How to output attributes of nodes of a Graph (NetworkX) into a DataFrame (Pandas)

Question

I am working with networks as graph of the interaction between characters in Spanish theatre plays. Here a visualisation:

I passed several attributes of the nodes (characters) as a dataframe to the network, so that I can use this values (for example the color of the nodes is set by the gender of the character). I want to calculate with NetworkX different values for each nodes (degree, centrality, betweenness...); then, I would like to output as a DataFrame both my attributes of the nodes and also the values calculated with NetworkX. I know I can ask for specific attributes of the nodes, like:

nx.get_node_attributes(graph,'degree')

And I could build a DataFrame using that, but I wonder if there is no a more elegant solution. I have tried also:

nx.to_dict_of_dicts(graph)

But this outputs only the edges and not the information about the nodes.

So, any help, please? Thanks!

Hi! This creates the adjacency matrix, it doesn't print the attributes. I have been reading the parameters and I don't think this function is useful for that. — José
– José, Commented Nov 2, 2017 at 6:57

Alz · Accepted Answer · 2017-10-27 08:09:39Z

5

If I understand your question correctly, you want to have a DataFrame which has nodes and some of the attribute of each node.

G = nx.Graph()
G.add_node(1, {'x': 11, 'y': 111})
G.add_node(2, {'x': 22, 'y': 222})

You can use list comprehension as follow to get specific node attributes:

pd.DataFrame([[i[0], i[1]['x'], i[1]['y']] for i in G.nodes(data=True)]
             , columns=['node_name', 'x', 'y']).set_index('node_name')


#           x   y
#node_name      
#1         11   111
#2         22   222

or if there are many attributes and you need all of them, this could be a better solution:

pd.DataFrame([i[1] for i in G.nodes(data=True)], index=[i[0] for i in G.nodes(data=True)])

answered Oct 27, 2017 at 8:09

Alz

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1 Comment

José Over a year ago

Perfect, thanks! The last solution was exactly what I was looking for :)

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