28 of 29 people found the following review helpful
An essential for any R programmer.,
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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Initial post: 7 May 2014 12:26:36 BDT
Ricky McMaster says:
Great review, appreciated.
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