- Series: O'reilly Cookbooks
- Paperback: 438 pages
- Publisher: O'Reilly Media; 1 edition (March 25, 2011)
- Language: English
- ISBN-10: 0596809158
- ISBN-13: 978-0596809157
- Product Dimensions: 7 x 1 x 9.2 inches
- Shipping Weight: 1.6 pounds (View shipping rates and policies)
- Average Customer Review: 98 customer reviews
- Amazon Best Sellers Rank: #13,648 in Books (See Top 100 in Books)
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R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O'reilly Cookbooks) 1st Edition
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About the Author
Paul Teetor is a quantitative developer with Masters degrees in statistics and computer science. He specializes in analytics and software engineering for investment management, securities trading, and risk management. He works with hedge funds, market makers, and portfolio managers in the greater Chicago area.
Top customer reviews
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As with everything, there is a downside. R is accessed through a command line interface, has an overwhelming number of commands, and its syntax is difficult to learn and remember. R users, especially novices, will find this cookbook of tremendous help. It contains many brief sections, each of which lists example R code for a specific analysis task.
Tasks supported range from downloading and installing R through more complex data analysis. The sections I found most useful were:
- Finding Relevant Functions and Packages
- Performing Matrix Operations
- Editing a Data Frame
- Generating Reproducible Random Numbers
- Plotting Multiple Data Sets
- Predicting a Binary-Valued Variable (Logistic Regression)
Paul Teetor has produced a well-organized and useful reference book. The sections are straightforward and the example R code is no more complex than necessary. The explanations in each sections are instructive, yet concise. Numerous cross-links between sections allow readers to understand related tasks when writing more complex code. There are even a few sections on common R error messages and useful programming tricks. I recommend this book to anyone working with R who already has some background in data analysis with one or more other software tools.
Note: The book comes with an offer from the published to purchase upgrades as new versions are released. This seems like a good idea, but I have no experience with this from O'Reilly.
Most of the book just summarizes what you could learn from reading the on-line help. I expected detailed worked examples. The structure of the books follows a 'You want to do this, here's how to do it" format. But the "you want to do this" sections are more like "You want to use xyplot, here's the function call." But I can read about that from the command line. Not helpful.
Perhaps the book would be useful for someone just starting out, but there are plenty of on-line PDF versions of "Intro to R" books that you can print out for free.
I feel like a spent $30 for nothing.
published by O'Reilly. While it follows the familiar O'Reilly cookbook
format, it also provides a gentle introduction, with all the necessary
information to get started As a particularly nice touch for a cookbook, it
includes basic statistics and input/output in the early chapters so that the
reader doesn't need to wade through (or fearfully skip over) a lot of
material before getting to the needed resources.
A common complaint with other R resources is that the novice in
statistics is overwhelmed with statistical terminology. Teetor
is not trying to provide a statistics textbook, but he includes refreshing
explanations for the underlying statistics.
Some chapters are particular standouts:
Chapter 2: Some Basics. This chapter is an appetizer of what R can do,
and it's very helpful to get this early. Aside from the basic usage of R
covered in this chapter, section 2.6 (Computing Basic Statistics) provides a
quick introduction to performing basic statistics with R.
Chapter 4: Input and Output. R's input/output support is a bit cumbersome,
but the R Cookbook provides examples for many common cases that newcomers
need to handle (text files, CSV's, etc).
Chapter 9: General Statistics. This is the meat and potatoes of R for many
statistical users. Students in a basic statistics course (or practitioners
needing to do most fundamental analyses) will find chapter 9 to be
Chapter 10: Graphics provides a nice dessert as visualizing data is often
critical to understanding it. Teetor provides simple, concrete examples
that cover many of the common graphics, as well as how to handle their
titles, labels, and legends.
As an added bonus, Teetor and O'Reilly provide Chapter 14: Time Series
Analysis. The coverage here goes beyond standard cookbook fare and provides
a good starting point for those interested in Time Series Analysis.
Overall, the R Cookbook is the best O'Reilly cookbook I've read since the
release of the Perl Cookbook, and it's by far the best introduction to R
that I've seen. It's a must-have for every newcomer to R.
[Disclaimer: I got this book for free as part of the Oreilly blogger review
program I was not required to write a positive review. The opinions I have
expressed are my own. I am disclosing this in accordance with the Federal
Trade Commission's 16 CFR, Part 255 : "Guides Concerning the Use of
Endorsements and Testimonials in Advertising."]