A Year with R

A year ago I stumbled upon the R programming language, mostly by accident on YouTube. I wanted a better platform for making graphics and maps and was running up against a lot of limitations in Python with matplotlib. Matplotlib is powerful but it often requires a lot of explicit code to make elegant well thought out graphics.

R has proven to be a very worthwhile skill to learn. While I consider myself to be a fairly experienced Python programmer, R has proven a lot more valuable especially when it comes to making good basic, attractive maps in SVG files. Simply said, R defaults with ggplot just make sense and are attractive. The pipe mechanism in R based around maggitir is fantastic for complicated data wrangling in a single line of code. Pipes are a wonderful thing in Unix and they make a lot of sense for processing data.

R is a werid language to get the hang of at first. It’s not necessarily bad – it’s actually pretty awesome for manipulating data with pipes. But it is different with strange operators and syntax, based around 1 indexing rather than 0 indexing of most C derived languages like Python. But I’ve really gotten the hang of it by doing a lot of reading and watching videos on R and just digging through the commands, reading help files and even the raw R code on objects.

R really excels with automating GIS processes and being a one stop shop from extract, transform, load to render. Interestingly, outside of academia it seems like R doesn’t get the credit it deserves – especially with Census data and tidycensus its a one stop shop from obtaining data to manipulating it to rendering it on a map, often with just a single pipeline of code. It’s pretty neat.

I’m glad I taught myself R and it’s a technology I will probably continue to use daily for exploring my world.