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Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics Paperback – 8 Jul 2011

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Product details

  • Paperback: 384 pages
  • Publisher: John Wiley & Sons; 1 edition (8 July 2011)
  • Language: English
  • ISBN-10: 0470944889
  • ISBN-13: 978-0470944882
  • Product Dimensions: 18.8 x 2 x 23.4 cm
  • Average Customer Review: 3.7 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Bestsellers Rank: 112,805 in Books (See Top 100 in Books)
  • See Complete Table of Contents

More About the Author

My name is Nathan Yau, and I'm the one writing for FlowingData. In a previous life I was an electrical engineering and computer science student at Berkeley, but now I'm a UCLA PhD candidate in statistics with a focus in data visualization.
More specifically, I'm most interested in social data visualization, personal data collection, and data for non-professionals.

In a nutshell, I want to make data available and useful to those who aren't necessarily data experts; I think visualization plays a major role in this.

When I'm not playing with data, I'm usually cooking, eating, watching basketball, or hanging out with my wife.

Product Description

From the Author

From the Author: Telling Stories with Data

A common mistake in data design is to approach a project with a visual layout before looking at your data. This leads to graphics that lack context and provide little value. Visualize This teaches you a data-first approach. Explore what your data has to say first, and you can design graphics that mean something.

Visualization and data design all come easier with practice, and you can advance your skills with every new dataset and project. To begin though, you need a proper foundation and know what tools are available to you (but not let them bog you down). I wrote Visualize This with that in mind.

You'll be exposed to a variety of software and code and jump right into real-world datasets so that you can learn visualization by doing, and most importantly be able to apply what you learn to your own data.

Three Data Visualization Steps:

1) Ask a Question
(Click Graphic to See Larger Version)

When you get a dataset, it sometimes is a challenge figuring out where to start, especially when it's a large dataset. Approach your data with a simple curiosity or a question that you want answered, and go from there.

2) Explore Your Data
(Click Graphic to See Larger Version)

A simple curiosity often leads to more questions, which are a good guide for what stories to dig into. What variables are related to each other? Can you see changes over time? Are there any features in the data that stand out? Find out all you can about your data, because the more you know what's behind the numbers, the better story you can tell.

3) Visualize Your Data
(Click Graphic to See Larger Version)

Once you know the important parts of your data, you can design graphics the best way you see fit. Use shapes, colors, and sizes that make sense and help tell your story clearly to readers. While the base of your charts and graphs will share many of the same properties – bars, slices, dots, and lines – the final design elements will and should vary by your unique dataset.

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


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


Inside This Book

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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews

3.7 out of 5 stars
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Most Helpful Customer Reviews

18 of 18 people found the following review helpful By Finn Newick on 16 July 2011
Format: Paperback Verified Purchase
This book concentrates on the visual presentation of numerical data. Most books on this subject that are already out there either focus on the data or the presentation but rather uniquely this one picks up on how these two ends of the spectrum meet in the middle. The techniques for extracting data from various sources, exploring the data and then selecting clear visualisations that enable further exploration and discovery are all presented in clear, practical examples that can be worked through. You won't find any meaningless data-porn here, just modern techniques for developing elegant and beautiful visualisations!

The book seems to be aimed at beginning or lower-intermediate data designers who are comfortable with either design or statistics (but not necessarily both) but it's good refreshing read even if you're already familiar with the content as the text contains many insightful thoughts from the author. I'm giving it 4 rather than 5 stars as it would've been nice if the book was rounded off with with one or two more challenging examples.
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12 of 12 people found the following review helpful By Andrew Scotchmer on 23 July 2012
Format: Paperback Verified Purchase
I bought this book on a Friday with delivery the following day. All of that weekend I wasn't able to put the book down and even now I am always flicking through the pages for inspiration. It is a must read for anyone who handles data and/or prepares reports based on data, and is simply beautiful in its presentation. It is clear that every aspect of this book has been carefully considered, from the typeface to the page layout.

This book will open your eyes to what is possible once you move away from Microsoft Excel. As a professional analyst and data modeller, I have been using Excel for years but was growing frustrated with its limitations. In this book, Nathan Yau uses R, Python and Adobe Illustrator (though I personally prefer the open-source Inkscape equivalent) to show just what can be achieved with a little imagination and creativity.

I have given this five stars. Although it would have been nice to have more complex walk-throughs from raw data to final graphic as suggested in other reviews, to do so would have required the reader to have a solid foundation in R and Python programming. To include the required learning material in these programming languages so as to bring the reader up to speed as a programmer, as well as containing the excellent material it already does contain, would have required a book three or four times the thickness. If we were then to add a needed introductory statistics course into the book as well...

I think therefore to penalise the book for focusing purely on the creation of great looking graphics is a bit harsh especially when it says "Visualise", "design" and "visualisation" in the title.
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4 of 4 people found the following review helpful By Thinksamuel on 27 May 2013
Format: Paperback Verified Purchase
The book is definitely nice for people who want to get their hands dirty and start visualising right away. The author gives simple, easy-to-understand tutorials on how to use the different software packages (mainly R and Adobe Illustrator). The extent of links and other references is big and sure enough offers a lot of future possibilities. The book is nicely printed, the illustrations are good quality which helps a lot when reading.

The downside for me was that I was looking more for theoretical concepts behind it (my own research is in data sonification and I wanted to see what visualists do). The author seems (at least to me) to speak for personal experiences, he does not refer to scientific parameters which is a bit of a miss to me. As such, the most interesting part was the first chapter on data gathering.

Conclusion: do you want to get a quickstart with visualisation, read this book. If you want to read something more theoretical, look further. The links to different datasites are interesting nevertheless
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1 of 1 people found the following review helpful By PTBW on 23 Sept. 2013
Format: Paperback Verified Purchase
I bought this book to get a different viepoint on how to generate graohics which were not just your usual two colour bar charts etc. and this book doesn't dissapoint!. The author presents a dazzling array of options together with the R code required to generate them but some of them are definately not for the novice user. Overall the book has an esy style and can be dipped into as required. Explanations are good and it is well worth the money.
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3 of 4 people found the following review helpful By David Brake on 9 Aug. 2013
Format: Paperback
I don't usually review books but this one's utility leapt out at me as I leafed through it. Not only does it 1) provide a good introduction to some basic visualisation design principles and basic statistical/visual literacy (worth it in itself), it also provides 2) step by step instructions to enable the reader to put this knowledge into action using (mostly) free open source software - R, python, javascript etc - and in a reasonably accessible style with plenty of relevant illustrations (as you expect/need in a book about visualisation).

My main reservation about this book is that the author uses the "R" statistical software to do many of the manipulations. It is powerful and free but as he says himself "the software itself isn't very helpful in guiding new users"... and if you like "buttons and clicking and dragging" (which I do!) you will find it hard to use (p. 73). As a result you end up towards the end of the book with chunks like "the c()directive creates an empty vector, which you add to in each iteration [9 lines of code] then pass the reading_colors array into parallel instead of the lone #000000". This gives you Figure 7-24..." But some of this complexity is probably unavoidable if you want to get your hands dirty.
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