“k-means”聚类分析

Question

我想要得到值​​，比如mean，min，max。标准开发对于使用k-means方法计算的每组集群。下面的代码是否正确？

    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]))

我之所以问这个问题，是因为获得的值(例如年龄和体重指数的平均值以及心脏计数的== 0)与统计中获得的值(照片显示程序Statistica results的结果)不同。下面是​​(Python计算)的结果。

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

感谢您的所有帮助和提示:)

Answer 1

下面的代码将在一行代码中完成您想要的操作：

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