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Book by Cotton Richard

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Amazon.com: 11 commentaires
12 internautes sur 12 ont trouvé ce commentaire utile 
Why Such a Low Rating? 3 juin 2014
Par Kim Jong Un - Publié sur Amazon.com
Format: Format Kindle
I was going to give a four-star rating on this book, but seeing all these one and two stars made me give five instead. As someone starting out with R, you shouldn't expect book like this to read like a bible. Learning R is what it is -- a concise and easy tutorial for a beginning R student, and this is exactly what this book delivers. I see that some reviewers suggested R in Action or R for Everyone, and don't get me wrong those are excellent textbooks. The problem with those books is that they contain no exercises, and that could spell a major trouble for undisciplined learners like myself. Learning R, on the other hand, may not be the most comprehensive tome on the subject of R, but it does accomplish what it set out to do --- get started with R and move on to advanced R/data analysis topics -- by breaking down the contents into small chapters and providing review questions and exercises at the end of each chapter.
24 internautes sur 29 ont trouvé ce commentaire utile 
There are better options now 1 novembre 2013
Par Dimitri Shvorob - Publié sur Amazon.com
Format: Broché
The low rating reflects my opinion of the book vis-à-vis the alternatives, not its merits when viewed on its own. My original review was actually robust four stars; I did point to a book which, in my opinion, was a better proposition than "Learning R" - "R in Action" by Robert Kabacoff - but acknowledged a few areas where "Learning R" had the edge. Then "R for Everyone" by Jared Lander came out and, what can I say, I see "R in Action" and "R for Everyone" as the two plausible beginner-to-intermediate-R-book choices, and "Learning R" a very distant third.
6 internautes sur 8 ont trouvé ce commentaire utile 
Intro to the R language 20 novembre 2013
Par IADev - Publié sur Amazon.com
Format: Broché
With a background as a developer, I found this book very approachable having not touched R before this book. It remained close to the R language itself and did not veer too deep into statistics. For a programmer new to the language and the topic, I was fine with the subject matter depth. I really liked that the end of each chapter included a quiz as well as exercise portions. The answers are included as part of the Appendix and I think are a good reminder to readers to try out what they just learned. Part of learning new languages is finding about different concepts or how data structures are implemented with different names, functions, or packages. Newer topics to me were data frames and factors. These concepts are explained very well and allowed for me to quickly apply existing knowledge from other languages to make the concepts clear. In my opinion, I really liked the chapters involving getting data and on cleaning and transforming. These chapters are very practical and apply to anyone who has had to parse data in one format to put it into another. Topics like loading packages and data and time coverage are sections that you would expect to be in a book for beginners new to the language and hint at the audience this book is geared toward. It is a good starting point for those totally new to the language who will use this as a foundation to dig deeper for specific tasks later.

Overall conclusion: Good for the programmer interested in learning the R language over in-depth statistics.
Disclaimer: I got a copy of this book for review as part of O'Reilly blogger program.
but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusin 27 novembre 2015
Par Luis-philly - Publié sur Amazon.com
Format: Broché Achat vérifié
If you want to start learning R, there several things you may want to consider. There are two kind of skills you want to cultivate: programming skills and actual data analysis ones. In principle, you can learn techniques alone, but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusing only on coding may make you a good programmer, but it will be hard to get started on putting your skill into practice.

Any book should strike a tradeoff in where to stand between training you in these two topics. Cotton's book try its best in this and does a pretty good job. The first part of the book, covering the intricacies of the language is the one I found most useful. I has all sort of good advise and explanations on the data structures and functions you can use. It is appropriately applied - not just about computation and programming, but actually links how they are applied in the actual data analysis. In this sense, this was the most original and interesting part of the book. The second part of the book, covering data analysis techniques was more conventional but still good. As such, there are perhaps better books if you are interested on any of the two sides ("machine learning for hackers" is very good to learn how to apply the techniques and seeing them in action; "Introduction to statistical learning" is a bit more theoretical; Advanced R or The Art of R Computing are unbeatable about teaching the language, although a bit dray).

The approach of Cotton is really instructive. He is friendly, he write well in a easygoing fashion and the book is full of useful tips that helped me to understand how the language merge with the technique.

The book is not encyclopedic, it does not cover every single topic (there are better books for that, Matloff and Wickhams books are better). Instead, it does a really good job as a tutorial that walks you through many topics that are somehow not covered in many other books -the chapter that covers factors and dates is perhaps not something you will deal with everyday, but very useful if you have to.

Overall, I think the book teaches you really well how to play with the R language.

A very final remark. I've seen other comments that suggest this is an introductory book. The book hardly takes things from scratch. If you have never written a line of code, you are likely to find it, particularly the first part, pretty dry. It is more an intermediate text, otherwise you will find yourself wondering why you need to know all these pages about data structures if you just want to learn to load a csv file and run a regression.
1 internautes sur 1 ont trouvé ce commentaire utile 
Clear, concise and witty introduction to R 31 juillet 2014
Par Jens Meydam - Publié sur Amazon.com
Format: Broché
If you are looking for an introduction to R that prepares you for more advanced texts "Learning R" is an excellent choice. If you already know R this book still deserves five stars, but you may want to buy another book.
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