集團通過另一列與蟒蛇

Question

一列與和內容我有一個數據幀merged_df_energy：

+------------------------+------------------------+------------------------+--------------+ 
| ACT_TIME_AERATEUR_1_F1 | ACT_TIME_AERATEUR_1_F3 | ACT_TIME_AERATEUR_1_F5 | class_energy | 
+------------------------+------------------------+------------------------+--------------+ 
| 63.333333    | 63.333333    | 63.333333    | low   | 
| 0      | 0      | 0      | high   | 
| 45.67     | 0      | 55.94     | high   | 
| 0      | 0      | 23.99     | low   | 
| 0      | 20      | 23.99     | medium  | 
+------------------------+------------------------+------------------------+--------------+ 

我想爲每一個ACT_TIME_AERATEUR_1_Fx（ACT_TIME_AERATEUR_1_F1，ACT_TIME_AERATEUR_1_F3和ACT_TIME_AERATEUR_1_F5）一個數據幀至極包含這些列：class_energy和sum_time

例如，對於對應於ACT_TIME_AERATEUR_1_F1數據幀：

+-----------------+-----------+ 
| class_energy | sum_time | 
+-----------------+-----------+ 
| low    | 63.333333 | 
| medium   | 0   | 
| high   | 45.67  | 
+-----------------+-----------+ 

我做的事情我應該這樣使用組：

data.groupby(by=['class_energy'])['sum_time'].sum() 

任何主意，幫幫我好嗎？

Answer 1

您可以添加所有列[]用於聚集：

print (df.groupby(by=['class_energy'])['ACT_TIME_AERATEUR_1_F1', 'ACT_TIME_AERATEUR_1_F3','ACT_TIME_AERATEUR_1_F5'].sum()) 
       ACT_TIME_AERATEUR_1_F1 ACT_TIME_AERATEUR_1_F3 \ 
class_energy             
high      45.670000    0.000000 
low      63.333333    63.333333 
medium      0.000000    20.000000 

       ACT_TIME_AERATEUR_1_F5 
class_energy       
high      55.940000 
low      87.323333 
medium      23.990000 

您可以使用還參數as_index=False：

print (df.groupby(by=['class_energy'], as_index=False)['ACT_TIME_AERATEUR_1_F1', 'ACT_TIME_AERATEUR_1_F3','ACT_TIME_AERATEUR_1_F5'].sum()) 
    class_energy ACT_TIME_AERATEUR_1_F1 ACT_TIME_AERATEUR_1_F3 \ 
0   high    45.670000    0.000000 
1   low    63.333333    63.333333 
2  medium    0.000000    20.000000 

    ACT_TIME_AERATEUR_1_F5 
0    55.940000 
1    87.323333 
2    23.990000 

如果需要骨料僅第一3列：

print (df.groupby(by=['class_energy'], as_index=False)[df.columns[:3]].sum()) 
    class_energy ACT_TIME_AERATEUR_1_F1 ACT_TIME_AERATEUR_1_F3 \ 
0   high    45.670000    0.000000 
1   low    63.333333    63.333333 
2  medium    0.000000    20.000000 

    ACT_TIME_AERATEUR_1_F5 
0    55.940000 
1    87.323333 
2    23.990000 

...或沒有最後一列的所有列：

print (df.groupby(by=['class_energy'], as_index=False)[df.columns[:-1]].sum()) 
    class_energy ACT_TIME_AERATEUR_1_F1 ACT_TIME_AERATEUR_1_F3 \ 
0   high    45.670000    0.000000 
1   low    63.333333    63.333333 
2  medium    0.000000    20.000000 

    ACT_TIME_AERATEUR_1_F5 
0    55.940000 
1    87.323333 
2    23.990000