Note

Go to the end to download the full example code.

# Quick Start

For the eager folks out there, this intro will give you a quick overview of the following operations:

- Construct a graph

- Set attributes of nodes and edges

- Plot a graph using matplotlib

- Save the plot as an image

- Export and import a graph as a `.gml` file

To find out more features that igraph has to offer, check out the gallery!

    /build/python-igraph-T4hlyX/python-igraph-0.11.8+ds/debian/python3-igraph/usr/lib/python3.12/dist-packages/igraph/io/files.py:494: RuntimeWarning: The boolean edge attribute 'married' was converted to numeric. at src/io/gml.c:1282
      return writer(f, *args, **kwds)

    import igraph as ig
    import matplotlib.pyplot as plt

    # Construct a graph with 5 vertices
    n_vertices = 5
    edges = [(0, 1), (0, 2), (0, 3), (0, 4), (1, 2), (1, 3), (1, 4), (3, 4)]
    g = ig.Graph(n_vertices, edges)

    # Set attributes for the graph, nodes, and edges
    g["title"] = "Small Social Network"
    g.vs["name"] = ["Daniel Morillas", "Kathy Archer", "Kyle Ding", "Joshua Walton", "Jana Hoyer"]
    g.vs["gender"] = ["M", "F", "F", "M", "F"]
    g.es["married"] = [False, False, False, False, False, False, False, True]

    # Set individual attributes
    g.vs[1]["name"] = "Kathy Morillas"
    g.es[0]["married"] = True

    # Plot in matplotlib
    # Note that attributes can be set globally (e.g. vertex_size), or set individually using arrays (e.g. vertex_color)
    fig, ax = plt.subplots(figsize=(5,5))
    ig.plot(
        g,
        target=ax,
        layout="circle", # print nodes in a circular layout
        vertex_size=30,
        vertex_color=["steelblue" if gender == "M" else "salmon" for gender in g.vs["gender"]],
        vertex_frame_width=4.0,
        vertex_frame_color="white",
        vertex_label=g.vs["name"],
        vertex_label_size=7.0,
        edge_width=[2 if married else 1 for married in g.es["married"]],
        edge_color=["#7142cf" if married else "#AAA" for married in g.es["married"]]
    )

    plt.show()

    # Save the graph as an image file
    fig.savefig('social_network.png')
    fig.savefig('social_network.jpg')
    fig.savefig('social_network.pdf')

    # Export and import a graph as a GML file.
    g.save("social_network.gml")
    g = ig.load("social_network.gml")

Total running time of the script: (0 minutes 0.282 seconds)

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