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Data Visualization and R Programming Books (Updated 2011-09-07)

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Disclosure

As you probably know, I live in the Portland, Oregon area and have for many years. One of the must-visit places here is Powell’s Books. The book links in this post will all take you to Powell’s as part of their Partner Program. If you’d like to join the program too, here’s the link.

Updated September 7, 2011: I recently purchased a Kindle, and quite a few of these books are now available in that format. For those that are, I’ve tweeted my Amazon Affiliate links out and have embedded those tweets here.

Updated May 18, 2010: There is an interesting discussion happening on LinkedIn about this subject, and quite a few links to data mining and predictive analytics resources have been posted there. So here’s the link. Enjoy! @znmeb

I’m a big fan of the R programming language, especially for data visualization. The following books are all books that I own and recommend.

The Grammar of Graphics (Statistics and Computing) by Leland Wilkinson http://t.co/zEz5210 via @amazon

2011/09/07 08:07 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Grammar of Graphics 2ND Edition

by Leland Wilkinson

ggplot2: Elegant Graphics for Data Analysis (Use R) by Hadley Wickham http://t.co/GfXsOJm via @amazon

2011/09/07 07:41 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Ggplot2: Elegant Graphics for Data Analysis (Use R)

by Hadley Wickham

Interactive and Dynamic Graphics for Data Analysis: With R and GGobi (Use R) by Dianne Cook http://t.co/TxTU5ov via @amazon

2011/09/07 07:46 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Interactive and Dynamic Graphics for Data Analysis: With R and Ggobi (Use R)

by Dianne Cook

Graphics of Large Datasets: Visualizing a Million by Antony Unwin http://t.co/8PKQMNI via @amazon

2011/09/07 07:49 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Graphics of Large Datasets: Visualizing a Million (Statistics and Computing)

by Antony Unwin

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Seco... by Jerome Friedman http://t.co/UjlmX1v via @amazon

2011/09/07 07:52 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

by Trevor Hastie

Modern Applied Statistics with S (Statistics and Computing) by W.N. Venables http://t.co/fxEeMPb via @amazon

2011/09/07 07:54 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Modern Applied Statistics With S 4TH Edition

by William Venables

S Programming (Statistics and Computing) by William Venables http://t.co/ptFdyms via @amazon

2011/09/07 07:58 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

S Programming (Statistics and Computing)

by William N. Venables

Software for Data Analysis: Programming with R (Statistics and Computing) by John Chambers http://t.co/N3ka81j via @amazon

2011/09/07 08:00 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Software for Data Analysis: Programming with R (Statistics and Computing)

by John M Chambers

Quantile Regression (Econometric Society Monographs) by Roger Koenker http://t.co/a22nCrG via @amazon

2011/09/07 08:04 via Tweet Button ReplyRetweetFavorite

M. Edward Borasky

Econometric Society Monographs #38: Quantile Regression

by Roger Koenker

Finding Groups in Data

by Leonard Kaufman

Programming with Data

by John M. Chambers

Interactive Graphics for Data Analysis: Principles and Examples

by Martin Theus

Oxford Statistical Science Series #18: Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations

by A. W. Bowman

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