Coloring specific nodes based on a condition within a network

Question

I have a dataset with a list of accounts sorted by a variable called time

Account Time
13124    1
215732   2 
76239    3
76054    4
975235   

I have also a graph where a full list of accounts is considered:

Account1 Account2
13124    215732
215732   418954
5130953  214182
760524   5398723
975235   13124

The graph is built using networkx:

G = nx.from_pandas_edgelist(df, 'Account1', 'Account2')

I would like to visualize nodes that are in the top list (Account Time) within the network, by highlighting the node based on the time. This could be achieved as follows:

• either to plot multiple plots showing different time
• or to plot the graph just coloring the nodes based on the time of opening. For those nodes that are not in the graph or that do not have a time assigned (e.g., 975235) , it would be nice to assign a default color to distinguish them.

I would like to understand better how to select (colorinig) only the nodes on the top list within the network.

Answer 1

A way to do this is to create and pair a colormap with the time associated to your node and then to use the node_color argument of the nx.draw function to color your nodes. You can additionally set up a legend for your nodes by creating empty placeholder scatter plots. See code below for more details:

import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
import pandas as pd
from matplotlib import cm

df=pd.read_fwf('graph.txt') #(Account1, Account2) dataframe
df_time=pd.read_fwf('timestamp.txt') #(Account, Time) dataframe

G = nx.from_pandas_edgelist(df,'Account1', 'Account2')

#Setting up colormap
N_colors=4
cm_dis=np.linspace(0, 1,N_colors) 
colors = [ cm.viridis(x) for x in cm_dis]
color_edges=[]

#Pairing each node with the a color associated with time of the node
for node in G:
    temp=df_time.loc[df_time['Account']==node] #Finding time of node 

    if temp.empty or temp['Time'].isnull().values.any(): #Checking if there is atime associated to node

      color='tab:orange'
      if color not in color_edges: #Setting up legend
        plt.scatter([],[],color='tab:orange',label='No time')
      color_edges.append(color) 
      
    else:

      color=colors[int(temp['Time'])]

      if color not in color_edges:
         plt.scatter([],[],color=color, label='Time:'+str(int(temp['Time'])))
      color_edges.append(color)

#Drawing graph and legend
nx.draw(G,with_labels=True,node_color=color_edges)
plt.legend()
plt.show()

And the output of this code gives: