Overview of R

Read about R, its history, connections to other languages, and alternatives for statistical computing. You will also learn about various interfaces that can be used to edit and run R code, such as RStudio.

Interfaces

Various applications can be used to edit or run R code.

Early developers preferred to run R via the command line console, succeeded by those who preferred an IDE. IDEs for R include (in alphabetical order) Rattle GUI, R Commander, RKWard, RStudio, and Tinn-R. R is also supported in multi-purpose IDEs such as Eclipse via the StatET plugin and Visual Studio via the R Tools for Visual Studio. Of these, RStudio is the most commonly used.

Editors that support R include Emacs, Vim (Nvim-R plugin), Kate, LyX, Notepad++, Visual Studio Code, WinEdt, and Tinn-R. The Jupyter Notebook can also be configured to edit and run R code.

R functionality is accessible from scripting languages, including Python, Perl, Ruby, F#, and Julia. Interfaces to other high-level programming languages, like Java and .NET C#, are available.