熊猫drop_duplicate - TypeError: *之后的类型对象参数必须是一个序列，而不是映射

I have updated my question to provide a clearer example.

我已经更新了我的问题以提供一个更清晰的例子。

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).

是否可以在熊猫中使用drop_duplicate方法根据列id删除重复的行，其中的值包含列表。考虑列“3”，它包含列表中的两个项目。是否有一种方法可以删除重复的行，而不是迭代执行(这是我当前的解决方案)。

I have outlined my problem by providing the following example:

我通过提供以下示例概述了我的问题:

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:

导致以下错误:

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

1 个解决方案

#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:

我认为这是因为列表类型是不可洗的，这会打乱重复的逻辑。作为一种变通方法，您可以对tuple进行如下转换:

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