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R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics 1st Edition

by Paul Teetor (Author)
4.6 4.6 out of 5 stars 216 ratings
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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

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  1. ISBN-10
    0596809158
  2. ISBN-13
    978-0596809157
  3. Edition
    1st
  4. Publisher
    O'Reilly Media
  5. Publication date
    April 19, 2011
  6. Language
    English
  7. Dimensions
    7.13 x 0.92 x 9.17 inches
  8. Print length
    434 pages
  9. See all details
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Editorial Reviews

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

  • Publisher ‏ : ‎ O'Reilly Media; 1st edition (April 19, 2011)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 434 pages
  • ISBN-10 ‏ : ‎ 0596809158
  • ISBN-13 ‏ : ‎ 978-0596809157
  • Item Weight ‏ : ‎ 1.7 pounds
  • Dimensions ‏ : ‎ 7.13 x 0.92 x 9.17 inches
  • Customer Reviews:
    4.6 4.6 out of 5 stars 216 ratings

About the author

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Paul Teetor

Paul Teetor

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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, where he lives with his wife and sons. In his mind, he is a fabulous musician and one of the world's great futures traders.

Customer reviews

4.6 out of 5 stars
4.6 out of 5
216 global ratings

Top reviews from the United States

Paulo Cysne Jr
5.0 out of 5 stars A simple and masterful book with many insights - better than many textbooks on R
Reviewed in the United States on May 14, 2015
Verified Purchase
With clear and concise explanations covering most of the important areas, this is a brilliant book. It can not only save you plenty of time, but also help you to gain new insights as you learn from comprehensive but short and clear discussions of so many different topics. They are all explained in a such a way that you can directly access anyone of them without having to read the rest of the book. Some highlights:
- The chapter 2 on "Some Basics" is simple but mandatory for any beginner.
- Chapter 5 on "Data Structures" is one of the best along with Chapter 12 on "Useful Tricks". Chapter 5 covers data structures in a clearer and better way than many other books on R.
- Chapter 6 on "Data Transformations" shows the beauty and power of R in short but very good examples.
- Statistics with R is covered in Chapter 8 on "Probability" and chapter 9 on "General Statistics", whereas Chapter 11 covers "Linear Regression and ANOVA". Here again the very clear prose and simple examples show these applications of R in a much better way than books on R and "advanced analytics" like "R for Everyone" (a book that is a big disappointment).
- There is a good coverage of graphics in Chapter 10, whereas the author still found space to treat time series analysis in Chapter 14 with more brilliant examples.
What is missing? A coverage of RStudio, a great and free development environment for R. There is also a lack of any examples covering statistical learning data analysis other than linear regression which actually belongs more to standard statistical analysis.
But this is little in comparison to what it offers. This is a great book written in a masterful way not only in knowing the subject matter but also in knowing how to present it and teach it.
One person found this helpful
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Kelly Maurice
5.0 out of 5 stars A High Quality Book On R Programming!
Reviewed in the United States on August 19, 2015
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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).
9 people found this helpful
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John M. Ford
4.0 out of 5 stars O'Reilly R Reference
Reviewed in the United States on July 13, 2012
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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.
6 people found this helpful
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Top reviews from other countries

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Amazon Customer
5.0 out of 5 stars Buen libro de referencia de R
Reviewed in Spain on April 27, 2019
Verified Purchase
Es un buen libro tanto tanto para iniciarse con el programa R como para profundizar en dicho lenguaje. Enseña con ejemplos como resolver problemas habituales que puedan surgir al analizar datos, como hacer gráficos, todo tipo de análisis estadísticos, modificar y transformar set de datos, etc
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Amazonfreund
5.0 out of 5 stars Ist ok
Reviewed in Germany on December 5, 2015
Verified Purchase
Ein gutes Buch, setzt gute Englischkenntnisse voraus, schade, dass es dieses Buch nicht in deutsch gibt, da sind uns die USA halt immer ein
Stück voraus., Preis ist angemessen, ist für Programmierer mit tiefer gehenden Ambitionen.
One person found this helpful
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VR
5.0 out of 5 stars Wish I'd bought it sooner
Reviewed in the United Kingdom on November 5, 2014
Verified Purchase
Used during my MSc. Found it very helpful - some of the websites I've looked for help with before are aimed at people who really know that they are doing with R, whereas this was at the right level for me. I found the sections explaining the results of GLMs particularly useful. I only wish I'd bought it sooner - t would have been so useful!
2 people found this helpful
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A. Narasimhan
5.0 out of 5 stars Paul Teetor is the head chef
Reviewed in Canada on January 15, 2013
Verified Purchase
By far the best R book around. Excellent book for both absolute beginners looking to hit the ground running and advanced users looking to expand their set of tools with immediate results. If you're interested in quantitative finance, the time-series section (chapter 14) alone is worth a lot more than the price of the book. The 'recipe' based approach of the book truly sets it apart.
3 people found this helpful
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gg
5.0 out of 5 stars Nice and simple
Reviewed in Italy on February 17, 2014
Verified Purchase
This is a concise and effective overview of the R programming basic aspects.
A must have for quick solving issues.
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