This book is the second that I purchased this past year to get up to speed on the R language and environment, along with "R in Action" and "R Graphics Cookbook" (see my reviews), but unlike these other two, I fully expected this book to serve as a reference rather than a tutorial, based on my experience with "UNIX in a Nutshell" many years ago. However, through my experience I was quickly made aware of the breadth of the R language, which includes over 2500 packages that have become available to the community, and I have instead typically used this book as a starting point for additional research on websites which cater to the R community, including CRAN ("Comprehensive R Archive Network").
Even given its near 700-page size, it is difficult for any book to cover R extensively, so I credit this book to continue to provide pointers in the right direction as I gain experience using the language. While "R in Action" in its introductory chapters gets one up and running with R more gracefully, chapter 1 ("Getting and Installing R") and chapter 2 ("The R User Interface") in this book also provide a glimpse into the many options available with regard to environments. The closest that one will get with a tutorial in this book is the 18-page chapter 3 ("A Short R Tutorial"), but this chapter should really only be considered a way to wet one's appetite with regard to basic operations, functions, variables, data structures, objects and classes, models and formulas, and charts and graphics, as chapters 5 through 10 go over these topics more extensively.
Chapter 11 ("Saving, Loading, and Editing Data") along with Chapter 12 ("Preparing Data") provide useful information on working with data, because, like it or not, as with any language most data work revolves around first getting it into the correct format, but although these chapters present more available options in this area than "R in Action", these chapters also again read more like an encyclopedia and do not provide any guidance, because as is the case with most of this text, readers are likely best served when they have a decent idea of what they are looking to accomplish.
Most of my use of this book has involved Part 4 ("Data Visualization"), Part 5 ("Statistics with R"), and Part 6 ("Additional Topics"). After experimenting with the packages included with R by default, it is Chapter 15 ("ggplot2") which led me to purchase "R Graphics Cookbook", a well recommended book to learn the ggplot2 package, but it is the other chapters within this part of the book that made me realize that although the ggplot2 package provides standardization that is often lacking with R, no single package is likely to ever serve the needs of a developer, at least over time. Recommended text for those in the earlier stages of using the R language and environment and still finding their way, but not for the neophyte, as this book is not a tutorial, nor is it the encyclopedia one would expect from the "In a Nutshell" series.