| | |  | Software Development | Home » » » » Data Manipulation with R (Use R!) | | | | | | | Description: | | This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data. In addition to the built-in functions, a number of readily available packages from CRAN (the Comprehensive R Archive Network) are also covered. All of the methods presented take advantage of the core features of R: vectorization, efficient use of subscripting, and the proper use of the varied functions in R that are provided for common data management tasks. Most experienced R users discover that, especially when working with large data sets, it may be helpful to use other programs, notably databases, in conjunction with R. Accordingly, the use of databases in R is covered in detail, along with methods for extracting data from spreadsheets and datasets created by other programs. Character manipulation, while sometimes overlooked within R, is also covered in detail, allowing problems that are traditionally solved by scripting languages to be carried out entirely within R. For users with experience in other languages, guidelines for the effective use of programming constructs like loops are provided. Since many statistical modeling and graphics functions need their data presented in a data frame, techniques for converting the output of commonly used functions to data frames are provided throughout the book. | | | Product Details: | | | Author:
| Phil Spector | | Paperback:
| 164 pages | | Publisher:
| Springer | | Publication Date:
| March 19, 2008 | | Language:
| English | | ISBN:
| 0387747303 | | Product Width:
| 1.5 centimeters | | Product Height:
| 2.31 centimeters | | Product Weight:
| 0.01 pounds | | Package Length:
| 9.1 inches | | Package Width:
| 5.9 inches | | Package Height:
| 0.5 inches | | Package Weight:
| 0.4 pounds | | Average Customer Rating:
| based on 15 reviews |
| | | | Customer Reviews: | |
Average Customer Review:
( 15 customer reviews )
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Most Helpful Customer Reviews
75 of 79 found the following review helpful:
a must for statisticians wanting to learn RMay 11, 2008
By Michael R. Chernick
"statman31147"
This book along with Jim Albert's should be read by every statistician that does a lot of statistical computing. Both books help you learn R quickly and apply it to many important problems in research both applied and theoretical. Albert emphasizes applications in Bayesian statistics whereas Spector is teaching how to do data manipulation, things like merging and transposing data sets. These techniques can be easy to do in a language like SAS after a little training but in other programming languages it can be very difficult.
23 of 23 found the following review helpful:
Great little bookJun 13, 2008
By F. Tusell Palomer
"F.Tusell"
This concise 150 page book contains a wealth of information, writen clearly and with many well-chosen examples. I liked it a lot. It covers reading and writing data in/out of the R workspace, including access to databases. The names of other chapters suggest the topics covered: "Dates", "Factors", "Subscripting", "Character manipulation", "Data aggregation", "Reshaping data".
This book will be helpful to any but the most absolutely new to R, and even the seasoned user will find interesting hints and examples. I cannot recommend it enough.
One minor qualm I have is the absence of references. Some topics (for instance, regular expressions) are fairly complex, and well documented elsewhere: a pointer or two would be helpful. Same with, for instance, SQL, which is mentioned and demonstrated briefly.
Another not-so-minor qualm is price. A book of this size from, for instance, Dover classics collection, with similar paper quality and covers, is about a third or fourth of the price. Although this is a new book I find the $54.95 tag (Amazon discounted price is about $44.50) fairly high. But this has nothing to do with the quality of the book, rather it has to do with the Springer pricing policies.
All in all, if you don't mind the price, this is a good buy.
18 of 18 found the following review helpful:
Start hereDec 20, 2008
By I Teach Typing All too often novices wanting to use R for an analysis never get to the analysis because they can't successfully import, clean-up and restructure their data for the analysis functions. This book prevents those problems by telling you the critical data and file manipulation materials that are usually briefly (and inadequately) covered in stat books. It is a short easy read that will give you the tools to get your data ready to go.
You can see the table of contents and read the other reviews but areas that really shine include: dealing with categorical (named or ordered) factor variables, recoding numeric data into categorical variables, and also making and working with summary tables.
When it comes to data manipulation and clean-up Spector has the best coverage of any book or web FAQ. This book is very expensive for its size but it is worth every cent.
6 of 6 found the following review helpful:
Useful code but disorganizedSep 06, 2009
By Formicarius I am neither a statistician nor a computer programmer yet I used statistics and programming on a daily basis and that is my perspective on this book. I am an ecologist with messy data with relational databases, missing data, dates etc. Most statisticians will already have more than a dollop of programming under their belts and will have a completely different experience with this book. I found the book disorganized with sections that should occur together in different sections or in the wrong order of how a user would approach a problem. For example, Chapter 3 goes over SQL coding but I wasn't sure what package we were supposed to be using or if this coding was used for all of them and, if so, what are the caveats to each. It would have been incredibly useful to discuss these three packages with strengths, weaknesses, and examples of each. It's great that there's code to use MySQL but it would have been useful to provide some information on the MySQL side so one could get going on queries without referring to yet another manual. Much of this information was redundant with other manuals that one should already have such as Introductory Statistics with R (Statistics and Computing), Modern Applied Statistics with S, and The R Book.
3 of 3 found the following review helpful:
Not as good a book as "R in a Nutshell"Nov 08, 2010
By Marty Epstein I was pretty disappointed with the thoroughness of this book on R. I ordered the book "R in a Nutshell" as well and Nutshell does a much better job explaining the same topics and does it in a much more through manner and you don't feel like you got ripped off spending $50 on this very thin book. I would not recommend it and instead would choose R in a Nutshell for learning how to do R data cleaning, manipulation, processing and analysis.
See all 15 customer reviews on Amazon.com
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