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.

• Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers


• Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table


• Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more


• Examines standard rules across all visualization applications, then explores when and where you can break those rules

Create visualizations that register at all levels, with Data Points: Visualization That Means Something.

Nathan Yau has a PhD in statistics and is a statistical consultant who helps clients make use of their data through visualization. He created the popular site FlowingData.com, and is the author of Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, also published by Wiley.

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