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97_references.Rmd
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# (PART) Backmatter {-}
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][adv-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.
[adv-r]: https://adv-r.hadley.nz/
Other texts I've found useful include:
* [What They Forgot to Teach You About R][r-wtf] by Bryan & Hester.
* [The Art of R Programming][art-of-r] 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][r-inferno] by Burns. A discussion of the most difficult and
confusing parts of R.
* [R Packages][r-pkgs] by Wickham. A gentle, modern introduction to creating
packages for R.
* [Writing R Extensions][r-exts] by the R core developers. A description of how
to create packages and other extensions for R.
* [R Language Definition][r-lang] by the R core developers. Documentation about
how R works at a low level.
* [R Internals][r-ints] by the R core developers. Documentation about how R
works internally (that is, its C code).
[r-wtf]: https://rstats.wtf/
[art-of-r]: https://ebookcentral.proquest.com/lib/ucdavis/detail.action?docID=1137514
[r-inferno]: http://www.burns-stat.com/documents/books/the-r-inferno/
[r-pkgs]: https://r-pkgs.org/
[r-exts]: https://cran.r-project.org/doc/manuals/R-exts.html
[r-lang]: https://cran.r-project.org/doc/manuals/r-devel/R-lang.html
[r-ints]: https://cran.r-project.org/doc/manuals/r-devel/R-ints.html
Finally, here are a few other readers and notes created by DataLab staff:
* [My personal teaching notes][notes] from several years of teaching
statistical computing.
* [R Basics][r-basics], our workshop series aimed at people just starting to
learn R.
* [Adventures in Data Science][adventures], our course introducing humanities
undergraduates to data science techniques.
* [Python Basics][py-basics], our workshop series aimed at people just starting
to learn Python.
* [Intermediate Python][int-py], this reader's counterpart for Python users.
[notes]: https://github.com/nick-ulle/teaching-notes
[r-basics]: https://ucdavisdatalab.github.io/workshop_r_basics/
[adventures]: https://ucdavisdatalab.github.io/adventures_in_data_science/
[py-basics]: https://ucdavisdatalab.github.io/workshop_python_basics/
[int-py]: https://ucdavisdatalab.github.io/workshop_intermediate_python/