Comparing 2 columns of two Python Pandas dataframes and getting the common rows

Question

I have 2 Dataframe as follows:

DF1=
    A    B   C    D
0   AA   BA  KK   0
1   AD   BD  LL   0
2   AF   BF  MM   0

DF2=
    K    L
0   AA   BA
1   AD   BF
2   AF   BF

At the end what I want to get is:

DF1=
    A    B   C    D
0   AA   BA  KK   1
1   AD   BD  LL   0
2   AF   BF  MM   1

So, I want to compare two dataframe, I want to see which rows of first data frame (for column A and B) are in common of of second dataframe(Column K and L) and assign 1 on the coulmn D of first dataframe.

I can use for loop, but It will be very slow for large number of entries.

Any clue or suggestion will be appreciated.

Answer 1

This would be easier if you renamed the columns of df2 and then you can compare row-wise:

In [35]:

df2.columns = ['A', 'B']
df2
Out[35]:
    A   B
0  AA  BA
1  AD  BF
2  AF  BF
In [38]:

df1['D'] = (df1[['A', 'B']] == df2).all(axis=1).astype(int)
df1
Out[38]:
    A   B   C  D
0  AA  BA  KK  1
1  AD  BD  LL  0
2  AF  BF  MM  1

Answer 2

df1['ColumnName'].isin(df2['ColumnName']).value_counts()