O'Reilly logo

Mastering Data Mining with Python – Find patterns hidden in your data by Megan Squire

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Representing graph data

The theoretical aspects of networks are important, but in order to be able to apply these ideas to a real-world problem, we have to first transform our data into a format that a network analysis program can understand. In this section, we will discover the common formats for representing data in a network-friendly way.

Adjacency matrix

An adjacency matrix is a convenient way to represent graph data. To construct an adjacency matrix for an undirected, unweighted graph, we can create a grid that has all the nodes listed across the top as columns, and also down the side of the grid as rows. Then we use a 1 or 0 to indicate whether there is a link between those two nodes. Consider the unweighted, undirected graph shown in Figure ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required