CODEWITHSUNDEEP
pythonpandasnetworkx
Math
Math

Reputation: 251

How to reduce dimension/size of edges?

I have the following dataset:

    Person1            Age       Person2         Wedding
0   Adam John          3        Yao Ming         Green
1   Mary Abbey         5       Adam Lebron       Green
2   Samuel Bradley     24      Mary Lane         Orange
3   Lucas Barney       12      Julie Lime        Yellow
4   Christopher Rice   0.9     Matt Red          Green

I would like to reduce the weight of size (for example dividing by 100 the original values). I am currently adding edges in the networks as follows:

G = nx.from_pandas_edgelist(df_test, source='Person1', target='Person2', edge_attr='Age')

pos=nx.spring_layout(G, k=0.30, iterations=20)
nx.draw_networkx_nodes(G, pos, node_size=900, nodelist=collist['value'], node_color=collist['Wedding'])
nx.draw_networkx_edges(G, pos, width = [i['Age'] for i in dict(G.edges).values()])

I have tried to create a new column as Age_n by taking Age column and dividing by 100, but actually it does not work (as the edges do not change their size/weight), when I replace Age_n in the code.

Upvotes: 0

Views: 74

Answers (1)

yatu
yatu

Reputation: 88236

You could just divide the Age by some factor at the same creation of the width list, like so:

G = nx.from_pandas_edgelist(df, source='Person1', target='Person2', edge_attr='Age')

plt.figure(figsize=(12,8))
pos=nx.spring_layout(G, k=0.30, iterations=20)
nx.draw_networkx_nodes(G, pos, node_size=500)
nx.draw_networkx_labels(G, pos)
nx.draw_networkx_edges(G, pos, width = [i['Age']/2 for i in dict(G.edges).values()])
plt.box(False)
plt.show()

enter image description here

Though assigning a new Age column as you're specifying does work too, since its doing the same as the above:

G = nx.from_pandas_edgelist(df.assign(Age=df.Age/2), source='Person1', 
                            target='Person2', edge_attr='Age')

Upvotes: 1

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