Question

我有以下数据框

np.random.seed(0)
header = [np.array(['location','location','location','location2','location2','location2']), 
np.array(['S1','S2','S3','S1','S2','S3'])] 
df = pd.DataFrame(np.random.randn(5, 6), columns = header ) 
df

   location                     location2                    
         S1        S2        S3        S1        S2        S3
0  1.764052  0.400157  0.978738  2.240893  1.867558 -0.977278
1  0.950088 -0.151357 -0.103219  0.410599  0.144044  1.454274
2  0.761038  0.121675  0.443863  0.333674  1.494079 -0.205158
3  0.313068 -0.854096 -2.552990  0.653619  0.864436 -0.742165
4  2.269755 -1.454366  0.045759 -0.187184  1.532779  1.469359

我要执行以下计算

['location2']['s1'] * 100 if ['location2']['s2] >= 0

以下查询无法解决

df['location2']['s1'] = np.where((df["location2"]['S2'] >= 0), df["location2"]['S1'] * 100, df["location2"]['S1'])
df

Answer 1

使用loc，为MultiIndex键指定元组：

df.loc[df.loc[:, ('location2', 'S2')] >=0, ('location', 'S1')] *= 100
df

     location                     location2                    
           S1        S2        S3        S1        S2        S3
0  176.405235  0.400157  0.978738  2.240893  1.867558 -0.977278
1   95.008842 -0.151357 -0.103219  0.410599  0.144044  1.454274
2   76.103773  0.121675  0.443863  0.333674  1.494079 -0.205158
3   31.306770 -0.854096 -2.552990  0.653619  0.864436 -0.742165
4  226.975462 -1.454366  0.045759 -0.187184  1.532779  1.469359

以多头熊猫数据框为条件

1 个答案: