Networkx Multigraph from_pandas_dataframe

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.

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'})])