is there anyway to filter the first dataframe based on the index of second dataframe and generate the output dataframe? In first datafarme, we filterout the rows whose index are present in second dataframe and need to insert whole 0 zero in place of index value of second dataframe.
first dataframe
C1 C2 C3 C4
A 1 1 1 1
B 1 1 1 1
C 0 0 0 0
D 1 1 1 1
second dataframe
C1 C2 C3 C4
A 1 1 1 1
output dataframe
C1 C2 C3 C4
A 0 0 0 0
B 1 1 1 1
C 0 0 0 0
D 1 1 1 1
>Solution :
If you always have 1s in df2
, a simple method would be a subtraction:
out = df1.sub(df2, fill_value=0)
Otherwise, build a mask using reindexed df2
:
out = df1.mask(df2.notna().reindex(index=df1.index, columns=df1.columns, fill_value=False), 0)
Output:
C1 C2 C3 C4
A 0 0 0 0
B 1 1 1 1
C 0 0 0 0
D 1 1 1 1