Resources for learning R (from workshops to reference cards)

December 7, 2016
By

(This article was first published on Ista Zahn (Posts about R), and kindly contributed to R-bloggers)

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.

Workshops

Many organizations (including Harvard) offer R workshops. If you would like to attend an R workshop, here are some good places to start.

http://r-exercises.com/r-courses/
List of R workshops, including those offered by udemy, coursera, and others.
https://www.rstudio.com/workshops/
R workshops offered by RStudio.
http://dss.iq.harvard.edu/workshop-registration
R workshops offered by the Institute for Quantitative Social Science (IQSS) at Harvard.

Tutorials

Interactive

There are some great efforts to provide interactive self-paced R tutorials in your browser or in R itself.

https://www.datacamp.com/
Interactive R tutorials with feedback, right in your web browser!
http://swirlstats.com/students.html
Interactive R tutorials with feedback in R.
http://dss.iq.harvard.edu/workshop-materials#widget-1
Interactive R tutorials in your web browser. Includes a ggplot tutorial.

Static

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.

http://www.statmethods.net/
“Quick-R” aims to get you up and running in R quickly.
http://personality-project.org/r/r.guide.html
Notes on “Using R for psychological research”.
http://r4ds.had.co.nz/
“R for Data Science” by R luminary Hadley Wickham. Includes a ggplot tutorial.
http://adv-r.had.co.nz/
Advanced R programming by Hadley Wickham.
http://rmarkdown.rstudio.com/lesson-1.html
A comprehensive RMarkdown tutorial.

Reference cards

RStudio maintains a collection of high-quality cheat sheets at https://www.rstudio.com/resources/cheatsheets/ (these are also accessible from the Help -> cheat-sheets menu in the RStudio IDE). Additional resources are listed below.

http://mathesaurus.sourceforge.net/r-numpy.html
A numpy cheat sheet for R users, but it works just as well the other way around.
http://www.math.umaine.edu/~hiebeler/comp/matlabR.pdf
An R cheat sheet for MATLAB users.
http://mathesaurus.sourceforge.net/matlab-python-xref.pdf
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.

https://cran.r-project.org/web/views/
R Task Views are curated lists of R packages and functions organized by topic.
http://r-pkg.org
METACRAN is a friendly, search-able web interface to CRAN.
http://rdocumentation.org
A search-able interactive interface to R and R package documentation.

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.

To leave a comment for the author, please follow the link and comment on their blog: Ista Zahn (Posts about R).

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