pandas 使用python对另一列的列和总内容进行分组
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Group by of a Column and Sum Contents of another column with python
提问by Poisson
I have a dataframe merged_df_energy:
我有一个数据框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 |
+------------------------+------------------------+------------------------+--------------+
I would like to create for each ACT_TIME_AERATEUR_1_Fx(ACT_TIME_AERATEUR_1_F1, ACT_TIME_AERATEUR_1_F3and ACT_TIME_AERATEUR_1_F5) a dataframe wich contains these columns : class_energyand sum_time
我想为每个ACT_TIME_AERATEUR_1_Fx( ACT_TIME_AERATEUR_1_F1,ACT_TIME_AERATEUR_1_F3和ACT_TIME_AERATEUR_1_F5)创建一个包含这些列的数据框：class_energy和sum_time
For example for the dataframe corresponding to ACT_TIME_AERATEUR_1_F1:
例如对于对应于的数据框ACT_TIME_AERATEUR_1_F1：
+-----------------+-----------+
| class_energy | sum_time |
+-----------------+-----------+
| low | 63.333333 |
| medium | 0 |
| high | 45.67 |
+-----------------+-----------+
I thing to do I should use the group by like this:
我要做的事情我应该像这样使用该组：
data.groupby(by=['class_energy'])['sum_time'].sum()
Any idea to help me please?
有什么想法可以帮助我吗？
采纳答案by jezrael
You can add all columns to []for aggregating:
您可以将所有列添加到[]聚合：
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
You can use also parameter as_index=False:
您还可以使用参数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
If need aggregate only first 3columns:
如果只需要聚合第一3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
...or all columns without last:
...或没有最后一个的所有列：
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
