| Visualize This: The FlowingData Guide to Design, Visualization, and Statistics |  | Author: Nathan Yau
Publisher: Wiley
Category: Book
List Price: $39.99
Buy New: $21.50
as of 5/18/2012 14:26 EDT details
You Save: $18.49 (46%)
New (50) Used (21) from $20.47
Seller: indoobestsellers
Sales Rank: 3,008
Languages: English (Unknown), English (Original Language), English (Published)
Media: Paperback
Edition: 1
Pages: 384
Number Of Items: 1
Shipping Weight (lbs): 1.9
Dimensions (in): 9.1 x 7.4 x 0.8
ISBN: 0470944889
EAN: 9780470944882
ASIN: 0470944889
Publication Date: July 20, 2011
Availability: Usually ships in 1-2 business days
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Product Description
Practical data design tips from a data visualization expert of the modern ageData 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: Telling Stories with Data
 | | Author Nathan Yau | 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.
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