Exclude rows whose column contains values that are in another dataframe

Question

I have two dataframes, df1 and df2. One is the initial dataframe (data obtained from a source), the other is smaller and contains some mathematical transformation. For simplicity, they both have this layout:

df1:

A   B        C 
1   apple    a
2   pear     b
3   banana   c
4   berry    d
5   coconut  e
6   mango    f

df2:
A   B        C     D      E
1   apple    a     AT     14
2   pear     b     BT     DA
5   coconut  e     OT     OT
6   mango    f     MA     AP

Essentially, I would need another dataframe, i.e. df_excluded_values, that contains the rows that have been excluded from df2, based on the A column.

Thanks!

Does this answer your question? python pandas: how to find rows in one dataframe but not in another? — NYC Coder
– NYC Coder, Commented Jul 8, 2020 at 18:48

Celius Stingher · Accepted Answer · 2020-07-08 18:46:08Z

1

You can use ~ and isin():

df_excluded = df1[~df1['A'].isin(df2['A'].values)]

Returns the expected output for the rows, whose column 'A' values in df1 are not present in df2's column 'A':

   A       B  C
2  3  banana  c
3  4   berry  d

answered Jul 8, 2020 at 18:46

Celius Stingher

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