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I created a graph G (network library) through the adjacency matrix A (numpy matrix) that stores the weights of the links.

import numpy as np
import networkx as nx

A = np.loadtxt('SM_waste.csv',delimiter=';')
G = nx.from_numpy_matrix(A, parallel_edges=False, create_using=None)

I also have the list of the names of the nodes but I don't know how to assign the name to each node. How can I do?

Fabio
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  • Does this answer your question? [Group nodes together in networkx](https://stackoverflow.com/questions/55750436/group-nodes-together-in-networkx) – Ali_Sh Jun 24 '22 at 17:33

1 Answers1

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You can loop over the nodes and append the label from the row index.

Example with faker data:

import faker
import networkx as nx

for node in G.nodes():
    G.nodes[node]['name'] = faker.Faker().name()

G.nodes(data=True)

With some fake names this outputs for ten nodes a NodeDataView looking like so

>>> NodeDataView({0: {'name': 'Kayla Martin'}, 1: {'name': 'Billy Knight'}, 2: {'name': 'Joshua Landry'}, 3: {'name': 'Jessica Perez'}, 4: {'name': 'Emily Garcia'}, 5: {'name': 'Stephen Foster'}, 6: {'name': 'Timothy Howell'}, 7: {'name': 'Stephanie Gonzales'}, 8: {'name': 'Maurice Miller'}, 9: {'name': 'Emily Caldwell'}, 10: {'name': 'Amy Rice'}

In your case this could look something like:

import numpy as np
import networkx as nx

A = np.loadtxt('SM_waste.csv',delimiter=';')
G = nx.from_numpy_matrix(A, parallel_edges=False, create_using=None)

labels = ["<list of your row labels here indexed according to the adjacency matrix>"]

for idx, node in enumerate(G.nodes()):
    G.nodes[node]['label'] = labels[idx]

Note that the above solution probably won't work if you call G.nodes() with data=True.

Hope this helps.

Huug.
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