Where to Learn More

This reader provides an introduction to the basics of R, but there’s lots more to learn!

DataLab’s Intermediate R workshops are designed specifically for learners who have taken this workshop and want to learn more about R.

DataLab also teaches many other workshops about data science. If you’re not sure where to start or how these workshops all fit together, take a look at our Reproducibility Principles and Practices reader.

If you want to learn more about how to design clear and effective data visualizations, take a look at our Principles of Data Visualization reader.

Many R and data science learning resources are available for free online or through the library. Here are a few books created by others that we’ve found useful:

• R for Data Science by Wickham & Grolemund. An introduction to using R for data science, but with a very heavy focus on Tidyverse packages.
• The Art of R Programming by Matloff. A general reference on R programming.
• Advanced R by Wickham. A description of how R works at a deeper level, with many examples of R features that are important for package/software development.
• The R Inferno by Burns. A discussion of the most difficult and confusing parts of R.

Finally, here are some websites popular in the R community:

• R Graph Gallery. Examples of graphs you can make in R, with code.
• RStudio Cheat Sheets. Cheat sheets for a variety of R tools and packages.
• R Weekly. Weekly updates about what’s happening in the R community.
• R-bloggers. An aggregator for blog posts about R.