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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

Reading and writing network files

NetworkX provides support for reading and writing many network file formats. Of course, if a network has been provided in one of these formats, it will be very easy to load into NetworkX! But, even if you have data in another format, it is often possible to convert it to one of the supported formats without too much difficulty (I would guess that 90% of network science work is converting data between formats most of the rest is complaining about converting data). Spreadsheets, for instance, can often be converted to an appropriate format just by reordering columns and exporting as tab-separated values (TSV format). This section will describe several common formats, including adjacency list, edge list, GEXF, and JSON.

The edge list format is a simple but useful plain-text format. It supports edge attributes, but not node attributes. Edge lists...

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