如何按组(属性)计算来自python networkx的索引

Question

我有一个包含'from'、'to'、'date'列的表格。

我想通过"日期"获取任何 networkx 索引(例如度、边缘、节点(。

实际上有很多日期，不可能手动计算索引。

有没有办法根据"日期"计算度数((或边缘((？

感谢您的阅读。

示例代码如下。

df = pd.DataFrame({'from' : ['1','2','1','3'], 
'to' : ['3','3','2','2'], 
'date' : ['20200501','20200501','20200502','20200502']})
G = nx.from_pandas_edgelist(df, source = 'from', target = 'to',
create_using=nx.DiGraph(), edge_attr = 'date')
# It's easy to calculate any index such as 'degree','node','edge'.
G.nodes()
G.degree()
G.edge()
# However, it's not easy to calculate an index based on 'date' column.

Answer 1

要检查那些包含特定日期作为属性的边，请遍历边，设置data=True并保持匹配的边。然后使用Graph.edge_subgraph生成由这些边诱导的新图：

edges_from_date_x = [] 
some_date = '20200502'
for *edge, attr in G.edges(data=True):
if attr['date'] == some_date:
edges_from_date_x.append((*edge,))
print(edges_from_date_x)
# [('1', '2'), ('3', '2')]

或者，如果您更喜欢列表组合，您可以按照@AKX的建议进行操作：

edges_from_date_x = [(*edge,) for *edge, attr in G.edges(data=True)
if attr['date'] == some_date]
# [('1', '2'), ('3', '2')]

现在生成诱导子图：

# induced subgraph
G_induced = G.edge_subgraph(edges_from_date_x)
# edgelist from the induced subgraph
G_induced.edges(data=True)
#OutEdgeDataView([('1', '2', {'date': '20200502'}), ('3', '2', {'date': '20200502'})])
# same with the nodes
G.nodes()
# NodeView(('1', '3', '2'))