网络中错误的属性分配导致的 KeyError？

Question

我的数据集格式不正确，因为它包含以下列

Source   Target  Label_Source    Label_Target
    E   N   0.0 0.0
    A   B   1.0 1.0
    A   C   1.0 0.0
    A   D   1.0 0.0
    A   N   1.0 0.0
    S   G   0.0 0.0
    S   L   0.0 1.0
    S   C   0.0 0.0

Label_Source 和 Label_Target 是节点属性 Label_Source 是源属性，而 Label_Target 是目标属性。尝试复制以下项目：https://www.fatalerrors.org/a/python-networkx-learning-notes.html, I have encountered some errors, including a KeyError due to Label_Source. As explained in this answer: ，问题似乎是由 edge/node 属性中的错误分配引起的，因为代码正在读取 Label_Source 作为边的属性。正如我所说，我想复制该项目，因此任何可以使其成为可能的格式都是可以接受的。但是，我真的很感激有人可以解释（不仅是展示）如何解决这个问题，因为我不清楚是什么驱动了它。我到目前为止所做的如下所示：

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

G = nx.from_pandas_edgelist(filtered, 'Source', 'Target',  edge_attr=True)
df_pos = nx.spring_layout(G,k = 0.3) 

nx.draw_networkx(G, df_pos)
plt.show()

node_color = [
    '#1f78b4' if G.nodes[v]["Label_Source"] == 0 # actually this assignment should just Label and it should include also Target, so the whole list of nodes and their labels. A way to address this would be to select all distinct nodes in the network and their labels
    else '#33a02c' for v in G]

# Iterate through all edges
for v, w in G.edges:
    if G.nodes[v]["Label_Source"] == G.nodes[w]["Label_Source"]: # this should refer to all the Labels 
        G.edges[v, w]["internal"] = True
    else:
        G.edges[v, w]["internal"] = False

如果您能帮助我了解如何解决问题并复制代码，那就太好了。我猜错误还在于尝试遍历字符串而不是索引。

Answer 1

创建图表后：

G = nx.from_pandas_edgelist(filtered, 'Source', 'Target',  edge_attr=True)
df_pos = nx.spring_layout(G,k = 0.3)

您具有以下属性：

# For edges:
print(G.edges(data=True))
[('E', 'N', {'Label_Source': 0.0, 'Label_Target': 0.0}),
 ('N', 'A', {'Label_Source': 1.0, 'Label_Target': 0.0}),  # Problem here
 ('A', 'B', {'Label_Source': 1.0, 'Label_Target': 1.0}),
 ('A', 'C', {'Label_Source': 1.0, 'Label_Target': 0.0}),
 ('A', 'D', {'Label_Source': 1.0, 'Label_Target': 0.0}),
 ('C', 'S', {'Label_Source': 0.0, 'Label_Target': 0.0}),
 ('S', 'G', {'Label_Source': 0.0, 'Label_Target': 0.0}),
 ('S', 'L', {'Label_Source': 0.0, 'Label_Target': 1.0})]

# For nodes:
print(G.nodes(data=True))
[('E', {}), ('N', {}), ('A', {}), ('B', {}),
 ('C', {}), ('D', {}), ('S', {}), ('G', {}), ('L', {})]

如您所见，节点没有属性。您必须将 Label_xxx 值从边属性复制到右节点：

# Don't use it, check update below
for source, target, attribs in G.edges(data=True):
    G.nodes[source]['Label'] = int(attribs['Label_Source'])
    G.nodes[target]['Label'] = int(attribs['Label_Target'])

print(G.nodes(data=True))
[('E', {'Label': 0}), ('N', {'Label': 1}), ('A', {'Label': 1}),
 ('B', {'Label': 1}), ('C', {'Label': 0}), ('D', {'Label': 0}),
 ('S', {'Label': 0}), ('G', {'Label': 0}), ('L', {'Label': 1})]

现在您可以为图形的每个节点设置颜色：

node_color = ['#1f78b4' if v == 0 else '#33a02c'
              for v in nx.get_node_attributes(G, 'Label').values()]

print(node_color)
['#1f78b4', '#33a02c', '#33a02c', '#33a02c',
 '#1f78b4', '#1f78b4', '#1f78b4', '#1f78b4', '#33a02c']

最后一步：

nx.draw_networkx(G, df_pos, label=True, node_color=node_color)
plt.show()

更新

I think there is some problem with the code for assigning the color to nodes. Some nodes have a wrong color (e.g., they should be green and they are blue).

问题出在存储为 ('N', 'A') -> (1, 0) 的边 ('A', 'N') -> (1, 0) 上，因为你的图形没有方向，所以边是 ('A', 'N') 还是 [=20 并不重要=].如果这对您的问题有意义，您可以通过使用选项 create_using=nx.DiGraph 创建图形来解决此问题。

另一种解决方案是创建 Label 属性，而不是从边缘属性而是从你的数据框创建，就像我的建议的那样：

for _, sr in df.iterrows():
    G.nodes[sr['Source']]['Label'] = int(sr['Label_Source'])
    G.nodes[sr['Target']]['Label'] = int(sr['Label_Target'])

print(G.nodes(data=True))
[('E', {'Label': 0}), ('N', {'Label': 0}), ('A', {'Label': 1}),
 ('B', {'Label': 1}), ('C', {'Label': 0}), ('D', {'Label': 0}),
 ('S', {'Label': 0}), ('G', {'Label': 0}), ('L', {'Label': 1})]

现在，每个节点都有正确的 Label 属性：

网络中错误的属性分配导致的 KeyError？

KeyError caused by a wrong attribute assignment within the network?

python

networkx

pandas