Thanks for coming out to my R workshop today. If you felt like this workshop was worth your time, please consider attending future installments of the R Series at the UGA DigiLab.
In Introduction to R (September 13, 2017): In this workshop I go over the basics of R including installation, basic functions, loading your data into R, filtering, visualizations, and where to find help.
ggplot2 (October 12, 2017): Here I discuss the popular
ggplot2 package, a collection of functions that makes it easy to create stunning, professional-quality visualizations. Specifically, I cover basic plots, how to modify them, and some of my thoughts on data visualization.
tidyverse (November 10, 2017): This workshop will discuss a collection of R packages known as the
tidyverse. This includes packages like
ggplot2. They are designed with the same underlying mechanisms so they they work harmoneously together to make it easy to import, tidy, and reshape your data for future analysis.
Network Analysis (Spring, 2018): I’ll give a primer on network data and what that should look like, how to get it in R, and how to make some basic visualizations and statistical analyses using the
igraph package and others. Hopefully we’ll attract a slightly different crowd to this one, so I’ll make it less about R itself and more about the practical application.
Corpus/Text Analysis (Spring, 2018): This one will be primarily geared towards linguists, English majors, and other folks that use text-heavy data. Here I plan on showcasing the
stringr package (part of
tidyverse), which makes it easy to do string-based functions like regular expressions and whatnot.
Shiny (Spring, 2018): For this day, I’d cover the basics of Shiny, which is an extension to R that lets you build your own interactive websites. This is great for showcasing personal projects or presentations. I’ll only be able to cover the basics of building the UI and server-side parts of a working Shiny app since it will take more than an hour to learn it all.
R Markdown (Spring, 2018): If in interactive website it too much, perhaps an R Markdown file is more convenient. This will let you build an interactive notebook where you can embed text, code, and visualizations all in one file. If your data changes, just rerun the whole thing and the entire notebook automatically updates. The output can be static or dynamic (using Shiny) and can be formatted as a PDF, HTML, or even full-fledged books.