Assign Edge Weights To A Networkx Graph Using Pandas Dataframe

Answer :

Let's try:

import pandas as pd import numpy as np import networkx as nx import matplotlib.pyplot as plt  df = pd.DataFrame({'number':['123','234','345'],'contactnumber':['234','345','123'],'callduration':[1,2,4]})  df  G = nx.from_pandas_edgelist(df,'number','contactnumber', edge_attr='callduration') durations = [i['callduration'] for i in dict(G.edges).values()] labels = [i for i in dict(G.nodes).keys()] labels = {i:i for i in dict(G.nodes).keys()}  fig, ax = plt.subplots(figsize=(12,5)) pos = nx.spring_layout(G) nx.draw_networkx_nodes(G, pos, ax = ax, labels=True) nx.draw_networkx_edges(G, pos, width=durations, ax=ax) _ = nx.draw_networkx_labels(G, pos, labels, ax=ax) 

Output:

Do not agree with what has been said. In the calcul of different metrics that takes into account the weight of each edges like the pagerank or the betweeness centrality your weight would not be taking into account if is store as an edge attributes. Use graph.

Add_edges(source, target, weight, *attrs)