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Learning RStudio for R Statistical Computing Paperback – December 24, 2012


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Product Details

  • Paperback: 126 pages
  • Publisher: Packt Publishing (December 24, 2012)
  • Language: English
  • ISBN-10: 1782160604
  • ISBN-13: 978-1782160601
  • Product Dimensions: 0.3 x 7.4 x 9.1 inches
  • Shipping Weight: 6.4 ounces (View shipping rates and policies)
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #272,211 in Books (See Top 100 in Books)

Editorial Reviews

About the Author

Mark van der Loo

Mark van der Loo obtained his PhD at the Institute for Theoretical Chemistry at the University of Nijmegen (The Netherlands). Since 2007 he has worked at the statistical methodology department of the Dutch official statistics office (Statistics Netherlands). His research interests include automated data cleaning methods and statistical computing. At Statistics Netherlands he is responsible for the local R center of expertise, which supports and educates users on statistical computing with R. Mark has been teaching R for several years and coauthored a number of R packages that are available via CRAN: editrules, deducorrect, rspa, and extremevalues. A list of publications can be found viahttp://www.markvanderloo.eu..



Edwin de Jonge

Edwin de Jonge has worked for more than 15 years at the Dutch official statistics office (Statistics Netherlands). With a background in theoretical and computational solid state physics (MSc), he started in the statistical computing department. Currently he works in the statistical methodology department. His research interests include data visualization, data analysis, and statistical computing. He trained over 150 people in a workshop entitled "Graphical Analysis with R". Edwin has coauthored several R packages that are available via CRAN: tabplot, tabplotd3, ffbase, whisker, editrules, and deducorrect.


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Customer Reviews

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Most Helpful Customer Reviews

6 of 6 people found the following review helpful By Nick H on January 22, 2013
Format: Paperback
The book focuses more on giving an overview of RStudio's capabilities without getting too in-depth with examples. At a few over 100 pages, the book is a quick read, and as with most R references, the author gives guidance for readers to find more information on particular topics online. I particularly enjoyed the section on Markdown and knitr because I haven't used these tools in RStudio before. If you aren't the type of person who likes to browse the web for answers, search documentation, read forums, etc... this is a great book.
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8 of 10 people found the following review helpful By Renato Vitolo on March 4, 2013
Format: Paperback
I have just had the pleasure of reading "Learning RStudio for R Statistical Computing" and found it very useful for my work as a quantitative analyst.

The book offers a self-contained introduction to RStudio, an extremely well-designed and functional interface to the R interpreter.

Given its strong "hands-on", "get-things-done" approach, the book provides a rather complete introduction for the beginner, be she an experienced data analyst who is not familiar with R, or an altogether inexperienced data analyst.

While the book does not present advanced statistical theories or methods, it focuses on how to get started with data analysis, from setting up and managing a project (Chapter 4), through data exploration (Chapter 3 on data viewing and plotting), down to generating reports (Chapter 5).

As an expert R developer, I found the last chapters particularly useful for me: they provide simple access to advanced features of RStudio, such as the automatic generation of reports in different formats (HTML, LaTeX, Chapter 5) and the development of an R package for distribution among colleagues or in the web (Chapter 6).

What I find particularly valuable in the book is its conciseness, whereby many topics are introduced with minimal examples, retaining, however all the essential ingredients and bibliographic references. This allows a hasty (or lazy) reader to quickly skim through and reach her goal.

I therefore definitely recommend this book as a handy swiss-knife for the eager (wannabe) data analyst.
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1 of 1 people found the following review helpful By BBCReview on November 8, 2013
Format: Kindle Edition Verified Purchase
Best part is that the R Studio tool does a lot of useful stuff like organizing packages and making functions that you can reuse.
No terrible parts, but most users will only scratch the surface with R Studio.
The book is helpful in that its organized well into chunks. You can skip the parts you dont need right now and get to the next chunk quickly.
Also, there is not a single example that you have to track from end to end. Examples are contained only in one chunk, so you are free to move about the book.
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Format: Paperback Verified Purchase
I had already used RStudio for a while before reading the book, but until a few weeks ago I was more impressed by Eclipse (if it wasn't for the horribly complex installation process, I would have recommended Eclipse to everyone).
However, it took this book to understand RStudio's full potential, including for version control with Git - it will now be very hard to convince me there is anything better on the market than RStudio.
The book would have been even better if it had covered some topics (such as version control with several contributors) in more depth.
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3 of 7 people found the following review helpful By Mary Anne Thygesen on January 21, 2013
Format: Paperback
I wish that I would of had this book Learning RStudio for R Statistical Computing last summer when I had a job using R. I would of been more efficient and able to turn out sweet reports.
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