NetworkX节点按属性设置颜色不匹配问题求助

问题根源 #

颜色与属性不匹配的核心原因是节点顺序不一致：

• nx.draw渲染节点时，默认遵循g.nodes()的遍历顺序
• 你通过pd.DataFrame.from_dict(dict(G.nodes(data=True)), orient='index')生成的DataFrame，其行顺序不一定和g.nodes()的顺序完全一致，导致颜色列表和节点列表错位

修复方案 #

修改attri_to_color函数，让颜色列表的顺序严格对应g.nodes()的遍历顺序，避免依赖DataFrame的自动排序：

def attri_to_color(G, attri_name):
    replace_dict = {"A": "red", "B": 'blue', "C": 'green', "D": 'purple'}
    # 按g.nodes()的顺序逐个获取节点属性并映射颜色
    color = [replace_dict[G.nodes[node][attri_name]] for node in G.nodes()]
    return color

完整修正后的代码 #

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

path = "data/"

df = pd.read_excel(path + "example_data_for_test1.xlsx")
node_attri = pd.read_excel(path + "example_data_for_test2.xlsx")

edgelist = list(zip(df["source"], df["target"], df["weight"]))
node_attri = dict(zip(node_attri["city"], node_attri["type"]))

g = nx.DiGraph()
g.add_weighted_edges_from(edgelist, weight="weight")
nx.set_node_attributes(g, node_attri, "city_type")

# 修正后的颜色映射函数
def attri_to_color(G, attri_name):
    replace_dict = {"A": "red", "B": 'blue', "C": 'green', "D": 'purple'}
    color = [replace_dict[G.nodes[node][attri_name]] for node in G.nodes()]
    return color

def draw_network(g):
    fig = plt.figure(1, figsize=(40, 30))
    pos = nx.spring_layout(g, k=2.5, iterations=50)

    d = nx.degree(g)
    d = [(d[node] + 0.1) * 50 for node in g.nodes()]

    colors = attri_to_color(g, "city_type")

    nx.draw(
        g,
        pos=pos,
        node_size=d,
        node_color=colors,
        with_labels=True,
        edge_color="gainsboro",
        arrows=True,
        arrowsize=5,
        alpha=0.4,
    )
    plt.show()

draw_network(g)

额外优化提示 #

你也可以直接在绘图时生成颜色列表，省去单独的函数，让代码更简洁：

# 替换原colors = attri_to_color(...)这一行
replace_dict = {"A": "red", "B": 'blue', "C": 'green', "D": 'purple'}
colors = [replace_dict[g.nodes[node]['city_type']] for node in g.nodes()]

这样就能确保每个节点的颜色和其city_type属性严格对应，不会出现错位问题。

内容的提问来源于stack exchange，提问作者yy w