Advanced Data Science and Analytics with Python by Rogel-Salazar Jesus;

Author:Rogel-Salazar, Jesus;
Language: eng
Format: epub
Publisher: CRC Press LLC
Published: 2020-10-15T00:00:00+00:00

We can use separate methods to render the network in the way we want. Using draw_networkx_edges for the edges, draw_networkx_nodes for the nodes and draw_networkx_labels for the labels. Notice that all have the same position attribute.

We are drawing separately the edges, nodes and labels all with the same position layout. Note that we are encoding the closeness measure both in the size of the node and in its colour. Figure 3.12 shows the result of the commands above. You can see that the size alone would not tell us much about the closeness; however, the colour lets us obtain the information desired.

We can now turn our attention to what nodes are best connected within the network. We have seen that the eigenvector centrality provides a view of the nodes that are endorsed by influential actors. We can calculate the eigenvector centrality as follows:

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