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Network Science with Python and NetworkX Quick Start Guide

You're reading from   Network Science with Python and NetworkX Quick Start Guide Explore and visualize network data effectively

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789955316
Length 190 pages
Edition 1st Edition
Languages
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Author (1):
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Edward L. Platt Edward L. Platt
Author Profile Icon Edward L. Platt
Edward L. Platt
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Table of Contents (15) Chapters Close

Preface 1. What is a Network? 2. Working with Networks in NetworkX FREE CHAPTER 3. From Data to Networks 4. Affiliation Networks 5. The Small Scale - Nodes and Centrality 6. The Big Picture - Describing Networks 7. In-Between - Communities 8. Social Networks and Going Viral 9. Simulation and Analysis 10. Networks in Space and Time 11. Visualization 12. Conclusion 13. Other Books You May Enjoy Appendix

Summary

All networks are composed of nodes and edges, but different systems require nodes and edges with different attributes. This chapter introduced the Graph class for undirected networks, and the DiGraph class for directed networks, as well as the MultiGraph and MultiDiGraph classes. In addition, this chapter demonstrated how to attach data to nodes and edges using attributes. Now you know how to access the basic properties of a network in NetworkX using these classes, but where do those networks come from? The next chapter describes various techniques for creating networks from data.

You have been reading a chapter from
Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019
Publisher: Packt
ISBN-13: 9781789955316
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