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R Graphics Cookbook Paperback – January 6, 2013

ISBN-13: 978-1449316952 ISBN-10: 1449316956 Edition: 1st

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Product Details

  • Paperback: 416 pages
  • Publisher: O'Reilly Media; 1 edition (January 6, 2013)
  • Language: English
  • ISBN-10: 1449316956
  • ISBN-13: 978-1449316952
  • Product Dimensions: 7 x 0.9 x 9.2 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (46 customer reviews)
  • Amazon Best Sellers Rank: #14,292 in Books (See Top 100 in Books)

Editorial Reviews

Amazon.com Review

Q&A with Winston Chang, author of "R Graphics Cookbook: Practical Recipes for Visualizing Data"

Winston Chang

Q. Why is your book timely?

A. Interest in R for data analysis and visualization has exploded in recent years. In the computer-tech world, computers and networks have made it much easier to gather and organize data, and more and more people have recognized that there's useful information to be found. To illustrate, consider the job "data scientist": this is a job title that didn't even exist five years ago, and now it's one of the hottest tickets on the market.

At the same time, there's been a swell of interest in R in its more traditional setting, in science and engineering. I think there are many reasons for this. One, is that there's a growing recognition outside of the computer-programmer world that learning a little programming can save you a lot of time and reduce errors. Another reason is that the last few years have seen an improvement in the user-friendliness of tools for using R.

So there's a lot of interest in using R for finding information in data, and visualization an essential tool for doing this. Data visualizations can help you understand your data and find patterns when you're in the exploratory phase of data analysis, and they are essential for communicating your findings to others.

Q. What information do you hope that readers of your book will walk away with?

A. As my book is a Cookbook, the primary goal is to efficiently present solutions for visualizing data, without demanding a large investment of time from the reader. For many readers, the goal is to just figure out how to make a particular type of graph and be done with it.

There are others who will want to gain a deeper understanding of how graphing works in R. For these readers, I've written an appendix on the graphing package ggplot2, which is used extensively in the recipes in the book. This appendix explains some of the concepts in the grammar of graphics, and how they relate to structures common to data visualizations in general.

Finally, I hope that readers will find ideas and inspiration for visualizing their data by browsing the pages and looking at the pictures.

Q. What's the most exciting/important thing happening in your space?

A. I'm excited that R is becoming more and more accessible to users who don't primarily identify as programmers. Many scientists, engineers, and data analysts have outgrown programs that provide canned data analysis routines, and they're turning increasingly to R. The growing popularity of R is part of a virtuous circle: as R gains a larger user base, it encourages people to create better educational materials and programming tools for R, which in turn helps to grow the number of R users.

Technology-wise, I'm excited by Shiny, which is a framework for bringing R analyses to the web. (I should mention that this it's part of my job to work on the development of Shiny.) This makes it possible to build interactive applications for data analysis and visualization for users who don't need to know R, or even that the application is backed by R.

Book Description

Practical Recipes for Visualizing Data

Customer Reviews

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A very interesting book.
Hector Gustavo Gonzalez Padilla
I have Hadley Wickham's book on ggplot2 ggplot2: Elegant Graphics for Data Analysis (Use R!), which is a great introduction to advanced R graphics.
steve_oakland
I am about halfway through this book and I love it.
AAJN

Most Helpful Customer Reviews

29 of 30 people found the following review helpful By Ravi Aranke on January 10, 2013
Format: Paperback
Even if you know R, learning to do graphs well in R is like learning (yet another) new language - that of ggplot2.

You could learn a new language by first studying its grammar and building some vocabulary. In that case, you might want to start with ggplot2 creator's book ggplot2: Elegant Graphics for Data Analysis (Use R!). That's an excellent book and that's where I started.

Still, there are many loose ends in my understanding of ggplot2 and sometimes I struggle to find the exact technique to achieve the effect I want. e.g. do I set fill or colour? What does grouping exactly do? How do I rearrange factors? How do I remove the legends and clean up the grid lines?

I am sure answers to all such questions could be found by googling and reading Hadley's original text carefully. However, the beauty of Winston Chang's book is that it has compiled tons of such examples in recipe format and is a huge time saver. Now this is my first stop reference, even before hitting google or stackoverflow.

Another advantage of the book is that all recipes are self contained and you could quickly pick up a technique or two in any 5 minute of break time. After immersing myself in enough examples during last week, I feel I am getting better hang of grammar of graphics (philosophy behind ggplot2).

By the way, if you have not read Hadley's book or tutorial, please read Appendix A before you dive in.
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7 of 7 people found the following review helpful By Felipe Carrillo on February 24, 2013
Format: Paperback Verified Purchase
Even though I am really familiar with ggplot2, plyr and reshape, Winston Chang have some great tricks manipulating data and creating awesome graphics that I had never seen before. The recipe format of this book is great for beginners and advanced users because one can get straight answers without having to read too much.
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9 of 10 people found the following review helpful By Dimitri Shvorob on February 6, 2013
Format: Paperback
... "ggplot2" being a particular, fairly mature and popular R graphics package developed by Hadley Wickham, and described in his 2009 book "ggplot2: Elegant graphics for data analysis". Three years later, Winston Chang's accessible and inexpensive how-to book can push "ggplot2" into the mainstream. It is actually a different book, "R for Everyone" by Jared Lander, that brought me over the fence separating "old school" R graphics and "ggplot2" - it's a pity that, talking about a "syntax" of graphics, neither "ggplot2"-focused book manages to be textbook-systematic about it, and the reader has to pick up the general points as they go through examples - but once I am here, "R Graphics Cookbook" is a necessity.
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3 of 3 people found the following review helpful By steve_oakland VINE VOICE on September 5, 2013
Format: Paperback Verified Purchase
I have Hadley Wickham's book on ggplot2 ggplot2: Elegant Graphics for Data Analysis (Use R!), which is a great introduction to advanced R graphics. However, since that book was published in 2009, a few updates in R and ggplot2 have made some of the tricks I used for plots obsolete and I've had to refer to the online ggplot2 documentation to update my code. The R Graphics Cookbook makes this task of finding best practices for ggplot2 much easier, and provides some really concrete examples. This R Graphics Cookbook and the ggplot2 book make for a powerful combination.
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3 of 3 people found the following review helpful By W. Hogan on December 12, 2013
Format: Kindle Edition Verified Purchase
This book is nice to have on hand for finding example code quickly.
There are a variety of examples.
The code is more up to date than Hadley Wickham's book.
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2 of 2 people found the following review helpful By Grant Coble-Neal on February 2, 2014
Format: Kindle Edition Verified Purchase
Very helpful to have a comprehensive set of examples in a single book. I treat it like a lexicon, looking up what I want to do and seeing how it's done in just a few pages. Great companion for serious and casual R users.
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3 of 4 people found the following review helpful By Luiz Marques on January 14, 2013
Format: Paperback
I have just finished looking through (and trying out) the recipes in R Graphics Cookbook. First of all, I'm very much a beginner in R, but it was possible to follow the examples.

One thing I really liked about the book is that the example data comes straight from a package. So you install and download them with a simple command in R when you start the book, and you just have to do a library(gcookbook) each time you use an example in a session. Very nice (vs downloading, setting a folder or using the full name for each file,etc).

The book seems to cover the material well enough, and the discussion section usually present useful options. For example, on the recipe Labeling Points in a Scatter Plot the basic solution is presented, and then it shows how to shift labels so they don't crowd the data points, or how to add only a few relevant labels.

Since my background only include the most common graphs, I also learned about a few other graph types, such as correlation matrix, dendograms, vector fields and choropleth map.

Overall, pretty good.
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Format: Paperback Verified Purchase
This book is the third that I have recently used to get up to speed on the R language and environment. The other two texts include "R in a Nutshell" and "R in Action" (see my review). The main catalysts behind my decision to purchase another book on R was my need to get up to speed with using the language to create graphs, and that not only are plotting functions that come with base R not unified behind a common interface and set of options, there exist limitations with base R plotting functions. Of course, there are other plotting functions across the over 2500 packages that have become available to the community, but the ggplot2 package that is the focus of this book is well regarded and grown in use to become one of the most popular R packages since its release in 2005.

What Chang presents in this book is extremely practical. My recent pro bono work to move a client away from Microsoft Excel to this powerful open source platform and industry standard used for both small and big data analytics is partially testament to the usefulness of this book. While I have needed to peruse R package documentation as part of this work, it is not a stretch to say that a majority of what I needed was contained in this book, either as starting points or complete examples. The explanations are very well written and organized, and the fact that all of the pertinent graphs are in color was very helpful when it came time to understanding how ggplot2 can be used for tasks such as plotting multiple lines in one plot, and the data setup that is necessary to perform these tasks, which is a bit different than base R plotting functions, but worth the effort to use since ggplot2 employs universal usage patterns.
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