How can I get branch of a networkx graph from pandas dataframe in Python in the form of a new pandas-CodePudding

I have a pandas dataframe df which looks as follows:

From    To
0   Node1   Node2
1   Node1   Node3
2   Node2   Node4
3   Node2   Node5
4   Node3   Node6
5   Node3   Node7
6   Node4   Node8
7   Node5   Node9
8   Node6   Node10
9   Node7   Node11

df.to_dict() is:

{'From': {0: 'Node1',
  1: 'Node1',
  2: 'Node2',
  3: 'Node2',
  4: 'Node3',
  5: 'Node3',
  6: 'Node4',
  7: 'Node5',
  8: 'Node6',
  9: 'Node7'},
 'To': {0: 'Node2',
  1: 'Node3',
  2: 'Node4',
  3: 'Node5',
  4: 'Node6',
  5: 'Node7',
  6: 'Node8',
  7: 'Node9',
  8: 'Node10',
  9: 'Node11'}}

I have plotted this pandas dataframe as a network graph using networkx package which looks as follows:

I want to get the unique scenarios/branches from this network graph in the form of a new pandas dataframe as follows:

  A B   C   D
0   Node1   Node2   Node4   Node8
1   Node1   Node2   Node5   Node9
2   Node1   Node3   Node6   Node10
3   Node1   Node3   Node7   Node11

How is it possible to get this?

CodePudding user response：

You can iterate graph like DFS then save path on each iterate and return path and convert to DataFrame like below:

import pandas as pd

df = pd.DataFrame({
          'From':['Node1','Node1', 'Node2', 'Node2', 'Node3', 'Node3', 'Node4', 'Node5', 'Node6', 'Node7'],
          'TO'  :['Node2','Node3', 'Node4', 'Node5', 'Node6', 'Node7', 'Node8', 'Node9', 'Node10', 'Node11']
        })

fnl_result = []
def svPath(path, node, df, lst_vst, fnl_result):
    for val in df.values:
        if val[0] == node:
            path.append(val[1])
            svPath(path, val[1], df, lst_vst, fnl_result)
    
    if not path[-1] in lst_vst:
        fnl_result.append([p for p in path])
    for p in path: lst_vst.add(p)
    path.pop()
    return
    
lst_vst = set()
svPath(['Node1'],'Node1', df, lst_vst, fnl_result)
dfOut = pd.DataFrame(fnl_result, columns=['A','B','C','D'])

Output:

>>> dfOut
        A       B       C       D
0   Node1   Node2   Node4   Node8
1   Node1   Node2   Node5   Node9
2   Node1   Node3   Node6   Node10
3   Node1   Node3   Node7   Node11