<｜begin▁of▁sentence｜>### Instruction:
As a Sales Associate working at a popular sports merchandise store specializing in college football memorabilia, you are responsible for assisting customers in finding their favorite team's apparel and accessories. One day, a loyal customer walks into the store looking for a special gift for a friend who is a huge college football fan. The customer mentions that their friend is interested in the network structure of American college football teams and suggests using a GML file named football.gml to analyze the relationships between different teams.

In order to provide top-notch customer service, you decide to leverage the Entropy-Based Graph Clustering (EBGC) function available in the cdlib API to perform community detection on the American College Football Graph provided in the football.gml file. By applying this cutting-edge methodology, you aim to offer valuable insights to the customer regarding the clustering and connections among various college football teams, ultimately enhancing their shopping experience and satisfaction with your store.
### Response:
import networkx as nx
from cdlib import algorithms

# Create a graph from the American College Football dataset
G = nx.read_gml('path_to_football.gml')

# Apply Entropy-Based Graph Clustering algorithm
coms = algorithms.ebgc(G)

# Display the resulting communities
print(coms.communities)
<|EOT|>
