I have 2 subsets that have similar columns, but the one column they have in common is column A.
I have the left df L and the right df R.
I want to make sure that any duplicates for column A seen in L that are also in df R are removed from L - the whole column.
How would one do this?
import pandas as pd
L_df = pd.DataFrame({'A': ['bob/is/cool', 'alice/is/cool', 'jim/is/cool'], 
                   'view': ['A', 'B', 'B']})
R_df = pd.DataFrame({'A': ['ralf/is/cool', 'i/am/cool', 'alice/is/cool'], 
                   'view': ['A', 'B', 'C']})
I want to get the result of this with the result taking away duplicates for column A, and taking the duplicated value from L not R.
So we take alice/is/cool with a view value of C and not B if that makes sense :)
Output would be
out = pd.DataFrame({'A': ['ralf/is/cool', 'i/am/cool', 'alice/is/cool', 'bob/is/cool', 'jim/is/cool'], 
                   'view': ['A', 'B', 'C', 'A', 'B']})
 
    