Python provides different dtypes for same column

Question

I am trying to provide a minimal example soon, but in the meantime: How is it possible, that column "Home Points" is type object and int64 simultaniously? Any hint? Is this a pandas bug?

>>>print(df[["Home Team", "Away Team", "Home Points", "Away Points"]].dtypes)
>>>print()
>>>print(df["Home Points"].describe())
>>>print()
>>>df['Home Points'].unique()

Home Team      object
Away Team      object
Home Points    object
Away Points    object
dtype: object

count     8754
unique       3
top          3
freq      3801
Name: Home Points, dtype: int64

array([3, 1, 0], dtype=object)