CODEWITHSUNDEEP
pythongraphnetworkxgraphviz
winnie
winnie

Reputation: 135

Visualizing Network plot from the same value in dataframe

Suppose I have this dataframe df that contains 3794 rows x 2 columns, where column a-number represents nodes with directed edges to nodes in b-number:

      a_number         b_number
0   0123456789343   0123456789991
1   0123456789343   0123456789633
2   0123456789343   0123456789633
3   0123456789343   0123456789628
4   0123456789343   0123456789633
... ... ...
3789    0123456789697   0123456789916
3790    0123456789697   0123456789886
3791    0123456789697   0123456789572
3792    0123456789697   0123456789884
3793    0123456789697   0123456789125
3794 rows × 2 columns

Additional information:

len(df['a_number'].unique())
>>> 18

len(df['b_number'].unique())
>>>1145

I am trying to generate an image representation of the graph. Here's code to apply networkx:

import networkx as nx
G = nx.DiGraph()

for  i, (x, y) in df.iterrows():
    G.add_node(x)
    G.add_node(y)
    G.add_edge(x,y)
    
nx.draw(G, with_labels = True, font_size=14 , node_size=2000)

The thing is what if I want to visualizing the graphs only from the same value in the column a_number to the b_number column, for example:

The 1st graph

       a_number        b_number
0   0123456789343   0123456789991
1   0123456789343   0123456789633
2   0123456789343   0123456789633
3   0123456789343   0123456789628
4   0123456789343   0123456789633

The next graph

          a_number       b_number
3789    0123456789697   0123456789916
3790    0123456789697   0123456789886
3791    0123456789697   0123456789572
3792    0123456789697   0123456789884
3793    0123456789697   0123456789125

Please advise. What can I do on the code? thank you.

Upvotes: 0

Views: 73

Answers (1)

Niels Henkens
Niels Henkens

Reputation: 2696

You could iterate through all values of 'a_number':

import networkx as nx
import pandas as pd

a_values = df['a_number'].unique()

for a_value in a_values:
    df_temp = df[df['a_number'] == a_value]
   
    G = nx.DiGraph()
    
    for  i, (x, y) in df_temp.iterrows():
        G.add_node(x)
        G.add_node(y)
        G.add_edge(x,y)
    
    nx.draw(G, with_labels = True, font_size=14 , node_size=2000)
    --- save and close plot ---

Upvotes: 1

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