Python 基于另一列创建true或false列'；s值

对于

Prediction

列的最小值，我想在

is\u best

列中返回

True

，其余的返回

False

。所以我想要的是：

import numpy as np
import pandas as pd

df_summary_sklearn = pd.DataFrame(columns=['Method','Prediction' , 'is_best'])
df_summary_sklearn['Method'] = ['1-KNN', '5-KNN', '10-KNN']
df_summary_sklearn['Prediction'] = [1, 2, 3] # example data
df_summary_sklearn['is_best'] = np.where((df_summary_sklearn['Prediction']).min(), True, False)

print(df_summary_sklearn)

但我现在得到的是：

   Method  Prediction  is_best
0   1-KNN           1     True
1   5-KNN           2    False
2  10-KNN           3    False

---

如何正确创建此列？

由于您没有最低限度的工作示例，因此我为

预测

列采用了人为值

   Method  Prediction  is_best
0   1-KNN           1     True
1   5-KNN           2     True
2  10-KNN           3     True

这将提供以下输出

df_summary_sklearn = pd.DataFrame(columns=['Method','Prediction' , 'is_best'])
df_summary_sklearn['Method'] = ['1-KNN', '5-KNN', '10-KNN']
df_summary_sklearn['Prediction'] = [1, 2, 3]

# This returns a boolean array where the condition holds True.
df_summary_sklearn['Prediction'] == df_summary_sklearn['Prediction'].min()

# Set the is_best column to the result of the previous statement.
df_summary_sklearn['is_best'] = df_summary_sklearn['Prediction'] == df_summary_sklearn['Prediction'].min()

您可以用自己的值替换上例中的

[1,2,3]

，比如问题中的

[1,5,10\u fold]

>>> df_summary_sklearn
   Method  Prediction  is_best
0   1-KNN           1     True
1   5-KNN           2    False
2  10-KNN           3    False