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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

Working with Networks in NetworkX

The basic features of NetworkX are contained in several Python classes that represent different types of networks. In particular, this chapter discusses Graph, DiGraph, MultiGraph, and MultiDiGraph. These classes can be used to represent, analyze, and visualize most networks. In this chapter, you will learn to use these classes to work with real-world network data in NetworkX. The code examples in this and future chapters will assume that you have already imported the networkx package.

In this chapter, we will cover the following topics:

  • The Graph class: Understand the properties of undirected networks and how they are represented using the NetworkX Graph class.
  • Attributes: How to associate data with nodes and edges.
  • Edge weights: Learn how to quantify connection strength, and annotate edges with that information.
  • The DiGraph class: Understand...
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