<｜begin▁of▁sentence｜>### Instruction:
As a network analysis expert, I can assist in applying the Louvain algorithm to the American College Football network. Imagine you are a data scientist tasked with analyzing the network of college football teams to identify communities within the network. By using the Louvain algorithm from the cdlib library, you can detect communities and then calculate the scaled density for each community. This approach will provide valuable insights into the structure of the college football network and the relationships between different teams. The data for this analysis can be obtained from a GML file named football.gml, which contains information about the connections between the college football teams.
### Response:
import networkx as nx
from cdlib import algorithms
from cdlib import evaluation

# Create a graph
G = nx.read_gml('football.gml')

# Apply the Louvain community detection algorithm
communities = algorithms.louvain(G)

# Compute the scaled density of the detected communities
scaled_density_score = evaluation.scaled_density(G, communities)

# Print the scaled density of the communities
print(scaled_density_score)
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