PDF Ebook R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O'reilly Cookbooks)
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R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O'reilly Cookbooks)
PDF Ebook R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O'reilly Cookbooks)
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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.
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Product details
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:
4.6 out of 5 stars
101 customer reviews
Amazon Best Sellers Rank:
#25,807 in Books (See Top 100 in Books)
This is an excellent book. I read it from cover to cover. I did not try out the examples however. I found the writing to be very good and the book, although a cookbook, actually provides a great way to get an in depth overview of R. The R packages facilitate the use of the book examples by providing test data in the packages. The book is organized well, especially the file I/O and data structures, as well as the statistics sections.I have worked with statistics at various levels over the years and taken courses but I wanted to brush up on concepts and applications, and this book was really good for that. I think it is also a decent book for learning programming although one would start using the 1-based paradigm instead of 0-based for indexing and that is kind of nonstandard and used only for math software. But a beginner could learn quite a bit by just playing around with the examples.The explanations of the statistics concepts was particularly good. The author is very precise with his language and even repetitive (which I appreciated) about the rigorous interpretation of results.The R software thankfully provides a well designed, open source alternative to Matlab and this cookbook (with its references) is an ideal place to start learning for practical use at work or on projects. I thoroughly recommend it. I found very few typos which for me is one of many quality indicators. The author also writes in an entertaining style making the book fun to read - which is a challenge considering the subject matter could be considered dry (by some).
This is a very well written and clear book on a broad variety of topics is R. It is not a book for learning statistics: it assumes you have a good knowledge of statistics. But it does review basic concepts to explain how R output relates to statistical concepts. The coverage of linear models is a good example. It goes into great detail explaining what every bit of output means. One big R concept missing is R Studio. There is a good reason for that, though. R Studio was just being developed when this book was written. A good survey book of R that does include R Studio is "R for Dummies", which actually is very similar in layout and style to "R Cookbook", but "R Cookbook" goes into greater detail in some explanations. This book, along with others, is an important addition to R references.
This is a really great book -- I found it to be exceptionally clear in (1) the way the various features of R are broken into tidbits for explanation, (2) the explanations, and (3) the clarity of the examples which highlight the single point that is being explained (versus, say, Wickham's ggplot2 book, which combines too much into a single example). The only issue is that it is a bit out of date in terms of the most recent plot (e.g., ggplot2) and some of the tidyverse, etc., stuff. But still a great book, used frequently for some things, and another edition with more up-to-date content would be great to have. So, six stars for presentation, 3.5 stars for wishing it was more current, average 4.
I'm a long time Matlab user, but have been using R for a couple months now. Still on the fence on their relative merits (they're different, let me say), but it's been interesting. I had the help of friends, but this book got me going. I bought probably 10 books, and this is far and away the best place to start. Nice combination of keeping it simple and still giving you a sense of the logic of the software. What it doesn't have is details about specific things (graphics, for example), but it gets you close enough that you can usually figure the rest out for yourself. Great book, well written, good coverage of topics -- at least for my use (analysis of international macroeconomic data).
This book is meant to be a reference. It doesn't teach you, and it is not meant to, anything about regression statistics. It does, however, cover using R for statistics (including regression).I think much of the information contained in this book is widely available free on the internet.Pros:1)Comprehensive reference on R.2)Good explanations and writing.Cons:1)Mostly for beginner-intermediate users. Not too many expert level concepts.2)Most of the information is available for free on the internet, and usually in much more comprehensive form.If you already have a good R reference, then this book will probably be redundant.
If you are trying to learn the powerful, but challenging, statistical programming language R then you will find this book very handy. It's one of many such books from O'Reilly. As with all their Cookbook series, this is not a general introduction to the language, for that you need a different book. But the main thing I need when picking up a new language is lots of annotated code samples; this book has those.From my experience with comparable books for other languages, I expect this book would also be useful for an experienced user of R. I've been using Perl on a daily basis for over 20 years, and I still keep a well-thumbed copy of the Perl Cookbook handy!
The book contains numerous recipes for addressing specific topics related to R. I found several solutions to topics that I have faced while using R. I found the coverage of solutions strike a good balance for beginning and advanced users. The author directs the reader to other books where necessary to learn more about specific topics.
I use R to put together and organize data in my work and have been taking classes to take it a little further. When I googled questions about tasks with R, I kept winding up on a set of pages referencing this book. I gave up and bought it. It is a gem to have if you are far enough along to be writing your own code and putting together your own reports, but aren't sure how to implement sorting algorithms and the like in R, as opposed to more procedural languages. I recommend this highly for people who can code in R but have not been doing so long enough to build up their own bag of tricks and who don't want to reinvent the wheel when their translations of code from other languages into R don't quite seem to work.
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