This book contains a fantastic first glance at the R language and its possibilities for statistical data analysis. The book is targeted to the new R programmer, and assumes just a basic knowledge of statistics. Easy to read, it provides readers with the basics to start working with this exciting language. Its main disadvantage: it is just too short and leaves the reader wanting more.
As a complete newbie to the R language, I have found the first recipes describing data input extremely helpful. These by themselves are worth the price of the book. R allows for quite a wide range of input formats as well as parsing options. The author gives illustrative examples for the functions and parameters used to import the most common file formats (e.g. csv). It seems obvious after reading these pages that finding this information in the R reference manual would have taken hours instead of minutes.
The second part of the book describes data representation within the R environment, namely vectors and data frames. This part is also very useful for the new R programmer: knowing the native R data types helps to understand how the statistical methods function.
The book ends with recipes describing basic statistical functions. While the first few examples are illustrative and helpful for about every new R programmer, I find that the last examples are way too specific and not as helpful. This leaves the reader with mixed feelings about the book: for such a short book, every single line should be meaningful to every reader.
Buy the book if you are new to the language and want to start using it and getting results in a matter of minutes, literally. Don’t buy it if you know your way around the language. If you are not in a rush, I would recommend alternative and more comprehensive readings, such as “R in a Nutshell” by Joseph Alder.