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Hands-On Programming with R: Write Your Own Functions and Simulations [Kindle Edition]

Garrett Grolemund
5.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)

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Produktbeschreibungen

Kurzbeschreibung

Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools.

RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time.

  • Work hands-on with three practical data analysis projects based on casino games
  • Store, retrieve, and change data values in your computer’s memory
  • Write programs and simulations that outperform those written by typical R users
  • Use R programming tools such as if else statements, for loops, and S3 classes
  • Learn how to write lightning-fast vectorized R code
  • Take advantage of R’s package system and debugging tools
  • Practice and apply R programming concepts as you learn them

Über den Autor und weitere Mitwirkende

Garrett Grolemund is a statistician, teacher and R developer who currently works for RStudio. He sees data analysis as a largely untapped fountain of value for both industry and science. Garrett received his Ph.D at Rice University in Hadley Wickham's lab, where his research traced the origins of data analysis as a cognitive process and identified how attentional and epistemological concerns guide every data analysis.

Produktinformation

  • Format: Kindle Edition
  • Dateigröße: 3140 KB
  • Seitenzahl der Print-Ausgabe: 250 Seiten
  • Gleichzeitige Verwendung von Geräten: Keine Einschränkung
  • Verlag: O'Reilly Media; Auflage: 1 (11. Juli 2014)
  • Verkauf durch: Amazon Media EU S.à r.l.
  • Sprache: Englisch
  • ASIN: B00LPUIB8C
  • Text-to-Speech (Vorlesemodus): Aktiviert
  • X-Ray:
  • Word Wise: Nicht aktiviert
  • Durchschnittliche Kundenbewertung: 5.0 von 5 Sternen  Alle Rezensionen anzeigen (1 Kundenrezension)
  • Amazon Bestseller-Rang: #195.434 Bezahlt in Kindle-Shop (Siehe Top 100 Bezahlt in Kindle-Shop)

  •  Ist der Verkauf dieses Produkts für Sie nicht akzeptabel?

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5.0 von 5 Sternen guter Einstieg in die Programmierung mit R 17. November 2014
Von Marc
Format:Taschenbuch|Verifizierter Kauf
sehr angenehmer Schreibstil, didaktisch gut gemacht, für Einsteiger sehr gut geeignet. wer mit R programmieren lernen möchte, dem kann ich das Buch zum Einstieg nur weiterempfehlen.
War diese Rezension für Sie hilfreich?
Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)
Amazon.com: 3.8 von 5 Sternen  6 Rezensionen
6 von 7 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen An ambitious start 4. September 2014
Von Ian J Lyttle - Veröffentlicht auf Amazon.com
Format:Taschenbuch
Full disclosure - I have worked with the author. I have considered him a friend and colleague since he taught a course at my employer. Part of the information in my review is based on conversations I have had with the author, so please discount my opinion accordingly.

I don't think this book is meant to be a competitor to Norman Matloff's book (which I consider *the* tutorial/reference for base R). This book is trying to do something different, and I think it's an ambitious experiment.

In recent years, there has been a lot of activity surrounding the "Hadleyverse", a collection of R packages architected by Hadley Wickham and coworkers, the goal of which is to offer the user a consistent, simple, yet powerful set of tools to tidy, transform, and visualize data. The best way to jump into the Hadleyverse has been to just jump in. For someone who has just taken the leap to learn base R, it can be difficult to consider taking that second leap. There hasn't been a book (as least to my knowledge) that says, "start here, here's how to learn R in a way leads to dplyr". I think that's a goal of this book.

For example, knowing how functions work will make it easier to work with the piping operator (%>%). Knowing how environments work will make it easier to navigate the vagaries of non-standard evaluation, to get the most out of dplyr and ggvis. I don't think these topics were chosen by accident.

Part of my job is to help R users in my company, particularly those who are just starting out with the language. I will gladly recommend this book to them because: (1) it reveals to the reader just a little at a time, which is ideal for someone just starting out with R, (2) what is covered in the book is complementary to learning dplyr, etc., rather than duplicative. In other words, this book emphasizes those parts of base R that fit in with using tidyr, dplyr, and ggvis.

Another thing I like about this book is that it walks through the process of installing R and RStudio, which can be intimidating if you are just starting out and you don't have someone to walk you through it.

The frustrating thing is that we have to wait for the next book for the payoff. I hope I can come back to this review to give it a fifth star with the release of the next volume.
11 von 14 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Redundant? 2. August 2014
Von Dimitri Shvorob - Veröffentlicht auf Amazon.com
Format:Taschenbuch
In my mind, R programming is mostly about data manipulation and visualization. In this book, R programming is about procedural programming in R, with a quick glance at the language's OOP features. This places "Hands-On R Programming" between most R learning aids, which cover [most of] these things within a chapter - my recommendation in this field is Robert Kabacoff's "R in Action" - and Norman Matloff's "The Art of R Programming", which covers a lot more ground and has a lot more depth, while being just as accessible, and actually cheaper. I have no complaints about the author's execution of his plan for the book - put simply and positively, I like his writing - but am pessimistic about the plan itself, and do not see the book as a worthwhile investment of $30+.
3 von 3 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Lots of fun and need to know techniques 28. August 2014
Von chrisinsouthphx - Veröffentlicht auf Amazon.com
Format:Taschenbuch
I really like this book.. I would give it 5 stars if it used real world problems instead of creating casino games. A lot of fun to read and I learned a lot. No more huge if-else trees! I know better now. Thanks Garrett! I recommend. this is a good beginner book to help you step up to that next, elusive level. Easy to follow. This book will boost your knowledge and programming confidence.
2 von 2 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Great programming focused introduction to R 12. Dezember 2014
Von Eric Watt - Veröffentlicht auf Amazon.com
Format:Taschenbuch
Garrett's book is exactly what I was looking for. Having some background in other languages, including some C++ and having just gone through Learning Python, I needed to get up to speed on R. The book is concise and well structured. The theme of the book, casino games, uses dice, cards, and a slot machine to systematically build up the complexity of what you can do in R. This cohesiveness helps to reinforce what you learned previously while better understanding the new topic. The depth into each topic was what I was hoping and expecting. You learn the structure and enough of the nuts and bolts that you can go look up more when necessary without it being too much to absorb at once. Garrett refers to websites and other books that have this detailed information that goes beyond the scope of this book.

The focus of the book is obvious from the title. Garrett approaches R like a programmer. I found this focus to be better for me than the first book on R that I read, Jared Lander's "R for Everyone: Advanced Analytics and Graphics". Jared's book goes into much more complicated statistics, but misses some of the fundamentals that made it difficult for me to understand later parts of the book. Garrett's approach, however, ensures you build up your base before moving on. If your background is more programming than stats, I think you should strongly consider Hand-On Programming with R.

The main problem I had with the book were related to formatting and editorial issues. Many of the problems are listed in the Errata, so hopefully this gets fixed. In some cases the output did not match what would be expected. In one case, a code example did not run as written, and needed a small change. Without these issues I would have gone with five stars.

In summary:

Pros:
Themes help to bridge topics. You spend your time learning the commands and functions, not trying to understand the dataset or the new example topic for that chapter.

Concise and tight writing with references for where to go for more info, including the help files for functions and packages themselves.

Mundane tasks such as installing R, R packages, updating, nuts and bolts of loading files, etc are all in the appendix. While this is great info to include, I'm glad this did not clog up the first few chapters. This lets you get right into learning R rather than learning how to download R.

Cons:
Editorial errors distract from learning the topic. Most are listed in the Errata already, I will add any new ones I found after finishing this review.

For the pdf version, links to external website or within the pdf are colored dark red and not underlined. On my screen, they don't show up as links and make it hard to be aware that they are clickable.

Though mentioned briefly at the start, you REALLY need to save all commands in an R script file and not just use the interactive prompt. There are points where you'll use a function or data frame from previous chapters. Unless you're going through the entire book in one session, you'll need to either retype these or load them back in from your R script. I had saved everything in an R script, but it would at times take some time to find the function. Referring to what chapter or page it was listed on when they are reused would be helpful. A minor point, but something I could see people being frustrated by, especially if you're going through the book slowly.

In full disclosure, I received an electronic copy of the book as part of the O'Reilly reader review program. However, I did not let this influence my review.
1 von 1 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Great R Book using the newer developments in R language such as RStudio 5. Februar 2015
Von Marc Telesha - Veröffentlicht auf Amazon.com
Format:Kindle Edition|Verifizierter Kauf
Another great resource for learning R. While it is frustrating that all these books cover the same basic information they all cover it slightly differently. This book coming from the RStudio's chief trainer is a well designed book which covers many aspects not covered as well as other books.

R as a programing language has also evolved so much over the past 5 years that I find that the newer books are a better start for beginners, not that the classics should be skipped. This book has a cleaner narrower focus and is a great fit for someone new to R. It uses less libraries and the libraries it uses are clean and make working with R easier. Also I couldn't imagine working with R without using RStudio and this book also shows short cuts on the language's best IDE that is free for personal use.

My suggestion is that someone with little to no experience programing should maybe get two books to learn R. 1) R for Everyone by Jared P. Lander (Though the font for the code in Kindle is frustrating because it doesn't show symbols correctly unless you copy and paste the code!) 2) Hands-On Programming with R by Garrett Gromlemund. Than after under standing these books and maybe doing a few free online courses get 1) The Art of R Programming by Norman Matloff and 2) R in Action by Robert Kabacoff (Only available for sale at the publishers website for the EBook)

What I want is a second book on using Hadley Wickham's libraries as a second book. Using Reshape2, ddplyr, tidyr, stringr, tidyr, ggplot2, ggvis and shiny.
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