Graph Analysis and Visualization

Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.

Introduction xvii PART 1 Overview Chapter 1 Why Graphs? 3 Chapter 2 A Graph for Every Problem 27 PART 2 Process and Tools Chapter 3 Data--Collect, Clean, and Connect 55 Chapter 4 Stats and Layout 87 Chapter 5 Visual Attributes 125 Chapter 6 Explore and Explain 157 Chapter 7 Point-and-Click Graph Tools 187 Chapter 8 Lightweight Programming 223 PART 3 Visual Analysis of Graphs Chapter 9 Relationships 275 Chapter 10 Hierarchies 293 Chapter 11 Communities 315 Chapter 12 Flows 351 Chapter 13 Spatial Networks 389 PART 4 Advanced Techniques Chapter 14 Big Data 419 Chapter 15 Dynamic Graphs 449 Chapter 16 Design 473 Glossary 497 Index 501