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25 of 26 people found the following review helpful
5.0 out of 5 stars An essential for any R programmer.
I could make this review very short. Do you use R as a tool or do you want to use R to make new and better tools. If the former then you may not get full value from this book if the latter buy it. Buy it now. Yes it really is that good.

The Art Of R Programming is an excellent overview of statistical tool building with R and is nicely broken down as...
Published on 12 Nov. 2011 by renaissance geek

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3.0 out of 5 stars this book is useful if you want to master the nuts and bolts ...
The five star reviews here are highly dubious. That said, this book is useful if you want to master the nuts and bolts of R - data frames, matrices, functions, etc. Where it falls down is when the author begins to to lose himself in "Extended examples" which seem to serve no other useful purpose than that of him trying to show us how clever he is. Example: the section...
Published 25 days ago by malachy


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25 of 26 people found the following review helpful
5.0 out of 5 stars An essential for any R programmer., 12 Nov. 2011
This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
I could make this review very short. Do you use R as a tool or do you want to use R to make new and better tools. If the former then you may not get full value from this book if the latter buy it. Buy it now. Yes it really is that good.

The Art Of R Programming is an excellent overview of statistical tool building with R and is nicely broken down as follows:

Getting started - the obligatory how to get started with R and how to get help when you're using it. I'm not sure how useful this will be as I'm guessing that the majority of this book's market will be pretty R savvy.

Vectors - an in depth look at the fundamental R data type. Useful but dry.

Matrices and Arrays - matrices are essentially a special type of vector in R. Equally useful but equally dry!

Lists and Data Frames - two separate chapters covering multi-type data formats.

Factors and tables - covering single and multi-dimensional types for categorised data.

As you can see there is a lot of time spent on data types and corresponding functions. This is a little bit dry to read but covers the fundamental building blocks of R. It's worth reading these chapters and getting the basics down pat before trying anything more complex.

Programming structures - covers the programming fundamentals of loops, recursion and control structures.

Mathematics and simulations - this is probably the closest to a "how-to" you'll find in the book. This chapter covers mathematical functions.

Object oriented programming - pretty much as it says. I have to admit that I'm more a procedural than OO programmer so I only skimmed this chapter but it covers what you might expect.

Input/output - reading and writing files. This is actually a really useful chapter - if your chomping through large data files as I tend to do then having a good grip of how to get them into and out of R is going to be high on your list of requirements. The chapter covers both reading and writing files and reading and writing across the internet using sockets.

String manipulation - you might not expect that a statistical programming language would have much use for string manipulation but string functions are very useful for parsing textual information out of pre-existing data files. Most usefully it has a full suite of regular expression functions.

Graphics - or possibly more accurately graphs. When working with large and complex data sets a good visualisation is worth several million data points and this is where you will find out how to use R's graphing functions.

I'm going to lump the final topics together as they are pretty much all hardcore programming chapters covering debugging, performance enhancement, interfacing R to other languages and parallel programming. Of these chapters the one covering interfacing to other languages (other languages being C/C++ and Python) is probably going to see the most use. The others are much more niche but if you need them you're going to really need them.

The author's writing style is clear, concise and excellent and covers all the programming bases. If there is an omission at all it's that there isn't a functional cheat sheet or appendix which I like to see in any programming book. That aside if you work with R for anything other than just using a suite of existing tools this is an essential for your bookshelf.
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11 of 12 people found the following review helpful
5.0 out of 5 stars The only book you need to learn and master R, 17 Nov. 2011
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J. Tavares (PT) - See all my reviews
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
"The Art of R Programming" by Norman Matloff is an excellent book and probably is the only book you need to learn and master R. Master it as a programmer and not just as an occasional user. I was such a user, using R only for some statistical tests and doing some plots. However, Norman's book completely changed the way I approached R. By teaching it as a programming language rather than a statistical tool, it increased immensely my knowledge on R and making it more useful for my research work. The book covers the fundamentals about R (always with a programmer's view) and guides you to advanced and useful topics such as Parallel R, debugging, interface to other languages, etc. The writing style is very concise and clear. The explanations, advices and examples very good. This book convinced me early on to properly learn R and I am sure it is the best book for that. I highly recommend this book to everyone who needs to use R or wants to add it to their toolbox.
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7 of 8 people found the following review helpful
4.0 out of 5 stars Useful, but needs a glossary, 6 Sept. 2013
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
I needed some advanced statistical software and R came highly recommended. Having downloaded the software it became rapidly apparent I would need a guide. I have no background in computer program and the Amazon.co.uk reviews indicated this was the book for me. While I am finding the book useful as I slowly get to grips with how R runs, I would disagree about not needing previous computer programming experience. While the author explains some terms used, eg %%, I am left baffled by others and have to resort to online guides (which I was trying to avoid) in order to make sure I understand everything. If the author had included a simple glossary so I could understand why terms such as "==" are required, then I probably would have been all the way through the book by now and a competent R user. These may be simple for those with basic computer programming, but they are baffling to a newbie!

This all said I would recommend the book because it has increased my knowledge. The layout is good and the level of usage builds up gradually. However external sources are also required, hence my four star rating.
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3.0 out of 5 stars this book is useful if you want to master the nuts and bolts ..., 2 Jan. 2015
This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
The five star reviews here are highly dubious. That said, this book is useful if you want to master the nuts and bolts of R - data frames, matrices, functions, etc. Where it falls down is when the author begins to to lose himself in "Extended examples" which seem to serve no other useful purpose than that of him trying to show us how clever he is. Example: the section on matrix manupulations - you find yourself spending more time trying to wrap your head around the theoretical underpinnings of Random Markov Chains than actually assimilating the basic R functionality that the author is presumably trying to demonstrate. And this happens fairly regularly throughout the book.

In short, useful as a reference for some of the most important concepts in R but not exactly a pedagogical work of wonder either.
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3 of 4 people found the following review helpful
5.0 out of 5 stars Great introductory book for those who want to program in R, 17 Mar. 2013
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
The book requires no background in programming in general, and does a solid work explaining the basics of R data structures, data manipulations and so forth. Beginning with simple things, the book discusses some of the more advanced subjects as well. I have read a few books on R already, but this one has had the largest impact in terms of understanding the language. My programs became better and faster for sure.
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4 of 6 people found the following review helpful
5.0 out of 5 stars A book for developers., 25 Dec. 2012
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
Clearly doing what it states in the title, the book introduces the developer to the art of R programming.
It is written with a clear vision to address developers (C++, Pearl, etc) it fully succeeds not only to provide a smooth introduction to R, but also to be used as a reference book afterwords, for quick checking during development. Through the examples, the book manages to give the reader the flavor of developing algorithms in R, turning the learning process into an easy adaptation of programming skills to the comfortable R environment.
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2 of 3 people found the following review helpful
5.0 out of 5 stars As it says on the tin, 13 Jun. 2014
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
This book is an excellent short introduction to programming in R, explains clearly several of the key concepts that are unlike 'normal' languages - eg data frames. However, don't expect any discussion of statistics - that's not what this book is about.
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0 of 1 people found the following review helpful
5.0 out of 5 stars Joins the Top 3 of my favorite data science books, 24 Aug. 2014
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
Very well written, it's up there with Wes's Python for Data Analysis. Joins the Top 3 of my favorite data science books. Strongly recommend it, for anyone interested in R - beginner or intermediate level
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0 of 1 people found the following review helpful
5.0 out of 5 stars GOOD, 2 Jun. 2013
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
Very helpful book for R language learner with a reasonable price. Clear structure and understandable interpretation. Good for both starter and higher level. Strongly recommend it.
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0 of 1 people found the following review helpful
5.0 out of 5 stars Great book, 21 Feb. 2013
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This review is from: The Art of R Programming: A Tour of Statistical Software Design (Paperback)
This is really nice book and it is very good place to start and also the advanced R users can learn few useful tricks. I would strongly recommend this book.
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The Art of R Programming: A Tour of Statistical Software Design
The Art of R Programming: A Tour of Statistical Software Design by Norman Matloff (Paperback - 15 Oct. 2011)
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