Networkx Multigraph from_pandas_dataframe

Question

Update:
The question, as written, is relevant to Networkx version < 2.0. The from_pandas_dataframe method has been dropped .
To accomplish the same task in Networkx >= 2.0, see the update to the accepted answer.

Trying to create a MultiGraph() instance from a pandas DataFrame using networkx's from_pandas_dataframe . What am I doing wrong in the example below?

In [1]: import pandas as pd
        import networkx as nx

        df = pd.DataFrame([['geneA', 'geneB', 0.05, 'method1'],
                           ['geneA', 'geneC', 0.45, 'method1'],
                           ['geneA', 'geneD', 0.35, 'method1'],
                           ['geneA', 'geneB', 0.45, 'method2']], 
                           columns = ['gene1','gene2','conf','type'])

First try with the default nx.Graph():

In [2]: G= nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr=['conf','type'], 
                                    create_using=nx.Graph())

As a non-MultiGraph(), I'm missing one of the duplicate edges:

In [3]: G.edges(data=True)
Out[3]: [('geneA', 'geneB', {'conf': 0.45, 'type': 'method2'}),
         ('geneA', 'geneC', {'conf': 0.45, 'type': 'method1'}),
         ('geneA', 'geneD', {'conf': 0.35, 'type': 'method1'})]

With MultiGraph() :

In [4]: MG= nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr=['conf','type'], 
                             create_using=nx.MultiGraph())

This:

TypeError                                 Traceback (most recent call last)
<ipython-input-49-d2c7b8312ea7> in <module>()
----> 1 MG= nx.from_pandas_dataframe(df, 'gene1', 'gene2', ['conf','type'], create_using=nx.MultiGraph())

/usr/lib/python2.7/site-packages/networkx-1.10-py2.7.egg/networkx/convert_matrix.pyc in from_pandas_dataframe(df, source, target, edge_attr, create_using)
    209         # Iteration on values returns the rows as Numpy arrays
    210         for row in df.values:
--> 211             g.add_edge(row[src_i], row[tar_i], {i:row[j] for i, j in edge_i})
    212 
    213     # If no column names are given, then just return the edges.

/usr/lib/python2.7/site-packages/networkx-1.10-py2.7.egg/networkx/classes/multigraph.pyc in add_edge(self, u, v, key, attr_dict, **attr)
    340             datadict.update(attr_dict)
    341             keydict = self.edge_key_dict_factory()
--> 342             keydict[key] = datadict
    343             self.adj[u][v] = keydict
    344             self.adj[v][u] = keydict

TypeError: unhashable type: 'dict'

Question How do I instantiate a MultiGraph() from a pandas dataframe?

Answer 1

Networkx < 2.0:
It's was a bug, I opened an issue on GitHub, once I made the suggested edit :

It changed line 211 of convert_matrix.py to to read:

g.add_edge(row[src_i], row[tar_i], attr_dict={i:row[j] for i, j in edge_i})

Results from that change: (which have since been incorporated)

MG= nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr=['conf','type'], 
                                 create_using=nx.MultiGraph())

MG.edges(data=True)
[('geneA', 'geneB', {'conf': 0.05, 'type': 'method1'}),
         ('geneA', 'geneB', {'conf': 0.45, 'type': 'method2'}),
         ('geneA', 'geneC', {'conf': 0.45, 'type': 'method1'}),
         ('geneA', 'geneD', {'conf': 0.35, 'type': 'method1'})]

Networkx >= 2.0:
In DataFrames with this format (edge list), use from_pandas_edgelist

MG= nx.from_pandas_edgelist(df, 'gene1', 'gene2', edge_attr=['conf','type'], 
                             create_using=nx.MultiGraph())

MG.edges(data=True)
MultiEdgeDataView([('geneA', 'geneB', {'conf': 0.05, 'type': 'method1'}),
                   ('geneA', 'geneB', {'conf': 0.45, 'type': 'method2'}),
                   ('geneA', 'geneC', {'conf': 0.45, 'type': 'method1'}), 
                   ('geneA', 'geneD', {'conf': 0.35, 'type': 'method1'})])

Answer 2

That's a nice question. I tried to reproduce your problem building your MultiGraph() in a different way, using only three/four columns with:

MG = nx.MultiGraph()

MG.add_weighted_edges_from([tuple(d) for d in df[['gene1','gene2','conf']].values])

this correctly returns as MG.edges(data=True) :

[('geneA', 'geneB', {'weight': 0.05}), ('geneA', 'geneB', {'weight': 0.45}), ('geneA', 'geneC', {'weight': 0.45}), ('geneA', 'geneD', {'weight': 0.35})]

I tried also with your from_pandas_dataframe method using only three columns but it doesn't work:

MG = nx.from_pandas_dataframe(df, 'gene1', 'gene2', edge_attr='conf', create_using=nx.MultiGraph())

this returns the same error you encountered. I don't know if it is a bug or that method doesn't support more than one weight type for MultiGraph() . In the meantime you can use the above workaround to build your MultiGraph, at least with only one weight type. Hope that helps.