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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? FREE CHAPTER 2. Working with Networks in NetworkX 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

MultiGraph and MultiDiGraph – parallel edges

Meanwhile, in 18th-century Königsberg, both Graph and DiGraph fall short. Several of the bridges of Königsberg (discussed in Chapter 1, What is a Network?) connected the same two landmasses. In order to represent the bridges as a network, the nodes representing the land masses need to have multiple parallel edges, but the Graph class only allows one edge between a pair of nodes. For situations like this, NetworkX provides the MultiGraph and MultiDiGraph classes. For many applications, parallel edges can be combined into a single weighted edge, but when they can't, these classes can be used.

These MultiGraph and MultiDigraph classes work very much like Graph and DiGraph, but allow parallel edges. Any number of edges can be added between the same two endpoints. The following example reconstructs the Königsberg...

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