R’s packaging system is great, but there are a few minor annoyances it has. I think I’ve solved them, and wanted to share my setup so that others can fix these annoyances as well. I use Linux, and this setup works well there. It should work on Mac and Windows as well. If you run into problems, though, feel free to comment on this post.
Where R installs packages By default, R installs packages somewhere quite obnoxious.
Update 19-May-2016: broken link removed and link to the github repo added instead
I ran across this post (link broken, github repo) announcing a weekly R/python visualization challenge and decided that this was the perfect excuse I needed to brush up on my mapping skills.
An R script with all the code in one place is available on my github repo.
Here, we’ll graph the lower 48 states and color them depending on how many drone sightings have been reported to the FAA in 2014 and 2015 total.
The Southern Political Science Association’s 2016 Annual Meeting just finished up in San Juan, Puerto Rico. Since I’ve been meaning to learn the twitteR package for a little bit, I figured that this was a perfect time to do a fun little analysis. You can find the R code I used to generate the images on Github.
I started out by grabbing all the tweets containing the official conference tag (#SPSA2016).