# Self-Learning Resources for R

## Content from Princeton University

### Getting Started

in R

A resource maintained by the Princeton Data and Statistical Service Center. Contains a series of text-based guides covering getting started in R as well as topics such as descriptive statistics.

### R Data Analysis, Wrangling, And Visualization Workshops

View recordings of select R workshops from Princeton’s Research Computing’s annual Bootcamp Training. Topics include Intro to Data Analysis, R Data Wrangling, and Visualization. To find the R workshops on the Bootcamp’s Agenda page, start with the workshops listed for January 20 and 21.

### R Workshops from OPR

View materials from all of the R workshops held by The Office of Population (OPR). OPR’s R workshop topics over the past several years have included topics such as data wrangling (tidyr, dplyr), latent class analysis (poLCA), text analysis and manipulation (stm, stringr), graphics (ggplots2, broom), multiple imputation (amelia), and reproducible research tools (sweave, knitr, rmarkdown).

## R Books (Free and Online)

See all available books in Rstudio’s Books page.

Books with a focus on visualization:

## Cheatsheets

RStudio offers dozens of free cheatsheets covering a variety of aspects of the R programming language as well as topics specific to the RStudio IDE.

## Interactive Tutorials

- R Courses from DataCamp, for example Introduction to R
*You can access 3 months of DataCamp for free if you set up a student GitHub account:*https://www.datacamp.com/github-students/ - Interactive Tutorials for R from RStudio
- swirl – an interactive guide for learning R right inside your R console
*Instructions for getting started in this medium article.*

## Instructional Videos

RStudio has published various videos on Vimeo covering a range of basic topics like Installing R, Installing RStudio, or Installing Packages, to more advanced topics like Introduction to Debugging in R, or tutorials on creating interactive apps with Shiny.

LinkedIn Learning is available to Princeton students, faculty, and staff for free. Access LinkedIn Learning’s (formerly Lynda.com) resources through: https://linkedinlearning.princeton.edu/

The Summer Institutes in Computational Social Science (SICSS) were created to provide free training to the next generation of researchers at the intersection of social science and data science. Videos include Installing RStudio, R Basics, Data “Wrangling,” Visualization, Basic Programming, Modeling, and Communicating and Collaborating.

## Text-Based Tutorials

### Software & Data Carpentry’s Lessons:

If you find additional resources that could be added to this list, let us know at exploringr@princeton.edu.