“K-means”聚类分析

Question

我想要获取平均值、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]))我问这个是因为获得的值（例如年龄和BMI的平均值以及有氧运动计数== 0）与Statistica中获得的值不同（照片显示了程序Statistica结果的结果）下面是BMI的结果（ Python计算）24.46858773626099624.04785593330728230.54886546867411631.9841046300499332.89129084635681166.5735714285714641.9784573748308524.16813400017246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

以下内容将在一行中完成您想要的操作：

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