Pandas drop_duplicates - TypeError: type object argument after * must be a sequence, not map

Question

I have updated my question to provide a clearer example.

Is it possible to use the drop_duplicates method in Pandas to remove duplicate rows based on a column id where the values contain a list. Consider column 'three' which consists of two items in a list. Is there a way to drop the duplicate rows rather than doing it iteratively (which is my current workaround).

I have outlined my problem by providing the following example:

import pandas as pd

data = [
{'one': 50, 'two': '5:00', 'three': 'february'}, 
{'one': 25, 'two': '6:00', 'three': ['february', 'january']},
{'one': 25, 'two': '6:00', 'three': ['february', 'january']},
{'one': 25, 'two': '6:00', 'three': ['february', 'january']},
{'one': 90, 'two': '9:00', 'three': 'january'}
]

df = pd.DataFrame(data)

print(df)

   one                three   two
0   50             february  5:00
1   25  [february, january]  6:00
2   25  [february, january]  6:00
3   25  [february, january]  6:00
4   90              january  9:00

df.drop_duplicates(['three'])

Results in the following error:

TypeError: type object argument after * must be a sequence, not map

Answer 1

I think it's because the list type isn't hashable and that's messing up the duplicated logic. As a workaround you could cast to tuple like so:

df['four'] = df['three'].apply(lambda x : tuple(x) if type(x) is list else x)
df.drop_duplicates('four')

   one                three   two                 four
0   50             february  5:00             february
1   25  [february, january]  6:00  (february, january)
4   90              january  9:00              january