PDF Ebook R Graphics Cookbook, by Winston Chang
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R Graphics Cookbook, by Winston Chang
PDF Ebook R Graphics Cookbook, by Winston Chang
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This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.
Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started.
- Use R’s default graphics for quick exploration of data
- Create a variety of bar graphs, line graphs, and scatter plots
- Summarize data distributions with histograms, density curves, box plots, and other examples
- Provide annotations to help viewers interpret data
- Control the overall appearance of graphics
- Render data groups alongside each other for easy comparison
- Use colors in plots
- Create network graphs, heat maps, and 3D scatter plots
- Structure data for graphing
- Sales Rank: #101435 in eBooks
- Published on: 2012-12-06
- Released on: 2012-12-05
- Format: Kindle eBook
Amazon.com Review
Q&A with Winston Chang, author of "R Graphics Cookbook: Practical Recipes for Visualizing Data"
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.
About the Author
Winston Chang is a software engineer at RStudio, where he works on data visualization and software development tools for R. He holds a Ph.D. in Psychology from Northwestern University. During his time as a graduate student, he created a website called "Cookbook for R", which contains recipes for handling common tasks in R. In previous lives, he was a philosophy graduate student and a computer programmer.
Most helpful customer reviews
45 of 46 people found the following review helpful.
Treasure trove of graphing ideas and recipes
By Ravi Aranke
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.
17 of 17 people found the following review helpful.
Great book
By Felipe Carrillo
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.
13 of 14 people found the following review helpful.
Actually, ggplot2 graphics cookbook
By Dimitri Shvorob
... "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.
UPD. With the benefit of a little more life experience, I would say: don't spend your time on *any* R book. Python is the way to go.
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