The Art of R Programming
- 6h 7m
- Norman Matloff
- No Starch Press
- 2011
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
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, Ph.D., is a Professor of Computer Science at the University of California, Davis. He is the creator of several popular software packages, as well as a number of widely-used Web tutorials on computer topics. He has written articles for the New York Times, the Washington Post, Forbes Magazine, the San Francisco Chronicle, and the Los Angeles Times, among others, and is also the author, with Peter Jay Salzman, of The Art of Debugging (No Starch Press).
In this Book
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Art of R Programming—A Tour of Statistical Software Design
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Getting Started
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Vectors
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Matrices and Arrays
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Lists
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Data Frames
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Factors and Tables
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R Programming Structures
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Doing Math and Simulations in R
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Object-Oriented Programming
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Input/Output
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String Manipulation
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Graphics
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Debugging
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Performance Enhancement: Speed and Memory
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Interfacing R to Other Languages
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Parallel R
