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You're reading from  Network Science with Python and NetworkX Quick Start Guide

Product typeBook
Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789955316
Edition1st Edition
Languages
Python
Tools
NetworkX
Concepts
Data Science
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Author (1)
Edward L. Platt
Edward L. Platt
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Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
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Summary

All networks are composed of nodes and edges, but different systems require nodes and edges with different attributes. This chapter introduced the Graph class for undirected networks, and the DiGraph class for directed networks, as well as the MultiGraph and MultiDiGraph classes. In addition, this chapter demonstrated how to attach data to nodes and edges using attributes. Now you know how to access the basic properties of a network in NetworkX using these classes, but where do those networks come from? The next chapter describes various techniques for creating networks from data.

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Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955316
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
Read more about Edward L. Platt

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