包含DIC值的切片Pandas列

import pandas as pd
from sklearn.cluster import KMeans
from sklearn.metrics import pairwise_distances

# 创建一个示例DataFrame
data = {'A': [1, 2, 3, 4, 5],
        'B': [6, 7, 8, 9, 10],
        'C': [11, 12, 13, 14, 15]}
df = pd.DataFrame(data)

# 使用KMeans算法进行聚类
kmeans = KMeans(n_clusters=2)
kmeans.fit(df)

# 计算聚类结果的DIC值
distances = pairwise_distances(df)
labels = kmeans.labels_
intra_cluster_distances = distances[labels == labels[:, None]].max(axis=1)
inter_cluster_distances = distances[labels != labels[:, None]].min(axis=1)
dic_values = inter_cluster_distances / intra_cluster_distances
df['DIC'] = dic_values

# 打印包含DIC值的切片Pandas列
print(df['DIC'])