share/doc/networkx-3.1/examples/graph/plot_football.py

"""
========
Football
========

Load football network in GML format and compute some network statistcs.

Shows how to download GML graph in a zipped file, unpack it, and load
into a NetworkX graph.

Requires Internet connection to download the URL
http://www-personal.umich.edu/~mejn/netdata/football.zip
"""

import urllib.request
import io
import zipfile

import matplotlib.pyplot as plt
import networkx as nx

url = "http://www-personal.umich.edu/~mejn/netdata/football.zip"

sock = urllib.request.urlopen(url)  # open URL
s = io.BytesIO(sock.read())  # read into BytesIO "file"
sock.close()

zf = zipfile.ZipFile(s)  # zipfile object
txt = zf.read("football.txt").decode()  # read info file
gml = zf.read("football.gml").decode()  # read gml data
# throw away bogus first line with # from mejn files
gml = gml.split("\n")[1:]
G = nx.parse_gml(gml)  # parse gml data

print(txt)
# print degree for each team - number of games
for n, d in G.degree():
    print(f"{n:20} {d:2}")

options = {"node_color": "black", "node_size": 50, "linewidths": 0, "width": 0.1}

pos = nx.spring_layout(G, seed=1969)  # Seed for reproducible layout
nx.draw(G, pos, **options)
plt.show()