Art of R Programming
A Tour of Statistical Software Design
by Norman Matloff

October 2011, 400 pp.
ISBN: 978-1-59327-384-2
Contents | Reviews | Updates

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 R packages for text analysis, image manipulation, and more
  • Squash annoying bugs with advanced debugging techniques

Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

About the Author

Norman Matloff is a professor of computer science (and was formerly a professor of statistics) at the University of California, Davis. His research interests include parallel processing and statistical regression, and he is the author of a number of widely-used Web tutorials on software development. He has written articles for the New York Times, the Washington Post, Forbes Magazine, and the Los Angeles Times, and is the co-author of The Art of Debugging (No Starch Press).

Table of Contents

Introduction

Chapter 1: Getting Started
Chapter 2: Vectors
Chapter 3: Matrices and Arrays
Chapter 4: Lists
Chapter 5: Data Frames
Chapter 6: Factors and Tables
Chapter 7: R Programming Structures
Chapter 8: Doing Math and Simulations in R
Chapter 9: Object-Oriented Programming
Chapter 10: Input/Output
Chapter 11: String Manipulation
Chapter 12: Graphics
Chapter 13: Debugging
Chapter 14: Performance Enhancement: Tradeoffs in Time and Space
Chapter 15: Interfacing R to Other Languages
Chapter 16: Parallel R

Appendix A: Installing R
Appendix B: Installing and Using Packages

View the detailed Table of Contents (PDF)

View the Index (PDF)

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Reviews

"The book I'd recommend for someone wanting to learn R, especially for someone with more experience in programming than statistics."
—John D. Cook, The Endeavor (Read More)

"If a person really wants to be able to speak the R language and become a competent R programmer then, at the present time, one can find no better guide than Norman Matloff’s The Art of R Programming."
—Joe Rickert, Revolution Analytics (Read More)

"If you're interested in adding R to your arsenal of programming tools, The Art of R Programming is a great way to get started."
—Pat Eyler, On Ruby (Read More)

"There is no reason why anyone with a need for statistical programming ought to choose any approach other than to obtain a copy of this book and work through it. Any other approach would be more expensive and far less efficient."
—Stephen Chapman, Ask Felgall (Read More)

"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."
—Bryan Bell, Math and More (Read More)

"If you've never written a line of code, you might find some of the concepts challenging, but if you have at least a vague idea of what programming is, you should find The Art of R Programming useful."
—Nathan Yau, FlowingData (Read More)

"With a fluent style, Matloff is able to deal with a large number of topics in a relatively limited number of pages, resulting in an astonishingly complete yet handy guide."
—Xi'an's Og (Read More)

"Has helped me capitalize on my coding experience and has made my relationship with the language much healthier (and efficient)! If you want to get more done with R, I highly recommend it."
—Derek Blanchette, Data, Statistics & Technology (Read More)

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