Здесь ниже приведен фрагмент, который поможет
from pandas import DataFrame
arr1 = [['AU002', '000000000037080', 'VB_ADJ'],
['AU002', '000000000037080', 'VB_ADJ'],
['AU002', '000000000039325', 'VB_ADJ'],
['AU002', '000000000039325', 'VB_ADJ']]
arr2 = [['AU002', '000000000037080', 'HUNTER_DOUGLAS'],
['AU002', '000000000037080', 'EXP'],
['AU002', '000000000037080', 'GEN'],
['AU002', '000000000037080', 'VB_ADJ'],
['AU002', '000000000039325', 'EXP']]
df1 = DataFrame.from_records(arr1)
df1.columns = ["Col1", "Col2", "Col3"]
df2 = DataFrame.from_records(arr2)
df2.columns = ["Col1", "Col2", "Col3"]
df1['compressed']=df1.apply(lambda x:'%s%s%s' % (x['Col1'],x['Col2'],x['Col3']),axis=1)
df2['compressed']=df2.apply(lambda x:'%s%s%s' % (x['Col1'],x['Col2'],x['Col3']),axis=1)
df1['Success'] = df1['compressed'].isin(df2['compressed']).astype(int)
print(df1)
Вывод:
Col1 Col2 Col3 compressed Success
0 AU002 000000000037080 VB_ADJ AU002000000000037080VB_ADJ 1
1 AU002 000000000037080 VB_ADJ AU002000000000037080VB_ADJ 1
2 AU002 000000000039325 VB_ADJ AU002000000000039325VB_ADJ 0
3 AU002 000000000039325 VB_ADJ AU002000000000039325VB_ADJ 0