R

R is a powerful programing language for data visualization and statistical analysis.

Installation

R can be installed standalone, but RStudio is highly recommended as a working environment. Be sure to first install R. On the left side of the web page you can install it from the CRAN mirror. After the install is complete, you can install RStudio.

Alternatively, you can use R within Jupyter Lab. This is Aaron's preferred approach. See the next section on How to set up your computer for NCIL Data Science.

Recommended Packages and Resources

R packages can be installed in RStudio with install.packages("package") typed into the console. The ggplot2 R package is the gold standard for data visualization. For data manipulation, base R has many functions, but the dplyr package increases the functionality for some applications. For simplicity, installing the entire collection of tidyverse packages is another option, and can be done with install.packages("tidyverse"). It should also be noted that when using the packages, they must first be instantiated using at the beginning of the R file with library("[package]")

For learning how to use R, and R packages, Datacamp has multiple relevant courses - please see "Learn some code"

From Data to Viz is a fantastic web resource for data visualization using R, including code examples and graph ideas based on what type of data you have.