Additional Resources for Learning and Practicing R

There’s a multitude of resources for learning R out there. So many, in fact, that it can be overwhelming! Here is a list of some of the resources that we like. It is by no means complete or exhaustive! If you have more that you find helpful, please share them with us by sending us an email. And remember, the best way to learn and practice is to have a data set that you need to clean, visualize, and analyze. Each data set presents unique problems to solve, and that will give you opportunities to use R to solve them!

R Workshops and Bootcamps

• D-Lab: Berkeley’s center for all things data, including resources, professional development, and assistance. They offer trainings in a variety of technical skills, including R and Python. They offer frequent workshops (sign up for their newsletter for updates), and they also post all of their materials on GitHub. They have a variety of levels of workshops on R, including:
  • R Fundamentals: Parts 1-4 (no prior knowledge assumed)
  • R Data Wrangling and Manipulation
  • R Visualization

• Berkeley Psych’s Fall R Workshop (QuACK; Fall 2020): Semester-long and more extensive intro to R workshop taught by Willa and Elena for first-year PhD students in the department

• University of Oregon Psych Department’s R Bootcamp

Books and Guides

• R for Data Science
• A Pirates Guide to R
• Learning Stats with R by Dani Navarro

Tidyverse and ggplot2 Resources

• Tidyverse Style Guide
• ggplot Book
• ggplot Flipbook: Cool flipbook where as you scroll, you add layers onto your ggplot: code on the left and plot on the right to see how when you add lines of code your plot changes (Note: Code is not necessarily in the order generally used, but in an order to show how the plots are built up and what each line does).
• STDA: Easy, step-by-step guides for ggplot and much more.
• Tidy Tuesday: A podcast and community activity for learning R in real-world contexts (Also see twitter resources below).
• See Tidyverse’s learn page for more

R “Cheat Sheets”

• Data wrangling with dplyr and tidyr
• Data visualization with ggplot
• List of more cheatsheets

People to know of and follow on Twitter

• Hadley Wickham, @hadleywickham: Chief Scientist at RStudio, and an Adjunct Professor of Statistics at the University of Auckland, Stanford University, and Rice University, excellent R teacher who has written books on it and helped develop tidyverse packages
• Allison Horst, @allison_horst: Assistant Teaching Professor at the Bren School of Environmental Science and Management at UC Santa Barbara, where she teaches statistics, data analysis, and science communication, and an amazing artist who created illustrations depicting how many tidyverse functions work! https://github.com/allisonhorst/stats-illustrations
• Danielle Navarro, @djnavarro: Computational cognitive scientist, and data science teacher, she has great materials on her YouTube channel
• Twitter accounts to follow:
  • @R4DScommunity, which hosts #TidyTuesday, a short and fun weekly data project in R for the R4DS community to do!
  • @RLangTip
  • @RLadiesGlobal and @WeAreRLadies
  • @rfortherest
  • @rstatsmemes

Additional Resources

A more extensive list of R resources can be found here.