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

Software for Data Analysis: Programming with R (Statistics and Computing) [Kindle Edition]

John Chambers
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From the reviews:

"R is nowadays the language used in programming for statistics. Most of the thesis and practical programming are implemented in this language. This is a valuable book for every body involved in data analysis, not only statisticians. Being written by the father of S programming language, as R is S based, the development of the presentation as well as the advises are good for fitting the minds of the students within the roots of the art of programming with R." (J. Scheneweiss, Revista Investigación Operacional, Vol. 30 (2), 2009)

“…Written by one of the developers of R’s predecessor, S, the book’s aim…is to take the reader ‘from user to programmer to contributor’ in R. …It is written in plain, clear English. The necessary terminology that is specific to R is defined over the course of the book and is easy to locate should a reader not start from the beginning. The author has attempted to keep chapters somewhat independent so that not starting from the beginning is an option for more advanced R users who are in need of a reference rather than a tutorial. There are two special indexes, separate from the main index, covering ‘R Functions and Documentation’ and ‘R Classes and Types.’…I would expect that this book will find a home on a great many bookshelves. …” (Biometrics 65, 1313, December 2009)

“…This is a book that will appeal to readers of diverse backgrounds. For R users it has a wealth of information on learning to use R effectively; from efficient and reliable programming to writing packages. It is an authoritative reference for programmers and developers. It is the type of book that will be referenced often, as the reader’s experience with R, level of expertise and interest in programming grows.” ( The American Statistician, August 2009, Vol. 63, No. 3)

“This text is about using computer software, in particular R, for obtaining information from the data … . ‘is aimed at those who need to select, modify, and create software to explore data, in other words, to program.’ … The book is aimed at (i) data analysts, namely anyone involved in exploring data, from data arising in scientific research to, say, data collected by the tax office; (ii) researchers in, and teachers of, statistical techniques and theory; (iii) those primarily interested in software and programming.” (Susan R. Wilson, Zentralblatt MATH, Vol. 1180, 2010)

“This book is for software developers and advanced R users who want to become export R users: developing packages and new classes, and working with methods and generic functions. … This book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual steps, starting with simple functions. More advanced programming techniques can be added as needed…. Software developers and advanced R users should find that this book is full of wisdom … .” (David J. Olive, Technometrics, Vol. 52 (2), May, 2010)



John Chambers has been the principal designer of the S language since its beginning, and in 1999 received the ACM System Software award for S, the only statistical software to receive this award. He is author or coauthor of the landmark books on S.
Now he turns to R, the enormously successful open-source system based on the S language. R's international support and the thousands of packages and other contributions have made it the standard for statistical computing in research and teaching.
This book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated.
The techniques covered include such modern programming enhancements as classes and methods, namespaces, and interfaces to spreadsheets or data bases, as well as computations for data visualization, numerical methods, and the use of text data.


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2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen R verstehen 27. März 2010
Von jl
Format:Gebundene Ausgabe
Das Open-Source-Projekt R implementiert die Statistik-Programmiersprache S und stellt eine Umgebung für statistische Berechnungen bereit. John Chambers ist der Erfinder von S und Mitglied im R Core Development Team. Dies hervorragende Buch (SoDA) ist nicht für Einsteiger gedacht, z.B. wird die Erstellung eigener Pakete schon vor "Basic data and computations" behandelt. Dem fortgeschritteneren Nutzer hilft das Buch zu verstehen, wie R intern funktioniert und wie man R als *Programmiersprache* nutzt. SoDA ist eines der besten Bücher, die ich seit K&R auf diesem Gebiet gelesen habe: präzise formuliert, gewürzt mit historischen Anekdoten. 5 Sterne trotz verzichtbarer (?) Star Trek Zitate.
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1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Pflichtlektüre! Ein absolutes Muss! 23. Februar 2010
Von W.D.72
Format:Gebundene Ausgabe
Jeder der R nicht nur anwenden sondern auch verstehen will, wie es funktioniert sollte unbedingt einen Blick in dieses Buch werfen. Es erwartet Ihn eine geballte Ladung Know-How von einem der Designer der Sprache S, die man guten Gewissens als Grundstein von R betrachten kann und der sich nunmehr in diesem Buch R zuwendet. Klar und verständlich geschrieben und neben der zur Installation gehörigen hervorragenden R Dokumentation und R in a Nutshell ein absolutes "must have".
War diese Rezension für Sie hilfreich?
Die hilfreichsten Kundenrezensionen auf (beta) 4.0 von 5 Sternen  10 Rezensionen
58 von 58 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen The gateway from 'pretty good' to 'expert' 1. September 2008
Von J. Michaelson - Veröffentlicht auf
Format:Gebundene Ausgabe
This is not an introductory text, and should not be the first R book in your collection. However, if you are a "pretty good" R programmer and want to take the next step in becoming an "expert" R programmer, this is your Bible.

For me, this book fills the hole of understanding how R thinks. To get a complete and accurate view of why R works the way it does, the author supplements the technical discussion with the philosophy of R, as well as pieces of the history of statistical computing and computing in general.

Others might consider this integration of technical detail with philosophical and historical background (complete with Star Trek references) to be "wordy", but this is precisely why I bought the book. If one is interested only in the purely technical aspects, the thorough documentation on the R website is free. I consider the insights - provided by the mind that laid the foundation for R in S - to be well worth the price of the book.

That said, this book is an invaluable guide (both technical and philosophical) on the road to becoming an R expert. I'm looking forward to putting some dog ears on my copy.
33 von 33 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen could have been titled _Understanding_How_R_works_ 18. Juli 2009
Von davs2rt - Veröffentlicht auf
Format:Gebundene Ausgabe
For the past year or so I have been puttering with R, but never really "got it". This book is just what I've been looking for, to understand what R is "thinking". It isn't a cookbook with loads of examples, but a thorough guide to understanding how R works and how to be productive in it. After only an hour, I understand data.frames, and the environment structure better than several nights of struggling with the online documentation. This isn't really a book about how to analyze data, it's about becoming comfortable and expert in R to make it easy to analyze data. Once you understand the tool, the data analysis becomes much much easier.

I agree with the reviewers who say it's chatty, but that makes it very readable. You don't have to work every example to understand the points the book is making. Likewise, it _is_ cross referenced to death, but it's easy enough to read over the links, and when you're trying to make sense of something, the cross references do take you to the right information to round out a picture.
11 von 11 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Enlightening 1. Oktober 2009
Von Rodrigo Aluizio - Veröffentlicht auf
Format:Gebundene Ausgabe|Verifizierter Kauf
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.
5 von 5 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Very insightful but poorly edited text 19. Mai 2014
Von Code Monkey - Veröffentlicht auf
Format:Gebundene Ausgabe|Verifizierter Kauf
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.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Should be titled Understanding how R works and building interfaces 18. August 2013
Von timers - Veröffentlicht auf
Format:Gebundene Ausgabe|Verifizierter Kauf
I don't know where else to find all the useful information in this book. It was INVALUABLE as I tried to extend R with software packages, a must for anyone who wants to understand the R internals better.
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