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R is a statistical programming language, and is highly optimized for that purpose (though additional functionality exists). It can be relatively slow and doesn’t use memory particularly effectively, but it has a wide variety of data analysis and statistical modeling functions and libraries. R syntax is a bit different than other languages, but you may collaborate with people who prefer to work in R, so it’s good to know your way around it.


Use the latest version of R that you can, but it’s not essential (usually) to stay on top of updates. R can be managed using conda, but conda only maintains some packages. It’s still generally good practice to create new environments for different projects.


Hadley Wickham has several good (and freely available online!) R books, depending on your level of familiarity:

Kieran Healy has an excellent book on data visualization using the ggplot2 library.

Development Environments

RStudio is the best graphical R IDE around. Otherwise, you can work in a text editor like Atom equipped with an R linter and (maybe) a code-completion package.

Last update: February 16, 2022