使用python3表示实体之间的关系

Question

我想使用 Python3 的 networkx 库来表示一系列数据，但我不知道如何解决这个问题。

基本上我在两个entities 之间有一个relation，它位于一个名为nations.csv 的csv 文件中。它看起来像这样：

China, Economicaid, Egypt
China, Economicaid, Indonesia
USSR, Economicaid, Cuba 
USSR, Economicaid, India
USSR, Economicaid, Poland
UK, Economicaid, India 
UK, Economicaid, Jordan
USA, Economicaid, Brazil

了解第一行是与第二行之间的第三行（实体 2）相关的实体之一：

我已经解析了 csv 文件，以便将每一行存储在字典中，如下所示：

d = {}
d['entity1'] = []
d['relation'] = []
d['entity2'] = []

dictReader = csv.DictReader(open('nations.csv', 'rt'), fieldnames = 
['entity1', 'relation', 'entity2'], delimiter = ',', quotechar = '"')

for row in dictReader:
    for key in row:
        d[key].append(row[key])

我设法做的是使用函数add_node() 绘制节点，如下例所示：

import csv
import networkx as nx
import matplotlib.pyplot as plt


d = {}
d['entity1'] = []
d['relation'] = []
d['entity2'] = []

dictReader = csv.DictReader(open('nations.csv', 'rt'), fieldnames = ['entity1', 'relation', 'entity2'], delimiter = ',', quotechar = '"')

for row in dictReader:
    for key in row:
        d[key].append(row[key])

print()

for i in range (1, len(d['entity1'])):
    r.append(d['entity1'][i])

for k in range (1, len(d['entity2'])):
    o.append(d['entity2'][k])


G=nx.Graph()

for j in range(len(r)):
    G.add_node(r[j])
    G.add_node(o[j])

nx.draw_networkx(G, with_labels = True, node_size = 500)

plt.show()

但是当我想表示节点之间的边时，问题就来了，因为它不仅是边本身，它还有自己的带有含义的标签。

Answer 1

基本上，标志with_labels 应该真正称为with_node_labels，因为它只触发节点标签的绘制。因此，您需要在绘制图形 (networkx.draw`) 后手动添加边缘标签 (networkx.draw_networkx_edge_labels)，并且您需要 1) 在同一轴上绘图，以及 2) 对两个绘图使用相同的图形布局。

import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
import csv

# load data
dictReader = csv.DictReader(open('nations.csv', 'rt'), fieldnames = ['entity1', 'relation', 'entity2'], delimiter = ',', quotechar = '"')

# create a more amenable data structure
edge_to_label = {(d['entity1'], d['entity2']) : d['relation'] for d in dictReader}

# create graph
G = nx.from_edgelist(edge_to_label.keys())

# precompute layout (default layout used here)
layout = nx.layout.fruchterman_reingold_layout(G)

# create figure so we plot the graph and labels on the same plot
fig, ax = plt.subplots(1,1)

# draw graph
nx.draw(G, pos=layout, ax=ax, with_labels=True)

# draw labels using the same, pre-computed graph layout
nx.draw_networkx_edge_labels(G, pos=layout, edge_labels=edge_to_label, ax=ax)

plt.show()