- Paperback: 384 pages
- Publisher: John Wiley & Sons (8 July 2011)
- Language: English
- ISBN-10: 0470944889
- ISBN-13: 978-0470944882
- Product Dimensions: 18.5 x 2.3 x 22.9 cm
- Average Customer Review: 2 customer reviews
- Amazon Bestsellers Rank: #4,07,462 in Books (See Top 100 in Books)
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Visualize This: The FlowingData Guide to Design, Visualization, and Statistics Paperback – 8 Jul 2011
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From the Back Cover
See your data in new ways
Our world is awash in data. To mean anything, it must be presented in a way that enables us to interpret, analyze, and apply the information. One of the best ways to do that is visually.
Nathan Yau is a pioneer of this innovative approach. In this book, he offers you dozens of ideas for telling your story with data presented in creative, visual ways. Open the book, open your mind, and discover an almost endless variety of ways to give your data new dimensions.
Learn to present data with visual representations that allow your audience to see the unexpected
Find the stories your data can tell
Explore different data sources and determine effective formats for presentation
Experiment with and compare different visualization tools
Look for trends and patterns in your data and select appropriate ways to chart them
Establish clear goals to guide your visualizations
Visit the companion web site at www.wiley.com/go/visualizethis for code samples, data files you can download, and interactive examples to show you how visualization works
About the Author
Nathan Yau is a PhD candidate in Statistics at UCLA and a lifelong data junkie. His goal is to make data available and useful to those who aren′t necessarily data experts, and he focuses on data visualization and personal data collection. You can follow his visualization experiments at http://flowingdata.com.
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Most helpful customer reviews on Amazon.com
The book describes several visualization methods. For each topic, Yau starts with a quick overview of the technique. He then follows with programming details (for example using R). He eventually shows the way from standard R graphics to nice visualizations using Illustrator. The book is thus very practical, with few place for theoretical concepts.
Yau provides several good advices such as the importance to question your data. The books contains tips and tricks for preparing and programming graphics. It is sometimes more of a R user manual than a general book on the topic. To be noted the excellent Chapter 7, about visualizing multi-dimensional data. This book is a must-have for people who want to prepare nice graphics in R. For expert users, the book is too straightforward (out of the last few chapters). For others, it’s a nice non-theoretical journey in the world of data visualization.
There is very little to complain about here except the fact that the author shows off Illustrator instead of its less expensive competitors. I had avoided Illustrator because of cost and the nasty learning curve but now, thanks to this book, I am using it to edit my SAS and R graphics that were "almost perfect." Happily this book has great examples for showing how to manipulate/clean up scientific graphics without getting bogged down in the endless complexity that is Illustrator.
So, this is all around beautiful, friendly and worth every cent if you need to make high quality graphics.