www.allitebooks.com

Discovering Accounts to Follow Using Graph Mining
Next, iterate over each connected component and add a subplot for each. The
parameters to add_subplot are the number of rows of subplots, the number of
columns, and the index of the subplot we are interested in. My visualization uses
three columns, but you can try other values instead of three (just remember to
change both values):
for i, sub_graph in enumerate(sub_graphs):
ax = fig.add_subplot(int(n_subgraphs / 3), 3, i)
By default, pyplot shows plots with axis labels, which are meaningless in this
context. For that reason, we turn labels off:
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
Then we plot the nodes and edges (using the ax parameter to plot to the correct
subplot). To do this, we also need to set up a layout first:
pos = nx.spring_layout(G)
nx.draw_networkx_nodes(G, pos, sub_graph.nodes(), ax=ax,
node_size=500)
nx.draw_networkx_edges(G, pos, sub_graph.edges(), ax=ax)
The results visualize each connected component, giving us a sense of the number
of nodes in each and also how connected they are.
[ 154 ]