Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I would like to call this the best second book on R, except that I wouldn’t know what the first one would be. I learned R from classes and tutorials about 10 years ago, used it on my PhD and four articles, and use it today on a daily basis at work; yet only now, after reading this book, do I feel like I could possibly be called an R programmer rather than just a user.

The book deals with a variety of topics that are seldom discussed in the R tutorials you are likely to find freely available. Some are perhaps unnecessary in a book like this (Ch. 5 Style Guide), some could easily deserve an entire book (Ch. 7 OO field guide), but the chapters on Functions, Environments, the three chapters in Part II (Functional Programming) and the chapter on Non-standard evaluation are easily reasons enough to buy this book.

How many time indeed have you spent hours, frustrated, trying to write a function that would act as a wrapper around, say, lattice plotting functions that use non-standard evaluation? Or try to call subset() from another function, only to see cryptic error messages? Now, for the first time, the solution is not only clear to me; I feel like I could also explain to a colleague why things work the way they do.

R is incredibly powerful and dynamic and will, most of the time, do just what you expect it to do. But if you want to really understand what is going on under the hood, or if you want to write your own packages (whether for self-, internal-, or widespread use), you owe it to yourself to read this book.