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

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Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789955316
Edition1st Edition
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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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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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Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955316

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