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Visualize filtered graph using nxviz

Here, you'll visualize the filtered graph using a circos plot. The circos plot is a natural choice for this visualization, as you can use node grouping and coloring to visualize the partitions, while the circular layout preserves the aesthetics of the visualization.

This exercise is part of the course

Intermediate Network Analysis in Python

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Exercise instructions

  • Compute degree centrality scores of each node using the bipartite module degree centralities, but based on the degree centrality in the original graph.
    • Use the nx.bipartite.degree_centrality() function for this, with the arguments G and nodes=forum_nodes.
  • Create a new circos plot with nodes colored and grouped (parameters node_color_by and group_by) by their partition label ('bipartite'), and ordered (parameter sort_by) by their degree centrality ('dc') and display it.
    • To ensure that the nodes are visible when displayed, we have included the argument node_enc_kwargs={'radius': 10}.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import necessary modules
from nxviz import circos
import networkx as nx
import matplotlib.pyplot as plt

# Compute degree centrality scores of each node
dcs = ____(____, nodes=____)
for n, d in G_sub.nodes(data=True):
    G_sub.nodes[n]['dc'] = dcs[n]

# Create the circos plot: c
c = _____(___, _____, _____, _____, node_enc_kwargs={'radius': 5})

# Display the plot
plt.show()
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