Summary

Visualizing Graph Data teaches you not only how to build graph data structures, but also how to create your own dynamic and interactive visualizations using a variety of tools. This book is loaded with fascinating examples and case studies to show you the real-world value of graph visualizations.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Assume you are doing a great job collecting data about your customers and products. Are you able to turn your rich data into important insight? Complex relationships in large data sets can be difficult to recognize. Visualizing these connections as graphs makes it possible to see the patterns, so you can find meaning in an otherwise over-whelming sea of facts.

About the Book

Visualizing Graph Data teaches you how to understand graph data, build graph data structures, and create meaningful visualizations. This engaging book gently introduces graph data visualization through fascinating examples and compelling case studies. You'll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data. By the end, you'll have a conceptual foundation as well as the practical skills to explore your own data with confidence.

What's Inside

• Techniques for creating effective visualizations
• Examples using the Gephi and KeyLines visualization packages
• Real-world case studies

About the Reader

No prior experience with graph data is required.

About the Author

Corey Lanum has decades of experience building visualization and analysis applications for companies and government agencies around the globe.

Table of Contents

PART 1 - GRAPH VISUALIZATION BASICS

1. Getting to know graph visualization
2. Case studies
3. An introduction to Gephi and KeyLines

PART 2 VISUALIZE YOUR OWN DATA

4. Data modeling
5. How to build graph visualizations
6. Creating interactive visualizations
7. How to organize a chart
8. Big data: using graphs when there's too much data
9. Dynamic graphs: how to show data over time
10. Graphs on maps: the where of graph visualization