DataFrame return slices of dataframe that a column value equal some value else 0 based on column of the dataframe

I have a dataframe like below

df = pd.DataFrame({'testid':(1,2,1,2,1,2),'Name':('apple','apple','melon','melon','orange','orange'), 'A': (1,2,10,20,5,5), 'B': (1,5,4,2,3,1)})

testid	Name	A	B
1	apple	1	1
2	apple	2	5
1	melon	10	4
2	melon	20	2
1	orange	5	3
2	orange	5	1

I want to return a slice of this dataframe ( still a dataframe ) for every testid and Column A and B that if the corresponding apple value is larger than 1 then it returns the corresonding melon value, else return 0. basically I want to get a DataFrame like this

testid	A	B
1	0	0
2	20	2

how to achieve this? I tried apply() with lambda x:, but didn’t find a way to put in the dataframe column into the lambda function.

Answer

I believe this should work for you. Replace values corresponding to melon by according to values corresponding to apple.

p = df.groupby(['testid','Name']).sum()
p.xs('melon', level=1).where(p.xs('apple', level=1)>1, 0).reset_index()