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Data Points
Visualization That Means Something
Nathan Yau (Author)
9781118462195, Wiley
Paperback / softback, published 12 April 2013
320 pages
22.9 x 18.3 x 2 cm, 0.635 kg
"Data Points opens an exciting view of information blending data analysis, visual interaction, and digital storytelling... the visuals are stunning." (Managing Information, October 2013) "Ultimately, I would recommend this book for anyone interested in the process of design and analysis. It is about making sense of data and that is becoming a crucial skill in this digital age." (Media Information & Technology Journal, August 2013) "A detailed handbook, Data Points is espe??cially useful for those working on scientific data visualization, guiding the reader through fascinat??ing examples of data, graph??ics, context, presentation and analytics. But this is more than a mere how-to manual. Yau reminds us that the real purpose of most visualiza??tion work is to communicate data to pragmatic ends." (Nature, May 2013)
A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Create visualizations that register at all levels, with Data Points: Visualization That Means Something.
Introduction xi 1 Understanding Data 1 What Data Represents 2 Variability 20 Uncertainty 30 Context 35 Wrapping Up 41 2 Visualization: The Medium 43 Analysis and Exploration 45 Information Graphics and Presentation 58 Entertainment 69 Data Art 74 The Everyday 81 Wrapping Up 89 3 Representing Data 91 Visualization Components 93 Putting It Together 115 Wrapping Up 132 4 Exploring Data Visually 135 Process 136 Visualizing Categorical Data 143 Visualizing Time Series Data 154 Visualizing Spatial Data 165 Multiple Variables 176 Distributions 193 Wrapping Up 199 5 Visualizing with Clarity 201 Visual Hierarchy 202 Readability 205 Highlighting 221 Annotation 228 Do the Math 236 Wrapping Up 239 6 Designing for an Audience 241 Common Misconceptions 242 Present Data to People 254 Things to Consider 258 Putting It Together 268 Wrapping Up 273 7 Where to Go from Here 277 Visualization Tools 278 Programming 283 Illustration 288 Statistics 289 Wrapping Up 289
Index 291
Subject Areas: Mathematics [PB]
