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Product Description
Product Description
Practical data design tips from a data visualization expert of the modern age
Data doesn’t decrease; it is ever–increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn’t it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full–color book, data visualization guru and author Nathan Yau uses step–by–step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships.
- Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau
- Offers step–by–step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers
- Details tools that can be used to visualize data–native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator
- Contains numerous examples and descriptions of patterns and outliers and explains how to show them
Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.
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
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
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
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.
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.
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Learn to present data with visual representations that allow your audience to see the unexpected
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Find the stories your data can tell
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Explore different data sources and determine effective formats for presentation
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Experiment with and compare different visualization tools
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Look for trends and patterns in your data and select appropriate ways to chart them
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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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Customer Reviews
Most Helpful Customer Reviews
12 of 12 people found the following review helpful
Format:Paperback
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.
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.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
28 reviews
36 of 38 people found the following review helpful
Great start
9 Aug 2011
Format:Paperback|Amazon Verified Purchase
I really enjoyed this book. It is absolutely beautifully printed and the examples are well made and well explained. There are a couple of things I would have liked to see done a little differently.
First, every example uses Adobe Illustrator to make the visualization look as good as they do. In order to complete the exercises, you must have Illustrator. Nathan does explain that it can be obtained at a discount or you can an older version, but it's still a pretty big financial investment. If I hadn't been able to dig up a old copy, Illustrator 9, I would have been out of luck. Even with my outdated copy, not everything worked for me. If he had included at least a couple of examples with the open source Inkscape, this would have been a 5 star rating.
The second thing I would have liked to see a little different is more statistical info to go along with the visualizations. We often visualize data to help make decisions. Nathan shows how to display a LOESS line to see the best fit for the curve, but he stops there. Maybe discussing R² ( correlation coefficient) analysis to determine whether the values are are a good match would help me feel better about analyzing the data beyond just visualization.
That said, this is an extremely well written book and easily deserves 4 stars. Dig up an old copy of Illustrator (preferably CSx versions) and enjoy this book.
First, every example uses Adobe Illustrator to make the visualization look as good as they do. In order to complete the exercises, you must have Illustrator. Nathan does explain that it can be obtained at a discount or you can an older version, but it's still a pretty big financial investment. If I hadn't been able to dig up a old copy, Illustrator 9, I would have been out of luck. Even with my outdated copy, not everything worked for me. If he had included at least a couple of examples with the open source Inkscape, this would have been a 5 star rating.
The second thing I would have liked to see a little different is more statistical info to go along with the visualizations. We often visualize data to help make decisions. Nathan shows how to display a LOESS line to see the best fit for the curve, but he stops there. Maybe discussing R² ( correlation coefficient) analysis to determine whether the values are are a good match would help me feel better about analyzing the data beyond just visualization.
That said, this is an extremely well written book and easily deserves 4 stars. Dig up an old copy of Illustrator (preferably CSx versions) and enjoy this book.
15 of 16 people found the following review helpful
Diappointingly Vague and Circular
10 Jan 2012
Format:Paperback|Amazon Verified Purchase
I was really hoping for a book on how to abstract data sets into visualizations, with concrete programming examples. In other words, "ask yourself these questions about the data; with these answers (or those), the data is best visualized in these formats. Now, let's implement".
Instead, I found it to be a kind of "circular" logic (visualize data in good ways is important... here is some data visualized in a good way... now doesn't that show how important it is - and it's cool... btw here is a code snippet). It is almost like the book is just trying to convince me that data visualization can be powerful and cool. I know that - that's why I bought this, I wanted to learn the tools and techniques to determine the best and most innovative way to visualize data sets, not how the author has visualized existing data sets he has dealt with.
Interesting enough to borrow if you see it on a friend's desk, but I don't think I'd purchase it again if I had the opportunity.
Instead, I found it to be a kind of "circular" logic (visualize data in good ways is important... here is some data visualized in a good way... now doesn't that show how important it is - and it's cool... btw here is a code snippet). It is almost like the book is just trying to convince me that data visualization can be powerful and cool. I know that - that's why I bought this, I wanted to learn the tools and techniques to determine the best and most innovative way to visualize data sets, not how the author has visualized existing data sets he has dealt with.
Interesting enough to borrow if you see it on a friend's desk, but I don't think I'd purchase it again if I had the opportunity.
19 of 22 people found the following review helpful
Nice book on visualizing with R
20 July 2011
Format:Paperback|Amazon Verified Purchase
This is a nice addition to the books on data visualization. It will be particulary useful for people wanting to learn R (the lingua franca of statisticians) to create good looking visualizations. The writing style is crisp and conversational and is organized around the kind of things one might want the data to communicate: time series, part-to-whole comparisons, relationships, etc. It does not require any expertise in programming or statistics to understand.
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