Software for Data Analysis: Programming with R (Statistics and Computing)

Reading the thoughts of a key designer or inventor of a programming language is always a treat. John Chambers was there when S was born, and perhaps no one is better qualified to write about the rationale behind the design of S-Plus and R than him. Unlike many books written by the creators of a programming language this one is not an introductory text. As the preface makes clear, it is written for relatively experienced R/S-Plus programmers who want to understand the design choices behind the language.The text assumes that the reader is familiar with packages, generic functions, model fitting formulae, and much of the base functions and libraries. The first instance of an interaction with the R system in this text (Section 2.2, page 13 in my copy) does not quite work if you copy and paste it! The next chapter starts with "constructing a fairly complicated linear model." Again, the code snippet there will not work if you just type it in, and there is no detailed explanation of what the code snippet actually does (but it would be "obvious" to some one experienced with statistical analysis in this language). Still another example is chapter 9 which describes (mostly S4) object classes. I doubt anyone without considerable experience with object oriented programming and the generic function mechanism in R would be able to make sense of this chapter without a lot of effort; consider, for example, that the term "slot" does not even have any entry in the index!I found the writing style formal, hard to read, and somewhat turgid. There are many seemingly bizzare choices of examples or topics, most notably an introduction to perl programming! I ended up comparing the text with the paper "Evaluating the design of the R language" from the ECOOP 2012 proceedings (easily found on the web). In a few pages that paper seemed to provide a considerable portion of the insight that this book contains, but without the somewhat overwrought philosophizing and Star Trek references. I cannot help but think a better editor would have helped improve this book tremendously. So I have to say that the book was a bit of a let down for me.I did find parts of this book truly outstanding and enjoyable. In my opinion the final chapter, titled "How R Works", should be required reading for any serious R programmer. The early chapters that dealt with debugging and organizing packages, as opposed to merely detailing language features, were very insightful. The focus is always on why the language works the way it does, and how it was intended to be used. Yes, this book can be considered the "Prime Directive" for R programmers!In the end this is a book that has definitely found a place on my bookshelf, but it is one I cannot really love. It's hard to read, and meanders too much. But it sprinkles enough truly insightful information through its four hundred odd pages that it is worth reading at least once, and perhaps many more times.

John Chambers was one of the creators of S, the ancestor of R, at Bell Labs in 1976, when his colleagues there were creating Unix and C, and as those languages revolutionized computing so did S revolutionize the practice of statistics. In other words, there can be few other people with Chambers' depth of understanding of how S and R came to be what they are. If you are an experienced user of R, you will enjoy this book very much, and learn many helpful things you didn't know, but it is not a book for beginners. (My favorite book on R for beginners is Garrett Grolemund's "Hands-On Programming with R".)The reviewer named Code Monkey "found the writing style formal, hard to read, and somewhat turgid," but I think that is far too harsh, and that "discursive" would be a fairer description. Moreover, the bar for clarity in writing about R has now been raised so high by Hadley Wickham, Yihui Xie, Garrett Grolemund and J. J. Allaire (all of whom, not coincidentally work for RStudio), that it would be difficult for anyone of Chambers' generation to compete in that dimension. In the long ago, when when Chambers was minted, sentences WERE long and readers were able to extract meaning from multi-clause sentences without conscious effort. It was a very different time.There is too much good stuff in this book to list, so all I will say is that it is enjoyable and thought-provoking, and if you open it at random you will be entertained to such a degree that you may eventually find yourself reading it regularly as a form of displacement activity. For a user and teacher of R, the book has more charm than most novels.

I agree with most reviews here. On one hand, it provides a lot of information about R that I cannot find anywhere else. On the other hand, the presentation style is awkward. I think the author could have done a better job organizing the information and explaining how R works. Each chapter seems to stand alone and does not follow any particular orders. The examples used are not particularly illuminating. For example, there are some examples that the author used to split the work between R and Perl. I don't quite understand why it was done that way and why it was discussed in the chapter of text processing. The examples work and if you need to call Perl from R to do some work, it maybe worthwhile to read that section. I give it a 3 star because it does provide some very useful information.

John Chambers, a pioneer and legend for many statistician who is the father of S language and the dream fulfiller for statisticians. The graphic statistics is once a dream for statistician from 1960's. Many statistician once dreamed about to use the high-quality graphics to say something about statistics. the dream get realized by Mr. chambers. The S language is born from the Bell lab which is a great place for the Unix lovers and the once expensive printer users.Now it is transplanted to the Microsoft Windows more than two decades. Mr. Chambers helps statistician fulfill the dream of last century- the graphic statistics and brings the people to the promised land of statistical computing. He is a superstar for statisticians, like Jeff Bezos to the Online book selling. The legend has something to say. So..we..LISTEN.....

Well, there is not a better way to understand any kind of processes than knowing the way it works. That is exactly the point of this book, and it is done in a didactic, uncomplicated way. You can find your own pathways to interact, program and get more and more from R. It will help with functions understanding and customizations, starting from the basic S language to R's specifics characteristics and goals. This book turns R easier than I have expected.

Okay. but certainly not a reference book. For example, if you want to look up how DataFrames are manipulated, good luck. Good book for learning, but get something like "R in a Nutshell" also.

Fantastic as a technical reference, not so great for a new programmer.

No aporta nada sobre otros textos de la misma editorial sobre R. Muy mal editado, tanto por tipografía, márgenes, ausencia casi total de figuras, etc.No lo recomendaría.

i bought this as used, but actually looks like brand new, more then happy with it, i have to read it now ;P