无法使用pandas.Series.replace方法将字符串"NaT“替换为None

Question

我无法替换object类型的列中的“”NaT“”字符串。“

代码

print(d['cancellation_month'].dtype)
d['cancellation_month'] = d['cancellation_month'].replace('NaT', None)
print((d['cancellation_month'] == 'NaT').sum())

d.loc[d.cancellation_month == 'NaT', 'cancellation_month'] = None
print((d['cancellation_month'] == 'NaT').sum())

输出：

object
3
0

Answer 1

您是对的，您不能在value=None中使用replace

如果value为None并且to_replace不是字典，则将该值设置为to_replace参数。因此，Nat将取代NaT。

检查code

        if value is None:
            # passing a single value that is scalar like
            # when value is None (GH5319), for compat
            if not is_dict_like(to_replace) and not is_dict_like(regex):
                to_replace = [to_replace]