R

R is a widely used programming language and software environment for statistical computing and graphics. The software is free, open source and available for Linux, Mac and Windows platforms. The base installation is highly extensible and a huge set (5000+) of contributed packages is freely available for data import and manipulation, visualisation, statistical modelling, and reporting. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time.
The links below point to a selection of (hopefully) usefull resssources to learn and use R. Comments and suggestions are welcome.

Official information/documentation

• The R-project website
• The CRAN for R downloads and documentation
• R manuals edited by the R Development Core Team
• Task views – lists of useful packages by subject area
• Packages – full listing of contributed packages

Getting started

• An Introduction to R – “official” R introdution manual
• R Programming Tutorials – a collection of short videos by Gordon Davis using RStudio
• Introduction to R – a collection of short videos by Google Developers
• Advanced R programming – the in-progress book site for “Advanced R development” by Hadley Wickham
• Introduction à la programmation en R – a tutorial (in French) by Vincent Goulet with script files for examples
• Quick-R – a tutorial to get quickly access to R
• Try R – an interactive web-based R tutorial

Books
There are 100+ books on R programming and its use in applications. Here is a selection of books on R programming:

• The Art of R Programming by N. Matloff
• A beginner’s Guide to R by A. Zuur, E. Ieno and E Meesters
• R in a Nutshell: A Desktop Quick Reference by J. Adler
• The R Book by M. Crawley

Many books on applications with R were published by Springer (Use R! series), Chapman & Hall/CRC (the R series), Wiley, and O’Reilly.

Editors and IDEs

• RStudio – cross-platform open source IDE
• ESS (Emacs Speaks Statistics) – package for Emacs
• StatET – plugin for the Eclipse IDE
• NppToR – plugin for Notepad++

R coding style

• Google’s R Style Guide
• Hadley Wickham’s style guide
• Henrik Bengtsson’s R Coding Conventions

Blogs

• R-bloggers – an aggregator of R blogs
• Revolution analytics
• Rob Hyndman
• Dirk Eddelbuettel

Getting help

• RSeek – a search engine for R
• Stack Overflow
• R mailing lists such as R-help or R-SIG-Finance

Other ressources

• The R Journal – journal covering topics that might be of interest to R users/developers
• useR! – the international R user conference