References

This reader would not have been possible without the many excellent reference texts created by other members of the R community. Now that you’ve completed this reader, these texts are a great way to continue you R learning journey.

Advanced R by Hadley Wickham is a must-read if you want a deep understanding of R. It provides many examples of R features that are important for package/software development.

Other texts I’ve found useful include:

• What They Forgot to Teach You About R by Bryan & Hester.
• The Art of R Programming by Matloff (of UC Davis). A general reference on R programming, with more of a computer science and software engineering perspective than most R texts.
• The R Inferno by Burns. A discussion of the most difficult and confusing parts of R.
• R Packages by Wickham. A gentle, modern introduction to creating packages for R.
• Writing R Extensions by the R core developers. A description of how to create packages and other extensions for R.
• R Language Definition by the R core developers. Documentation about how R works at a low level.
• R Internals by the R core developers. Documentation about how R works internally (that is, its C code).

Finally, here are a few other readers and notes created by DataLab staff:

• My personal teaching notes from several years of teaching statistical computing.
• R Basics, our workshop series aimed at people just starting to learn R.
• Adventures in Data Science, our course introducing humanities undergraduates to data science techniques.
• Python Basics, our workshop series aimed at people just starting to learn Python.
• Intermediate Python, this reader’s counterpart for Python users.