按计数和总和分组，基于pandas数据框中的特定列以及其他列

Question

I have a dataframe(df):

A   B   C   D   E   F
A1  B1  c   10  E1  F1
A2  B2  c   50  E2  F2
A3  B3  c   20  E2  F3
A4  B4  c   30  E1  F4
A5  B5  c   40  E3  F5

Output should be like;

df:
A   B   C   D   E   F   count   sum
A1  B1  c   10  E1  F1  2   40
A2  B2  c   50  E2  F2  2   70
A3  B3  c   20  E2  F3  2   70
A4  B4  c   30  E1  F4  2   40
A5  B5  c   40  E3  F5  1   40

taking count and sum based on E column.

I tried :

df.groupby('E').agg(['count','sum'])

I am getting only count and sum column not other columns of df . Please suggest the solution.

Answer 1

Try it like this:

df['count'] = df.groupby('E')['E'].transform('count')
df['sum'] = df.groupby('E')['D'].transform('sum')

Output:

    A   B  C   D   E   F  count  sum
0  A1  B1  c  10  E1  F1      2   40
1  A2  B2  c  50  E2  F2      2   70
2  A3  B3  c  20  E2  F3      2   70
3  A4  B4  c  30  E1  F4      2   40
4  A5  B5  c  40  E3  F5      1   40

Answer 2

我无法理解您的数据，但您想要做的是：

df.groupby('E').agg({'column1': 'count', 'column2': 'sum'})