New to R?
There are hundreds of websites that can help you learn the language. Here's how you can use some of the best to become a productive R programmer.
Start by downloading R and RStudio.
Learn the basics
Visit Try R to learn how to write basic R code. These interactive lessons will get you writing real code in minutes, and they'll tell you immediately when you go wrong.
Broaden your skills
Work through The Beginner's Guide to R by Computerworld Magazine. This 30 page guide will show you how to install R, load data, run analyses, make graphs, and more.
Practice good habits
Read the R Style Guide for advice on how to write readable, maintainable code. This is how other R users will expect your code to look when you share it.
Look up help
When you need to learn more about an R function or package, visit Rdocumentation.org, a searchable database of R documentation. You can search for R packages and functions, look at package download statistics, and leave and read comments about R functions.
Seek help at StackOverflow, a searchable forum of questions and answers about computer programming. StackOverflow has answered (and archived) over 240,000 questions related to R programming. You can browse StackOverflow's archives and see which answers have been upvoted by users, or you can ask your own R related questions and wait for a response.
If you a have question that is more about statistical methodology there are also plenty of R users active on the the CrossValidated Q&A community.
You may ask for help from R and RStudio users on community.rstudio.com. To start a new community discussion, click here.
Keep tabs on the R community
Read R bloggers, a blog aggregator that reposts R related articles from across the web. A good place to find R tutorials, announcements, and other random happenings.
Subscribe to R-Weekly, a collaboratively maintained community newsletter summarizing each week in R.
Deepen your expertise
Once you've gained some familiarity with R, Advanced R provides an entertaining roadmap to some of the deeper subtleties of the language and how to work with it most effectively.
This blog post by Noam Ross also provides valuable advice for writing fast R code.
Got R down? Give Shiny a try
Now that you know R, work through our Shiny lessons to learn how to make interactive web apps with R.