I guess what turned into one post about ACS data is now an installment series. The #rstats community is so productive with its output that as I finally figure out the extant of one package someone has made a streamlined, optimized, or shiny new one. Kyle Walker’s new tidycensus package is the latest in that long line and before you go any further I encourage you to follow the link to read his brief introductions.
Graph!? more like art Every once in a while, I run into an article with some data that really intrigues me, and sometimes I run into a data visualization that makes me think, “How can I do something like that?” Sometimes they both happen simultaneously and I have to drop everything to start working on it. That happened to me with the 538 article, The Most Conservative And Most Liberal Elite Law Schools.
UPDATE: I had mentioned that I did not believe ggplot2 was the right route for the four panel style presentation but see the R-Bloggers post on how to achieve it with ggplot2 and ggalt. It has been awhile since I have posted a tutorial, or anything for that matter, on my website so I decided to revisit some data from my old post. If you recall in that quick little visualization I just wanted to plot this great new data set.
Below is a tutorial that helps take ZIP code data and, with R, get rough latitude and longitude data from them as well as County. Then using ggplot2 we can create a nice visual of the data plotted at the county level. The first section was written as part of a larger project and I like to keep it around as it was one of the first tutorials on this website.