[FIXED] Iterate through a pandas dataframe to get a specific output

Issue

I have a dataframe which I want to iterate to get a specific result.

Portion of the dataframe df (the name of the columns are guid1 and guid2) : DataSet

 guid1  guid2
 A865   OR4
 A875   OR4
 OR4    JN1397
 JN1400 JN1401
 JN1402 DEL131KS-
 Unset  AND1

Interpretation : Both A865 and A875 are connected to OR4 and OR4 is then connected to JN1397 (it's a representation of a logical diagram). My goal here is to iterate through the dataframe (to verify if there is any connections) to get a string result (as follows) in which I interpret the different connections:

A865, A875, OR4, JN1397

I already posted this question and it has been closed for lack of clarity, I really hope it's clear enough now because I really need some help here..

Solution

You could use networkx to handle your graph.

This is how it looks (showing as directed graph, but using an undirected graph later):

You can create the graph using:

import networkx as nx

G = nx.from_pandas_edgelist(df, source='guid1', target='guid2')

Then keep the subgraph that contains your initial node:

start = df['guid1'].iloc[0] # 'A865'

keep = nx.node_connected_component(G, start)
# {'A865', 'A875', 'JN1397', 'OR4'}

If you really want the pseudo-path in original order of the DataFrame:

key = {v: k for k,v in enumerate(df['guid1'].drop_duplicates())}
# {'A865': 0, 'A875': 1, 'OR4': 2, 'JN1400': 3, 'JN1402': 4, 'Unset': 5}

path = ' -> '.join(sorted(keep, key=lambda x: key.get(x, float('inf'))))

output: 'A865 -> A875 -> OR4 -> JN1397'

Answered By - mozway