DOCS: series.astype return error when a datetime64 (unitless) series astype numpy.datetime64 · Issue #47844 · pandas-dev/pandas (original) (raw)

Pandas version checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandas.
• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

pandas master branch:

import pandas as pd import numpy

pd.Series(['1970-01-01', '1970-01-01', '1970-01-01'], dtype="datetime64[ns]").astype(numpy.datetime64, copy=False) *** TypeError: Cannot cast DatetimeArray to dtype datetime64

Issue Description

I'm not sure whether it is expect behavior. I can repro on main branch, but can not repro on 1.4.x.
I know pandas community introduce a new feature about ENH: DTI/DTA.astype support non-nano . But the new feature disable the original code tree.
In this case, the original code tree will locate on

        elif self.tz is None and is_datetime64_dtype(dtype) and dtype != self.dtype:
            # unit conversion e.g. datetime64[s]
            return self._ndarray.astype(dtype)

But now, it is

        return dtl.DatetimeLikeArrayMixin.astype(self, dtype, copy)

And raise an error.

Expected Behavior

>>> import pandas as pd
>>> import numpy
>>> pd.Series(['1970-01-01', '1970-01-01', '1970-01-01'], dtype="datetime64[ns]").astype(numpy.datetime64, copy=False)
0   1970-01-01
1   1970-01-01
2   1970-01-01
dtype: datetime64[ns]

Installed Versions

pandas-1.5.0.dev0+1135.gc711be009b