Book Review: The Art of R Programming

My former professor, Norm Matloff, wrote “The Art of R Programming” and NoStarch Press was kind enough to send me a review copy.

The Art of R Programming is a straight forward explanation of R for programmers who are reasonably familiar with programming in another language. Matloff makes no assumptions of expertise in C or algorithms and his explanations are succinct and easy to follow.

If you’re aren’t familiar with R, it is a statistical programming language, with some similarities to Matlab.

Rating 9/10

The big advantages of R are (1) it’s high level, (2) reasonably easy to read, (3) functional in nature, (4) simple syntax. If you’re familiar with Python, it has a similar feel. Compared to complex languages such as C++, Java, etc, R is a breadth of fresh air due to the lightness of its syntax. That said as a programming language Python is nicer. R has a few annoyances (for me at least) that make it less pleasant to write in than Python.
A couple of those are:

• Non-standard assignment operator e.g. to assign 5 to x in R we use “x <- 5" instead of the normal "x = 5" used in other languages. This is annoying because a significant amount of programming is doing assignments and a two character assignment operator is twice as much typing. Contrast this with Python which uses the plain "x = 5".
• Vector creation using “c(1,2,3,4)”. Vectors in R are similar to lists in Python, it would be more natural to add a little syntactic sugar and use “[1,2,3,4]” for vector creation i.e. the same syntax as Python and many other languages.

The real reason to use R are its statistical libraries, it’s very widely used for statistics and is the most pleasant environment to work in.

The areas Matloff covers are:

1 Why R?	2 Getting Started	3 Vectors
4 Matrices	5 Lists	6 Data Frames
7 Factors and Tables	8 R Programming Structures	9 R Functions
10 Doing Math in R	11 Input/Output	12 Object-Oriented Programming
13 Graphics	14 Debugging	15 Writing Fast R Code
16 Interfacing R to Other Languages	17 Parallel R	18 String Manipulation
19 Installation: R Base, New Packages	20 User Interfaces	21 To Learn More

Much of the material is available online in tutorials such as John Cook’s, R Language For Programmers. The real gems are the chapters “Writing Fast R Code”, “Interfacing R to Other Languages”, and “Parallel R”. These chapters have great information that is not easily discoverable otherwise.

“The Art of R Programming” is a fun read, albeit somewhat specialized. If you need to do statistical work as a programmer I highly recommend buying it and spending an afternoon browsing it.

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