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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

Adding attributes to nodes and edges

In the last chapter, I said that networks were entirely defined by the number of nodes and which nodes were connected. I lied. Kind of. Now that we're all a little older and wiser than we were in Chapter 1, What is a Network?, I can tell you the whole truth: sometimes, network nodes and edges are annotated with additional information. In the Graph class, each node and edge can have a set of attributes to store this additional information. Attributes can simply be a convenient place to store information related to the nodes and edges, or they can be used by visualizations and network algorithms.

The Graph class allows you to add any number of attributes to a node. For a G, network, each node's attributes are stored in the dict at G.nodes[v], where v is the node's ID. In the karate club example, the club members eventually split...

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