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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.
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).
I learned a lot from ‘The Art of R Programming.’ This was my introduction to programming with R. I carefully worked through most of the examples in chapters 1-14 and skipped the last two chapters.
The material is very well organized, and the text guides the reader through the material. The strongest aspect of this text is its collection of well thought out examples that clearly demonstrate the concepts.
The difficulty of obtaining the data files for examples is the books only shortcoming. Many examples are meaningless without the data; I was unable to run the Mt. Rushmore example.
I recommend this excellent text without hesitation.
3 out of 3 people found this review helpful.
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