github.com/ThomasJockin/lexend)
+Libre Barcode 128,normal,400,LibreBarcode128-Regular.ttf,LibreBarcode128-Regular,Libre Barcode 128 Regular,Copyright 2017 The Libre Barcode Project Authors (lasse@graphicore.de)
+Libre Barcode 128 Text,normal,400,LibreBarcode128Text-Regular.ttf,LibreBarcode128Text-Regular,Libre Barcode 128 Text Regular,Copyright 2017 The Libre Barcode Project Authors (lasse@graphicore.de)
+Libre Barcode 39,normal,400,LibreBarcode39-Regular.ttf,LibreBarcode39-Regular,Libre Barcode 39 Regular,Copyright 2017 The Libre Barcode Project Authors (lasse@graphicore.de)
+Libre Barcode 39 Extended,normal,400,LibreBarcode39Extended-Regular.ttf,LibreBarcode39Extended-Regular,Libre Barcode 39 Extended,Copyright 2017 The Libre Barcode Project Authors (lasse@graphicore.de)
+Libre Barcode 39 Extended Text,normal,400,LibreBarcode39ExtendedText-Regular.ttf,LibreBarcode39ExtendedText-Regular,Libre Barcode 39 Extended Text,Copyright 2017 The Libre Barcode Project Authors (lasse@graphicore.de)
+Libre Barcode 39 Text,normal,400,LibreBarcode39Text-Regular.ttf,LibreBarcode39Text-Regular,Libre Barcode 39 Text Regular,Copyright 2017 The Libre Barcode Project Authors (lasse@graphicore.de)
+Libre Baskerville,normal,400,LibreBaskerville-Regular.ttf,LibreBaskerville-Regular,Libre Baskerville,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), with Reserved Font Name Libre Baskerville."
+Libre Baskerville,italic,400,LibreBaskerville-Italic.ttf,LibreBaskerville-Italic,Libre Baskerville Italic,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), with Reserved Font Name Libre Baskerville."
+Libre Baskerville,normal,700,LibreBaskerville-Bold.ttf,LibreBaskerville-Bold,Libre Baskerville Bold,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), with Reserved Font Name Libre Baskerville."
+Libre Caslon Display,normal,400,LibreCaslonDisplay-Regular.ttf,LibreCaslonDisplay-Regular,Libre Caslon Display Regular,Copyright 2012 The Libre Caslon Display Authors (https://github.com/impallari/Libre-Caslon-Display)
+Libre Caslon Text,normal,400,LibreCaslonText-Regular.ttf,LibreCaslonText-Regular,Libre Caslon Text Regular,Copyright 2012 The Libre Caslon Text Project Authors (https://github.com/impallari/Libre-Caslon-Text)
+Libre Caslon Text,italic,400,LibreCaslonText-Italic.ttf,LibreCaslonText-Italic,Libre Caslon Text Italic,Copyright 2012 The Libre Caslon Text Project Authors (https://github.com/impallari/Libre-Caslon-Text)
+Libre Caslon Text,normal,700,LibreCaslonText-Bold.ttf,LibreCaslonText-Bold,Libre Caslon Text Bold,Copyright 2012 The Libre Caslon Text Project Authors (https://github.com/impallari/Libre-Caslon-Text)
+Libre Franklin,normal,100,LibreFranklin-Thin.ttf,LibreFranklin-Thin,Libre Franklin Thin,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,100,LibreFranklin-ThinItalic.ttf,LibreFranklin-ThinItalic,Libre Franklin Thin Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,200,LibreFranklin-ExtraLight.ttf,LibreFranklin-ExtraLight,Libre Franklin ExtraLight,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,200,LibreFranklin-ExtraLightItalic.ttf,LibreFranklin-ExtraLightItalic,Libre Franklin ExtraLight Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,300,LibreFranklin-Light.ttf,LibreFranklin-Light,Libre Franklin Light,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,300,LibreFranklin-LightItalic.ttf,LibreFranklin-LightItalic,Libre Franklin Light Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,400,LibreFranklin-Regular.ttf,LibreFranklin-Regular,Libre Franklin,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,400,LibreFranklin-Italic.ttf,LibreFranklin-Italic,Libre Franklin Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,500,LibreFranklin-Medium.ttf,LibreFranklin-Medium,Libre Franklin Medium,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,500,LibreFranklin-MediumItalic.ttf,LibreFranklin-MediumItalic,Libre Franklin Medium Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,600,LibreFranklin-SemiBold.ttf,LibreFranklin-SemiBold,Libre Franklin SemiBold,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,600,LibreFranklin-SemiBoldItalic.ttf,LibreFranklin-SemiBoldItalic,Libre Franklin SemiBold Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,700,LibreFranklin-Bold.ttf,LibreFranklin-Bold,Libre Franklin Bold,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,700,LibreFranklin-BoldItalic.ttf,LibreFranklin-BoldItalic,Libre Franklin Bold Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,800,LibreFranklin-ExtraBold.ttf,LibreFranklin-ExtraBold,Libre Franklin ExtraBold,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,800,LibreFranklin-ExtraBoldItalic.ttf,LibreFranklin-ExtraBoldItalic,Libre Franklin ExtraBold Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,normal,900,LibreFranklin-Black.ttf,LibreFranklin-Black,Libre Franklin Black,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Libre Franklin,italic,900,LibreFranklin-BlackItalic.ttf,LibreFranklin-BlackItalic,Libre Franklin Black Italic,"Copyright (c) 2015, Impallari Type (www.impallari.com)"
+Life Savers,normal,400,LifeSavers-Regular.ttf,LifeSavers-Regular,Life Savers Regular,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com),  Copyright (c) 2012, Igino Marini. (www.ikern.com|mail@iginomarini.com), with Reserved Font Name Life Savers."
+Life Savers,normal,700,LifeSavers-Bold.ttf,LifeSavers-Bold,Life Savers Bold,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com),  Copyright (c) 2012, Igino Marini. (www.ikern.com|mail@iginomarini.com), with Reserved Font Name Life Savers."
+Life Savers,normal,800,LifeSavers-ExtraBold.ttf,LifeSavers-ExtraBold,Life Savers ExtraBold,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com),\nCopyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), \nCopyright (c) 2012, Igino Marini. (www.ikern.com|mail@iginomarini.com),\nwith Reserved Font Name Life Savers."
+Lilita One,normal,400,LilitaOne-Regular.ttf,LilitaOne,Lilita One,"Copyright (c) 2011 Juan Montoreano (juan@remolacha.biz), with Reserved Font Names \Lilita One\"
+Lily Script One,normal,400,LilyScriptOne-Regular.ttf,LilyScriptOne-Regular,Lily Script One,"Copyright (c) 2012-2013, Julia Petretta (www.juliapetretta.com julia.petretta@googlemail.com), with Reserved Font Name 'Lily'"
+Limelight,normal,400,Limelight-Regular.ttf,Limelight,Limelight,"Copyright (c) 2010 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name Limelight. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Linden Hill,normal,400,LindenHill-Regular.ttf,LindenHill-Regular,Linden Hill Regular,"Copyright (c) 2010, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Linden Hill,italic,400,LindenHill-Italic.ttf,LindenHill-Italic,Linden Hill Italic,"Copyright (c) 2010, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Literata,normal,400,Literata[wght].ttf,Literata-Regular,Literata Regular,Copyright 2017 The Literata Project Authors (https://github.com/googlefonts/literata)
+Literata,italic,400,Literata-Italic[wght].ttf,Literata-Italic,Literata Italic,Copyright 2017 The Literata Project Authors (https://github.com/googlefonts/literata)
+Liu Jian Mao Cao,normal,400,LiuJianMaoCao-Regular.ttf,LiuJianMaoCao-Regular,Liu Jian Mao Cao Regular,Copyright 2018 The Liu Jian Mao Cao Project Authors (https://www.github.com/googlefonts/liujianmaocao)
+Livvic,normal,100,Livvic-Thin.ttf,Livvic-Thin,Livvic Thin,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,100,Livvic-ThinItalic.ttf,Livvic-ThinItalic,Livvic Thin Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,200,Livvic-ExtraLight.ttf,Livvic-ExtraLight,Livvic ExtraLight,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,200,Livvic-ExtraLightItalic.ttf,Livvic-ExtraLightItalic,Livvic ExtraLight Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,300,Livvic-Light.ttf,Livvic-Light,Livvic Light,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,300,Livvic-LightItalic.ttf,Livvic-LightItalic,Livvic Light Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,400,Livvic-Regular.ttf,Livvic-Regular,Livvic Regular,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,400,Livvic-Italic.ttf,Livvic-Italic,Livvic Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,500,Livvic-Medium.ttf,Livvic-Medium,Livvic Medium,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,500,Livvic-MediumItalic.ttf,Livvic-MediumItalic,Livvic Medium Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,600,Livvic-SemiBold.ttf,Livvic-SemiBold,Livvic SemiBold,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,600,Livvic-SemiBoldItalic.ttf,Livvic-SemiBoldItalic,Livvic SemiBold Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,700,Livvic-Bold.ttf,Livvic-Bold,Livvic Bold,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,700,Livvic-BoldItalic.ttf,Livvic-BoldItalic,Livvic Bold Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,normal,900,Livvic-Black.ttf,Livvic-Black,Livvic Black,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Livvic,italic,900,Livvic-BlackItalic.ttf,Livvic-BlackItalic,Livvic Black Italic,Copyright 2019 The Livvic Project Authors (https://github.com/Fonthausen/Livvic)
+Lobster,normal,400,Lobster-Regular.ttf,Lobster-Regular,Lobster Regular,"Copyright 2010 The Lobster Project Authors (https://github.com/impallari/The-Lobster-Font), with Reserved Font Name \Lobster\."
+Lobster Two,normal,400,LobsterTwo-Regular.ttf,LobsterTwo,Lobster Two,Copyright (c) 2011 by Pablo Impallari (www.impallari.com impallari@gmail.com). All rights reserved.
+Lobster Two,italic,400,LobsterTwo-Italic.ttf,LobsterTwo-Italic,Lobster Two Italic,Copyright (c) 2011 by Pablo Impallari (www.impallari.com impallari@gmail.com). All rights reserved.
+Lobster Two,normal,700,LobsterTwo-Bold.ttf,LobsterTwo-Bold,Lobster Two Bold,Copyright (c) 2011 by Pablo Impallari (www.impallari.com impallari@gmail.com). All rights reserved.
+Lobster Two,italic,700,LobsterTwo-BoldItalic.ttf,LobsterTwo-BoldItalic,Lobster Two Bold Italic,Copyright (c) 2011 by Pablo Impallari (www.impallari.com impallari@gmail.com). All rights reserved.
+Lohit Bengali,normal,400,Lohit-Bengali.ttf,Lohit-Bengali,Lohit Bengali,Copyright 2011 Lohit Fonts Project contributors (psatpute@redhat.com). <http://fedorahosted.org/lohit> Licensed under the SIL Open Font License 1.1 (see file OFL.txt)
+Lohit Tamil,normal,400,Lohit-Tamil.ttf,Lohit-Tamil,Lohit Tamil,Copyright 2011 Lohit Fonts Project contributors (psatpute@redhat.com). <http://fedorahosted.org/lohit> Licensed under the SIL Open Font License 1.1 (see file OFL.txt)
+Londrina Outline,normal,400,LondrinaOutline-Regular.ttf,LondrinaOutline-Regular,Londrina Outline Regular,"Copyright 2011 The Londrina Outline Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Outline\"
+Londrina Shadow,normal,400,LondrinaShadow-Regular.ttf,LondrinaShadow-Regular,Londrina Shadow Regular,"Copyright 2011 The Londrina Shadow Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Shadow\"
+Londrina Sketch,normal,400,LondrinaSketch-Regular.ttf,LondrinaSketch-Regular,Londrina Sketch Regular,"Copyright 2011 The Londrina Sketch Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Sketch\"
+Londrina Solid,normal,100,LondrinaSolid-Thin.ttf,LondrinaSolid-Thin,Londrina Solid Thin,"Copyright 2011 The Londrina Solid Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Solid\"
+Londrina Solid,normal,300,LondrinaSolid-Light.ttf,LondrinaSolid-Light,Londrina Solid Light,"Copyright 2011 The Londrina Solid Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Solid\"
+Londrina Solid,normal,400,LondrinaSolid-Regular.ttf,LondrinaSolid-Regular,Londrina Solid Regular,"Copyright 2011 The Londrina Solid Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Solid\"
+Londrina Solid,normal,900,LondrinaSolid-Black.ttf,LondrinaSolid-Black,Londrina Solid Black,"Copyright 2011 The Londrina Solid Authors (https://github.com/marcelommp/Londrina-Typeface), with Reserved Font Name \Londrina Solid\"
+Long Cang,normal,400,LongCang-Regular.ttf,LongCang-Regular,Long Cang Regular,Copyright 2018 The LongCang Project Authors (https://github.com/googlefonts/longcang)
+Lora,normal,400,Lora[wght].ttf,Lora-Regular,Lora Regular,"Copyright 2011 The Lora Project Authors (https://github.com/cyrealtype/Lora-Cyrillic), with Reserved Font Name \Lora\."
+Lora,italic,400,Lora-Italic[wght].ttf,Lora-Italic,Lora Italic,"Copyright 2011 The Lora Project Authors (https://github.com/cyrealtype/Lora-Cyrillic), with Reserved Font Name \Lora\."
+Loved by the King,normal,400,LovedbytheKing.ttf,LovedbytheKing,Loved by the King,Copyright (c) 2006 by Kimberly Geswein (kimberlygeswein@gmail.com). All rights reserved.
+Lovers Quarrel,normal,400,LoversQuarrel-Regular.ttf,LoversQuarrel-Regular,Lovers Quarrel,"Copyright (c) 2012 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Lovers Quarrel\"
+Love Ya Like A Sister,normal,400,LoveYaLikeASister.ttf,LoveYaLikeASister-Regular,Love Ya Like A Sister Regular,Copyright (c) 2011 by Kimberly Geswein (kimberlygeswein@gmail.com). All rights reserved.
+Lusitana,normal,400,Lusitana-Regular.ttf,Lusitana,Lusitana,"Copyright (c) 2011 by Ana Paula Megda (www.anamegda.com|anapbm@gmail.com), with Reserved Font Name Lusitana."
+Lusitana,normal,700,Lusitana-Bold.ttf,Lusitana-Bold,Lusitana Bold,"Copyright (c) 2011 by Ana Paula Megda (www.anamegda.com|anapbm@gmail.com), with Reserved Font Name Lusitana."
+Lustria,normal,400,Lustria-Regular.ttf,Lustria-Regular,Lustria,"Copyright (c) 2011, Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name Lustria"
+Macondo,normal,400,Macondo-Regular.ttf,Macondo-Regular,Macondo,"Copyright (c) 1997 - 2011, John Vargas Beltran. (www.johnvargasbeltran.com|john.vargasbeltran@gmail.com), with Reserved Font Name \Macondo\"
+Macondo Swash Caps,normal,400,MacondoSwashCaps-Regular.ttf,MacondoSwashCaps-Regular,Macondo Swash Caps,"Copyright (c) 1997 - 2011, John Vargas Beltran. (www.johnvargasbeltran.com|john.vargasbeltran@gmail.com), with Reserved Font Name \Macondo\"
+Mada,normal,200,Mada-ExtraLight.ttf,Mada-ExtraLight,Mada ExtraLight,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Mada,normal,300,Mada-Light.ttf,Mada-Light,Mada Light,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Mada,normal,400,Mada-Regular.ttf,Mada-Regular,Mada Regular,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Mada,normal,500,Mada-Medium.ttf,Mada-Medium,Mada Medium,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Mada,normal,600,Mada-SemiBold.ttf,Mada-SemiBold,Mada SemiBold,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Mada,normal,700,Mada-Bold.ttf,Mada-Bold,Mada Bold,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Mada,normal,900,Mada-Black.ttf,Mada-Black,Mada Black,"Copyright  2015-2016 The Mada Project Authors, with Reserved Font Name \Source\. Source is a trademark of Adobe Systems Incorporated in the United States and/or other countries."
+Magra,normal,400,Magra-Regular.ttf,Magra,Magra,"Copyright (c) 2011, FontFuror (info@fontfuror.com), with Reserved Names \Magra\ \Magra Pro\"
+Magra,normal,700,Magra-Bold.ttf,Magra-Bold,Magra Bold,"Copyright (c) 2011, FontFuror (info@fontfuror.com), with Reserved Names \Magra\ \Magra Pro\"
+Maitree,normal,200,Maitree-ExtraLight.ttf,Maitree-ExtraLight,Maitree ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Maitree,normal,300,Maitree-Light.ttf,Maitree-Light,Maitree Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Maitree,normal,400,Maitree-Regular.ttf,Maitree-Regular,Maitree Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Maitree,normal,500,Maitree-Medium.ttf,Maitree-Medium,Maitree Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Maitree,normal,600,Maitree-SemiBold.ttf,Maitree-SemiBold,Maitree SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Maitree,normal,700,Maitree-Bold.ttf,Maitree-Bold,Maitree Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Major Mono Display,normal,400,MajorMonoDisplay-Regular.ttf,MajorMonoDisplay-Regular,Major Mono Display Regular,Copyright 2018 The Major Mono Project Authors (https://github.com/googlefonts/majormono)
+Mako,normal,400,Mako-Regular.ttf,Mako,Mako,Copyright (c) 2007 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Mako'. All rights reserved.
+Mali,normal,200,Mali-ExtraLight.ttf,Mali-ExtraLight,Mali ExtraLight,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,italic,200,Mali-ExtraLightItalic.ttf,Mali-ExtraLightItalic,Mali ExtraLight Italic,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,normal,300,Mali-Light.ttf,Mali-Light,Mali Light,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,italic,300,Mali-LightItalic.ttf,Mali-LightItalic,Mali Light Italic,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,normal,400,Mali-Regular.ttf,Mali-Regular,Mali Regular,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,italic,400,Mali-Italic.ttf,Mali-Italic,Mali Italic,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,normal,500,Mali-Medium.ttf,Mali-Medium,Mali Medium,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,italic,500,Mali-MediumItalic.ttf,Mali-MediumItalic,Mali Medium Italic,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,normal,600,Mali-SemiBold.ttf,Mali-SemiBold,Mali SemiBold,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,italic,600,Mali-SemiBoldItalic.ttf,Mali-SemiBoldItalic,Mali SemiBold Italic,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,normal,700,Mali-Bold.ttf,Mali-Bold,Mali Bold,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mali,italic,700,Mali-BoldItalic.ttf,Mali-BoldItalic,Mali Bold Italic,Copyright 2018 The Mali Project Authors (https://github.com/cadsondemak/Mali)
+Mallanna,normal,400,Mallanna-Regular.ttf,Mallanna,Mallanna,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Name Nunito"
+Mandali,normal,400,Mandali-Regular.ttf,Mandali,Mandali,"Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Name Nunito"
+Manjari,normal,100,Manjari-Thin.ttf,Manjari-Thin,Manjari Thin,Copyright 2018 The Manjari Project Authors (https://gitlab.com/smc/fonts/manjari)
+Manjari,normal,400,Manjari-Regular.ttf,Manjari-Regular,Manjari Regular,Copyright 2018 The Manjari Project Authors (https://gitlab.com/smc/fonts/manjari)
+Manjari,normal,700,Manjari-Bold.ttf,Manjari-Bold,Manjari Bold,Copyright 2018 The Manjari Project Authors (https://gitlab.com/smc/fonts/manjari)
+Manrope,normal,400,Manrope[wght].ttf,Manrope-ExtraLight,Manrope ExtraLight,Copyright 2019 The Manrope Project Authors (https://github.com/sharanda/manrope)
+Mansalva,normal,400,Mansalva-Regular.ttf,Mansalva-Regular,Mansalva Regular,Copyright 2019 The Mansalva Project Authors (https://github.com/carolinashort/mansalva)
+Manuale,normal,400,Manuale[wght].ttf,Manuale-Regular,Manuale Regular,Copyright 2016 The Manuale Project Authors (https://github.com/Omnibus-Type/Manuale)
+Manuale,italic,400,Manuale-Italic[wght].ttf,Manuale-Italic,Manuale Italic,Copyright 2016 The Manuale Project Authors (https://github.com/Omnibus-Type/Manuale)
+Marcellus,normal,400,Marcellus-Regular.ttf,Marcellus-Regular,Marcellus,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Marcellus\"
+Marcellus SC,normal,400,MarcellusSC-Regular.ttf,MarcellusSC-Regular,Marcellus SC,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Marcellus\"
+Marck Script,normal,400,MarckScript-Regular.ttf,MarckScript-Regular,Marck Script,"Copyright (c) 2011, Denis Masharov <denis.masharov@gmail.com>, Marck Fogel, with Reserved Font Names \Marck Script\."
+Margarine,normal,400,Margarine-Regular.ttf,Margarine-Regular,Margarine,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Margarine\"
+Markazi Text,normal,400,MarkaziText[wght].ttf,MarkaziText-Regular,Markazi Text Regular,Copyright 2017 The Markazi Text Authors (https://github.com/BornaIz/markazitext)
+Marko One,normal,400,MarkoOne-Regular.ttf,MarkoOne-Regular,Marko One,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Marko\ and \Marko One\."
+Marmelad,normal,400,Marmelad-Regular.ttf,Marmelad-Regular,Marmelad Regular,"Copyright 2016 The Marmelad Project Authors (manveltype@gmail.com), with Reserved Font Name \Marmelad\."
+Martel,normal,200,Martel-UltraLight.ttf,Martel-UltraLight,Martel UltraLight,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel,normal,300,Martel-Light.ttf,Martel-Light,Martel Light,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel,normal,400,Martel-Regular.ttf,Martel-Regular,Martel,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel,normal,600,Martel-DemiBold.ttf,Martel-DemiBold,Martel DemiBold,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel,normal,700,Martel-Bold.ttf,Martel-Bold,Martel Bold,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel,normal,800,Martel-ExtraBold.ttf,Martel-ExtraBold,Martel ExtraBold,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel,normal,900,Martel-Heavy.ttf,Martel-Heavy,Martel Heavy,"Copyright (c) 2015 Dan Reynolds. Copyright (c) 2010-2015, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Merriweather'"
+Martel Sans,normal,200,MartelSans-ExtraLight.ttf,MartelSans-ExtraLight,Martel Sans ExtraLight,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Martel Sans,normal,300,MartelSans-Light.ttf,MartelSans-Light,Martel Sans Light,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Martel Sans,normal,400,MartelSans-Regular.ttf,MartelSans-Regular,Martel Sans Regular,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Martel Sans,normal,600,MartelSans-SemiBold.ttf,MartelSans-SemiBold,Martel Sans SemiBold,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Martel Sans,normal,700,MartelSans-Bold.ttf,MartelSans-Bold,Martel Sans Bold,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Martel Sans,normal,800,MartelSans-ExtraBold.ttf,MartelSans-ExtraBold,Martel Sans ExtraBold,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Martel Sans,normal,900,MartelSans-Black.ttf,MartelSans-Black,Martel Sans Black,Copyright (c) 2014 Dan Reynolds. Copyright (c) 2014 Mathieu Rguer.
+Marvel,normal,400,Marvel-Regular.ttf,Marvel-Regular,Marvel,"Copyright (c) 2011, Carolina Trebol <ca@fromzero.org>, with Reserved Font Name \Marvel\."
+Marvel,italic,400,Marvel-Italic.ttf,Marvel-Italic,Marvel Italic,"Copyright (c) 2011, Carolina Trebol <ca@fromzero.org>, with Reserved Font Name \Marvel\."
+Marvel,normal,700,Marvel-Bold.ttf,Marvel-Bold,Marvel Bold,"Copyright (c) 2011, Carolina Trebol <ca@fromzero.org>, with Reserved Font Name \Marvel\."
+Marvel,italic,700,Marvel-BoldItalic.ttf,Marvel-BoldItalic,Marvel Bold Italic,"Copyright (c) 2011, Carolina Trebol <ca@fromzero.org>, with Reserved Font Name \Marvel\."
+Ma Shan Zheng,normal,400,MaShanZheng-Regular.ttf,MaShanZheng-Regular,Ma Shan Zheng Regular,Copyright 2018 The MaShanZheng Project Authors (https://github.com/googlefonts/mashanzheng)
+Mate,normal,400,Mate-Regular.ttf,Mate-Regular,Mate-Regular,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Mate\"
+Mate,italic,400,Mate-Italic.ttf,Mate-Italic,Mate Italic,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Mate\"
+Mate SC,normal,400,MateSC-Regular.ttf,MateSC-Regular,Mate SC Regular,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Mate\"
+Maven Pro,normal,400,MavenPro[wght].ttf,MavenPro-Regular,Maven Pro Regular,"Copyright 2011 The Maven Pro Project Authors (http://www.vissol.co.uk/mavenpro/), with Reserved Font Name \Maven Pro\."
+McLaren,normal,400,McLaren-Regular.ttf,McLaren-Regular,McLaren,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \McLaren\"
+Meddon,normal,400,Meddon.ttf,Meddon,Meddon,Copyright (c) 2011 by Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Meddon'. All rights reserved.
+MedievalSharp,normal,400,MedievalSharp.ttf,MedievalSharp,MedievalSharp,"Copyright (c) 2011, Wojciech 'wmk69' Kalinowski (wmk69@o2.pl)"
+Medula One,normal,400,MedulaOne-Regular.ttf,MedulaOne-Regular,Medula One,"Copyright (c) 2011 by LatinoType Limitada (luciano@latinotype.com), with Reserved Font Names \Medula\"
+Meera Inimai,normal,400,MeeraInimai-Regular.ttf,MeeraInimai-Regular,Meera Inimai Regular,"Copyright 2012-2016 Hussain K.H, Santhosh Thottingal, Anilan NG, AKM Kutty, Swathanthra Malayalam Computing (http://smc.org.in)"
+Megrim,normal,400,Megrim.ttf,Megrim,Megrim,"Copyright (c) 2010, 2011 by Daniel Johnson (il.basso.buffo@gmail.com). Released under the terms of the SIL Open Font License."
+Meie Script,normal,400,MeieScript-Regular.ttf,MeieScript-Regular,Meie Script,"Copyright (c) 2011, 2012 Johan Kallas (johankallas@gmail.com), Mihkel Virkus (mihkelvirkus@gmail.com), with Reserved Font Name 'Meie Script'"
+Merge One,normal,400,MergeOne-Regular.ttf,MergeOne-Regular,Merge One,"Copyright (c) 2012, Kosal Sen, Philatype (holla@philatype.com), with Reserved Font Name 'Merge'"
+Merienda,normal,400,Merienda-Regular.ttf,Merienda-Regular_0_wt,Merienda,"Copyright (c) 2011-2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Merienda'"
+Merienda,normal,700,Merienda-Bold.ttf,Merienda-Bold,Merienda Bold,"Copyright (c) 2011-2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Merienda'"
+Merienda One,normal,400,MeriendaOne-Regular.ttf,MeriendaOne-Regular,Merienda One,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Merienda\"
+Merriweather,normal,300,Merriweather-Light.ttf,Merriweather-Light,Merriweather Light,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,italic,300,Merriweather-LightItalic.ttf,Merriweather-LightItalic,Merriweather Light Italic,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,normal,400,Merriweather-Regular.ttf,Merriweather-Regular,Merriweather Regular,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,italic,400,Merriweather-Italic.ttf,Merriweather-Italic,Merriweather Italic,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,normal,700,Merriweather-Bold.ttf,Merriweather-Bold,Merriweather Bold,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,italic,700,Merriweather-BoldItalic.ttf,Merriweather-BoldItalic,Merriweather Bold Italic,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,normal,900,Merriweather-Black.ttf,Merriweather-Black,Merriweather Black,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather,italic,900,Merriweather-BlackItalic.ttf,Merriweather-BlackItalic,Merriweather Black Italic,"Copyright 2016 The Merriweather Project Authors (https://github.com/EbenSorkin/Merriweather), with Reserved Font Name \Merriweather\."
+Merriweather Sans,normal,300,MerriweatherSans-Light.ttf,MerriweatherSans-Light,Merriweather Sans Light,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,italic,300,MerriweatherSans-LightItalic.ttf,MerriweatherSans-LightItalic,Merriweather Sans Light Italic,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,normal,400,MerriweatherSans-Regular.ttf,MerriweatherSans-Regular,Merriweather Sans,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,italic,400,MerriweatherSans-Italic.ttf,MerriweatherSans-Italic,Merriweather Sans Italic,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,normal,700,MerriweatherSans-Bold.ttf,MerriweatherSans-Bold,Merriweather Sans Bold,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,italic,700,MerriweatherSans-BoldItalic.ttf,MerriweatherSans-BoldItalic,Merriweather Sans Bold Italic,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,normal,800,MerriweatherSans-ExtraBold.ttf,MerriweatherSans-ExtraBold,Merriweather Sans ExtraBold,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Merriweather Sans,italic,800,MerriweatherSans-ExtraBoldItalic.ttf,MerriweatherSans-ExtraBoldItalic,Merriweather Sans ExtraBold Italic,"Copyright (c) 2013-2016, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name \'Merriweather\'"
+Mervale Script,normal,400,MervaleScript-Regular.ttf,MervaleScript-Regular,Mervale Script,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Mervale Script\"
+Metal,normal,400,Metal.ttf,Metal,Metal,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Metalchrieng. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Metal Mania,normal,400,MetalMania-Regular.ttf,MetalMania-Regular,Metal Mania,Copyright (c) 2012 by Open Window (dathanboardman@gmail.com) with Reseved Font Name \Metal Mania\
+Metamorphous,normal,400,Metamorphous-Regular.ttf,Metamorphous,Metamorphous,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Metamorphous\."
+Metrophobic,normal,400,Metrophobic-Regular.ttf,Metrophobic-Regular,Metrophobic Regular,"Copyright 2011 The Metrophobic Project Authors (https://github.com/googlefonts/MetrophobicFont), with Reserved Font Name \'Metrophobic\'."
+Miama,italic,400,Miama-Regular.ttf,Miama-Regular,Miama,"Copyright (c) 2008-2011, Linus Romer, with Reserved Font Name Miama. This Font Software is licensed under the SIL Open Font License, Version 1.1."
+Michroma,normal,400,Michroma.ttf,Michroma,Michroma,"Copyright (c) 2011, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Michroma'"
+Milonga,normal,400,Milonga-Regular.ttf,Milonga-Regular,Milonga,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Brenda Gallo (gbrenda1987@gmail.com), Copyright (c) 2011, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), with Reserved Font Name Milonga."
+Miltonian,normal,400,Miltonian-Regular.ttf,Miltonian-Regular,Miltonian,Copyright (c) 2011 by Pablo Impallari (www.impallari.com impallari@gmail.com). Igino Marini (www.ikern.com)
+Miltonian Tattoo,normal,400,MiltonianTattoo-Regular.ttf,MiltonianTattoo-Regular,Miltonian Tattoo,Copyright (c) 2011 by Pablo Impallari (www.impallari.com impallari@gmail.com). Igino Marini (www.ikern.com)
+Mina,normal,400,Mina-Regular.ttf,Mina-Regular,Mina,"Copyright 2015 The Mina Project Authors, with Reserved Font Name \'Exo\'"
+Mina,normal,700,Mina-Bold.ttf,Mina-Bold,Mina Bold,"Copyright 2015 The Mina Project Authors, with Reserved Font Name \'Exo\'"
+Miniver,normal,400,Miniver-Regular.ttf,Miniver,Miniver,Copyright (c) 2011 by Open Window (dathanboardman@gmail.com) with Reseved Font Name \Miniver\
+Miriam Libre,normal,400,MiriamLibre-Regular.ttf,MiriamLibre-Regular,Miriam Libre Regular,Copyright 2016 Michal Sahar. All rights reserved.
+Miriam Libre,normal,700,MiriamLibre-Bold.ttf,MiriamLibre-Bold,Miriam Libre Bold,Copyright 2016 Michal Sahar. All rights reserved.
+Mirza,normal,400,Mirza-Regular.ttf,Mirza-Regular,Mirza Regular,"Copyright 2015, 2016 KB-Studio (www.k-b-studio.com|tarobish@gmail.com). Copyright 2015, 2016 Lasse Fister (lasse@graphicore.de). Copyright 2015, 2016 Eduardo Tunni(edu@tipo.net.ar)."
+Mirza,normal,500,Mirza-Medium.ttf,Mirza-Medium,Mirza Medium,"Copyright 2015, 2016 KB-Studio (www.k-b-studio.com|tarobish@gmail.com). Copyright 2015, 2016 Lasse Fister (lasse@graphicore.de). Copyright 2015, 2016 Eduardo Tunni(edu@tipo.net.ar)."
+Mirza,normal,600,Mirza-SemiBold.ttf,Mirza-SemiBold,Mirza SemiBold,"Copyright 2015, 2016 KB-Studio (www.k-b-studio.com|tarobish@gmail.com). Copyright 2015, 2016 Lasse Fister (lasse@graphicore.de). Copyright 2015, 2016 Eduardo Tunni(edu@tipo.net.ar)."
+Mirza,normal,700,Mirza-Bold.ttf,Mirza-Bold,Mirza Bold,"Copyright 2015, 2016 KB-Studio (www.k-b-studio.com|tarobish@gmail.com). Copyright 2015, 2016 Lasse Fister (lasse@graphicore.de). Copyright 2015, 2016 Eduardo Tunni(edu@tipo.net.ar)."
+Miss Fajardose,normal,400,MissFajardose-Regular.ttf,MissFajardose-Regular,Miss Fajardose Regular,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \MissFajardose\"
+Miss Saint Delafield,normal,400,MrsSaintDelafield-Regular.ttf,MrsSaintDelafield-Regular,Mrs Saint Delafield Regular,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mrs Saint Delafield\"
+Mitr,normal,200,Mitr-ExtraLight.ttf,Mitr-ExtraLight,Mitr ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Mitr,normal,300,Mitr-Light.ttf,Mitr-Light,Mitr Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Mitr,normal,400,Mitr-Regular.ttf,Mitr-Regular,Mitr Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Mitr,normal,500,Mitr-Medium.ttf,Mitr-Medium,Mitr Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Mitr,normal,600,Mitr-SemiBold.ttf,Mitr-SemiBold,Mitr SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Mitr,normal,700,Mitr-Bold.ttf,Mitr-Bold,Mitr Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Modak,normal,400,Modak-Regular.ttf,Modak,Modak,Copyright (c) 2015 Ek Type (www.ektype.in)
+Modern Antiqua,normal,400,ModernAntiqua-Regular.ttf,ModernAntiqua-Regular,Modern Antiqua Regular,"Copyright (c) 2011, wmk69, (wmk69@o2.pl), with Reserved Font Names 'ModernAntiqua' and 'Modern Antiqua'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Mogra,normal,400,Mogra-Regular.ttf,Mogra-Regular,Mogra Regular,Copyright (c) 2015 Lipi Raval (raval.lipi@gmail.com)
+Mohave,normal,400,Mohave[wght].ttf,Mohave-Light,Mohave Light,Copyright 2019 The Mohave Project Authors (https://github.com/bghryct/Mohave-Typefaces)
+Mohave,italic,400,Mohave-Italic[wght].ttf,Mohave-LightItalic,Mohave Light Italic,Copyright 2019 The Mohave Project Authors (https://github.com/bghryct/Mohave-Typefaces)
+Molengo,normal,400,Molengo-Regular.ttf,Molengo-Regular,Molengo,"Copyright (c) 2007, Denis Moyogo Jacquerye <moyogo@gmail.com>, with Reserved Font Name Molengo"
+Molle,italic,400,Molle-Regular.ttf,Molle-Regular,Molle,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Spinnaker\."
+Monda,normal,400,Monda-Regular.ttf,Monda-Regular,Monda Regular,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Monda'"
+Monda,normal,700,Monda-Bold.ttf,Monda-Bold,Monda Bold,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Monda'"
+Monofett,normal,400,Monofett.ttf,Monofett,Monofett,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Monofett'. All rights reserved."
+Monoton,normal,400,Monoton-Regular.ttf,Monoton-Regular,Monoton,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Name 'Monoton'. All rights reserved."
+Monsieur La Doulaise,normal,400,MonsieurLaDoulaise-Regular.ttf,MonsieurLaDoulaise-Regular,Monsieur La Doulaise Regular,"Copyright (c) 2006 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \MonsieurLaDoulaise\"
+Montaga,normal,400,Montaga-Regular.ttf,Montaga-Regular,Montaga,"Copyright (c) 2011, Alejandra Rodriguez (ale_guez@yahoo.com.ar http://twitter.com/ale_guez), with Reserved Font Name \Montaga\"
+Montserrat,normal,100,Montserrat-Thin.ttf,Montserrat-Thin,Montserrat Thin,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,100,Montserrat-ThinItalic.ttf,Montserrat-ThinItalic,Montserrat Thin Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,200,Montserrat-ExtraLight.ttf,Montserrat-ExtraLight,Montserrat ExtraLight,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,200,Montserrat-ExtraLightItalic.ttf,Montserrat-ExtraLightItalic,Montserrat ExtraLight Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,300,Montserrat-Light.ttf,Montserrat-Light,Montserrat Light,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,300,Montserrat-LightItalic.ttf,Montserrat-LightItalic,Montserrat Light Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,400,Montserrat-Regular.ttf,Montserrat-Regular,Montserrat Regular,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,400,Montserrat-Italic.ttf,Montserrat-Italic,Montserrat Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,500,Montserrat-Medium.ttf,Montserrat-Medium,Montserrat Medium,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,500,Montserrat-MediumItalic.ttf,Montserrat-MediumItalic,Montserrat Medium Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,600,Montserrat-SemiBold.ttf,Montserrat-SemiBold,Montserrat SemiBold,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,600,Montserrat-SemiBoldItalic.ttf,Montserrat-SemiBoldItalic,Montserrat SemiBold Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,700,Montserrat-Bold.ttf,Montserrat-Bold,Montserrat Bold,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,700,Montserrat-BoldItalic.ttf,Montserrat-BoldItalic,Montserrat Bold Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,800,Montserrat-ExtraBold.ttf,Montserrat-ExtraBold,Montserrat ExtraBold,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,800,Montserrat-ExtraBoldItalic.ttf,Montserrat-ExtraBoldItalic,Montserrat ExtraBold Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,normal,900,Montserrat-Black.ttf,Montserrat-Black,Montserrat Black,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat,italic,900,Montserrat-BlackItalic.ttf,Montserrat-BlackItalic,Montserrat Black Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,100,MontserratAlternates-Thin.ttf,MontserratAlternates-Thin,Montserrat Alternates Thin,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,100,MontserratAlternates-ThinItalic.ttf,MontserratAlternates-ThinItalic,Montserrat Alternates Thin Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,200,MontserratAlternates-ExtraLight.ttf,MontserratAlternates-ExtraLight,Montserrat Alternates ExtraLight,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,200,MontserratAlternates-ExtraLightItalic.ttf,MontserratAlternates-ExtraLightItalic,Montserrat Alternates ExtraLight Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,300,MontserratAlternates-Light.ttf,MontserratAlternates-Light,Montserrat Alternates Light,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,300,MontserratAlternates-LightItalic.ttf,MontserratAlternates-LightItalic,Montserrat Alternates Light Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,400,MontserratAlternates-Regular.ttf,MontserratAlternates-Regular,Montserrat Alternates Regular,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,400,MontserratAlternates-Italic.ttf,MontserratAlternates-Italic,Montserrat Alternates Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,500,MontserratAlternates-Medium.ttf,MontserratAlternates-Medium,Montserrat Alternates Medium,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,500,MontserratAlternates-MediumItalic.ttf,MontserratAlternates-MediumItalic,Montserrat Alternates Medium Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,600,MontserratAlternates-SemiBold.ttf,MontserratAlternates-SemiBold,Montserrat Alternates SemiBold,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,600,MontserratAlternates-SemiBoldItalic.ttf,MontserratAlternates-SemiBoldItalic,Montserrat Alternates SemiBold Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,700,MontserratAlternates-Bold.ttf,MontserratAlternates-Bold,Montserrat Alternates Bold,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,700,MontserratAlternates-BoldItalic.ttf,MontserratAlternates-BoldItalic,Montserrat Alternates Bold Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,800,MontserratAlternates-ExtraBold.ttf,MontserratAlternates-ExtraBold,Montserrat Alternates ExtraBold,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,800,MontserratAlternates-ExtraBoldItalic.ttf,MontserratAlternates-ExtraBoldItalic,Montserrat Alternates ExtraBold Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,normal,900,MontserratAlternates-Black.ttf,MontserratAlternates-Black,Montserrat Alternates Black,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Alternates,italic,900,MontserratAlternates-BlackItalic.ttf,MontserratAlternates-BlackItalic,Montserrat Alternates Black Italic,Copyright 2011 The Montserrat Project Authors (https://github.com/JulietaUla/Montserrat)
+Montserrat Subrayada,normal,400,MontserratSubrayada-Regular.ttf,MontserratSubrayada-Regular,MontserratSubrayada-Regular,"Copyright (c) 2011-2012, Julieta Ulanovsky (julieta.ulanovsky@gmail.com), with Reserved Font Names 'Montserrat'"
+Montserrat Subrayada,normal,700,MontserratSubrayada-Bold.ttf,MontserratSubrayada-Bold,MontserratSubrayada-Bold,"Copyright (c) 2011-2012, Julieta Ulanovsky (julieta.ulanovsky@gmail.com), with Reserved Font Names 'Montserrat'"
+Moul,normal,400,Moul.ttf,Moul,Moul,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Moul. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Moulpali,normal,400,Moulpali.ttf,MoulPali,Moul Pali,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Moulpali. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Mouse Memoirs,normal,400,MouseMemoirs-Regular.ttf,MouseMemoirs-Regular,Mouse Memoirs,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name 'Mouse Memoirs'"
+Mr Bedford,normal,400,MrBedfort-Regular.ttf,MrBedfort-Regular,Mr Bedfort Regular,"Copyright (c) 2006 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mr Bedfort\"
+Mr Bedfort,normal,400,MrBedfort-Regular.ttf,MrBedfort-Regular,Mr Bedfort,"Copyright (c) 2006 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mr Bedfort\"
+Mr Dafoe,normal,400,MrDafoe-Regular.ttf,MrDafoe-Regular,Mr Dafoe Regular,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mr Dafoe\"
+Mr De Haviland,normal,400,MrDeHaviland-Regular.ttf,MrDeHaviland-Regular,Mr De Haviland Regular,"Copyright (c) 2006 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mr De Haviland\"
+Mrs Saint Delafield,normal,400,MrsSaintDelafield-Regular.ttf,MrsSaintDelafield-Regular,Mrs Saint Delafield,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mrs Saint Delafield\"
+Mrs Sheppards,normal,400,MrsSheppards-Regular.ttf,MrsSheppards-Regular,Mrs Sheppards Regular,"Copyright (c) 2004 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Mrs Sheppards\"
+Mukta,normal,200,Mukta-ExtraLight.ttf,Mukta-ExtraLight,Mukta ExtraLight,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta,normal,300,Mukta-Light.ttf,Mukta-Light,Mukta Light,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta,normal,400,Mukta-Regular.ttf,Mukta-Regular,Mukta Regular,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta,normal,500,Mukta-Medium.ttf,Mukta-Medium,Mukta Medium,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta,normal,600,Mukta-SemiBold.ttf,Mukta-SemiBold,Mukta SemiBold,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta,normal,700,Mukta-Bold.ttf,Mukta-Bold,Mukta Bold,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta,normal,800,Mukta-ExtraBold.ttf,Mukta-ExtraBold,Mukta ExtraBold,"Copyright (c) 2014, Girish Dalvi, Ek Type. All rights reserved."
+Mukta Mahee,normal,200,MuktaMahee-ExtraLight.ttf,MuktaMahee-ExtraLight,Mukta Mahee ExtraLight,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Mahee,normal,300,MuktaMahee-Light.ttf,MuktaMahee-Light,Mukta Mahee Light,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Mahee,normal,400,MuktaMahee-Regular.ttf,MuktaMahee-Regular,Mukta Mahee Regular,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Mahee,normal,500,MuktaMahee-Medium.ttf,MuktaMahee-Medium,Mukta Mahee Medium,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Mahee,normal,600,MuktaMahee-SemiBold.ttf,MuktaMahee-SemiBold,Mukta Mahee SemiBold,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Mahee,normal,700,MuktaMahee-Bold.ttf,MuktaMahee-Bold,Mukta Mahee Bold,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Mahee,normal,800,MuktaMahee-ExtraBold.ttf,MuktaMahee-ExtraBold,Mukta Mahee ExtraBold,"Copyright (c) 2017, Ek Type. All rights reserved."
+Mukta Malar,normal,200,MuktaMalar-ExtraLight.ttf,MuktaMalar-ExtraLight,Mukta Malar ExtraLight,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Malar,normal,300,MuktaMalar-Light.ttf,MuktaMalar-Light,Mukta Malar Light,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Malar,normal,400,MuktaMalar-Regular.ttf,MuktaMalar-Regular,Mukta Malar Regular,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Malar,normal,500,MuktaMalar-Medium.ttf,MuktaMalar-Medium,Mukta Malar Medium,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Malar,normal,600,MuktaMalar-SemiBold.ttf,MuktaMalar-SemiBold,Mukta Malar SemiBold,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Malar,normal,700,MuktaMalar-Bold.ttf,MuktaMalar-Bold,Mukta Malar Bold,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Malar,normal,800,MuktaMalar-ExtraBold.ttf,MuktaMalar-ExtraBold,Mukta Malar ExtraBold,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,200,MuktaVaani-ExtraLight.ttf,MuktaVaani-ExtraLight,Mukta Vaani ExtraLight,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,300,MuktaVaani-Light.ttf,MuktaVaani-Light,Mukta Vaani Light,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,400,MuktaVaani-Regular.ttf,MuktaVaani-Regular,Mukta Vaani Regular,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,500,MuktaVaani-Medium.ttf,MuktaVaani-Medium,Mukta Vaani Medium,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,600,MuktaVaani-SemiBold.ttf,MuktaVaani-SemiBold,Mukta Vaani SemiBold,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,700,MuktaVaani-Bold.ttf,MuktaVaani-Bold,Mukta Vaani Bold,"Copyright (c) 2016, Ek Type. All rights reserved."
+Mukta Vaani,normal,800,MuktaVaani-ExtraBold.ttf,MuktaVaani-ExtraBold,Mukta Vaani ExtraBold,"Copyright (c) 2016, Ek Type. All rights reserved."
+Muli,normal,400,Muli[wght].ttf,Muli-Regular,Muli Regular,Copyright 2016 The Muli Project Authors (https://github.com/googlefonts/MuliFont)
+Muli,italic,400,Muli-Italic[wght].ttf,Muli-Italic,Muli Italic,Copyright 2016 The Muli Project Authors (https://github.com/googlefonts/MuliFont)
+MuseoModerno,normal,400,MuseoModerno[wght].ttf,MuseoModerno-SemiBold,MuseoModerno SemiBold,Copyright 2020 The MuseoModerno Project Authors (https://github.com/Omnibus-Type/MuseoModerno)
+Mystery Quest,normal,400,MysteryQuest-Regular.ttf,MysteryQuest,Mystery Quest,"Copyright (c) 2012 by Font Diner, Inc DBA Sideshow (diner@fontdiner.com) with Reserved Font Name \Mystery Quest\"
+Nanum Brush Script,normal,400,NanumBrushScript-Regular.ttf,NanumBrush,Nanum Brush Script,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+Nanum Gothic,normal,400,NanumGothic-Regular.ttf,NanumGothic,NanumGothic,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+Nanum Gothic,normal,600,NanumGothic-Bold.ttf,NanumGothicBold,NanumGothicBold,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+Nanum Gothic,normal,700,NanumGothic-ExtraBold.ttf,NanumGothicExtraBold,NanumGothicExtraBold,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+Nanum Gothic Coding,normal,400,NanumGothicCoding-Regular.ttf,NanumGothicCoding,NanumGothicCoding,Copyright © 2009 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+Nanum Gothic Coding,normal,700,NanumGothicCoding-Bold.ttf,NanumGothicCoding-Bold,NanumGothicCoding-Bold,Copyright © 2009 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+Nanum Myeongjo,normal,400,NanumMyeongjo-Regular.ttf,NanumMyeongjo,NanumMyeongjo,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by FONTRIX.
+Nanum Myeongjo,normal,600,NanumMyeongjo-Bold.ttf,NanumMyeongjoBold,NanumMyeongjoBold,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by FONTRIX.
+Nanum Myeongjo,normal,700,NanumMyeongjo-ExtraBold.ttf,NanumMyeongjoExtraBold,NanumMyeongjoExtraBold,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by FONTRIX.
+Nanum Pen Script,normal,400,NanumPenScript-Regular.ttf,NanumPen,Nanum Pen,Copyright © 2010 NHN Corporation. All rights reserved. Font designed by Sandoll Communications Inc.
+NATS,normal,400,NATS-Regular.ttf,NATS,NATS,"Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2011-2012, Julieta Ulanovsky (julieta.ulanovsky@gmail.com), with Reserved Font Names 'Montserrat'"
+Neucha,normal,400,Neucha.ttf,Neucha,Neucha,Copyright (c) 2005-2010 by Jovanny Lemonad (lemonad@jovanny.ru). All rights reserved.
+Neuton,normal,200,Neuton-ExtraLight.ttf,Neuton-ExtraLight,Neuton ExtraLight,"Copyright 2010 The Neuton Project Authors (http://www.21326.info/), with Reserved Font Name \Neuton\."
+Neuton,normal,300,Neuton-Light.ttf,Neuton-Light,Neuton Light,"Copyright 2010 The Neuton Project Authors (http://www.21326.info/), with Reserved Font Name \Neuton\."
+Neuton,normal,400,Neuton-Regular.ttf,Neuton-Regular,Neuton Regular,"Copyright 2010 The Neuton Project Authors (http://www.21326.info/), with Reserved Font Name \Neuton\."
+Neuton,italic,400,Neuton-Italic.ttf,Neuton-Italic,Neuton Italic,"Copyright 2010 The Neuton Project Authors (http://www.21326.info/), with Reserved Font Name \Neuton\."
+Neuton,normal,700,Neuton-Bold.ttf,Neuton-Bold,Neuton Bold,"Copyright 2010 The Neuton Project Authors (http://www.21326.info/), with Reserved Font Name \Neuton\."
+Neuton,normal,800,Neuton-ExtraBold.ttf,Neuton-ExtraBold,Neuton ExtraBold,"Copyright 2010 The Neuton Project Authors (http://www.21326.info/), with Reserved Font Name \Neuton\."
+New Rocker,normal,400,NewRocker-Regular.ttf,NewRocker-Regular,New Rocker,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2012, Brenda Gallo (gbrenda1987@gmail.com), Copyright (c) 2012, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com), with Reserved Font Name 'New Rocker'"
+News Cycle,normal,400,NewsCycle-Regular.ttf,NewsCycle,News Cycle,"Copyright (c) 2010-2011, Nathan Willis (nwillis@glyphography.com), with Reserved Font Name \News Cycle.\"
+News Cycle,normal,700,NewsCycle-Bold.ttf,NewsCycle-Bold,News Cycle Bold,"Copyright (c) 2010-2011, Nathan Willis (nwillis@glyphography.com), with Reserved Font Name \News Cycle.\"
+Niconne,normal,400,Niconne-Regular.ttf,Niconne-Regular,Niconne,"Copyright (c) 2011 by vernon adams (vern@newtypography.co.uk), with Reserved Font Name Niconne."
+Niramit,normal,200,Niramit-ExtraLight.ttf,Niramit-ExtraLight,Niramit ExtraLight,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,italic,200,Niramit-ExtraLightItalic.ttf,Niramit-ExtraLightItalic,Niramit ExtraLight Italic,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,normal,300,Niramit-Light.ttf,Niramit-Light,Niramit Light,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,italic,300,Niramit-LightItalic.ttf,Niramit-LightItalic,Niramit Light Italic,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,normal,400,Niramit-Regular.ttf,Niramit-Regular,Niramit Regular,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,italic,400,Niramit-Italic.ttf,Niramit-Italic,Niramit Italic,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,normal,500,Niramit-Medium.ttf,Niramit-Medium,Niramit Medium,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,italic,500,Niramit-MediumItalic.ttf,Niramit-MediumItalic,Niramit Medium Italic,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,normal,600,Niramit-SemiBold.ttf,Niramit-SemiBold,Niramit SemiBold,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,italic,600,Niramit-SemiBoldItalic.ttf,Niramit-SemiBoldItalic,Niramit SemiBold Italic,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,normal,700,Niramit-Bold.ttf,Niramit-Bold,Niramit Bold,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Niramit,italic,700,Niramit-BoldItalic.ttf,Niramit-BoldItalic,Niramit Bold Italic,Copyright 2018 The Niramit Project Authors (https://github.com/cadsondemak/Niramit)
+Nixie One,normal,400,NixieOne-Regular.ttf,NixieOne-Regular,Nixie One,"Copyright (c) 2011, Jovanny Lemonad (lemonad@jovanny.ru), with Reserved Font Name \Nixie\"
+Nobile,normal,400,Nobile-Regular.ttf,Nobile-Regular,Nobile,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Nobile'. All rights reserved.
+Nobile,italic,400,Nobile-Italic.ttf,Nobile-Italic,Nobile Italic,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Nobile'. All rights reserved.
+Nobile,normal,500,Nobile-Medium.ttf,Nobile-Medium,Nobile Medium,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Nobile'. All rights reserved.
+Nobile,italic,500,Nobile-MediumItalic.ttf,Nobile-MediumItalic,Nobile Medium Italic,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Nobile'. All rights reserved.
+Nobile,normal,700,Nobile-Bold.ttf,Nobile-Bold,Nobile Bold,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Nobile'. All rights reserved.
+Nobile,italic,700,Nobile-BoldItalic.ttf,Nobile-BoldItalic,Nobile Bold Italic,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Nobile'. All rights reserved.
+Norican,normal,400,Norican-Regular.ttf,Norican-Regular,Norican Regular,"Copyright (c) 2011 by vernon adams (www.newtypography.co.uk vern@newtypography.co.uk), with Reserved Font Names \Norican\"
+Nosifer,normal,400,Nosifer-Regular.ttf,Nosifer-Regular,Nosifer,"Copyright (c) 2011, Vernon Adams DBA Typomondo (vern@newtypography.co.uk), with Reserved Font Name \Nosifer\"
+Nosifer Caps,normal,400,NosiferCaps-Regular.ttf,NosiferCaps-Regular,Nosifer Caps Regular,"Copyright (c) 2011, Vernon Adams DBA Typomondo (vern@newtypography.co.uk), with Reserved Font Name \Nosifer\"
+Notable,normal,400,Notable-Regular.ttf,Notable-Regular,Notable Regular,Copyright 2018 The Notable Project Authors (https://github.com/googlefonts/notable)
+Nothing You Could Do,normal,400,NothingYouCouldDo.ttf,NothingYouCouldDo,Nothing You Could Do,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com). This Font Software is licensed under the SIL Open Font License, Version 1.1. This license available with a FAQ at: http://scripts.sil.org/OFL"
+Noticia Text,normal,400,NoticiaText-Regular.ttf,NoticiaText-Regular,Noticia Text,"Copyright (c) 2011 JM Sole (info@jmsole.cl), with Reserved Font Name \Noticia Text\."
+Noticia Text,italic,400,NoticiaText-Italic.ttf,NoticiaText-Italic,Noticia Text Italic,"Copyright (c) 2011 JM Sole (info@jmsole.cl), with Reserved Font Name \Noticia Text\."
+Noticia Text,normal,700,NoticiaText-Bold.ttf,NoticiaText-Bold,Noticia Text Bold,"Copyright (c) 2011 JM Sole (info@jmsole.cl), with Reserved Font Name \Noticia Text\."
+Noticia Text,italic,700,NoticiaText-BoldItalic.ttf,NoticiaText-BoldItalic,Noticia Text Bold Italic,"Copyright (c) 2011 JM Sole (info@jmsole.cl), with Reserved Font Name \Noticia Text\."
+Noto Sans,normal,400,NotoSans-Regular.ttf,NotoSans,Noto Sans,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Sans,italic,400,NotoSans-Italic.ttf,NotoSans-Italic,Noto Sans Italic,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Sans,normal,700,NotoSans-Bold.ttf,NotoSans-Bold,Noto Sans Bold,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Sans,italic,700,NotoSans-BoldItalic.ttf,NotoSans-BoldItalic,Noto Sans Bold Italic,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Serif,normal,400,NotoSerif-Regular.ttf,NotoSerif,Noto Serif,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Serif,italic,400,NotoSerif-Italic.ttf,NotoSerif-Italic,Noto Serif Italic,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Serif,normal,700,NotoSerif-Bold.ttf,NotoSerif-Bold,Noto Serif Bold,Copyright 2012 Google Inc. All Rights Reserved.
+Noto Serif,italic,700,NotoSerif-BoldItalic.ttf,NotoSerif-BoldItalic,Noto Serif Bold Italic,Copyright 2012 Google Inc. All Rights Reserved.
+Nova Cut,normal,400,NovaCut.ttf,NovaCut,Nova Cut,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names 'NovaCut' and 'Nova Cut'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Nova Flat,normal,400,NovaFlat.ttf,NovaFlat,Nova Flat,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names 'NovaFlat' and 'Nova Flat'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Nova Mono,normal,400,NovaMono.ttf,NovaMono,NovaMono,"Copyright (c) 2011, Wojciech 'wmk69' Kalinowski (wmk69@o2.pl)"
+Nova Oval,normal,400,NovaOval.ttf,NovaOval,Nova Oval,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names 'NovaOval' and 'Nova Oval'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Nova Round,normal,400,NovaRound.ttf,NovaRound,Nova Round,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names 'NovaRound' and 'Nova Round'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Nova Script,normal,400,NovaScript-Regular.ttf,NovaScript-Regular,Nova Script Regular,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names \'NovaScript\' and \'Nova Script\'"
+Nova Slim,normal,400,NovaSlim.ttf,NovaSlim,Nova Slim,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names 'NovaSlim' and 'Nova Slim'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Nova Square,normal,400,NovaSquare.ttf,NovaSquare,Nova Square,"Copyright (c) 2011, wmk69 (wmk69@o2.pl) with Reserved Font Names 'NovaSquare' and 'Nova Square'. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+NTR,normal,400,NTR-Regular.ttf,NTR,NTR,"Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2011, Joe Prince, Admix Designs (http://www.admixdesigns.com/) with Reserved Font Name Varela Round."
+Numans,normal,400,Numans-Regular.ttf,Numans-Regular,Numans,Copyright (c) 2011 by Jovanny Lemonad (lemonad@jovanny.ru). All rights reserved.
+Nunito,normal,200,Nunito-ExtraLight.ttf,Nunito-ExtraLight,Nunito ExtraLight,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,200,Nunito-ExtraLightItalic.ttf,Nunito-ExtraLightItalic,Nunito ExtraLight Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,normal,300,Nunito-Light.ttf,Nunito-Light,Nunito Light,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,300,Nunito-LightItalic.ttf,Nunito-LightItalic,Nunito Light Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,normal,400,Nunito-Regular.ttf,Nunito-Regular,Nunito Regular,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,400,Nunito-Italic.ttf,Nunito-Italic,Nunito Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,normal,600,Nunito-SemiBold.ttf,Nunito-SemiBold,Nunito SemiBold,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,600,Nunito-SemiBoldItalic.ttf,Nunito-SemiBoldItalic,Nunito SemiBold Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,normal,700,Nunito-Bold.ttf,Nunito-Bold,Nunito Bold,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,700,Nunito-BoldItalic.ttf,Nunito-BoldItalic,Nunito Bold Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,normal,800,Nunito-ExtraBold.ttf,Nunito-ExtraBold,Nunito ExtraBold,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,800,Nunito-ExtraBoldItalic.ttf,Nunito-ExtraBoldItalic,Nunito ExtraBold Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,normal,900,Nunito-Black.ttf,Nunito-Black,Nunito Black,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito,italic,900,Nunito-BlackItalic.ttf,Nunito-BlackItalic,Nunito Black Italic,Copyright 2014 The Nunito Project Authors (https://github.com/googlefonts/NunitoFont)
+Nunito Sans,normal,200,NunitoSans-ExtraLight.ttf,NunitoSans-ExtraLight,Nunito Sans ExtraLight,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,200,NunitoSans-ExtraLightItalic.ttf,NunitoSans-ExtraLightItalic,Nunito Sans ExtraLight Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,normal,300,NunitoSans-Light.ttf,NunitoSans-Light,Nunito Sans Light,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,300,NunitoSans-LightItalic.ttf,NunitoSans-LightItalic,Nunito Sans Light Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,normal,400,NunitoSans-Regular.ttf,NunitoSans-Regular,Nunito Sans Regular,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,400,NunitoSans-Italic.ttf,NunitoSans-Italic,Nunito Sans Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,normal,600,NunitoSans-SemiBold.ttf,NunitoSans-SemiBold,Nunito Sans SemiBold,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,600,NunitoSans-SemiBoldItalic.ttf,NunitoSans-SemiBoldItalic,Nunito Sans SemiBold Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,normal,700,NunitoSans-Bold.ttf,NunitoSans-Bold,Nunito Sans Bold,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,700,NunitoSans-BoldItalic.ttf,NunitoSans-BoldItalic,Nunito Sans Bold Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,normal,800,NunitoSans-ExtraBold.ttf,NunitoSans-ExtraBold,Nunito Sans ExtraBold,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,800,NunitoSans-ExtraBoldItalic.ttf,NunitoSans-ExtraBoldItalic,Nunito Sans ExtraBold Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,normal,900,NunitoSans-Black.ttf,NunitoSans-Black,Nunito Sans Black,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Nunito Sans,italic,900,NunitoSans-BlackItalic.ttf,NunitoSans-BlackItalic,Nunito Sans Black Italic,Copyright 2016 The Nunito Project Authors (contact@sansoxygen.com)
+Odibee Sans,normal,400,OdibeeSans-Regular.ttf,OdibeeSans-Regular,Odibee Sans Regular,Copyright 2017 The Odibee Sans Project Authors (https://github.com/barnard555/odibeesans)
+Odor Mean Chey,normal,400,OdorMeanChey.ttf,OdorMeanChey,OdorMeanChey,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name NiDA OdorMeanChey. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Offside,normal,400,Offside-Regular.ttf,Offside-Regular,Offside,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Offside'"
+OFL Sorts Mill Goudy TT,normal,400,OFLGoudyStMTT.ttf,OFLGoudyStMTT,OFL Sorts Mill Goudy TT,Copyright (c) 2009 Barry Schwartz (http://crudfactory.com chemoelectric@chemoelectric.org)
+OFL Sorts Mill Goudy TT,italic,400,OFLGoudyStMTT-Italic.ttf,OFLGoudyStMTT-Italic,OFL Sorts Mill Goudy TT Italic,Copyright (c) 2009 Barry Schwartz (http://crudfactory.com chemoelectric@chemoelectric.org)
+Oldenburg,normal,400,Oldenburg-Regular.ttf,Oldenburg-Regular,Oldenburg,Copyright (c) 2010 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name Oldenburgh.
+Old Standard TT,normal,400,OldStandard-Regular.ttf,OldStandardTT-Regular,Old Standard TT Regular,Copyright 2011 The Old Standard Project Authors (amkryukov@gmail.com)
+Old Standard TT,italic,400,OldStandard-Italic.ttf,OldStandardTT-Italic,Old Standard TT Italic,Copyright 2011 The Old Standard Project Authors (amkryukov@gmail.com)
+Old Standard TT,normal,700,OldStandard-Bold.ttf,OldStandardTT-Bold,Old Standard TT Bold,Copyright 2011 The Old Standard Project Authors (amkryukov@gmail.com)
+Oleo Script,normal,400,OleoScript-Regular.ttf,OleoScript-Regular,Oleo Script,"Copyright (c) 2012, Soytutype (contact@soytutype.com.ar|soytutype@gmail.com), with reserved fontname 'Oleo'"
+Oleo Script,normal,700,OleoScript-Bold.ttf,OleoScript-Bold,Oleo Script Bold,"Copyright (c) 2012, Soytutype (contact@soytutype.com.ar|soytutype@gmail.com), with reserved fontname 'Oleo'"
+Oleo Script Swash Caps,normal,400,OleoScriptSwashCaps-Regular.ttf,OleoScriptSwashCaps-Regular,Oleo Script Swash Caps,"Copyright (c) 2012, Soytutype (contact@soytutype.com.ar|soytutype@gmail.com), with reserved fontname 'Oleo'"
+Oleo Script Swash Caps,normal,700,OleoScriptSwashCaps-Bold.ttf,OleoScriptSwashCaps-Bold,Oleo Script Swash Caps Bold,"Copyright (c) 2012, Soytutype (contact@soytutype.com.ar|soytutype@gmail.com), with reserved fontname 'Oleo'"
+Oranienbaum,normal,400,Oranienbaum-Regular.ttf,Oranienbaum-Regular,Oranienbaum,"Copyright (c) 2012, Oleg Pospelov (oleg@pospelov.com), Jovanny Lemonad (lemonad@jovanny.ru), with Reserved Font Name 'Oranienbaum'"
+Orbitron,normal,400,Orbitron[wght].ttf,Orbitron-Regular,Orbitron Regular,Copyright 2018 The Orbitron Project Authors (https://github.com/theleagueof/orbitron)
+Oregano,normal,400,Oregano-Regular.ttf,Oregano-Regular,Oregano,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Oregano\"
+Oregano,italic,400,Oregano-Italic.ttf,Oregano-Italic,Oregano Italic,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Oregano Italic\"
+Orienta,normal,400,Orienta-Regular.ttf,Orienta-Regular,Orienta,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Orienta'"
+Original Surfer,normal,400,OriginalSurfer-Regular.ttf,OriginalSurfer-Regular,Original Surfer,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Original Surfer\"
+Oswald,normal,400,Oswald[wght].ttf,Oswald-Regular,Oswald Regular,Copyright 2016 The Oswald Project Authors (https://github.com/googlefonts/OswaldFont)
+Overlock,normal,400,Overlock-Regular.ttf,Overlock-Regular,Overlock Regular,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar), with Reserved Font Name \Overlock\."
+Overlock,italic,400,Overlock-Italic.ttf,Overlock-Italic,Overlock Italic,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar), with Reserved Font Name \Overlock\."
+Overlock,normal,700,Overlock-Bold.ttf,Overlock-Bold,Overlock Bold,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar), with Reserved Font Name \Overlock\."
+Overlock,italic,700,Overlock-BoldItalic.ttf,Overlock-BoldItalic,Overlock Bold Italic,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar), with Reserved Font Name \Overlock\."
+Overlock,normal,900,Overlock-Black.ttf,Overlock-Black,Overlock Black,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar), with Reserved Font Name \Overlock\."
+Overlock,italic,900,Overlock-BlackItalic.ttf,Overlock-BlackItalic,Overlock Black Italic,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar), with Reserved Font Name \Overlock\."
+Overlock SC,normal,400,OverlockSC-Regular.ttf,OverlockSC-Regular,Overlock SC,"Copyright (c) 2011, Dario Manuel Muhafara (http://www.tipo.net.ar dario@tipo.net.ar), with Reserved Font Name \Overlock\."
+Overpass,normal,100,Overpass-Thin.ttf,Overpass-Thin,Overpass Thin,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,100,Overpass-ThinItalic.ttf,Overpass-ThinItalic,Overpass Thin Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,200,Overpass-ExtraLight.ttf,Overpass-ExtraLight,Overpass ExtraLight,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,200,Overpass-ExtraLightItalic.ttf,Overpass-ExtraLightItalic,Overpass ExtraLight Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,300,Overpass-Light.ttf,Overpass-Light,Overpass Light,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,300,Overpass-LightItalic.ttf,Overpass-LightItalic,Overpass Light Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,400,Overpass-Regular.ttf,Overpass-Regular,Overpass Regular,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,400,Overpass-Italic.ttf,Overpass-Italic,Overpass Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,600,Overpass-SemiBold.ttf,Overpass-SemiBold,Overpass SemiBold,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,600,Overpass-SemiBoldItalic.ttf,Overpass-SemiBoldItalic,Overpass SemiBold Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,700,Overpass-Bold.ttf,Overpass-Bold,Overpass Bold,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,700,Overpass-BoldItalic.ttf,Overpass-BoldItalic,Overpass Bold Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,800,Overpass-ExtraBold.ttf,Overpass-ExtraBold,Overpass ExtraBold,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,800,Overpass-ExtraBoldItalic.ttf,Overpass-ExtraBoldItalic,Overpass ExtraBold Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass,normal,900,Overpass-Black.ttf,Overpass-Black,Overpass Black,"Copyright  2016 by Red Hat, Inc. All rights reserved."
+Overpass,italic,900,Overpass-BlackItalic.ttf,Overpass-BlackItalic,Overpass Black Italic,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass Mono,normal,300,OverpassMono-Light.ttf,OverpassMono-Light,Overpass Mono Light,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass Mono,normal,400,OverpassMono-Regular.ttf,OverpassMono-Regular,Overpass Mono Regular,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass Mono,normal,600,OverpassMono-SemiBold.ttf,OverpassMono-SemiBold,Overpass Mono SemiBold,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Overpass Mono,normal,700,OverpassMono-Bold.ttf,OverpassMono-Bold,Overpass Mono Bold,"Copyright (c) 2016 by Red Hat, Inc. All rights reserved."
+Over the Rainbow,normal,400,OvertheRainbow.ttf,OvertheRainbow,Over the Rainbow,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Ovo,normal,400,Ovo-Regular.ttf,Ovo,Ovo,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Ovo\."
+Oxanium,normal,200,Oxanium-ExtraLight.ttf,Oxanium-ExtraLight,Oxanium ExtraLight,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxanium,normal,300,Oxanium-Light.ttf,Oxanium-Light,Oxanium Light,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxanium,normal,400,Oxanium-Regular.ttf,Oxanium-Regular,Oxanium Regular,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxanium,normal,500,Oxanium-Medium.ttf,Oxanium-Medium,Oxanium Medium,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxanium,normal,600,Oxanium-SemiBold.ttf,Oxanium-SemiBold,Oxanium SemiBold,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxanium,normal,700,Oxanium-Bold.ttf,Oxanium-Bold,Oxanium Bold,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxanium,normal,800,Oxanium-ExtraBold.ttf,Oxanium-ExtraBold,Oxanium ExtraBold,Copyright 2019 The Oxanium Project Authors (https://github.com/sevmeyer/oxanium)
+Oxygen,normal,300,Oxygen-Light.ttf,Oxygen-Light,Oxygen Light,"Copyright (c) 2012, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \'Oxygen\'"
+Oxygen,normal,400,Oxygen-Regular.ttf,Oxygen-Regular,Oxygen Regular,"Copyright (c) 2012, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \'Oxygen\'"
+Oxygen,normal,700,Oxygen-Bold.ttf,Oxygen-Bold,Oxygen Bold,"Copyright (c) 2012, Vernon Adams (vern@newtypography.co.uk), with Reserved Font Names \'Oxygen\'"
+Oxygen Mono,normal,400,OxygenMono-Regular.ttf,OxygenMono-Regular,Oxygen Mono,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Names 'Oxygen'"
+Pacifico,normal,400,Pacifico-Regular.ttf,Pacifico-Regular,Pacifico Regular,Copyright 2018 The Pacifico Project Authors (https://github.com/googlefonts/Pacifico)
+Padauk,normal,400,Padauk-Regular.ttf,Padauk-Regular,Padauk Regular,"Copyright SIL International, all rights reserved"
+Padauk,normal,700,Padauk-Bold.ttf,Padauk-Bold,Padauk Bold,"Copyright SIL International, all rights reserved"
+Palanquin,normal,100,Palanquin-Thin.ttf,Palanquin-Thin,Palanquin Thin,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin,normal,200,Palanquin-ExtraLight.ttf,Palanquin-ExtraLight,Palanquin ExtraLight,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin,normal,300,Palanquin-Light.ttf,Palanquin-Light,Palanquin Light,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin,normal,400,Palanquin-Regular.ttf,Palanquin-Regular,Palanquin Regular,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin,normal,500,Palanquin-Medium.ttf,Palanquin-Medium,Palanquin Medium,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin,normal,600,Palanquin-SemiBold.ttf,Palanquin-SemiBold,Palanquin SemiBold,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin,normal,700,Palanquin-Bold.ttf,Palanquin-Bold,Palanquin Bold,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin Dark,normal,400,PalanquinDark-Regular.ttf,PalanquinDark-Regular,Palanquin Dark Regular,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin Dark,normal,500,PalanquinDark-Medium.ttf,PalanquinDark-Medium,Palanquin Dark Medium,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin Dark,normal,600,PalanquinDark-SemiBold.ttf,PalanquinDark-SemiBold,Palanquin Dark SemiBold,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Palanquin Dark,normal,700,PalanquinDark-Bold.ttf,PalanquinDark-Bold,Palanquin Dark Bold,Copyright 2014 Pria Ravichandran (pria.ravichandran@gmail.com)
+Pangolin,normal,400,Pangolin-Regular.ttf,Pangolin-Regular,Pangolin Regular,Copyright 2016 The Pangolin Project Authors (https://github.com/googlefonts/pangolin)
+Paprika,normal,400,Paprika-Regular.ttf,Paprika-Regular,Paprika,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Paprika'"
+Parisienne,normal,400,Parisienne-Regular.ttf,Parisienne-Regular,Parisienne,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Parisienne\"
+Passero One,normal,400,PasseroOne-Regular.ttf,PasseroOne-Regular,Passero One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Names \Passero\"
+Passion One,normal,400,PassionOne-Regular.ttf,PassionOne-Regular,Passion One Regular,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Passion\"
+Passion One,normal,700,PassionOne-Bold.ttf,PassionOne-Bold,Passion One Bold,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Passion\"
+Passion One,normal,900,PassionOne-Black.ttf,PassionOne-Black,Passion One Black,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Passion\"
+Pathway Gothic One,normal,400,PathwayGothicOne-Regular.ttf,PathwayGothicOne-Regular,Pathway Gothic One Regular,"Copyright (c) 2013, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \'Pathway\'"
+Patrick Hand,normal,400,PatrickHand-Regular.ttf,PatrickHand-Regular,Patrick Hand,Copyright (c) 2010-2012 Patrick Wagesreiter (mail@patrickwagesreiter.at)
+Patrick Hand SC,normal,400,PatrickHandSC-Regular.ttf,PatrickHandSC-Regular,Patrick Hand SC Regular,Copyright 2012 The Patrick Hand Authors (mail@patrickwagesreiter.at)
+Pattaya,normal,400,Pattaya-Regular.ttf,Pattaya-Regular,Pattaya Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com), Copyright (c) 2010, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2010, 2011, Alexei Vanyashin (www.cyreal.org|a@cyreal.org), with Reserved Font Name Lobster."
+Patua One,normal,400,PatuaOne-Regular.ttf,PatuaOne-Regular,Patua One,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com), with Reserved Font Names \Patua\ and \Patua One\"
+Pavanam,normal,400,Pavanam-Regular.ttf,Pavanam-Regular,Pavanam Regular,"Copyright (c) 2015, Tharique Azeez (http://thariqueazeez.com | zeezat@gmail.com). Copyright (c) 2012, vernon adams (vern@newtypography.co.uk)"
+Paytone One,normal,400,PaytoneOne-Regular.ttf,PaytoneOne-Regular,Paytone One Regular,Copyright 2011 The Paytone Project Authors (https://github.com/googlefonts/paytoneFont)
+Pecita,normal,400,Pecita.ttf,Pecita,Pecita,"Copyright (c) 2009-2011, Philippe Cochy (http://pecita.com acquadoria@gmail.com), with Reserved Font Name Pecita."
+Peddana,normal,400,Peddana-Regular.ttf,Peddana,Peddana Regular,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 1997-2014, SIL International (http://scripts.sil.org/) with Reserved Font Names \Charis\ and \SIL\."
+Peralta,normal,400,Peralta-Regular.ttf,Peralta-Regular,Peralta,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Peralta\"
+Petit Formal Script,normal,400,PetitFormalScript-Regular.ttf,PetitFormalScript-Regular,Petit Formal Script,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), Copyright (c) 2011, Rodrigo Fuenzalida (www.rfuenzalida.com|hello@rfuenzalida.com),   with Reserved Font Name Petit Formal Script."
+Petrona,normal,400,Petrona-Regular.ttf,Petrona-Regular,Petrona Regular,"Copyright (c) 2011, Huerta Tipografica (www.huertatipografica.com.ar info@huertatipografica.com.ar), with Reserved Font Names \Petrona\, \Petrona Pro\ and \Petrona HT\. All rights reserved."
+Phetsarath,normal,400,Phetsarath-Regular.ttf,Phetsarath-Regular,Phetsarath Regular,"Copyright (c) 2010-2012, Ministry of Posts and Telecommunications, Laos (www.phetsarath.gov.la)"
+Phetsarath,normal,700,Phetsarath-Bold.ttf,Phetsarath-Bold,Phetsarath Bold,"Copyright (c) 2010-2012, Ministry of Posts and Telecommunications, Laos (www.phetsarath.gov.la)"
+Philosopher,normal,400,Philosopher-Regular.ttf,Philosopher-Regular,Philosopher Regular,Copyright 2011 The Philosopher Project Authors (lemonad@jovanny.ru)
+Philosopher,italic,400,Philosopher-Italic.ttf,Philosopher-Italic,Philosopher Italic,Copyright 2011 The Philosopher Project Authors (lemonad@jovanny.ru)
+Philosopher,normal,700,Philosopher-Bold.ttf,Philosopher-Bold,Philosopher Bold,Copyright 2011 The Philosopher Project Authors (lemonad@jovanny.ru)
+Philosopher,italic,700,Philosopher-BoldItalic.ttf,Philosopher-BoldItalic,Philosopher Bold Italic,Copyright 2011 The Philosopher Project Authors (lemonad@jovanny.ru)
+Piedra,normal,400,Piedra-Regular.ttf,Piedra-Regular,Piedra Regular,"Copyright (c) 2011 Angel Koziupa (sudtipos@sudtipos.com), Copyright (c) 2011 Alejandro Paul (sudtipos@sudtipos.com), with Reserved Font Name \Piedra\"
+Pinyon Script,normal,400,PinyonScript-Regular.ttf,PinyonScript,Pinyon Script,"Copyright (c) 2010 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name Pinyon Script. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: http://scripts.sil.org/OFL"
+Pirata One,normal,400,PirataOne-Regular.ttf,PirataOne-Regular,Pirata One,"Copyright (c) 2012, Rodrigo Fuenzalida (hello@rfuenzalida.com), Nicolas Massi (www.taip.com.ar / abc.taip.com.ar / nmassi@gmail.com), with Reserved Font Name 'Pirata'"
+Plaster,normal,400,Plaster-Regular.ttf,Plaster-Regular,Plaster,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Plaster\"
+Play,normal,400,Play-Regular.ttf,Play-Regular,Play Regular,"Copyright (c) 2011, Jonas Hecksher, Playtypes, e-types AS (lasse@e-types.com), with Reserved Font Name \'Play\', \'Playtype\', \'Playtype Sans\'."
+Play,normal,700,Play-Bold.ttf,Play-Bold,Play Bold,"Copyright (c) 2011, Jonas Hecksher, Playtypes, e-types AS (lasse@e-types.com), with Reserved Font Name \'Play\', \'Playtype\', \'Playtype Sans\'."
+Playball,normal,400,Playball-Regular.ttf,Playball-Regular,Playball,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Playball\"
+Playfair Display,normal,400,PlayfairDisplay[wght].ttf,PlayfairDisplay-Regular,Playfair Display Regular,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display,italic,400,PlayfairDisplay-Italic[wght].ttf,PlayfairDisplay-Italic,Playfair Display Italic,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display SC,normal,400,PlayfairDisplaySC-Regular.ttf,PlayfairDisplaySC-Regular,Playfair Display SC Regular,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display SC,italic,400,PlayfairDisplaySC-Italic.ttf,PlayfairDisplaySC-Italic,Playfair Display SC Italic,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display SC,normal,700,PlayfairDisplaySC-Bold.ttf,PlayfairDisplaySC-Bold,Playfair Display SC Bold,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display SC,italic,700,PlayfairDisplaySC-BoldItalic.ttf,PlayfairDisplaySC-BoldItalic,Playfair Display SC Bold Italic,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display SC,normal,900,PlayfairDisplaySC-Black.ttf,PlayfairDisplaySC-Black,Playfair Display SC Black,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Playfair Display SC,italic,900,PlayfairDisplaySC-BlackItalic.ttf,PlayfairDisplaySC-BlackItalic,Playfair Display SC Black Italic,"Copyright 2017 The Playfair Display Project Authors (https://github.com/clauseggers/Playfair-Display), with Reserved Font Name \Playfair Display\."
+Podkova,normal,400,Podkova[wght].ttf,Podkova-Regular,Podkova Regular,Copyright 2011 The Podkova Project Authors (https://github.com/cyrealtype/Podkova)
+Poetsen One,normal,400,PoetsenOne-Regular.ttf,PoetsenOne-Regular,Poetsen One,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com) and Rodrigo Fuenzalida (www.rfuenzalida.com), with Reserved Font Name Poetsen."
+Poiret One,normal,400,PoiretOne-Regular.ttf,PoiretOne-Regular,Poiret One Regular,Copyright 2011 The Poiret One Project Authors (https://github.com/alexeiva/poiretone)
+Poller One,normal,400,PollerOne.ttf,PollerOne-Regular,Poller One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Names \Poller\ and \Poller One\."
+Poly,normal,400,Poly-Regular.ttf,Poly-Regular,Poly-Regular,"Copyright (c) 2010 by Jos Nicols Silva Schwarzenberg.<info@nsilva.com>, with Reserved Font Names \Poly\."
+Poly,italic,400,Poly-Italic.ttf,Poly-Italic,Poly-Italic,"Copyright (c) 2010 by Jos Nicols Silva Schwarzenberg.<info@nsilva.com>, with Reserved Font Names \Poly\."
+Pompiere,normal,400,Pompiere-Regular.ttf,Pompiere-Regular,Pompiere,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Pompiere\."
+Ponnala,normal,400,Ponnala-Regular.ttf,Ponnala,Ponnala,Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org)
+Pontano Sans,normal,400,PontanoSans-Regular.ttf,PontanoSans-Regular,Pontano Sans,"Copyright (c) 2012, vernon adams (vern@newtypography.co.uk), with Reserved Font Names \Potano\"
+Poor Story,normal,400,PoorStory-Regular.ttf,PoorStory-Regular,Poor Story Regular,Copyright (c) YoonDesign Inc. All Rights Reserved.
+Poppins,normal,100,Poppins-Thin.ttf,Poppins-Thin,Poppins Thin,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,100,Poppins-ThinItalic.ttf,Poppins-ThinItalic,Poppins Thin Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,200,Poppins-ExtraLight.ttf,Poppins-ExtraLight,Poppins ExtraLight,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,200,Poppins-ExtraLightItalic.ttf,Poppins-ExtraLightItalic,Poppins ExtraLight Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,300,Poppins-Light.ttf,Poppins-Light,Poppins Light,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,300,Poppins-LightItalic.ttf,Poppins-LightItalic,Poppins Light Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,400,Poppins-Regular.ttf,Poppins-Regular,Poppins Regular,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,400,Poppins-Italic.ttf,Poppins-Italic,Poppins Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,500,Poppins-Medium.ttf,Poppins-Medium,Poppins Medium,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,500,Poppins-MediumItalic.ttf,Poppins-MediumItalic,Poppins Medium Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,600,Poppins-SemiBold.ttf,Poppins-SemiBold,Poppins SemiBold,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,600,Poppins-SemiBoldItalic.ttf,Poppins-SemiBoldItalic,Poppins SemiBold Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,700,Poppins-Bold.ttf,Poppins-Bold,Poppins Bold,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,700,Poppins-BoldItalic.ttf,Poppins-BoldItalic,Poppins Bold Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,800,Poppins-ExtraBold.ttf,Poppins-ExtraBold,Poppins ExtraBold,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,800,Poppins-ExtraBoldItalic.ttf,Poppins-ExtraBoldItalic,Poppins ExtraBold Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,normal,900,Poppins-Black.ttf,Poppins-Black,Poppins Black,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Poppins,italic,900,Poppins-BlackItalic.ttf,Poppins-BlackItalic,Poppins Black Italic,Copyright 2014-2019 Indian Type Foundry (info@indiantypefoundry.com)
+Porter Sans Block,normal,400,PorterSansBlock-Regular.ttf,PorterSansBlock,Porter Sans Block,"Copyright (c) 2013, Tyler Finck (hello@sursly.com)"
+Port Lligat Sans,normal,400,PortLligatSans-Regular.ttf,PortLligatSans-Regular,Port Lligat Sans,"Copyright (c) 2011, Tipo (http://www.tipo.net.ar dario@tipo.net.ar), with Reserved Font Name \Port Lligat Sans\"
+Port Lligat Slab,normal,400,PortLligatSlab-Regular.ttf,PortLligatSlab-Regular,Port Lligat Slab,"Copyright (c) 2011, Tipo (http://www.tipo.net.ar dario@tipo.net.ar), with Reserved Font Name \Port Lligat Slab\"
+Post No Bills Colombo,normal,300,PostNoBillsColombo-Light.ttf,PostNoBillsColombo-Light,Post No Bills Colombo Light,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Colombo,normal,400,PostNoBillsColombo-Regular.ttf,PostNoBillsColombo-Regular,Post No Bills Colombo Regular,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Colombo,normal,500,PostNoBillsColombo-Medium.ttf,PostNoBillsColombo-Medium,Post No Bills Colombo Medium,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Colombo,normal,600,PostNoBillsColombo-SemiBold.ttf,PostNoBillsColombo-SemiBold,Post No Bills Colombo SemiBold,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Colombo,normal,700,PostNoBillsColombo-Bold.ttf,PostNoBillsColombo-Bold,Post No Bills Colombo Bold,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Colombo,normal,800,PostNoBillsColombo-ExtraBold.ttf,PostNoBillsColombo-ExtraBold,Post No Bills Colombo ExtraBold,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Jaffna,normal,300,PostNoBillsJaffna-Light.ttf,PostNoBillsJaffna-Light,Post No Bills Jaffna Light,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Jaffna,normal,400,PostNoBillsJaffna-Regular.ttf,PostNoBillsJaffna-Regular,Post No Bills Jaffna Regular,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Jaffna,normal,500,PostNoBillsJaffna-Medium.ttf,PostNoBillsJaffna-Medium,Post No Bills Jaffna Medium,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Jaffna,normal,600,PostNoBillsJaffna-SemiBold.ttf,PostNoBillsJaffna-SemiBold,Post No Bills Jaffna SemiBold,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Jaffna,normal,700,PostNoBillsJaffna-Bold.ttf,PostNoBillsJaffna-Bold,Post No Bills Jaffna Bold,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Post No Bills Jaffna,normal,800,PostNoBillsJaffna-ExtraBold.ttf,PostNoBillsJaffna-ExtraBold,Post No Bills Jaffna ExtraBold,Copyright (c) 2013-2015 Gall Productions Pvt. Ltd (http://www.sticknobillsonline.com) Copyright (c) 2015 mooniak (http://mooniak.com)
+Pragati Narrow,normal,400,PragatiNarrow-Regular.ttf,PragatiNarrow-Regular,Pragati Narrow,"Copyright (c) 2012-2015, Omnibus-Type (www.omnibus-type.com omnibus.type@gmail.com)"
+Pragati Narrow,normal,700,PragatiNarrow-Bold.ttf,PragatiNarrow-Bold,Pragati Narrow Bold,"Copyright (c) 2012-2015, Omnibus-Type (www.omnibus-type.com omnibus.type@gmail.com)"
+Prata,normal,400,Prata-Regular.ttf,Prata-Regular,Prata Regular,Copyright 2011 The Prata Project Authors (contact@cyreal.org)
+Preahvihear,normal,400,Preahvihear.ttf,PreahVihear,Preah Vihear,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name NiDA Preahvihear. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Press Start 2P,normal,400,PressStart2P-Regular.ttf,PressStart2P-Regular,Press Start 2P Regular,"Copyright 2012 The Press Start 2P Project Authors (cody@zone38.net), with Reserved Font Name \Press Start 2P\"
+Pridi,normal,200,Pridi-ExtraLight.ttf,Pridi-ExtraLight,Pridi ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Pridi,normal,300,Pridi-Light.ttf,Pridi-Light,Pridi Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Pridi,normal,400,Pridi-Regular.ttf,Pridi-Regular,Pridi Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Pridi,normal,500,Pridi-Medium.ttf,Pridi-Medium,Pridi Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Pridi,normal,600,Pridi-SemiBold.ttf,Pridi-SemiBold,Pridi SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Pridi,normal,700,Pridi-Bold.ttf,Pridi-Bold,Pridi Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Princess Sofia,normal,400,PrincessSofia-Regular.ttf,PrincessSofia,Princess Sofia,"Copyright (c) 2012 by Font Diner, Inc DBA Tart Workshop (diner@fontdiner.com) with Reseved Font Name \Princess Sofia\"
+Prociono,normal,400,Prociono-Regular.ttf,Prociono-Regular,Prociono,"Copyright (c) 2011, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Prompt,normal,100,Prompt-Thin.ttf,Prompt-Thin,Prompt Thin,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,100,Prompt-ThinItalic.ttf,Prompt-ThinItalic,Prompt Thin Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,200,Prompt-ExtraLight.ttf,Prompt-ExtraLight,Prompt ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,200,Prompt-ExtraLightItalic.ttf,Prompt-ExtraLightItalic,Prompt ExtraLight Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,300,Prompt-Light.ttf,Prompt-Light,Prompt Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,300,Prompt-LightItalic.ttf,Prompt-LightItalic,Prompt Light Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,400,Prompt-Regular.ttf,Prompt-Regular,Prompt Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,400,Prompt-Italic.ttf,Prompt-Italic,Prompt Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,500,Prompt-Medium.ttf,Prompt-Medium,Prompt Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,500,Prompt-MediumItalic.ttf,Prompt-MediumItalic,Prompt Medium Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,600,Prompt-SemiBold.ttf,Prompt-SemiBold,Prompt SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,600,Prompt-SemiBoldItalic.ttf,Prompt-SemiBoldItalic,Prompt SemiBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,700,Prompt-Bold.ttf,Prompt-Bold,Prompt Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,700,Prompt-BoldItalic.ttf,Prompt-BoldItalic,Prompt Bold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,800,Prompt-ExtraBold.ttf,Prompt-ExtraBold,Prompt ExtraBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,800,Prompt-ExtraBoldItalic.ttf,Prompt-ExtraBoldItalic,Prompt ExtraBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,normal,900,Prompt-Black.ttf,Prompt-Black,Prompt Black,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prompt,italic,900,Prompt-BlackItalic.ttf,Prompt-BlackItalic,Prompt Black Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Prosto One,normal,400,ProstoOne-Regular.ttf,ProstoOne-Regular,Prosto One,"Copyright (c) 2012, Jovanny Lemonad (http://www.jovanny.ru), Copyright (c) 2012, Pavel Emelyanov (zakachka2006@mail.ru), with Reserved Font Name \Prosto\ and \Prosto One\."
+Proza Libre,normal,400,ProzaLibre-Regular.ttf,ProzaLibre-Regular,Proza Libre Regular,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,italic,400,ProzaLibre-Italic.ttf,ProzaLibre-Italic,Proza Libre Italic,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,normal,500,ProzaLibre-Medium.ttf,ProzaLibre-Medium,Proza Libre Medium,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,italic,500,ProzaLibre-MediumItalic.ttf,ProzaLibre-MediumItalic,Proza Libre Medium Italic,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,normal,600,ProzaLibre-SemiBold.ttf,ProzaLibre-SemiBold,Proza Libre SemiBold,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,italic,600,ProzaLibre-SemiBoldItalic.ttf,ProzaLibre-SemiBoldItalic,Proza Libre SemiBold Italic,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,normal,700,ProzaLibre-Bold.ttf,ProzaLibre-Bold,Proza Libre Bold,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,italic,700,ProzaLibre-BoldItalic.ttf,ProzaLibre-BoldItalic,Proza Libre Bold Italic,Copyright (c) 2015 by Jasper de Waard. All rights reserved.
+Proza Libre,normal,800,ProzaLibre-ExtraBold.ttf,ProzaLibre-ExtraBold,Proza Libre ExtraBold,Copyright (c) 2013 by Jasper de Waard. All rights reserved.
+Proza Libre,italic,800,ProzaLibre-ExtraBoldItalic.ttf,ProzaLibre-ExtraBoldItalic,Proza Libre ExtraBold Italic,Copyright (c) 2013 by Jasper de Waard. All rights reserved.
+PT Mono,normal,400,PTM55FT.ttf,PTMono-Regular,PT Mono,"Copyright © 2010 ParaType Inc., ParaType Ltd (yakupov@paratype.com). All rights reserved."
+PT Sans,normal,400,PT_Sans-Web-Regular.ttf,PTSans-Regular,PT Sans,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans,italic,400,PT_Sans-Web-Italic.ttf,PTSans-Italic,PT Sans Italic,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans,normal,700,PT_Sans-Web-Bold.ttf,PTSans-Bold,PT Sans Bold,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans,italic,700,PT_Sans-Web-BoldItalic.ttf,PTSans-BoldItalic,PT Sans Bold Italic,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans Caption,normal,400,PT_Sans-Caption-Web-Regular.ttf,PTSans-Caption,PT Sans Caption,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans Caption,normal,700,PT_Sans-Caption-Web-Bold.ttf,PTSans-CaptionBold,PT Sans Caption Bold,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans Narrow,normal,400,PT_Sans-Narrow-Web-Regular.ttf,PTSans-Narrow,PT Sans Narrow,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Sans Narrow,normal,700,PT_Sans-Narrow-Web-Bold.ttf,PTSans-NarrowBold,PT Sans Narrow Bold,Copyright © 2009 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Serif,normal,400,PT_Serif-Web-Regular.ttf,PTSerif-Regular,PT Serif,Copyright © 2010 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Serif,italic,400,PT_Serif-Web-Italic.ttf,PTSerif-Italic,PT Serif Italic,Copyright © 2010 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Serif,normal,700,PT_Serif-Web-Bold.ttf,PTSerif-Bold,PT Serif Bold,Copyright © 2010 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Serif,italic,700,PT_Serif-Web-BoldItalic.ttf,PTSerif-BoldItalic,PT Serif Bold Italic,Copyright © 2010 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Serif Caption,normal,400,PT_Serif-Caption-Web-Regular.ttf,PTSerif-Caption,PT Serif Caption,Copyright © 2010 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+PT Serif Caption,italic,400,PT_Serif-Caption-Web-Italic.ttf,PTSerif-CaptionItalic,PT Serif Caption Italic,Copyright © 2010 ParaType Ltd (yakupov@paratype.com). All rights reserved.
+Public Sans,normal,400,PublicSans[wght].ttf,PublicSans-Thin,Public Sans Thin,"Copyright (c) 2015, Pablo Impallari, Rodrigo Fuenzalida (Modified by Dan O. Williams and USWDS) (https://github.com/uswds/public-sans)"
+Public Sans,italic,400,PublicSans-Italic[wght].ttf,PublicSans-ThinItalic,Public Sans Thin Italic,"Copyright (c) 2015, Pablo Impallari, Rodrigo Fuenzalida (Modified by Dan O. Williams and USWDS) (https://github.com/uswds/public-sans)"
+Puritan,normal,400,Puritan-Regular.ttf,Puritan-Regular,Puritan Regular,Copyright 1999-2010 Ben Weiner (ben@readingtype.org.uk). Licensed under the Open Font License v1.1 (http://scripts.sil.org/OFL)
+Puritan,italic,400,Puritan-Italic.ttf,Puritan-Italic,Puritan Italic,Copyright 1999-2010 Ben Weiner (ben@readingtype.org.uk). Licensed under the Open Font License v1.1 (http://scripts.sil.org/OFL)
+Puritan,normal,700,Puritan-Bold.ttf,Puritan-Bold,Puritan Bold,Copyright 1999-2010 Ben Weiner (ben@readingtype.org.uk). Licensed under the Open Font License v1.1 (http://scripts.sil.org/OFL)
+Puritan,italic,700,Puritan-BoldItalic.ttf,Puritan-BoldItalic,Puritan Bold Italic,Copyright 1999-2010 Ben Weiner (ben@readingtype.org.uk). Licensed under the Open Font License v1.1 (http://scripts.sil.org/OFL)
+Purple Purse,normal,400,PurplePurse-Regular.ttf,PurplePurse-Regular,Purple Purse,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Purple Purse\"
+Pushster,normal,400,Pushster-Regular.ttf,Pushster-Regular,Pushster Regular,"Copyright 2010 abcdefgh The Lobster Project Authors (https://github.com/impallari/The-Lobster-Font), with Reserved Font Name \Lobster\.4"
+Quando,normal,400,Quando-Regular.ttf,Quando-Regular,Quando-Regular,"Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Quando\"
+Quantico,normal,400,Quantico-Regular.ttf,Quantico-Regular,Quantico,"Copyright (c) 2011 Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name \Quantico\"
+Quantico,italic,400,Quantico-Italic.ttf,Quantico-Italic,Quantico-Italic,"Copyright (c) 2011 Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name \Quantico\"
+Quantico,normal,700,Quantico-Bold.ttf,Quantico-Bold,Quantico-Bold,"Copyright (c) 2011 Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name \Quantico\"
+Quantico,italic,700,Quantico-BoldItalic.ttf,Quantico-BoldItalic,Quantico-BoldItalic,"Copyright (c) 2011 Matthew Desmond (http://www.madtype.com | mattdesmond@gmail.com), with Reserved Font Name \Quantico\"
+Quattrocento,normal,400,Quattrocento-Regular.ttf,Quattrocento,Quattrocento,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Quattrocento."
+Quattrocento,normal,700,Quattrocento-Bold.ttf,Quattrocento-Bold,Quattrocento Bold,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Quattrocento."
+Quattrocento Sans,normal,400,QuattrocentoSans-Regular.ttf,QuattrocentoSans,Quattrocento Sans,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Quattrocento Sans."
+Quattrocento Sans,italic,400,QuattrocentoSans-Italic.ttf,QuattrocentoSans-Italic,Quattrocento Sans Italic,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Quattrocento Sans."
+Quattrocento Sans,normal,700,QuattrocentoSans-Bold.ttf,QuattrocentoSans-Bold,Quattrocento Sans Bold,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Quattrocento Sans."
+Quattrocento Sans,italic,700,QuattrocentoSans-BoldItalic.ttf,QuattrocentoSans-BoldItalic,Quattrocento Sans Bold Italic,"Copyright (c) 2011, Pablo Impallari (www.impallari.com|impallari@gmail.com), Copyright (c) 2011, Igino Marini. (www.ikern.com|mail@iginomarini.com), Copyright (c) 2011, Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Quattrocento Sans."
+Questrial,normal,400,Questrial-Regular.ttf,Questrial-Regular,Questrial,"Copyright (c) 2011, Admix Designs (http://www.admixdesigns.com joe@admixdesigns.com) with Reserved Font Name Questrial."
+Quicksand,normal,300,Quicksand[wght].ttf,Quicksand-Light,Quicksand Light,"Copyright 2019 The Quicksand Project Authors (https://github.com/andrew-paglinawan/QuicksandFamily.git), with Reserved Font Name \Quicksand\"
+Quintessential,normal,400,Quintessential-Regular.ttf,Quintessential-Regular,Quintessential,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name 'Quintessential'"
+Qwigley,normal,400,Qwigley-Regular.ttf,Qwigley-Regular,Qwigley,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Qwigley\"
+Racing Sans One,normal,400,RacingSansOne-Regular.ttf,RacingSansOne-Regular,Racing Sans One,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com) and Rodrigo Fuenzalida (www.rfuenzalida.com), with Reserved Font Name Racing Sans."
+Radley,normal,400,Radley-Regular.ttf,Radley-Regular,Radley Regular,Copyright 2011 The Radley Project Authors (https://github.com/googlefonts/RadleyFont)
+Radley,italic,400,Radley-Italic.ttf,Radley-Italic,Radley Italic,Copyright 2011 The Radley Project Authors (https://github.com/googlefonts/RadleyFont)
+Rajdhani,normal,300,Rajdhani-Light.ttf,Rajdhani-Light,Rajdhani Light,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Rajdhani,normal,400,Rajdhani-Regular.ttf,Rajdhani-Regular,Rajdhani Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Rajdhani,normal,500,Rajdhani-Medium.ttf,Rajdhani-Medium,Rajdhani Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Rajdhani,normal,600,Rajdhani-SemiBold.ttf,Rajdhani-SemiBold,Rajdhani SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Rajdhani,normal,700,Rajdhani-Bold.ttf,Rajdhani-Bold,Rajdhani Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Rakkas,normal,400,Rakkas-Regular.ttf,Rakkas-Regular,Rakkas Regular,Copyright 2017 The Rakkas Project Authors (https://github.com/zeynepakay/Rakkas)
+Raleway,normal,100,Raleway-Thin.ttf,Raleway-Thin,Raleway Thin,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,100,Raleway-ThinItalic.ttf,Raleway-ThinItalic,Raleway Thin Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,200,Raleway-ExtraLight.ttf,Raleway-ExtraLight,Raleway ExtraLight,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,200,Raleway-ExtraLightItalic.ttf,Raleway-ExtraLightItalic,Raleway ExtraLight Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,300,Raleway-Light.ttf,Raleway-Light,Raleway Light,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,300,Raleway-LightItalic.ttf,Raleway-LightItalic,Raleway Light Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,400,Raleway-Regular.ttf,Raleway-Regular,Raleway,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,400,Raleway-Italic.ttf,Raleway-Italic,Raleway Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,500,Raleway-Medium.ttf,Raleway-Medium,Raleway Medium,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,500,Raleway-MediumItalic.ttf,Raleway-MediumItalic,Raleway Medium Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,600,Raleway-SemiBold.ttf,Raleway-SemiBold,Raleway SemiBold,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,600,Raleway-SemiBoldItalic.ttf,Raleway-SemiBoldItalic,Raleway SemiBold Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,700,Raleway-Bold.ttf,Raleway-Bold,Raleway Bold,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,700,Raleway-BoldItalic.ttf,Raleway-BoldItalic,Raleway Bold Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,800,Raleway-ExtraBold.ttf,Raleway-ExtraBold,Raleway ExtraBold,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,800,Raleway-ExtraBoldItalic.ttf,Raleway-ExtraBoldItalic,Raleway ExtraBold Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,normal,900,Raleway-Black.ttf,Raleway-Black,Raleway Black,"Copyright (c) 2010 - 2013, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway,italic,900,Raleway-BlackItalic.ttf,Raleway-BlackItalic,Raleway Black Italic,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari (impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) with Reserved Font Name \Raleway\"
+Raleway Dots,normal,400,RalewayDots-Regular.ttf,RalewayDots-Regular,Raleway Dots,"Copyright (c) 2010 - 2012, Matt McInerney (matt@pixelspread.com), Pablo Impallari(impallari@gmail.com), Rodrigo Fuenzalida (hello@rfuenzalida.com) and Brenda Gallo(gbrenda1987@gmail.com), with Reserved Font Name \Raleway\"
+Ramabhadra,normal,400,Ramabhadra-Regular.ttf,Ramabhadra,Ramabhadra,Copyright (c) 2012 Andhra Pradesh Society for Knowledge Networks (fonts.siliconandhra.org). Digitized data copyright (c) 2010-2012 Google Corporation.
+Ramaraja,normal,400,Ramaraja-Regular.ttf,Ramaraja,Ramaraja,"Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2010, Sebastian Kosch (sebastian@aldusleaf.org), with Reserved Font Name 'Crimson'"
+Rambla,normal,400,Rambla-Regular.ttf,Rambla-Regular,Rambla,"Copyright (c) 2011-2012, Martin Sommaruga (martin@estudiotrama.com), with Reserved Font Name 'Rambla'"
+Rambla,italic,400,Rambla-Italic.ttf,Rambla-Italic,Rambla Italic,"Copyright (c) 2011-2012, Martin Sommaruga (martin@estudiotrama.com), with Reserved Font Name 'Rambla'"
+Rambla,normal,700,Rambla-Bold.ttf,Rambla-Bold,Rambla Bold,"Copyright (c) 2011-2012, Martin Sommaruga (martin@estudiotrama.com), with Reserved Font Name 'Rambla'"
+Rambla,italic,700,Rambla-BoldItalic.ttf,Rambla-BoldItalic,Rambla Bold Italic,"Copyright (c) 2011-2012, Martin Sommaruga (martin@estudiotrama.com), with Reserved Font Name 'Rambla'"
+Rammetto One,normal,400,RammettoOne-Regular.ttf,RammettoOne-Regular,Rammetto One Regular,"Copyright (c) 2011 by vernon adams (vern@newtypography.co.uk), with Reserved Font Names \Rammetto\"
+Ranchers,normal,400,Ranchers-Regular.ttf,Ranchers-Regular,Ranchers,"Copyright (c) 2012, Pablo Impallari (www.impallari.com|impallari@gmail.com), Brenda Gallo. (gbrenda1987@gmail.com), with Reserved Font Name Ranchers."
+Ranga,normal,400,Ranga-Regular.ttf,Ranga-Regular,Ranga Regular,Copyright (c) 2014 by TipTopTyp.
+Ranga,normal,700,Ranga-Bold.ttf,Ranga-Bold,Ranga Bold,Copyright (c) 2014 by TipTopTyp.
+Rasa,normal,300,Rasa-Light.ttf,Rasa-Light,Rasa Light,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Rasa,normal,400,Rasa-Regular.ttf,Rasa-Regular,Rasa Regular,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Rasa,normal,500,Rasa-Medium.ttf,Rasa-Medium,Rasa Medium,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Rasa,normal,600,Rasa-SemiBold.ttf,Rasa-SemiBold,Rasa SemiBold,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Rasa,normal,700,Rasa-Bold.ttf,Rasa-Bold,Rasa Bold,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Rationale,normal,400,Rationale-Regular.ttf,Rationale-Regular,Rationale,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Rationale\."
+Ravi Prakash,normal,400,RaviPrakash-Regular.ttf,RaviPrakash-Regular,Ravi Prakash,"Copyright (c) 2011 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar), with Reserved Font Name 'Joti'"
+Recursive,normal,400,"Recursive[CASL,CRSV,MONO,slnt,wght].ttf",Recursive,Recursive,Copyright 2019 The Recursive Project Authors (info@arrowtype.com)
+Redacted,normal,400,Redacted-Regular.ttf,RedactedRegular,Redacted Regular,"Copyright (c) 2013, Christian Naths (christiannaths@gmail.com christiannaths.com)"
+Redacted Script,normal,400,RedactedScript-Regular.ttf,RedactedScriptRegular,Redacted Script Regular,"Copyright (c) 2013, Christian Naths (christiannaths@gmail.com christiannaths.com)"
+Redacted Script,normal,700,RedactedScript-Bold.ttf,RedactedScriptBold,Redacted Script Bold,"Copyright (c) 2013, Christian Naths (christiannaths@gmail.com christiannaths.com)"
+Red Hat Display,normal,400,RedHatDisplay-Regular.ttf,RedHatDisplay-Regular,Red Hat Display,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,italic,400,RedHatDisplay-Italic.ttf,RedHatDisplay-Italic,Red Hat Display It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,normal,500,RedHatDisplay-Medium.ttf,RedHatDisplay-Medium,Red Hat Display Medium,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,italic,500,RedHatDisplay-MediumItalic.ttf,RedHatDisplay-MediumItalic,Red Hat Display Medium It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,normal,700,RedHatDisplay-Bold.ttf,RedHatDisplay-Bold,Red Hat Display Bold,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,italic,700,RedHatDisplay-BoldItalic.ttf,RedHatDisplay-BoldItalic,Red Hat Display Bold It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,normal,900,RedHatDisplay-Black.ttf,RedHatDisplay-Black,Red Hat Display Black,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Display,italic,900,RedHatDisplay-BlackItalic.ttf,RedHatDisplay-BlackItalic,Red Hat Display Black It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Text,normal,400,RedHatText-Regular.ttf,RedHatText-Regular,Red Hat Text,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Text,italic,400,RedHatText-Italic.ttf,RedHatText-Italic,Red Hat Text It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Text,normal,500,RedHatText-Medium.ttf,RedHatText-Medium,Red Hat Text Medium,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Text,italic,500,RedHatText-MediumItalic.ttf,RedHatText-MediumItalic,Red Hat Text Medium It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Text,normal,700,RedHatText-Bold.ttf,RedHatText-Bold,Red Hat Text Bold,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Red Hat Text,italic,700,RedHatText-BoldItalic.ttf,RedHatText-BoldItalic,Red Hat Text Bold It,Copyright 2019 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont)
+Reem Kufi,normal,400,ReemKufi-Regular.ttf,ReemKufi-Regular,Reem Kufi Regular,Copyright  2015-2016 The Reem Kufi Project Authors.
+Reenie Beanie,normal,400,ReenieBeanie.ttf,ReenieBeanie,Reenie Beanie,Copyright (c) 2010 Typeco (james@typeco.com). All rights reserved.
+Revalia,normal,400,Revalia-Regular.ttf,Revalia-Regular,Revalia-Regular,"Copyright (c) 2011, Johan Kallas (johankallas@gmail.com), Copyright (c) 2011, Mihkel Virkus (mihkelvirkus@gmail.com), with Reserved Font Name Revalia."
+Rhodium Libre,normal,400,RhodiumLibre-Regular.ttf,RhodiumLibre-Regular,Rhodium Libre,"Copyright (c) 2014, Dunwich Type Founders (http://dunwichtype.com). Rhodium is a trademark of Dunwich Type Founders."
+Ribeye,normal,400,Ribeye-Regular.ttf,Ribeye-Regular,Ribeye,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Ribeye\"
+Ribeye Marrow,normal,400,RibeyeMarrow-Regular.ttf,RibeyeMarrow-Regular,Ribeye Marrow,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Ribeye Marrow\"
+Righteous,normal,400,Righteous-Regular.ttf,Righteous-Regular,Righteous,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Righteous\"
+Risque,normal,400,Risque-Regular.ttf,Risque-Regular,Risque,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Risque\"
+Roboto,normal,400,"Roboto[wdth,wght].ttf",Roboto-Regular,Roboto,Copyright 2011 Google Inc. All Rights Reserved.
+Roboto,italic,400,"Roboto-Italic[wdth,wght].ttf",Roboto-Italic,Roboto Italic,Copyright 2011 Google Inc. All Rights Reserved.
+Rokkitt,normal,400,Rokkitt[wght].ttf,Rokkitt-Regular,Rokkitt Regular,Copyright 2016 The Rokkit Project Authors (https://github.com/googlefonts/RokkittFont)
+Romanesco,normal,400,Romanesco-Regular.ttf,Romanesco-Regular,Romanesco,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Romanesco\"
+Ropa Sans,normal,400,RopaSans-Regular.ttf,RopaSans-Regular,Ropa Sans Regular,"Copyright 2013 The Ropa Sans Project Authors (nikoltchev@lettersoup.de), with Reserved Font Name \Ropa Sans\."
+Ropa Sans,italic,400,RopaSans-Italic.ttf,RopaSans-Italic,Ropa Sans Italic,"Copyright 2013 The Ropa Sans Project Authors (nikoltchev@lettersoup.de), with Reserved Font Name \Ropa Sans\."
+Rosario,normal,400,Rosario[wght].ttf,Rosario-Light,Rosario Light,Copyright 2019 The Rosario Project Authors (https://github.com/Omnibus-Type/Rosario)
+Rosario,italic,400,Rosario-Italic[wght].ttf,Rosario-LightItalic,Rosario Light Italic,Copyright 2019 The Rosario Project Authors (https://github.com/Omnibus-Type/Rosario)
+Rosarivo,normal,400,Rosarivo-Regular.ttf,Rosarivo-Regular,Rosarivo,"Copyright (c) 2011, UGR Design (www.ugrdesign.com.ar info@ugrdesign.com.ar), with Reserved Font Names \Rosarivo\, \Rosarivo Pro\, \Rosarivo UGR\"
+Rosarivo,italic,400,Rosarivo-Italic.ttf,Rosarivo-Italic,Rosarivo Italic,"Copyright (c) 2011, UGR Design (www.ugrdesign.com.ar info@ugrdesign.com.ar), with Reserved Font Names \Rosarivo\, \Rosarivo Pro\, \Rosarivo UGR\"
+Rouge Script,normal,400,RougeScript-Regular.ttf,RougeScript-Regular,Rouge Script,"Copyright (c) 2011 Typesenses (typesenses@live.com.ar), with Reserved Font Name \Rouge Script\"
+Rowdies,normal,300,Rowdies-Light.ttf,Rowdies-Light,Rowdies Light,Copyright 2018 The Rowdies Project Authors (https://github.com/magictype/rowdy)
+Rowdies,normal,400,Rowdies-Regular.ttf,Rowdies-Regular,Rowdies Regular,Copyright 2018 The Rowdies Project Authors (https://github.com/magictype/rowdy)
+Rowdies,normal,700,Rowdies-Bold.ttf,Rowdies-Bold,Rowdies Bold,Copyright 2018 The Rowdies Project Authors (https://github.com/magictype/rowdy)
+Rozha One,normal,400,RozhaOne-Regular.ttf,RozhaOne-Regular,Rozha One Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Rubik,normal,300,Rubik-Light.ttf,Rubik-Light,Rubik Light,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,italic,300,Rubik-LightItalic.ttf,Rubik-LightItalic,Rubik Light Italic,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,normal,400,Rubik-Regular.ttf,Rubik-Regular,Rubik Regular,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,italic,400,Rubik-Italic.ttf,Rubik-Italic,Rubik Italic,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,normal,500,Rubik-Medium.ttf,Rubik-Medium,Rubik Medium,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,italic,500,Rubik-MediumItalic.ttf,Rubik-MediumItalic,Rubik Medium Italic,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,normal,700,Rubik-Bold.ttf,Rubik-Bold,Rubik Bold,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,italic,700,Rubik-BoldItalic.ttf,Rubik-BoldItalic,Rubik Bold Italic,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,normal,900,Rubik-Black.ttf,Rubik-Black,Rubik Black,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik,italic,900,Rubik-BlackItalic.ttf,Rubik-BlackItalic,Rubik Black Italic,Copyright 2015 The Rubik Project Authors (https://github.com/googlefonts/rubik)
+Rubik Mono One,normal,400,RubikMonoOne-Regular.ttf,RubikMonoOne-Regular,Rubik Mono One Regular,Copyright 2015 The Rubik Project Authors (mail@hubertfischer.com)
+Rubik One,normal,400,RubikOne-Regular.ttf,RubikOne-Regular,Rubik One Regular,"Copyright (c) 2013, 2014, Hubert and Fischer, Philipp Hubert (philipp@hubertfischer.com), Sebastian Fischer (sebastian@hubertfischer.com)"
+Ruda,normal,400,Ruda[wght].ttf,Ruda-Regular,Ruda Regular,Copyright 2019 The Ruda Project Authors (https://github.com/marmonsalve/Ruda-new)
+Rufina,normal,400,Rufina-Regular.ttf,Rufina-Regular,Rufina,"Copyright (c) 2011-2012, Martin Sommaruga (martin@estudiotrama.com), with Reserved Font Name 'Rufina'"
+Rufina,normal,700,Rufina-Bold.ttf,Rufina-Bold,Rufina Bold,"Copyright (c) 2011-2012, Martin Sommaruga (martin@estudiotrama.com), with Reserved Font Name 'Rufina'"
+Ruge Boogie,normal,400,RugeBoogie-Regular.ttf,RugeBoogie-Regular,Ruge Boogie,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Ruge Boogie\"
+Ruluko,normal,400,Ruluko-Regular.ttf,Ruluko,Ruluko,"Copyright (c) 2011, Ana Sanfelippo, Angelica Diaz y Meme Hernandez (anasanfe@gmail.com - angiecina@gmail.com), with Reserved Font Name \Ruluko\"
+Rum Raisin,normal,400,RumRaisin-Regular.ttf,RumRaisin-Regular,Rum Raisin,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name 'Rum Raisin'"
+Ruslan Display,normal,400,RuslanDisplay.ttf,RuslanDisplay,Ruslan Display,"Copyright (c) 2010, 2011, Denis Masharov <denis.masharov@gmail.com>, Vladimir Rabdu. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Russo One,normal,400,RussoOne-Regular.ttf,RussoOne-Regular,Russo One,"Copyright (c) 2011-2012, Jovanny Lemonad (lemonad@jovanny.ru), with Reserved Font Name \Russo\"
+Ruthie,normal,400,Ruthie-Regular.ttf,Ruthie-Regular,Ruthie,"Copyright (c) 2011 TypeSETit, LLC (typesetit@att.net), with Reserved Font Name \Ruthie\"
+Rye,normal,400,Rye-Regular.ttf,Rye-Regular,Rye Regular,"Copyright (c) 2012, Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name 'Rye'"
+Sacramento,normal,400,Sacramento-Regular.ttf,Sacramento-Regular,Sacramento,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name 'Sacramento'"
+Sahitya,normal,400,Sahitya-Regular.ttf,Sahitya-Regular,Sahitya,Copyright (c) 2015 by Juan Pablo del Peral (http://www.huertatipografica.com). All rights reserved.
+Sahitya,normal,700,Sahitya-Bold.ttf,Sahitya-Bold,Sahitya Bold,Copyright (c) 2015 by Juan Pablo del Peral (http://www.huertatipografica.com). All rights reserved.
+Sail,normal,400,Sail-Regular.ttf,Sail-Regular,Sail,"Copyright (c) 2011 by LatinoType Limitada (luciano@latinotype.com), with Reserved Font Names \Sail\"
+Saira,normal,100,Saira-Thin.ttf,Saira-Thin,Saira Thin,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,200,Saira-ExtraLight.ttf,Saira-ExtraLight,Saira ExtraLight,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,300,Saira-Light.ttf,Saira-Light,Saira Light,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,400,Saira-Regular.ttf,Saira-Regular,Saira Regular,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,500,Saira-Medium.ttf,Saira-Medium,Saira Medium,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,600,Saira-SemiBold.ttf,Saira-SemiBold,Saira SemiBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,700,Saira-Bold.ttf,Saira-Bold,Saira Bold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,800,Saira-ExtraBold.ttf,Saira-ExtraBold,Saira ExtraBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira,normal,900,Saira-Black.ttf,Saira-Black,Saira Black,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,100,SairaCondensed-Thin.ttf,SairaCondensed-Thin,Saira Condensed Thin,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,200,SairaCondensed-ExtraLight.ttf,SairaCondensed-ExtraLight,Saira Condensed ExtraLight,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,300,SairaCondensed-Light.ttf,SairaCondensed-Light,Saira Condensed Light,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,400,SairaCondensed-Regular.ttf,SairaCondensed-Regular,Saira Condensed Regular,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,500,SairaCondensed-Medium.ttf,SairaCondensed-Medium,Saira Condensed Medium,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,600,SairaCondensed-SemiBold.ttf,SairaCondensed-SemiBold,Saira Condensed SemiBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,700,SairaCondensed-Bold.ttf,SairaCondensed-Bold,Saira Condensed Bold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,800,SairaCondensed-ExtraBold.ttf,SairaCondensed-ExtraBold,Saira Condensed ExtraBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Condensed,normal,900,SairaCondensed-Black.ttf,SairaCondensed-Black,Saira Condensed Black,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,100,SairaExtraCondensed-Thin.ttf,SairaExtraCondensed-Thin,Saira ExtraCondensed Thin,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,200,SairaExtraCondensed-ExtraLight.ttf,SairaExtraCondensed-ExtraLight,Saira ExtraCondensed ExtraLight,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,300,SairaExtraCondensed-Light.ttf,SairaExtraCondensed-Light,Saira ExtraCondensed Light,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,400,SairaExtraCondensed-Regular.ttf,SairaExtraCondensed-Regular,Saira ExtraCondensed Regular,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,500,SairaExtraCondensed-Medium.ttf,SairaExtraCondensed-Medium,Saira ExtraCondensed Medium,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,600,SairaExtraCondensed-SemiBold.ttf,SairaExtraCondensed-SemiBold,Saira ExtraCondensed SemiBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,700,SairaExtraCondensed-Bold.ttf,SairaExtraCondensed-Bold,Saira ExtraCondensed Bold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,800,SairaExtraCondensed-ExtraBold.ttf,SairaExtraCondensed-ExtraBold,Saira ExtraCondensed ExtraBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Extra Condensed,normal,900,SairaExtraCondensed-Black.ttf,SairaExtraCondensed-Black,Saira ExtraCondensed Black,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,100,SairaSemiCondensed-Thin.ttf,SairaSemiCondensed-Thin,Saira SemiCondensed Thin,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,200,SairaSemiCondensed-ExtraLight.ttf,SairaSemiCondensed-ExtraLight,Saira SemiCondensed ExtraLight,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,300,SairaSemiCondensed-Light.ttf,SairaSemiCondensed-Light,Saira SemiCondensed Light,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,400,SairaSemiCondensed-Regular.ttf,SairaSemiCondensed-Regular,Saira SemiCondensed Regular,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,500,SairaSemiCondensed-Medium.ttf,SairaSemiCondensed-Medium,Saira SemiCondensed Medium,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,600,SairaSemiCondensed-SemiBold.ttf,SairaSemiCondensed-SemiBold,Saira SemiCondensed SemiBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,700,SairaSemiCondensed-Bold.ttf,SairaSemiCondensed-Bold,Saira SemiCondensed Bold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,800,SairaSemiCondensed-ExtraBold.ttf,SairaSemiCondensed-ExtraBold,Saira SemiCondensed ExtraBold,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Semi Condensed,normal,900,SairaSemiCondensed-Black.ttf,SairaSemiCondensed-Black,Saira SemiCondensed Black,"Copyright 2016 The Saira Project Authors (omnibus.type@gmail.com), with reserved font name \Saira\."
+Saira Stencil One,normal,400,SairaStencilOne-Regular.ttf,SairaStencilOne-Regular,Saira Stencil One Regular,Copyright 2019 The Saira Stencil Project Authors (https://github.com/Omnibus-Type/Saira)
+Salsa,normal,400,Salsa-Regular.ttf,Salsa-Regular,Salsa-Regular,"Copyright (c) 2011 by John Vargas Beltrn (john.vargasbeltran@gmail.com), with Reserved Font Name Salsa."
+Sanchez,normal,400,Sanchez-Regular.ttf,Sanchez-Regular,Sanchez,"Copyright (c) 2012, LatinoType (luciano@latinotype.com), with Reserved Font Names 'Sanchez'"
+Sanchez,italic,400,Sanchez-Italic.ttf,Sanchez-Italic,Sanchez Italic,"Copyright (c) 2012, LatinoType (luciano@latinotype.com), with Reserved Font Names 'Sanchez'"
+Sancreek,normal,400,Sancreek-Regular.ttf,Sancreek-Regular,Sancreek Regular,"Copyright (c) 2011 by vernon adams (vern@newtypography.co.uk), with Reserved Font Names \Sancreek\"
+Sansation,normal,300,Sansation-Light.ttf,Sansation-Light,Sansation Light,"Copyright (c) 2011 by Bernd Montag (berndmontag@gmx.de), with Reserved Font Name 'Sansation'"
+Sansation,italic,300,Sansation-LightItalic.ttf,Sansation-LightItalic,Sansation Light Italic,"Copyright (c) 2011 by Bernd Montag (berndmontag@gmx.de), with Reserved Font Name 'Sansation'"
+Sansation,normal,400,Sansation-Regular.ttf,Sansation-Regular,Sansation Regular,"Copyright (c) 2011 by Bernd Montag (berndmontag@gmx.de), with Reserved Font Name 'Sansation'"
+Sansation,italic,400,Sansation-Italic.ttf,Sansation-Italic,Sansation Italic,"Copyright (c) 2011 by Bernd Montag (berndmontag@gmx.de), with Reserved Font Name 'Sansation'"
+Sansation,normal,700,Sansation-Bold.ttf,Sansation-Bold,Sansation Bold,"Copyright (c) 2011 by Bernd Montag (berndmontag@gmx.de), with Reserved Font Name 'Sansation'"
+Sansation,italic,700,Sansation-BoldItalic.ttf,Sansation-BoldItalic,Sansation Bold Italic,"Copyright (c) 2011 by Bernd Montag (berndmontag@gmx.de), with Reserved Font Name 'Sansation'"
+Sansita,normal,400,Sansita-Regular.ttf,Sansita-Regular,Sansita Regular,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,italic,400,Sansita-Italic.ttf,Sansita-Italic,Sansita Italic,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,normal,700,Sansita-Bold.ttf,Sansita-Bold,Sansita Bold,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,italic,700,Sansita-BoldItalic.ttf,Sansita-BoldItalic,Sansita Bold Italic,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,normal,800,Sansita-ExtraBold.ttf,Sansita-ExtraBold,Sansita ExtraBold,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,italic,800,Sansita-ExtraBoldItalic.ttf,Sansita-ExtraBoldItalic,Sansita ExtraBold Italic,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,normal,900,Sansita-Black.ttf,Sansita-Black,Sansita Black,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita,italic,900,Sansita-BlackItalic.ttf,Sansita-BlackItalic,Sansita Black Italic,Copyright 2016 The Sansita Project Authors (omnibus.type@gmail.com)
+Sansita One,normal,400,SansitaOne-Regular.ttf,SansitaOne-Regular,Sansita One Regular,"Copyright (c) 2011 by Omnibus-Type (www.omnibus-type.com omnibus.type@gmail.com), with Reserved Font Name \Sansita One\."
+Sarabun,normal,100,Sarabun-Thin.ttf,Sarabun-Thin,Sarabun Thin,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,100,Sarabun-ThinItalic.ttf,Sarabun-ThinItalic,Sarabun Thin Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,200,Sarabun-ExtraLight.ttf,Sarabun-ExtraLight,Sarabun ExtraLight,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,200,Sarabun-ExtraLightItalic.ttf,Sarabun-ExtraLightItalic,Sarabun ExtraLight Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,300,Sarabun-Light.ttf,Sarabun-Light,Sarabun Light,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,300,Sarabun-LightItalic.ttf,Sarabun-LightItalic,Sarabun Light Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,400,Sarabun-Regular.ttf,Sarabun-Regular,Sarabun Regular,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,400,Sarabun-Italic.ttf,Sarabun-Italic,Sarabun Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,500,Sarabun-Medium.ttf,Sarabun-Medium,Sarabun Medium,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,500,Sarabun-MediumItalic.ttf,Sarabun-MediumItalic,Sarabun Medium Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,600,Sarabun-SemiBold.ttf,Sarabun-SemiBold,Sarabun SemiBold,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,600,Sarabun-SemiBoldItalic.ttf,Sarabun-SemiBoldItalic,Sarabun SemiBold Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,700,Sarabun-Bold.ttf,Sarabun-Bold,Sarabun Bold,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,700,Sarabun-BoldItalic.ttf,Sarabun-BoldItalic,Sarabun Bold Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,normal,800,Sarabun-ExtraBold.ttf,Sarabun-ExtraBold,Sarabun ExtraBold,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarabun,italic,800,Sarabun-ExtraBoldItalic.ttf,Sarabun-ExtraBoldItalic,Sarabun ExtraBold Italic,Copyright 2018 The Sarabun Project Authors (https://github.com/cadsondemak/Sarabun)
+Sarala,normal,400,Sarala-Regular.ttf,Sarala-Regular,Sarala,Copyright 2015 by Andres Torresi. All rights reserved.
+Sarala,normal,700,Sarala-Bold.ttf,Sarala-Bold,Sarala Bold,Copyright 2015 by Andres Torresi. All rights reserved.
+Sarina,normal,400,Sarina-Regular.ttf,Sarina-Regular,Sarina,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Sarina\."
+Sarpanch,normal,400,Sarpanch-Regular.ttf,Sarpanch-Regular,Sarpanch Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Sarpanch,normal,500,Sarpanch-Medium.ttf,Sarpanch-Medium,Sarpanch Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Sarpanch,normal,600,Sarpanch-SemiBold.ttf,Sarpanch-SemiBold,Sarpanch SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Sarpanch,normal,700,Sarpanch-Bold.ttf,Sarpanch-Bold,Sarpanch Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Sarpanch,normal,800,Sarpanch-ExtraBold.ttf,Sarpanch-ExtraBold,Sarpanch ExtraBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Sarpanch,normal,900,Sarpanch-Black.ttf,Sarpanch-Black,Sarpanch Black,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Scada,normal,400,Scada-Regular.ttf,Scada-Regular,Scada Regular,Copyright 2012 The Scada Project Authors (lemonad@jovanny.ru)
+Scada,italic,400,Scada-Italic.ttf,Scada-Italic,Scada Italic,Copyright 2012 The Scada Project Authors (lemonad@jovanny.ru)
+Scada,normal,700,Scada-Bold.ttf,Scada-Bold,Scada Bold,Copyright 2012 The Scada Project Authors (lemonad@jovanny.ru)
+Scada,italic,700,Scada-BoldItalic.ttf,Scada-BoldItalic,Scada Bold Italic,Copyright 2012 The Scada Project Authors (lemonad@jovanny.ru)
+Scheherazade,normal,400,Scheherazade-Regular.ttf,Scheherazade-Regular,Scheherazade,Copyright (c) 1994 - 2015 by SIL International. All rights reserved.
+Scheherazade,normal,700,Scheherazade-Bold.ttf,Scheherazade-Bold,Scheherazade Bold,Copyright (c) 1994-2015 SIL International. All rights reserved.
+Scope One,normal,400,ScopeOne-Regular.ttf,ScopeOne-Regular,Scope One Regular,Copyright 2015 Dalton Maag Ltd (info@daltonmaag.com)
+Seaweed Script,normal,400,SeaweedScript-Regular.ttf,SeaweedScript-Regular,Seaweed Script,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Seaweed Script\"
+Secular One,normal,400,SecularOne-Regular.ttf,SecularOne-Regular,Secular One Regular,Copyright 2016 Michal Sahar. All rights reserved.
+Sedan,normal,400,Sedan-Regular.ttf,Sedan-Regular,Sedan,"Copyright (c) 2012, Sebastian Salazar (sebotas26@hotmail.com), with Reserved Font Name 'Sedan'"
+Sedan,italic,400,Sedan-Italic.ttf,Sedan-Italic,Sedan Italic,"Copyright (c) 2012, Sebastian Salazar (sebotas26@hotmail.com), with Reserved Font Name 'Sedan'"
+Sedan SC,normal,400,SedanSC-Regular.ttf,SedanSC-Regular,Sedan SC,"Copyright (c) 2012, Sebastian Salazar (sebotas26@hotmail.com), with Reserved Font Name 'Sedan'"
+Sedgwick Ave,normal,400,SedgwickAve-Regular.ttf,SedgwickAve-Regular,Sedgwick Ave Regular,Copyright 2017 The Sedgwick Ave Project Authors (https://github.com/googlefonts/sedgwickave)
+Sedgwick Ave Display,normal,400,SedgwickAveDisplay-Regular.ttf,SedgwickAveDisplay-Regular,Sedgwick Ave Display Regular,Copyright 2017 The Sedgwick Ave Project Authors (https://github.com/googlefonts/sedgwickave)
+Sen,normal,400,Sen-Regular.ttf,Sen-Regular,Sen Regular,Copyright 2015 The Sen Project Authors (https://github.com/philatype/Sen)
+Sen,normal,700,Sen-Bold.ttf,Sen-Bold,Sen Bold,Copyright 2015 The Sen Project Authors (https://github.com/philatype/Sen)
+Sen,normal,800,Sen-ExtraBold.ttf,Sen-ExtraBold,Sen ExtraBold,Copyright 2015 The Sen Project Authors (https://github.com/philatype/Sen)
+Sevillana,normal,400,Sevillana-Regular.ttf,Sevillana-Regular,Sevillana,"Copyright (c) 2011, Brownfox (gayaneh.b@gmail.com), with Reserved Font Names \Sevillana\"
+Seymour One,normal,400,SeymourOne-Regular.ttf,SeymourOne,Seymour One,Copyright (c) 2011-12 by vernon adams (vern@newtypography.co.uk) with Reserved Font Names 'Seymour'. All rights reserved.
+Shadows Into Light,normal,400,ShadowsIntoLight.ttf,ShadowsIntoLight,Shadows Into Light,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Shadows Into Light Two,normal,400,ShadowsIntoLightTwo-Regular.ttf,ShadowsIntoLightTwo-Regular,Shadows Into Light Two,"Copyright (c) 2012, Kimberly Geswein (kimberlygeswein@gmail.com)."
+Shanti,normal,400,Shanti-Regular.ttf,Shanti,Shanti,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names 'Shanti'. All rights reserved."
+Share,normal,400,Share-Regular.ttf,Share-Regular,Share Regular,"Copyright (c) 2005-2011, Carrois Type Design (carrois.com), with Reserved Font Name \Share\"
+Share,italic,400,Share-Italic.ttf,Share-Italic,Share Italic,"Copyright (c) 2005-2011, Carrois Type Design (carrois.com), with Reserved Font Name \Share\"
+Share,normal,700,Share-Bold.ttf,Share-Bold,Share Bold,"Copyright (c) 2005-2011, Carrois Type Design (carrois.com), with Reserved Font Name \Share\"
+Share,italic,700,Share-BoldItalic.ttf,Share-BoldItalic,Share Bold Italic,"Copyright (c) 2005-2011, Carrois Type Design (carrois.com), with Reserved Font Name \Share\"
+Share Tech,normal,400,ShareTech-Regular.ttf,ShareTech-Regular,Share Tech Regular,"Copyright 2012 The Share Tech Project Authors (post@carrois.com), with Reserved Font Name \'Share."
+Share Tech Mono,normal,400,ShareTechMono-Regular.ttf,ShareTechMono-Regular,Share Tech Mono,"Copyright (c) 2012, Carrois Type Design, Ralph du Carrois (www.carrois.com post@carrois.com), with Reserved Font Name 'Share'"
+Shojumaru,normal,400,Shojumaru-Regular.ttf,Shojumaru-Regular,Shojumaru,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Shojumaru\"
+Short Stack,normal,400,ShortStack-Regular.ttf,ShortStack,Short Stack,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Names \Short Stack\ and \Short Stack One\."
+Shrikhand,normal,400,Shrikhand-Regular.ttf,Shrikhand-Regular,Shrikhand Regular,Copyright (c) 2015 Jonny Pinhorn (jonpinhorn.typedesign@gmail.com)
+Siamreap,normal,400,Siemreap.ttf,Siemreap,Siemreap,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Siemreap. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Siemreap,normal,400,Siemreap.ttf,Siemreap,Siemreap,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name Khmer OS Siemreap. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Sigmar One,normal,400,SigmarOne-Regular.ttf,SigmarOne-Regular,Sigmar One Regular,Copyright 2011 The Sigmar One Project Authors (contact@sansoxygen.com)
+Signika,normal,300,Signika-Light.ttf,Signika-Light,Signika Light,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika,normal,400,Signika-Regular.ttf,Signika-Regular,Signika Regular,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika,normal,600,Signika-SemiBold.ttf,Signika-SemiBold,Signika SemiBold,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika,normal,700,Signika-Bold.ttf,Signika-Bold,Signika Bold,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika Negative,normal,300,SignikaNegative-Light.ttf,SignikaNegative-Light,Signika Negative Light,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika Negative,normal,400,SignikaNegative-Regular.ttf,SignikaNegative-Regular,Signika Negative Regular,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika Negative,normal,600,SignikaNegative-SemiBold.ttf,SignikaNegative-SemiBold,Signika Negative SemiBold,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Signika Negative,normal,700,SignikaNegative-Bold.ttf,SignikaNegative-Bold,Signika Negative Bold,"Copyright (c) 2011 by Anna Giedrys (info@ancymonic.com), with Reserved Font Names \Signika\."
+Simonetta,normal,400,Simonetta-Regular.ttf,Simonetta-Regular,Simonetta Regular,"Copyright (c) 2011-2012, Brownfox (www.brownfox.org gayaneh.b@gmail.com), with Reserved Font Name \Simonetta\"
+Simonetta,italic,400,Simonetta-Italic.ttf,Simonetta-Italic,Simonetta Italic,"Copyright (c) 2011-2012, Brownfox (www.brownfox.org gayaneh.b@gmail.com), with Reserved Font Name \Simonetta\"
+Simonetta,normal,900,Simonetta-Black.ttf,Simonetta-Black,Simonetta Black,"Copyright (c) 2011-2012, Brownfox (www.brownfox.org gayaneh.b@gmail.com), with Reserved Font Name \Simonetta\"
+Simonetta,italic,900,Simonetta-BlackItalic.ttf,Simonetta-BlackItalic,Simonetta Black Italic,"Copyright (c) 2011-2012, Brownfox (www.brownfox.org gayaneh.b@gmail.com), with Reserved Font Name \Simonetta\"
+Single Day,normal,400,SingleDay-Regular.ttf,SingleDay-Regular,Single Day Regular,Copyright 2015 DXKorea Inc. All rights reserved.
+Sintony,normal,400,Sintony-Regular.ttf,Sintony,Sintony,"Copyright (c) 2013, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Sintony'"
+Sintony,normal,700,Sintony-Bold.ttf,Sintony-Bold,Sintony Bold,"Copyright (c) 2013, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Sintony'"
+Sirin Stencil,normal,400,SirinStencil-Regular.ttf,SirinStencil-Regular,SirinStencil,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Sirin\ and \Sirin Stencil\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Sitara,normal,400,Sitara-Regular.ttf,Sitara-Regular,Sitara,"Copyright (c) 2014, Neelakash Kshetrimayum (github.com/Neelakash/sitara). Copyright 2013, Google Corporation."
+Sitara,italic,400,Sitara-Italic.ttf,Sitara-Italic,Sitara Italic,"Copyright (c) 2014, Neelakash Kshetrimayum (github.com/Neelakash/sitara). Copyright 2013, Google Corporation."
+Sitara,normal,700,Sitara-Bold.ttf,Sitara-Bold,Sitara Bold,"Copyright (c) 2014, Neelakash Kshetrimayum (github.com/Neelakash/sitara). Copyright 2013, Google Corporation."
+Sitara,italic,700,Sitara-BoldItalic.ttf,Sitara-BoldItalic,Sitara Bold Italic,"Copyright (c) 2014, Neelakash Kshetrimayum (github.com/Neelakash/sitara). Copyright 2013, Google Corporation."
+Six Caps,normal,400,SixCaps.ttf,SixCaps,Six Caps,Copyright (c) 2010 by vernon adams (vern@newtypography.co.uk) with Reserved Font Names 'Six Caps'. All rights reserved.
+Skranji,normal,400,Skranji-Regular.ttf,Skranji,Skranji,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Skranji\"
+Skranji,normal,700,Skranji-Bold.ttf,Skranji-Bold,Skranji Bold,"Copyright (c) 2012 by Font Diner, Inc DBA Neapolitan (diner@fontdiner.com) with Reseved Font Name \Skranji Bold\"
+Slabo 13px,normal,400,Slabo13px-Regular.ttf,Slabo13px-Regular,Slabo 13px,"Copyright (c) 2013, Tiro Typeworks Ltd (www.tiro.com)."
+Slabo 27px,normal,400,Slabo27px-Regular.ttf,Slabo27px-Regular,Slabo 27px,"Copyright (c) 2013, Tiro Typeworks Ltd (www.tiro.com)."
+Smythe,normal,400,Smythe-Regular.ttf,Smythe,Smythe,Copyright (c) 2011 by Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names 'Smythe'. All rights reserved.
+Sniglet,normal,400,Sniglet-Regular.ttf,Sniglet-Regular,Sniglet Regular,"Copyright (c) 2008, Haley Fiege (haley@kingdomofawesome.com), Copyright (c) 2012, Brenda Gallo (gbrenda1987@gmail.com) Copyright (c) 2013, Pablo Impallari (www.impallari.com|impallari@gmail.com), with no Reserved Font Name."
+Sniglet,normal,800,Sniglet-ExtraBold.ttf,Sniglet-ExtraBold,Sniglet ExtraBold,"Copyright (c) 2008, Haley Fiege (haley@kingdomofawesome.com), Copyright (c) 2012, Brenda Gallo (gbrenda1987@gmail.com) Copyright (c) 2013, Pablo Impallari (www.impallari.com|impallari@gmail.com), with no Reserved Font Name."
+Snippet,normal,400,Snippet.ttf,Snippet,Snippet,"Copyright (c) 2011 Gesine Todt (www.gesine-todt.de hallo@gesine-todt.de), with Reserved Font Name \Snippet\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Snowburst One,normal,400,SnowburstOne-Regular.ttf,SnowburstOne-Regular,Snowburst One,"Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name 'Snowburst'"
+Sofadi One,normal,400,SofadiOne-Regular.ttf,SofadiOne-Regular,Sofadi One Regular,"Copyright (c) 2011 by Botjo Nikoltchev, with Reserved Font Name \'Sofadi One\'"
+Sofia,normal,400,Sofia-Regular.ttf,Sofia-Regular,Sofia,"Copyright (c) 2011 by LatinoType Limitada (info@latinotype.com), with Reserved Font Names \Sofia\"
+Solway,normal,300,Solway-Light.ttf,Solway-Light,Solway Light,Copyright 2018 The Solway Project Authors (https://github.com/mashavp/Solway)
+Solway,normal,400,Solway-Regular.ttf,Solway-Regular,Solway Regular,Copyright 2018 The Solway Project Authors (https://github.com/mashavp/Solway)
+Solway,normal,500,Solway-Medium.ttf,Solway-Medium,Solway Medium,Copyright 2018 The Solway Project Authors (https://github.com/mashavp/Solway)
+Solway,normal,700,Solway-Bold.ttf,Solway-Bold,Solway Bold,Copyright 2018 The Solway Project Authors (https://github.com/mashavp/Solway)
+Solway,normal,800,Solway-ExtraBold.ttf,Solway-ExtraBold,Solway ExtraBold,Copyright 2018 The Solway Project Authors (https://github.com/mashavp/Solway)
+Sometype Mono,normal,400,SometypeMono-Regular.ttf,SometypeMono-Regular,Sometype Mono Regular,Copyright 2018 The Sometype Mono Project Authors (https://github.com/dharmatype/Sometype-Mono)
+Sometype Mono,italic,400,SometypeMono-Italic.ttf,SometypeMono-Italic,Sometype Mono Italic,Copyright 2018 The Sometype Mono Project Authors (https://github.com/dharmatype/Sometype-Mono)
+Sometype Mono,normal,500,SometypeMono-Medium.ttf,SometypeMono-Medium,Sometype Mono Medium,Copyright 2018 The Sometype Mono Project Authors (https://github.com/dharmatype/Sometype-Mono)
+Sometype Mono,italic,500,SometypeMono-MediumItalic.ttf,SometypeMono-MediumItalic,Sometype Mono Medium Italic,Copyright 2018 The Sometype Mono Project Authors (https://github.com/dharmatype/Sometype-Mono)
+Sometype Mono,normal,700,SometypeMono-Bold.ttf,SometypeMono-Bold,Sometype Mono Bold,Copyright 2018 The Sometype Mono Project Authors (https://github.com/dharmatype/Sometype-Mono)
+Sometype Mono,italic,700,SometypeMono-BoldItalic.ttf,SometypeMono-BoldItalic,Sometype Mono Bold Italic,Copyright 2018 The Sometype Mono Project Authors (https://github.com/dharmatype/Sometype-Mono)
+Song Myung,normal,400,SongMyung-Regular.ttf,SongMyung-Regular,Song Myung Regular,Copyright 2018 The Song Myung Project Authors
+Sonsie One,normal,400,SonsieOne-Regular.ttf,SonsieOne-Regular,Sonsie One,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Sonsie One\."
+Sorts Mill Goudy,normal,400,SortsMillGoudy-Regular.ttf,SortsMillGoudy-Regular,Sorts Mill Goudy Regular,"Copyright (c) 2010, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Sorts Mill Goudy,italic,400,SortsMillGoudy-Italic.ttf,SortsMillGoudy-Italic,Sorts Mill Goudy Italic,"Copyright (c) 2010, Barry Schwartz (chemoelectric@chemoelectric.org)"
+Source Code Pro,normal,200,SourceCodePro-ExtraLight.ttf,SourceCodePro-ExtraLight,Source Code Pro ExtraLight,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,200,SourceCodePro-ExtraLightItalic.ttf,SourceCodePro-ExtraLightIt,Source Code Pro ExtraLight Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,normal,300,SourceCodePro-Light.ttf,SourceCodePro-Light,Source Code Pro Light,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,300,SourceCodePro-LightItalic.ttf,SourceCodePro-LightIt,Source Code Pro Light Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,normal,400,SourceCodePro-Regular.ttf,SourceCodePro-Regular,Source Code Pro Regular,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,400,SourceCodePro-Italic.ttf,SourceCodePro-It,Source Code Pro Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,normal,500,SourceCodePro-Medium.ttf,SourceCodePro-Medium,Source Code Pro Medium,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,500,SourceCodePro-MediumItalic.ttf,SourceCodePro-MediumIt,Source Code Pro Medium Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,normal,600,SourceCodePro-SemiBold.ttf,SourceCodePro-SemiBold,Source Code Pro SemiBold,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,600,SourceCodePro-SemiBoldItalic.ttf,SourceCodePro-SemiBoldIt,Source Code Pro SemiBold Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,normal,700,SourceCodePro-Bold.ttf,SourceCodePro-Bold,Source Code Pro Bold,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,700,SourceCodePro-BoldItalic.ttf,SourceCodePro-BoldIt,Source Code Pro Bold Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,normal,900,SourceCodePro-Black.ttf,SourceCodePro-Black,Source Code Pro Black,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Code Pro,italic,900,SourceCodePro-BlackItalic.ttf,SourceCodePro-BlackIt,Source Code Pro Black Italic,"Copyright 2010, 2012 Adobe Systems Incorporated. All Rights Reserved."
+Source Sans Pro,normal,200,SourceSansPro-ExtraLight.ttf,SourceSansPro-ExtraLight,Source Sans Pro ExtraLight,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,italic,200,SourceSansPro-ExtraLightItalic.ttf,SourceSansPro-ExtraLightItalic,Source Sans Pro ExtraLight Italic,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,normal,300,SourceSansPro-Light.ttf,SourceSansPro-Light,Source Sans Pro Light,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,italic,300,SourceSansPro-LightItalic.ttf,SourceSansPro-LightItalic,Source Sans Pro Light Italic,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,normal,400,SourceSansPro-Regular.ttf,SourceSansPro-Regular,Source Sans Pro Regular,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,italic,400,SourceSansPro-Italic.ttf,SourceSansPro-Italic,Source Sans Pro Italic,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,normal,600,SourceSansPro-SemiBold.ttf,SourceSansPro-SemiBold,Source Sans Pro SemiBold,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,italic,600,SourceSansPro-SemiBoldItalic.ttf,SourceSansPro-SemiBoldItalic,Source Sans Pro SemiBold Italic,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,normal,700,SourceSansPro-Bold.ttf,SourceSansPro-Bold,Source Sans Pro Bold,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,italic,700,SourceSansPro-BoldItalic.ttf,SourceSansPro-BoldItalic,Source Sans Pro Bold Italic,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,normal,900,SourceSansPro-Black.ttf,SourceSansPro-Black,Source Sans Pro Black,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Sans Pro,italic,900,SourceSansPro-BlackItalic.ttf,SourceSansPro-BlackItalic,Source Sans Pro Black Italic,"Copyright 2010, 2012, 2014 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name Source."
+Source Serif Pro,normal,200,SourceSerifPro-ExtraLight.ttf,SourceSerifPro-ExtraLight,Source Serif Pro ExtraLight,"Copyright 2014, 2015, 2016 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'."
+Source Serif Pro,normal,300,SourceSerifPro-Light.ttf,SourceSerifPro-Light,Source Serif Pro Light,"Copyright 2014, 2015, 2016 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'."
+Source Serif Pro,normal,400,SourceSerifPro-Regular.ttf,SourceSerifPro-Regular,Source Serif Pro Regular,"Copyright 2014, 2015, 2016 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'."
+Source Serif Pro,normal,600,SourceSerifPro-SemiBold.ttf,SourceSerifPro-SemiBold,Source Serif Pro SemiBold,"Copyright 2014, 2015, 2016 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'."
+Source Serif Pro,normal,700,SourceSerifPro-Bold.ttf,SourceSerifPro-Bold,Source Serif Pro Bold,"Copyright 2014, 2015, 2016 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'."
+Source Serif Pro,normal,900,SourceSerifPro-Black.ttf,SourceSerifPro-Black,Source Serif Pro Black,"Copyright 2014, 2015, 2016 Adobe Systems Incorporated (http://www.adobe.com/), with Reserved Font Name \'Source\'."
+Space Mono,normal,400,SpaceMono-Regular.ttf,SpaceMono-Regular,Space Mono Regular,Copyright 2016 Google Inc. All Rights Reserved.
+Space Mono,italic,400,SpaceMono-Italic.ttf,SpaceMono-Italic,Space Mono Italic,Copyright 2016 Google Inc. All Rights Reserved.
+Space Mono,normal,700,SpaceMono-Bold.ttf,SpaceMono-Bold,Space Mono Bold,Copyright 2016 Google Inc. All Rights Reserved.
+Space Mono,italic,700,SpaceMono-BoldItalic.ttf,SpaceMono-BoldItalic,Space Mono Bold Italic,Copyright 2016 Google Inc. All Rights Reserved.
+Spartan,normal,400,Spartan[wght].ttf,Spartan-Thin,Spartan Thin,Copyright 2020 The Spartan Project Authors (https://github.com/bghryct/Spartan-MB)
+Spectral,normal,200,Spectral-ExtraLight.ttf,Spectral-ExtraLight,Spectral ExtraLight,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,200,Spectral-ExtraLightItalic.ttf,Spectral-ExtraLightItalic,Spectral ExtraLight Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,normal,300,Spectral-Light.ttf,Spectral-Light,Spectral Light,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,300,Spectral-LightItalic.ttf,Spectral-LightItalic,Spectral Light Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,normal,400,Spectral-Regular.ttf,Spectral-Regular,Spectral Regular,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,400,Spectral-Italic.ttf,Spectral-Italic,Spectral Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,normal,500,Spectral-Medium.ttf,Spectral-Medium,Spectral Medium,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,500,Spectral-MediumItalic.ttf,Spectral-MediumItalic,Spectral Medium Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,normal,600,Spectral-SemiBold.ttf,Spectral-SemiBold,Spectral SemiBold,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,600,Spectral-SemiBoldItalic.ttf,Spectral-SemiBoldItalic,Spectral SemiBold Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,normal,700,Spectral-Bold.ttf,Spectral-Bold,Spectral Bold,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,700,Spectral-BoldItalic.ttf,Spectral-BoldItalic,Spectral Bold Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,normal,800,Spectral-ExtraBold.ttf,Spectral-ExtraBold,Spectral ExtraBold,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral,italic,800,Spectral-ExtraBoldItalic.ttf,Spectral-ExtraBoldItalic,Spectral ExtraBold Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,200,SpectralSC-ExtraLight.ttf,SpectralSC-ExtraLight,Spectral SC ExtraLight,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,200,SpectralSC-ExtraLightItalic.ttf,SpectralSC-ExtraLightItalic,Spectral SC ExtraLight Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,300,SpectralSC-Light.ttf,SpectralSC-Light,Spectral SC Light,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,300,SpectralSC-LightItalic.ttf,SpectralSC-LightItalic,Spectral SC Light Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,400,SpectralSC-Regular.ttf,SpectralSC-Regular,Spectral SC Regular,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,400,SpectralSC-Italic.ttf,SpectralSC-Italic,Spectral SC Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,500,SpectralSC-Medium.ttf,SpectralSC-Medium,Spectral SC Medium,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,500,SpectralSC-MediumItalic.ttf,SpectralSC-MediumItalic,Spectral SC Medium Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,600,SpectralSC-SemiBold.ttf,SpectralSC-SemiBold,Spectral SC SemiBold,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,600,SpectralSC-SemiBoldItalic.ttf,SpectralSC-SemiBoldItalic,Spectral SC SemiBold Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,700,SpectralSC-Bold.ttf,SpectralSC-Bold,Spectral SC Bold,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,700,SpectralSC-BoldItalic.ttf,SpectralSC-BoldItalic,Spectral SC Bold Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,normal,800,SpectralSC-ExtraBold.ttf,SpectralSC-ExtraBold,Spectral SC ExtraBold,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spectral SC,italic,800,SpectralSC-ExtraBoldItalic.ttf,SpectralSC-ExtraBoldItalic,Spectral SC ExtraBold Italic,Copyright 2017 The Spectral Project Authors (http://github.com/productiontype/spectral)
+Spicy Rice,normal,400,SpicyRice-Regular.ttf,SpicyRice-Regular,Spicy Rice,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Spicy Rice\"
+Spinnaker,normal,400,Spinnaker-Regular.ttf,Spinnaker-Regular,Spinnaker,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Spinnaker\."
+Spirax,normal,400,Spirax-Regular.ttf,Spirax-Regular,Spirax-Regular,"Copyright (c) 2011 by Brenda Gallo (gbrenda1987@gmail.com), with Reserved Font Name Spirax."
+Squada One,normal,400,SquadaOne-Regular.ttf,SquadaOne-Regular,Squada One,"Copyright (c) 2011, Admix Designs (http://www.admixdesigns.com joe@admixdesigns.com) with Reserved Font Name Squada."
+Sree Krushnadevaraya,normal,400,SreeKrushnadevaraya-Regular.ttf,SreeKrushnadevaraya,Sree Krushnadevaraya,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 2011-2012, Sorkin Type Co (www.sorkintype.com) with Reserved Font Name 'Cantata'"
+Sriracha,normal,400,Sriracha-Regular.ttf,Sriracha-Regular,Sriracha,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com), Copyright (c) 2014, Pablo Impallari (www.impallari.com|impallari@gmail.com)"
+Srisakdi,normal,400,Srisakdi-Regular.ttf,Srisakdi-Regular,Srisakdi Regular,Copyright 2018 The Srisakdi Project Authors (https://github.com/cadsondemak/Srisakdi)
+Srisakdi,normal,700,Srisakdi-Bold.ttf,Srisakdi-Bold,Srisakdi Bold,Copyright 2018 The Srisakdi Project Authors (https://github.com/cadsondemak/Srisakdi)
+Staatliches,normal,400,Staatliches-Regular.ttf,Staatliches-Regular,Staatliches Regular,Copyright 2018 The Staatliches Project Authors (https://github.com/googlefonts/staatliches)
+Stalemate,normal,400,Stalemate-Regular.ttf,Stalemate-Regular,Stalemate,"Copyright (c) 2012 by Jim Lyles for Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name 'Stalemate'"
+Stalinist One,normal,400,StalinistOne-Regular.ttf,StalinistOne-Regular,Stalinist One,"Copyright (c) 2009-2011, Alexey Maslov, Jovanny Lemonad (lemonad@jovanny.ru), with Reserved Font Name 'Stalinist'"
+Stalin One,normal,400,StalinOne-Regular.ttf,StalinOne-Regular,Stalin One,"Copyright (c) 2009-2011, Alexey Maslov, Jovanny Lemonad (lemonad@jovanny.ru), with Reserved Font Name 'Stalin'"
+Stardos Stencil,normal,400,StardosStencil-Regular.ttf,StardosStencil-Regular,Stardos Stencil Regular,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names 'Stardos'. All rights reserved."
+Stardos Stencil,normal,700,StardosStencil-Bold.ttf,StardosStencil-Bold,Stardos Stencil Bold,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names 'Stardos'. All rights reserved."
+Stint Ultra Condensed,normal,400,StintUltraCondensed-Regular.ttf,StintUltraCondensed-Regular,Stint Ultra Condensed,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Stint Ultra Condensed\"
+Stint Ultra Expanded,normal,400,StintUltraExpanded-Regular.ttf,StintUltraExpanded-Regular,Stint Ultra Expanded,"Copyright (c) 2012 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Stint Ultra Expanded\"
+Stoke,normal,300,Stoke-Light.ttf,Stoke-Light,Stoke Light,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name 'Stoke'"
+Stoke,normal,400,Stoke-Regular.ttf,Stoke-Regular,Stoke Regular,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name 'Stoke'"
+Strait,normal,400,Strait-Regular.ttf,Strait-Regular,Strait,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Strait'"
+Strong,normal,400,Strong-Regular.ttf,Strong-Regular,Strong,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Strong\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Stylish,normal,400,Stylish-Regular.ttf,Stylish-Regular,Stylish Regular,Copyright (c) 1992-2018 AsiaSoft Inc. Seoul Korea All Rights Reserved.
+Sue Ellen Francisco,normal,400,SueEllenFrancisco-Regular.ttf,SueEllenFrancisco,Sue Ellen Francisco,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Suez One,normal,400,SuezOne-Regular.ttf,SuezOne-Regular,Suez One Regular,Copyright 2016 Michal Sahar. All rights reserved.
+Sulphur Point,normal,300,SulphurPoint-Light.ttf,SulphurPoint-Light,Sulphur Point Light,Copyright 2019 The Sulphur Point Project Authors (https://github.com/noponies)
+Sulphur Point,normal,400,SulphurPoint-Regular.ttf,SulphurPoint-Regular,Sulphur Point Regular,Copyright 2019 The Sulphur Point Project Authors (https://github.com/noponies)
+Sulphur Point,normal,700,SulphurPoint-Bold.ttf,SulphurPoint-Bold,Sulphur Point Bold,Copyright 2019 The Sulphur Point Project Authors (https://github.com/noponies)
+Sumana,normal,400,Sumana-Regular.ttf,Sumana-Regular,Sumana,Copyright © 2015 by Cyreal. All rights reserved.
+Sumana,normal,700,Sumana-Bold.ttf,Sumana-Bold,Sumana Bold,Copyright © 2015 by Cyreal. All rights reserved.
+Sunflower,normal,300,Sunflower-Light.ttf,Sunflower-Light,Sunflower Light,Copyright 2008 The Sunflower Project Authors
+Sunflower,normal,500,Sunflower-Medium.ttf,Sunflower-Medium,Sunflower Medium,Copyright 2008 The Sunflower Project Authors
+Sunflower,normal,700,Sunflower-Bold.ttf,Sunflower-Bold,Sunflower Bold,Copyright 2008 The Sunflower Project Authors
+Supermercado One,normal,400,SupermercadoOne-Regular.ttf,SupermercadoOne-Regular,Supermercado One Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Supermercado One\."
+Sura,normal,400,Sura-Regular.ttf,Sura-Regular,Sura,Copyright 2015 by Carolina Giovagnoli. All rights reserved.
+Sura,normal,700,Sura-Bold.ttf,Sura-Bold,Sura Bold,Copyright 2015 by Carolina Giovagnoli. All rights reserved.
+Suranna,normal,400,Suranna-Regular.ttf,Suranna,Suranna,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 2011, Cyreal (www.cyreal.org) with Reserved Font Name 'Prata'"
+Suravaram,normal,400,Suravaram-Regular.ttf,Suravaram,Suravaram,Copyright (c) 2012 Silicon Andhra (fonts.siliconandhra.org). Copyright (c) 2011 by vernon adams (vern@newtypography.co.uk) with Reserved Font Name 'Tienne'
+Suwannaphum,normal,400,Suwannaphum-Regular.ttf,Suwannaphum-Regular,Suwannaphum Regular,"Copyright (c) 2013, Danh Hong (khmertype.org)"
+Swanky and Moo Moo,normal,400,SwankyandMooMoo.ttf,SwankyandMooMoo,Swanky and Moo Moo,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Tajawal,normal,200,Tajawal-ExtraLight.ttf,Tajawal-ExtraLight,Tajawal ExtraLight,(c) 2017 by Boutros International. All rights reserved.
+Tajawal,normal,300,Tajawal-Light.ttf,Tajawal-Light,Tajawal Light,(c) 2017 by Boutros International. All rights reserved.
+Tajawal,normal,400,Tajawal-Regular.ttf,Tajawal-Regular,Tajawal,(c) 2017 by Boutros International. All rights reserved.
+Tajawal,normal,500,Tajawal-Medium.ttf,Tajawal-Medium,Tajawal Medium,(c) 2017 by Boutros International. All rights reserved.
+Tajawal,normal,700,Tajawal-Bold.ttf,Tajawal-Bold,Tajawal Bold,(c) 2017 by Boutros International. All rights reserved.
+Tajawal,normal,800,Tajawal-ExtraBold.ttf,Tajawal-ExtraBold,Tajawal ExtraBold,(c) 2017 by Boutros International. All rights reserved.
+Tajawal,normal,900,Tajawal-Black.ttf,Tajawal-Black,Tajawal Black,(c) 2017 by Boutros International. All rights reserved.
+Tangerine,normal,400,Tangerine-Regular.ttf,Tangerine-Regular,Tangerine Regular,Copyright (c) 2010 by Toshi Omagari. All rights reserved.
+Tangerine,normal,700,Tangerine-Bold.ttf,Tangerine-Bold,Tangerine Bold,Copyright (c) 2010 by Toshi Omagari. All rights reserved.
+Taprom,normal,400,Taprom.ttf,Taprom,Taprom,"Copyright (c) 2010, Danh Hong (khmertype.blogspot.com danhhong@gmail.com), with Reserved Font Name NiDA Taprom. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Tauri,normal,400,Tauri-Regular.ttf,Tauri-Regular,Tauri Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name 'Tauri'."
+Taviraj,normal,100,Taviraj-Thin.ttf,Taviraj-Thin,Taviraj Thin,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,100,Taviraj-ThinItalic.ttf,Taviraj-ThinItalic,Taviraj Thin Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,200,Taviraj-ExtraLight.ttf,Taviraj-ExtraLight,Taviraj ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,200,Taviraj-ExtraLightItalic.ttf,Taviraj-ExtraLightItalic,Taviraj ExtraLight Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,300,Taviraj-Light.ttf,Taviraj-Light,Taviraj Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,300,Taviraj-LightItalic.ttf,Taviraj-LightItalic,Taviraj Light Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,400,Taviraj-Regular.ttf,Taviraj-Regular,Taviraj Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,400,Taviraj-Italic.ttf,Taviraj-Italic,Taviraj Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,500,Taviraj-Medium.ttf,Taviraj-Medium,Taviraj Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,500,Taviraj-MediumItalic.ttf,Taviraj-MediumItalic,Taviraj Medium Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,600,Taviraj-SemiBold.ttf,Taviraj-SemiBold,Taviraj SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,600,Taviraj-SemiBoldItalic.ttf,Taviraj-SemiBoldItalic,Taviraj SemiBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,700,Taviraj-Bold.ttf,Taviraj-Bold,Taviraj Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,700,Taviraj-BoldItalic.ttf,Taviraj-BoldItalic,Taviraj Bold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,800,Taviraj-ExtraBold.ttf,Taviraj-ExtraBold,Taviraj ExtraBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,800,Taviraj-ExtraBoldItalic.ttf,Taviraj-ExtraBoldItalic,Taviraj ExtraBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,normal,900,Taviraj-Black.ttf,Taviraj-Black,Taviraj Black,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Taviraj,italic,900,Taviraj-BlackItalic.ttf,Taviraj-BlackItalic,Taviraj Black Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Teko,normal,300,Teko-Light.ttf,Teko-Light,Teko Light,Copyright 2014 Indian Type Foundry. All rights reserved.
+Teko,normal,400,Teko-Regular.ttf,Teko-Regular,Teko Regular,Copyright 2014 Indian Type Foundry. All rights reserved.
+Teko,normal,500,Teko-Medium.ttf,Teko-Medium,Teko Medium,Copyright 2014 Indian Type Foundry. All rights reserved.
+Teko,normal,600,Teko-SemiBold.ttf,Teko-SemiBold,Teko SemiBold,Copyright 2014 Indian Type Foundry. All rights reserved.
+Teko,normal,700,Teko-Bold.ttf,Teko-Bold,Teko Bold,Copyright 2014 Indian Type Foundry. All rights reserved.
+Telex,normal,400,Telex-Regular.ttf,Telex-Regular,Telex Regular,"Copyright 2011 The Telex Project Authors (info@andrestorresi.com.ar), with Reserved Font Name Telex."
+Tenali Ramakrishna,normal,400,TenaliRamakrishna-Regular.ttf,TenaliRamakrishna,Tenali Ramakrishna,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 2011, Wojciech Kalinowski (wmk69@o2.pl), with Reserved Font Names 'Classica'"
+Tenor Sans,normal,400,TenorSans-Regular.ttf,TenorSans,Tenor Sans,"Copyright (c) 2010, 2011, Denis Masharov <denis.masharov@gmail.com>. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Terminal Dosis,normal,200,TerminalDosis-ExtraLight.ttf,TerminalDosis-ExtraLight,Terminal Dosis ExtraLight,"Copyright (c) 2011, Edgar Tolentino, Pablo Impallari, Igino Marini (impallari.com impallari@gmail.com), with Reserved Font Name Dosis."
+Terminal Dosis,normal,300,TerminalDosis-Light.ttf,TerminalDosis-Light,Terminal Dosis Light,"Copyright (c) 2011, Edgar Tolentino, Pablo Impallari, Igino Marini (impallari.com impallari@gmail.com), with Reserved Font Name Dosis."
+Terminal Dosis,normal,400,TerminalDosis-Regular.ttf,TerminalDosis-Regular,Terminal Dosis Regular,"Copyright (c) 2011, Edgar Tolentino, Pablo Impallari, Igino Marini (impallari.com impallari@gmail.com), with Reserved Font Name Dosis."
+Terminal Dosis,normal,500,TerminalDosis-Medium.ttf,TerminalDosis-Medium,Terminal Dosis Medium,"Copyright (c) 2011, Edgar Tolentino, Pablo Impallari, Igino Marini (impallari.com impallari@gmail.com), with Reserved Font Name Dosis."
+Terminal Dosis,normal,600,TerminalDosis-SemiBold.ttf,TerminalDosis-SemiBold,Terminal Dosis SemiBold,"Copyright (c) 2011, Edgar Tolentino, Pablo Impallari, Igino Marini (impallari.com impallari@gmail.com), with Reserved Font Name Dosis."
+Terminal Dosis,normal,700,TerminalDosis-Bold.ttf,TerminalDosis-Bold,Terminal Dosis Bold,"Copyright (c) 2011 by EdgarTolentino, PabloImpallari, IginoMarini. All rights reserved."
+Terminal Dosis,normal,800,TerminalDosis-ExtraBold.ttf,TerminalDosis-ExtraBold,Terminal Dosis ExtraBold,"Copyright (c) 2011 by EdgarTolentino, PabloImpallari, IginoMarini. All rights reserved."
+Terminal Dosis Light,normal,400,TerminalDosis-Light.ttf,TerminalDosis-Light,Terminal Dosis Light,"Copyright (c) 2011 by Edgar Tolentino, Pablo Impallari, Igino Marini (impallari.com impallari@gmail.com). All rights reserved."
+Text Me One,normal,400,TextMeOne-Regular.ttf,TextMeOne-Regular,Text Me One,"Copyright (c) 2012, Julia Petretta (julia.petretta@googlemail.com), with Reserved Font Name 'Text Me'"
+Thabit,normal,400,Thabit.ttf,Thabit,Thabit,"Typeface and data (C) 2002-2008, Khaled Hosny (khaledhosny@eglug.org). This font is distributed under the terms of OFL license. Latin glyphs are Copyright (c) IBM Corporation 1990,1991."
+Thabit,italic,400,Thabit-Oblique.ttf,Thabit-Oblique,Thabit-Oblique Oblique,"Typeface and data (C) 2002-2008, Khaled Hosny (khaledhosny@eglug.org). This font is distributed under the terms of OFL license. Latin glyphs are Copyright (c) IBM Corporation 1990,1991."
+Thabit,normal,700,Thabit-Bold.ttf,Thabit-Bold,Thabit-Bold Bold,"Typeface and data (C) 2002-2008, Khaled Hosny (khaledhosny@eglug.org). This font is distributed under the terms of OFL license. Latin glyphs are Copyright (c) IBM Corporation 1990,1991."
+Thabit,italic,700,Thabit-BoldOblique.ttf,Thabit-Bold-Oblique,Thabit-Bold-Oblique Bold Oblique,"Typeface and data (C) 2002-2008, Khaled Hosny (khaledhosny@eglug.org). This font is distributed under the terms of OFL license. Latin glyphs are Copyright (c) IBM Corporation 1990,1991."
+Thasadith,normal,400,Thasadith-Regular.ttf,Thasadith-Regular,Thasadith Regular,Copyright 2018 The Thasadith Project Authors (https://github.com/cadsondemak/Thasadith)
+Thasadith,italic,400,Thasadith-Italic.ttf,Thasadith-Italic,Thasadith Italic,Copyright 2018 The Thasadith Project Authors (https://github.com/cadsondemak/Thasadith)
+Thasadith,normal,700,Thasadith-Bold.ttf,Thasadith-Bold,Thasadith Bold,Copyright 2018 The Thasadith Project Authors (https://github.com/cadsondemak/Thasadith)
+Thasadith,italic,700,Thasadith-BoldItalic.ttf,Thasadith-BoldItalic,Thasadith Bold Italic,Copyright 2018 The Thasadith Project Authors (https://github.com/cadsondemak/Thasadith)
+The Girl Next Door,normal,400,TheGirlNextDoor.ttf,TheGirlNextDoor,The Girl Next Door,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Tienne,normal,400,Tienne-Regular.ttf,Tienne-Regular,Tienne Regular,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names \'Tienne\'"
+Tienne,normal,700,Tienne-Bold.ttf,Tienne-Bold,Tienne Bold,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names \'Tienne\'"
+Tienne,normal,900,Tienne-Black.ttf,Tienne-Black,Tienne Black,"Copyright (c) 2011, Vernon Adams (vern@newtypography.co.uk) with Reserved Font Names \'Tienne\'"
+Tillana,normal,400,Tillana-Regular.ttf,Tillana-Regular,Tillana Regular,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Tillana,normal,500,Tillana-Medium.ttf,Tillana-Medium,Tillana Medium,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Tillana,normal,600,Tillana-SemiBold.ttf,Tillana-SemiBold,Tillana SemiBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Tillana,normal,700,Tillana-Bold.ttf,Tillana-Bold,Tillana Bold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Tillana,normal,800,Tillana-ExtraBold.ttf,Tillana-ExtraBold,Tillana ExtraBold,Copyright (c) 2014 Indian Type Foundry (info@indiantypefoundry.com)
+Timmana,normal,400,Timmana-Regular.ttf,Timmana,Timmana,"Copyright (c) 2012 Andhrapradesh Society for Knowledge Networks (fonts.siliconandhra.org). Copyright (c) 2011, Sergiy Tkachenko (www.4thfebruary.com.ua info@4thfebruary.com.ua), with Reserved Font Names 'Sansus', 'Webissimo'."
+Titan One,normal,400,TitanOne-Regular.ttf,TitanOne,Titan One,"Copyright (c) 2011 Rodrigo Fuenzalida (hello@rfuenzalida.com), with Reserved Font Name \Titan One\"
+Titillium Web,normal,200,TitilliumWeb-ExtraLight.ttf,TitilliumWeb-ExtraLight,Titillium Web ExtraLight,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,italic,200,TitilliumWeb-ExtraLightItalic.ttf,TitilliumWeb-ExtraLightItalic,Titillium Web ExtraLight Italic,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,normal,300,TitilliumWeb-Light.ttf,TitilliumWeb-Light,Titillium Web Light,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,italic,300,TitilliumWeb-LightItalic.ttf,TitilliumWeb-LightItalic,Titillium Web Light Italic,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,normal,400,TitilliumWeb-Regular.ttf,TitilliumWeb-Regular,Titillium Web Regular,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,italic,400,TitilliumWeb-Italic.ttf,TitilliumWeb-Italic,Titillium Web Italic,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,normal,600,TitilliumWeb-SemiBold.ttf,TitilliumWeb-SemiBold,Titillium Web SemiBold,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,italic,600,TitilliumWeb-SemiBoldItalic.ttf,TitilliumWeb-SemiBoldItalic,Titillium Web SemiBold Italic,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,normal,700,TitilliumWeb-Bold.ttf,TitilliumWeb-Bold,Titillium Web Bold,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,italic,700,TitilliumWeb-BoldItalic.ttf,TitilliumWeb-BoldItalic,Titillium Web Bold Italic,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Titillium Web,normal,900,TitilliumWeb-Black.ttf,TitilliumWeb-Black,Titillium Web Black,Copyright (c) 2009-2011 by Accademia di Belle Arti di Urbino and students of MA course of Visual design. Some rights reserved.
+Tomorrow,normal,100,Tomorrow-Thin.ttf,Tomorrow-Thin,Tomorrow Thin,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,100,Tomorrow-ThinItalic.ttf,Tomorrow-ThinItalic,Tomorrow Thin Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,200,Tomorrow-ExtraLight.ttf,Tomorrow-ExtraLight,Tomorrow ExtraLight,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,200,Tomorrow-ExtraLightItalic.ttf,Tomorrow-ExtraLightItalic,Tomorrow ExtraLight Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,300,Tomorrow-Light.ttf,Tomorrow-Light,Tomorrow Light,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,300,Tomorrow-LightItalic.ttf,Tomorrow-LightItalic,Tomorrow Light Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,400,Tomorrow-Regular.ttf,Tomorrow-Regular,Tomorrow Regular,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,400,Tomorrow-Italic.ttf,Tomorrow-Italic,Tomorrow Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,500,Tomorrow-Medium.ttf,Tomorrow-Medium,Tomorrow Medium,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,500,Tomorrow-MediumItalic.ttf,Tomorrow-MediumItalic,Tomorrow Medium Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,600,Tomorrow-SemiBold.ttf,Tomorrow-SemiBold,Tomorrow SemiBold,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,600,Tomorrow-SemiBoldItalic.ttf,Tomorrow-SemiBoldItalic,Tomorrow SemiBold Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,700,Tomorrow-Bold.ttf,Tomorrow-Bold,Tomorrow Bold,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,700,Tomorrow-BoldItalic.ttf,Tomorrow-BoldItalic,Tomorrow Bold Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,800,Tomorrow-ExtraBold.ttf,Tomorrow-ExtraBold,Tomorrow ExtraBold,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,800,Tomorrow-ExtraBoldItalic.ttf,Tomorrow-ExtraBoldItalic,Tomorrow ExtraBold Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,normal,900,Tomorrow-Black.ttf,Tomorrow-Black,Tomorrow Black,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Tomorrow,italic,900,Tomorrow-BlackItalic.ttf,Tomorrow-BlackItalic,Tomorrow Black Italic,Copyright 2019 The Tomorrow Project Authors (https://github.com/MonicaRizzolli/Tomorrow)
+Trade Winds,normal,400,TradeWinds-Regular.ttf,TradeWinds,Trade Winds,"Copyright (c) 2011 by Font Diner, Inc DBA Sideshow (diner@fontdiner.com) with Reserved Font Name \Trade Winds\"
+Trirong,normal,100,Trirong-Thin.ttf,Trirong-Thin,Trirong Thin,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,100,Trirong-ThinItalic.ttf,Trirong-ThinItalic,Trirong Thin Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,200,Trirong-ExtraLight.ttf,Trirong-ExtraLight,Trirong ExtraLight,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,200,Trirong-ExtraLightItalic.ttf,Trirong-ExtraLightItalic,Trirong ExtraLight Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,300,Trirong-Light.ttf,Trirong-Light,Trirong Light,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,300,Trirong-LightItalic.ttf,Trirong-LightItalic,Trirong Light Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,400,Trirong-Regular.ttf,Trirong-Regular,Trirong Regular,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,400,Trirong-Italic.ttf,Trirong-Italic,Trirong Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,500,Trirong-Medium.ttf,Trirong-Medium,Trirong Medium,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,500,Trirong-MediumItalic.ttf,Trirong-MediumItalic,Trirong Medium Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,600,Trirong-SemiBold.ttf,Trirong-SemiBold,Trirong SemiBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,600,Trirong-SemiBoldItalic.ttf,Trirong-SemiBoldItalic,Trirong SemiBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,700,Trirong-Bold.ttf,Trirong-Bold,Trirong Bold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,700,Trirong-BoldItalic.ttf,Trirong-BoldItalic,Trirong Bold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,800,Trirong-ExtraBold.ttf,Trirong-ExtraBold,Trirong ExtraBold,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,800,Trirong-ExtraBoldItalic.ttf,Trirong-ExtraBoldItalic,Trirong ExtraBold Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,normal,900,Trirong-Black.ttf,Trirong-Black,Trirong Black,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trirong,italic,900,Trirong-BlackItalic.ttf,Trirong-BlackItalic,Trirong Black Italic,"Copyright (c) 2015, Cadson Demak (info@cadsondemak.com)"
+Trocchi,normal,400,Trocchi-Regular.ttf,Trocchi-Regular,Trocchi Regular,Copyright 2012 The Trocchi Project Authors (vern@newtypography.co.uk)
+Trochut,normal,400,Trochut-Regular.ttf,Trochut,Trochut,"Copyright (c) 2011, Andreu Balius (www.andreubalius.com|mail@andreubalius.com), with Reserved Font Name Trochut"
+Trochut,italic,400,Trochut-Italic.ttf,Trochut-Italic,Trochut Italic,"Copyright (c) 2011, Andreu Balius (www.andreubalius.com|mail@andreubalius.com), with Reserved Font Name Trochut"
+Trochut,normal,700,Trochut-Bold.ttf,Trochut-Bold,Trochut Bold,"Copyright (c) 2011, Andreu Balius (www.andreubalius.com|mail@andreubalius.com), with Reserved Font Name Trochut"
+Trykker,normal,400,Trykker-Regular.ttf,Trykker-Regular,Trykker Regular,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name \Trykker\."
+Tuffy,normal,400,Tuffy-Regular.ttf,Tuffy-Regular,Tuffy Regular,"Copyright (c) 2011, Thatcher Ulrich (http://tulrich.com tu@tulrich.com), Karoly Barta (brtkr@freemail.hu), Michael Everson (http://www.evertype.com everson@evertype.com), with Reserved Font Name \Tuffy\"
+Tuffy,italic,400,Tuffy-Italic.ttf,Tuffy-Italic,Tuffy Italic,"Copyright (c) 2011, Thatcher Ulrich (http://tulrich.com tu@tulrich.com), Karoly Barta (brtkr@freemail.hu), Michael Everson (http://www.evertype.com everson@evertype.com), with Reserved Font Name \Tuffy\"
+Tuffy,normal,700,Tuffy-Bold.ttf,Tuffy-Bold,Tuffy Bold,"Copyright (c) 2011, Thatcher Ulrich (http://tulrich.com tu@tulrich.com), Karoly Barta (brtkr@freemail.hu), Michael Everson (http://www.evertype.com everson@evertype.com), with Reserved Font Name \Tuffy\"
+Tuffy,italic,700,Tuffy-BoldItalic.ttf,Tuffy-BoldItalic,Tuffy Bold Italic,"Copyright (c) 2011, Thatcher Ulrich (http://tulrich.com tu@tulrich.com), Karoly Barta (brtkr@freemail.hu), Michael Everson (http://www.evertype.com everson@evertype.com), with Reserved Font Name \Tuffy\"
+Tulpen One,normal,400,TulpenOne-Regular.ttf,TulpenOne-Regular,Tulpen One,"Copyright (c) 2011, Naima Ben Ayed (naima.benayed@gmail.com), with Reserved Font Names \Tulpen\ and \Tulpen One\."
+Turret Road,normal,200,TurretRoad-ExtraLight.ttf,TurretRoad-ExtraLight,Turret Road ExtraLight,Copyright 2018 The Turret Road Project Authors (https://github.com/noponies/turret-road)
+Turret Road,normal,300,TurretRoad-Light.ttf,TurretRoad-Light,Turret Road Light,Copyright 2018 The Turret Road Project Authors (https://github.com/noponies/turret-road)
+Turret Road,normal,400,TurretRoad-Regular.ttf,TurretRoad-Regular,Turret Road Regular,Copyright 2018 The Turret Road Project Authors (https://github.com/noponies/turret-road)
+Turret Road,normal,500,TurretRoad-Medium.ttf,TurretRoad-Medium,Turret Road Medium,Copyright 2018 The Turret Road Project Authors (https://github.com/noponies/turret-road)
+Turret Road,normal,700,TurretRoad-Bold.ttf,TurretRoad-Bold,Turret Road Bold,Copyright 2018 The Turret Road Project Authors (https://github.com/noponies/turret-road)
+Turret Road,normal,800,TurretRoad-ExtraBold.ttf,TurretRoad-ExtraBold,Turret Road ExtraBold,Copyright 2018 The Turret Road Project Authors (https://github.com/noponies/turret-road)
+Uchen,normal,400,Uchen-Regular.ttf,Uchen-Regular,Uchen Regular,Font designed by Christopher J. Fynn. Copyright © 2010 by Dzongkha Development Commission.
+Uncial Antiqua,normal,400,UncialAntiqua-Regular.ttf,UncialAntiqua-Regular,Uncial Antiqua,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Uncial Antiqua\"
+Underdog,normal,400,Underdog-Regular.ttf,Underdog-Regular,Underdog,"Copyright (c) 2012, Sergey Steblina (sergey@steblina.com), Jovanny Lemonad (lemonad@jovanny.ru), with Reserved Font Name 'Underdog'"
+Unica One,normal,400,UnicaOne-Regular.ttf,UnicaOne-Regular,Unica One,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Unica'"
+UnifrakturCook,normal,700,UnifrakturCook-Bold.ttf,UnifrakturCook-Bold,UnifrakturCook,"Copyright (c) 2010 j. 'mach' wust (j.mach.wust@gmail.com) with Reserved Font Name UnifrakturCook. Copyright (c) 2009 Peter Wiegel (wiegel@peter-wiegel.de). This Font Software is licensed under the SIL Open Font License, Version 1.1."
+UnifrakturMaguntia,normal,400,UnifrakturMaguntia-Book.ttf,UnifrakturMaguntia,UnifrakturMaguntia,"Copyright (c) 2010 j. 'mach' wust (j.mach.wust@gmail.com) with Reserved Font Name UnifrakturMaguntia. Copyright (c) 2009 Peter Wiegel (wiegel@peter-wiegel.de). This Font Software is licensed under the SIL Open Font License, Version 1.1."
+Unlock,normal,400,Unlock-Regular.ttf,Unlock-Regular,Unlock Regular,"Copyright (c) 2011, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name \Unlock\"
+Unna,normal,400,Unna-Regular.ttf,Unna-Regular,Unna Regular,Copyright 2016 The Unna Project Authors (omnibus.type@gmail.com)
+Unna,italic,400,Unna-Italic.ttf,Unna-Italic,Unna Italic,Copyright 2016 The Unna Project Authors (omnibus.type@gmail.com)
+Unna,normal,700,Unna-Bold.ttf,Unna-Bold,Unna Bold,Copyright 2016 The Unna Project Authors (omnibus.type@gmail.com)
+Unna,italic,700,Unna-BoldItalic.ttf,Unna-BoldItalic,Unna Bold Italic,Copyright 2016 The Unna Project Authors (omnibus.type@gmail.com)
+Vampiro One,normal,400,VampiroOne-Regular.ttf,VampiroOne-Regular,Vampiro One,"Copyright (c) 2012, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Name 'Vampiro'."
+Varela,normal,400,Varela-Regular.ttf,Varela,Varela,Copyright (c) 2011 by Admix Designs (joe@admixdesigns.com). All rights reserved.
+Varela Round,normal,400,VarelaRound-Regular.ttf,VarelaRound-Regular,Varela Round Regular,"Copyright 2011-2016 The Varela Round Project Authors (https://github.com/alefalefalef/Varela-Round-Hebrew/), with Reserved Font Names \'Varela\' and Varela Round."
+Varta,normal,300,Varta-Light.ttf,Varta-Light,Varta Light,"Copyright (c) 2014-2015, Sorkin Type Co (sorkintype.com | sorkintype@gmail.com)"
+Varta,normal,400,Varta-Regular.ttf,Varta-Regular,Varta Regular,"Copyright (c) 2014-2015, Sorkin Type Co (sorkintype.com | sorkintype@gmail.com)"
+Varta,normal,600,Varta-SemiBold.ttf,VartaSemiBold,Varta SemiBold,"Copyright (c) 2014-2015, Sorkin Type Co (sorkintype.com | sorkintype@gmail.com)"
+Varta,normal,700,Varta-Bold.ttf,Varta-Bold,Varta Bold,"Copyright (c) 2014-2015, Sorkin Type Co (sorkintype.com | sorkintype@gmail.com)"
+Vast Shadow,normal,400,VastShadow-Regular.ttf,VastShadow-Regular,Vast Shadow Regular,"Copyright (c) 2010 by Sorkin Type Co (eben@eyebytes.com) with Reserved Font Name Vast and Vast Shadow. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: http://scripts.sil.org/OFL"
+Vesper Libre,normal,400,VesperLibre-Regular.ttf,VesperLibre-Regular,Vesper Libre,"Copyright (c) 2007, Robert Keller (www.motaitalic.com)"
+Vesper Libre,normal,500,VesperLibre-Medium.ttf,VesperLibre-Medium,Vesper Libre Medium,"Copyright (c) 2007, Robert Keller (www.motaitalic.com)"
+Vesper Libre,normal,700,VesperLibre-Bold.ttf,VesperLibre-Bold,Vesper Libre Bold,"Copyright (c) 2007, Robert Keller (www.motaitalic.com)"
+Vesper Libre,normal,900,VesperLibre-Heavy.ttf,VesperLibre-Heavy,Vesper Libre Heavy,"Copyright (c) 2007, Robert Keller (www.motaitalic.com)"
+Viaoda Libre,normal,400,ViaodaLibre-Regular.ttf,ViaodaLibre-Regular,Viaoda Libre Regular,Copyright 2020 The Viaodalibre Project Authors (https://github.com/bettergui/ViaodaLibre)
+Vibes,normal,400,Vibes-Regular.ttf,Vibes-Regular,Vibes Regular,Copyright 2019 The Vibes Project Authors (https://github.com/bluemix/vibes-typeface)
+Vibur,normal,400,Vibur-Regular.ttf,Vibur,Vibur,"Copyright (c) 2010, Johan Kallas (johan.kallas@gmail.com). All rights reserved. Licenced under SIL OFL v1.1"
+Vidaloka,normal,400,Vidaloka-Regular.ttf,Vidaloka-Regular,Vidaloka,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Vidaloka\."
+Viga,normal,400,Viga-Regular.ttf,Viga-Regular,Viga-Regular,"Copyright (c) 2011 Fontstage (info@fontstage.com), with Reserved Font Name \Viga\"
+Voces,normal,400,Voces-Regular.ttf,Voces-Regular,Voces Regular,"Copyright 2012 The Voces Project Authors (https://github.com/googlefonts/VocesFont), with Reserved Font Names \Voces\, \Voceso Pro\, \Voces UGR\"
+Volkhov,normal,400,Volkhov-Regular.ttf,Volkhov-Regular,Volkhov Regular,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Volkhov\ and \Volkhov Regular\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Volkhov,italic,400,Volkhov-Italic.ttf,Volkhov-Italic,Volkhov Italic,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Volkhov\ and \Volkhov Italic\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Volkhov,normal,700,Volkhov-Bold.ttf,Volkhov-Bold,Volkhov Bold,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Volkhov\ and \Volkhov Bold\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Volkhov,italic,700,Volkhov-BoldItalic.ttf,Volkhov-BoldItalic,Volkhov Bold Italic,"Copyright (c) 2011, Cyreal (www.cyreal.org a@cyreal.org) with Reserved Font Name \Volkhov\ and \Volkhov Bold Italic\. This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is available with a FAQ at: http://scripts.sil.org/OFL"
+Vollkorn,normal,400,Vollkorn[wght].ttf,Vollkorn-Regular,Vollkorn Regular,Copyright 2018 The Vollkorn Project Authors (https://github.com/FAlthausen/Vollkorn-Typeface)
+Vollkorn,italic,400,Vollkorn-Italic[wght].ttf,Vollkorn-Italic,Vollkorn Italic,Copyright 2018 The Vollkorn Project Authors (https://github.com/FAlthausen/Vollkorn-Typeface)
+Vollkorn SC,normal,400,VollkornSC-Regular.ttf,VollkornSC-Regular,Vollkorn SC Regular,Copyright 2017 The Vollkorn Project Authors (https://github.com/FAlthausen/Vollkorn-Typeface)
+Vollkorn SC,normal,600,VollkornSC-SemiBold.ttf,VollkornSC-SemiBold,Vollkorn SC SemiBold,Copyright 2017 The Vollkorn Project Authors (https://github.com/FAlthausen/Vollkorn-Typeface)
+Vollkorn SC,normal,700,VollkornSC-Bold.ttf,VollkornSC-Bold,Vollkorn SC Bold,Copyright 2017 The Vollkorn Project Authors (https://github.com/FAlthausen/Vollkorn-Typeface)
+Vollkorn SC,normal,900,VollkornSC-Black.ttf,VollkornSC-Black,Vollkorn SC Black,Copyright 2017 The Vollkorn Project Authors (https://github.com/FAlthausen/Vollkorn-Typeface)
+Voltaire,normal,400,Voltaire-Regular.ttf,Voltaire,Voltaire,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com) with Reserved Font Names \Voltaire\ and \Voltaire One\."
+VT323,normal,400,VT323-Regular.ttf,VT323-Regular,VT323 Regular,"Copyright 2011, The VT323 Project Authors (peter.hull@oikoi.com)"
+Waiting for the Sunrise,normal,400,WaitingfortheSunrise.ttf,WaitingfortheSunrise,Waiting for the Sunrise,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Wallpoet,normal,400,Wallpoet-Regular.ttf,Wallpoet,Wallpoet,Copyright (c) 2011 by Lars Berggren (punktlars@gmail.com). All rights reserved.
+Warnes,normal,400,Warnes-Regular.ttf,Warnes-Regular,Warnes,"Copyright (c) 2012, Eduardo Tunni (http://www.tipo.net.ar edu@tipo.net.ar), with Reserved Font Name 'Warnes'"
+Wellfleet,normal,400,Wellfleet-Regular.ttf,Wellfleet-Regular,Wellfleet,"Copyright (c) 2011, Sorkin Type Co (www.sorkintype.com eben@eyebytes.com), with Reserved Font Name Wellfleet"
+Wendy One,normal,400,WendyOne-Regular.ttf,WendyOne-Regular,Wendy One,"Copyright (c) 2012, Alejandro Inler (alejandroinler@gmail.com), with Reserved Font Name 'Wendy'"
+Wire One,normal,400,WireOne.ttf,WireOne,Wire One,"Copyright (c) 2011, Cyreal Type Foundry (a@cyreal.org), with Reserved Font Name 'Wire'"
+Work Sans,normal,400,WorkSans[wght].ttf,WorkSans-Regular,Work Sans Regular,Copyright 2019 The Work Sans Project Authors (https://github.com/weiweihuanghuang/Work-Sans)
+Work Sans,italic,400,WorkSans-Italic[wght].ttf,WorkSans-Italic,Work Sans Italic,Copyright 2019 The Work Sans Project Authors (https://github.com/weiweihuanghuang/Work-Sans)
+Yaldevi Colombo,normal,200,YaldeviColombo-ExtraLight.ttf,YaldeviColombo-ExtraLight,Yaldevi Colombo ExtraLight,Copyright (c) 2015-2016 Mooniak (hello@mooniak.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar)
+Yaldevi Colombo,normal,300,YaldeviColombo-Light.ttf,YaldeviColombo-Light,Yaldevi Colombo Light,Copyright (c) 2015-2016 Mooniak (hello@mooniak.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar)
+Yaldevi Colombo,normal,400,YaldeviColombo-Regular.ttf,YaldeviColombo-Regular,Yaldevi Colombo Regular,Copyright (c) 2015-2016 Mooniak (hello@mooniak.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar)
+Yaldevi Colombo,normal,500,YaldeviColombo-Medium.ttf,YaldeviColombo-Medium,Yaldevi Colombo Medium,Copyright (c) 2015-2016 Mooniak (hello@mooniak.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar)
+Yaldevi Colombo,normal,600,YaldeviColombo-SemiBold.ttf,YaldeviColombo-SemiBold,Yaldevi Colombo SemiBold,Copyright (c) 2015-2016 Mooniak (hello@mooniak.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar)
+Yaldevi Colombo,normal,700,YaldeviColombo-Bold.ttf,YaldeviColombo-Bold,Yaldevi Colombo Bold,Copyright (c) 2015-2016 Mooniak (hello@mooniak.com) Copyright (c) 2015 Sol Matas (sol@sonnenshine.com.ar)
+Yanone Kaffeesatz,normal,400,YanoneKaffeesatz[wght].ttf,YanoneKaffeesatz-ExtraLight,Yanone Kaffeesatz ExtraLight,Copyright 2010 The Yanone Kaffeesatz Project Authors (https://github.com/alexeiva/yanone-kaffeesatz)
+Yantramanav,normal,100,Yantramanav-Thin.ttf,Yantramanav-Thin,Yantramanav Thin,"Copyright 2014, Erin McLaughlin (hello@erinmclaughlin.com). Copyright 2010, Google Inc. All Rights Reserved."
+Yantramanav,normal,300,Yantramanav-Light.ttf,Yantramanav-Light,Yantramanav Light,"Copyright 2014, Erin McLaughlin (hello@erinmclaughlin.com). Copyright 2010, Google Inc. All Rights Reserved."
+Yantramanav,normal,400,Yantramanav-Regular.ttf,Yantramanav-Regular,Yantramanav Regular,"Copyright 2014, Erin McLaughlin (hello@erinmclaughlin.com). Copyright 2010, Google Inc. All Rights Reserved."
+Yantramanav,normal,500,Yantramanav-Medium.ttf,Yantramanav-Medium,Yantramanav Medium,"Copyright 2014, Erin McLaughlin (hello@erinmclaughlin.com). Copyright 2010, Google Inc. All Rights Reserved."
+Yantramanav,normal,700,Yantramanav-Bold.ttf,Yantramanav-Bold,Yantramanav Bold,"Copyright 2014, Erin McLaughlin (hello@erinmclaughlin.com). Copyright 2010, Google Inc. All Rights Reserved."
+Yantramanav,normal,900,Yantramanav-Black.ttf,Yantramanav-Black,Yantramanav Black,"Copyright 2014, Erin McLaughlin (hello@erinmclaughlin.com). Copyright 2010, Google Inc. All Rights Reserved."
+Yatra One,normal,400,YatraOne-Regular.ttf,YatraOne-Regular,Yatra One Regular,Copyright 2014 The Yatra Project Authors.
+Yeon Sung,normal,400,YeonSung-Regular.ttf,YeonSung-Regular,Yeon Sung Regular,Copyright 2018 The Yeon Sung Project Authors
+Yeseva One,normal,400,YesevaOne-Regular.ttf,YesevaOne-Regular,Yeseva One Regular,"Copyright 2012 The Yeseva One Project Authors (lemonad@jovanny.ru), with Reserved Font Name \Yeseva\."
+Yesteryear,normal,400,Yesteryear-Regular.ttf,Yesteryear-Regular,Yesteryear,"Copyright (c) 2011 by Brian J. Bonislawsky DBA Astigmatic (AOETI) (astigma@astigmatic.com), with Reserved Font Name \Yesteryear\"
+Yinmar,normal,400,Yinmar-Regular.ttf,Yinmar-Regular,Yinmar,Copyright 2014 Google Inc. All Rights Reserved.
+Yrsa,normal,300,Yrsa-Light.ttf,Yrsa-Light,Yrsa Light,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Yrsa,normal,400,Yrsa-Regular.ttf,Yrsa-Regular,Yrsa Regular,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Yrsa,normal,500,Yrsa-Medium.ttf,Yrsa-Medium,Yrsa Medium,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Yrsa,normal,600,Yrsa-SemiBold.ttf,Yrsa-SemiBold,Yrsa SemiBold,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+Yrsa,normal,700,Yrsa-Bold.ttf,Yrsa-Bold,Yrsa Bold,Copyright (c) 2015 by Rosetta Type Foundry s.r.o. (info@rosettatype.com).
+ZCOOL KuaiLe,normal,400,ZCOOLKuaiLe-Regular.ttf,ZCOOLKuaiLe-Regular,ZCOOL KuaiLe Regular,Copyright 2018 The ZCOOL KuaiLe Project Authors (https://www.github.com/googlefonts/zcool-kuaile)
+ZCOOL QingKe HuangYou,normal,400,ZCOOLQingKeHuangYou-Regular.ttf,ZCOOLQingKeHuangYou-Regular,ZCOOL QingKe HuangYou Regular,Copyright 2018 The ZCOOL QingKe HuangYou Project Authors (https://www.github.com/googlefonts/zcool-qingke-huangyou)
+ZCOOL XiaoWei,normal,400,ZCOOLXiaoWei-Regular.ttf,ZCOOLXiaoWei-Regular,ZCOOL XiaoWei Regular,Copyright 2018 The ZCOOL XiaoWei Project Authors (https://www.github.com/googlefonts/xiaowei)
+Zeyada,normal,400,Zeyada.ttf,Zeyada,Zeyada,"Copyright (c) 2010, Kimberly Geswein (kimberlygeswein.com kimberlygeswein@gmail.com)"
+Zhi Mang Xing,normal,400,ZhiMangXing-Regular.ttf,ZhiMangXing-Regular,Zhi Mang Xing Regular,Copyright 2018 The ZhiMangXing Project Authors (https://github.com/googlefonts/zhimangxing)
+Zilla Slab,normal,300,ZillaSlab-Light.ttf,ZillaSlab-Light,Zilla Slab Light,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,italic,300,ZillaSlab-LightItalic.ttf,ZillaSlab-LightItalic,Zilla Slab Light Italic,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,normal,400,ZillaSlab-Regular.ttf,ZillaSlab-Regular,Zilla Slab,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,italic,400,ZillaSlab-Italic.ttf,ZillaSlab-Italic,Zilla Slab Italic,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,normal,500,ZillaSlab-Medium.ttf,ZillaSlab-Medium,Zilla Slab Medium,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,italic,500,ZillaSlab-MediumItalic.ttf,ZillaSlab-MediumItalic,Zilla Slab Medium Italic,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,normal,600,ZillaSlab-SemiBold.ttf,ZillaSlab-SemiBold,Zilla Slab SemiBold,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,italic,600,ZillaSlab-SemiBoldItalic.ttf,ZillaSlab-SemiBoldItalic,Zilla Slab SemiBold Italic,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,normal,700,ZillaSlab-Bold.ttf,ZillaSlab-Bold,Zilla Slab Bold,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab,italic,700,ZillaSlab-BoldItalic.ttf,ZillaSlab-BoldItalic,Zilla Slab Bold Italic,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab Highlight,normal,400,ZillaSlabHighlight-Regular.ttf,ZillaSlabHighlight-Regular,Zilla Slab Highlight,"Copyright 2017, The Mozilla Foundation"
+Zilla Slab Highlight,normal,700,ZillaSlabHighlight-Bold.ttf,ZillaSlabHighlight-Bold,Zilla Slab Highlight Bold,"Copyright 2017, The Mozilla Foundation"
diff --git a/man/adjust_luminance.Rd b/man/adjust_luminance.Rd
index b05511c46..23ffd9894 100644
--- a/man/adjust_luminance.Rd
+++ b/man/adjust_luminance.Rd
@@ -38,7 +38,7 @@ argument).
 
 \section{Function ID}{
 
-7-18
+7-20
 }
 
 \examples{
@@ -97,7 +97,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cell_borders.Rd b/man/cell_borders.Rd
index 353b50bfc..4b96e38c4 100644
--- a/man/cell_borders.Rd
+++ b/man/cell_borders.Rd
@@ -112,7 +112,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cell_fill.Rd b/man/cell_fill.Rd
index 632bb2e82..4836325f1 100644
--- a/man/cell_fill.Rd
+++ b/man/cell_fill.Rd
@@ -76,7 +76,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cell_text.Rd b/man/cell_text.Rd
index b48fc1d68..f5cce017f 100644
--- a/man/cell_text.Rd
+++ b/man/cell_text.Rd
@@ -36,8 +36,8 @@ or \code{"xx-large"}.}
 \item{v_align}{The vertical alignment of the text in the cell. Options are
 \code{"middle"}, \code{"top"}, or \code{"bottom"}.}
 
-\item{style}{The text style. Can be one of either \code{"center"}, \code{"normal"},
-\code{"italic"}, or \code{"oblique"}.}
+\item{style}{The text style. Can be one of either \code{"normal"}, \code{"italic"}, or
+\code{"oblique"}.}
 
 \item{weight}{The weight of the font. Can be a text-based keyword such as
 \code{"normal"}, \code{"bold"}, \code{"lighter"}, \code{"bolder"}, or, a numeric value between
@@ -124,7 +124,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_body.Rd b/man/cells_body.Rd
index dba7a1252..228c3df4d 100644
--- a/man/cells_body.Rd
+++ b/man/cells_body.Rd
@@ -94,7 +94,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_column_labels.Rd b/man/cells_column_labels.Rd
index d67e7f883..13cc31a49 100644
--- a/man/cells_column_labels.Rd
+++ b/man/cells_column_labels.Rd
@@ -99,7 +99,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_column_spanners.Rd b/man/cells_column_spanners.Rd
index cbe96dae3..a8f07ee76 100644
--- a/man/cells_column_spanners.Rd
+++ b/man/cells_column_spanners.Rd
@@ -91,7 +91,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_grand_summary.Rd b/man/cells_grand_summary.Rd
index b993f403d..4d4c49d59 100644
--- a/man/cells_grand_summary.Rd
+++ b/man/cells_grand_summary.Rd
@@ -108,7 +108,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_row_groups.Rd b/man/cells_row_groups.Rd
index be00e5eeb..9c2598afd 100644
--- a/man/cells_row_groups.Rd
+++ b/man/cells_row_groups.Rd
@@ -103,7 +103,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_stub.Rd b/man/cells_stub.Rd
index 6ec46afd1..459ce09e1 100644
--- a/man/cells_stub.Rd
+++ b/man/cells_stub.Rd
@@ -99,7 +99,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_stubhead.Rd b/man/cells_stubhead.Rd
index 0b02d5dad..f47944736 100644
--- a/man/cells_stubhead.Rd
+++ b/man/cells_stubhead.Rd
@@ -87,7 +87,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_summary.Rd b/man/cells_summary.Rd
index ade57d655..41437175a 100644
--- a/man/cells_summary.Rd
+++ b/man/cells_summary.Rd
@@ -127,7 +127,9 @@ Other Helper Functions:
 \code{\link{cells_stub}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/cells_title.Rd b/man/cells_title.Rd
index 000165b4a..d507cd9a8 100644
--- a/man/cells_title.Rd
+++ b/man/cells_title.Rd
@@ -95,7 +95,9 @@ Other Helper Functions:
 \code{\link{cells_stub}()},
 \code{\link{cells_summary}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/currency.Rd b/man/currency.Rd
index 77a7384b3..ebbe1a0a8 100644
--- a/man/currency.Rd
+++ b/man/currency.Rd
@@ -78,7 +78,9 @@ Other Helper Functions:
 \code{\link{cells_stub}()},
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/default_fonts.Rd b/man/default_fonts.Rd
new file mode 100644
index 000000000..193abd760
--- /dev/null
+++ b/man/default_fonts.Rd
@@ -0,0 +1,81 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/helpers.R
+\name{default_fonts}
+\alias{default_fonts}
+\title{A vector of default fonts for use with \strong{gt} tables}
+\usage{
+default_fonts()
+}
+\value{
+A character vector of font names.
+}
+\description{
+The vector of fonts given by \code{default_fonts()} should be used with a \strong{gt}
+table that is rendered to HTML. We can specify additional fonts to use but
+this default set should be placed after that to act as fallbacks. This is
+useful when specifying \code{font} values in the \code{\link[=cell_text]{cell_text()}} function (itself
+used in the \code{\link[=tab_style]{tab_style()}} function). If using \code{\link[=opt_table_font]{opt_table_font()}} (which also
+has a \code{font} argument) we probably don't need to specify this vector of fonts
+since it is handled by its \code{add} option (which is \code{TRUE} by default).
+}
+\section{Figures}{
+
+\if{html}{\figure{man_default_fonts_1.png}{options: width=100\%}}
+}
+
+\section{Function ID}{
+
+7-19
+}
+
+\examples{
+# Use `exibble` to create a gt table;
+# attempting to modify the fonts used
+# for the `time` column is much safer
+# if `default_fonts()` is appended to
+# the end of the `font` listing in the
+# `cell_text()` call (the "Comic Sansa"
+# and "Menloa" fonts don't exist, but,
+# we'll get the first available font
+# from the `default_fonts()` set)
+tab_1 <-
+  exibble \%>\%
+  dplyr::select(char, time) \%>\%
+  gt() \%>\%
+  tab_style(
+    style = cell_text(
+      font = c(
+        "Comic Sansa", "Menloa",
+        default_fonts()
+      )
+    ),
+    locations = cells_body(columns = vars(time))
+  )
+
+}
+\seealso{
+Other Helper Functions: 
+\code{\link{adjust_luminance}()},
+\code{\link{cell_borders}()},
+\code{\link{cell_fill}()},
+\code{\link{cell_text}()},
+\code{\link{cells_body}()},
+\code{\link{cells_column_labels}()},
+\code{\link{cells_column_spanners}()},
+\code{\link{cells_grand_summary}()},
+\code{\link{cells_row_groups}()},
+\code{\link{cells_stubhead}()},
+\code{\link{cells_stub}()},
+\code{\link{cells_summary}()},
+\code{\link{cells_title}()},
+\code{\link{currency}()},
+\code{\link{escape_latex}()},
+\code{\link{google_font}()},
+\code{\link{gt_latex_dependencies}()},
+\code{\link{html}()},
+\code{\link{md}()},
+\code{\link{pct}()},
+\code{\link{px}()},
+\code{\link{random_id}()}
+}
+\concept{Helper Functions}
diff --git a/man/escape_latex.Rd b/man/escape_latex.Rd
index b933d7fc2..ae8ad6300 100644
--- a/man/escape_latex.Rd
+++ b/man/escape_latex.Rd
@@ -20,7 +20,7 @@ LaTeX tables.
 }
 \section{Function ID}{
 
-7-20
+7-22
 }
 
 \seealso{
@@ -39,6 +39,8 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/figures/man_cols_width_1.png b/man/figures/man_cols_width_1.png
index 99002cef5b316b58b0e85978c5b01e1da2aeff49..759fe24bcde8fbfe19cd4c3ebb3afd4eb7301751 100644
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diff --git a/man/figures/man_default_fonts_1.png b/man/figures/man_default_fonts_1.png
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diff --git a/man/google_font.Rd b/man/google_font.Rd
new file mode 100644
index 000000000..eb293e231
--- /dev/null
+++ b/man/google_font.Rd
@@ -0,0 +1,113 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/helpers.R
+\name{google_font}
+\alias{google_font}
+\title{Helper function for specifying a font from the Google Fonts service}
+\usage{
+google_font(name)
+}
+\arguments{
+\item{name}{The complete name of a font available in Google Fonts.}
+}
+\value{
+An object of class \code{font_css}.
+}
+\description{
+The \code{google_font()} helper function can be used wherever a font name should
+be specified. There are two instances where this helper can be used: the
+\code{name} argument in \code{\link[=opt_table_font]{opt_table_font()}} (for setting a table font) and in that
+of \code{\link[=cell_text]{cell_text()}} (used with \code{\link[=tab_style]{tab_style()}}). To get a helpful listing of fonts
+that work well in tables, use the \code{\link[=info_google_fonts]{info_google_fonts()}} function.
+}
+\section{Figures}{
+
+\if{html}{\figure{man_google_font_1.png}{options: width=100\%}}
+
+\if{html}{\figure{man_google_font_2.png}{options: width=100\%}}
+}
+
+\section{Function ID}{
+
+7-18
+}
+
+\examples{
+if (interactive()) {
+
+# Use `exibble` to create a gt table of
+# eight rows, replace missing values with
+# em dashes; for text in the `time` column,
+# we use the Google font 'IBM Plex Mono'
+# and set up the `default_fonts()` as
+# fallbacks (just in case the webfont is
+# not accessible)
+tab_1 <-
+  exibble \%>\%
+  dplyr::select(char, time) \%>\%
+  gt() \%>\%
+  fmt_missing(columns = everything()) \%>\%
+  tab_style(
+    style = cell_text(
+      font = c(
+        google_font(name = "IBM Plex Mono"),
+        default_fonts()
+      )
+    ),
+    locations = cells_body(columns = vars(time))
+  )
+
+# Use `sp500` to create a small gt table,
+# using `fmt_currency()` to provide a
+# dollar sign for the first row of monetary
+# values; then, set a larger font size for
+# the table and use the 'Merriweather' font
+# using the `google_font()` function (with
+# two font fallbacks: 'Cochin' and the
+# catchall 'Serif' group)
+tab_2 <-
+  sp500 \%>\%
+  dplyr::slice(1:10) \%>\%
+  dplyr::select(-volume, -adj_close) \%>\%
+  gt() \%>\%
+  fmt_currency(
+    columns = 2:5,
+    rows = 1,
+    currency = "USD",
+    use_seps = FALSE
+  ) \%>\%
+  tab_options(table.font.size = px(20)) \%>\%
+  opt_table_font(
+    font = list(
+      google_font(name = "Merriweather"),
+      "Cochin", "Serif"
+    )
+  )
+}
+
+}
+\seealso{
+Other Helper Functions: 
+\code{\link{adjust_luminance}()},
+\code{\link{cell_borders}()},
+\code{\link{cell_fill}()},
+\code{\link{cell_text}()},
+\code{\link{cells_body}()},
+\code{\link{cells_column_labels}()},
+\code{\link{cells_column_spanners}()},
+\code{\link{cells_grand_summary}()},
+\code{\link{cells_row_groups}()},
+\code{\link{cells_stubhead}()},
+\code{\link{cells_stub}()},
+\code{\link{cells_summary}()},
+\code{\link{cells_title}()},
+\code{\link{currency}()},
+\code{\link{default_fonts}()},
+\code{\link{escape_latex}()},
+\code{\link{gt_latex_dependencies}()},
+\code{\link{html}()},
+\code{\link{md}()},
+\code{\link{pct}()},
+\code{\link{px}()},
+\code{\link{random_id}()}
+}
+\concept{Helper Functions}
diff --git a/man/gt_latex_dependencies.Rd b/man/gt_latex_dependencies.Rd
index c492efdcd..a5fde4e7a 100644
--- a/man/gt_latex_dependencies.Rd
+++ b/man/gt_latex_dependencies.Rd
@@ -47,7 +47,7 @@ exibble %>% gt()
 }
 \section{Function ID}{
 
-7-21
+7-23
 }
 
 \seealso{
@@ -66,7 +66,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{html}()},
 \code{\link{md}()},
 \code{\link{pct}()},
diff --git a/man/html.Rd b/man/html.Rd
index 43b5ddda6..a5253e942 100644
--- a/man/html.Rd
+++ b/man/html.Rd
@@ -59,7 +59,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{md}()},
 \code{\link{pct}()},
diff --git a/man/info_currencies.Rd b/man/info_currencies.Rd
index f5cf5ef12..31f77d5c0 100644
--- a/man/info_currencies.Rd
+++ b/man/info_currencies.Rd
@@ -17,9 +17,12 @@ those that begin with that letter in their currency code. The default
 (\code{NULL}) will produce a table with all currencies displayed. This option
 only constrains the information table where \code{type == "code"}.}
 }
+\value{
+An object of class \code{gt_tbl}.
+}
 \description{
-The \code{fmt_currency()} function lets us format numeric values as currencies.
-The table generated by the \code{info_currencies()} function provides a quick
+The \code{\link[=fmt_currency]{fmt_currency()}} function lets us format numeric values as currencies.
+The table generated by the \code{\link[=info_currencies]{info_currencies()}} function provides a quick
 reference to all the available currencies. The currency identifiers are
 provided (name, 3-letter currency code, and 3-digit currency code) along with
 the each currency's exponent value (number of digits of the currency
@@ -60,6 +63,7 @@ tab_2 <- info_currencies(type = "symbol")
 \seealso{
 Other Information Functions: 
 \code{\link{info_date_style}()},
+\code{\link{info_google_fonts}()},
 \code{\link{info_locales}()},
 \code{\link{info_paletteer}()},
 \code{\link{info_time_style}()}
diff --git a/man/info_date_style.Rd b/man/info_date_style.Rd
index 468999fba..de2bd1f62 100644
--- a/man/info_date_style.Rd
+++ b/man/info_date_style.Rd
@@ -6,8 +6,11 @@
 \usage{
 info_date_style()
 }
+\value{
+An object of class \code{gt_tbl}.
+}
 \description{
-The \code{fmt_date()} function lets us format date-based values in a convenient
+The \code{\link[=fmt_date]{fmt_date()}} function lets us format date-based values in a convenient
 manner using preset styles. The table generated by the \code{info_date_style()}
 function provides a quick reference to all 14 styles, with associated number
 codes, the format names, and example outputs using a fixed date
@@ -34,6 +37,7 @@ tab_1 <- info_date_style()
 \seealso{
 Other Information Functions: 
 \code{\link{info_currencies}()},
+\code{\link{info_google_fonts}()},
 \code{\link{info_locales}()},
 \code{\link{info_paletteer}()},
 \code{\link{info_time_style}()}
diff --git a/man/info_google_fonts.Rd b/man/info_google_fonts.Rd
new file mode 100644
index 000000000..11eb74557
--- /dev/null
+++ b/man/info_google_fonts.Rd
@@ -0,0 +1,43 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/info_tables.R
+\name{info_google_fonts}
+\alias{info_google_fonts}
+\title{View a table on recommended Google Fonts}
+\usage{
+info_google_fonts()
+}
+\value{
+An object of class \code{gt_tbl}.
+}
+\description{
+The \code{\link[=google_font]{google_font()}} helper function can be used wherever a font name should
+be specified. There are two instances where this helper can be used: the
+\code{name} argument in \code{\link[=opt_table_font]{opt_table_font()}} (for setting a table font) and in that
+of \code{\link[=cell_text]{cell_text()}} (used with \code{\link[=tab_style]{tab_style()}}). Because there is an overwhelming
+number of fonts available in the \emph{Google Fonts} catalog, the
+\code{info_google_fonts()} provides a table with a set of helpful font
+recommendations. These fonts look great in the different parts of a \strong{gt}
+table. Why? For the most part they are suitable for body text, having large
+counters, large x-height, reasonably low contrast, and open apertures. These
+font features all make for high legibility at smaller sizes.
+}
+\section{Function ID}{
+
+10-6
+}
+
+\examples{
+# Get a table of info on some of the
+# recommended Google Fonts for tables
+tab_1 <- info_google_fonts()
+
+}
+\seealso{
+Other Information Functions: 
+\code{\link{info_currencies}()},
+\code{\link{info_date_style}()},
+\code{\link{info_locales}()},
+\code{\link{info_paletteer}()},
+\code{\link{info_time_style}()}
+}
+\concept{Information Functions}
diff --git a/man/info_locales.Rd b/man/info_locales.Rd
index 4a79da3e2..a40d995e6 100644
--- a/man/info_locales.Rd
+++ b/man/info_locales.Rd
@@ -11,6 +11,9 @@ info_locales(begins_with = NULL)
 those that begin with that letter in their base locale ID. The default
 (\code{NULL}) will produce a table with all locales displayed.}
 }
+\value{
+An object of class \code{gt_tbl}.
+}
 \description{
 Many of the \verb{fmt_*()} functions have a \code{locale} argument that makes
 locale-based formatting easier. The table generated by the \code{info_locales()}
@@ -43,6 +46,7 @@ tab_1 <- info_locales(begins_with = "v")
 Other Information Functions: 
 \code{\link{info_currencies}()},
 \code{\link{info_date_style}()},
+\code{\link{info_google_fonts}()},
 \code{\link{info_paletteer}()},
 \code{\link{info_time_style}()}
 }
diff --git a/man/info_paletteer.Rd b/man/info_paletteer.Rd
index 2835cb5d4..b40fd505b 100644
--- a/man/info_paletteer.Rd
+++ b/man/info_paletteer.Rd
@@ -12,6 +12,9 @@ palettes should be displayed in the information table. If this is
 \code{NULL} (the default) then all of the discrete palettes from all of the
 color packages represented in \strong{paletteer} will be displayed.}
 }
+\value{
+An object of class \code{gt_tbl}.
+}
 \description{
 While the \code{\link[=data_color]{data_color()}} function allows us to flexibly color data cells in
 our \strong{gt} table, the harder part of this process is discovering and
@@ -81,6 +84,7 @@ tab_1 <-
 Other Information Functions: 
 \code{\link{info_currencies}()},
 \code{\link{info_date_style}()},
+\code{\link{info_google_fonts}()},
 \code{\link{info_locales}()},
 \code{\link{info_time_style}()}
 }
diff --git a/man/info_time_style.Rd b/man/info_time_style.Rd
index ec01ac33b..46b61d2d2 100644
--- a/man/info_time_style.Rd
+++ b/man/info_time_style.Rd
@@ -6,8 +6,11 @@
 \usage{
 info_time_style()
 }
+\value{
+An object of class \code{gt_tbl}.
+}
 \description{
-The \code{fmt_time()} function lets us format time-based values in a convenient
+The \code{\link[=fmt_time]{fmt_time()}} function lets us format time-based values in a convenient
 manner using preset styles. The table generated by the \code{info_time_style()}
 function provides a quick reference to all five styles, with associated
 number codes, the format names, and example outputs using a fixed time
@@ -35,6 +38,7 @@ tab_1 <- info_time_style()
 Other Information Functions: 
 \code{\link{info_currencies}()},
 \code{\link{info_date_style}()},
+\code{\link{info_google_fonts}()},
 \code{\link{info_locales}()},
 \code{\link{info_paletteer}()}
 }
diff --git a/man/md.Rd b/man/md.Rd
index cfcf9929e..d37bd69ec 100644
--- a/man/md.Rd
+++ b/man/md.Rd
@@ -58,7 +58,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{pct}()},
diff --git a/man/opt_align_table_header.Rd b/man/opt_align_table_header.Rd
index 80b44a544..afe8aaa3b 100644
--- a/man/opt_align_table_header.Rd
+++ b/man/opt_align_table_header.Rd
@@ -68,8 +68,10 @@ tab_1 <-
 \seealso{
 Other Table Option Functions: 
 \code{\link{opt_all_caps}()},
+\code{\link{opt_css}()},
 \code{\link{opt_footnote_marks}()},
 \code{\link{opt_row_striping}()},
+\code{\link{opt_table_font}()},
 \code{\link{opt_table_lines}()},
 \code{\link{opt_table_outline}()}
 }
diff --git a/man/opt_all_caps.Rd b/man/opt_all_caps.Rd
index be8baca6d..e4ad4e428 100644
--- a/man/opt_all_caps.Rd
+++ b/man/opt_all_caps.Rd
@@ -79,8 +79,10 @@ tab_1 <-
 \seealso{
 Other Table Option Functions: 
 \code{\link{opt_align_table_header}()},
+\code{\link{opt_css}()},
 \code{\link{opt_footnote_marks}()},
 \code{\link{opt_row_striping}()},
+\code{\link{opt_table_font}()},
 \code{\link{opt_table_lines}()},
 \code{\link{opt_table_outline}()}
 }
diff --git a/man/opt_css.Rd b/man/opt_css.Rd
new file mode 100644
index 000000000..9149697a5
--- /dev/null
+++ b/man/opt_css.Rd
@@ -0,0 +1,86 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/opts.R
+\name{opt_css}
+\alias{opt_css}
+\title{Option to add custom CSS for the table}
+\usage{
+opt_css(data, css, add = TRUE, allow_duplicates = FALSE)
+}
+\arguments{
+\item{data}{A table object that is created using the \code{\link[=gt]{gt()}} function.}
+
+\item{css}{The CSS to include as part of the rendered table's \verb{<style>}
+element.}
+
+\item{add}{If \code{TRUE}, the default, the CSS is added to any already-defined
+CSS (typically from previous calls of \code{\link[=opt_table_font]{opt_table_font()}}, \code{opt_css()}, or,
+directly setting CSS the \code{table.additional_css} value in \code{\link[=tab_options]{tab_options()}}).
+If this is set to \code{FALSE}, the CSS provided here will replace any
+previously-stored CSS.}
+
+\item{allow_duplicates}{When this is \code{FALSE} (the default), the CSS provided
+here won't be added (provided that \code{add = TRUE}) if it is seen in the
+already-defined CSS.}
+}
+\value{
+An object of class \code{gt_tbl}.
+}
+\description{
+The \code{opt_css()} function makes it possible to add CSS to a \strong{gt} table. This
+CSS will be added after the compiled CSS that \strong{gt} generates automatically
+when the object is transformed to an HTML output table. You can supply \code{css}
+as a vector of lines or as a single string.
+}
+\section{Figures}{
+
+\if{html}{\figure{man_opt_css_1.png}{options: width=100\%}}
+}
+
+\section{Function ID}{
+
+9-8
+}
+
+\examples{
+# Use `exibble` to create a gt table and
+# format the data in both columns; with
+# `opt_css()` insert CSS rulesets as
+# as string and be sure to set the table
+# ID explicitly (here as "one")
+tab_1 <-
+  exibble \%>\%
+  dplyr::select(num, currency) \%>\%
+  gt(id = "one") \%>\%
+  fmt_currency(
+    columns = vars(currency),
+    currency = "HKD"
+  ) \%>\%
+  fmt_scientific(
+    columns = vars(num)
+  ) \%>\%
+  opt_css(
+    css = "
+    #one .gt_table {
+      background-color: skyblue;
+    }
+    #one .gt_row {
+      padding: 20px 30px;
+    }
+    #one .gt_col_heading {
+      text-align: center !important;
+    }
+    "
+  )
+
+}
+\seealso{
+Other Table Option Functions: 
+\code{\link{opt_align_table_header}()},
+\code{\link{opt_all_caps}()},
+\code{\link{opt_footnote_marks}()},
+\code{\link{opt_row_striping}()},
+\code{\link{opt_table_font}()},
+\code{\link{opt_table_lines}()},
+\code{\link{opt_table_outline}()}
+}
+\concept{Table Option Functions}
diff --git a/man/opt_footnote_marks.Rd b/man/opt_footnote_marks.Rd
index d1bfaaf7c..772982821 100644
--- a/man/opt_footnote_marks.Rd
+++ b/man/opt_footnote_marks.Rd
@@ -96,7 +96,9 @@ tab_1 <-
 Other Table Option Functions: 
 \code{\link{opt_align_table_header}()},
 \code{\link{opt_all_caps}()},
+\code{\link{opt_css}()},
 \code{\link{opt_row_striping}()},
+\code{\link{opt_table_font}()},
 \code{\link{opt_table_lines}()},
 \code{\link{opt_table_outline}()}
 }
diff --git a/man/opt_row_striping.Rd b/man/opt_row_striping.Rd
index 070a787ee..edf88dd09 100644
--- a/man/opt_row_striping.Rd
+++ b/man/opt_row_striping.Rd
@@ -67,7 +67,9 @@ tab_1 <-
 Other Table Option Functions: 
 \code{\link{opt_align_table_header}()},
 \code{\link{opt_all_caps}()},
+\code{\link{opt_css}()},
 \code{\link{opt_footnote_marks}()},
+\code{\link{opt_table_font}()},
 \code{\link{opt_table_lines}()},
 \code{\link{opt_table_outline}()}
 }
diff --git a/man/opt_table_font.Rd b/man/opt_table_font.Rd
new file mode 100644
index 000000000..6a2099366
--- /dev/null
+++ b/man/opt_table_font.Rd
@@ -0,0 +1,120 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/opts.R
+\name{opt_table_font}
+\alias{opt_table_font}
+\title{Option to define a custom font for the table}
+\usage{
+opt_table_font(data, font, weight = NULL, style = NULL, add = TRUE)
+}
+\arguments{
+\item{data}{A table object that is created using the \code{\link[=gt]{gt()}} function.}
+
+\item{font}{Either the name of a font available in the user system or a call
+to \code{\link[=google_font]{google_font()}}, which has a large selection of typefaces.}
+
+\item{weight}{The weight of the font. Can be a text-based keyword such as
+\code{"normal"}, \code{"bold"}, \code{"lighter"}, \code{"bolder"}, or, a numeric value between
+\code{1} and \code{1000}, inclusive. Note that only variable fonts may support the
+numeric mapping of weight.}
+
+\item{style}{The text style. Can be one of either \code{"normal"}, \code{"italic"}, or
+\code{"oblique"}.}
+
+\item{add}{Should this font be added to the front of the already-defined
+fonts for the table? By default, this is \code{TRUE} and is recommended since
+the list serves as fallbacks when certain fonts are not available.}
+}
+\value{
+An object of class \code{gt_tbl}.
+}
+\description{
+The \code{opt_table_font()} function makes it possible to define a custom font for
+the entire \strong{gt} table. The standard fallback fonts are still set by default
+but the font defined here will take precedence. You could still have
+different fonts in select locations in the table, and for that you would need
+to use \code{\link[=tab_style]{tab_style()}} in conjunction with the \code{\link[=cell_text]{cell_text()}} helper function.
+
+We have the option to supply either a system font for the \code{font_name}, or, a
+font available at the Google Fonts service by use of the \code{\link[=google_font]{google_font()}}
+helper function.
+}
+\section{Figures}{
+
+\if{html}{\figure{man_opt_table_font_1.png}{options: width=100\%}}
+
+\if{html}{\figure{man_opt_table_font_2.png}{options: width=100\%}}
+}
+
+\section{Function ID}{
+
+9-7
+}
+
+\examples{
+if (interactive()) {
+
+# Use `sp500` to create a small gt table,
+# using `fmt_currency()` to provide a
+# dollar sign for the first row of monetary
+# values; then, set a larger font size for
+# the table and use the 'Merriweather' font
+# (from Google Fonts, via `google_font()`)
+# with two font fallbacks ('Cochin' and the
+# catchall 'Serif' group)
+tab_1 <-
+  sp500 \%>\%
+  dplyr::slice(1:10) \%>\%
+  dplyr::select(-volume, -adj_close) \%>\%
+  gt() \%>\%
+  fmt_currency(
+    columns = 2:5,
+    rows = 1,
+    currency = "USD",
+    use_seps = FALSE
+  ) \%>\%
+  tab_options(table.font.size = px(18)) \%>\%
+  opt_table_font(
+    font = list(
+      google_font(name = "Merriweather"),
+      "Cochin", "Serif"
+    )
+  )
+
+# Use `sza` to create an eleven-row table;
+# within `opt_table_font()`, set up a
+# preferred list of sans-serif fonts that
+# are commonly available in macOS (using
+# part of the `default_fonts()` vector as
+# a fallback)
+# and Windows 10
+tab_2 <-
+  sza \%>\%
+  dplyr::filter(
+    latitude == 20 &
+      month == "jan" &
+      !is.na(sza)
+  ) \%>\%
+  dplyr::select(-latitude, -month) \%>\%
+  gt() \%>\%
+  opt_table_font(
+    font = c(
+      "Helvetica Neue", "Segoe UI",
+      default_fonts()[-c(1:3)]
+    )
+  ) \%>\%
+  opt_all_caps()
+
+}
+
+}
+\seealso{
+Other Table Option Functions: 
+\code{\link{opt_align_table_header}()},
+\code{\link{opt_all_caps}()},
+\code{\link{opt_css}()},
+\code{\link{opt_footnote_marks}()},
+\code{\link{opt_row_striping}()},
+\code{\link{opt_table_lines}()},
+\code{\link{opt_table_outline}()}
+}
+\concept{Table Option Functions}
diff --git a/man/opt_table_lines.Rd b/man/opt_table_lines.Rd
index b698759ed..7f6e6383c 100644
--- a/man/opt_table_lines.Rd
+++ b/man/opt_table_lines.Rd
@@ -70,8 +70,10 @@ tab_1 <-
 Other Table Option Functions: 
 \code{\link{opt_align_table_header}()},
 \code{\link{opt_all_caps}()},
+\code{\link{opt_css}()},
 \code{\link{opt_footnote_marks}()},
 \code{\link{opt_row_striping}()},
+\code{\link{opt_table_font}()},
 \code{\link{opt_table_outline}()}
 }
 \concept{Table Option Functions}
diff --git a/man/opt_table_outline.Rd b/man/opt_table_outline.Rd
index bbce199a1..f6bab4291 100644
--- a/man/opt_table_outline.Rd
+++ b/man/opt_table_outline.Rd
@@ -78,8 +78,10 @@ tab_2 <-
 Other Table Option Functions: 
 \code{\link{opt_align_table_header}()},
 \code{\link{opt_all_caps}()},
+\code{\link{opt_css}()},
 \code{\link{opt_footnote_marks}()},
 \code{\link{opt_row_striping}()},
+\code{\link{opt_table_font}()},
 \code{\link{opt_table_lines}()}
 }
 \concept{Table Option Functions}
diff --git a/man/pct.Rd b/man/pct.Rd
index bc5a1b606..dd73592a6 100644
--- a/man/pct.Rd
+++ b/man/pct.Rd
@@ -63,7 +63,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/px.Rd b/man/px.Rd
index 43b7e6201..afdaed3c8 100644
--- a/man/px.Rd
+++ b/man/px.Rd
@@ -60,7 +60,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/random_id.Rd b/man/random_id.Rd
index 26e552fd3..3bdce0c54 100644
--- a/man/random_id.Rd
+++ b/man/random_id.Rd
@@ -18,7 +18,7 @@ value argument of variable length (the default is 10 letters).
 }
 \section{Function ID}{
 
-7-19
+7-21
 }
 
 \seealso{
@@ -37,7 +37,9 @@ Other Helper Functions:
 \code{\link{cells_summary}()},
 \code{\link{cells_title}()},
 \code{\link{currency}()},
+\code{\link{default_fonts}()},
 \code{\link{escape_latex}()},
+\code{\link{google_font}()},
 \code{\link{gt_latex_dependencies}()},
 \code{\link{html}()},
 \code{\link{md}()},
diff --git a/man/reexports.Rd b/man/reexports.Rd
index 1105bf771..32b0a3890 100644
--- a/man/reexports.Rd
+++ b/man/reexports.Rd
@@ -10,6 +10,7 @@
 \alias{matches}
 \alias{one_of}
 \alias{everything}
+\alias{css}
 \title{Objects exported from other packages}
 \keyword{internal}
 \description{
@@ -19,6 +20,8 @@ below to see their documentation.
 \describe{
   \item{dplyr}{\code{\link[dplyr]{vars}}}
 
+  \item{htmltools}{\code{\link[htmltools]{css}}}
+
   \item{tidyselect}{\code{\link[tidyselect:starts_with]{contains}}, \code{\link[tidyselect:starts_with]{ends_with}}, \code{\link[tidyselect]{everything}}, \code{\link[tidyselect:starts_with]{matches}}, \code{\link[tidyselect]{one_of}}, \code{\link[tidyselect]{starts_with}}}
 }}
 
diff --git a/man/tab_options.Rd b/man/tab_options.Rd
index 76675eb10..c851f65ae 100644
--- a/man/tab_options.Rd
+++ b/man/tab_options.Rd
@@ -16,9 +16,13 @@ tab_options(
   table.margin.left = NULL,
   table.margin.right = NULL,
   table.background.color = NULL,
+  table.additional_css = NULL,
+  table.font.names = NULL,
+  table.font.size = NULL,
+  table.font.weight = NULL,
+  table.font.style = NULL,
   table.font.color = NULL,
   table.font.color.light = NULL,
-  table.font.size = NULL,
   table.border.top.style = NULL,
   table.border.top.width = NULL,
   table.border.top.color = NULL,
@@ -181,11 +185,13 @@ elements: \code{heading}, \code{column_labels}, \code{row_group}, \code{stub}, \
 \code{grand_summary_row}, \code{footnotes}, and \code{source_notes}. A color name or a
 hexadecimal color code should be provided.}
 
-\item{table.font.color, table.font.color.light}{The text color used throughout the table. There are two variants:
-\code{table.font.color} is for text overlaid on lighter background colors, and
-\code{table.font.color.light} is automatically used when text needs to be
-overlaid on darker background colors. A color name or a hexadecimal color
-code should be provided.}
+\item{table.additional_css}{This option can be used to supply an additional
+block of CSS rules to be applied after the automatically generated table
+CSS.}
+
+\item{table.font.names}{The names of the fonts used for the table. This is
+a vector of several font names. If the first font isn't available, then
+the next font is tried (and so on).}
 
 \item{table.font.size, heading.title.font.size, heading.subtitle.font.size, column_labels.font.size, row_group.font.size, stub.font.size, footnotes.font.size, source_notes.font.size}{The font sizes for the parent text element \code{table} and the following child
 elements: \code{heading.title}, \code{heading.subtitle}, \code{column_labels},
@@ -196,18 +202,27 @@ it is assumed that the value is given in units of pixels. The \code{\link[=px]{p
 \code{\link[=pct]{pct()}} helper functions can also be used to pass in numeric values and
 obtain values as pixel or percentage units.}
 
+\item{table.font.weight, heading.title.font.weight, heading.subtitle.font.weight, column_labels.font.weight, row_group.font.weight, stub.font.weight}{The font weights of the table, \code{heading.title}, \code{heading.subtitle},
+\code{column_labels}, \code{row_group}, and \code{stub} text elements. Can be a text-based
+keyword such as \code{"normal"}, \code{"bold"}, \code{"lighter"}, \code{"bolder"}, or, a
+numeric value between \code{1} and \code{1000}, inclusive. Note that only variable
+fonts may support the numeric mapping of weight.}
+
+\item{table.font.style}{The font style for the table. Can be one of either
+\code{"normal"}, \code{"italic"}, or \code{"oblique"}.}
+
+\item{table.font.color, table.font.color.light}{The text color used throughout the table. There are two variants:
+\code{table.font.color} is for text overlaid on lighter background colors, and
+\code{table.font.color.light} is automatically used when text needs to be
+overlaid on darker background colors. A color name or a hexadecimal color
+code should be provided.}
+
 \item{table.border.top.style, table.border.top.width, table.border.top.color, table.border.right.style, table.border.right.width, table.border.right.color, table.border.bottom.style, table.border.bottom.width, table.border.bottom.color, table.border.left.style, table.border.left.width, table.border.left.color}{The style, width, and color properties of the table's absolute top and
 absolute bottom borders.}
 
 \item{heading.align}{Controls the horizontal alignment of the heading title
 and subtitle. We can either use \code{"center"}, \code{"left"}, or \code{"right"}.}
 
-\item{heading.title.font.weight, heading.subtitle.font.weight, column_labels.font.weight, row_group.font.weight, stub.font.weight}{The font weights of the \code{heading.title}, \code{heading.subtitle},
-\code{column_labels}, \code{row_group}, and \code{stub} text elements. Can be a text-based
-keyword such as \code{"normal"}, \code{"bold"}, \code{"lighter"}, \code{"bolder"}, or, a
-numeric value between \code{1} and \code{1000}, inclusive. Note that only variable
-fonts may support the numeric mapping of weight.}
-
 \item{heading.border.bottom.style, heading.border.bottom.width, heading.border.bottom.color}{The style, width, and color properties of the header's bottom border. This
 border shares space with that of the \code{column_labels} location. If the
 \code{width} of this border is larger, then it will be the visible border.}
diff --git a/man/tab_style.Rd b/man/tab_style.Rd
index c5e45189c..654957960 100644
--- a/man/tab_style.Rd
+++ b/man/tab_style.Rd
@@ -11,8 +11,9 @@ tab_style(data, style, locations)
 
 \item{style}{a vector of styles to use. The \code{\link[=cell_text]{cell_text()}}, \code{\link[=cell_fill]{cell_fill()}}, and
 \code{\link[=cell_borders]{cell_borders()}} helper functions can be used here to more easily generate
-valid styles. If using more than one helper function to define styles, all
-calls must be enclosed in a \code{\link[=list]{list()}}.}
+valid styles.  If using more than one helper function to define styles, all
+calls must be enclosed in a \code{\link[=list]{list()}}. Custom CSS declarations can be used
+for HTML output by including a \code{\link[=css]{css()}}-based statement as a list item.}
 
 \item{locations}{the cell or set of cells to be associated with the style.
 Supplying any of the \verb{cells_*()} helper functions is a useful way to target
@@ -52,6 +53,8 @@ bold text (the degree of choice is greater with variable fonts)
 \if{html}{\figure{man_tab_style_1.png}{options: width=100\%}}
 
 \if{html}{\figure{man_tab_style_2.png}{options: width=100\%}}
+
+\if{html}{\figure{man_tab_style_3.png}{options: width=100\%}}
 }
 
 \section{Function ID}{
@@ -116,6 +119,25 @@ tab_2 <-
       rows = open > close)
   )
 
+# Use `exibble` to create a gt table;
+# replace missing values with the
+# `fmt_missing()` function and then
+# add styling to the `char` column
+# with `cell_fill()` and with a
+# CSS style declaration
+tab_3 <-
+  exibble \%>\%
+  dplyr::select(char, fctr) \%>\%
+  gt() \%>\%
+  fmt_missing(everything()) \%>\%
+  tab_style(
+    style = list(
+      cell_fill(color = "lightcyan"),
+      "font-variant: small-caps;"
+    ),
+    locations = cells_body(columns = vars(char))
+  )
+
 }
 \seealso{
 \code{\link[=cell_text]{cell_text()}}, \code{\link[=cell_fill]{cell_fill()}}, and \code{\link[=cell_borders]{cell_borders()}} as helpers for
diff --git a/tests/gt-examples/01-html-script/html-16-table_options_everywhere.R b/tests/gt-examples/01-html-script/html-16-table_options_everywhere.R
index 26c3a7a36..3d0cf61cc 100644
--- a/tests/gt-examples/01-html-script/html-16-table_options_everywhere.R
+++ b/tests/gt-examples/01-html-script/html-16-table_options_everywhere.R
@@ -61,7 +61,7 @@ many_options_tbl <-
   tab_source_note("A source note for the table.") %>%
   tab_options(
     table.font.size = px(14),            # Entire table's font size
-    table.background.color = NULL,       # Entire table's background color
+    table.background.color = "aliceblue",# Entire table's background color
     table.width = px(360),               # Entire table's width
     table.border.top.style = "solid",    # Top line of table - style
     table.border.top.width = px(3),      # Top line of table - width
@@ -86,7 +86,7 @@ many_options_tbl <-
     row_group.border.bottom.color = "orange",    # Bottom line of row group - color
     table_body.border.top.style = "solid",          # Top line of table body - style
     table_body.border.top.width = px(5),            # Top line of table body - width
-    table_body.border.top.color = "indianred",      # Top line of table body - color
+    table_body.border.top.color = "chocolate1",     # Top line of table body - color
     table_body.border.bottom.style = "solid",       # Bottom line of table body - style
     table_body.border.bottom.width = px(5),         # Bottom line of table body - width
     table_body.border.bottom.color = "turquoise",   # Bottom line of table body - color
diff --git a/tests/testthat/helper-gt_attr_expectations.R b/tests/testthat/helper-gt_attr_expectations.R
index e64e3b6b0..b6d6838fe 100644
--- a/tests/testthat/helper-gt_attr_expectations.R
+++ b/tests/testthat/helper-gt_attr_expectations.R
@@ -102,7 +102,7 @@ expect_tab <- function(tab,
 
   dt_options_get(data = tab) %>%
     dim() %>%
-    expect_equal(c(129, 5))
+    expect_equal(c(133, 5))
 
   dt_transforms_get(data = tab) %>%
     length() %>%
diff --git a/tests/testthat/test-info_tables.R b/tests/testthat/test-info_tables.R
index bd9e30af2..485ed722e 100644
--- a/tests/testthat/test-info_tables.R
+++ b/tests/testthat/test-info_tables.R
@@ -33,3 +33,20 @@ test_that("the `info_time_style()` function works correctly", {
       dim(),
     c(5, 3))
 })
+
+test_that("the `info_google_fonts()` function works correctly", {
+
+  # Expect that the `info_google_fonts()` function produces an
+  # information table with certain classes
+  expect_is(
+    info_google_fonts(),
+    c("gt_tbl", "data.frame"))
+
+  # Expect the internal source data frame to be of
+  # specific dimensions
+  expect_equal(
+    info_google_fonts() %>%
+      dt_data_get() %>%
+      dim(),
+    c(37, 4))
+})
diff --git a/tests/testthat/test-opt_functions.R b/tests/testthat/test-opt_functions.R
index fa5a1076f..448e662d9 100644
--- a/tests/testthat/test-opt_functions.R
+++ b/tests/testthat/test-opt_functions.R
@@ -1,5 +1,10 @@
 context("Ensuring that the `opt_*()` functions work properly")
 
+# Helper function to compare a contiguous set of HTML fragments with raw html
+html_fragment_within <- function(raw_html, ...) {
+  grepl(paste0("\\Q", c(...), "\\E", "[\\n\\s]*?", collapse = ""), raw_html, perl = TRUE)
+}
+
 test_that("The `opt_footnote_marks()` function sets the correct options", {
 
   set_marks <- c("*", "+", "~", "<", ">")
@@ -306,3 +311,109 @@ test_that("The `opt_table_outline()` function sets the correct options", {
   tbl %>% dt_options_get_value("table_border_right_width") %>% expect_equal("5px")
   tbl %>% dt_options_get_value("table_border_right_color") %>% expect_equal("#D3D3D3")
 })
+
+test_that("The `opt_table_font()` function sets the correct options", {
+
+  # Prepare a common gt table for all tests
+  tbl <- exibble %>% dplyr::select(char, time) %>% gt()
+
+  # Expect that a desired system font is placed at the
+  # head of the `font-family` font listing
+  tbl %>% opt_table_font(font = "Courier") %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      ".gt_table {", "font-family: Courier, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;", "}"
+    ) %>% expect_true()
+
+  # Expect a replacement of the table's default
+  # `font-family` values when `add = FALSE`
+  tbl %>% opt_table_font(font = "Courier", add = FALSE) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      ".gt_table {", "font-family: Courier;", "}"
+    ) %>% expect_true()
+
+  # Expect that `weight` and `style` options are passed as CSS values
+  tbl %>% opt_table_font(font = "Courier", weight = "bold", style = "italic") %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "font-weight: bold;",
+      "font-style: italic;"
+    ) %>% expect_true()
+
+  # Expect that adding a font from the Google Fonts service
+  # is possible with the `google_font()` function
+  tbl %>% opt_table_font(font = google_font(name = "Dancing Script")) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "@import url(\"https://fonts.googleapis.com/css2?family=Dancing+Script:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      ".gt_table {", "font-family: 'Dancing Script', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;", "}"
+    ) %>% expect_true()
+
+  # Expect that equally valid inputs include wrapping in a list or `c()`
+  expect_equivalent(
+    tbl %>% opt_table_font(font = google_font(name = "Dancing Script")) %>% compile_scss(),
+    tbl %>% opt_table_font(font = list(google_font(name = "Dancing Script"))) %>% compile_scss(),
+    tbl %>% opt_table_font(font = c(google_font(name = "Dancing Script"))) %>% compile_scss()
+  )
+
+  # Expect `google_font()` with system fonts inside of
+  # a list or `c()`
+  tbl %>% opt_table_font(font = list(google_font(name = "Dancing Script"), "serif")) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "@import url(\"https://fonts.googleapis.com/css2?family=Dancing+Script:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      ".gt_table {", "font-family: 'Dancing Script', serif, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;", "}"
+    ) %>% expect_true()
+
+  tbl %>% opt_table_font(font = c(google_font(name = "Dancing Script"), "serif")) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "@import url(\"https://fonts.googleapis.com/css2?family=Dancing+Script:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      ".gt_table {", "font-family: 'Dancing Script', serif, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;", "}"
+    ) %>% expect_true()
+
+  # Expect any combination of vectors and `google_font()` calls inside
+  # of a list or `c()`
+  tbl %>% opt_table_font(font = list("serif", google_font(name = "Dancing Script"), "Courier", google_font(name = "Exo 2"))) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "@import url(\"https://fonts.googleapis.com/css2?family=Dancing+Script:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      "@import url(\"https://fonts.googleapis.com/css2?family=Exo+2:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      ".gt_table {", "font-family: serif, 'Dancing Script', Courier, 'Exo 2', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;", "}"
+    ) %>% expect_true()
+
+  tbl %>% opt_table_font(font = c("serif", google_font(name = "Dancing Script"), "Courier", google_font(name = "Exo 2"))) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "@import url(\"https://fonts.googleapis.com/css2?family=Dancing+Script:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      "@import url(\"https://fonts.googleapis.com/css2?family=Exo+2:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      ".gt_table {", "font-family: serif, 'Dancing Script', Courier, 'Exo 2', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;", "}"
+    ) %>% expect_true()
+
+  # Expect that font names are de-duplicated
+  tbl %>% opt_table_font(font = list(google_font(name = "Dancing Script"), "Courier", "Oxygen", "Courier")) %>%
+    compile_scss() %>% as.character() %>%
+    html_fragment_within(
+      "@import url(\"https://fonts.googleapis.com/css2?family=Dancing+Script:ital,wght@0,100;0,200;0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,100;1,200;1,300;1,400;1,500;1,600;1,700;1,800;1,900&display=swap\");",
+      ".gt_table {",
+      "font-family: 'Dancing Script', Courier, Oxygen, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', 'Droid Sans', Arial, sans-serif;",
+      "}"
+    ) %>% expect_true()
+
+  # Expect that weights given as numbers or strings create the
+  # same outputs (e.g., 500 and "500")
+  expect_equivalent(
+    tbl %>% opt_table_font(font = google_font(name = "Dancing Script"), weight = 500) %>% compile_scss(),
+    tbl %>% opt_table_font(font = google_font(name = "Dancing Script"), weight = "500") %>% compile_scss()
+  )
+
+  # Expect an error if input to `font` is not a character vector
+  # or a list (but no errors otherwise)
+  expect_error(tbl %>% opt_table_font(font = c(TRUE, FALSE)))
+  expect_error(tbl %>% opt_table_font(font = 1:3))
+  expect_error(regexp = NA, tbl %>% opt_table_font(font = c("Courier", "Comic Sans MS")))
+  expect_error(regexp = NA, tbl %>% opt_table_font(font = list("Courier", "Comic Sans MS")))
+  expect_error(regexp = NA, tbl %>% opt_table_font(font = LETTERS))
+})
+
diff --git a/tests/testthat/test-tab_style.R b/tests/testthat/test-tab_style.R
index 3a47d48f8..433701541 100644
--- a/tests/testthat/test-tab_style.R
+++ b/tests/testthat/test-tab_style.R
@@ -430,3 +430,43 @@ test_that("a gt table can store the correct style statements", {
       "data", NA_character_, "hp", "5", "1", NA_character_, "#FFFF00")
     )
 })
+
+test_that("using fonts in `cell_text()` works", {
+
+  # Prepare a small gt table for all tests
+  tbl <- exibble %>% dplyr::select(char, time) %>% gt()
+
+  # Expect that system fonts can be combined with default fonts
+  # and set at a specific location
+  tbl %>%
+    tab_style(
+      style = cell_text(font = c("Comic Sans MS", "Menlo", default_fonts())),
+      locations = cells_body(columns = vars(time), rows = 1)
+    ) %>%
+    as_raw_html() %>%
+    expect_match(
+      "<td style=\"padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; margin: 10px; border-top-style: solid; border-top-width: 1px; border-top-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; overflow-x: hidden; text-align: left; font-family: &#39;Comic Sans MS&#39;, Menlo, -apple-system, BlinkMacSystemFont, &#39;Segoe UI&#39;, Roboto, Oxygen, Ubuntu, Cantarell, &#39;Helvetica Neue&#39;, &#39;Fira Sans&#39;, &#39;Droid Sans&#39;, Arial, sans-serif;\">13:35</td>"
+    )
+
+  # Expect that a Google Fonts and system fonts can be combined
+  # (using a list or `c()`) with default fonts and set at a specific location
+  tbl %>%
+    tab_style(
+      style = cell_text(font = c(google_font(name = "Dancing Script"), default_fonts())),
+      locations = cells_body(columns = vars(time), rows = 1)
+    ) %>%
+    as_raw_html() %>%
+    expect_match(
+      "<td style=\"padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; margin: 10px; border-top-style: solid; border-top-width: 1px; border-top-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; overflow-x: hidden; text-align: left; font-family: &#39;Dancing Script&#39;, -apple-system, BlinkMacSystemFont, &#39;Segoe UI&#39;, Roboto, Oxygen, Ubuntu, Cantarell, &#39;Helvetica Neue&#39;, &#39;Fira Sans&#39;, &#39;Droid Sans&#39;, Arial, sans-serif;\">13:35</td>"
+    )
+
+  tbl %>%
+    tab_style(
+      style = cell_text(font = list(google_font(name = "Dancing Script"), default_fonts())),
+      locations = cells_body(columns = vars(time), rows = 1)
+    ) %>%
+    as_raw_html() %>%
+    expect_match(
+      "<td style=\"padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; margin: 10px; border-top-style: solid; border-top-width: 1px; border-top-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; overflow-x: hidden; text-align: left; font-family: &#39;Dancing Script&#39;, -apple-system, BlinkMacSystemFont, &#39;Segoe UI&#39;, Roboto, Oxygen, Ubuntu, Cantarell, &#39;Helvetica Neue&#39;, &#39;Fira Sans&#39;, &#39;Droid Sans&#39;, Arial, sans-serif;\">13:35</td>"
+    )
+})
diff --git a/tests/testthat/test-util_functions.R b/tests/testthat/test-util_functions.R
index 481e707d5..7eb4ff230 100644
--- a/tests/testthat/test-util_functions.R
+++ b/tests/testthat/test-util_functions.R
@@ -360,7 +360,7 @@ test_that("the `get_css_tbl()` function works correctly", {
 
   css_tbl %>% expect_is(c("tbl_df", "tbl", "data.frame"))
 
-  css_tbl %>% dim() %>% expect_equal(c(226, 4))
+  css_tbl %>% dim() %>% expect_equal(c(228, 4))
 
   css_tbl %>%
     colnames() %>%
@@ -388,7 +388,8 @@ test_that("the `inline_html_styles()` function works correctly", {
         "Roboto, Oxygen, Ubuntu, Cantarell, 'Helvetica Neue', 'Fira Sans', ",
         "'Droid Sans', Arial, sans-serif; display: table; border-collapse: ",
         "collapse; margin-left: auto; margin-right: auto; color: #333333; ",
-        "font-size: 16px; background-color: #FFFFFF; width: auto; ",
+        "font-size: 16px; font-weight: normal; font-style: normal; ",
+        "background-color: #FFFFFF; width: auto; ",
         "border-top-style: solid; border-top-width: 2px; ",
         "border-top-color: #A8A8A8; border-right-style: none; ",
         "border-right-width: 2px; border-right-color: #D3D3D3; ",

From c97cb4c0485f4fa28b9d00a44b2ac6570873cc62 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Wed, 5 Aug 2020 19:13:05 -0400
Subject: [PATCH 26/30] v0.2.2 Release Candidate (#629)

* Update version number

* Delete external.css

* Update gt_styles_default.scss

* Update test-util_functions.R

* Update NEWS.md

* Update gt_styles_default.scss

* Update test-util_functions.R
---
 DESCRIPTION           |  2 +-
 NEWS.md               | 18 ++++++++++++++++--
 inst/css/external.css | 11 -----------
 3 files changed, 17 insertions(+), 14 deletions(-)
 delete mode 100644 inst/css/external.css

diff --git a/DESCRIPTION b/DESCRIPTION
index 59157168f..b3ea380ea 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Type: Package
 Package: gt
-Version: 0.2.1
+Version: 0.2.2
 Title: Easily Create Presentation-Ready Display Tables
 Description: Build display tables from tabular data with an easy-to-use set of
     functions. With its progressive approach, we can construct display tables
diff --git a/NEWS.md b/NEWS.md
index 827c1599e..de24c5d67 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,12 +1,26 @@
-# gt (unreleased)
+# gt 0.2.2
+
+## New features
+
+* The new `opt_table_font()` function makes it possible to define a custom font for the entire **gt** table. The standard fallback fonts are still set by default but the font defined here will take precedence. You could still have different fonts in select locations in the table, and for that you would need to use `tab_style()` in conjunction with the `cell_text()` helper function. The new `google_font()` helper function provides an option for supplying a font available at the Google Fonts service (this is in addition to using system fonts in the `font` argument). Using the `info_google_fonts()` function will provide a table with a set of helpful font recommendations from the *Google Fonts* catalog. The new `default_fonts()` functions provides a helpful vector of system fallback fonts which works well when defining a vector of fonts. (#591)
+
+* The new `opt_css()` function makes allows for the addition of custom CSS to a **gt** table. This CSS will be added after the compiled CSS that **gt** generates automatically when the `gt_tbl` object is transformed to an HTML output table. You can supply `css` as a vector of lines or as a single string. The `css()` function has been re-exported from **htmltools** to make it easier to build CSS style declarations. (Also #591)
+
+* Setting the widths of table columns is now easier and more dependable with `cols_width()`. Widths can be expressed in units of pixels (easily set by use of the `px()` helper function), as percentages (where the `pct()` helper function is useful), or a mixture of the two. The function takes into consideration whether an overall table width has been provided with `tab_options(table.width = ...)`. Providing pixel widths for all columns serves to override any table width defined (yielding columns with the exact widths specified). (#561)
 
 * There are new options for numeric formatting: (1) using significant figures (with `n_sigfig` in `fmt_number`), and (2) the ability to retain/drop trailing decimal marks (with `drop_trailing_dec_mark` in `fmt_number()`, `fmt_percent()`, and `fmt_currency()`). Thank you @drolejoel for the suggestion in #535! (#546).
 
 * The new `scale_values` argument for `fmt_percent()` makes it easy to use values that are already scaled (and just require the percent mark). Thank you @djohn215 for the suggestion in #559. (#565)
 
+* Font weights expressed as numeric values (e.g., `400`, `600`, etc.) in `cell_text()`'s `weight` argument now works properly. (#591)
+
+## Minor improvements and bug fixes
+
+* The `data_color()` function has been rewritten to improve performance (#543). (#576)
+
 * Restore the ability to have row striping in stub cells (with `tab_option()`'s `row.striping.include_stub = TRUE`). Thanks @gergness for creating PR #537, which prompted this final fix. (#564)
 
-# gt 0.2.1
+# gt 0.2.1 (2020-05-26)
 
 * `summary_rows()` and `grand_summary_rows()` no longer incorrectly calculate summary values in cases where rows aren't already sorted by group (#556).
 
diff --git a/inst/css/external.css b/inst/css/external.css
deleted file mode 100644
index a34a2a9de..000000000
--- a/inst/css/external.css
+++ /dev/null
@@ -1,11 +0,0 @@
-.gt_table {
-  background-color: skyblue;
-}
-
-.gt_row {
-  padding: 20px 30px;
-}
-
-.gt_col_heading {
-  text-align: center !important;
-}

From 6a791b5fa4b764f8635854a18770d30a52e179d7 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Tue, 29 Sep 2020 17:01:17 -0400
Subject: [PATCH 27/30] Rewrite of RTF building functions and `as_rtf()` (#638)

* Add file of RTF table-building functions

* Update the `as_rtf()` function

* Modify conditional expression

* Update DESCRIPTION

* Update `context_missing_text()`

* Move `split_body_content()` to `utils_render_common.R`

* Create rtf_tests.R

* Remove unnecessary `:::` calls

* Modify use of `append()` to avoid partial-match arg

* Include correct stmts for returning an empty list()

* Transform select HTML tags to RTF code

* Include correct representation of scientific notn for RTF

* Add correct text processing for RTF

* Add RTF context code for `fmt_missing()`

* Increase widths of certain borders

* Define a plus/minus mark for RTF

* Minimize heights of table rows

* Add repeating header functionality

* Update rtf_tests.R

* Update rtf_tests.R

* Update html-13-adding_footnotes.R

* Ensure that footnote glyphs appear in more locations

* Delete ~$rquality-msrtf_2.rtf

* Use correct binding of stub col to body cols

* Update rtf_tests.R

* Add rendered RTF output

* Incorporate grand summary rows

* Update rtf_tests.R

* Update summary.rtf

* Update utils_render_rtf_redo.R

* Update rtf_tests.R

* wip: Convert Markdown to RTF via commonmark XML

* wip: Implement md text (escaping and unicode), softbreak, linebreak

* Implement md2rtf code, heading, thematic break

* Modify md2rtf strong & emph to use `{ }`

* Implement md2rtf conversion for links

* Implement md2rtf conversion for lists

* Implement md2rtf conversion for thematic break

* Make corrections to 'heading' and 'thematic break'

* Update RTF export code

At this point, RTF escaping is generally not applied (should be done in `rtf_text()`).

* Prevent double escaping RTF where necessary

* Update tests and their outputs

* Perform extra checks for title/subtitle presence

* Ensure that summary row text isn't double escaped

* Update RTF examples

* Modify characters used for missing text (RTF)

* Revert "Modify characters used for missing text (RTF)"

This reverts commit c7471a578f7fec6f23f7c055b86001d64f641204.

* Add rtf_paste0

* Refactor RTF code

First pass of replacing `paste0()` with `rtf_paste0()`.

* Replace RTF output test files

* Improve md2rtf for 'html_inline'

* Make correction to cmark rule for lists

* Make correction to testthat test

* Update testthat tests for md2rtf conversion

* Add more md2rtf testthat tests

* Add the `block_quote` cmark rule

* Update md2rtf testthat tests

* Make several changes based on code review

* Fix remaining issue with footnotes in RTF

* Add to `globalVariables()` vector

* Update rtf_tests.R

* Create exibble.rtf

* Make changes to md2rtf paragraph and block_quote

* Update test-utils.R

* Update md.rtf

* Update test-utils.R

* Add md2rtf translation for code_block

* Update test-utils.R

* Eliminate the return of names in `text`

* Update the `md_rtf()` testing function

* Remove unnecessary RTF control words

* Modify `select()` statement

* Update utils.R

* Update test-utils.R

* Update .rtf output files

* Use `NULL` if table subtitle isn't present

* Delete utils_render_rtf.R

* Slight refactor of rtf_paste0

* Update DESCRIPTION

* Update comment

* Remove uses of `*text_list()`; reprocess examples

* Simplify stmt for obtaining `row_components`

* Refactor method for getting colors and fonts (for the header)

* Simplify `rtf_table()`

* Remove unneeded `rtf_document()` fcn

* Update `fmt_passthrough()` for RTF

* Correct `context_missing_text()`; add test

* Remove unneeded tab stops for list item.

* Make changes based on code review

* Update test-utils.R

* Remove tab stops in block_quote cmark rule

* Update test-utils.R

* Defer implementation of `block_quote`

* Update exibble.rtf

* Update test-utils.R

Co-authored-by: Joe Cheng <joe@rstudio.com>
---
 DESCRIPTION                                   |    3 +-
 R/build_data.R                                |    3 +-
 R/dt_heading.R                                |    5 +-
 R/dt_stubhead.R                               |    2 +-
 R/export.R                                    |   40 +-
 R/format_data.R                               |   35 +
 R/helpers.R                                   |    7 +
 R/utils.R                                     |  248 +
 R/utils_formatters.R                          |  106 +-
 R/utils_render_common.R                       |   15 +
 R/utils_render_footnotes.R                    |   42 +-
 R/utils_render_html.R                         |   44 +-
 R/utils_render_rtf.R                          |  570 ---
 R/utils_render_rtf_redo.R                     | 1200 +++++
 R/zzz.R                                       |    1 +
 .../01-html-script/html-13-adding_footnotes.R |    9 +
 tests/gt-examples/04-rtf/rtf_tests.R          |  508 ++
 tests/gt-examples/rtf_output/airquality.rtf   | 4343 +++++++++++++++++
 tests/gt-examples/rtf_output/cell_styles.rtf  |  147 +
 tests/gt-examples/rtf_output/conditional.rtf  |  283 ++
 tests/gt-examples/rtf_output/exibble.rtf      |  363 ++
 tests/gt-examples/rtf_output/footnotes.rtf    |  227 +
 tests/gt-examples/rtf_output/iris.rtf         | 3675 ++++++++++++++
 tests/gt-examples/rtf_output/many_options.rtf |  331 ++
 tests/gt-examples/rtf_output/md.rtf           |   19 +
 tests/gt-examples/rtf_output/morley.rtf       | 1619 ++++++
 tests/gt-examples/rtf_output/passthrough.rtf  |  363 ++
 tests/gt-examples/rtf_output/pressure.rtf     |  243 +
 tests/gt-examples/rtf_output/sh_caption.rtf   |  203 +
 tests/gt-examples/rtf_output/sleep.rtf        |  347 ++
 tests/gt-examples/rtf_output/sp500.rtf        |  283 ++
 tests/gt-examples/rtf_output/spanner.rtf      |  123 +
 tests/gt-examples/rtf_output/summary.rtf      |  355 ++
 tests/gt-examples/rtf_output/uncert.rtf       |   63 +
 tests/gt-examples/rtf_output/unicode.rtf      |   51 +
 tests/testthat/test-table_parts.R             |    2 +-
 tests/testthat/test-utils.R                   |  149 +
 37 files changed, 15357 insertions(+), 670 deletions(-)
 delete mode 100644 R/utils_render_rtf.R
 create mode 100644 R/utils_render_rtf_redo.R
 create mode 100644 tests/gt-examples/04-rtf/rtf_tests.R
 create mode 100644 tests/gt-examples/rtf_output/airquality.rtf
 create mode 100644 tests/gt-examples/rtf_output/cell_styles.rtf
 create mode 100644 tests/gt-examples/rtf_output/conditional.rtf
 create mode 100644 tests/gt-examples/rtf_output/exibble.rtf
 create mode 100644 tests/gt-examples/rtf_output/footnotes.rtf
 create mode 100644 tests/gt-examples/rtf_output/iris.rtf
 create mode 100644 tests/gt-examples/rtf_output/many_options.rtf
 create mode 100644 tests/gt-examples/rtf_output/md.rtf
 create mode 100644 tests/gt-examples/rtf_output/morley.rtf
 create mode 100644 tests/gt-examples/rtf_output/passthrough.rtf
 create mode 100644 tests/gt-examples/rtf_output/pressure.rtf
 create mode 100644 tests/gt-examples/rtf_output/sh_caption.rtf
 create mode 100644 tests/gt-examples/rtf_output/sleep.rtf
 create mode 100644 tests/gt-examples/rtf_output/sp500.rtf
 create mode 100644 tests/gt-examples/rtf_output/spanner.rtf
 create mode 100644 tests/gt-examples/rtf_output/summary.rtf
 create mode 100644 tests/gt-examples/rtf_output/uncert.rtf
 create mode 100644 tests/gt-examples/rtf_output/unicode.rtf
 create mode 100644 tests/testthat/test-utils.R

diff --git a/DESCRIPTION b/DESCRIPTION
index b3ea380ea..c54c488ef 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -27,6 +27,7 @@ RoxygenNote: 7.1.1
 Depends:
     R (>= 3.2.0)
 Imports: 
+    bitops (>= 1.0.6),
     checkmate (>= 2.0.0),
     commonmark (>= 1.7),
     dplyr (>= 0.8.5),
@@ -109,5 +110,5 @@ Collate:
     'utils_render_footnotes.R'
     'utils_render_html.R'
     'utils_render_latex.R'
-    'utils_render_rtf.R'
+    'utils_render_rtf_redo.R'
     'zzz.R'
diff --git a/R/build_data.R b/R/build_data.R
index 5263bafad..3ef47f2ba 100644
--- a/R/build_data.R
+++ b/R/build_data.R
@@ -4,7 +4,6 @@
 build_data <- function(data, context) {
 
   checkmate::assert_class(data, "gt_tbl")
-
   # Create `body` with rendered values; move
   # input data cells to `body` that didn't have
   # any rendering applied during `render_formats()`;
@@ -58,7 +57,7 @@ build_data <- function(data, context) {
 
   # Add footnote marks to the `summary` cells
   # TODO: `context` is missing in `apply_footnotes_to_summary()`
-  data <- apply_footnotes_to_summary(data = data)
+  data <- apply_footnotes_to_summary(data = data, context = context)
 
   data <- dt_has_built_set(data = data, value = TRUE)
 
diff --git a/R/dt_heading.R b/R/dt_heading.R
index b53a230db..d45d7360a 100644
--- a/R/dt_heading.R
+++ b/R/dt_heading.R
@@ -42,13 +42,12 @@ dt_heading_has_title <- function(data) {
 
   heading <- dt_heading_get(data = data)
 
-  length(heading) > 0 && !is.null(heading$title)
+  length(heading) > 0 && length(heading$title) > 0 && !is.null(heading$title)
 }
 
 dt_heading_has_subtitle <- function(data) {
 
   heading <- dt_heading_get(data = data)
 
-  length(heading) > 0 && !is.null(heading$subtitle)
+  length(heading) > 0 && length(heading$subtitle) > 0 && !is.null(heading$subtitle)
 }
-
diff --git a/R/dt_stubhead.R b/R/dt_stubhead.R
index f6d8ef0f5..e5d669226 100644
--- a/R/dt_stubhead.R
+++ b/R/dt_stubhead.R
@@ -40,5 +40,5 @@ dt_stubhead_has_label <- function(data) {
 
   stubhead <- dt_stubhead_get(data = data)
 
-  length(stubhead) > 0 && !is.null(stubhead$label)
+  length(stubhead$label) > 0 && !is.null(stubhead$label)
 }
diff --git a/R/export.R b/R/export.R
index 8313ea30f..7e94e7137 100644
--- a/R/export.R
+++ b/R/export.R
@@ -457,39 +457,36 @@ as_rtf <- function(data) {
 
   # Composition of RTF ------------------------------------------------------
 
-  # Create a RTF fragment for the start of the table
-  table_start <- rtf_head()
-
   # Create the heading component
-  heading_component <- create_heading_component(data = data, context = "rtf")
+  heading_component <- create_heading_component_rtf(data = data)
 
   # Create the columns component
-  columns_component <- create_columns_component_r(data = data)
+  columns_component <- create_columns_component_rtf(data = data)
 
   # Create the body component
-  body_component <- create_body_component_r(data = data)
+  body_component <- create_body_component_rtf(data = data)
 
   # Create the footnotes component
-  footnotes_component <- create_footnotes_component_r(data = data)
+  footnotes_component <- create_footnotes_component_rtf(data = data)
 
   # Create the source notes component
-  source_notes_component <- create_source_notes_component_r(data = data)
-
-  # Create a fragment for the ending tabular statement
-  table_end <- "}\n"
+  source_notes_component <- create_source_notes_component_rtf(data = data)
 
   # Compose the RTF table
   rtf_table <-
-    paste0(
-      table_start,
-      heading_component,
-      columns_component,
-      body_component,
-      footnotes_component,
-      source_notes_component,
-      table_end,
-      collapse = ""
-    )
+    rtf_file(
+      document = {
+        rtf_table(
+          rows = c(
+            heading_component,
+            columns_component,
+            body_component,
+            footnotes_component,
+            source_notes_component
+          )
+        )
+      }) %>%
+    as_rtf_string()
 
   if (isTRUE(getOption('knitr.in.progress'))) {
     rtf_table <- rtf_table %>% knitr::raw_output()
@@ -498,6 +495,7 @@ as_rtf <- function(data) {
   rtf_table
 }
 
+
 #' Extract a summary list from a **gt** object
 #'
 #' Get a list of summary row data frames from a `gt_tbl` object where summary
diff --git a/R/format_data.R b/R/format_data.R
index d98471d5a..d7100df9f 100644
--- a/R/format_data.R
+++ b/R/format_data.R
@@ -1300,6 +1300,9 @@ fmt_markdown <- function(data,
       latex = function(x) {
         markdown_to_latex(x)
       },
+      rtf = function(x) {
+        markdown_to_rtf(x)
+      },
       default = function(x) {
         vapply(x, commonmark::markdown_text, character(1), USE.NAMES = FALSE) %>%
           stringr::str_replace("\n$", "")
@@ -1414,6 +1417,24 @@ fmt_passthrough <- function(data,
 
         x_str
       },
+      latex = function(x) {
+
+        # Create `x_str` with same length as `x`
+        x_str <- rep(NA_character_, length(x))
+
+        # Handle formatting of pattern
+        x_str <-
+          apply_pattern_fmt_x(
+            pattern,
+            values = x
+          )
+
+        if (escape) {
+          x_str <- x_str %>% process_text(context = "rtf")
+        }
+
+        x_str
+      },
       default = function(x) {
 
         # Create `x_str` with same length as `x`
@@ -1511,6 +1532,20 @@ fmt_missing <- function(data,
         # value, if it exists, should be inherited)
         ifelse(is.na(x), missing_text, NA_character_)
       },
+      rtf = function(x) {
+        missing_text <-
+          context_missing_text(
+            missing_text = missing_text,
+            context = "rtf"
+          )
+
+        # Any values of `x` that are `NA` get
+        # `missing_text` as output; any values that
+        # are not missing get `NA` as their output
+        # (meaning, the existing output for that
+        # value, if it exists, should be inherited)
+        ifelse(is.na(x), missing_text, NA_character_)
+      },
       default = function(x) {
 
         # Any values of `x` that are `NA` get
diff --git a/R/helpers.R b/R/helpers.R
index 47dcbdfa1..d0b1afa19 100644
--- a/R/helpers.R
+++ b/R/helpers.R
@@ -86,6 +86,13 @@ is_html <- function(x) {
   inherits(x, "html") && isTRUE(attr(x, "html"))
 }
 
+#' Does an object have the `rtf_text` class?
+#'
+#' @noRd
+is_rtf <- function(x) {
+  inherits(x, "rtf_text")
+}
+
 #' Helper for providing a numeric value as pixels value
 #'
 #' For certain parameters, a length value is required. Examples include the
diff --git a/R/utils.R b/R/utils.R
index d56edf8fd..ba693ce5c 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -240,6 +240,26 @@ process_text <- function(text,
 
       text <- text %>% escape_latex()
 
+      return(text)
+    }
+  } else if (context == "rtf") {
+
+    # Text processing for RTF output
+
+    if (inherits(text, "from_markdown")) {
+
+      return(markdown_to_rtf(text))
+
+    } else if (inherits(text, "rtf_text")) {
+
+      text <- text %>% as.character()
+
+      return(text)
+
+    } else {
+
+      text <- rtf_escape(text)
+
       return(text)
     }
   } else {
@@ -330,6 +350,234 @@ markdown_to_latex <- function(text) {
     unname()
 }
 
+cmark_rules <- list(
+
+  heading = function(x, process) {
+    heading_sizes <- c(36, 32, 28, 24, 20, 16)
+    fs <- heading_sizes[as.numeric(xml2::xml_attr(x, attr = "level"))]
+
+    rtf_paste0(
+      rtf_raw("{\\ql \\f0 \\sa180 \\b \\fs"),
+      rtf_raw(fs),
+      rtf_raw(" "),
+      process(xml2::xml_children(x)),
+      rtf_raw("}")
+    )
+  },
+  thematic_break = function(x, process) {
+    rtf_raw("{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  },
+  link = function(x, process) {
+    # NOTE: RTF doesn't handle the `title` attr (Pandoc also ignores)
+    destination <- xml2::xml_attr(x, attr = "destination")
+    text <- process(xml2::xml_children(x))
+    if (text == "") text <- destination
+    rtf_raw("{\\field{\\*\\fldinst{HYPERLINK \"", destination, "\"}}{\\fldrslt{\\ul ", text, "}}}")
+  },
+  list = function(x, process) {
+
+    type <- xml2::xml_attr(x, attr = "type")
+    n_items <- length(xml2::xml_children(x))
+
+    # NOTE: `start`, `delim`, and `tight` attrs are ignored; we also
+    # assume there is only `type` values of "ordered" and "bullet" (unordered)
+    rtf_raw(
+      paste(
+        "\\pard\\intbl\\itap1\\li300\\fi-300",
+        paste(
+          vapply(
+            seq_len(n_items),
+            FUN.VALUE = character(1),
+            USE.NAMES = FALSE,
+            FUN = function(n) {
+
+              paste0(
+                ifelse(n == 1, "\\ls1\\ilvl0\\cf0 \n", ""),
+                "{\\listtext\t}",
+                ifelse(type == "bullet", "\\u8226  ", ""),
+                process(xml2::xml_children(x)[n]),
+                "\\",
+                "\n"
+              )
+            }
+          ),
+          collapse = ""
+        ),
+        collapse = ""
+      )
+    )
+  },
+  item = function(x, process) {
+    # TODO: probably needs something like process_children()
+    rtf_escape(xml2::xml_text(x))
+  },
+  code_block = function(x, process) {
+    rtf_paste0(rtf_raw("{\\f1 "), xml2::xml_text(x), rtf_raw("}"))
+  },
+  html_inline = function(x, process) {
+
+    tag <- xml2::xml_text(x)
+
+    match <- stringr::str_match(tag, pattern = "^<(/?)([a-zA-Z0-9\\-]+)")
+
+    if (!is.na(match[1, 1])) {
+
+      span_map <-
+        c(
+          sup = "super",
+          sub = "sub",
+          strong = "b",
+          b = "b",
+          em = "i",
+          i = "i",
+          code = "f1"
+        )
+
+      key_map <- c(br = "line")
+
+      is_closing <- match[1, 2] == "/"
+      tag_name <- match[1, 3]
+
+      if (!is_closing) {
+
+        if (tag_name %in% names(key_map)) {
+
+          return(rtf_key(key_map[tag_name], space = TRUE))
+
+        } else if (tag_name %in% names(span_map)) {
+
+          return(
+            rtf_paste0(
+              rtf_raw("{"),
+              rtf_key(span_map[tag_name], space = TRUE)
+            )
+          )
+        }
+
+      } else {
+
+        if (tag_name %in% names(span_map)) {
+          return(rtf_raw("}"))
+        }
+      }
+    }
+
+    # Any unrecognized HTML tags are stripped, returning nothing
+    return(rtf_raw(""))
+  },
+  softbreak = function(x, process) {
+    rtf_raw("\n ")
+  },
+  linebreak = function(x, process) {
+    rtf_raw("\\line ")
+  },
+  block_quote = function(x, process) {
+    # TODO: Implement
+    process(xml2::xml_children(x))
+  },
+  code = function(x, process) {
+    rtf_paste0(rtf_raw("{\\f1 "), xml2::xml_text(x), rtf_raw("}"))
+  },
+  strong = function(x, process) {
+    rtf_raw("{\\b ", process(xml2::xml_children(x)), rtf_raw("}"))
+  },
+  emph = function(x, process) {
+    rtf_raw("{\\i ", process(xml2::xml_children(x)), rtf_raw("}"))
+  },
+  text = function(x, process) {
+    rtf_escape(xml2::xml_text(x))
+  },
+  paragraph = function(x, process) {
+
+    rtf_paste0(
+      rtf_raw("{"),
+      process(xml2::xml_children(x)),
+      #if (!is_last(x)) rtf_raw("\\par"),
+      rtf_raw("}")
+    )
+  }
+)
+
+is_last <- function(x) {
+  children <- xml2::xml_parent(x) %>% xml2::xml_children()
+  last <- children[[xml2::xml_length(xml2::xml_parent(x))]]
+  identical(last, x)
+}
+
+markdown_to_rtf <- function(text) {
+
+  text <-
+    text %>%
+    as.character() %>%
+    vapply(
+      FUN.VALUE = character(1),
+      USE.NAMES = FALSE,
+      FUN = commonmark::markdown_xml
+    ) %>%
+    vapply(
+      FUN.VALUE = character(1),
+      USE.NAMES = FALSE,
+      FUN = function(cmark) {
+        # cat(cmark)
+        x <- xml2::read_xml(cmark)
+        if (!identical(xml2::xml_name(x), "document")) {
+          stop("Unexpected result from markdown parsing: `document` element not found")
+        }
+
+        children <- xml2::xml_children(x)
+        if (length(children) == 1 &&
+            xml2::xml_type(children[[1]]) == "element" &&
+            xml2::xml_name(children[[1]]) == "paragraph") {
+          children <- xml2::xml_children(children[[1]])
+        }
+
+        apply_rules <- function(x) {
+
+          if (inherits(x, "xml_nodeset")) {
+            len <- length(x)
+            results <- character(len) # preallocate vector
+            for (i in seq_len(len)) {
+              results[[i]] <- apply_rules(x[[i]])
+            }
+            # TODO: is collapse = "" correct?
+            rtf_raw(paste0("", results, collapse = ""))
+          } else {
+            output <- if (xml2::xml_type(x) == "element") {
+
+              rule <- cmark_rules[[xml2::xml_name(x)]]
+              if (is.null(rule)) {
+                rlang::warn(
+                  paste0("Unknown commonmark element encountered: ", xml2::xml_name(x)),
+                  .frequency = "once",
+                  .frequency_id = "gt_commonmark_unknown_element"
+                )
+                apply_rules(xml2::xml_contents(x))
+              } else if (is.character(rule)) {
+                rtf_wrap(rule, x, apply_rules)
+              } else if (is.function(rule)) {
+                rule(x, apply_rules)
+              }
+            }
+            if (!is_rtf(output)) {
+              warning("Rule for ", xml2::xml_name(x), " did not return RTF")
+            }
+            # TODO: is collapse = "" correct?
+            rtf_raw(paste0("", output, collapse = ""))
+          }
+        }
+
+        apply_rules(children)
+      }
+    )
+
+  text
+}
+
+rtf_wrap <- function(control, x, process) {
+  content <- paste0("", process(xml2::xml_contents(x))) # coerce even NULL to string
+  paste0("\\", control, " ", content, "\\", control, "0 ")
+}
+
 #' Transform Markdown text to plain text
 #'
 #' @noRd
diff --git a/R/utils_formatters.R b/R/utils_formatters.R
index d618bd580..b159e60de 100644
--- a/R/utils_formatters.R
+++ b/R/utils_formatters.R
@@ -327,29 +327,39 @@ to_latex_math_mode <- function(x,
 context_missing_text <- function(missing_text,
                                  context) {
 
-  missing_text <- process_text(missing_text, context)
-
-  switch(context,
-         html =
-           {
-             if (!inherits(missing_text, "AsIs") && missing_text == "---") {
-               "&mdash;"
-             } else if (!inherits(missing_text, "AsIs") && missing_text == "--") {
-               "&ndash;"
-             } else {
-               missing_text
-             }
-           },
-         latex =
-           {
-             if (!inherits(missing_text, "AsIs") && missing_text == "---") {
-               "\u2014"
-             } else if (!inherits(missing_text, "AsIs") && missing_text == "--") {
-               "\u2013"
-             } else {
-               missing_text
-             }
-           })
+  switch(
+    context,
+    html =
+      {
+        if (!inherits(missing_text, "AsIs") && missing_text == "---") {
+          "&mdash;"
+        } else if (!inherits(missing_text, "AsIs") && missing_text == "--") {
+          "&ndash;"
+        } else {
+          process_text(missing_text, context)
+        }
+      },
+    latex =
+      {
+        if (!inherits(missing_text, "AsIs") && missing_text == "---") {
+          "\u2014"
+        } else if (!inherits(missing_text, "AsIs") && missing_text == "--") {
+          "\u2013"
+        } else {
+          process_text(missing_text, context)
+        }
+      },
+    rtf =
+      {
+        if (!inherits(missing_text, "AsIs") && missing_text == "---") {
+          "\\'97"
+        } else if (!inherits(missing_text, "AsIs") && missing_text == "--") {
+          "\\'96"
+        } else {
+          process_text(missing_text, context)
+        }
+      }
+  )
 }
 context_dash_mark <- context_missing_text
 
@@ -360,25 +370,36 @@ context_dash_mark <- context_missing_text
 context_plusminus_mark <- function(plusminus_mark,
                                    context) {
 
-  switch(context,
-         html =
-           {
-             if (!inherits(plusminus_mark, "AsIs") &&
-                 plusminus_mark == " +/- ") {
-               " &plusmn; "
-             } else {
-               plusminus_mark
-             }
-           },
-         latex =
-         {
-           if (!inherits(plusminus_mark, "AsIs") &&
-               plusminus_mark == " +/- ") {
-             " \u00B1 "
-           } else {
-             plusminus_mark
-           }
-         })
+  switch(
+    context,
+    html =
+      {
+        if (!inherits(plusminus_mark, "AsIs") &&
+            plusminus_mark == " +/- ") {
+          " &plusmn; "
+        } else {
+          plusminus_mark
+        }
+      },
+    latex =
+      {
+        if (!inherits(plusminus_mark, "AsIs") &&
+            plusminus_mark == " +/- ") {
+          " \u00B1 "
+        } else {
+          plusminus_mark
+        }
+      },
+    rtf =
+      {
+        if (!inherits(plusminus_mark, "AsIs") &&
+            plusminus_mark == " +/- ") {
+          " \\'b1 "
+        } else {
+          plusminus_mark
+        }
+      }
+  )
 }
 
 #' Obtain the contextually correct minus mark
@@ -424,6 +445,7 @@ context_exp_marks <- function(context) {
   switch(context,
          html = c(" &times; 10<sup class='gt_super'>", "</sup>"),
          latex = c(" \\times 10^{", "}"),
+         rtf = c(" \\'d7 10{\\super ", "}"),
          c(" x 10(", ")"))
 }
 
diff --git a/R/utils_render_common.R b/R/utils_render_common.R
index c367d5b2c..e578c8d63 100644
--- a/R/utils_render_common.R
+++ b/R/utils_render_common.R
@@ -369,6 +369,21 @@ create_data_rows <- function(n_rows,
     unname()
 }
 
+#' Split the body content vector into a list structure
+#'
+#' Taking the `body_content` vector, split into list components with one item
+#' per row in the output table
+#' @noRd
+split_body_content <- function(body_content,
+                               n_cols) {
+
+  if (length(body_content) == 0) {
+    return(list(rep("", n_cols)))
+  }
+
+  split(body_content, ceiling(seq_along(body_content) / n_cols))
+}
+
 # Function to build a vector of `summary` rows in the table body
 create_summary_rows <- function(n_rows,
                                 n_cols,
diff --git a/R/utils_render_footnotes.R b/R/utils_render_footnotes.R
index f68440b83..62e1f7262 100644
--- a/R/utils_render_footnotes.R
+++ b/R/utils_render_footnotes.R
@@ -607,7 +607,7 @@ apply_footnotes_to_output <- function(data,
 
 #' @noRd
 set_footnote_marks_row_groups <- function(data,
-                                           context = "html") {
+                                          context = "html") {
 
   groups_rows_df <- dt_groups_rows_get(data = data)
   footnotes_tbl <- dt_footnotes_get(data = data)
@@ -673,9 +673,8 @@ set_footnote_marks_row_groups <- function(data,
 #' Apply footnotes to the summary rows
 #'
 #' @noRd
-apply_footnotes_to_summary <- function(data) {
-
-  # TODO: `context` is missing in this function
+apply_footnotes_to_summary <- function(data,
+                                       context = "html") {
 
   list_of_summaries <- dt_summary_df_get(data = data)
   footnotes_tbl <- dt_footnotes_get(data = data)
@@ -708,8 +707,21 @@ apply_footnotes_to_summary <- function(data) {
         summary_df_list[[footnotes_data_marks[i, ][["grpname"]]]][[
           footnotes_data_marks$row[i], footnotes_data_marks$colname[i]]]
 
-      text <-
-        paste0(text, footnote_mark_to_html(footnotes_data_marks$fs_id_coalesced[i]))
+      if (context == "html") {
+
+        text <-
+          paste0(text, footnote_mark_to_html(footnotes_data_marks$fs_id_coalesced[i]))
+
+      } else if (context == "rtf") {
+
+        text <-
+          paste0(text, footnote_mark_to_rtf(footnotes_data_marks$fs_id_coalesced[i]))
+
+      } else if (context == "latex") {
+
+        text <-
+          paste0(text, footnote_mark_to_latex(footnotes_data_marks$fs_id_coalesced[i]))
+      }
 
       summary_df_list[[footnotes_data_marks[i, ][["grpname"]]]][[
         footnotes_data_marks$row[i], footnotes_data_marks$colname[i]]] <- text
@@ -738,8 +750,21 @@ apply_footnotes_to_summary <- function(data) {
         summary_df_list[[grand_summary_col]][[
           footnotes_data_marks$rownum[i], footnotes_data_marks$colname[i]]]
 
-      text <-
-        paste0(text, footnote_mark_to_html(footnotes_data_marks$fs_id_coalesced[i]))
+      if (context == "html") {
+
+        text <-
+          paste0(text, footnote_mark_to_html(footnotes_data_marks$fs_id_coalesced[i]))
+
+      } else if (context == "rtf") {
+
+        text <-
+          paste0(text, footnote_mark_to_rtf(footnotes_data_marks$fs_id_coalesced[i]))
+
+      } else if (context == "latex") {
+
+        text <-
+          paste0(text, footnote_mark_to_latex(footnotes_data_marks$fs_id_coalesced[i]))
+      }
 
       summary_df_list[[grand_summary_col]][[
         footnotes_data_marks$rownum[i], footnotes_data_marks$colname[i]]] <- text
@@ -750,6 +775,5 @@ apply_footnotes_to_summary <- function(data) {
   }
 
   data <- dt_summary_data_set(data = data, summary = list_of_summaries)
-
   data
 }
diff --git a/R/utils_render_html.R b/R/utils_render_html.R
index 22a205013..8838e3d5e 100644
--- a/R/utils_render_html.R
+++ b/R/utils_render_html.R
@@ -150,6 +150,10 @@ get_table_defs <- function(data) {
 create_heading_component <- function(data,
                                      context = "html") {
 
+  # TODO: This should probably become `create_heading_component_h()`;
+  # The other 'part creation' functions follow this convention and this
+  # one is the last holdout (there is now a `create_heading_component_rtf()`)
+
   heading <- dt_heading_get(data = data)
 
   # If there is no heading component, then return an empty string
@@ -320,26 +324,26 @@ create_heading_component <- function(data,
       paste_between(x_2 = c("\\caption*{\n", "} \\\\ \n"))
   }
 
-  if (context == "rtf") {
-
-    if (subtitle_defined) {
-
-      heading_component <-
-        rtf_title_subtitle(
-          title = paste0(remove_html(heading$title), footnote_title_marks),
-          subtitle = paste0(remove_html(heading$subtitle), footnote_subtitle_marks),
-          n_cols = n_cols
-        )
-
-    } else {
-
-      heading_component <-
-        rtf_title(
-          title = paste0(remove_html(heading$heading), footnote_title_marks),
-          n_cols = n_cols
-        )
-    }
-  }
+  # if (context == "rtf") {
+  #
+  #   if (subtitle_defined) {
+  #
+  #     heading_component <-
+  #       rtf_title_subtitle(
+  #         title = paste0(remove_html(heading$title), footnote_title_marks),
+  #         subtitle = paste0(remove_html(heading$subtitle), footnote_subtitle_marks),
+  #         n_cols = n_cols
+  #       )
+  #
+  #   } else {
+  #
+  #     heading_component <-
+  #       rtf_title(
+  #         title = paste0(remove_html(heading$heading), footnote_title_marks),
+  #         n_cols = n_cols
+  #       )
+  #   }
+  # }
 
   heading_component
 }
diff --git a/R/utils_render_rtf.R b/R/utils_render_rtf.R
deleted file mode 100644
index 706b30b00..000000000
--- a/R/utils_render_rtf.R
+++ /dev/null
@@ -1,570 +0,0 @@
-# Transform a footnote mark to an RTF representation as a superscript
-footnote_mark_to_rtf <- function(mark) {
-
-  paste0("{\\super \\i ", mark, "}")
-}
-
-create_body_component_r <- function(data) {
-
-  boxh <- dt_boxhead_get(data = data)
-  styles_tbl <- dt_styles_get(data = data)
-  body <- dt_body_get(data = data)
-  summaries_present <- dt_summary_exists(data = data)
-  list_of_summaries <- dt_summary_df_get(data = data)
-  groups_rows_df <- dt_groups_rows_get(data = data)
-  stub_components <- dt_stub_components(data = data)
-
-  n_data_cols <- dt_boxhead_get_vars_default(data = data) %>% length()
-  n_rows <- nrow(body)
-
-  # Get the column alignments for the data columns (this
-  # doesn't include the stub alignment)
-  col_alignment <-
-    boxh %>%
-    dplyr::filter(type == "default") %>%
-    dplyr::pull(column_align)
-
-  # Get the column headings for the visible (e.g., `default`) columns
-  default_vars <- dt_boxhead_get_vars_default(data = data)
-
-  if ("rowname" %in% names(body)) {
-    default_vars <- c("rowname", default_vars)
-  }
-
-  # Determine whether the stub is available through analysis
-  # of the `stub_components`
-  stub_available <- dt_stub_components_has_rowname(stub_components)
-
-  if (stub_available) {
-    n_cols <- n_data_cols + 1
-  } else {
-    n_cols <- n_data_cols
-  }
-
-  # Split `body_content` by slices of rows and create data rows
-  body_content <- as.vector(t(body[, default_vars]))
-  row_splits <- split(body_content, ceiling(seq_along(body_content) / n_cols))
-
-  body_rows <- c()
-  for (i in seq_len(n_rows)) {
-
-    # Process group rows
-    if (!is.null(groups_rows_df) &&
-        i %in% groups_rows_df$row) {
-
-      body_rows <-
-        c(body_rows,
-          rtf_body_row(
-            c(
-              groups_rows_df[which(groups_rows_df$row %in% i), 1][[1]],
-              rep("", n_cols - 1)), type = "group"))
-    }
-
-    # Process "data" rows
-    if (i != length(row_splits)) {
-      body_rows <-
-        c(body_rows, rtf_body_row(row_splits[[i]], type = "row"))
-    } else {
-      body_rows <-
-        c(body_rows, rtf_last_body_row(content = row_splits[[i]]))
-    }
-
-    # Process summary rows
-    if (stub_available && summaries_present &&
-        i %in% groups_rows_df$row_end) {
-
-      group <-
-        groups_rows_df %>%
-        dplyr::filter(row_end == i) %>%
-        dplyr::pull(group)
-
-      if (group %in% names(list_of_summaries$summary_df_display_list)) {
-
-        summary_df <-
-          list_of_summaries$summary_df_display_list[[
-            which(names(list_of_summaries$summary_df_display_list) == group)]] %>%
-          as.data.frame(stringsAsFactors = FALSE)
-
-        body_content_summary <-
-          as.vector(t(summary_df)) %>%
-          tidy_gsub("\u2014", "-")
-
-        row_splits_summary <-
-          split_body_content(
-            body_content = body_content_summary,
-            n_cols = n_cols)
-
-        for (j in seq(length(row_splits_summary))) {
-
-          body_rows <-
-            c(body_rows, rtf_body_row(row_splits_summary[[j]], type = "row"))
-        }
-      }
-    }
-  }
-
-  paste0(body_rows, collapse = "")
-}
-
-create_source_notes_component_r <- function(data) {
-
-  source_notes <- dt_source_notes_get(data = data)
-
-  # Create the source note rows and handle any available footnotes
-  if (length(source_notes) != 0) {
-
-    # Create a source note
-    source_note_rows <-
-      paste0(
-        "\\pard\\pardeftab720\\sl288\\slmult1\\partightenfactor0\n",
-        paste0(
-          "\\cf0 \\strokec2 ", remove_html(text = source_notes), "\\\n",
-          collapse = ""),
-        collapse = "")
-  } else {
-    source_note_rows <- ""
-  }
-
-  source_note_rows
-}
-
-#' @noRd
-create_footnotes_component_r <- function(data) {
-
-  body <- dt_body_get(data = data)
-  opts_df <- dt_options_get(data = data)
-  footnotes_tbl <- dt_footnotes_get(data = data)
-
-  # Get the column headings for the visible (e.g., `default`) columns
-  default_vars <- dt_boxhead_get_vars_default(data = data)
-
-  if ("rowname" %in% names(body)) {
-    default_vars <- c("rowname", default_vars)
-  }
-
-  body_content <- as.vector(t(body[, default_vars]))
-
-  # If the `footnotes_tbl` object has no
-  # rows, then return an empty footnotes component
-  if (nrow(footnotes_tbl) == 0) {
-    return("")
-  }
-
-  footnotes_tbl <-
-    footnotes_tbl %>%
-    dplyr::select(fs_id, footnotes) %>%
-    dplyr::distinct()
-
-  # Get the separator option from `opts_df`
-  separator <-
-    opts_df %>%
-    dplyr::filter(parameter == "footnotes_sep") %>%
-    dplyr::pull(value)
-
-  # Convert common HTML tags/entities to plaintext
-  separator <-
-    separator %>%
-    tidy_gsub("<br\\s*?(/|)>", "\n") %>%
-    tidy_gsub("&nbsp;", " ")
-
-  # Create the footnotes block
-  footnotes_component <-
-    paste0(
-      "\\pard\\pardeftab720\\sl288\\slmult1\\partightenfactor0\n",
-      paste0(
-        # "\\f2\\i\\fs14\\fsmilli7333 \\super \\strokec2 ", footnotes_tbl[["fs_id"]],
-        # "\\f0\\i0\\fs22 \\nosupersub \\strokec2 ",
-        footnote_mark_to_rtf(footnotes_tbl[["fs_id"]]),
-        footnotes_tbl[["footnotes"]] %>% remove_html(), "\\",
-        collapse = separator), "\n"
-    )
-
-  footnotes_component
-}
-
-#' @noRd
-col_width_twips <- function() {
-  935L
-}
-
-#' @noRd
-rtf_head <- function() {
-
-  paste0(
-    "{\\rtf1\\ansi\\ansicpg1252\\cocoartf1561\\cocoasubrtf400\n",
-    "{\\fonttbl\\f0\\fswiss\\fcharset0 Helvetica;}\n",
-    "{\\colortbl;\\red255\\green255\\blue255;\n",
-    "}\n",
-    "{\\*\\expandedcolortbl;;\\cssrgb\\c0\\c0\\c0;\\cssrgb\\c37036\\c37036\\c37036;\\csgray\\c0\\c0;\n",
-    "}\n",
-    "\\deftab20\n",
-    "\\cf0\n", collapse = "")
-}
-
-#' @noRd
-rtf_title_subtitle <- function(title, subtitle, n_cols) {
-
-  twips <- 1:n_cols * col_width_twips()
-
-  paste0(
-    "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrt\\brdrnil \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-    paste0("\\clmgf \\clvertalb \\clshdrawnil \\clheight340 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrnil \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt100 \\gaph\\cellx", twips[1], "\n"),
-    paste0("\\clmrg \\clvertalb \\clshdrawnil \\clheight340 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrnil \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt100 \\gaph\\cellx", twips[2:length(twips)], "\n", collapse = ""),
-    "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-    "\\f0\\fs36 \\expnd0\\expndtw0\\kerning0\n",
-    paste0("\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", title, "\n"),
-    "\\fs24  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n",
-    paste0(rep("\\pard\\intbl\\itap1\\cell\n", n_cols - 1), collapse = ""),
-    "\\row\n\n",
-    "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-    paste0("\\clmgf \\clvertalc \\clshdrawnil \\clheight240 \\clbrdrt\\brdrnil \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadb100 \\gaph\\cellx", twips[1], "\n"),
-    paste0("\\clmrg \\clvertalc \\clshdrawnil \\clheight240 \\clbrdrt\\brdrnil \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadb100 \\gaph\\cellx", twips[2:length(twips)], "\n", collapse = ""),
-    "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n\n",
-    "\\fs20 \\expnd0\\expndtw0\\kerning0",
-    paste0("\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", subtitle, "\n"),
-    "\\fs28  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell",
-    paste0(rep("\\pard\\intbl\\itap1\\cell\n", n_cols - 1), collapse = ""),
-    "\\row")
-}
-
-#' @noRd
-rtf_title <- function(title, n_cols) {
-
-  twips <- 1:n_cols * col_width_twips()
-
-  paste0(
-    "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrt\\brdrnil \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-    paste0("\\clmgf \\clvertalb \\clshdrawnil \\clheight340 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt100 \\clpadb100 \\gaph\\cellx", twips[1], "\n"),
-    paste0("\\clmrg \\clvertalb \\clshdrawnil \\clheight340 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt100 \\clpadb100 \\gaph\\cellx", twips[2:length(twips)], "\n", collapse = ""),
-    "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-    "\\f0\\fs36 \\expnd0\\expndtw0\\kerning0\n",
-    paste0("\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", title, "\n"),
-    "\\fs24  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n",
-    paste0(rep("\\pard\\intbl\\itap1\\cell\n", n_cols - 1), collapse = ""),
-    "\\row\n\n")
-}
-
-#' @noRd
-rtf_heading_group_row <- function(spanners_lengths,
-                                  headings,
-                                  spanners) {
-
-  values <- spanners_lengths$values
-  lengths <- spanners_lengths$lengths
-
-  twips <- 1:sum(lengths) * col_width_twips()
-
-  # Creation of Top Row
-
-  output <- "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrt\\brdrnil \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n"
-
-  for (i in seq(lengths)) {
-
-    if (lengths[i] == 1 && values[i] %in% headings) {
-
-      output <- c(output, "\\clvmgf \\clvertalc \\clshdrawnil \\clheight1100 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrs\\brdrw20\\brdrcf3 \\clpadl100 \\clpadr100 \\gaph\\cellx")
-
-    } else if (lengths[i] > 1 && !(values[i] %in% headings)) {
-
-      for (j in 1:lengths[i]) {
-
-        if (j == 1) {
-          output <- c(output, "\\clmgf \\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrs\\brdrw20\\brdrcf3 \\clbrdrb\\brdrs\\brdrw20\\brdrcf3 \\clbrdrr\\brdrs\\brdrw20\\brdrcf3 \\clpadl100 \\clpadr100 \\gaph\\cellx")
-        }
-
-        if (j != 1) {
-          output <- c(output, "\\clmrg \\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrs\\brdrw20\\brdrcf3 \\clbrdrb\\brdrs\\brdrw20\\brdrcf3 \\clbrdrr\\brdrs\\brdrw20\\brdrcf3 \\clpadl100 \\clpadr100 \\gaph\\cellx")
-        }
-      }
-
-    } else if (lengths[i] == 1 && !(values[i] %in% headings)) {
-
-      output <- c(output, "\\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrs\\brdrw20\\brdrcf3 \\clbrdrb\\brdrs\\brdrw20\\brdrcf3 \\clbrdrr\\brdrs\\brdrw20\\brdrcf3 \\clpadl100 \\clpadr100 \\gaph\\cellx")
-    }
-  }
-
-  for (i in 2:length(output)) {
-    output[i] <- paste0(output[i], twips[i - 1], "\n")
-  }
-
-  for (i in seq(lengths)) {
-
-    if (lengths[i] == 1 && values[i] %in% headings) {
-
-      output <-
-        c(output,
-          "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-          ifelse(i == 1, "\\f0\\fs24\n", ""),
-          "\\expnd0\\expndtw0\\kerning0\n",
-          "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\b ", values[i], "\\b0  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n")
-
-    } else if (lengths[i] > 1 && !(values[i] %in% headings)) {
-
-      for (j in 1:lengths[i]) {
-
-        if (j == 1) {
-          output <-
-            c(output,
-              "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-              ifelse(i == 1, "\\f0\\fs24\n", ""),
-              "\\expnd0\\expndtw0\\kerning0\n",
-              "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\b ", values[i], "\\b0  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n")
-        }
-
-        if (j != 1) {
-          output <- c(output, "\\pard\\intbl\\itap1\\cell\n")
-        }
-      }
-
-    } else if (lengths[i] == 1 && !(values[i] %in% headings)) {
-
-      output <-
-        c(output,
-          "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-          ifelse(i == 1, "\\f0\\fs24\n", ""),
-          "\\expnd0\\expndtw0\\kerning0\n",
-          "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\b ", values[i], "\\b0  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n")
-    }
-  }
-
-  output <- c(output, "\\row\n")
-
-  output <- paste0(output, collapse = "")
-
-  # Creation of Bottom Row
-  output_b <- "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrl\\brdrnil \\trbrdrt\\brdrnil \\trbrdrr\\brdrnil\n"
-
-  for (i in seq(lengths)) {
-
-    if (lengths[i] == 1 && values[i] %in% headings) {
-
-      output_b <- c(output_b, "\\clvmrg \\clvertalc \\clshdrawnil \\clheight1100 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\gaph\\cellx")
-
-    } else if (lengths[i] > 1 && !(values[i] %in% headings)) {
-
-      for (j in 1:lengths[i]) {
-
-        if (j == 1) {
-          output_b <- c(output_b, "\\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw20\\brdrcf3 \\clbrdrl\\brdrs\\brdrw20\\brdrcf3 \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\gaph\\cellx")
-        }
-
-        if (j > 1 & j < lengths[i]) {
-          output_b <- c(output_b, "\\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw20\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\gaph\\cellx")
-        }
-
-        if (j == lengths[i]) {
-          output_b <- c(output_b, "\\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw20\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrs\\brdrw20\\brdrcf3 \\clpadl100 \\clpadr100 \\gaph\\cellx")
-        }
-      }
-
-    } else if (lengths[i] == 1 && !(values[i] %in% headings)) {
-
-      output_b <- c(output_b, "\\clvertalc \\clshdrawnil \\clheight540 \\clbrdrt\\brdrs\\brdrw20\\brdrcf3 \\clbrdrl\\brdrs\\brdrw20\\brdrcf3 \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrs\\brdrw20\\brdrcf3 \\clpadl100 \\clpadr100 \\gaph\\cellx")
-    }
-  }
-
-  for (i in 2:length(output_b)) {
-    output_b[i] <- paste0(output_b[i], twips[i - 1], "\n")
-  }
-
-  for (i in seq(headings)) {
-
-    if (headings[i] == spanners[i]) {
-
-      output_b <- c(output_b, "\\pard\\intbl\\itap1\\cell\n")
-
-    } else if (headings[i] != spanners[i] && sum(spanners == spanners[i]) > 1) {
-
-      output_b <-
-        c(output_b,
-          "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-          "\\expnd0\\expndtw0\\kerning0\n",
-          "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\b ", headings[i], "\\b0  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n")
-
-    } else if (headings[i] != spanners[i] && sum(spanners == spanners[i]) == 1) {
-
-      output_b <-
-        c(output_b,
-          "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-          "\\expnd0\\expndtw0\\kerning0\n",
-          "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\b ", headings[i], "\\b0  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\expnd0\\expndtw0\\kerning0\n",
-          "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\cell\n")
-    }
-  }
-
-  output_b <- c(output_b, "\\row\n")
-  output_b <- paste0(output_b, collapse = "")
-
-  paste0(output, output_b, collapse = "")
-}
-
-#' @noRd
-rtf_heading_row <- function(content) {
-
-  twips <- 1:length(content) * col_width_twips()
-
-  paste0(
-    paste0(
-      "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-      paste0("\\clvertalc \\clshdrawnil \\clheight520 \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\gaph\\cellx", twips, "\n", collapse = ""),
-      paste0(
-        "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-        "\\expnd0\\expndtw0\\kerning0\n",
-        "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", content, " \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n", collapse = ""),
-      collapse = ""),
-    " \\row")
-}
-
-#' @noRd
-rtf_body_row <- function(content,
-                         type) {
-
-  twips <- 1:length(content) * col_width_twips()
-
-  if (type == "row") {
-
-    return(
-      paste0(
-        paste0(
-          "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-          paste0("\\clvertalc \\clshdrawnil \\clbrdrt\\brdrnil \\clbrdrl\\brdrnil \\clbrdrb\\brdrnil \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt50 \\clpadb50 \\gaph\\cellx", twips, "\n", collapse = ""),
-          paste0(
-            "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-            "\\expnd0\\expndtw0\\kerning0\n",
-            "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", content, " \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n", collapse = ""),
-          collapse = ""),
-        " \\row"))
-
-  } else if (type == "group") {
-
-    return(
-      paste0(
-        paste0(
-          "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-          paste0("\\clvertalc \\clshdrawnil \\clbrdrt\\brdrs\\brdrw40\\brdrcf3 \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw10\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt50 \\clpadb50 \\gaph\\cellx", twips, "\n", collapse = ""),
-          paste0(
-            "\\pard\\intbl\\itap1\\pardeftab20\\ql\\partightenfactor0\n",
-            "\\expnd0\\expndtw0\\kerning0\n",
-            "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\b ", content, "\\b0  \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n", collapse = ""),
-          collapse = ""),
-        " \\row"))
-  }
-}
-
-#' @noRd
-rtf_last_body_row <- function(content) {
-
-  twips <- 1:length(content) * col_width_twips()
-
-  output <-
-    paste0(
-      "\\itap1\\trowd \\taflags1 \\trgaph108\\trleft-108 \\trbrdrl\\brdrnil \\trbrdrr\\brdrnil\n",
-      paste0("\\clvertalc \\clshdrawnil \\clbrdrt\\brdrnil \\clbrdrl\\brdrnil \\clbrdrb\\brdrs\\brdrw40\\brdrcf3 \\clbrdrr\\brdrnil \\clpadl100 \\clpadr100 \\clpadt50 \\clpadb50 \\gaph\\cellx", twips, "\n", collapse = ""))
-
-  for (i in seq(content)) {
-
-    if (i != length(content)) {
-      output <-
-        c(output,
-          paste0(
-            "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-            "\\expnd0\\expndtw0\\kerning0\n",
-            "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", content[i], " \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\cell\n"))
-
-    } else {
-      output <-
-        c(output,
-          paste0(
-            "\\pard\\intbl\\itap1\\pardeftab20\\qc\\partightenfactor0\n",
-            "\\expnd0\\expndtw0\\kerning0\n",
-            "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 ", content[i], " \\kerning1\\expnd0\\expndtw0 \\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0\\expnd0\\expndtw0\\kerning0\n",
-            "\\up0 \\nosupersub \\ulnone \\outl0\\strokewidth0 \\strokec2 \\cell \\lastrow\\row"))
-    }
-  }
-
-  output <- paste(output, collapse = "")
-
-  output
-}
-
-#' Split the body content vector into a list structure
-#'
-#' Taking the `body_content` vector, split into list components with one item
-#' per row in the output table
-#' @noRd
-split_body_content <- function(body_content,
-                               n_cols) {
-
-  if (length(body_content) == 0) {
-    return(list(rep("", n_cols)))
-  }
-
-  split(body_content, ceiling(seq_along(body_content) / n_cols))
-}
-
-
-create_columns_component_r <- function(data) {
-
-  boxh <- dt_boxhead_get(data = data)
-  stubh <- dt_stubhead_get(data = data)
-  stub_available <- dt_stub_df_exists(data = data)
-  spanners_present <- dt_spanners_exists(data = data)
-
-  headings_vars <- boxh %>% dplyr::filter(type == "default") %>% dplyr::pull(var)
-  headings_labels <- dt_boxhead_get_vars_labels_default(data = data)
-
-  # If `stub_available` == TRUE, then replace with a set stubhead
-  # label or nothing
-  if (isTRUE(stub_available) && length(stubh$label) > 0) {
-
-    headings_labels <- prepend_vec(headings_labels, stubh$label)
-    headings_vars <- prepend_vec(headings_vars, "::stub")
-
-  } else if (isTRUE(stub_available)) {
-
-    headings_labels <- prepend_vec(headings_labels, "")
-    headings_vars <- prepend_vec(headings_vars, "::stub")
-  }
-
-  # Remove any HTML tags from `headings`
-  headings_labels <- remove_html(headings_labels)
-
-  if (spanners_present == FALSE) {
-
-    columns_component <-
-      paste0(rtf_heading_row(content = headings_labels), collapse = "")
-
-  } else {
-
-    # spanners
-    spanners <- dt_spanners_print(data = data, include_hidden = FALSE)
-
-    # Promote column labels to the group level wherever the
-    # spanner label is NA
-    spanners[is.na(spanners)] <- headings_vars[is.na(spanners)]
-
-    # Remove any HTML tags from `spanners`
-    spanners <- remove_html(spanners)
-
-    if (stub_available) {
-      spanners <- c(NA_character_, spanners)
-    }
-
-    # for (i in seq(spanners)) {
-    #   if (is.na(spanners[i])) {
-    #     spanners[i] <- headings[i]
-    #   }
-    # }
-
-    spanners_lengths <- rle(spanners)
-
-    columns_component <-
-      rtf_heading_group_row(
-        spanners_lengths = spanners_lengths,
-        headings = headings_labels,
-        spanners = spanners
-      )
-  }
-
-  columns_component
-}
diff --git a/R/utils_render_rtf_redo.R b/R/utils_render_rtf_redo.R
new file mode 100644
index 000000000..31564210b
--- /dev/null
+++ b/R/utils_render_rtf_redo.R
@@ -0,0 +1,1200 @@
+rtf_paste0 <- function(..., collapse = NULL) {
+  args <- lapply(list(...), function(x) {
+    if (is.null(x) || is_rtf(x)) {
+      x
+    } else {
+      rtf_escape(as.character(x))
+    }
+  })
+  args$collapse <- collapse
+  rtf_raw(do.call(paste0, args))
+}
+
+rtf_key <- function(word, val = NULL, space = FALSE) {
+  rtf_raw(paste0("\\", word, val %||% "", if (space) " "))
+}
+
+rtf_fonttbl <- function(...,
+                        .font_names = NULL,
+                        .default_n = NULL) {
+
+  fonts <- list(...)
+
+  if (!is.null(.font_names)) {
+    fonts <- lapply(.font_names, FUN = function(x) rtf_font_def(x))
+  }
+
+  if (length(fonts) < 1) {
+    fonts <-
+      list(
+        rtf_font_def(font = "Calibri", family = "roman"),
+        rtf_font_def(font = "Courier", family = "roman")
+      )
+  }
+
+  # TODO: Validate that all provided objects are "rtf_font"
+  default_n <- if (!is.null(.default_n)) rtf_key("deff", .default_n - 1) else ""
+
+  font_sequence <- seq_len(length(fonts)) - 1
+
+  fontinfo_values <-
+    vapply(
+      seq_along(fonts),FUN.VALUE = character(1), USE.NAMES = FALSE,
+      FUN = function(x) {
+        fonts[x] %>% unlist() %>% gsub("{x}", font_sequence[x], ., fixed = TRUE)
+      }
+    )
+
+  fonttbl_values <- rtf_key("fonttbl", paste(fontinfo_values, collapse = ""))
+
+  rtf_fonttbl <- list(paste0(default_n, paste0("{", fonttbl_values, "}")))
+
+  class(rtf_fonttbl) <- "rtf_fonttbl"
+  rtf_fonttbl
+}
+
+rtf_font_def <- function(font,
+                         family = NULL,
+                         number = NULL,
+                         charset = NULL,
+                         pitch = NULL) {
+
+  font_family_name <- family %||% "nil"
+  font_charset <- charset %||% 0
+  font_pitch <- pitch %||% 0
+
+  rtf_font_n <- rtf_key("f", "{x}")
+  rtf_fontfamily <- rtf_key("f", font_family_name)
+  rtf_fontcharset <- rtf_key("fcharset", font_charset)
+  rtf_fontpitch <- rtf_key("fprq", font_pitch)
+
+  rtf_font <-
+    list(
+      paste0(
+        "{",
+        rtf_font_n,
+        rtf_fontfamily,
+        rtf_fontcharset,
+        rtf_fontpitch,
+        " ",
+        font,
+        ";}"
+      )
+    )
+
+  class(rtf_font) <- "rtf_font"
+  rtf_font
+}
+
+rtf_colortbl <- function(...,
+                         .hexadecimal_colors = NULL,
+                         .add_default = TRUE) {
+
+  colors <- list(...)
+
+  if (!is.null(.hexadecimal_colors)) {
+    colors <- lapply(.hexadecimal_colors, FUN = function(x) rtf_color(x))
+  }
+
+  rtf_colortbl <-
+    list(
+      paste0(
+        "{",
+        rtf_key(
+          "colortbl",
+          paste0(if (.add_default) ";", paste(unlist(colors), collapse = ";"), ";")
+        ),
+        "}"
+      )
+    )
+
+  class(rtf_colortbl) <- "rtf_colortbl"
+  rtf_colortbl
+}
+
+rtf_color <- function(color = NULL, rgb = NULL) {
+
+  if (!is.null(color)) {
+    rgb <- as.integer(t(grDevices::col2rgb(col = color)))
+  }
+
+  rtf_color <-
+    list(
+      paste0(
+        rtf_key("red", rgb[1]),
+        rtf_key("green", rgb[2]),
+        rtf_key("blue", rgb[3])
+      )
+    )
+
+  class(rtf_color) <- "rtf_color"
+  rtf_color
+}
+
+rtf_header <- function(..., .charset = "ansi", .ansi_code_page = 1252) {
+
+  # Requires the font table (<fonttbl>)
+
+  # Optionally can use the:
+  #   [1] file table (<filetbl>)
+  #   [2] color table (<colortbl>)
+  #   [3] stylesheet (<stylesheet>)
+  #   [4] list tables (<listtables>)
+  #   [5] revision table (<revtbl>)
+
+  dots_list <- list(...)
+
+  additional_items <- c()
+
+  # TODO: Validate `dots_list` for object types
+
+  rtf_rtf_key <- rtf_key("rtf")
+  charset_key <- rtf_key(.charset)
+  ansi_code_page_key <- rtf_key("ansicpg", .ansi_code_page)
+
+  # Get a vector of the different object types
+  object_types <- vapply(dots_list, class, FUN.VALUE = character(1), USE.NAMES = FALSE)
+
+  # TODO: Validate the `object_types` vector
+
+  # Extract the `font_table` object
+  font_table <- unlist(dots_list[object_types == "rtf_fonttbl"])
+
+  if ("rtf_colortbl" %in% object_types) {
+    additional_items <- c(additional_items, unlist(dots_list[object_types == "rtf_colortbl"]))
+  }
+
+  # Arrange the keywords of the RTF header
+  rtf_header <-
+    list(
+      rtf_header = paste0(
+        rtf_rtf_key,
+        charset_key,
+        ansi_code_page_key,
+        font_table,
+        additional_items,
+        "\n"
+      )
+    )
+
+  class(rtf_header) <- c("rtf_header", "rtf")
+  rtf_header
+}
+
+rtf_file <- function(header = NULL, document = NULL) {
+
+  if (is.null(header) && is.null(document)) {
+    header <- document <- ""
+  } else if (is.null(header) && !is.null(document)) {
+
+    # If `header` is NULL then generate the header based on the
+    # `document` content (and also modify the document)
+
+    # Scan for hexadecimal colors in the document; generate
+    # a <colortbl> object
+    matched_colors <-
+      unique(unlist(stringr::str_extract_all(document, "<<COLOR:#[0-9a-fA-F]{6}>>")))
+
+    if (length(matched_colors) > 0) {
+
+      colortbl <-
+        rtf_colortbl(.hexadecimal_colors = gsub("<<COLOR:|>>", "", matched_colors))
+
+      for (i in seq_along(matched_colors)) {
+        document <- gsub(matched_colors[i], as.character(i), document, fixed = TRUE)
+      }
+    } else {
+      colortbl <- rtf_colortbl(.hexadecimal_colors = "#FFFFFF")
+    }
+
+    # Scan for hexadecimal colors in the document; generate
+    # a <fonttbl> object
+    matched_fonts <-
+      unique(unlist(stringr::str_extract_all(document, "<<FONT:.*?>>")))
+
+    if (length(matched_fonts) > 0) {
+
+      fonttbl <-
+        rtf_fonttbl(.font_names = c("Calibri", gsub("<<FONT:|>>", "", matched_fonts)), .default_n = 1)
+
+      for (i in seq_along(matched_fonts)) {
+        document <- gsub(matched_fonts[i], as.character(i), document, fixed = TRUE)
+      }
+    } else {
+      fonttbl <- rtf_fonttbl()
+    }
+
+    # Create the document header
+    header <- rtf_header(fonttbl, colortbl)
+  }
+
+
+  rtf_file <- list(header = header, document = document)
+
+  class(rtf_file) <- c("rtf_file", "rtf")
+  rtf_file
+}
+
+rtf_table <- function(rows) {
+
+  rtf_raw(paste(unlist(rows), collapse = ""))
+}
+
+rtf_tbl_row <- function(x,
+                        widths = NULL,
+                        height = NULL,
+                        borders = NULL,
+                        repeat_header = FALSE) {
+
+  if (is.list(x)) x <- unlist(x)
+
+  cell_count <- length(x)
+
+  if (!is.null(widths)) {
+    widths_twips <- cumsum(widths)
+  } else {
+    widths_twips <- cumsum(rep(standard_width_twips / cell_count, cell_count))
+  }
+
+  if (is.null(height)) height <- 425
+
+  # Set border values
+  if (!is.null(borders)) {
+
+    if (inherits(borders, "list")) {
+      borders <- unlist(borders, recursive = FALSE)
+    }
+
+    tb_borders <-
+      borders %>%
+      lapply(
+        FUN = function(x) {
+
+          if (is.numeric(x$color)) {
+            border_color_value <- x$color
+          } else {
+            border_color_value <- rtf_paste0("<<COLOR:", rtf_raw(x$color), ">>")
+          }
+
+          if (x$direction %in% c("top", "bottom")) {
+
+            rtf_paste0(
+              rtf_key("clbrdr", substr(x$direction, 1, 1)),
+              rtf_key("brdr", x$style),
+              rtf_key("brdrw", x$width),
+              rtf_key("brdrcf", border_color_value)
+            )
+          } else {
+            ""
+          }
+        }
+      ) %>% unlist()
+
+    lr_borders <-
+      borders %>%
+      lapply(
+        FUN = function(x) {
+
+          if (is.numeric(x$color)) {
+            border_color_value <- x$color
+          } else {
+            border_color_value <- rtf_paste0("<<COLOR:", rtf_raw(x$color), ">>")
+          }
+
+          if (x$direction %in% c("left", "right")) {
+
+            rtf_paste0(
+              rtf_key("clbrdr", substr(x$direction, 1, 1)),
+              rtf_key("brdr", x$style),
+              rtf_key("brdrw", x$width),
+              rtf_key("brdrcf", border_color_value)
+            )
+          } else {
+            ""
+          }
+        }
+      ) %>% unlist()
+
+  } else {
+    tb_borders <- ""
+    lr_borders <- ""
+  }
+
+  # Combine all row settings
+  row_settings <-
+    rtf_paste0(
+      rtf_key("trowd"),
+      rtf_key("trrh", height),
+      if (repeat_header) rtf_key("trhdr")
+    )
+
+  # Divide `x` into a list with three elements
+  x <- strsplit(x, "\n")
+
+  # Combine additional row components to the first element
+  row_components <- paste0(tb_borders, paste0("\\cellx", floor(widths_twips)))
+
+  for (i in seq_along(row_components)) {
+    x[[i]][1] <- rtf_paste0(rtf_raw(x[[i]][1]), rtf_raw(row_components[i]))
+  }
+
+  x <- lapply(x, FUN = function(x) paste(x, collapse = "\n")) %>% unlist()
+
+  # Return a complete row of RTF table cells (marked as `rtf_text`)
+  rtf_paste0(
+    row_settings,
+    "\n\n",
+    rtf_raw(paste0(x, collapse = "\n\n")),
+    "\n\n",
+    rtf_key("row"),
+    "\n\n"
+  )
+}
+
+rtf_tbl_cell <- function(x,
+                         borders = NULL,
+                         h_align = c("left", "center", "right"),
+                         v_align = c("center", "top", "bottom"),
+                         h_merge = NULL,
+                         padding = NULL,
+                         cell_background_color = NULL,
+                         font = NULL,
+                         font_size = NULL,
+                         font_color = NULL,
+                         bold = FALSE,
+                         italic = FALSE,
+                         super_sub = NULL) {
+
+
+  x <- paste(x, collapse = " ")
+
+  h_align <- substr(match.arg(h_align), 1, 1)
+  v_align <- substr(match.arg(v_align), 1, 1)
+
+  # Set default padding values if `padding = NULL`
+  if (is.null(padding)) padding <- c(50, 50, 50, 50)
+
+  # Set padding in units of twips, in the order bottom, right, left, and top
+  padding_values <-
+    c(
+      rtf_key("clpadb", padding[1]), rtf_key("clpadr", padding[2]),
+      rtf_key("clpadl", padding[3]), rtf_key("clpadt", padding[4])
+    )
+  padding_units <-
+    c(
+      rtf_key("clpadfb", 3), rtf_key("clpadfr", 3),
+      rtf_key("clpadfl", 3), rtf_key("clpadft", 3)
+    )
+
+  cell_padding <- paste(paste0(padding_values, padding_units), collapse = "")
+
+  # Set border values
+  if (!is.null(borders)) {
+
+    if (inherits(borders, "list")) {
+      borders <- unlist(borders, recursive = FALSE)
+    }
+
+    cell_borders <-
+      vapply(
+        borders,
+        FUN.VALUE = character(1),
+        USE.NAMES = FALSE,
+        FUN = function(x) {
+
+          if (is.numeric(x$color)) {
+            border_color_value <- x$color
+          } else {
+            border_color_value <- rtf_raw(paste0("<<COLOR:", x$color, ">>"))
+          }
+
+          rtf_paste0(
+            rtf_key("clbrdr", substr(x$direction, 1, 1)),
+            rtf_key("brdr", x$style),
+            rtf_key("brdrw", x$width),
+            rtf_key("brdrcf", border_color_value)
+          )
+        }
+      ) %>%
+      paste(collapse = "")
+  } else {
+    cell_borders <- ""
+  }
+
+  # Set background color
+  if (!is.null(cell_background_color)) {
+    cell_background_color <- rtf_key("clcbpat", paste0("<<COLOR:", cell_background_color, ">>"))
+  } else {
+    cell_background_color <- ""
+  }
+
+  # Set horizontal cell merging
+  if (!is.null(h_merge)) {
+    if (h_merge == 1) {
+      cell_merging <- rtf_key("clmgf")
+    } else if (h_merge == 2) {
+      cell_merging <- rtf_key("clmrg")
+    } else {
+      cell_merging <- NULL
+    }
+  } else {
+    cell_merging <- NULL
+  }
+
+  # Pass all text fragments and options though `rtf_font()`
+  cell_text <-
+    rtf_font(
+      font = font,
+      font_size = font_size,
+      font_color = font_color,
+      bold = bold,
+      italic = italic,
+      super_sub = super_sub,
+      rtf_raw(x)
+    ) %>%
+    unlist() %>%
+    unname() %>%
+    tidy_gsub("\\\\super", "\\super", fixed = TRUE) %>%
+    tidy_gsub("\\\\i", "\\i", fixed = TRUE)
+
+  # Combine all cell settings
+  cell_settings <-
+    rtf_paste0(
+      rtf_key("pard"),
+      rtf_key("plain"),
+      rtf_key("uc", 0),
+      rtf_key("q", h_align),
+      rtf_key("clvertal", v_align),
+      rtf_raw(cell_padding),
+      rtf_raw(cell_borders),
+      rtf_raw(cell_background_color),
+      rtf_raw(cell_merging)
+    )
+
+  # Combine all cell content
+  cell_content <-
+    rtf_paste0(
+      rtf_key("intbl"),
+      " ",
+      cell_text,
+      rtf_key("cell"), "\n",
+      rtf_key("pard"),
+      rtf_key("plain")
+    )
+
+  # Return a complete RTF table cell (marked as `rtf_text`)
+  rtf_paste0(cell_settings, "\n", cell_content)
+}
+
+rtf_font <- function(...,
+                     font = NULL,
+                     font_size = NULL,
+                     font_color = NULL,
+                     bold = FALSE,
+                     italic = FALSE,
+                     super_sub = NULL) {
+
+  # Obtain font-specific settings
+  font_styles <-
+    rtf_font_styling(
+      font = font,
+      font_size = font_size,
+      font_color = font_color,
+      bold = bold,
+      italic = italic,
+      super_sub = super_sub
+    )
+
+  rtf_paste0(rtf_raw("{"), rtf_raw(font_styles), " ", ..., rtf_raw("}"))
+}
+
+# Mark the given text as being RTF, meaning, it should not be escaped if passed
+# to rtf_text
+rtf_raw <- function(...) {
+  text <- paste0(..., collapse = "")
+  class(text) <- "rtf_text"
+  text
+}
+
+# Transform a footnote mark to an RTF representation as a superscript
+footnote_mark_to_rtf <- function(mark) {
+  rtf_paste0(rtf_raw("{\\super \\i "), mark, rtf_raw("}"))
+}
+
+rtf_escape <- function(x) {
+
+  if (length(x) < 1) return(x)
+
+  x <- gsub("\\", "\\'5c", x, fixed = TRUE)
+  x <- gsub("{", "\\'7b", x, fixed = TRUE)
+  x <- gsub("}", "\\'7d", x, fixed = TRUE)
+  x <- vapply(x, FUN.VALUE = character(1), FUN = rtf_escape_unicode, USE.NAMES = FALSE)
+  class(x) <- "rtf_text"
+  x
+}
+
+rtf_escape_unicode <- function(x) {
+
+  # Ensure that we encode non-UTF-8 strings to UTF-8 in a
+  # two-step process: (1) to UTF-8, (2) to RTF's weird signed
+  # 16 bit integer encoding
+  if (Encoding(x) != 'UTF-8') {
+    x <- enc2utf8(x)
+  }
+
+  chars <- unlist(strsplit(x, ""))
+  codepoints <- utf8ToInt(x)
+  needs_escape <- codepoints > 127
+  codepoints_subset <- codepoints[needs_escape]
+
+  # RTF wants the code points as signed 16 bit integers
+  codepoints_subset_signed <- ifelse(
+    codepoints_subset > 2^15-1,
+    -(bitops::bitFlip(codepoints_subset, 16) + 1), # twos complement
+    codepoints_subset)
+
+  chars[needs_escape] <- paste0("\\u", codepoints_subset_signed, " ")
+  paste(chars, collapse = "")
+}
+
+rtf_font_styling <- function(font = NULL,
+                             font_size = NULL,
+                             font_color = NULL,
+                             bold = FALSE,
+                             italic = FALSE,
+                             super_sub = NULL) {
+
+  # Set font for text
+  if (!is.null(font)) {
+    cell_font <- rtf_key("f", rtf_paste0(rtf_raw("<<FONT:"), font, rtf_raw(">>")))
+  } else {
+    cell_font <- rtf_key("f", 0)
+  }
+
+  # Set font size for text (in half-points)
+  if (!is.null(font_size)) {
+    cell_font_size <- rtf_key("fs", font_size * 2)
+  } else {
+    cell_font_size <- ""
+  }
+
+  # Set font color
+  if (!is.null(font_color)) {
+    cell_font_color <- rtf_key("cf", rtf_paste0(rtf_raw("<<COLOR:"), font_color, rtf_raw(">>")))
+  } else {
+    cell_font_color <- ""
+  }
+
+  # Optionally set bold type
+  if (bold) {
+    cell_bold <- rtf_key("b")
+  } else {
+    cell_bold <- ""
+  }
+
+  # Optionally set italic type
+  if (italic) {
+    cell_italic <- rtf_key("i")
+  } else {
+    cell_italic <- ""
+  }
+
+  # Set font superscripting or subscripting
+  if (!is.null(super_sub)) {
+    if (super_sub == "super") {
+      cell_super_sub <- rtf_key("super")
+    } else if (super_sub == "sub") {
+      cell_super_sub <- rtf_key("sub")
+    } else {
+      stop("The super_sub value must be either `\"super\"` or `\"sub\"`.")
+    }
+  } else {
+    cell_super_sub <- ""
+  }
+
+  rtf_paste0(
+    cell_font,
+    cell_font_size,
+    cell_font_color,
+    cell_bold,
+    cell_italic,
+    cell_super_sub
+  )
+}
+
+rtf_border <- function(direction,
+                       style = "s",
+                       width = 20,
+                       color = 0) {
+
+  if (direction == "all") {
+    direction <- c("top", "bottom", "left", "right")
+  }
+
+  rtf_border <- list()
+
+  for (dir in direction) {
+    rtf_border <-
+      append(
+        rtf_border,
+        list(
+          list(
+            direction = dir,
+            style = style,
+            width = width,
+            color = color
+          )
+        )
+      )
+  }
+
+  class(rtf_border) <- "rtf_border"
+  rtf_border
+}
+
+as_rtf_string <- function(x) {
+
+  rtf_paste0(
+    rtf_raw("{"),
+    rtf_raw(as.character(x$header)),
+    "\n",
+    rtf_raw(as.character(x$document)),
+    rtf_raw("}")
+  )
+}
+
+# This is the assumed width of the area within page
+# margins in a default Word document
+standard_width_twips <- 9468L
+
+#
+# Table Header
+#
+create_heading_component_rtf <- function(data) {
+
+  if (!dt_heading_has_title(data = data) &&
+      !dt_heading_has_subtitle(data = data)) {
+    return(list())
+  }
+
+  # Get table components and metadata using the `data`
+  heading <- dt_heading_get(data)
+  footnotes_tbl <- dt_footnotes_get(data)
+
+  # Get table options
+  table_font_color <- dt_options_get_value(data, option = "table_font_color")
+  table_border_top_include <- dt_options_get_value(data, option = "table_border_top_include")
+  table_border_top_color <- dt_options_get_value(data, option = "table_border_top_color")
+  if ("title" %in% footnotes_tbl$locname) {
+    footnote_title_marks <- footnotes_tbl %>% coalesce_marks(locname = "title")
+    footnote_title_marks <- footnote_title_marks$fs_id_c
+  } else {
+    footnote_title_marks <- ""
+  }
+
+  if ("subtitle" %in% footnotes_tbl$locname) {
+    footnote_subtitle_marks <- footnotes_tbl %>% coalesce_marks(locname = "subtitle")
+    footnote_subtitle_marks <- footnote_subtitle_marks$fs_id_c
+  } else {
+    footnote_subtitle_marks <- ""
+  }
+
+  if (dt_heading_has_subtitle(data = data)) {
+    subtitle_component <-
+      c(
+        rtf_key("line"),
+        rtf_font(
+          font_size = 8,
+          rtf_raw(heading$subtitle)
+        ),
+        rtf_font(
+          italic = TRUE,
+          super_sub = "super",
+          font_size = 8,
+          rtf_raw(footnote_subtitle_marks)
+        )
+      )
+  } else {
+    subtitle_component <- NULL
+  }
+
+  tbl_cell <-
+    rtf_tbl_cell(
+      c(
+        rtf_font(
+          font_size = 14,
+          rtf_raw(heading$title)
+        ),
+        rtf_font(
+          italic = TRUE,
+          super_sub = "super",
+          font_size = 14,
+          rtf_raw(footnote_title_marks)
+        ),
+        subtitle_component
+      ),
+      h_align = "center",
+      borders = if (table_border_top_include) list(rtf_border("top", color = table_border_top_color, width = 40)) else NULL,
+      font_color = table_font_color
+    )
+
+  # Return a list of RTF table rows (in this case, a single row)
+  list(
+    rtf_tbl_row(
+      tbl_cell,
+      height = 0,
+      repeat_header = TRUE
+    )
+  )
+}
+
+#
+# Table Column Labels
+#
+create_columns_component_rtf <- function(data) {
+
+  # Get table components and metadata using the `data`
+  boxh <- dt_boxhead_get(data)
+  spanners_present <- dt_spanners_exists(data)
+  column_labels_hidden <- dt_options_get_value(data, option = "column_labels_hidden")
+  headings_labels <- dt_boxhead_get_vars_labels_default(data = data)
+  stub_available <- dt_stub_df_exists(data)
+  stubh_available <- dt_stubhead_has_label(data)
+
+  footnotes_tbl <- dt_footnotes_get(data) # not used currently
+
+  # Get table options
+  column_labels_border_top_color <- dt_options_get_value(data = data, option = "column_labels_border_top_color")
+  column_labels_border_bottom_color <- dt_options_get_value(data = data, option = "column_labels_border_bottom_color")
+  column_labels_vlines_color <- dt_options_get_value(data = data, option = "column_labels_vlines_color")
+  column_labels_border_lr_color <- dt_options_get_value(data = data, option = "column_labels_border_lr_color") # not used currently
+
+  # Obtain alignments for each visible column label
+  col_alignment <-
+    boxh %>%
+    dplyr::filter(type == "default") %>%
+    dplyr::pull(column_align)
+
+  if (column_labels_hidden) {
+    return(list())
+  }
+
+  if (stub_available) {
+    headings_labels <- c("", headings_labels)
+    col_alignment <- c("left", col_alignment)
+  }
+
+  if (stubh_available) headings_labels[1] <- dt_stubhead_get(data = data) %>% .$label
+
+  if (isTRUE(spanners_present)) {
+
+    spanners <- dt_spanners_print(data = data, include_hidden = FALSE)
+    spanners[is.na(spanners)] <- ""
+
+    if (stub_available) {
+      spanners <- c("", spanners)
+    }
+
+    # TODO: add vertical lines separating adjacent spanner
+
+    # TODO: Need to differentiate between (1) non-merging spanners, (2) first
+    # instance of multi-column spanner, and (3) continuation of multi-column spanner
+
+    spanners_rle <- rle(spanners)$lengths
+
+    merge_keys <- c()
+    for (i in seq(spanners_rle)) {
+      if (spanners_rle[i] == 1) {
+        merge_keys <- c(merge_keys, 0)
+      } else {
+        merge_keys <- c(merge_keys, 1, rep(2, spanners_rle[i] - 1))
+      }
+    }
+
+    spanners_list <-
+      lapply(
+        seq_along(spanners), FUN = function(x) {
+          rtf_tbl_cell(
+            rtf_font(
+              font_size = 10,
+              rtf_raw(spanners[x])
+            ),
+            h_align = "center",
+            h_merge = merge_keys[x],
+            borders = list(
+              rtf_border("top", color = column_labels_border_top_color, width = 40),
+              rtf_border("bottom", color = column_labels_border_bottom_color),
+              rtf_border("left", color = column_labels_vlines_color),
+              rtf_border("right", color = column_labels_vlines_color)
+            )
+          )
+        }
+      )
+  } else {
+    spanners_list <- list()
+  }
+
+  cell_list <-
+    lapply(
+      seq_along(headings_labels), FUN = function(x) {
+        rtf_tbl_cell(
+          rtf_font(
+            font_size = 10,
+            rtf_raw(headings_labels[x])
+          ),
+          h_align = col_alignment[x],
+          borders = list(
+            rtf_border("top", color = column_labels_border_top_color, width = 40),
+            rtf_border("bottom", color = column_labels_border_bottom_color, width = 40),
+            rtf_border("left", color = column_labels_vlines_color),
+            rtf_border("right", color = column_labels_vlines_color)
+          )
+        )
+      }
+    )
+
+  if (isTRUE(spanners_present)) {
+    row_list_column_labels <-
+      list(
+        rtf_tbl_row(spanners_list, height = 0, repeat_header = TRUE),
+        rtf_tbl_row(cell_list, height = 0, repeat_header = TRUE)
+      )
+  } else {
+    row_list_column_labels <-
+      list(rtf_tbl_row(cell_list, height = 0, repeat_header = TRUE))
+  }
+
+  # Return a list of RTF table rows (either one or two rows)
+  row_list_column_labels
+}
+
+#
+# Table Body
+#
+create_body_component_rtf <- function(data) {
+
+  # Get table components and metadata using the `data`
+  body <- dt_body_get(data)
+  boxh <- dt_boxhead_get(data)
+  stubh <- dt_stubhead_get(data)
+  opts_df <- dt_options_get(data)
+  stub_available <- dt_stub_df_exists(data)
+  stub_df <- dt_stub_df_get(data)
+  groups_rows <- dt_groups_rows_get(data)
+  summaries_present <- dt_summary_exists(data = data)
+  list_of_summaries <- dt_summary_df_get(data = data)
+  groups_rows_df <- dt_groups_rows_get(data = data)
+  stub_components <- dt_stub_components(data = data)
+
+  # Get table options
+  row_group_border_top_color <- dt_options_get_value(data = data, option = "row_group_border_top_color")
+  row_group_border_bottom_color <- dt_options_get_value(data = data, option = "row_group_border_bottom_color")
+  row_group_border_left_color <- dt_options_get_value(data = data, option = "row_group_border_left_color")
+  row_group_border_right_color <- dt_options_get_value(data = data, option = "row_group_border_right_color")
+  table_body_hlines_color <- dt_options_get_value(data = data, option = "table_body_hlines_color")
+  table_body_vlines_color <- dt_options_get_value(data = data, option = "table_body_vlines_color")
+  table_border_bottom_color <- dt_options_get_value(data, option = "table_border_bottom_color")
+
+  headings_vars <- boxh %>% dplyr::filter(type == "default") %>% dplyr::pull(var)
+  row_groups_present <- nrow(groups_rows) > 0
+  row_group_rows <- groups_rows$row
+  row_group_labels <- groups_rows$group_label
+  row_group_labels[is.na(row_group_labels)] <- ""
+
+  # Obtain alignments for each values in each visible column label
+  col_alignment <-
+    boxh %>%
+    dplyr::filter(type == "default") %>%
+    dplyr::pull(column_align)
+
+  # Ensure that the columns are only the visible ones, and,
+  # that they are in order
+  body <- body %>% dplyr::select(dplyr::all_of(headings_vars))
+
+  if (stub_available) {
+
+    stub_var <- dt_boxhead_get_var_stub(data = data)
+
+    body <-
+      dplyr::bind_cols(
+        dt_body_get(data) %>% dplyr::select(dplyr::one_of(stub_var)),
+        body
+      )
+
+    col_alignment <- c("left", col_alignment)
+  }
+
+  n_cols <- ncol(body)
+  n_rows <- nrow(body)
+  row_list_body <- list()
+
+  for (i in seq_len(n_rows)) {
+
+    # Add group rows where necessary
+    if (row_groups_present && i %in% row_group_rows) {
+
+      row_list_body <-
+        c(
+          row_list_body,
+          rtf_tbl_row(
+            list(
+              rtf_tbl_cell(
+                row_group_labels[which(row_group_rows == i)],
+                font_size = 10,
+                h_align = "left",
+                borders = list(
+                  rtf_border("top", color = row_group_border_top_color, width = 40),
+                  rtf_border("bottom", color = row_group_border_bottom_color, width = 40),
+                  rtf_border("left", color = row_group_border_left_color),
+                  rtf_border("right", color = row_group_border_right_color)
+                )
+              )
+            ),
+            height = 0
+          )
+        )
+    }
+
+    cell_list <-
+      lapply(
+        seq_len(n_cols), FUN = function(x) {
+
+          rtf_tbl_cell(
+            rtf_font(
+              font_size = 10,
+              rtf_raw(body[[i, x]])
+            ),
+            h_align = col_alignment[x],
+            borders = list(
+              rtf_border("bottom", color = table_body_hlines_color, width = 10),
+              rtf_border("left", color = table_body_vlines_color, width = 10),
+              rtf_border("right", color = table_body_vlines_color, width = 10)
+            )
+          )
+        }
+      )
+
+    if (i == 1 && row_groups_present && !(i %in% row_group_rows)) {
+
+      body_row <-
+        rtf_tbl_row(
+          cell_list,
+          borders = list(
+            rtf_border(direction = "top", color = table_body_hlines_color)
+          ),
+          height = 0
+        )
+    } else {
+      body_row <- rtf_tbl_row(cell_list, height = 0)
+    }
+
+    row_list_body <- c(row_list_body, body_row)
+
+    #
+    # Add groupwise summary rows
+    #
+
+    if (stub_available && summaries_present &&
+        i %in% groups_rows_df$row_end) {
+
+      group <-
+        groups_rows_df %>%
+        dplyr::filter(row_end == i) %>%
+        dplyr::pull(group)
+
+      if (group %in% names(list_of_summaries$summary_df_display_list)) {
+
+        summary_df <-
+          list_of_summaries$summary_df_display_list[[
+            which(names(list_of_summaries$summary_df_display_list) == group)]] %>%
+          as.data.frame(stringsAsFactors = FALSE) %>%
+          dplyr::select(-matches("^group[s]?$"))
+
+        for (j in seq_len(nrow(summary_df))) {
+
+          cell_list <-
+            lapply(
+              seq_len(n_cols), FUN = function(x) {
+
+                rtf_tbl_cell(
+                  rtf_font(
+                    font_size = 10,
+                    rtf_raw(summary_df[[j, x]])
+                  ),
+                  h_align = col_alignment[x],
+                  borders = list(
+                    rtf_border(
+                      "top",
+                      style = ifelse(j == 1, "db", "s"),
+                      color = table_body_hlines_color,
+                      width = ifelse(j == 1, 20, 10)
+                    ),
+                    rtf_border("bottom", color = table_body_hlines_color, width = 10),
+                    rtf_border("left", color = table_body_vlines_color, width = 10),
+                    rtf_border("right", color = table_body_vlines_color, width = 10)
+                  )
+                )
+              }
+            )
+
+          row_list_body <-
+            c(
+              row_list_body,
+              rtf_tbl_row(cell_list, height = 0)
+            )
+        }
+      }
+    }
+  }
+
+  #
+  # Add grand summary rows
+  #
+
+  if (summaries_present &&
+      grand_summary_col %in% names(list_of_summaries$summary_df_display_list)) {
+
+    summary_df <-
+      list_of_summaries$summary_df_display_list[["::GRAND_SUMMARY"]] %>%
+      as.data.frame(stringsAsFactors = FALSE) %>%
+      dplyr::select(-matches("^group[s]?$"))
+
+    for (j in seq_len(nrow(summary_df))) {
+
+      cell_list <-
+        lapply(
+          seq_len(n_cols), FUN = function(x) {
+
+            rtf_tbl_cell(
+              rtf_font(
+                font_size = 10,
+                rtf_raw(summary_df[[j, x]])
+              ),
+              h_align = col_alignment[x],
+              borders = list(
+                rtf_border(
+                  "bottom",
+                  color = table_body_hlines_color,
+                  width = ifelse(j == nrow(summary_df), 50, 10)
+                  ),
+                rtf_border("left", color = table_body_vlines_color, width = 10),
+                rtf_border("right", color = table_body_vlines_color, width = 10)
+              )
+            )
+          }
+        )
+
+      row_list_body <-
+        c(
+          row_list_body,
+          rtf_tbl_row(
+            cell_list,
+            height = 0,
+            borders = list(
+              rtf_border(
+                "top",
+                style = ifelse(j == 1, "db", "s"),
+                color = table_body_hlines_color,
+                width = ifelse(j == 1, 50, 10)
+              )
+            ),
+          )
+        )
+    }
+  }
+
+  # Return a list of RTF table rows for the body part
+  row_list_body
+}
+
+#
+# Table Footnotes
+#
+create_footnotes_component_rtf <- function(data) {
+
+  # Get table components and metadata using the `data`
+  footnotes_tbl <- dt_footnotes_get(data)
+
+  # If the `footnotes_tbl` object has no
+  # rows, then return an empty footnotes component
+  if (nrow(footnotes_tbl) == 0) {
+    row_list_footnotes <- list()
+    return(row_list_footnotes)
+  }
+
+  footnotes_tbl <-
+    footnotes_tbl %>%
+    dplyr::select(fs_id, footnotes) %>%
+    dplyr::distinct()
+
+  n_footnotes <- nrow(footnotes_tbl)
+
+  footnote_text <- footnotes_tbl$footnotes
+  footnote_mark <- footnotes_tbl[["fs_id"]]
+
+  footnote_text <-
+    vapply(
+      footnote_text, FUN.VALUE = character(1), USE.NAMES = FALSE,
+      FUN = markdown_to_rtf
+    )
+
+  cell_list <- ""
+
+  for (i in seq_len(n_footnotes)) {
+
+    use_newline <- i != n_footnotes
+
+    cell_list <-
+      rtf_paste0(
+        cell_list,
+        rtf_font(
+          italic = TRUE,
+          super_sub = "super",
+          font_size = 10,
+          rtf_raw(footnote_mark[i])
+        ),
+        rtf_font(
+          font_size = 10,
+          rtf_raw(footnote_text[i], " ")
+        )
+      )
+  }
+
+  # Return a list of RTF table rows (a single row) for the footnotes section
+  rtf_tbl_row(list(rtf_tbl_cell(cell_list)), height = 0)
+}
+
+#
+# Table Source Notes
+#
+create_source_notes_component_rtf <- function(data) {
+
+  # Get table components and metadata using the `data`
+  source_notes <- dt_source_notes_get(data)
+
+  # If there are no source notes then return an empty list
+  if (length(source_notes) == 0) {
+    row_list_source_notes <- list()
+    return(row_list_source_notes)
+  }
+
+  n_source_notes <- length(source_notes)
+  row_list_source_notes <- list()
+
+  cell_list <- ""
+
+  for (i in seq_len(n_source_notes)) {
+
+    cell_list <-
+      rtf_paste0(
+        cell_list,
+        rtf_font(
+          font_size = 10,
+          rtf_raw(source_notes[i])
+        )
+      )
+  }
+
+  # Return a list of RTF table rows (a single row) for the source notes section
+  rtf_tbl_row(list(rtf_tbl_cell(cell_list)), height = 0)
+}
diff --git a/R/zzz.R b/R/zzz.R
index df5c85944..2dbfd4fde 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -54,6 +54,7 @@ globalVariables(
     "g",
     "green",
     "group_label",
+    "groups",
     "grpname",
     "grprow",
     "integrate_summary_lines",
diff --git a/tests/gt-examples/01-html-script/html-13-adding_footnotes.R b/tests/gt-examples/01-html-script/html-13-adding_footnotes.R
index 322dfa890..55c26e5a1 100644
--- a/tests/gt-examples/01-html-script/html-13-adding_footnotes.R
+++ b/tests/gt-examples/01-html-script/html-13-adding_footnotes.R
@@ -20,6 +20,7 @@ tbl <-
 # Create a display table
 footnotes_tbl <-
   gt(data = tbl, groupname_col = "date") %>%
+  tab_header(title = "The Table Title", subtitle = "The subtitle.") %>%
   tab_spanner(
     label = "values",
     columns = starts_with("value")
@@ -51,6 +52,14 @@ footnotes_tbl <-
   tab_footnote(
     footnote = md("`value_1` is the first column of values."),
     locations = cells_column_labels(columns = vars(value_1))
+  ) %>%
+  tab_footnote(
+    footnote = md("The `title` can get a footnote."),
+    locations = cells_title(groups = "title")
+  ) %>%
+  tab_footnote(
+    footnote = md("The `subtitle` can likewise get a footnote."),
+    locations = cells_title(groups = "subtitle")
   )
 
 footnotes_tbl
diff --git a/tests/gt-examples/04-rtf/rtf_tests.R b/tests/gt-examples/04-rtf/rtf_tests.R
new file mode 100644
index 000000000..627995ec8
--- /dev/null
+++ b/tests/gt-examples/04-rtf/rtf_tests.R
@@ -0,0 +1,508 @@
+library(gt)
+library(tidyverse)
+library(readr)
+
+# Create a display table that uses markdown
+"- item 1\n- item 2\n\n" -> markdown_text
+"**bold** text<sup>2</sup>" -> markdown_text
+
+commonmark::markdown_xml(markdown_text) %>% cat()
+gt:::markdown_to_rtf(markdown_text) %>% cat()
+
+md_tbl <-
+  dplyr::tibble(markdown = markdown_text) %>%
+  gt() %>%
+  fmt_markdown(vars(markdown)) %>%
+  tab_options(
+    table.width = pct(100)
+  )
+
+out_path <- "tests/gt-examples/rtf_output/md.rtf"
+
+md_tbl %>% gtsave(out_path)
+
+readr::read_file(out_path) %>% cat()
+
+unicode_tbl <-
+  dplyr::tibble(a = "a\u2014b", b = "**bold** \u2014") %>%
+  gt() %>%
+  fmt_markdown(columns = vars(b)) %>%
+  tab_header(title = "title a\u2014b", subtitle = "subtitle a\u2014b") %>%
+  tab_source_note("source note a\u2014b") %>%
+  tab_footnote("footnote a\u2014b", locations = cells_body(1, 1))
+
+unicode_tbl %>% gtsave("tests/gt-examples/rtf_output/unicode.rtf")
+
+# Create a display table based on `iris`
+iris_tbl <-
+  gt(data = iris) %>%
+  tab_spanner_delim(delim = ".") %>%
+  cols_move_to_start(columns = vars(Species)) %>%
+  fmt_number(
+    columns = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width),
+    decimals = 1
+  ) %>%
+  tab_header(
+    title = md("The **iris** dataset"),
+    subtitle = md("[All about *Iris setosa*, *versicolor*, and *virginica*]")
+  ) %>%
+  tab_source_note(
+    source_note = "The data were collected by Anderson (1935)."
+  ) %>%
+  tab_footnote("Hello!", cells_title("title"))
+
+iris_tbl %>% gtsave("tests/gt-examples/rtf_output/iris.rtf")
+
+# Create two display tables based on `exibble`
+exibble_tbl <-
+  exibble %>%
+  dplyr::mutate(char = paste(">", char)) %>%
+  gt() %>%
+  fmt_markdown(vars(char))
+
+exibble_tbl %>%  gtsave("tests/gt-examples/rtf_output/exibble.rtf")
+
+passthrough_tbl <-
+  exibble %>%
+  gt() %>%
+  fmt_passthrough(columns = vars(char), pattern = "1 {x} 2")
+
+passthrough_tbl %>%  gtsave("tests/gt-examples/rtf_output/passthrough.rtf")
+
+# Create a display table based on `morley`
+morley_tbl <-
+  gt(data = morley) %>%
+  fmt_number(
+    columns = vars(Speed),
+    decimals = 0,
+    sep_mark = ",") %>%
+  cols_align(align = "left", columns = vars(Run, Speed))
+
+morley_tbl %>% gtsave("tests/gt-examples/rtf_output/morley.rtf")
+
+# Create a display table based on `pressure`
+pressure_tbl <-
+  gt(data = pressure) %>%
+  fmt_scientific(
+    columns = vars(pressure),
+    decimals = 2
+  )
+
+pressure_tbl %>% gtsave("tests/gt-examples/rtf_output/pressure.rtf")
+
+# Create a display table based on `sleep`
+sleep_tbl <-
+  gt(data = sleep) %>%
+  fmt_scientific(columns = vars(extra)) %>%
+  tab_footnote(
+    footnote = "This is a footnote",
+    locations = cells_body(columns = 1, rows = c(2, 3, 4))
+  )
+
+sleep_tbl %>% gtsave("tests/gt-examples/rtf_output/sleep.rtf")
+
+# Create a display table based on `airquality`
+airquality_tbl <-
+  gt(data = airquality) %>%
+  cols_move_to_start(columns = vars(Month, Day)) %>%
+  cols_label(Solar.R = md("Solar  \nRadiation")) %>%
+  fmt_number(
+    columns = vars(Wind),
+    decimals = 2
+  ) %>%
+  cols_label(Month = md("**Month**")) %>%
+  tab_spanner(
+    label = "Measurement Period",
+    columns = vars(Month, Day)
+  ) %>%
+  fmt_missing(columns = vars(Solar.R, Wind, Temp)) %>%
+  fmt_missing(columns = vars(Ozone), missing_text = I("---"))
+
+airquality_tbl %>% gtsave("tests/gt-examples/rtf_output/airquality.rtf")
+
+sp500_tbl <-
+  readr::read_csv(
+    system.file("extdata", "sp500.csv", package = "gt"),
+    col_types = "cddddd"
+  ) %>%
+  gt() %>%
+  fmt_date(
+    columns = vars(Date),
+    date_style = 6
+  ) %>%
+  fmt_currency(
+    columns = vars(High, Open, Low, Close),
+    currency = "USD",
+    scale_by = 1/1000,
+    pattern = "{x}K"
+  ) %>%
+  fmt_number(
+    columns = vars(Volume),
+    decimals = 3,
+    scale_by = 1E-9,
+    pattern = "{x}B"
+  )
+
+sp500_tbl %>% gtsave("tests/gt-examples/rtf_output/sp500.rtf")
+
+# Input table
+tbl <-
+  dplyr::tribble(
+    ~groups,  ~rowname, ~value,  ~value_2,
+    "A",      "1",      NA,      260.1,
+    "A",      "2",      184.3,   84.4,
+    "A",      "3",      342.3,   126.3,
+    "A",      "4",      234.9,   NA,
+    "B",      "1",      190.9,   832.5,
+    "B",      "2",      743.3,   281.2,
+    "B",      "3",      252.3,   732.5,
+    "B",      "4",      344.7,   NA,
+    "C",      "1",      197.2,   818.0,
+    "C",      "2",      284.3,   394.4
+  )
+
+# Create a display table with summary rows
+summary_tbl <-
+  tbl %>%
+  gt(groupname_col = "groups") %>%
+  summary_rows(
+    groups = c("A", "C"),
+    columns = vars(value),
+    fns = list(
+      ~mean(., na.rm = TRUE),
+      ~sum(., na.rm = TRUE),
+      ~sd(., na.rm = TRUE)
+    )
+  ) %>%
+  grand_summary_rows(
+    columns = vars(value_2),
+    fns = list(
+      ~mean(., na.rm = TRUE),
+      ~sum(., na.rm = TRUE),
+      ~sd(., na.rm = TRUE)
+    )
+  ) %>%
+  tab_footnote(
+    footnote = "Note for Summary A.",
+    locations = cells_summary(
+      groups = "A", columns = 1, rows = 1)
+  ) %>%
+  tab_footnote(
+    footnote = "Note for Summary C.",
+    locations = cells_summary(
+      groups = "C", columns = 1, rows = 1)
+  ) %>%
+  fmt_missing(columns = vars(value, value_2)) %>%
+  tab_options(
+    summary_row.background.color = "#FFFEEE",
+    row_group.background.color = "lightblue"
+  )
+
+summary_tbl %>% gtsave("tests/gt-examples/rtf_output/summary.rtf")
+
+# Create a table with values and uncertainties
+tbl <-
+  dplyr::tribble(
+    ~value_1, ~uncertainty, ~value_2, ~uncertainty_2,
+    0.352,    0.10,         0.32,     NA_real_,
+    0.983,    0.13,         NA_real_, NA_real_,
+    0.639,    NA_real_,     0.21,     0.10,
+    NA_real_, 0.17,         0.74,     0.15
+  )
+
+# Create a display table with uncertainties
+uncert_tbl <-
+  gt(data = tbl) %>%
+  cols_merge_uncert(
+    col_val = vars(value_1),
+    col_uncert = vars(uncertainty)
+  ) %>%
+  cols_merge_uncert(
+    col_val = vars(value_2),
+    col_uncert = vars(uncertainty_2)
+  ) %>%
+  fmt_number(
+    columns = vars(value_1, value_2),
+    decimals = 2
+  ) %>%
+  fmt_missing(columns = vars(value_1, value_2))
+
+uncert_tbl %>% gtsave("tests/gt-examples/rtf_output/uncert.rtf")
+
+# Create a table where rows are formatted conditionally
+conditional_tbl <-
+  readr::read_csv(
+    system.file("extdata", "sp500.csv", package = "gt"),
+    col_types = "cddddd"
+  ) %>%
+  gt() %>%
+  fmt_number(
+    columns = vars(Open),
+    rows = Open > 1900,
+    decimals = 3,
+    scale_by = 1/1000,
+    pattern = "{x}K"
+  ) %>%
+  fmt_number(
+    columns = vars(Close),
+    rows = High < 1940 & Low > 1915,
+    decimals = 3
+  ) %>%
+  fmt_currency(
+    columns = vars(High, Low, Close),
+    rows = Date > "2016-02-20",
+    currency = "USD"
+  )
+
+conditional_tbl %>% gtsave("tests/gt-examples/rtf_output/conditional.rtf")
+
+# Create a table that has a stubhead label
+tbl <-
+  dplyr::tribble(
+    ~groups, ~rowname, ~value_1, ~value_2,
+    "A",        "1",      361.1,    260.1,
+    "A",        "2",      184.3,    84.4,
+    "A",        "3",      342.3,    126.3,
+    "A",        "4",      234.9,    37.1,
+    "B",        "1",      190.9,    832.5,
+    "B",        "2",      743.3,    281.2,
+    "B",        "3",      252.3,    732.5,
+    "B",        "4",      344.7,    281.2,
+    "C",        "1",      197.2,    818.0,
+    "C",        "2",      284.6,    394.4
+  )
+
+# Create a display table
+sh_caption_tbl <-
+  tbl %>%
+  gt(groupname_col = "groups") %>%
+  tab_stubhead(label = "groups")
+
+sh_caption_tbl %>% gtsave("tests/gt-examples/rtf_output/sh_caption.rtf")
+
+
+# Create a table with footnotes in various cell types
+tbl <-
+  dplyr::tribble(
+    ~date,        ~rowname,  ~value_1,  ~value_2,
+    "2018-02-10", "1",       20.4,      361.1,
+    "2018-02-10", "2",       10.9,      743.3,
+    "2018-02-10", "3",       34.6,      344.7,
+    "2018-02-10", "4",        8.3,      342.3,
+    "2018-02-11", "5",       28.3,      234.9,
+    "2018-02-11", "6",       75.5,      190.9,
+    "2018-02-11", "7",       63.1,        2.3,
+    "2018-02-11", "8",       25.8,      184.3,
+    "2018-02-11", "9",        5.2,      197.2,
+    "2018-02-11", "10",      55.3,      284.6
+  )
+
+# Create a display table
+footnotes_tbl <-
+  gt(data = tbl, groupname_col = "date") %>%
+  tab_header(title = md("The Table `Title`"), subtitle = "The subtitle.") %>%
+  tab_spanner(
+    label = "values",
+    columns = starts_with("value")
+  ) %>%
+  tab_footnote(
+    footnote = "This is an even smaller number.",
+    locations = cells_body(columns = vars(value_1), rows = 9)
+  ) %>%
+  tab_footnote(
+    footnote = "This is a small number.",
+    locations = cells_body(columns = vars(value_1), rows = 4)
+  ) %>%
+  tab_footnote(
+    footnote = "First data cell.",
+    locations = cells_body(columns = "value_1", rows = 1)
+  ) %>%
+  tab_footnote(
+    footnote = "The first row group",
+    locations = cells_row_groups(groups = ends_with("10"))
+  ) %>%
+  tab_footnote(
+    footnote = "Two sets of values",
+    locations = cells_column_spanners(spanners = starts_with("val"))
+  ) %>%
+  tab_footnote(
+    footnote = "A stub cell.",
+    locations = cells_stub(rows = 1)
+  ) %>%
+  tab_footnote(
+    footnote = md("`value_1` is the first column of values."),
+    locations = cells_column_labels(columns = vars(value_1))
+  ) %>%
+  tab_footnote(
+    footnote = md("The `title` can get a footnote."),
+    locations = cells_title(groups = "title")
+  ) %>%
+  tab_footnote(
+    footnote = md("The `subtitle` can likewise get a footnote."),
+    locations = cells_title(groups = "subtitle")
+  )
+
+footnotes_tbl %>% gtsave("tests/gt-examples/rtf_output/footnotes.rtf")
+
+# Create a table with spanner column labels
+tbl <-
+  dplyr::tribble(
+    ~v_1, ~v_2, ~v_3, ~v_4, ~v_5,
+    20.4, 36.1, 34.2, 21.6, 23.1,
+    25.8, 14.3, 13.7, 12.9, 75.9,
+    16.3, 34.3, 15.1, 93.2, 12.1
+  )
+
+# Create a display table
+spanner_tbl <-
+  gt(data = tbl) %>%
+  tab_spanner(
+    label = "v_1_2",
+    columns =  c("v_1", "v_2")
+  ) %>%
+  tab_spanner(
+    label = "v_4_5",
+    columns = c("v_4", "v_5")
+  ) %>%
+  cols_move_to_start(columns = "v_3")
+
+spanner_tbl %>% gtsave("tests/gt-examples/rtf_output/spanner.rtf")
+
+# Create a display table where individual table cells are styled
+tbl <-
+  dplyr::tribble(
+    ~rowname, ~value,  ~value_2,
+    "1",      361.1,   260.1,
+    "2",      184.3,   84.4,
+    "3",      342.3,   126.3,
+    "4",      234.9,   37.1,
+    "1",      190.9,   832.5,
+    "2",      743.3,   281.2,
+    "3",      252.3,   732.5,
+    "4",      344.7,   281.2
+  )
+
+# Create a display table
+cell_styles_tbl <-
+  gt(tbl) %>%
+  tab_style(
+    style = cell_text(size = px(28)),
+    locations = cells_column_labels(
+      columns = c("value", "value_2"))
+  ) %>%
+  tab_style(
+    style = list(
+      cell_fill(color = "orange"),
+      cell_text(color = "white")
+    ),
+    locations = cells_body(
+      columns = vars(value, value_2),
+      rows = 1
+    )
+  )
+
+cell_styles_tbl %>% gtsave("tests/gt-examples/rtf_output/cell_styles.rtf")
+
+
+# Create a table with options applied to every type of table part
+tbl <-
+  dplyr::tribble(
+    ~date,         ~rowname, ~col_1, ~col_2, ~col_3, ~col_4,
+    "2018-02-10",  "1",       767.6,  928.1,  382.0,  674.5,
+    "2018-02-10",  "2",       403.3,  461.5,   15.1,  242.8,
+    "2018-02-10",  "3",       686.4,   54.1,  282.7,   56.3,
+    "2018-02-10",  "4",       662.6,  148.8,  984.6,  928.1,
+    "2018-02-11",  "5",       198.5,   65.1,  127.4,  219.3,
+    "2018-02-11",  "6",       132.1,  118.1,   91.2,  874.3,
+    "2018-02-11",  "7",       349.7,  307.1,  566.7,  542.9,
+    "2018-02-11",  "8",        63.7,  504.3,  152.0,  724.5,
+    "2018-02-11",  "9",       105.4,  729.8,  962.4,  336.4,
+    "2018-02-11",  "10",      924.2,  424.6,  740.8,  104.2
+  )
+
+# Create a display table
+many_options_tbl <-
+  tbl %>%
+  gt(groupname_col = "date") %>%
+  tab_header(
+    title = "The Title",
+    subtitle = "The Subtitle"
+  ) %>%
+  tab_stubhead(label = "Stubhead Label") %>%
+  tab_spanner(
+    label = "Group 1",
+    columns = vars(col_1, col_2)
+  ) %>%
+  tab_spanner(
+    label = "Group 2",
+    columns = vars(col_3, col_4)
+  ) %>%
+  tab_footnote(
+    footnote = "Footnote #1",
+    locations = cells_body(
+      columns = vars(col_1), rows = 1
+    )
+  ) %>%
+  tab_footnote(
+    footnote = "Footnote #2",
+    locations = cells_body(
+      columns = vars(col_2), rows = 2
+    )
+  ) %>%
+  tab_footnote(
+    footnote = "Footnote #3",
+    locations = cells_body(
+      columns = vars(col_3), rows = 3
+    )
+  ) %>%
+  tab_footnote(
+    footnote = "Footnote #4",
+    locations = cells_body(
+      columns = vars(col_4), rows = 4
+    )
+  ) %>%
+  tab_source_note("A source note for the table.") %>%
+  tab_options(
+    table.font.size = px(14),            # Entire table's font size
+    table.background.color = "aliceblue",# Entire table's background color
+    table.width = px(360),               # Entire table's width
+    table.border.top.style = "solid",    # Top line of table - style
+    table.border.top.width = px(3),      # Top line of table - width
+    table.border.top.color = "#99AA22",   # Top line of table - color
+    heading.background.color = "lightblue",   # Heading background color
+    heading.title.font.size = px(18),         # Title of heading font size
+    heading.subtitle.font.size = px(14),      # Subtitle font size
+    heading.border.bottom.style = "solid",    # Bottom line of heading - style
+    heading.border.bottom.width = px(5),      # Bottom line of heading - width
+    heading.border.bottom.color = "purple",   # Bottom line of heading - color
+    column_labels.font.size = px(16),                # Column labels - font size
+    column_labels.font.weight = "normal",            # Column labels - font weight
+    column_labels.background.color = "olivedrab",    # Column labels background color
+    row_group.background.color = "green",        # Row group background color
+    row_group.font.size = px(14),                # Row group labels - font size
+    row_group.font.weight = "800",               # Row group labels - font weight
+    row_group.border.top.style = "solid",        # Top line of row group - style
+    row_group.border.top.width = px(5),          # Top line of row group - width
+    row_group.border.top.color = "#FF3388",         # Top line of row group - color
+    row_group.border.bottom.style = "solid",     # Bottom line of row group - style
+    row_group.border.bottom.width = px(4),       # Bottom line of row group - width
+    row_group.border.bottom.color = "#229900",    # Bottom line of row group - color
+    table_body.border.top.style = "solid",          # Top line of table body - style
+    table_body.border.top.width = px(5),            # Top line of table body - width
+    table_body.border.top.color = "chocolate1",     # Top line of table body - color
+    table_body.border.bottom.style = "solid",       # Bottom line of table body - style
+    table_body.border.bottom.width = px(5),         # Bottom line of table body - width
+    table_body.border.bottom.color = "turquoise",   # Bottom line of table body - color
+    data_row.padding = px(8),                     # Padding of all data rows (stub & table body)
+    summary_row.background.color = "pink",     # background color of all summary rows (stub & table body)
+    summary_row.padding = px(3),               # padding of all summary rows (stub & table body)
+    summary_row.text_transform = "lowercase",  # text transform on all summary row labels
+    footnotes.font.size = px(12),           # text size of the footnotes block
+    footnotes.padding = px(3),              # padding of the footnotes block
+    source_notes.font.size = px(12),    # text size of the source notes block
+    source_notes.padding = px(3)        # padding of the source note block
+  )
+
+many_options_tbl %>% gtsave("tests/gt-examples/rtf_output/many_options.rtf")
+
+
diff --git a/tests/gt-examples/rtf_output/airquality.rtf b/tests/gt-examples/rtf_output/airquality.rtf
new file mode 100644
index 000000000..72f3ae9e4
--- /dev/null
+++ b/tests/gt-examples/rtf_output/airquality.rtf
@@ -0,0 +1,4343 @@
+{\rtf\ansi\ansicpg1252{\fonttbl{\f0\froman\fcharset0\fprq0 Calibri;}{\f1\froman\fcharset0\fprq0 Courier;}}{\colortbl;\red211\green211\blue211;}
+
+\trowd\trrh0\trhdr
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw20\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\clmgf\cellx1578
+\intbl {\f0 {\f0\fs20 Measurement Period}}\cell
+\pard\plain
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw20\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\clmrg\cellx3156
+\intbl {\f0 {\f0\fs20 Measurement Period}}\cell
+\pard\plain
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw20\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\clmgf\cellx4734
+\intbl {\f0 {\f0\fs20 }}\cell
+\pard\plain
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw20\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\clmrg\cellx6312
+\intbl {\f0 {\f0\fs20 }}\cell
+\pard\plain
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw20\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\clmrg\cellx7890
+\intbl {\f0 {\f0\fs20 }}\cell
+\pard\plain
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw20\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\clmrg\cellx9468
+\intbl {\f0 {\f0\fs20 }}\cell
+\pard\plain
+
+\row
+
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diff --git a/tests/gt-examples/rtf_output/cell_styles.rtf b/tests/gt-examples/rtf_output/cell_styles.rtf
new file mode 100644
index 000000000..4c39f4dc0
--- /dev/null
+++ b/tests/gt-examples/rtf_output/cell_styles.rtf
@@ -0,0 +1,147 @@
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diff --git a/tests/gt-examples/rtf_output/conditional.rtf b/tests/gt-examples/rtf_output/conditional.rtf
new file mode 100644
index 000000000..b4dc0a24d
--- /dev/null
+++ b/tests/gt-examples/rtf_output/conditional.rtf
@@ -0,0 +1,283 @@
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diff --git a/tests/gt-examples/rtf_output/exibble.rtf b/tests/gt-examples/rtf_output/exibble.rtf
new file mode 100644
index 000000000..90f10c68a
--- /dev/null
+++ b/tests/gt-examples/rtf_output/exibble.rtf
@@ -0,0 +1,363 @@
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diff --git a/tests/gt-examples/rtf_output/footnotes.rtf b/tests/gt-examples/rtf_output/footnotes.rtf
new file mode 100644
index 000000000..90983e6fe
--- /dev/null
+++ b/tests/gt-examples/rtf_output/footnotes.rtf
@@ -0,0 +1,227 @@
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diff --git a/tests/gt-examples/rtf_output/iris.rtf b/tests/gt-examples/rtf_output/iris.rtf
new file mode 100644
index 000000000..815c44eda
--- /dev/null
+++ b/tests/gt-examples/rtf_output/iris.rtf
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diff --git a/tests/gt-examples/rtf_output/many_options.rtf b/tests/gt-examples/rtf_output/many_options.rtf
new file mode 100644
index 000000000..c5170739c
--- /dev/null
+++ b/tests/gt-examples/rtf_output/many_options.rtf
@@ -0,0 +1,331 @@
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diff --git a/tests/gt-examples/rtf_output/md.rtf b/tests/gt-examples/rtf_output/md.rtf
new file mode 100644
index 000000000..60ceb407f
--- /dev/null
+++ b/tests/gt-examples/rtf_output/md.rtf
@@ -0,0 +1,19 @@
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diff --git a/tests/gt-examples/rtf_output/morley.rtf b/tests/gt-examples/rtf_output/morley.rtf
new file mode 100644
index 000000000..4a3b204fa
--- /dev/null
+++ b/tests/gt-examples/rtf_output/morley.rtf
@@ -0,0 +1,1619 @@
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diff --git a/tests/gt-examples/rtf_output/passthrough.rtf b/tests/gt-examples/rtf_output/passthrough.rtf
new file mode 100644
index 000000000..0d6bc563e
--- /dev/null
+++ b/tests/gt-examples/rtf_output/passthrough.rtf
@@ -0,0 +1,363 @@
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diff --git a/tests/gt-examples/rtf_output/pressure.rtf b/tests/gt-examples/rtf_output/pressure.rtf
new file mode 100644
index 000000000..04b770ed7
--- /dev/null
+++ b/tests/gt-examples/rtf_output/pressure.rtf
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diff --git a/tests/gt-examples/rtf_output/sh_caption.rtf b/tests/gt-examples/rtf_output/sh_caption.rtf
new file mode 100644
index 000000000..12eef549b
--- /dev/null
+++ b/tests/gt-examples/rtf_output/sh_caption.rtf
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diff --git a/tests/gt-examples/rtf_output/sleep.rtf b/tests/gt-examples/rtf_output/sleep.rtf
new file mode 100644
index 000000000..a020cb359
--- /dev/null
+++ b/tests/gt-examples/rtf_output/sleep.rtf
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diff --git a/tests/gt-examples/rtf_output/sp500.rtf b/tests/gt-examples/rtf_output/sp500.rtf
new file mode 100644
index 000000000..4a9b8c1ed
--- /dev/null
+++ b/tests/gt-examples/rtf_output/sp500.rtf
@@ -0,0 +1,283 @@
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diff --git a/tests/gt-examples/rtf_output/spanner.rtf b/tests/gt-examples/rtf_output/spanner.rtf
new file mode 100644
index 000000000..78b39d1f9
--- /dev/null
+++ b/tests/gt-examples/rtf_output/spanner.rtf
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diff --git a/tests/gt-examples/rtf_output/summary.rtf b/tests/gt-examples/rtf_output/summary.rtf
new file mode 100644
index 000000000..8628ec7bc
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+
+}
diff --git a/tests/gt-examples/rtf_output/uncert.rtf b/tests/gt-examples/rtf_output/uncert.rtf
new file mode 100644
index 000000000..8f34ace16
--- /dev/null
+++ b/tests/gt-examples/rtf_output/uncert.rtf
@@ -0,0 +1,63 @@
+{\rtf\ansi\ansicpg1252{\fonttbl{\f0\froman\fcharset0\fprq0 Calibri;}{\f1\froman\fcharset0\fprq0 Courier;}}{\colortbl;\red211\green211\blue211;}
+
+\trowd\trrh0\trhdr
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw40\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\cellx4734
+\intbl {\f0 {\f0\fs20 value_1}}\cell
+\pard\plain
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\clbrdrb\brdrs\brdrw40\brdrcf1\clbrdrl\brdrs\brdrw20\brdrcf1\clbrdrr\brdrs\brdrw20\brdrcf1\cellx9468
+\intbl {\f0 {\f0\fs20 value_2}}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx4734
+\intbl {\f0 {\f0\fs20 0.35 \'b1 0.10}}\cell
+\pard\plain
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx9468
+\intbl {\f0 {\f0\fs20 0.32}}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx4734
+\intbl {\f0 {\f0\fs20 0.98 \'b1 0.13}}\cell
+\pard\plain
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx9468
+\intbl {\f0 {\f0\fs20 \'97}}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx4734
+\intbl {\f0 {\f0\fs20 0.64}}\cell
+\pard\plain
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx9468
+\intbl {\f0 {\f0\fs20 0.21 \'b1 0.10}}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx4734
+\intbl {\f0 {\f0\fs20 \'97}}\cell
+\pard\plain
+
+\pard\plain\uc0\qr\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf1\clbrdrl\brdrs\brdrw10\brdrcf1\clbrdrr\brdrs\brdrw10\brdrcf1\cellx9468
+\intbl {\f0 {\f0\fs20 0.74 \'b1 0.15}}\cell
+\pard\plain
+
+\row
+
+}
diff --git a/tests/gt-examples/rtf_output/unicode.rtf b/tests/gt-examples/rtf_output/unicode.rtf
new file mode 100644
index 000000000..4021431f1
--- /dev/null
+++ b/tests/gt-examples/rtf_output/unicode.rtf
@@ -0,0 +1,51 @@
+{\rtf\ansi\ansicpg1252{\fonttbl{\f0\froman\fcharset0\fprq0 Calibri;}{\f1\froman\fcharset0\fprq0 Courier;}}{\colortbl;\red168\green168\blue168;\red51\green51\blue51;\red211\green211\blue211;}
+
+\trowd\trrh0\trhdr
+
+\pard\plain\uc0\qc\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf1\cellx9468
+\intbl {\f0\cf2 {\f0\fs28 title a\u8212 b} {\f0\fs28\i\super } \line {\f0\fs16 subtitle a\u8212 b} {\f0\fs16\i\super }}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0\trhdr
+
+\pard\plain\uc0\ql\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf3\clbrdrb\brdrs\brdrw40\brdrcf3\clbrdrl\brdrs\brdrw20\brdrcf3\clbrdrr\brdrs\brdrw20\brdrcf3\cellx4734
+\intbl {\f0 {\f0\fs20 a}}\cell
+\pard\plain
+
+\pard\plain\uc0\ql\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrt\brdrs\brdrw40\brdrcf3\clbrdrb\brdrs\brdrw40\brdrcf3\clbrdrl\brdrs\brdrw20\brdrcf3\clbrdrr\brdrs\brdrw20\brdrcf3\cellx9468
+\intbl {\f0 {\f0\fs20 b}}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\ql\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf3\clbrdrl\brdrs\brdrw10\brdrcf3\clbrdrr\brdrs\brdrw10\brdrcf3\cellx4734
+\intbl {\f0 {\f0\fs20 a\u8212 b{\super \i 1}}}\cell
+\pard\plain
+
+\pard\plain\uc0\ql\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\clbrdrb\brdrs\brdrw10\brdrcf3\clbrdrl\brdrs\brdrw10\brdrcf3\clbrdrr\brdrs\brdrw10\brdrcf3\cellx9468
+\intbl {\f0 {\f0\fs20 {\b bold} \u8212 }}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\ql\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\cellx9468
+\intbl {\f0 {\f0\fs20\i\super 1}{\f0\fs20 footnote a\u8212 b }}\cell
+\pard\plain
+
+\row
+
+\trowd\trrh0
+
+\pard\plain\uc0\ql\clvertalc\clpadb50\clpadfb3\clpadr50\clpadfr3\clpadl50\clpadfl3\clpadt50\clpadft3\cellx9468
+\intbl {\f0 {\f0\fs20 source note a\u8212 b}}\cell
+\pard\plain
+
+\row
+
+}
diff --git a/tests/testthat/test-table_parts.R b/tests/testthat/test-table_parts.R
index e624e7536..721a7dc74 100644
--- a/tests/testthat/test-table_parts.R
+++ b/tests/testthat/test-table_parts.R
@@ -42,7 +42,7 @@ test_that("a gt table contains the expected heading components", {
 
   # Expect that the `table_heading` content is 'test heading'
   tbl_html %>%
-    selection_text("[class='gt_heading gt_title gt_font_normal']") %>%
+    selection_text("[class='gt_heading gt_title gt_font_normal gt_bottom_border']") %>%
     expect_equal("test heading")
 
   # Expect that the number of rows with `class='gt_row gt_right'` is `5`
diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R
new file mode 100644
index 000000000..a2022d6ea
--- /dev/null
+++ b/tests/testthat/test-utils.R
@@ -0,0 +1,149 @@
+md_rtf <- function(md, rtf) {
+  expect_equal(markdown_to_rtf(md), unclass(rtf_raw(rtf)))
+}
+
+rtf_with <- function(open, text, close = paste0(open, "0")) {
+  paste0("\\", open, " ", text, "\\", close, " ")
+}
+
+test_that("basic markdown_to_rtf works", {
+
+  # list
+  md_rtf(
+    "1. First item\n2. Second item\n3. Third item",
+    "\\pard\\intbl\\itap1\\li300\\fi-300 \\ls1\\ilvl0\\cf0 \n{\\listtext\t}First item\\\n{\\listtext\t}Second item\\\n{\\listtext\t}Third item\\\n"
+  )
+  md_rtf(
+    "- First item\n- Second item\n- Third item",
+    "\\pard\\intbl\\itap1\\li300\\fi-300 \\ls1\\ilvl0\\cf0 \n{\\listtext\t}\\u8226  First item\\\n{\\listtext\t}\\u8226  Second item\\\n{\\listtext\t}\\u8226  Third item\\\n"
+  )
+
+  # item
+  md_rtf("test &amp; &#x21e8;&#x9034;", "test & \\u8680 \\u-28620 ")
+
+  # code_block
+  md_rtf("    aaa\nbbb\n", "{\\f1 aaa\n}{bbb}")
+  md_rtf("        foo\n    bar\n", "{\\f1     foo\nbar\n}")
+  md_rtf("```\n<\n >\n```\n", "{\\f1 <\n >\n}")
+  md_rtf("```\naaa\n~~~\n```\n", "{\\f1 aaa\n~~~\n}")
+  md_rtf("```r\nSys.Date()\n```\n", "{\\f1 Sys.Date()\n}")
+
+  # html_block
+  # custom_block
+
+  # paragraph
+  md_rtf("aaa\n\nbbb\n", "{aaa}{bbb}")
+  md_rtf("   aaa\nbbb\n", "aaa\n bbb")
+  md_rtf("aaa\nbbb\n\nccc\nddd\n", "{aaa\n bbb}{ccc\n ddd}")
+  md_rtf(
+    "aaa\n             bbb\n                                       ccc\n",
+    "aaa\n bbb\n ccc"
+  )
+
+  # heading
+  md_rtf("# test", "{\\ql \\f0 \\sa180 \\b \\fs36 test}")
+  md_rtf("## test", "{\\ql \\f0 \\sa180 \\b \\fs32 test}")
+  md_rtf("### test", "{\\ql \\f0 \\sa180 \\b \\fs28 test}")
+  md_rtf("#### test", "{\\ql \\f0 \\sa180 \\b \\fs24 test}")
+  md_rtf("##### test", "{\\ql \\f0 \\sa180 \\b \\fs20 test}")
+  md_rtf("###### test", "{\\ql \\f0 \\sa180 \\b \\fs16 test}")
+  md_rtf("# te*s*t", "{\\ql \\f0 \\sa180 \\b \\fs36 te{\\i s}t}")
+
+  # thematic_break
+  md_rtf("***", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("---", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("___", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf(" ___", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("  ___", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("   ___", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("   ___________________", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("- - - -    \n", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+  md_rtf("*\t*\t*\t\n", "{\\qc \\f0 \\sa180 \\emdash\\emdash\\emdash\\emdash\\emdash}")
+
+  # text
+  md_rtf("test &amp; &#x21e8;&#x9034;", "test & \\u8680 \\u-28620 ")
+
+  # softbreak
+  md_rtf("test\ntest", "test\n test")
+
+  # linebreak
+  md_rtf("test  \ntest", "test\\line test")
+
+  # code
+  md_rtf("`test`", "{\\f1 test}")
+  md_rtf("`te**s**t`", "{\\f1 te**s**t}")
+  md_rtf("`test \\`", "{\\f1 test \\'5c}")
+
+  # html_inline
+  md_rtf("Line 1.<br>Line 2.", "Line 1.\\line Line 2.")
+  md_rtf("R<sup>2</sup>", "R{\\super 2}")
+  md_rtf("C<sub>6</sub>H<sub>6</sub>", "C{\\sub 6}H{\\sub 6}")
+  md_rtf("Text can get <strong>bolder</strong>", "Text can get {\\b bolder}")
+  md_rtf("Text can get <b>bolder</b>", "Text can get {\\b bolder}")
+  md_rtf("Use <em>emphasis</em> occasionally", "Use {\\i emphasis} occasionally")
+  md_rtf("Use <i>emphasis</i> occasionally", "Use {\\i emphasis} occasionally")
+  md_rtf("It's <em><strong>important</strong></em>.", "It's {\\i {\\b important}}.")
+  md_rtf("This is <code>code</code>.", "This is {\\f1 code}.")
+  md_rtf("Line 1.<br>Line 2.", "Line 1.\\line Line 2.")
+  md_rtf("Line 1.<br />Line 2.", "Line 1.\\line Line 2.")
+  md_rtf("Line 1.<br/>Line 2.", "Line 1.\\line Line 2.")
+  md_rtf("It's *<strong>important</strong>*.", "It's {\\i {\\b important}}.")
+  md_rtf("It's _<strong>important</strong>_.", "It's {\\i {\\b important}}.")
+  md_rtf("It's <em>**important**</em>.", "It's {\\i {\\b important}}.")
+  md_rtf("It's <em>__important__</em>.", "It's {\\i {\\b important}}.")
+  md_rtf(
+    "&nbsp; &amp; &copy; &AElig; &Dcaron;\n&frac34; &HilbertSpace; &DifferentialD;\n&ClockwiseContourIntegral; &ngE;",
+    "\\u160  & \\u169  \\u198  \\u270 \n \\u190  \\u8459  \\u8518 \n \\u8754  \\u8807 \\u824 "
+  )
+  # TODO: <pre>, <blockquote>
+
+  # custom_inline
+
+  # emph
+  md_rtf("_test_", "{\\i test}")
+
+  # strong
+  md_rtf("**test**", "{\\b test}")
+
+  # link
+  md_rtf("[link](google.com)", "{\\field{\\*\\fldinst{HYPERLINK \"google.com\"}}{\\fldrslt{\\ul link}}}")
+  md_rtf("[](google.com)", "{\\field{\\*\\fldinst{HYPERLINK \"google.com\"}}{\\fldrslt{\\ul google.com}}}")
+  md_rtf("[link](google.com \"A search engine.\")", "{\\field{\\*\\fldinst{HYPERLINK \"google.com\"}}{\\fldrslt{\\ul link}}}")
+  md_rtf("[](google.com \"A search engine.\")", "{\\field{\\*\\fldinst{HYPERLINK \"google.com\"}}{\\fldrslt{\\ul google.com}}}")
+  md_rtf("<http://example.com?find=\\*>", "{\\field{\\*\\fldinst{HYPERLINK \"http://example.com?find=\\*\"}}{\\fldrslt{\\ul http://example.com?find=\\'5c*}}}")
+
+  # image
+
+  #
+  ## Combined tests
+  #
+
+  # Multiple
+  md_rtf("**_this &amp; that_**", "{\\b {\\i this & that}}")
+  md_rtf("***this &amp; that***", "{\\i {\\b this & that}}")
+  md_rtf("_**this &amp; that**_", "{\\i {\\b this & that}}")
+  md_rtf("___this &amp; that___", "{\\i {\\b this & that}}")
+  md_rtf("\\\\*emphasis*", "\\'5c{\\i emphasis}")
+  md_rtf("Foo\nbar\n\\---\nbaz\n", "Foo\n bar\n ---\n baz")
+
+  # Backslash escapes
+  md_rtf("`` \\[\\` ``", "{\\f1 \\'5c[\\'5c`}")
+  md_rtf("foo\\\nbar\n", "foo\\line bar")
+  md_rtf("\\\\*emphasis*", "\\'5c{\\i emphasis}")
+  md_rtf(
+    "\\!\\\"\\#\\$\\%\\&\\'\\(\\)\\*\\+\\,\\-\\.\\/\\:\\;\\<\\=\\>\\?\\@\\[\\\\\\]\\^\\_\\`\\{\\|\\}\\~\n",
+    "!\"#$%&'()*+,-./:;<=>?@[\\'5c]^_`\\'7b|\\'7d~"
+  )
+  md_rtf(
+    "\\*not emphasized*\n\\<br/> not a tag\n\\[not a link](/foo)\n\\`not code`\n1\\. not a list\n\\* not a list\n\\# not a heading\n\\[foo]: /url \"not a reference\"\n\\&ouml; not a character entity",
+    "*not emphasized*\n <br/> not a tag\n [not a link](/foo)\n `not code`\n 1. not a list\n * not a list\n # not a heading\n [foo]: /url \"not a reference\"\n &ouml; not a character entity"
+  )
+
+  # Overlapping
+  md_rtf("**_this &amp;** that_", "{\\b _this &} that_")
+})
+
+test_that("markdown_to_rtf escaping", {
+  md_rtf("\\b{}", "\\'5cb\\'7b\\'7d")
+  md_rtf("&lt;&amp;", "<&")
+})

From 27a091cf3cd91d270961ff7954d4f04a29baaf26 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 23 Oct 2020 15:37:27 -0400
Subject: [PATCH 28/30] Fix for `gtsave()` when saving an image and specifying
 a `path` value (#592)

* Use `fs::path_abs()` in `gtsave_filename()`

This works around saving with `htmltools::save_html()`, which requires an expanded, absolute path.

* Rewrite the `gtsave_filename()` util fcn

* Add new path tests for gtsave(); fix previous tests

* Add several testthat tests
---
 R/export.R                   |  15 +-
 tests/testthat/test-gtsave.R | 334 ++++++++++++++++++++++++++++++++++-
 2 files changed, 337 insertions(+), 12 deletions(-)

diff --git a/R/export.R b/R/export.R
index 7e94e7137..8bd5b67af 100644
--- a/R/export.R
+++ b/R/export.R
@@ -251,11 +251,18 @@ gtsave_file_ext <- function(filename) {
 #' @noRd
 gtsave_filename <- function(path, filename) {
 
-  if (!is.null(path)) {
-    filename <- file.path(path, filename)
-  }
+  if (is.null(path)) path <- "."
+
+  # The use of `fs::path_abs()` works around
+  # the saving code in `htmltools::save_html()`
+  # See htmltools Issue #165 for more details
 
-  filename %>% path_expand()
+  fs::path_abs(
+    path = filename,
+    start = path
+  ) %>%
+    fs::path_expand() %>%
+    as.character()
 }
 
 #' Get the HTML content of a **gt** table
diff --git a/tests/testthat/test-gtsave.R b/tests/testthat/test-gtsave.R
index fe697e143..a58fe2740 100644
--- a/tests/testthat/test-gtsave.R
+++ b/tests/testthat/test-gtsave.R
@@ -1,5 +1,3 @@
-context("Ensuring that the `gtsave()` function works as expected")
-
 test_that("the `gtsave()` function creates an HTML file based on the extension", {
 
   # Create a filename with path, having the
@@ -53,13 +51,13 @@ test_that("the `gtsave()` function creates an HTML file based on the extension",
   expect_true(file.exists(path_2))
 
   # Expect that the content of the file is HTML
-  (path_1 %>%
+  (path_2 %>%
       readLines()) %>% paste(collapse = "\n") %>%
     tidy_grepl("<!DOCTYPE html>") %>%
     expect_true()
 
   # Expect that CSS styles are not inlined
-  (path_1 %>%
+  (path_2 %>%
       readLines()) %>% paste(collapse = "\n") %>%
     tidy_grepl("<style>html \\{") %>%
     expect_true()
@@ -81,16 +79,336 @@ test_that("the `gtsave()` function creates an HTML file based on the extension",
     gtsave(filename = path_3, inline_css = TRUE)
 
   # Expect that the content of the file is HTML
-  (path_1 %>%
+  (path_3 %>%
       readLines()) %>% paste(collapse = "\n") %>%
     tidy_grepl("<!DOCTYPE html>") %>%
     expect_true()
 
-  # Expect that CSS styles are not inlined
-  (path_1 %>%
+  # Expect that CSS styles are inlined
+  (path_3 %>%
       readLines()) %>% paste(collapse = "\n") %>%
-    tidy_grepl("<style>html \\{") %>%
+    tidy_grepl("<style>body\\{") %>%
+    expect_true()
+
+  # Create a filename with path, having the
+  # .html extension
+  path_4 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_4))
+
+  # Expect that a file does not yet exist
+  # on that path
+  expect_false(file.exists(path_4))
+
+  # Save a gt table based on the exibble dataset
+  # as an HTML file to the `path_4`; use the
+  # basename and dirname with `gtsave()`
+  exibble %>%
+    gt() %>%
+    gtsave(
+      filename = basename(path_4),
+      path = dirname(path_4),
+      inline_css = TRUE
+    )
+
+  # Expect that the content of the file is HTML
+  (path_4 %>%
+      readLines()) %>% paste(collapse = "\n") %>%
+    tidy_grepl("<!DOCTYPE html>") %>%
     expect_true()
+
+  # Expect that CSS styles are inlined
+  (path_4 %>%
+      readLines()) %>% paste(collapse = "\n") %>%
+    tidy_grepl("<style>body\\{") %>%
+    expect_true()
+})
+
+test_that("HTML saving with `gtsave()` is succesful with different path defs", {
+
+  skip_on_cran()
+  skip_on_ci()
+  skip_on_covr()
+
+  #
+  # [#1] Relative filename, default path
+  #
+
+  # Form final path, check for non-existence
+  path_1 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_1))
+  expect_false(file.exists(path_1))
+
+  # Get initial working directory
+  wd_i <- getwd()
+
+  # Split path and get total number of path components
+  split_path <- fs::path_split(path_1) %>% unlist()
+  path_n <- length(split_path)
+
+  # Set working directory
+  setwd(file.path(paste0("/", paste(split_path[2:3], collapse = "/"))))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gtsave(filename = file.path(paste(split_path[4:path_n], collapse = "/")))
+
+  # Check for existence
+  expect_true(file.exists(path_1))
+  expect_true(
+    path_1 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # Reset to initial working directory
+  setwd(wd_i)
+
+  #
+  # [#2] Relative filename, relative path
+  #
+
+  # Form final path, check for non-existence
+  path_2 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_2))
+  expect_false(file.exists(path_2))
+
+  # Get initial working directory
+  wd_i <- getwd()
+
+  # Split path and get total number of path components
+  split_path <- fs::path_split(path_2) %>% unlist()
+  path_n <- length(split_path)
+
+  # Set working directory
+  setwd(file.path(paste0("/", paste(split_path[2:3], collapse = "/"))))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gtsave(
+      filename = file.path(paste(split_path[7:path_n], collapse = "/")),
+      path =  file.path(paste(split_path[4:6], collapse = "/"))
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_2))
+  expect_true(
+    path_2 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # Reset to initial working directory
+  setwd(wd_i)
+
+  # [#3] Absolute filename, absolute path (expect that `path` is ignored)
+
+  # Form final path, check for non-existence
+  path_3 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_3))
+  expect_false(file.exists(path_3))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gtsave(
+      filename = path_3,
+      path = "/this/path/is/not/real"
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_3))
+  expect_true(
+    path_3 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # [#4] Filename starting with ~/, absolute path (expect that path is ignored)
+
+  # Form final path, check for non-existence
+  path_4 <- tempfile(tmpdir = "~", fileext = ".html")
+  on.exit(unlink(path_4))
+  expect_false(file.exists(path_4))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gtsave(
+      filename = path_4,
+      path = "/this/path/is/not/real"
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_4))
+  expect_true(
+    path_4 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # [#5] Using ~
+
+  # Form final path, check for non-existence
+  path_5 <- tempfile(tmpdir = "~", fileext = ".html")
+  on.exit(unlink(path_5))
+  expect_false(file.exists(path_5))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gtsave(
+      filename = basename(path_5),
+      path = "~"
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_5))
+  expect_true(
+    path_5 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+})
+
+test_that("HTML saving with `gt_save_html()` with different path defs works", {
+
+  skip_on_cran()
+  skip_on_ci()
+  skip_on_covr()
+
+  #
+  # [#1] Relative filename, default path
+  #
+
+  # Form final path, check for non-existence
+  path_1 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_1))
+  expect_false(file.exists(path_1))
+
+  # Get initial working directory
+  wd_i <- getwd()
+
+  # Split path and get total number of path components
+  split_path <- fs::path_split(path_1) %>% unlist()
+  path_n <- length(split_path)
+
+  # Set working directory
+  setwd(file.path(paste0("/", paste(split_path[2:3], collapse = "/"))))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gt_save_html(filename = file.path(paste(split_path[4:path_n], collapse = "/")))
+
+  # Check for existence
+  expect_true(file.exists(path_1))
+  expect_true(
+    path_1 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # Reset to initial working directory
+  setwd(wd_i)
+
+  #
+  # [#2] Relative filename, relative path
+  #
+
+  # Form final path, check for non-existence
+  path_2 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_2))
+  expect_false(file.exists(path_2))
+
+  # Get initial working directory
+  wd_i <- getwd()
+
+  # Split path and get total number of path components
+  split_path <- fs::path_split(path_2) %>% unlist()
+  path_n <- length(split_path)
+
+  # Set working directory
+  setwd(file.path(paste0("/", paste(split_path[2:3], collapse = "/"))))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gt_save_html(
+      filename = file.path(paste(split_path[7:path_n], collapse = "/")),
+      path =  file.path(paste(split_path[4:6], collapse = "/"))
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_2))
+  expect_true(
+    path_2 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # Reset to initial working directory
+  setwd(wd_i)
+
+  # [#3] Absolute filename, absolute path (expect that `path` is ignored)
+
+  # Form final path, check for non-existence
+  path_3 <- tempfile(fileext = ".html")
+  on.exit(unlink(path_3))
+  expect_false(file.exists(path_3))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gt_save_html(
+      filename = path_3,
+      path = "/this/path/is/not/real"
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_3))
+  expect_true(
+    path_3 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # [#4] Filename starting with ~/, absolute path (expect that path is ignored)
+
+  # Form final path, check for non-existence
+  path_4 <- tempfile(tmpdir = "~", fileext = ".html")
+  on.exit(unlink(path_4))
+  expect_false(file.exists(path_4))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gt_save_html(
+      filename = path_4,
+      path = "/this/path/is/not/real"
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_4))
+  expect_true(
+    path_4 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
+
+  # [#5] Using ~
+
+  # Form final path, check for non-existence
+  path_5 <- tempfile(tmpdir = "~", fileext = ".html")
+  on.exit(unlink(path_5))
+  expect_false(file.exists(path_5))
+
+  # Write the file
+  exibble %>%
+    gt() %>%
+    gt_save_html(
+      filename = basename(path_5),
+      path = "~"
+    )
+
+  # Check for existence
+  expect_true(file.exists(path_5))
+  expect_true(
+    path_5 %>% readLines() %>% paste(collapse = "\n") %>%
+      tidy_grepl("<!DOCTYPE html>")
+  )
 })
 
 # test_that("the `gtsave()` function creates a LaTeX file based on the extension", {

From c4b578e8546f0d65412adbb0b5bbf911daeb4f9e Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 23 Oct 2020 17:39:03 -0400
Subject: [PATCH 29/30] PEN currency fix (#663)

* Update X03-locales.R

* Update x_currencies.csv

* Update sysdata.rda

* Update X05-google_fonts.R

* Update info_tables.R

* Update sysdata.rda

* Update testthat test

Co-authored-by: Joe Cheng <joe@rstudio.com>
---
 R/info_tables.R                   |  70 +++---
 R/sysdata.rda                     | Bin 191478 -> 189640 bytes
 data-raw/X03-locales.R            |   2 +-
 data-raw/X05-google_fonts.R       |  20 +-
 data-raw/x_currencies.csv         | 346 +++++++++++++++---------------
 tests/testthat/test-info_tables.R |   2 +-
 6 files changed, 222 insertions(+), 218 deletions(-)

diff --git a/R/info_tables.R b/R/info_tables.R
index 6dfef8687..aa5dcfa2d 100644
--- a/R/info_tables.R
+++ b/R/info_tables.R
@@ -548,48 +548,44 @@ info_google_fonts <- function() {
   # Recommended Fonts
   recommended <-
     c(
-      "Space Mono",
-      "Work Sans",
-      "Inter",
-      "Rubik",
-      "Libre Franklin",
-      "Comorant",
-      "Fira Sans",
-      "Fira Code",
-      "Eczar",
-      "Chivo",
-      "Inknut",
-      "Source Sans Pro",
-      "Source Serif Pro",
-      "Roboto",
-      "Roboto Slab",
-      "BioRhyme",
-      "Poppins",
+      "Anonymous Pro",
       "Archivo Narrow",
-      "Libre Baskerville",
-      "Playfair Display",
-      "Karla",
+      "Bio Rhyme",
+      "Cabin",
+      "Cardo",
+      "Chivo",
+      "Crimson Text",
       "Encode Sans",
-      "Lora",
-      "Proza Libre",
-      "Spectral",
-      "IBM Plex Sans",
+      "Exo 2",
+      "Fira Code",
+      "Fira Sans",
       "IBM Plex Mono",
-      "Crimson Text",
+      "IBM Plex Sans",
+      "Inconsolata",
+      "Inter",
+      "Karla",
+      "Lato",
+      "Libre Baskerville",
+      "Libre Franklin",
+      "Lora",
+      "Merriweather",
       "Montserrat",
+      "Mulish",
+      "Open Sans",
+      "Playfair Display",
+      "Poppins",
+      "Proza Libre",
       "PT Sans",
       "PT Serif",
-      "Lato",
-      "Cardo",
-      "Open Sans",
-      "Inconsolata",
-      "Cabin",
-      "Raleway",
-      "Anonymous Pro",
-      "Merriweather",
-      "Exo 2",
       "Public Sans",
-      "Muli"
+      "Raleway",
+      "Roboto",
+      "Rubik",
+      "Source Sans Pro",
+      "Source Serif Pro",
+      "Space Mono",
+      "Spectral",
+      "Work Sans"
     )
 
   styles_summary <-
@@ -597,7 +593,7 @@ info_google_fonts <- function() {
     dplyr::mutate(weight = as.integer(weight)) %>%
     dplyr::filter(name %in% recommended) %>%
     dplyr::group_by(name, style) %>%
-    dplyr::summarize(min_weight = min(weight), max_weight = max(weight)) %>%
+    dplyr::summarize(min_weight = min(weight), max_weight = max(weight), .groups = "keep") %>%
     dplyr::ungroup() %>%
     dplyr::arrange(name, dplyr::desc(style)) %>%
     dplyr::mutate(weight_range = dplyr::case_when(
@@ -607,7 +603,7 @@ info_google_fonts <- function() {
       style == "italic" & min_weight == max_weight ~ paste0("*i*&nbsp;", min_weight)
     )) %>%
     dplyr::group_by(name) %>%
-    dplyr::summarize(weight_ranges = paste(weight_range, collapse = "<br>"))
+    dplyr::summarize(weight_ranges = paste(weight_range, collapse = "<br>"), .groups = "keep")
 
   source_notes <-
     google_styles_tbl %>%
diff --git a/R/sysdata.rda b/R/sysdata.rda
index 7486e496f5e91bad1c833b0b29de1b35a5cb4721..408c69cea7d89e945d7fe78fde7a8da8937696f0 100644
GIT binary patch
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diff --git a/data-raw/X03-locales.R b/data-raw/X03-locales.R
index 6331f3d52..009959364 100644
--- a/data-raw/X03-locales.R
+++ b/data-raw/X03-locales.R
@@ -1,3 +1,3 @@
 library(tidyverse)
 
-locales <- readr::read_rds(path = "data-raw/locales.RDS")
+locales <- readr::read_rds(file = "data-raw/locales.RDS")
diff --git a/data-raw/X05-google_fonts.R b/data-raw/X05-google_fonts.R
index 3c574af42..11340b1d5 100644
--- a/data-raw/X05-google_fonts.R
+++ b/data-raw/X05-google_fonts.R
@@ -14,12 +14,16 @@ downloader::download(
 )
 utils::untar(file.path(work_dir, "google_fonts.tar.gz"), exdir = work_dir)
 
-# Get the directory names for each of the OFL fonts
+# Get the directory names for each of the fonts
 file_list <- fs::dir_ls(path = fs::path_expand(work_dir)) %>% as.character()
 ofl_dirs <- fs::dir_ls(file.path(file_list[!grepl("tar.gz", file_list)], "ofl"))
+apache_dirs <- fs::dir_ls(file.path(file_list[!grepl("tar.gz", file_list)], "apache"))
+ufl_dirs <- fs::dir_ls(file.path(file_list[!grepl("tar.gz", file_list)], "apache"))
+
+all_dirs <- c(ofl_dirs, apache_dirs, ufl_dirs)
 
 # Copy all .pb files to the root of the work directory
-for (dr in ofl_dirs) {
+for (dr in all_dirs) {
 
   font_name <- dr %>% fs::path_split() %>% unlist() %>% rev() %>% .[1]
 
@@ -27,7 +31,8 @@ for (dr in ofl_dirs) {
 
     fs::file_copy(
       path = file.path(dr, "METADATA.pb"),
-      new_path = file.path(work_dir, paste0(font_name, "__METADATA.pb"))
+      new_path = file.path(work_dir, paste0(font_name, "__METADATA.pb")),
+      overwrite = TRUE
     )
   }
 
@@ -35,7 +40,7 @@ for (dr in ofl_dirs) {
 }
 
 # Get paths for all .pb files in the work directory
-ofl_files <- fs::dir_ls(work_dir, glob = "*.pb")
+all_files <- fs::dir_ls(work_dir, glob = "*.pb")
 
 # Initialize tibbles
 google_font_tbl <-
@@ -57,7 +62,7 @@ google_axes_tbl <-
 
 # For every font file, read the `.pb` metadata file and extract
 # font metrics and other items of information
-for (file in ofl_files) {
+for (file in all_files) {
 
   pb <-
     readr::read_file(file) %>%
@@ -132,8 +137,11 @@ rm(file_list)
 rm(font_info)
 rm(font_name)
 rm(i)
+rm(all_dirs)
 rm(ofl_dirs)
-rm(ofl_files)
+rm(apache_dirs)
+rm(ufl_dirs)
+rm(all_files)
 rm(pb)
 rm(work_dir)
 rm(font_variants)
diff --git a/data-raw/x_currencies.csv b/data-raw/x_currencies.csv
index 4e33f6d59..01ca7c673 100644
--- a/data-raw/x_currencies.csv
+++ b/data-raw/x_currencies.csv
@@ -1,173 +1,173 @@
-curr_code,curr_number,exponent,curr_name,symbol
-AED,784,2,United Arab Emirates dirham,DH
-AFN,971,2,Afghan afghani,&#1547;
-ALL,8,2,Albanian lek,Lek
-AMD,51,2,Armenian dram,AMD
-ANG,532,2,Netherlands Antillean guilder,NA&#402;
-AOA,973,2,Angolan kwanza,Kz
-ARS,32,2,Argentine peso,$
-AUD,36,2,Australian dollar,$
-AWG,533,2,Aruban florin,&#402;
-AZN,944,2,Azerbaijani manat,&#8380;
-BAM,977,2,Bosnia and Herzegovina convertible mark,KM
-BBD,52,2,Barbados dollar,$
-BDT,50,2,Bangladeshi taka,&#2547;
-BGN,975,2,Bulgarian lev,‌&#1083;&#1074;
-BHD,48,3,Bahraini dinar,BD
-BIF,108,0,Burundian franc,FBu
-BMD,60,2,Bermudian dollar,$
-BND,96,2,Brunei dollar,B$
-BOB,68,2,Boliviano,$b
-BOV,984,2,Bolivian Mvdol,BOV
-BRL,986,2,Brazilian real,R$
-BSD,44,2,Bahamian dollar,$
-BTN,64,2,Bhutanese ngultrum,Nu.
-BWP,72,2,Botswana pula,P
-BYR,974,0,Belarusian ruble,p.
-BZD,84,2,Belize dollar,BZ$
-CAD,124,2,Canadian dollar,$
-CDF,976,2,Congolese franc,FC
-CHE,947,2,WIR Bank,CHE
-CHF,756,2,Swiss franc,SFr.
-CHW,948,2,WIR Bank,CHW
-CLF,990,4,Unidad de Fomento,UF
-CLP,152,0,Chilean peso,$
-CNY,156,2,Renminbi,&#165;
-COP,170,2,Colombian peso,$
-COU,970,2,Unidad de Valor Real,COU
-CRC,188,2,Costa Rican colon,&#8353
-CUC,931,2,Cuban convertible peso,&#8369;
-CUP,192,2,Cuban peso,&#8369;
-CVE,132,0,Cape Verde escudo,$
-CZK,203,2,Czech koruna,K&#269;
-DJF,262,0,Djiboutian franc,Fdj
-DKK,208,2,Danish krone,kr.
-DOP,214,2,Dominican peso,RD$
-DZD,12,2,Algerian dinar,DA
-EGP,818,2,Egyptian pound,E&#163;
-ERN,232,2,Eritrean nakfa,Nfk
-ETB,230,2,Ethiopian birr,Br
-EUR,978,2,Euro,&#8364;
-FJD,242,2,Fiji dollar,FJ$
-FKP,238,2,Falkland Islands pound,FK&#163;
-GBP,826,2,Pound sterling,&#163;
-GEL,981,2,Georgian lari,GEL
-GHS,936,2,Ghanaian cedi,&#8373;
-GIP,292,2,Gibraltar pound,&#163;
-GMD,270,2,Gambian dalasi,D
-GNF,324,0,Guinean franc,FG
-GTQ,320,2,Guatemalan quetzal,Q
-GYD,328,2,Guyana dollar,GY$
-HKD,344,2,Hong Kong dollar,HK$
-HNL,340,2,Honduran lempira,L
-HRK,191,2,Croatian kuna,kn
-HTG,332,2,Haitian gourde,G
-HUF,348,2,Hungarian forint,Ft
-IDR,360,2,Indonesian rupiah,Rp
-ILS,376,2,Israeli new shekel,&#8362;
-IMP,,2,Isle of Man pound,M&#163;
-INR,356,2,Indian rupee,&#8377;
-IQD,368,3,Iraqi dinar,ID
-IRR,364,2,Iranian rial,&#65020;
-ISK,352,0,Icelandic krona,kr
-JMD,388,2,Jamaican dollar,$
-JOD,400,3,Jordanian dinar,JD
-JPY,392,0,Japanese yen,&#165;
-KES,404,2,Kenyan shilling,KSh
-KGS,417,2,Kyrgyzstani som,K.S.
-KHR,116,2,Cambodian riel,&#6107;
-KMF,174,0,Comoro franc,CF
-KPW,408,2,North Korean won,&#8361;
-KRW,410,0,South Korean won,&#8361;
-KWD,414,3,Kuwaiti dinar,K.D.
-KYD,136,2,Cayman Islands dollar,CI$
-KZT,398,2,Kazakhstani tenge,&#8376;
-LAK,418,2,Lao kip,&#8365;
-LBP,422,2,Lebanese pound,L&#163;
-LKR,144,2,Sri Lankan rupee,Rs
-LRD,430,2,Liberian dollar,L$
-LSL,426,2,Lesotho loti,L
-LYD,434,3,Libyan dinar,LD
-MAD,504,2,Moroccan dirham,Dh
-MDL,498,2,Moldovan leu,MDL
-MGA,969,1,Malagasy ariary,Ar
-MKD,807,2,Macedonian denar,&#1076;&#1077;&#1085;
-MMK,104,2,Myanmar kyat,K
-MNT,496,2,Mongolian togrog,&#8366;
-MOP,446,1,Macanese pataca,MOP$
-MRO,478,1,Mauritanian ouguiya,UM
-MUR,480,2,Mauritian rupee,Rs
-MVR,462,2,Maldivian rufiyaa,Rf
-MWK,454,2,Malawian kwacha,MK
-MXN,484,2,Mexican peso,Mex$
-MXV,979,2,Mexican Unidad de Inversion,MXV
-MYR,458,2,Malaysian ringgit,RM
-MZN,943,2,Mozambican metical,MT
-NAD,516,2,Namibian dollar,N$
-NGN,566,2,Nigerian naira,&#8358;
-NIO,558,2,Nicaraguan cordoba,C$
-NOK,578,2,Norwegian krone,kr
-NPR,524,2,Nepalese rupee,Rps
-NZD,554,2,New Zealand dollar,$
-OMR,512,3,Omani rial,RO
-PAB,590,2,Panamanian balboa,B/.
-PEN,604,2,Peruvian Sol,S/.
-PGK,598,2,Papua New Guinean kina,K
-PHP,608,2,Philippine peso,&#8369;
-PKR,586,2,Pakistani rupee,Re.
-PLN,985,2,Polish zloty,z&#322;
-PYG,600,0,Paraguayan guarani,&#8370;
-QAR,634,2,Qatari riyal,QR
-RON,946,2,Romanian Leu,RON
-RSD,941,2,Serbian dinar,d.
-RUB,643,2,Russian ruble,&#8381;
-RWF,646,0,Rwandan franc,FRw
-SAR,682,2,Saudi riyal,SR
-SBD,90,2,Solomon Islands dollar,SI$
-SCR,690,2,Seychelles rupee,SR
-SDG,938,2,Sudanese pound,SDG
-SEK,752,2,Swedish krona,kr
-SGD,702,2,Singapore dollar,S$
-SHP,654,2,Saint Helena pound,&#163;
-SLL,694,2,Sierra Leonean leone,Le
-SOS,706,2,Somali shilling,Sh.So.
-SRD,968,2,Surinamese dollar,$
-SSP,728,2,South Sudanese pound,SSP
-STD,678,2,Ṣo Tom̩ and Principe dobra,Db
-SYP,760,2,Syrian pound,S&#163;
-SZL,748,2,Swazi lilangeni,L
-THB,764,2,Thai baht,&#3647;
-TJS,972,2,Tajikistani somoni,TJS
-TMT,934,2,Turkmenistani manat,T
-TND,788,3,Tunisian dinar,DT
-TOP,776,2,Tongan pa'anga,T$
-TRY,949,2,Turkish lira,&#8378;
-TTD,780,2,Trinidad and Tobago dollar,TT$
-TWD,901,2,New Taiwan dollar,NT$
-TZS,834,2,Tanzanian shilling,TSh
-UAH,980,2,Ukrainian hryvnia,&#8372;
-UGX,800,0,Ugandan shilling,USh
-USD,840,2,United States dollar,$
-USN,997,2,United States dollar,$
-USS,998,2,United States dollar,$
-UYI,940,0,Uruguay Peso en Unidades Indexadas,UYI
-UYU,858,2,Uruguayan peso,$U
-UZS,860,2,Uzbekistan som,&#1083;&#1074;
-VEF,937,2,Venezuelan bolivar,Bs.
-VND,704,0,Vietnamese dong,&#8363;
-VUV,548,0,Vanuatu vatu,VT
-WST,882,2,Samoan tala,WS$
-XAF,950,0,Central African CFA franc,FCFA
-XAG,961,NA,Silver,Ag
-XAU,959,NA,Gold,Au
-XCD,951,2,East Caribbean dollar,$
-XDR,960,NA,Special drawing rights,XDR
-XOF,952,0,West African CFA franc,F
-XPD,964,NA,Palladium,Pd
-XPF,953,0,CFP franc,F
-XPT,962,NA,Platinum,Pt
-XSU,994,NA,XSU,XSU
-XUA,965,NA,XUA,XUA
-YER,886,2,Yemeni rial,&#65020;
-ZAR,710,2,South African rand,R
-ZMW,967,2,Zambian kwacha,K
\ No newline at end of file
+curr_code,curr_number,exponent,curr_name,symbol
+AED,784,2,United Arab Emirates dirham,DH
+AFN,971,2,Afghan afghani,&#1547;
+ALL,8,2,Albanian lek,Lek
+AMD,51,2,Armenian dram,AMD
+ANG,532,2,Netherlands Antillean guilder,NA&#402;
+AOA,973,2,Angolan kwanza,Kz
+ARS,32,2,Argentine peso,$
+AUD,36,2,Australian dollar,$
+AWG,533,2,Aruban florin,&#402;
+AZN,944,2,Azerbaijani manat,&#8380;
+BAM,977,2,Bosnia and Herzegovina convertible mark,KM
+BBD,52,2,Barbados dollar,$
+BDT,50,2,Bangladeshi taka,&#2547;
+BGN,975,2,Bulgarian lev,‌&#1083;&#1074;
+BHD,48,3,Bahraini dinar,BD
+BIF,108,0,Burundian franc,FBu
+BMD,60,2,Bermudian dollar,$
+BND,96,2,Brunei dollar,B$
+BOB,68,2,Boliviano,$b
+BOV,984,2,Bolivian Mvdol,BOV
+BRL,986,2,Brazilian real,R$
+BSD,44,2,Bahamian dollar,$
+BTN,64,2,Bhutanese ngultrum,Nu.
+BWP,72,2,Botswana pula,P
+BYR,974,0,Belarusian ruble,p.
+BZD,84,2,Belize dollar,BZ$
+CAD,124,2,Canadian dollar,$
+CDF,976,2,Congolese franc,FC
+CHE,947,2,WIR Bank,CHE
+CHF,756,2,Swiss franc,SFr.
+CHW,948,2,WIR Bank,CHW
+CLF,990,4,Unidad de Fomento,UF
+CLP,152,0,Chilean peso,$
+CNY,156,2,Renminbi,&#165;
+COP,170,2,Colombian peso,$
+COU,970,2,Unidad de Valor Real,COU
+CRC,188,2,Costa Rican colon,&#8353
+CUC,931,2,Cuban convertible peso,&#8369;
+CUP,192,2,Cuban peso,&#8369;
+CVE,132,0,Cape Verde escudo,$
+CZK,203,2,Czech koruna,K&#269;
+DJF,262,0,Djiboutian franc,Fdj
+DKK,208,2,Danish krone,kr.
+DOP,214,2,Dominican peso,RD$
+DZD,12,2,Algerian dinar,DA
+EGP,818,2,Egyptian pound,E&#163;
+ERN,232,2,Eritrean nakfa,Nfk
+ETB,230,2,Ethiopian birr,Br
+EUR,978,2,Euro,&#8364;
+FJD,242,2,Fiji dollar,FJ$
+FKP,238,2,Falkland Islands pound,FK&#163;
+GBP,826,2,Pound sterling,&#163;
+GEL,981,2,Georgian lari,GEL
+GHS,936,2,Ghanaian cedi,&#8373;
+GIP,292,2,Gibraltar pound,&#163;
+GMD,270,2,Gambian dalasi,D
+GNF,324,0,Guinean franc,FG
+GTQ,320,2,Guatemalan quetzal,Q
+GYD,328,2,Guyana dollar,GY$
+HKD,344,2,Hong Kong dollar,HK$
+HNL,340,2,Honduran lempira,L
+HRK,191,2,Croatian kuna,kn
+HTG,332,2,Haitian gourde,G
+HUF,348,2,Hungarian forint,Ft
+IDR,360,2,Indonesian rupiah,Rp
+ILS,376,2,Israeli new shekel,&#8362;
+IMP,,2,Isle of Man pound,M&#163;
+INR,356,2,Indian rupee,&#8377;
+IQD,368,3,Iraqi dinar,ID
+IRR,364,2,Iranian rial,&#65020;
+ISK,352,0,Icelandic krona,kr
+JMD,388,2,Jamaican dollar,$
+JOD,400,3,Jordanian dinar,JD
+JPY,392,0,Japanese yen,&#165;
+KES,404,2,Kenyan shilling,KSh
+KGS,417,2,Kyrgyzstani som,K.S.
+KHR,116,2,Cambodian riel,&#6107;
+KMF,174,0,Comoro franc,CF
+KPW,408,2,North Korean won,&#8361;
+KRW,410,0,South Korean won,&#8361;
+KWD,414,3,Kuwaiti dinar,K.D.
+KYD,136,2,Cayman Islands dollar,CI$
+KZT,398,2,Kazakhstani tenge,&#8376;
+LAK,418,2,Lao kip,&#8365;
+LBP,422,2,Lebanese pound,L&#163;
+LKR,144,2,Sri Lankan rupee,Rs
+LRD,430,2,Liberian dollar,L$
+LSL,426,2,Lesotho loti,L
+LYD,434,3,Libyan dinar,LD
+MAD,504,2,Moroccan dirham,Dh
+MDL,498,2,Moldovan leu,MDL
+MGA,969,1,Malagasy ariary,Ar
+MKD,807,2,Macedonian denar,&#1076;&#1077;&#1085;
+MMK,104,2,Myanmar kyat,K
+MNT,496,2,Mongolian togrog,&#8366;
+MOP,446,1,Macanese pataca,MOP$
+MRO,478,1,Mauritanian ouguiya,UM
+MUR,480,2,Mauritian rupee,Rs
+MVR,462,2,Maldivian rufiyaa,Rf
+MWK,454,2,Malawian kwacha,MK
+MXN,484,2,Mexican peso,Mex$
+MXV,979,2,Mexican Unidad de Inversion,MXV
+MYR,458,2,Malaysian ringgit,RM
+MZN,943,2,Mozambican metical,MT
+NAD,516,2,Namibian dollar,N$
+NGN,566,2,Nigerian naira,&#8358;
+NIO,558,2,Nicaraguan cordoba,C$
+NOK,578,2,Norwegian krone,kr
+NPR,524,2,Nepalese rupee,Rps
+NZD,554,2,New Zealand dollar,$
+OMR,512,3,Omani rial,RO
+PAB,590,2,Panamanian balboa,B/.
+PEN,604,2,Peruvian Sol,S/
+PGK,598,2,Papua New Guinean kina,K
+PHP,608,2,Philippine peso,&#8369;
+PKR,586,2,Pakistani rupee,Re.
+PLN,985,2,Polish zloty,z&#322;
+PYG,600,0,Paraguayan guarani,&#8370;
+QAR,634,2,Qatari riyal,QR
+RON,946,2,Romanian Leu,RON
+RSD,941,2,Serbian dinar,d.
+RUB,643,2,Russian ruble,&#8381;
+RWF,646,0,Rwandan franc,FRw
+SAR,682,2,Saudi riyal,SR
+SBD,90,2,Solomon Islands dollar,SI$
+SCR,690,2,Seychelles rupee,SR
+SDG,938,2,Sudanese pound,SDG
+SEK,752,2,Swedish krona,kr
+SGD,702,2,Singapore dollar,S$
+SHP,654,2,Saint Helena pound,&#163;
+SLL,694,2,Sierra Leonean leone,Le
+SOS,706,2,Somali shilling,Sh.So.
+SRD,968,2,Surinamese dollar,$
+SSP,728,2,South Sudanese pound,SSP
+STD,678,2,Ṣo Tom̩ and Principe dobra,Db
+SYP,760,2,Syrian pound,S&#163;
+SZL,748,2,Swazi lilangeni,L
+THB,764,2,Thai baht,&#3647;
+TJS,972,2,Tajikistani somoni,TJS
+TMT,934,2,Turkmenistani manat,T
+TND,788,3,Tunisian dinar,DT
+TOP,776,2,Tongan pa'anga,T$
+TRY,949,2,Turkish lira,&#8378;
+TTD,780,2,Trinidad and Tobago dollar,TT$
+TWD,901,2,New Taiwan dollar,NT$
+TZS,834,2,Tanzanian shilling,TSh
+UAH,980,2,Ukrainian hryvnia,&#8372;
+UGX,800,0,Ugandan shilling,USh
+USD,840,2,United States dollar,$
+USN,997,2,United States dollar,$
+USS,998,2,United States dollar,$
+UYI,940,0,Uruguay Peso en Unidades Indexadas,UYI
+UYU,858,2,Uruguayan peso,$U
+UZS,860,2,Uzbekistan som,&#1083;&#1074;
+VEF,937,2,Venezuelan bolivar,Bs.
+VND,704,0,Vietnamese dong,&#8363;
+VUV,548,0,Vanuatu vatu,VT
+WST,882,2,Samoan tala,WS$
+XAF,950,0,Central African CFA franc,FCFA
+XAG,961,NA,Silver,Ag
+XAU,959,NA,Gold,Au
+XCD,951,2,East Caribbean dollar,$
+XDR,960,NA,Special drawing rights,XDR
+XOF,952,0,West African CFA franc,F
+XPD,964,NA,Palladium,Pd
+XPF,953,0,CFP franc,F
+XPT,962,NA,Platinum,Pt
+XSU,994,NA,XSU,XSU
+XUA,965,NA,XUA,XUA
+YER,886,2,Yemeni rial,&#65020;
+ZAR,710,2,South African rand,R
+ZMW,967,2,Zambian kwacha,K
diff --git a/tests/testthat/test-info_tables.R b/tests/testthat/test-info_tables.R
index 485ed722e..1ef9c16ae 100644
--- a/tests/testthat/test-info_tables.R
+++ b/tests/testthat/test-info_tables.R
@@ -48,5 +48,5 @@ test_that("the `info_google_fonts()` function works correctly", {
     info_google_fonts() %>%
       dt_data_get() %>%
       dim(),
-    c(37, 4))
+    c(38, 4))
 })

From 35355c4b77cb8dbdcbb5237533241be8d83c1764 Mon Sep 17 00:00:00 2001
From: Richard Iannone <riannone@me.com>
Date: Fri, 23 Oct 2020 21:07:31 -0400
Subject: [PATCH 30/30] Spanner alignment correction (#662)

* Add the `dt_boxhead_get_alignment_by_var()` util fcn

* Undo forcing of subordinate column labels to be "center"

* Align integer values to the right

* Rearrange ordering of CSS classes for consistency

* Add testthat test, checking alignments with `tab_spanner()`
---
 R/dt_boxhead.R                    |  8 ++++++++
 R/modify_columns.R                |  2 +-
 R/utils_render_html.R             | 32 +++++++++++++++++++++++++------
 tests/testthat/test-table_parts.R | 23 ++++++++++++++++++++++
 4 files changed, 58 insertions(+), 7 deletions(-)

diff --git a/R/dt_boxhead.R b/R/dt_boxhead.R
index a3e690ef6..088cdc1c3 100644
--- a/R/dt_boxhead.R
+++ b/R/dt_boxhead.R
@@ -184,6 +184,14 @@ dt_boxhead_get_vars_labels_default <- function(data) {
     unlist()
 }
 
+dt_boxhead_get_alignment_by_var <- function(data, var) {
+
+  data %>%
+    dt_boxhead_get() %>%
+    dplyr::filter(var == !!var) %>%
+    magrittr::extract2("column_align")
+}
+
 check_names_dt_boxhead_expr <- function(expr) {
 
   if (!all(names(expr) %in% c(
diff --git a/R/modify_columns.R b/R/modify_columns.R
index 574bffdb6..f7be22c19 100644
--- a/R/modify_columns.R
+++ b/R/modify_columns.R
@@ -85,7 +85,7 @@ cols_align <- function(data,
       "factor" = "center",
       "list" = "center",
       "numeric" = "right",
-      "integer" = "center",
+      "integer" = "right",
       "center") %>%
       unname()
   } else {
diff --git a/R/utils_render_html.R b/R/utils_render_html.R
index 8838e3d5e..e127338ca 100644
--- a/R/utils_render_html.R
+++ b/R/utils_render_html.R
@@ -491,8 +491,11 @@ create_columns_component_h <- function(data) {
       first_set[[length(first_set) + 1]] <-
         htmltools::tags$th(
           class = paste(
-            c("gt_col_heading", "gt_columns_bottom_border",
-              paste0("gt_", stubhead_label_alignment)),
+            c(
+              "gt_col_heading",
+              "gt_columns_bottom_border",
+              paste0("gt_", stubhead_label_alignment)
+            ),
             collapse = " "),
           rowspan = 2,
           colspan = 1,
@@ -539,10 +542,17 @@ create_columns_component_h <- function(data) {
             NULL
           }
 
+        first_set_alignment <-
+          dt_boxhead_get_alignment_by_var(data = data, headings_vars[i])
+
         first_set[[length(first_set) + 1]] <-
           htmltools::tags$th(
             class = paste(
-              c("gt_col_heading", "gt_center", "gt_columns_bottom_border"),
+              c(
+                "gt_col_heading",
+                "gt_columns_bottom_border",
+                paste0("gt_", first_set_alignment)
+              ),
               collapse = " "),
             rowspan = 2,
             colspan = 1,
@@ -571,7 +581,11 @@ create_columns_component_h <- function(data) {
           first_set[[length(first_set) + 1]] <-
             htmltools::tags$th(
               class = paste(
-                c("gt_center", "gt_columns_top_border", "gt_column_spanner_outer"),
+                c(
+                  "gt_center",
+                  "gt_columns_top_border",
+                  "gt_column_spanner_outer"
+                ),
                 collapse = " "
               ),
               rowspan = 1,
@@ -620,17 +634,23 @@ create_columns_component_h <- function(data) {
             NULL
           }
 
+        remaining_alignment <-
+          dt_boxhead_get_alignment_by_var(data = data, remaining_headings[j])
+
         second_set[[length(second_set) + 1]] <-
           htmltools::tags$th(
             class = paste(
-              c("gt_col_heading", "gt_columns_bottom_border", "gt_center"),
+              c(
+                "gt_col_heading",
+                "gt_columns_bottom_border",
+                paste0("gt_", remaining_alignment)
+              ),
               collapse = " "
             ),
             rowspan = 1, colspan = 1,
             style = remaining_style,
             htmltools::HTML(remaining_headings_labels[j])
           )
-
       }
 
       table_col_headings <-
diff --git a/tests/testthat/test-table_parts.R b/tests/testthat/test-table_parts.R
index 721a7dc74..920a10429 100644
--- a/tests/testthat/test-table_parts.R
+++ b/tests/testthat/test-table_parts.R
@@ -180,6 +180,29 @@ test_that("a gt table contains the expected spanner column labels", {
   )
 })
 
+test_that("`tab_spanner()` doesn't adversely affect column alignment", {
+
+  tbl_html <-
+    gt(data = airquality) %>%
+    cols_move_to_start(columns = vars(Month, Day)) %>%
+    cols_label(Solar.R = html("Solar<br>Radiation")) %>%
+    tab_spanner(
+      label = "Measurement Period",
+      columns = vars(Month, Day)
+    ) %>%
+    render_as_html()
+
+  # Expect that all column labels (which are originally of the numeric
+  # and integer classes) are aligned to the right (i.e., all have the
+  # `gt_right` CSS class) even though a spanner is present above the
+  # `Month` and `Day` columns
+  tbl_html %>%
+    xml2::read_html() %>%
+    rvest::html_nodes("[class='gt_col_heading gt_columns_bottom_border gt_right']") %>%
+    rvest::html_text() %>%
+    expect_equal(c("Ozone", "SolarRadiation", "Wind", "Temp", "Month", "Day"))
+})
+
 test_that("`tab_spanner()` works even when columns are forcibly moved", {
 
   # Create a table with column spanners, moving the `carb` value