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R in a Nutshell (In a Nutshell (O'Reilly)) [Englisch] [Taschenbuch]

Joseph Adler
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Kurzbeschreibung

31. Oktober 2012 In a Nutshell (O'Reilly)
If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports. Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop. * Get started quickly with an R tutorial and hundreds of examples * Explore R syntax, objects, and other language details * Find thousands of user-contributed R packages online, including Bioconductor * Learn how to use R to prepare data for analysis * Visualize your data with R’s graphics, lattice, and ggplot2 packages * Use R to calculate statistical fests, fit models, and compute probability distributions * Speed up intensive computations by writing parallel R programs for Hadoop * Get a complete desktop reference to R

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R in a Nutshell (In a Nutshell (O'Reilly)) + R Cookbook (O'Reilly Cookbooks) + R Graphics Cookbook
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Produktinformation

  • Taschenbuch: 721 Seiten
  • Verlag: O'Reilly & Associates; Auflage: 2 (31. Oktober 2012)
  • Sprache: Englisch
  • ISBN-10: 144931208X
  • ISBN-13: 978-1449312084
  • Größe und/oder Gewicht: 22,9 x 15,2 x 4,1 cm
  • Durchschnittliche Kundenbewertung: 4.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)
  • Amazon Bestseller-Rang: Nr. 70.661 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)

Produktbeschreibungen

Über den Autor und weitere Mitwirkende

Joseph Adler has years of experience working with lots of popular data mining packages, including databases (including Oracle, PostgreSQL, and MS Access), statistical analysis tools (SAS, SPSS, S-Plus, and R), and data mining tools (SAS Enterprise Miner, Insightful Miner, Oracle Data Mining, Weka, and SPSS Clementine). He is currently leading a project at Verisign to pick a data mining package for enterprise deployment.

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4.0 von 5 Sternen Decent introduction to R 26. November 2012
Von mko
Format:Kindle Edition
I have bought R in a Nutshell some time ago (1-st edition) and I was pleased with it. It is very decent introduction to R. I am using R casually for doing server logs analysis, mostly. And from my point of view, a person who doesn’t speak R fluently, this book is very handy. I have requested 2-nd edition mostly from the mere curiosity. I wanted to know how book have changed.

You will find few minor shifts here, some chapters were moved and some of them were split or merged. However, the content remained quality remained at the same level. Book covers most recent release of R (at least when it comes to Mac OS, I can’t tell for the other systems). There are few new things I have learned. RStudio and ggplot2 are among them. As I said, I don’t follow all the recent news in the “R world” thus, reading about these two was a big surprise for me and big plus for my simple tasks done with R.

I would recommend this book for R newbies. If you have never ever worked with R but looking to start your journey with it this is a good start. Contrary, if you have already done some stuff with R and you are looking for straightforward solutions I’d suggest heading towards R Cookbook. Anyway, I think this book is a really decent introduction to R.
War diese Rezension für Sie hilfreich?
Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)
Amazon.com: 3.4 von 5 Sternen  13 Rezensionen
33 von 34 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen wait for the errata to fill in before buying 25. Januar 2013
Von J - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
Before buying, look at the book description at the publisher's website (oreilly.com) and click on the "errata" link. Check to see how long that list is. If you can live with cross-referencing this list with the book, then buy it. Otherwise, there are probably better books out there.

As it is, I am somewhat proficient in R and bought this book as a crash course for a better understanding of the basics, especially the graphics and statistics. After barrelling through roughly half of the book, I found many references to functions or parameters which were never explained or were explained later in the book (without saying so at the first reference). For someone who is hoping for a quick read through most of what R has to offer, this is like hitting a brick wall.

The book helps the reader understand a lot of what R is capable of, but it seems to be done in a more slip-shod manner than I was hoping for. I get the feeling the author was rushed in getting this to print. Or, they didn't pay the editor enough.

As an aside, the formatting for the kindle edition has been working pretty well. I've actually been reading it on the cloud reader without problems (be sure to download a local copy for offline reading).
13 von 15 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Decent introduction to R 26. November 2012
Von mko - Veröffentlicht auf Amazon.com
Format:Taschenbuch
I have bought R in a Nutshell some time ago (1-st edition) and I was pleased with it. It is very decent introduction to R. I am using R casually for doing server logs analysis, mostly. And from my point of view, a person who doesn't speak R fluently, this book is very handy. I have requested 2-nd edition mostly from the mere curiosity. I wanted to know how book have changed.

You will find few minor shifts here, some chapters were moved and some of them were split or merged. However, the content remained quality remained at the same level. Book covers most recent release of R (at least when it comes to Mac OS, I can't tell for the other systems). There are few new things I have learned. RStudio and ggplot2 are among them. As I said, I don't follow all the recent news in the "R world" thus, reading about these two was a big surprise for me and big plus for my simple tasks done with R.

I would recommend this book for R newbies. If you have never ever worked with R but looking to start your journey with it this is a good start. Contrary, if you have already done some stuff with R and you are looking for straightforward solutions I'd suggest heading towards R Cookbook. Anyway, I think this book is a really decent introduction to R.
10 von 11 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen practical and well-organized introduction to R 18. November 2012
Von joycie - Veröffentlicht auf Amazon.com
Format:Taschenbuch
This is a well-organized overview of R, which provides working examples and explanations of how you can use R to look at data. It provides concrete advice that you can directly apply -- it walks the reader through how you can think through data visualization and describes the tools available to analyze data in R.

The desktop reference is a solid guide for beginning and intermediate users of R. It is practical and task-oriented, so it will help anyone get up and running quickly on the R environment. Along with the basics of the R language, the book covers data processing, data visualization in R, and statistics in R, which will get you quite a fair ways in using R as a visualization and data discovery tool.

This is not an advanced book on R, or a cookbook-style book, or a pocket reference. It is a solid introductory book on R, and I like that the author's examples give you an idea of how one should go about taking a set of data and playing with it until you discover patterns and stories in that data.
3 von 3 Kunden fanden die folgende Rezension hilfreich
1.0 von 5 Sternen Not recommended 6. Dezember 2013
Von Filiep Samyn - Veröffentlicht auf Amazon.com
Format:Taschenbuch
I have bought this book but it has offered only limited help in understanding and using R. The author is obviously well versed in many of the intricacies of R but does not convey the message well. I think that some topics would find a better place later in the book instead of adding complexity for the user early on. For instance, the topic on data frames on p.87 is too succinct to be useful; the same is true for "The R interpreter" and "Seeing how R works" (p.57-59). I also found that chapter 8 "Symbols and environments" was out of place. The same holds for chapter 9 and 10.
As other authors have explained, getting data into R is not a trivial task. This should be the cornerstone for each R book, get the data (seriously nobody types data or uses some simple lists) and then start manipulating the data. I would never recommend this book for people who want to get a basic understanding of R and start doing data analysis. Some topics are nebulous at best. For instance the use of double square brackets versus single square brackets to access individual elements has completely escaped me. Properties of functions (p. 111) is a topic that does not seem needed (at least not at this point) for the beginning user and the wording is hard to understand "If you would like to manipulate the list of arguments with R code, then you may find the formals function more useful. The formals function will return a pairlist object with a pair for every arguments. The name of each pair will correspond to each argument in the function." But why would I need to edit function arguments? Without a clear answer to that question I have no desire to understand function argument manipulation.
Authors please consider your audience and if this is R in nutshell then please focus on essential topics to make the learning curve smooth instead of demonstrating your skills with a complex software package.
3 von 3 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Not a tutorial or the encyclopedia one would expect 24. Dezember 2013
Von Erik Gfesser - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
This book is the second that I purchased this past year to get up to speed on the R language and environment, along with "R in Action" and "R Graphics Cookbook" (see my reviews), but unlike these other two, I fully expected this book to serve as a reference rather than a tutorial, based on my experience with "UNIX in a Nutshell" many years ago. However, through my experience I was quickly made aware of the breadth of the R language, which includes over 2500 packages that have become available to the community, and I have instead typically used this book as a starting point for additional research on websites which cater to the R community, including CRAN ("Comprehensive R Archive Network").

Even given its near 700-page size, it is difficult for any book to cover R extensively, so I credit this book to continue to provide pointers in the right direction as I gain experience using the language. While "R in Action" in its introductory chapters gets one up and running with R more gracefully, chapter 1 ("Getting and Installing R") and chapter 2 ("The R User Interface") in this book also provide a glimpse into the many options available with regard to environments. The closest that one will get with a tutorial in this book is the 18-page chapter 3 ("A Short R Tutorial"), but this chapter should really only be considered a way to wet one's appetite with regard to basic operations, functions, variables, data structures, objects and classes, models and formulas, and charts and graphics, as chapters 5 through 10 go over these topics more extensively.

Chapter 11 ("Saving, Loading, and Editing Data") along with Chapter 12 ("Preparing Data") provide useful information on working with data, because, like it or not, as with any language most data work revolves around first getting it into the correct format, but although these chapters present more available options in this area than "R in Action", these chapters also again read more like an encyclopedia and do not provide any guidance, because as is the case with most of this text, readers are likely best served when they have a decent idea of what they are looking to accomplish.

Most of my use of this book has involved Part 4 ("Data Visualization"), Part 5 ("Statistics with R"), and Part 6 ("Additional Topics"). After experimenting with the packages included with R by default, it is Chapter 15 ("ggplot2") which led me to purchase "R Graphics Cookbook", a well recommended book to learn the ggplot2 package, but it is the other chapters within this part of the book that made me realize that although the ggplot2 package provides standardization that is often lacking with R, no single package is likely to ever serve the needs of a developer, at least over time. Recommended text for those in the earlier stages of using the R language and environment and still finding their way, but not for the neophyte, as this book is not a tutorial, nor is it the encyclopedia one would expect from the "In a Nutshell" series.
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