Learning Data Mining with Python

Discovering Accounts to Follow Using Graph Mining
We can now visualize network using NetworkX's draw function, which uses
matplotlib. To get the image in our notebook, we use the inline function on
matplotlib and then call the draw function. The code is as follows:
%matplotlib inline
nx.draw(G)
The results are a bit hard to make sense of; they show that there are some nodes with
few connections but many nodes with many connections:
We can make the graph a bit bigger by using pyplot to handle the creation of the
figure. To do that, we import pyplot, create a large figure, and then call NetworkX's
draw function (NetworkX uses pyplot to draw its figures):
from matplotlib import pyplot as plt
plt.figure(3,figsize=(20,20))
nx.draw(G, alpha=0.1, edge_color='b')
The results are too big for a page here, but by making the graph bigger, an outline
of how the graph appears can now be seen. In my graph, there was a major group
of users all highly connected to each other, and most other users didn't have many
connections at all. I've zoomed in on just the center of the network here and set the
edge color to blue with a low alpha in the preceding code.
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