Author(s): Phil Spector
Publisher/Date: Springer/2008
Statistics level: N/A
Programming level: Intermediate
Overall recommendation: Highly recommended
If there is one book that every beginning R user coming from a programming background should have, it is Spector’s Data Manipulation with R. New R users with analytic backgrounds and experience with software packages such as SAS and SPSS will do well to start with Muenchen’s R for SPSS and SAS users, especially given that a free abbreviated version is available, but those users should also make Data Manipulation with R a quick second addition to their library.
The text of this book is as concise and to the point as its title. It covers almost every relevant data manipulation topic in R, from modes and classes, through accessing data via database connections, to complex reshaping and aggregating functions. It has copious examples and the text hits just the right level of sophistication for the individual who has some experience with programming, but little experience with R idioms and data manipulation techniques.
My only critique of this book is that it skips over the basics of creating user-defined functions for data manipulation tasks. Spector addresses mapping functions to various data structures, but it seems likely that, at this level, the average R analyst would be better served by a discussion of how to simply create a function in R. Keep in mind that if you are looking for that type of information, you will need to look elsewhere. The same is true if you are looking for any sort of statistical instruction, as Data Manipulation with R focuses almost exclusively on programming.
Overall, I highly recommend this book. At around $50 USD ($25 for the Kindle Version), it is well worth the price. You’ll breeze through it on your first pass, but if you’re new to R you will get your money’s worth out of it as a reference text.
Finding it: This book is readily available at on Amazon.
I agree, this is a wonderful book. I own a copy and refer to it frequently. It’s full of all kinds of tips that are very hard to figure out on your own.
Also, I’m glad you liked my book, “R for SAS and SPSS Users”. When I started learning R, I was frustrated by the fact that I could often find how to do a single task, such as recode a variable, but the reference would not show how to do the task completely on a whole set of variables. I prefer not to modify my original data, so I make a duplicate set, with a similar but different set of variable names. That’s not hard to do in R, but you may have to look up all three steps: duplicate, rename, recode! If you go to the free version at http://r4stats.com and search for “recode” you’ll see all the steps together, for recoding and most of the other examples. The free version does most of its talking with code: run it, read the comments & it will be clear. The book adds lots of explanation, especially why things don’t work the way SAS & SPSS users expect.
Cheers,
Bob Muenchen
I have to say, I have learned a lot of his book. I had to read it for school and it was very helpful in many ways!
It also inspired me to create my own tutorials for basic R statistics. The tutorials I have written may be found here: R statistics.
The tutorials on R statistics contain the basic knowledge you need to achieve before going deeper into using R.
There will come some more detailed and more higher-level tutorials in the near future, but the tutorials that are online right now create a good base.
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