update graph index

graph00_index.md

@@ -8,7 +8,7 @@ output:
 
 We work on visualiation throughout the course. Here are the bits in rough order of presentation.
 
-  * R graphics landscape *[slides](http://www.slideshare.net/jenniferbryan5811/cm005-intro-ggplot2)*
+  * R graphics landscape *[slides](https://speakerdeck.com/jennybc/ggplot2-tutorial)*
     - why we prefer `ggplot2` (or `lattice`) over base R graphics
     - the underappreciated importance of data.frames, tidy data, and factor management to graphics
     - basic jargon of `ggplot2`
@@ -18,7 +18,7 @@ We work on visualiation throughout the course. Here are the bits in rough order
   * [Do's and don'ts of making effective graphs](block015_graph-dos-donts.html)
     - Effective = easy for audience to decode numerical info
     - Our ability to decode position along common axis >> area, angle, color, etc. 
-  * The [R Graph Catalog](http://shinyapps.stat.ubc.ca/r-graph-catalog/) presents a visual, clickable index of 100+ figures
+  * The [R Graph Catalog](http://shiny.stat.ubc.ca/r-graph-catalog/) presents a visual, clickable index of 100+ figures
     - mostly from Naomi Robbins' book ["Creating More Effective Graphs"](http://www.amazon.com/Creating-Effective-Graphs-Naomi-Robbins/dp/0985911123)
     - see figure and the exact `ggplot2` code to produce it, side-by-side
     - code for all figures and app itself is on [GitHub](https://github.com/jennybc/r-graph-catalog)
@@ -33,4 +33,4 @@ We work on visualiation throughout the course. Here are the bits in rough order
     - underappreciated basics: density plots, high-volume scatterplots
     good stuff here:
     http://www.ugrad.stat.ubc.ca/~stat540/seminars/seminar03_graphics-ggplot2.html
-    -->
+    -->