Coloring specific nodes based on a condition within a network-CodePudding

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.

CodePudding user response：

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: