Network Data Representations
Learn how to represent complex networks with edge lists, adjacency matrices, and adjacency lists.
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Representing complex networks
In this lesson, we’re going to explore different ways we can represent a complex network and how we can implement them in the NetworkX library. The importance of knowing these different types of representations is to know when to use each to be more productive and waste less computational resources. In some cases, some algorithms are applied more easily to one form over another, so converting between these forms will be very useful for our practice as a complex network analyst.
For every method, we’re going to see how to represent the following network:
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