A list of resources for learning R in preparation for CS109 this Spring. A wealth of R resources are available, and I’m sure I’ve missed some really good ones. If you have a favorite tutorial or resource that is not listed here, please email me or submit a bug report or pull request to http://github.com/izahn/blog.
Many organizations (including Harvard) offer R workshops. If you would like to attend an R workshop, here are some good places to start.
- List of R workshops, including those offered by udemy, coursera, and others.
- R workshops offered by RStudio.
- R workshops offered by the Institute for Quantitative Social Science (IQSS) at Harvard.
There are some great efforts to provide interactive self-paced R tutorials in your browser or in R itself.
- Interactive R tutorials with feedback, right in your web browser!
- Interactive R tutorials with feedback in R.
- Interactive R tutorials in your web browser. Includes a
Many R tutorials have been collected at https://www.r-project.org/other-docs.html. The list of contributed documentation at https://cran.r-project.org/other-docs.html is a great place to start. There are several excellent tutorials not listed on r-project.org. Some of these are listed below.
- “Quick-R” aims to get you up and running in R quickly.
- Notes on “Using R for psychological research”.
- “R for Data Science” by R luminary Hadley Wickham. Includes a
- Advanced R programming by Hadley Wickham.
- A comprehensive RMarkdown tutorial.
RStudio maintains a collection of high-quality cheat sheets at https://www.rstudio.com/resources/cheatsheets/ (these are also accessible from the
Help -> cheat-sheetsmenu in the RStudio IDE). Additional resources are listed below.
- A numpy cheat sheet for R users, but it works just as well the other way around.
- An R cheat sheet for MATLAB users.
- Another R cheat sheet for MATLAB or Python users.
R package discovery
The Comprehensive R Archive Network (CRAN) is the main R package repository. The web interface is not very sophisticated, so I recommend using the resources listed below instead.
Blogs, forums and mailing lists
R related blogs are aggregated at http://r-bloggers.com. http://stackoverflow.com is by far the most popular help forum for R. Use the
[r]tag or navigate directly to http://stackoverflow.com/questions/tagged/r. Although the R mailing lists have been losing traffic to stackoverflow there are still plenty of people responding to questions. You can subscribe to the main R-help mailing list at https://stat.ethz.ch/mailman/listinfo/r-help.