Adding weights to edges in networkx automatically depending of the number of connections form pandas dataframe

user_10232932 0
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I am trying to create out of a pandas dataframe a directed graph right now with networkx, so far i can use:

nx.from_pandas_edgelist(df, 'Activity', 'Activity followed', create_using=nx.DiGraph())

which shows me all the nodes and edges from Activity --> Activity followed.

In my dataframe there is sometimes the same activity followed by the same activity and i want to count this number in form of weights for the edges so far example this is my dataframe:

Index Activity Activityfollowed
0     Lunch    Dinner
1     Lunch    Dinner
2     Breakfast Lunch

should have the Edges:

Lunch --> Dinner (weight 2)

Breakfast --> Lunch (weight 1)

Is there any way to do it?

pandas networkx python
1 Answers

You could try adding the weight attribute as a column, using groupby.transform, then pass the edge_attr argument to the from_pandas_edgelist method:

df['weight'] = df.groupby(['Activity', 'Activityfollowed'])['Activity'].transform('size')

G = nx.from_pandas_edgelist(df, 'Activity', 'Activityfollowed',
                            create_using=nx.DiGraph(), edge_attr='weight')

Confirm that it's worked using:

G.edges(data=True)

[out]

OutEdgeDataView([('Lunch', 'Dinner', {'weight': 2}), ('Breakfast', 'Lunch', {'weight': 1})])
user_102015800
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