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doc(vignette): add explanation of vaccinations fields
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corybrunson committed Dec 3, 2020
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2 changes: 2 additions & 0 deletions NEWS.md
Expand Up @@ -9,6 +9,8 @@ A new vignette by Quentin D. Read shows how to build interactive Shiny apps with

Corrections have been made to erroneous legacy code, found in one example and two vignettes, to reorder the factor levels of the `"response"` field in the data set `vaccinations`. The documentation is updated accordingly.

Also, an explanation of the (misleading) column names of this data set has been added to the main vignette.

# ggalluvial 0.12.2

This patch addresses a bug introduced in v0.12.0 that had `is_lodes_form()` return an error when a data frame contains duplicate id-axis pairings, which may be appropriate for producing faceted plots. The new `site` parameter can be passed one or more grouping variables for this purpose, and internally it is passed `"PANEL"` to prevent this error from being thrown.
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3 changes: 2 additions & 1 deletion vignettes/ggalluvial.rmd
Expand Up @@ -191,7 +191,8 @@ This example demonstrates one way **ggalluvial** handles missing data. The alter
[^na.rm]: Be sure to set `na.rm` consistently in each layer, in this case both the flows and the strata.

Finally, lode format gives us the option to aggregate the flows between adjacent axes, which may be appropriate when the transitions between adjacent axes are of primary importance.
We can demonstrate this option on data from the influenza vaccination surveys conducted by the [RAND American Life Panel](https://alpdata.rand.org/):
We can demonstrate this option on data from the influenza vaccination surveys conducted by the [RAND American Life Panel](https://alpdata.rand.org/).
The data, including one question from each of three surveys, has been aggregated by response profile: Each "subject" (mapped to `alluvium`) actually represents a cohort of subjects who responded the same way on all three questions, and the size of each cohort (mapped to `y`) is recorded in "freq".

```{r alluvial plot of vaccinations dataset}
data(vaccinations)
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