networkx_relationships.py

import pandas as pd
import networkx as nx
import matplotlib.pyplot as plt

# Create a sample dataframe
df = pd.DataFrame({
    'ID': [1, 2, 3, 4],
    'Col1': ['apple', 'orange', 'banana', 'pear'],
    'Col2': [['apple', 'pear'], ['banana'], ['apple', 'orange'], ['banana', 'pear']]
})

# Create a dictionary to store the connections
connections = {}

# Loop through the rows of the dataframe
for i, row in df.iterrows():
    # Loop through the values in the 'Col2' column
    for value in row['Col2']:
        # Check if any of the values match the 'Col1' column
        if value in list(df['Col1']):
            # Get the indices of the matching rows
            indices = df.index[df['Col1'] == value].tolist()
            # Add the connections to the dictionary
            if i not in connections:
                connections[i] = set()
            connections[i].update(indices)

# Create a directed graph
G = nx.DiGraph()

# Add nodes to the graph
for i in range(len(df)):
    G.add_node(i)

# Add edges to the graph based on the connections
for key, values in connections.items():
    for value in values:
        G.add_edge(key, value)

# Plot the graph
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos, with_labels=True)
plt.show()