Authors Norman Matloff
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Product Description
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.
The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.
Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to:
* Create artful graphs to visualize complex data sets and functions
* Write more efficient code using parallel R and vectorization
* Interface R with C/C++ and Python for increased speed or functionality
* Find new packages for text analysis, image manipulation, and thousands more
* Squash annoying bugs with advanced debugging techniques
Product Details
# Paperback: 400 pages
# Publisher: No Starch Press; 1 edition (October 12, 2011)
# Language: English
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Reviews
The comparisons with C programming annoying in the first part of the book. The author continuously goes on about "if you're a C programmer" and then some comparison to C. I didn't find this helpful (and I am a C programmer) and I think it could have been safely left out. A good example of this is on page 12 where is says "Matrices are indexed using double subscripting, much as in C/C++, although subscripts start from 1 instead of 0." So pretty much not like C/C++. That's a good example of how the C interludes don't help the new reader.
Just occasionally the author gets ahead of himself. Early on in the book he introduces matrices and on page 28 does a matrix addition in the form m + 10:13. He hasn't explained how that addition is going to work.
There are lots of free R tutorials out there, among which, "The R Inferno" by Patrick Burns is my favorite. The Art of R Programming, however, covers much more grounds in much greater depth. In addition to standard data structure such as vector and matrix, the book discusses lists, data frames and factors in more detail than I have found in almost all other R books. In programming part, the discussion of R's powerful lexical scope is very thorough. It even has examples of using recursion to do quicksort and build binary trees. The book also covers S3 and S4 object models well. Two other topics you do not usually find are string manipulation and debugging. The book reflects state of art of R programming with a chapter dedicated to parallel computing in R. The recently introduced R byte complier is also discussed.
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