Copying and merging column values when condition met in pandas

Question

I am kinda new to pandas and am struggling to find a solution to my problem.

My dataframe looks something like this:

Id	num	A	B	C
1	3.5	0	0	1
1	10	0	1	0
1	30	1	0	0
2	3.6	0	0	1
2	11	0	1	0
2	20	1	0	0

When the value from the column "Id" is the same, I want to copy the value from the "num" column to the column that has "1" as a value in column A, B or C and then merge them into one row and remove "num" column completely.

Kinda like this:

Id	num	A	B	C
1	3.5	0	0	3.5
1	10	0	10	0
1	30	30	0	0
2	3.6	0	0	3.6
2	11	0	11	0
2	20	20	0	0

And finally:

Id	A	B	C
1	30	10	3.5
2	20	11	3.6

Answer 1

First step, this is a simple multiplication, use mul :

cols = ['A', 'B', 'C']
df[cols] = df[cols].mul(df['num'], axis=0)

Second step, use groupby + max :

df.groupby('Id', as_index=False)[cols].max()

All steps without intermediate:

cols = ['A', 'B', 'C']
(df[cols].mul(df['num'], axis=0)
         .groupby(df['Id']).max()
         .reset_index()
)

Output 1:

   Id   num     A     B    C
0   1   3.5   0.0   0.0  3.5
1   1  10.0   0.0  10.0  0.0
2   1  30.0  30.0   0.0  0.0
3   2   3.6   0.0   0.0  3.6
4   2  11.0   0.0  11.0  0.0
5   2  20.0  20.0   0.0  0.0

Output 2:

   Id     A     B    C
0   1  30.0  10.0  3.5
1   2  20.0  11.0  3.6