[FIXED] Flag subset of a dataframe based on another dataframe values

Issue

I've encountered a problem which I didn't succeed to solve, for now. Your assistance on this one would be highly appreciated.

I have 2 dataframes:

first_df:
   A  B  C  D
1  1  a  q  zz
2  2  b  w  xx
3  3  c  e  yy
4  4  d  r  vv

second_df:
   C1 C2
1  10  a 
2  20  b 
3  70  g 
4  80  h 

What I want to achieve is mark rows from first_df, based on values from second_df. Marking those rows should be based on comparing column values:

(first_df['A'] == second_df['C1'] * 10) & (first_df['B'] == second_df['C2'])

Expected output should be like this:

compared_df:
   A  B  C  D   Match
1  1  a  q  zz  True
2  2  b  w  xx  True
3  3  c  e  yy  False
4  4  d  r  vv  False

Could you please point me in a right direction? Which pandas methods should I use to achieve my goal? I've tried many things, but I'm pandas beginner, so it's hard to assess if those attempts were correct.

Solution

First create Multiindex on both the dataframes then use MultiIndex.isin to test for the occurrence of the index values of first dataframe in the index of second dataframe in order the create boolean flag:

i1 = first_df.set_index([first_df['A'] * 10, 'B']).index
i2 = second_df.set_index(['C1', 'C2']).index

first_df['Match'] = i1.isin(i2)

Result

print(first_df)

   A  B  C   D  Match
1  1  a  q  zz   True
2  2  b  w  xx   True
3  3  c  e  yy  False
4  4  d  r  vv  False

Answered By - Shubham Sharma