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R Cookbook (O'Reilly Cookbooks)
 
 

R Cookbook (O'Reilly Cookbooks) [Kindle Edition]

Paul Teetor
4.2 out of 5 stars  See all reviews (4 customer reviews)

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Product Description

Product Description

With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.

Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.

  • Create vectors, handle variables, and perform other basic functions
  • Input and output data
  • Tackle data structures such as matrices, lists, factors, and data frames
  • Work with probability, probability distributions, and random variables
  • Calculate statistics and confidence intervals, and perform statistical tests
  • Create a variety of graphic displays
  • Build statistical models with linear regressions and analysis of variance (ANOVA)
  • Explore advanced statistical techniques, such as finding clusters in your data

"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author

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.


Product details

  • Format: Kindle Edition
  • File Size: 2177 KB
  • Print Length: 438 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: O'Reilly Media; 1 edition (3 Mar 2011)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B004VB3UYW
  • Text-to-Speech: Enabled
  • X-Ray:
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Bestsellers Rank: #33,092 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most Helpful Customer Reviews
3 of 3 people found the following review helpful
4.0 out of 5 stars R is for Read it 6 Oct 2011
Format:Paperback
Having recently had to do some statistical analysis, I came across R, a seriously powerful tool for querying and analysing data.

The R cookbook helped me as a newbie to R to quickly get to grips with the requirements and considerations for its use.

If you know what you are looking for the cookbook format is a great way to access information. The recipes are easy to follow and are a great help in getting to the solution quickly while providing enough detail to explain the problem and solution sufficently.

If you want know more about 'R' this is the book to read.
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4 of 5 people found the following review helpful
4.0 out of 5 stars O'Reilly R Reference 13 July 2012
By John M. Ford TOP 500 REVIEWER
Format:Paperback
The R statistical analysis tool has much to recommend it to students, researchers, and commercial data analysts. It contains a powerful set of analysis and graphics commands and a constantly-growing number of add-on packages produced by its large user community. R and most of its add-ons are also available for free under an open source license. It is a realistic and readily available rival to major commercial tools such as SAS and SPSS.

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.
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3 of 4 people found the following review helpful
4.0 out of 5 stars Honestly - this is a great book 9 Aug 2011
Format:Paperback
I have bought a lot of books on R, some are great others less so. I must have 20 different recent books. This is the one I inevitably grab from my shelf whenever I am going away/to work/on a train whatever, because there is just so much relevant, bite-sized stuff that I can use every day. Recipes which are general enough to be applicable in different areas, but specific enough that the light up that "eureka" light bulb because you've suddenly discovered something that will have proper utility in your code.

Now I am a 3-months R "beginner" (though an accomplished Python programmer), so I'd hesitate to say that it's extremely advanced, but it certainly covers a lot of relevant material for quite advanced tasks. Of course, being a "cookbook", it doesn't delve much into the fundamental underpinnings of some of R's core technical foundations - it's more about useful stuff, now.

For anybody who's been flummoxed by the often-cryptic R online documentation, this is the book for you.
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5.0 out of 5 stars Simple, yet powerful 26 July 2011
By mko
Format:Kindle Edition
Simply put, one of the best R starters around. What you get here are recipes for most common problems you will face while working with R. This book is an extended version of 25 Recipes for Getting Started with R. However, the coverage of material is different. While 25 Recipes focus on getting started with R, R Cookbook penetrates the subject in greater details and goes beyond simple usage of R. You will find here not only how to load data, manipulate it and plot some graphic. You can find description of various statistical analysis as well.

This book, is not for a reading in bed just before you go to sleep. It is too pragmatic. Simple definition of the problem and just after that, simple solution - that's what you get when it comes to each issue covered within the book. This is the strength of R Cookbook. On the other hand, it's weakness. If you cant find the question within table of contents it might be hard to get the answer for what you ask about. As I like pragmatic approach, I like the book as well. For me it's just perfect. Well, maybe just too short.
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Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com: 4.4 out of 5 stars  42 reviews
83 of 86 people found the following review helpful
5.0 out of 5 stars Very Practical -- Saved me tons of time!!! 30 Mar 2011
By Bill y - Published on Amazon.com
Format:Paperback|Verified Purchase
I'd give this book ten stars if I could. I bought one copy for the office and one for my house. This guy has the ability to write simply and with the mind set of people who are busy and want to get results right away. Of course we'd all love to be leisurely scholars and plow through theory and practice but most of us just need to get things done. A good example is the way he treats ARIMA. He warns you about using auto.arima but does not hide it from you because it is "dangerous." The book is full of tips, well organized and is oriented towards beginners, though it gets into depth. So many of the R books I've read absolutely pound you with up front details, some of which relate to obscure concerns, rather than starting with a task. For example, on page 199 he writes "Problem -- you want to count the relative frequency of certain observations in your sample" Next is "Solution" -- and he explains just the minimum needed to do that job. Some of the tips are just simple time savers, such as the function head(dataframe) to show a few of the dataframe rows at the start and tail(dataframe) to show a few at the end. Finally .... I don't know this writer personally, but I hope he keeps on writing because it is a craft he has thoroughly absorbed somewhere along the line. Bill Yarberry, Houston, TX
34 of 34 people found the following review helpful
5.0 out of 5 stars best intro to R I've found 25 May 2011
By Dave Backus @ NYU - Published on Amazon.com
Format:Paperback|Verified Purchase
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).
21 of 21 people found the following review helpful
4.0 out of 5 stars Good, but not necessary. 10 May 2012
By Z. Sheffler - Published on Amazon.com
Format:Paperback
R Cookbook is a good book to have. It covers the bases well, and is organized in a logical method. The "Cookbook" formula works, for the most part.

But if I lost it, would I purchase another copy? Probably not. Here's why:

- Outside of base R (and some MASS), you're pretty much out of luck. Some other libraries are covered, but not extensively.
- R help is very good. ?[function] or ??"[topic]" get the job done 90% as well as this book, and much faster. (In fairness, this book is written in plain English, which can't always be said for R help)
- There's a ridiculous cornucopia of cookbook-esque material on the web, notably Stack Overflow.
- There's very little in the way of scripting, which is the bread and butter of R.

My only strong advice would be that this is a supplement, and not a standalone learning method. But if you have another book on R and the price tag doesn't bother you, you could certainly do much worse.
26 of 28 people found the following review helpful
5.0 out of 5 stars Required reference for working in R 6 April 2011
By John Brady - Published on Amazon.com
Format:Paperback
The R Cookbook should be on your bookshelf if you work with R.

The book is as self-described, a collection of tasks and how to accomplish those tasks in R (recipes). This is not a tutorial on the language, but is definitely recommended for novices. One of the most frustrating aspects of R for the beginner is to know what manipulations you require for a dataset, but to be clueless as to how to perform those steps in R; this book can help close that gap.

For intermediate users, it can serve as a reference. I'll often use this to jog my memory as to how a particular technique is applied, e.g., run a function on each row of a dataframe. Since the book has been available on the O'Reilly Safari system for several months, it's become one of my most-used options for R info.

Technically the book appears to be accurate, with the recipes I've used functioning well. Caveat, I have not tested any of the higher-end statistical recipes, as they aren't required in my work.

In summary, this should be one of the first books purchased when building an R library.

Disclaimer, I received access from O'Reilly Publishing to an electronic copy of this book for purposes of review.
10 of 10 people found the following review helpful
5.0 out of 5 stars Great for beginners 31 July 2011
By Dimitri Shvorob - Published on Amazon.com
Format:Paperback
You will be disappointed if you are a competent R programmer looking for "hacks". Note that the only negative review so far mentions its author's four-year experience with R. Mine is much shorter, yet I too find the book too "junior" for my needs. (With "R in Nutshell" and Google at my disposal, I can send "R Cookbook" back after making several notes to record what I learnt from it. There are several nuggets that you will not find in "R in Nutshell", or will not think to google). However, the book is not advertised as an "R in Depth", so no complaints.

"R Cookbook" is a friendly and highly informative introduction to "general-purpose" R (one half of the book) and doing basic statistics with R (the other half). A chapter on time series, with a look at "zoo" package, is a bonus; a somewhat light (but does-the-job) take on R graphics may be viewed as a downside, but I see the benefit of getting the basics right, and letting the reader explore other resources - I would recommend "R Graphs Cookbook" and Quick-R Web site - when he/she is ready.

Yes, there are free R tutorials out on the Web - but given that this one is widely praised and inexpensive (even if you are never going to resell it - and at some point you probably should, and move to "R in Nutshell" - $25 is not too much. How much saved time is worth $25 for you?), why not take a look?

PS. "R in Action" by Robert Kabacoff is another option, and one that I actually like better.

PPS. The second edition of Michael Crawley's "R Book" is a large improvement over the first, and is a stronger competitor to both "R Cookbook" and "R in Action".
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