Preface;
How This Book Is Organized;
Conventions Used in This Book;
Using Code Examples;
How to Contact Us;
Safari® Books Online;
Acknowledgments;
Chapter 1: On Beauty;
1.1 What Is Beauty?;
1.2 Learning from the Classics;
1.3 How Do We Achieve Beauty?;
1.4 Putting It Into Practice;
1.5 Conclusion;
Chapter 2: Once Upon a Stacked Time Series;
2.1 Question + Visual Data + Context = Story;
2.2 Steps for Creating an Effective Visualization;
2.3 Hands-on Visualization Creation;
2.4 Conclusion;
Chapter 3: Wordle;
3.1 Wordle's Origins;
3.2 How Wordle Works;
3.3 Is Wordle Good Information Visualization?;
3.4 How Wordle Is Actually Used;
3.5 Conclusion;
3.6 Acknowledgments;
3.7 References;
Chapter 4: Color: The Cinderella of Data Visualization;
4.1 Why Use Color in Data Graphics?;
4.2 Luminosity As a Means of Recovering Local Density;
4.3 Looking Forward: What About Animation?;
4.4 Methods;
4.5 Conclusion;
4.6 References and Further Reading;
Chapter 5: Mapping Information: Redesigning the New York City Subway Map;
5.1 The Need for a Better Tool;
5.2 London Calling;
5.3 New York Blues;
5.4 Better Tools Allow for Better Tools;
5.5 Size Is Only One Factor;
5.6 Looking Back to Look Forward;
5.7 New York's Unique Complexity;
5.8 Geography Is About Relationships;
5.9 Sweat the Small Stuff;
5.10 Conclusion;
Chapter 6: Flight Patterns: A Deep Dive;
6.1 Techniques and Data;
6.2 Color;
6.3 Motion;
6.4 Anomalies and Errors;
6.5 Conclusion;
6.6 Acknowledgments;
Chapter 7: Your Choices Reveal Who You Are: Mining and Visualizing Social Patterns;
7.1 Early Social Graphs;
7.2 Social Graphs of Amazon Book Purchasing Data;
7.3 Conclusion;
7.4 References;
Chapter 8: Visualizing the U.S. Senate Social Graph (1991-2009);
8.1 Building the Visualization;
8.2 The Story That Emerged;
8.3 What Makes It Beautiful?;
8.4 And What Makes It Ugly?;
8.5 Conclusion;
8.6 References;
Chapter 9: The Big Picture: Search and Discovery;
9.1 The Visualization Technique;
9.2 [...];
9.3 The Netflix Prize;
9.4 Creating Your Own;
9.5 Conclusion;
9.6 References;
Chapter 10: Finding Beautiful Insights in the Chaos of Social Network Visualizations;
10.1 Visualizing Social Networks;
10.2 Who Wants to Visualize Social Networks?;
10.3 The Design of SocialAction;
10.4 Case Studies: From Chaos to Beauty;
10.5 References;
Chapter 11: Beautiful History: Visualizing Wikipedia;
11.1 Depicting Group Editing;
11.2 History Flow in Action;
11.3 Chromogram: Visualizing One Person at a Time;
11.4 Conclusion;
Chapter 12: Turning a Table into a Tree: Growing Parallel Sets into a Purposeful Project;
12.1 Categorical Data;
12.2 Parallel Sets;
12.3 Visual Redesign;
12.4 A New Data Model;
12.5 The Database Model;
12.6 Growing the Tree;
12.7 Parallel Sets in the Real World;
12.8 Conclusion;
12.9 References;
Chapter 13: The Design of "X by Y";
13.1 Briefing and Conceptual Directions;
13.2 Understanding the Data Situation;
13.3 Exploring the Data;
13.4 First Visual Drafts;
13.5 The Final Product;
13.6 Conclusion;
13.7 Acknowledgments;
13.8 References;
Chapter 14: Revealing Matrices;
14.1 The More, the Better?;
14.2 Databases As Networks;
14.3 Data Model Definition Plus Emergence;
14.4 Network Dimensionality;
14.5 The Matrix Macroscope;
14.6 Reducing for Complexity;
14.7 Further Matrix Operations;
14.8 The Refined Matrix;
14.9 Scaling Up;
14.10 Further Applications;
14.11 Conclusion;
14.12 Acknowledgments;
14.13 References;
Chapter 15: This Was 1994: Data Exploration with the NYTimes Article Search API;
15.1 Getting Data: The Article Search API;
15.2 Managing Data: Using Processing;
15.3 Three Easy Steps;
15.4 Faceted Searching;
15.5 Making Connections;
15.6 Conclusion;
Chapter 16: A Day in the Life of the New York Times;
16.1 Collecting Some Data;
16.2 Let's Clean 'Em First;
16.3 Python, Map/Reduce, and Hadoop;
16.4 The First Pass at the Visualization;
16.5 Scene 1, Take 1;
16.6 Scene 1, Take 2;
16.7 The Second Pass at the Visualization;
16.8 Visual Scale and Other Visualization Optimizations;
16.9 Getting the Time Lapse Working;
16.10 So, What Do We Do with This Thing?;
16.11 Conclusion;
16.12 Acknowledgments;
Chapter 17: Immersed in Unfolding Complex Systems;
17.1 Our Multimodal Arena;
17.2 Our Roadmap to Creative Thinking;
17.3 Project Discussion;
17.4 Conclusion;
17.5 References;
Chapter 18: Postmortem Visualization: The Real Gold Standard;
18.1 Background;
18.2 Impact on Forensic Work;
18.3 The Virtual Autopsy Procedure;
18.4 The Future for Virtual Autopsies;
18.5 Conclusion;
18.6 References and Suggested Reading;
Chapter 19: Animation for Visualization: Opportunities and Drawbacks;
19.1 Principles of Animation;
19.2 Animation in Scientific Visualization;
19.3 Learning from Cartooning;
19.4 Presentation Is Not Exploration;
19.5 Types of Animation;
19.6 Staging Animations with DynaVis;
19.7 Principles of Animation;
19.8 Conclusion: Animate or Not?;
19.9 Further Reading;
19.10 Acknowledgments;
19.11 References;
Chapter 20: Visualization: Indexed.;
20.1 Visualization: It's an Elephant.;
20.2 Visualization: It's Art.;
20.3 Visualization: It's Business.;
20.4 Visualization: It's Timeless.;
20.5 Visualization: It's Right Now.;
20.6 Visualization: It's Coded.;
20.7 Visualization: It's Clear.;
20.8 Visualization: It's Learnable.;
20.9 Visualization: It's a Buzzword.;
20.10 Visualization: It's an Opportunity.;
Contributors;
Colophon;