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R in Action: Data Analysis and Graphics with R, by Robert Kabacoff
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Summary
R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Business pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you're likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide.
About the Book
R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.
What's Inside
- Complete R language tutorial
- Using R to manage, analyze, and visualize data
- Techniques for debugging programs and creating packages
- OOP in R
- Over 160 graphs
About the Author
Dr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net.
Table of Contents
PART 1 GETTING STARTED- Sales Rank: #10803 in Books
- Published on: 2015-06-06
- Original language: English
- Number of items: 1
- Dimensions: 9.20" h x 1.40" w x 7.30" l, .0 pounds
- Binding: Paperback
- 608 pages
About the Author
Dr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net.
Most helpful customer reviews
35 of 37 people found the following review helpful.
Reliably solid
By Dimitri Shvorob
Back in 2011, I was an early enthusiast of "R in Action"'s first edition, praising the book as the only high-quality product in a growing field of R introductions rushing to market. (In the parallel universe of statistics-with-R books, "The R Book" by Crowley - now also in its second edition - reigned). In 2014, I revised my review, and reiterated my endorsement, but noted "R for Everyone" by Jared Lander as an appealing, "fresh" upstart rival. At that time, second edition of "R in Action" was already listed on Amazon as available for pre-order, but the release date kept being postponed. Having pre-ordered "R in Action" 2.0 in May 2014, I only got it in June 2015.
The changes from the first edition are helpfully summarized on page xxvii, but I will distinguish five strands. First, there is a nod to the computer-science (vs. "proper" statistics) sensibility, via addition of a chapter on clustering and another chapter on classification, discussing CART and SVM methods. Second, two new chapters deal with R as a programming language, with one chapter dedicated to package-building. Third, there is a new chapter on producing reports, focusing on, but not limited to, the capability of "rmarkdown" R package. Fourth, second edition boosts coverage of "ggplot2" package. Finally, statistics repertoire is expanded with a short chapter on (very basic) time-series analysis, relying on "forecast" R package.
I may have wished for a few different choices. The package-building chapter could have been dropped, and more space given to either statistics (one could say more about regression - maybe taking a page from "Modern Regression Techniques Using R" by Wright and London) or machine learning. I would introduce RStudio from the outset, not in an appendix. I would say goodbye to R's base graphics, and, like Lander, embrace "ggplot2", instead of relegating it to Chapter 19. I would give space to "data.table" - like "ggplot2", this is a necessity - and I would give more space to "plyr"-and-friends. Turning to Manning, I would ask them why Addison Wesley could publish "R for Everyone" in color, and still charge only 60% of the price of the black-and-white "R in Action". I would also draw their attention to a typo ("Stark Trek"?) in line 5 (!) of the book's preface. This slip-up is odd considering how long the book was delayed.
This criticism aside, "R in Action" is an excellent, well-thought-out and well-presented book, with second edition offering incremental but important changes from the first. In the field of "generalist" R books, two titles stand out - "R in Action" and "R for Everyone" - and "R in Action" is the heavier part of the duo.
UPD. With the benefit of a little more life experience, I would say: don't spend your time on *any* R book. Python is the way to go.
14 of 14 people found the following review helpful.
More than 200 pages of new materials have been added in this updated edition
By Si Dunn
Whether data analysis is your field, your current major or your next career-change ambition, you likely need this book. Free and open source R is one of the world's most popular languages for data analysis and visualization. And Robert I. Kabacoff's updated new edition is, in my opinion, one of the top books out there for getting a handle on R. (I have used and previously reviewed several R how-to books.)
R is relatively easy to install on Windows, Mac OS X and Linux machines. But it is generally considered difficult to learn. Much of that is because of its rich abundance of features and packages, as well as its ability to create many types of graphs. "The base installation," Kabacoff writes, "provides hundreds of data-management, statistical, and graphical functions out of the box. But some of its most powerful features come from the thousands of extensions (packages) provided by contributing authors."
Kabacoff concedes: "It can be hard for new users to get a handle on what R is and what it can do." And: "Even the most experienced R user is surprised to learn about features they were unaware of."
R in Action, Second Edition, contains more than 200 pages of new material. And it is nicely structured to meet the needs of R beginners, as well as those of us who have some experience and want to gain more.
The book (579 pages in print format) is divided into five major parts. The first part, "Getting Started," takes the beginner from an installing and trying R to creating data sets, working with graphs, and managing data. Part 2, "Basic Methods,"focuses on graphical and statistical techniques for obtaining basic information about data." Part 3, "Intermediate Methods," moves the reader well beyond "describing the relationship between two variables." It introduces regression, analysis of variance, power analysis, intermediate graphs, and resampling statistics and bootstrapping. Part 4 presents "Advanced Methods," including generalized linear models, principal components and factor analysis, time series, cluster analysis, classification, and advanced methods for missing data. Part 5, meanwhile, offers how-to information for "Expanding Your Skills." The topics include: advanced graphics with ggplot2, advanced programming, creating a package, creating dynamic reports, and developing advanced graphics with the lattice program.
A key strength of R in Action is Kabacoff's use of generally short code examples to illustrate many of the ways that data can be entered, manipulated, analyzed and displayed in graphical form.
The first thing I did, however, was start at the very back of the book, Appendix G, and upgrade my existing version of R and its packages to version 3.2.1, "World-Famous Astronaut." The upgrade instructions could have been a little bit clearer, but after hitting a couple of unmentioned prompts and changing a couple of wrong choices, the process turned out to be quick and smooth.
Then I started reading chapters and keying in some of the code examples. I had not used R much recently, so it was fun again to enter some commands and numbers and have nicely formatted graphs suddenly pop open on the screen. Even better, it is nice to have a LOT of new stuff to learn, with a well-written, well-illustrated guidebook in hand.
(My thanks to Manning for sending a review copy.)
4 of 4 people found the following review helpful.
Really, really useful book
By Kat
Fantastic explanations and a logical lay-out (you do need to clean the data and understand how the language works before you leap into analysis... too many other books skip that!)
If you are new to the language, this is definitely the book you want to start with. And if you're already using R, this is still a great book because it contains lots of information on a variety of useful topics - this is still my preferred go-to reference for all R questions!
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