R in a Nutshell: A Desktop Quick Reference (In a Nutshell (O'Reilly)) 1st Edition
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About the Author
Joseph Adler has many years of experience in data mining and data analysis at companies including DoubleClick, American Express, and VeriSign. He graduated from MIT with an Sc.B and M.Eng in Computer Science and Electrical Engineering from MIT. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks. Currently, he is a senior data scientist at LinkedIn.
- Publisher : O'Reilly Media; 1st edition (January 14, 2010)
- Language : English
- Paperback : 636 pages
- ISBN-10 : 059680170X
- ISBN-13 : 978-0596801700
- Item Weight : 1.85 pounds
- Dimensions : 6 x 1.22 x 9 inches
- Best Sellers Rank: #863,884 in Books (See Top 100 in Books)
- Customer Reviews:
Top reviews from the United States
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I teach programming, so I found the references to how R differs from languages like LISP, C and JAVA very useful. However, those distinctions will be at best distracting or more likely horribly confusing to programming novices. With that distinction in mind, this book is exceptionally well written and has great clear explanations on things that are missing from practically every other R book (like the distinction between if else and ifelse. Other sections, like the coverage of graphics can be found elsewhere but require you to distill a LOT of other books.
If you want to really understand R start here and then go for John Chambers books (especially Software for Data Analysis: Programming with R (Statistics and Computing) ). If you want to learn how to use R for data analysis get Zuul's book then follow my learning R guide.
I made two attempts to learn R before purchasing this book. In both previous attempts, I had to abort and use another tool to solve my problem because it was taking me too long to accomplish very simple things in R.
The reason R is hard to learn is that its documentation is organized for statisticians that already know R, but have forgotten a detail or two. There are a few other books on learning R, but they are setup like a college course - complete the entire book and THEN you can actually accomplish something.
R in a Nutshell allows you to get working immediately. Simply lookup what you need to do. The firsts thing I did was load a file and make a histogram. I found that stuff in the section on "Loading Data" and the section on charts. In no time I was making stacked area charts for cohorts. Now R is an essential tool for me - and I haven't even taken the time to learn it well! With this book, I don't have to. I can learn as I go. So I actually use R.
Do not R without it.
I also ordered the Data Manipulation in R book and found this to be far superior as far as being easier to understand and more complete.
Finally, I have a sense of how the language works, and how I can make it work for me.
Beyond that, the book has an extensive description of the language itself, descriptions of the Graph and Lattice Graph models of interaction and presentation, and sections on preparing data, common statistical manipulations, and more.
For me, most Nutshell books sit within reach of my workstation, to be pulled down to read about a particular language feature. This book I find myself browsing and grazing.
Top reviews from other countries
The structure is slightly contrived with the topics forced into a "Problem - Solution - Discussion" treatment but the cross-referencing is well done and examples are given which are easy to transfer into R.
There are lots of topics presented here that I have found quite difficult to get by searching the help archives (including a good guide to finding help) but particularly in data transformation and applying functions.
Nach einer kurzen Einführung folgt in Kapitel zwei gleich ein Tutorial. Das kann man in einer Stunde durcharbeiten. Solide, aber nix besonderes. Zusätzlich daszu sollte man noch eines (oder zwei) der online frei erhältlichen R tutorials durcharbeiten.
Das Buch hat seine Stärken in den Erklärungen wie R funktioniert, was die besonderheiten der Sprache sind, welche Objekte unterschieden werden und wie man Daten in R holt (tolles Kapitel, echter Mehrwert zur Online help). Ein bisschen zu kurz gekommen ist aber das schreiben und debuggen von Funktionen.
Deckt nicht alles ab, trotzdem eines der besten Bücher, die ich als Einführung in eine Sprache gelesen habe. Ab hier gehts sehr schnell weiter. Mir hats geholfen. Kaufempfehlung.