networkx and pyviz how to add color to nodes based on dimenison

Question

I'm using networkx and pyviz together. I'm trying to figure out how to change the color of the nodes in pyviz based an attribute in my data frame.

My dataframe looks like this:

I want to show the connections between user_one and user_two but color their nodes based on their license type.

Here is what I have thus far:

import pandas as pd
import networkx as nx
from pyvis.network import Network

df_dict = {'PROJECT': {0: 'Finance Project',  1: 'Finance Project',  2: 'Finance Project',  3: 'Finance Project',  4: 'Finance Project',  5: 'Finance Project',  6: 'Finance Project',  7: 'Finance Project',  8: 'Finance Project',  9: 'Finance Project',  10: 'Finance Project',  11: 'Finance Project',  12: 'HR Project',  13: 'Finance Project',  14: 'HR Project',  15: 'Finance Project'},
 'PLAN': {0: 'COMPANY',  1: 'COMPANY',  2: 'COMPANY',  3: 'COMPANY',  4: 'COMPANY',  5: 'COMPANY',  6: 'COMPANY',  7: 'COMPANY',  8: 'COMPANY',  9: 'COMPANY',  10: 'COMPANY',  11: 'COMPANY',  12: 'COMPANY',  13: 'COMPANY',  14: 'COMPANY',  15: 'COMPANY'},
 'USER_ONE': {0: 'Mike Jones',  1: 'Eminem',  2: 'Mike Jones',  3: 'Mike Jones',  4: 'Michael Jordan',  5: 'Eminem',  6: 'Michael Jordan',  7: 'Michael Jordan',  8: 'Mike Jones',  9: 'Kobe Bryant',  10: 'Eminem',  11: 'Elon Musk',  12: 'Bill Gates',  13: 'Elon Musk',  14: 'Mark Zuckerberg',  15: 'Elon Musk'},
 'USER_ONE_LICENSE': {0: 'FULL',  1: 'FULL',  2: 'FULL',  3: 'FULL',  4: 'FULL',  5: 'FULL',  6: 'FULL',  7: 'FULL',  8: 'FULL',  9: 'OCCASIONAL',  10: 'FULL',  11: 'FULL',  12: 'FULL',  13: 'FULL',  14: 'FULL',  15: 'FULL'},
 'USER_ONE_LICENSE_COLOR': {0: 'lightgreen',  1: 'lightgreen',  2: 'lightgreen',  3: 'lightgreen',  4: 'lightgreen',  5: 'lightgreen',  6: 'lightgreen',  7: 'lightgreen', 8: 'lightgreen',  9: 'gray',  10: 'lightgreen',  11: 'lightgreen',  12: 'lightgreen',  13: 'lightgreen',  14: 'lightgreen',  15: 'lightgreen'},
 'USER_ONE_DAYS_COLLAB': {0: 88,  1: 55,  2: 67,  3: 1,  4: 70,  5: 54,  6: 2,  7: 114,  8: 4,  9: 1,  10: 10,  11: 19,  12: 5,  13: 11,  14: 100,  15: 13},
  'USER_TWO': {0: 'Michael Jordan',  1: 'Mike Jones',  2: 'Eminem',  3: 'Kobe Bryant',  4: 'Eminem',  5: 'Michael Jordan',  6: 'Elon Musk',  7: 'Mike Jones',  8: 'Elon Musk',  9: 'Mike Jones',  10: 'Elon Musk',  11: 'Eminem',  12: 'Mark Zuckerberg',  13: 'Michael Jordan',  14: 'Bill Gates',  15: 'Mike Jones'},
 'USER_TWO_LICENSE': {0: 'FULL',  1: 'FULL',  2: 'FULL',  3: 'OCCASIONAL',  4: 'FULL',  5: 'FULL',  6: 'FULL',  7: 'FULL',  8: 'FULL',  9: 'FULL',  10: 'FULL',  11: 'FULL',  12: 'FULL',  13: 'FULL',  14: 'FULL',  15: 'FULL'},
 'USER_TWO_LICENSE_COLOR': {0: 'lightgreen',  1: 'lightgreen',  2: 'lightgreen',  3: 'gray',  4: 'lightgreen',  5: 'lightgreen',  6: 'lightgreen',  7: 'lightgreen',  8: 'lightgreen',  9: 'lightgreen',  10: 'lightgreen',  11: 'lightgreen',  12: 'lightgreen',  13: 'lightgreen',  14: 'lightgreen',  15: 'lightgreen'},
 'USER_TWO_DAYS_COLLAB': {0: 114,  1: 67,  2: 55,  3: 1,  4: 54,  5: 70,  6: 11,  7: 88,  8: 13,  9: 1,  10: 19,  11: 10,  12: 100,  13: 2,  14: 5,  15: 4}
 , 'TOTAL_COLLABS': {0: 202,  1: 122,  2: 122,  3: 2,  4: 124,  5: 124,  6: 13,  7: 202,  8: 17,  9: 2,  10: 29,  11: 29,  12: 105,  13: 13,  14: 105,  15: 17}}


df = pd.DataFrame(df_dict)

G = nx.from_pandas_edgelist(df
                           ,source='USER_ONE'
                           ,target='USER_TWO' 
                           )

net = Network(notebook=True)

net.from_nx(G)
net.show_buttons(filter_=True)
net.show('example4.html')

I'm trying to follow this as a template: Assign color to NetworkX node based on column name

#code from stackoverflow
colors = []
for node in G:
    if node in df["person"].values:
        colors.append("lightblue")
    else: colors.append("lightgreen")

#my attempt:
#get distinct users and respective colors based on license type
colors_df = df.groupby(by='USER_ONE')['USER_ONE_LICENSE_COLOR'].max().reset_index()

#get list of nodes in the right order
nodes_list_ordered = list(G.nodes)

#order color df so i can turn it into list to match nodes
colors_df['ORDER'] = pd.Categorical(colors_df.USER_ONE, categories = nodes_list_ordered, ordered = True)
colors_df.sort_values(by='ORDER', inplace=True)
colors = colors_df['USER_ONE_LICENSE_COLOR'].to_list()

Am I doing this right? I now have a list of colors in the right order, but how do I apply it to pyviz?

I did all this to realize that from_pandas_edgelist() does not a have 'node_color' argument.