### Using `numpy.where`:
df.assign(
target=np.where(df.index.isin(df.groupby(['Group1', 'Group2']).Value.idxmax()),
df.Value, 0)
)
<!- ->
Group1 Group2 Value target
0 1 3 0 0
1 1 3 1 1
2 1 4 1 1
3 1 4 1 0
4 2 5 5 5
5 2 5 1 0
6 2 6 0 0
7 2 6 1 1
Using `idxmax`
df['Newcol']=0
df.loc[df.Value.ne(0).groupby(df['Group']).idxmax(),'Newcol']=1
df
Out[41]:
Group Value Target_Column Newcol
0 1 0 0 0
1 1 0 0 0
2 1 1 1 1
3 1 2 0 0
4 2 0 0 0
5 2 1 1 1
6 2 0 0 0
7 2 1 0 0
