How to properly write if-then lambda statement for pandas df?

I have the following code:

data = [[11001218, 'Value', 93483.37, 'G', '', 93483.37, '', '56117J100', 'FRA', 'Equity'], 
        [11001218, 'Value', 3572.73, 'G', 3572.73, '', '56117J100', '', 'LUM', 'Equity'], 
        [11001218, 'Value', 89910.64, 'G', 89910.64, '', '56117J100', '', 'WAR', 'Equity'],
        [11005597, 'Value', 72640313.34,'L','',72640313.34, 'REVR21964', '','IN2',  'Repo']
       ]

df = pd.DataFrame(data, columns = ['ID', 'Type', 'Diff', 'Group', 'Amount','Amount2', 'Id2', 'Id3', 'Executor', 'Name'])

def logic_builder(row, row2, row3):
    if row['Name'] == 'Repo' and row['Group'] == 'L':
        return 'Fine resultant'
    elif (row['ID'] == row2['ID']) and (row['ID'] == row3['ID']) and (row['Group'] == row2['Group']) and (row['Group'] == row3['Group']) and (row['Executor'] != row2['Executor']) and (row['Executor'] != row3['Executor']):    
        return 'Difference in Executor'

df['Results'] = df.apply(lambda row: logic_builder(row, row2, row3), axis=1)

If you look at the first 3 rows, they are all technically the same. They contain the same ID, Type, Group, and Name. The only difference is the executor, hence I would like my if-then statement to return "Difference in Executor". I am having trouble figuring out how to right the if-then to look at all the rows with similar attributes for the fields I mentioned above.

Thank you.