python 读取txt文件关联规则 画出关联规则网状图

要画出关联规则的网状图，可以使用Python中的networkx和matplotlib库。

首先，需要读取txt文件中的关联规则。假设文件中每行都是一条规则，格式为“item1, item2, confidence”，可以使用以下代码读取文件：

with open('rules.txt', 'r') as f:
    rules = []
    for line in f:
        item1, item2, confidence = line.strip().split(',')
        rules.append((item1.strip(), item2.strip(), float(confidence.strip())))

接下来，需要创建一个无向图，并将每个项作为节点添加到图中：

import networkx as nx
import matplotlib.pyplot as plt

G = nx.Graph()

for rule in rules:
    G.add_node(rule[0])
    G.add_node(rule[1])

然后，将每条规则作为一条边添加到图中：

for rule in rules:
    G.add_edge(rule[0], rule[1], weight=rule[2])

最后，使用matplotlib库绘制图形：

pos = nx.spring_layout(G)
nx.draw(G, pos, with_labels=True, node_size=1000, font_size=20)
labels = nx.get_edge_attributes(G, 'weight')
nx.draw_networkx_edge_labels(G, pos, edge_labels=labels, font_size=20)
plt.show()

完整代码如下：

import networkx as nx
import matplotlib.pyplot as plt

with open('rules.txt', 'r') as f:
    rules = []
    for line in f:
        item1, item2, confidence = line.strip().split(',')
        rules.append((item1.strip(), item2.strip(), float(confidence.strip())))

G = nx.Graph()

for rule in rules:
    G.add_node(rule[0])
    G.add_node(rule[1])

for rule in rules:
    G.add_edge(rule[0], rule[1], weight=rule[2])

pos = nx.spring_layout(G)
nx.draw(G, pos, with_labels=True, node_size=1000, font_size=20)
labels = nx.get_edge_attributes(G, 'weight')
nx.draw_networkx_edge_labels(G, pos, edge_labels=labels, font_size=20)
plt.show()