I am using R for three years now, I would recommend the following as resources that have helped me a lot to climb the steep learning curve of R.
As far as getting started with R by reading stuff, there is of course this book. Also, available from CRAN are
- An Introduction to R
- R Data Import/Export
- Writing R Extensions: A Discussion about how to write and organize R packages
- R Installation and Administration: This is one of the greatest article for building R from the source code
- R Internals: This is a manual which describes the low level structure of R. It is primarily for developers and R core members
- R Language Definition: This documents the R language and, again, is primarily for developer.
R Programming Resources:
- Checkout R Documention from CRAN.
- Learn very basic interactive tutorial from Code School
- R and Data Mining.
Best Books for R :
- R Programming for Data Science by Roger D. Peng
- R Cookbook
- R for Everyone
- Hands-On Programming with R
- The Art of R Programming – A Tour of Statistical Software Design
- Beginning R: The Statistical Programming
- Advanced Analytics and Graphics (Addison-Wesley Data & Analytics Series)
- Machine Learning With R
- Major technical publishers like Springer, Chapman & Hall/CRC have entire series of books dedicated to using R in various applications. For example, Springer has a series of books called
• A longer list of books can be found on the CRAN web site
- Hadley Wickham’s website:
- Hadley Wickham’s devtools wiki:
- J. D. Long (@CMastication) has a great resource page here:
- @CMastication recommends QuickR in particular
- @DataJunkie and his colleagues in UCLA Statistical Consulting Services have put together a great starter guide:
Learn Probability with R
Two awesomet books on probability use R for their “hands on” programming examples.
These are just two books that I have came across. If you dig deeper, you’ll find that among probability books that use a programming language, many (if not most) of them use R.
Learn statistics with R
Many statistics textbooks use R as a learning tool. For an introductory look a here’s one good book:
Learn Bayesian statistics with R
If you want to learn Bayesian stats and Bayesian analysis, nearly all of the books use R. According to my knowledge the best books that teach Bayesian statistics use R.
If you’re interested in Bayesian stats, check out these:
Learn Data Visualization in R
If you’re learning data visualization, I highly recommend a book named as Exploratory Data Analysis with R by Roger D. Peng. It is an awesome data visualization tutorials for the R programming language. This book is for sale at http://leanpub.com/exdata
There is another good book named as R for Data Science which provides a great introduction to data visualization, but additionally teaches you a broad set of data tools in R. I also recommend a book Data Points as a companion, though it teaches principles as opposed to programing language syntax. First, if you’re interested in data visualization in R, you need to read a book called ggplot2. It not only teaches you the syntax of this critical R data visualization library, but it will also reshape how you think about visualizing your data.
Learn machine learning with R
Here are two excellent introductions to machine learning that teach ML using the R programming language.
Check out my post about Top 6 MOOCS for Learning R Programming