英文:
pandas groupby one column except if one other column has different entry
问题
我想要根据给定的列对数据框进行分组，但仅当另一列也相同时，并对另一列进行求和。给定这个示例：
test=pd.DataFrame({'A':['0','0','0','1'],'B':['AAA','AAA','BBB','CCC'],'C':[0.5,0.2,0.3,0.1]})
我想要对A进行分组，但只有当B不同时才进行分组。我想要的结果如下：
A B C0 0 AAA 0.71 0 BBB 0.32 1 CCC 0.1
到目前为止，我还没有找到任何方法来实现这个。
英文:
I have a dataframe that I would like to group by a given column, BUT only if one other column is also the same, while doing a sum on an other column. Given this example:
test=pd.DataFrame({'A':['0','0','0','1'],'B':['AAA','AAA','BBB','CCC'],'C':[0.5,0.2,0.3,0.1]})A B C0 0 AAA 0.51 0 AAA 0.22 0 BBB 0.33 1 CCC 0.1
I would like group for A only if B is different. I am targeting following dataframe:
A B C0 0 AAA 0.71 0 BBB 0.32 1 CCC 0.1
So far I did not find any way to do it
答案1
得分: 1
test=pd.DataFrame({'A':['0','0','0','1'],'B':['AAA','AAA','BBB','CCC'],'C':[0.5,0.2,0.3,0.1]})test.groupby(['A','B'])['C'].sum()A B0 AAA 0.7BBB 0.31 CCC 0.1Name: C, dtype: float64
test.groupby(['A','B'], as_index=False)['C'].sum()A B C0 0 AAA 0.71 0 BBB 0.32 1 CCC 0.1
英文:
test=pd.DataFrame({'A':['0','0','0','1'],'B':['AAA','AAA','BBB','CCC'],'C':[0.5,0.2,0.3,0.1]})test.groupby(['A','B'])['C'].sum()A B0 AAA 0.7BBB 0.31 CCC 0.1Name: C, dtype: float64
test.groupby(['A','B'], as_index=False)['C'].sum()A B C0 0 AAA 0.71 0 BBB 0.32 1 CCC 0.1
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