问如何在NetworkX中的其余节点上对前20个节点进行着色

EN

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

df = pd.DataFrame({'ID': list(string.ascii_uppercase),
                   'PageRank': np.random.randint(10, 100, len(string.ascii_uppercase))})

top_5_lst = df.sort_values('PageRank')['ID'].head(5).tolist()
not_top_5_lst = df.loc[~df['ID'].isin(top_5_lst), 'ID'].tolist()

edges = pd.DataFrame({'from': np.random.choice(list(string.ascii_uppercase), 1000),
                      'to': np.random.choice(list(string.ascii_uppercase), 1000)})

G = nx.from_pandas_edgelist(edges, source='from', target='to')

# Compute positions
pos = nx.spring_layout(G)

# Draw nodes not in top5
pc1 = nx.draw_networkx_nodes(G, pos, nodelist=not_top_5_lst,
                             node_color='gray', node_size=10)

# Draw top5 nodes
pc2 = nx.draw_networkx_nodes(G, pos, nodelist=top_5_lst, 
                             node_color='#00D992', node_size=20)
pc2.zorder = 3  # set z-order to 3 (2 by default for gray nodes)

# Draw edges
lc = nx.draw_networkx_edges(G, pos, width=0.2)

plt.show()

import pandas as pd
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
import plotly.graph_objects as go
import string

df = pd.DataFrame({'ID': list(string.ascii_uppercase),
                   'PageRank': np.random.randint(10, 100, len(string.ascii_uppercase))})

top_5_lst = df.sort_values('PageRank')['ID'].head(5).tolist()
not_top_5_lst = df.loc[~df['ID'].isin(top_5_lst), 'ID'].tolist()

edges = pd.DataFrame({'from': np.random.choice(list(string.ascii_uppercase), 1000),
                      'to': np.random.choice(list(string.ascii_uppercase), 1000)})

G = nx.from_pandas_edgelist(edges, source='from', target='to')
pos = nx.spring_layout(G)

rank_dict = dict(zip(df.ID, df.PageRank))
for entry in rank_dict:
    rank_dict[entry] = {'Page Rank': rank_dict[entry]}
    
nx.set_node_attributes(G, rank_dict)

edge_x = []
edge_y = []
for edge in G.edges():
    x0, y0 = pos[edge[0]]
    x1, y1 = pos[edge[1]]
    edge_x.append(x0)
    edge_x.append(x1)
    edge_x.append(None)
    edge_y.append(y0)
    edge_y.append(y1)
    edge_y.append(None)

edge_trace = go.Scatter(
    x=edge_x, y=edge_y,
    line=dict(width=0.5, color='#888'),
    hoverinfo='none',
    mode='lines')

# Not Top 5 Nodes
g1_node_x = []
g1_node_y = []
g1_texts = []
# Top 5 Nodes
g2_node_x = []
g2_node_y = []
g2_texts = []
for node in G.nodes():
    x, y = pos[node]
    if node in not_top_5_lst:
        g1_node_x.append(x)
        g1_node_y.append(y)
        g1_texts.append('Page Rank: '+str(G.nodes[node]['Page Rank']))
    else:
        g2_node_x.append(x)
        g2_node_y.append(y)
        g2_texts.append('Page Rank: '+str(G.nodes[node]['Page Rank']))

node_trace = go.Scatter(
    x=g1_node_x, y=g1_node_y,
    mode='markers',
    hoverinfo='text',
    marker=dict(
        color='grey',
        size=10,
        line_width=2))

node_trace2 = go.Scatter(
    x=g2_node_x, y=g2_node_y,
    mode='markers',
    hoverinfo='text',
    marker=dict(
        color='green',
        size=20,
        line_width=2))

node_trace.text = g1_texts
node_trace2.text = g2_texts

fig = go.Figure(edge_trace)
fig = fig.add_trace(node_trace)
fig = fig.add_trace(node_trace2)

fig = fig.update_layout(titlefont_size=16,
                showlegend=False,
                hovermode='closest',
                margin=dict(b=20,l=5,r=5,t=40),
                annotations=[ dict(
                    text="",
                    showarrow=False,
                    xref="paper", yref="paper",
                    x=0.005, y=-0.002 ) ],
                xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
                yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)

fig.show()