- Series: In a Nutshell (O'Reilly)
- Paperback: 636 pages
- Publisher: O'Reilly Media; 1 edition (January 14, 2010)
- Language: English
- ISBN-10: 059680170X
- ISBN-13: 978-0596801700
- Product Dimensions: 6 x 1.2 x 9 inches
- Shipping Weight: 1.6 pounds
- Average Customer Review: 55 customer reviews
- Amazon Best Sellers Rank: #1,008,481 in Books (See Top 100 in Books)
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R in a Nutshell: A Desktop Quick Reference (In a Nutshell (O'Reilly)) 1st Edition
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About the Author
Joseph Adler has many years of experience in data mining and data analysis at companies including DoubleClick, American Express, and VeriSign. He graduated from MIT with an Sc.B and M.Eng in Computer Science and Electrical Engineering from MIT. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks. Currently, he is a senior data scientist at LinkedIn.
Top customer reviews
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As it is, I am somewhat proficient in R and bought this book as a crash course for a better understanding of the basics, especially the graphics and statistics. After barrelling through roughly half of the book, I found many references to functions or parameters which were never explained or were explained later in the book (without saying so at the first reference). For someone who is hoping for a quick read through most of what R has to offer, this is like hitting a brick wall.
The book helps the reader understand a lot of what R is capable of, but it seems to be done in a more slip-shod manner than I was hoping for. I get the feeling the author was rushed in getting this to print. Or, they didn't pay the editor enough.
As an aside, the formatting for the kindle edition has been working pretty well. I've actually been reading it on the cloud reader without problems (be sure to download a local copy for offline reading).
I teach programming, so I found the references to how R differs from languages like LISP, C and JAVA very useful. However, those distinctions will be at best distracting or more likely horribly confusing to programming novices. With that distinction in mind, this book is exceptionally well written and has great clear explanations on things that are missing from practically every other R book (like the distinction between if else and ifelse. Other sections, like the coverage of graphics can be found elsewhere but require you to distill a LOT of other books.
If you want to really understand R start here and then go for John Chambers books (especially Software for Data Analysis: Programming with R (Statistics and Computing) ). If you want to learn how to use R for data analysis get Zuul's book then follow my learning R guide.
That being said, Adler's range of knowledge is astounding and I certainly trust what he says. With just a slight tweak to meet the needs of his less academic readers, the book would be perfect.
I made two attempts to learn R before purchasing this book. In both previous attempts, I had to abort and use another tool to solve my problem because it was taking me too long to accomplish very simple things in R.
The reason R is hard to learn is that its documentation is organized for statisticians that already know R, but have forgotten a detail or two. There are a few other books on learning R, but they are setup like a college course - complete the entire book and THEN you can actually accomplish something.
R in a Nutshell allows you to get working immediately. Simply lookup what you need to do. The firsts thing I did was load a file and make a histogram. I found that stuff in the section on "Loading Data" and the section on charts. In no time I was making stacked area charts for cohorts. Now R is an essential tool for me - and I haven't even taken the time to learn it well! With this book, I don't have to. I can learn as I go. So I actually use R.
Do not R without it.