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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

The DiGraph class – when direction matters

So far, all of the edges in this chapter have been undirected, with no difference between an edge from A to B, and an edge from B to A. But not all relationships in life are so symmetric. If an employee-boss relationship is described by an undirected edge, it suggests that the employee can fire the boss as easily as the other way around. While possibly good for workplace morale, such arrangements aren't the norm. NetworkX supports directed edges through the DiGraph (directed graph) class.

Many of the operations already described for the Graph class translate seamlessly to the DiGraph class. Iterating through nodes and edges, accessing attributes, and visualization are all exactly the same. But there are a few differences. This section will describe the most important of these differences.

This section will use another social...

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