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Product details
File Size: 36567 KB
Print Length: 416 pages
Simultaneous Device Usage: Unlimited
Publisher: O'Reilly Media; 1 edition (December 6, 2012)
Publication Date: December 5, 2012
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B00AJ5X7W4
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This book is a must for anyone who works with ggplot2. There are so many excellent graph images, that I often flip through the book when I'm trying to figure out how to create a specific plot, but may not know what it is called.
If you're ever fumbling around with data in R, you're probably familiar with the built-in, unattractive graphics. ggplot2's been increasingly recognized as a necessity for getting the most out of your imagery. It offers nearly complete control over your graphics output, building them layer by layer.I spent a solid year learning and exploring R as a graduate student before I cracked open Winston Chang's R Graphics Cookbook and started learning ggplot2's little oddities. ggplot2 is itself almost like another language within R, but it's thankfully a very simple language -- far more simple and far more flexible, I feel, than the built-in graphics options.Since you'll be printing your graphics step by step -- your boundaries before your lines; your lines separately from points; etc. -- it's easy to keep track of where every impact on the output image is occurring, allowing you to easily tweak the code and get immediate results. E.g., if annotations are not lining up where you want, or font size needs to be reduced.Chang's cookbook is separated by what feature you need to either edit or create, making it easy to jump to what the reader needs. Full sections are devoted to bar graphs, line graphs, scatter plots, data distribution graphics, customizing annotations, axes, legends, color options, and cetera. Nearly 400 pages of text and images showing different ways of customizing and displaying every piece of your graphics. It's not a book you read cover to cover -- just the resource that 'cookbook' implies, meeting the reader's specific needs.If you want to just jump into the code and see what you can do with your own data, there's no better place to start. Almost no time is devoted to unnecessary exercises or teaching you the fundamentals of the R programming language. Exploring the far reaches of the Internet is a free alternative that's likely just as helpful, but Chang's book serves as a great reference, and contains almost everything you need all in one.
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.While "R in Action" might be better at easing the reader into the R language and environment, this book starts with enough R basics in its first two chapters, such as installing packages and loading data, that most will find it sufficient for getting their feet wet, and the author's introduction to ggplot2 in the appendix combined with Chapter 15 (Getting Your Data into Shape) are not only well done, but very succinct for busy professionals. After discussing bar graphs, line graphs, scatter plots, and summarized data distributions, the author presents annotations, axes, legends, and controlling the overall appearance of graphs, followed by discussions on facets, miscellaneous graphs, and outputting for presentation. If you are new to ggplot2, you will probably need to touch a majority of these chapters to some degree in order to get up to speed, but information is easy to find. Very well recommended.
Great book! The book is very well organized, which enables fast learning.The reason for missing a star:After 3 chapters, I notice that there are a lot of similarities among of the plots. It would be immensely helpful if the author added a brief introductions on ggplot: the philosophy of the developers and the common features of different geoms. To me, it works like a photoshop, things work in layers and the order of layers affect the output. An overview of ggplot is helpful is because before you plot anything, it is a good idea to have a holistic picture in mind what layers I would be needing and which is the best way to organize the layers. Recipes are easy for instant hands-on, but to figure out the principles based on discrete recipes is a demanding job for average users.Updated: in the end of the book, there is appendix A, which explains the philosophy of ggplot. -This is exactly what I wanted. I realized this after finishing the first 6 chapter. It really helps.
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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