Update link and fix graph cex

README.md

@@ -20,7 +20,7 @@ The goals of the ML Code Completeness Checklist are to:
 
 We find that those repositories that score higher on the checklist tend to have a higher number of GitHub stars. 
 
-We've verified this by analysing NeurIPS 2019 repositories. For more details on this analyis please refer to our [blog post](https://medium.com/paperswithcode/). We also provide the [data](notebooks/code_checklist-neurips2019.csv) and [notebook](notebooks/code_checklist-analysis.Rmd) to reproduce this analysis from the post. 
+We've verified this by analysing NeurIPS 2019 repositories. For more details on this analyis please refer to our [blog post](https://medium.com/paperswithcode/). We also provide the [data](notebooks/code_checklist-neurips2019.csv) and [notebook](notebooks/code_checklist-analysis.pdf) to reproduce this analysis from the post. 
 
 The checklist is made to be as general as possible. It consists of five items:
 

notebooks/code_checklist-analysis.Rmd

@@ -64,10 +64,10 @@ layout(matrix(c(1,2), 1, 2, byrow = TRUE), widths=c(3,2))
 barplot(medians, 
         xlab="", 
         ylab="Median GitHub stars", ylim=c(0,200),
-        col=brewer.pal(6, "Blues"), cex.axis=0.7, cex.names=0.7)
+        col=brewer.pal(6, "Blues"), cex.axis=0.6, cex.names=0.6)
 mtext("GitHub repos grouped by number of ticks on ML code checklist", side=1, line=3, cex=0.8)
 
-pie(rev(props), col=rev(brewer.pal(6, "Blues")), cex=0.7)
+pie(rev(props), col=rev(brewer.pal(6, "Blues")), cex=0.6)
 mtext("Proportion of repositories in each group", side=1, line=3, cex=0.8)
 ```