Find the unique values of the first column but not present in the second column and return the corresponding row number of the value in first column

I have a csv file and there are a few columns here. Some of these columns have values and some don’t. What code should I write to get the output in the example below?

     Id  Name      Library       Line Source      Line Destination
0    59  Ayla          2.0                57                    34
1    60  Mahmut        2.0                14                    22
2    61  Mine          2.0                22                    43
3    62  Greg          2.0                14                    62
4    63  Mahmut        2.0                14                    33
5    64  Fiko          2.0                33                    82
6    65  Jasmin                           82                    27
7    66  Mahmut        2.0                43                    11
8    67  Ashley        2.0                62                    53

Expected result

The necessary conditions are as follows: ‘Mahmut’ should be contained in the name column, and the number in the ‘Line Source’ field should not be in the ‘Line Destination’ area.

So records with index_id 1 and 4 should be listed. Finally, the ‘Line Source’ value of these two records should be unique, and the output should only be the number 14.

Is there a pandas way to do that?

Answer

df[(df.Name == 'Mahmut') & (~df['Line Source'].isin(df['Line Destination'])]['Line Source'].unique()