How can I use NetworkX for advanced graph analysis?

How can I use NetworkX for advanced graph analysis?

You can use NetworkX to perform various advanced analyses like community detection, centrality measures, and more. What specific analysis are you interested in?

I'm interested in community detection. How can I implement that?

You can use algorithms like Girvan-Newman or Louvain method in NetworkX. Would you like a code example for one of these?

Yes, please provide a code example for the Louvain method.

Sure! Here's a simple example:

import networkx as nx
from community import community_louvain

G = nx.erdos_renyi_graph(100, 0.05)
partition = community_louvain.best_partition(G)

This will give you the community partition of the graph.

That looks great! How can I visualize the communities?

You can use Matplotlib to visualize the communities. Here's how:

import matplotlib.pyplot as plt

pos = nx.spring_layout(G)

cmap = plt.get_cmap('viridis', max(partition.values()) + 1)

nx.draw(G, pos, node_color=[cmap(partition[node]) for node in G.nodes()], with_labels=True)
plt.show()