Programming Languages - R
R is a free, open-source software environment for statistical computing and graphics. It is able to compile and run across a wide variety of UNIX platforms, Windows, and MacOS.
- "Official" introduction manual HTML | PDF
- "Official" FAQ HTML
- List of Packages HTML
- Quick Refernce Card PDF
RStudio
RStudio is an integrated development environment (IDE) for R. The RStudio IDE is free and open-source that works across Windows, Mac, and Linux platforms.
Other IDEs, Editors, and Tools
- Rattle, gui for Data Mining using R Rattle
- ESS, Emacs Speaks Statistics ESS
- Vim-R plugin Vim
- Revolution Analytics RA
- Try R Online with R-Fiddle
Reproducible Research
Integrate publishing directly into code. R Markdown builds on Markdown with the ability to embed R code. Sweave also for combinging R with LaTeX. Pandoc is a universal mark-up converter.
- R Markdown Link
- Rpubs, public repository of RMarkdown in RStudio Rpubs
- Information on R Markdown with RStudio Link
Online Resources
- Cookbook for R Cookbook
- SimpleR by John Verzani, Using R for Introductory Statistics PDF
- The R Inferno by Patrick Burns, "If you are using R and you think you’re in hell, this is a map for you." PDF
- R Fundamental and Programming Techniques, Thomas Lumly - slides as PDF
- Learn R programming CodeSchool
- R Coding conventions Link
Online Courses
- Coursera Learn R Programming
part of a 9 course series on Data Science - edX Intro to R for Data Science
Tutorials
- Quick-R Tutorial
- R Tutorial, Kelly Black Tutorial
- Twotorials, video tutorials Tutorial-videos
- Di Cook, ACAS 2008, Tutorial, slides & code
Blogs
- Revolution R Blog
- R Bloggers
- Top 100 posts on R-bloggers Top posts