'K-means'聚类分析

Question

我想获取平均值，最小值，最大值等值。标准差对于使用 k-means 方法计算的每组簇。下面的代码正确吗？

    import pandas as pd
    from sklearn.cluster import KMeans

    dataset = pd.read_csv("C:/Users/../cardio_train_py.csv", sep=';')    
    clusterDB_1 = dataset[['Age','BMI','cardio']].copy()
    kmeans = KMeans(n_clusters=8).fit(clusterDB_1)
    
    X=[0,1,2,3,4,5,6,7]
    print('Age mean() for each cluster')
    for x in X:
        check = clusterDB_1[kmeans.labels_ == x]
        print(check['Age'].mean())
    print('BMI mean() for each cluster')
    for x in X:
        check = clusterDB_1[kmeans.labels_ == x]
        print(check['BMI'].mean())
    print('cardio == 0 count() for each cluster')
    
    for x in X:
        check = clusterDB_1[kmeans.labels_ == x]
        print(len(check[check['cardio'] == 1]))

我问是因为获得的值（例如年龄和 BMI 的平均值和有氧运动计数 == 0）与 Statistica 中获得的值不同（照片显示程序的结果 Statistica results ) 下面是BMI的结果（Python计算）

24.468587736260996
24.047855933307282
30.548865468674116
31.98410463004993
32.89129084635681
166.57357142857146
41.97845737483085
24.16813400017246

这是我的数据库 => https://www.easypaste.org/file/JcyGhA8Y/cardio.train.py.csv?lang=pl

感谢所有帮助和提示:)

Answer 1

以下将在一行中完成您想要的操作：

clusterDB_1.groupby(kmeans.labels_).mean()

'K-means'聚类分析

'K-means' cluster analysis

python

statistics

k-means