This documents the development version of NetworkX. Documentation for the current release can be found here.

Ego Graph

Example using the NetworkX ego_graph() function to return the main egonet of the largest hub in a Barabási-Albert network.

plot ego graph
from operator import itemgetter

import matplotlib.pyplot as plt
import networkx as nx

# Create a BA model graph
n = 1000
m = 2
G = nx.generators.barabasi_albert_graph(n, m)

# find node with largest degree
node_and_degree =
(largest_hub, degree) = sorted(node_and_degree, key=itemgetter(1))[-1]

# Create ego graph of main hub
hub_ego = nx.ego_graph(G, largest_hub)

# Draw graph
pos = nx.spring_layout(hub_ego)
nx.draw(hub_ego, pos, node_color="b", node_size=50, with_labels=False)

# Draw ego as large and red
options = {"node_size": 300, "node_color": "r"}
nx.draw_networkx_nodes(hub_ego, pos, nodelist=[largest_hub], **options)

Total running time of the script: ( 0 minutes 0.156 seconds)

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