Graphs from Edge Lists

Module 5: Complex Networks

Toolkit page

This page is self-study material for Session 23. It continues Drawing Attributes.

import matplotlib.pyplot as plt
import networkx as nx

Creating a Graph from an Edge List

In practice, you often have data in the form of an edge list, which is a list of pairs of nodes that are connected by edges. You can create a graph directly from an edge list using the from_edgelist() method. For example:

# Define the edge list (actors that have worked together in movies)
edge_list = [
    ("Antonio Banderas", "Brad Pitt"),  # Interview with the Vampire (1994)
    ("Antonio Banderas", "Javier Bardem"),  # Automata (2014)
    ("Antonio Banderas", "Penelope Cruz"),  # Dolor y Gloria (2019)
    ("Antonio Banderas", "Tom Holland"),  # Uncharted (2022)
    ("Brad Pitt", "Javier Bardem"),  # F1 (2025)
    ("Javier Bardem", "Timothée Chalamet"),  # Dune (2021)
    ("Timothée Chalamet", "Zendaya"),  # Dune (2021)
    ("Tom Holland", "Zendaya"),  # Spider-Man: No Way Home (2021)
]

# Create a graph from the edge list
G_actors = nx.from_edgelist(edge_list)
# Draw the graph
pos = nx.spring_layout(G_actors, k=0.15, iterations=20)
# k is the optimal distance between nodes (default 1/sqrt(N))
# iterations is the number of force-directed update steps (default 50)

nx.draw(
    G_actors,
    pos=pos,
    with_labels=True,
    node_color='lightgreen',
    edge_color='gray',
    node_size=2000,
    font_size=12
    )
plt.show()

Exercise

The comments next to the edges name the movie each pair made together. Build a graph whose edges carry a movie attribute and draw it with the movie titles as edge labels.

movies = [
    ("Antonio Banderas", "Brad Pitt", "Interview with the Vampire"),
    # TODO: the other seven pairs with their movie
]
G_movies = nx.Graph()
for a, b, title in movies:
    # TODO: add the edge with a movie attribute
    pass

pos = nx.spring_layout(G_movies, seed=1)
nx.draw(G_movies, pos=pos, with_labels=True)
# TODO: draw the edge labels with nx.draw_networkx_edge_labels
plt.show()

Solution

movies = [
    ("Antonio Banderas", "Brad Pitt", "Interview with the Vampire"),
    ("Antonio Banderas", "Javier Bardem", "Automata"),
    ("Antonio Banderas", "Penelope Cruz", "Dolor y Gloria"),
    ("Antonio Banderas", "Tom Holland", "Uncharted"),
    ("Brad Pitt", "Javier Bardem", "F1"),
    ("Javier Bardem", "Timothée Chalamet", "Dune"),
    ("Timothée Chalamet", "Zendaya", "Dune"),
    ("Tom Holland", "Zendaya", "Spider-Man: No Way Home"),
]
G_movies = nx.Graph()
for a, b, title in movies:
    G_movies.add_edge(a, b, movie=title)

pos = nx.spring_layout(G_movies, seed=1)
nx.draw(G_movies, pos=pos, with_labels=True, node_color="lightgreen", node_size=1500)
nx.draw_networkx_edge_labels(G_movies, pos, edge_labels=nx.get_edge_attributes(G_movies, "movie"))
plt.show()

What’s Next?

The next page measures paths, components and distances.

Paths and Components

--- title: "Graphs from Edge Lists" subtitle: "Module 5: Complex Networks" format: html --- ::: {.callout-note} ## Toolkit page This page is self-study material for Session 23. It continues [Drawing Attributes](networkx-drawing-attributes.qmd). ::: ```{python} import matplotlib.pyplot as plt import networkx as nx ``` ## Creating a Graph from an Edge List In practice, you often have data in the form of an edge list, which is a list of pairs of nodes that are connected by edges. You can create a graph directly from an edge list using the `from_edgelist()` method. For example: ```{python} #| echo: true #| message: true # Define the edge list (actors that have worked together in movies) edge_list = [ ("Antonio Banderas", "Brad Pitt"), # Interview with the Vampire (1994) ("Antonio Banderas", "Javier Bardem"), # Automata (2014) ("Antonio Banderas", "Penelope Cruz"), # Dolor y Gloria (2019) ("Antonio Banderas", "Tom Holland"), # Uncharted (2022) ("Brad Pitt", "Javier Bardem"), # F1 (2025) ("Javier Bardem", "Timothée Chalamet"), # Dune (2021) ("Timothée Chalamet", "Zendaya"), # Dune (2021) ("Tom Holland", "Zendaya"), # Spider-Man: No Way Home (2021) ] # Create a graph from the edge list G_actors = nx.from_edgelist(edge_list) # Draw the graph pos = nx.spring_layout(G_actors, k=0.15, iterations=20) # k is the optimal distance between nodes (default 1/sqrt(N)) # iterations is the number of force-directed update steps (default 50) nx.draw( G_actors, pos=pos, with_labels=True, node_color='lightgreen', edge_color='gray', node_size=2000, font_size=12 ) plt.show() ``` ::: {.callout-note} ## Exercise The comments next to the edges name the movie each pair made together. Build a graph whose edges carry a `movie` attribute and draw it with the movie titles as edge labels. ```python movies = [ ("Antonio Banderas", "Brad Pitt", "Interview with the Vampire"), # TODO: the other seven pairs with their movie ] G_movies = nx.Graph() for a, b, title in movies: # TODO: add the edge with a movie attribute pass pos = nx.spring_layout(G_movies, seed=1) nx.draw(G_movies, pos=pos, with_labels=True) # TODO: draw the edge labels with nx.draw_networkx_edge_labels plt.show() ``` ::: ::: {.callout-tip collapse="true"} ## Solution ```python movies = [ ("Antonio Banderas", "Brad Pitt", "Interview with the Vampire"), ("Antonio Banderas", "Javier Bardem", "Automata"), ("Antonio Banderas", "Penelope Cruz", "Dolor y Gloria"), ("Antonio Banderas", "Tom Holland", "Uncharted"), ("Brad Pitt", "Javier Bardem", "F1"), ("Javier Bardem", "Timothée Chalamet", "Dune"), ("Timothée Chalamet", "Zendaya", "Dune"), ("Tom Holland", "Zendaya", "Spider-Man: No Way Home"), ] G_movies = nx.Graph() for a, b, title in movies: G_movies.add_edge(a, b, movie=title) pos = nx.spring_layout(G_movies, seed=1) nx.draw(G_movies, pos=pos, with_labels=True, node_color="lightgreen", node_size=1500) nx.draw_networkx_edge_labels(G_movies, pos, edge_labels=nx.get_edge_attributes(G_movies, "movie")) plt.show() ``` ::: ## What's Next? The next page measures paths, components and distances. [Paths and Components](networkx-paths.qmd){.btn .btn-primary}