Pandas：分组依据和条件总和并添加回数据帧

Question

I have a data frame like below:

ID  Num  Letter  Count
1   17   D       1
1   12   D       2
1   13   D       3
2   17   D       4
2   12   A       5
2   16   D       1
3   16   D       1

The objective is to sum 'Count' value for each 'ID' when 'Num' is (17 or 12) and 'Letter' is 'D', and also add the calculation back to the original data frame in 'Total'.

Below is expected data frame:

ID  Num  Letter  Count Total
1   17   D       1     3   
1   12   D       2     3   
1   13   D       3     3 
2   17   D       4     4 
2   12   A       5     4 
2   16   D       1     4
3   16   D       1     0

Thanks in advance!

Answer 1

Idea is replace non matched values to 0 in Series.where and then is used GroupBy.transform with sum :

mask = df['Num'].isin([17,12]) & df['Letter'].eq('D')
df['Total'] = df['Count'].where(mask, 0).groupby(df['ID']).transform('sum')
print (df)
   ID  Num Letter  Count  Total
0   1   17      D      1      3
1   1   12      D      2      3
2   1   13      D      3      3
3   2   17      D      4      4
4   2   12      A      5      4
5   2   16      D      1      4
6   3   16      D      1      0