from_pandas_adjacency(df, create_using=None)
The Pandas DataFrame is interpreted as an adjacency matrix for the graph.
For directed graphs, explicitly mention create_using=nx.DiGraph, and entry i,j of df corresponds to an edge from i to j.
If :None:None:`df` has a single data type for each entry it will be converted to an appropriate Python data type.
If :None:None:`df` has a user-specified compound data type the names of the data fields will be used as attribute keys in the resulting NetworkX graph.
An adjacency matrix representation of a graph
Graph type to create. If graph instance, then cleared before populated.
Returns a graph from Pandas DataFrame.
Simple integer weights on edges:
>>> import pandas as pd
... pd.options.display.max_columns = 20
... df = pd.DataFrame([[1, 1], [2, 1]])
... df 0 1 0 1 1 1 2 1
>>> G = nx.from_pandas_adjacency(df)See :
... G.name = "Graph from pandas adjacency matrix"
... print(nx.info(G)) Graph named 'Graph from pandas adjacency matrix' with 2 nodes and 3 edges
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.convert_matrix.from_pandas_adjacency
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