R's popularity as a language for statistics, data analysis and data mining is increasing year on year, and as you'd expect there are some good books on the subject. R's strengths mean it is one of the most commonly used programming languages used in data mining. In this guide, we've highlighted the best of the R books that we've reviewed on I Programmer.

I Programmer covers hundreds of programming titles per year, good and bad, to make it easier for you to find the right ones. Our Programmer's Bookshelves aim to highlight the best.

If you want to read more of the original review click in the link in each title. The thumbnails of the book jacket in the side panel provide links to the Amazon website.

If you just want to view the book's product details (without making a purchase) click in the top portion of the thumbnail to open the book's product details page. If you do decide to buy a book via Amazon, accessing it from a link on I Programmer means that we are credited with a few cents - so thanks to all of you who support us in this way.

Learning R

Author: Richard Cotton
Publisher: O'Reilly
Pages:400
ISBN: 978-1449357108
Print: 1449357105
Kindle: B00F2ZO8Z6
Audience: Statisticians; novice programmers with a stats background
Rating: 4

Books on R often cover both programming and statistics. This one is only about the language, and Mike James thought it merited four stars, noting that readers looking for a book that teaches stats and R are going to think it isn't very good. 

If you know the stats and want to learn R as if it was a standard programming language then this might well be the book for you. Mike also pointed out that the teaching approach is very slow and very detailed. If you are an expert programmer it might not be fast paced enough and might not go deep enough.

R Cookbook  

Author: Paul Teetor
Publisher: O'Reilly
Pages: 236
ISBN: 978-1492040682

For the right reader this is an excellent book, according to Mike James, who reviewed the first edition. This has been expanded with a more recent second edition. Mike gave the book the maximum five stars, and said it's a good introduction to R and its basic use.

The programming might be a bit too simple for the advanced programmer and the statistics sections a bit too simple for the advanced statistician - but this probably means that there is a big audience who will find some aspect of the book really useful. None of the recipes are advanced or obscure and you could find out how to achieve the same result by reading the documentation - but the book presents things in a much more digestible form. It is worth getting just to have R's approach to data types sorted clearly.

Mike's conclusion is that while the book isn't essential for the R programmer or the statistician using R, it really will make your life easier whenever you need to do something new. So get a copy.

R in 24 Hours  

Authors: Andy Nicholls, Richard Pugh, Aimee Gott
Publisher: Sams 
Pages:624 
ISBN: 978-0672338489

Overall this is a good book, according to Mike James, who awarded it four stars, noting that the most important thing to know is that it won't teach you statistics and it is about programming in R. He says that the only real problem is that the presentation isn't from a programming point of view. If you are a programmer and want to learn R then you will find it hard going because it hardly makes use of the deeper ideas of programing to make things seem easier and logical.

Mike says that if you aren't a programmer then you are likely to find the approach good as long as you take your time and come back to the book when you need to clarify some aspect of using R. Overall, he recommends the book as long as you know stats and don't want to become a programmer in general - just an R programmer.

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