(This post is the preliminary version of a book review by Alessandra Iacobucci, to appear in CHANCE. Enjoy [both the review and the book]!)
As Rob J. Hyndman enthusiastically declares in his blog, “this is a gem of a book”. I would go even further and argue that The Art of R programming is a whole mine of gems. The book is well constructed, and has a very coherent structure.
After an introductory chapter, where the reader gets a quick overview on R basics that allows her to work through the examples in the following chapters, the rest of the book can be divided in three main parts. In the first part (Chapters 2 to 6) the reader is introduced to main R objects and to the functions built to handle and operate on each of them. The second part (Chapters 7 to 13) is focussed on general programming issues: R structures and object-oriented nature, I/O, string handling and manipulating issues, and graphics. Chapter 13 is all devoted to the topic of debugging. The third part deals with more advanced topics, such as speed of execution and performance issues (Chapter 14), mix-matching functions written in R and C (or Python), and parallel processing with R. Even though this last part is intended for more experienced programmers, the overall programming skills of the intended reader “may range anywhere from those of a professional software developer to `I took a programming course in college’.” (p.xxii).
With a fluent style, Matloff is able to deal with a large number of topics in a relatively limited number of pages, resulting in an astonishingly complete yet handy guide. At almost every page we discover a new command, most likely the command we had always looked for and done without by means of more or less cumbersome roundabouts. As a matter of fact, it is possible that there exists a ready-made and perfectly suited R function for nearly anything that comes up to one’s mind. Users coming from compiled programming languages may find it difficult to get used to this wealth of functions, just as they may feel uncomfortable not declaring variable types, not initializing vectors and arrays, or getting rid of loops. Nevertheless, through numerous examples and a precise knowledge of its strengths and limitations, Matloff masterly introduces the reader to the flexibility of R. He repeatedly underlines the functional nature of R in every part of the book and stresses from the outset how this feature has to be exploited for an effective programming. Continue reading