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Keywords {🔍}

pandas, issue, dtype, mroeschke, docs, return, error, datetime, member, bug, added, jbrockmendel, sign, pull, seriesastype, unitless, series, astype, numpydatetime, import, conversions, commented, code, projects, bzhaoopenstack, branch, numpy, behavior, nonnano, navigation, requests, actions, security, closed, description, version, confirmed, exists, main, pdseries, dtypedatetimensastypenumpydatetime, copyfalse, repro, feature, original, tree, case, selfndarrayastypedtype, triage, reviewed,

Topics {✒️}

[spark-39821][python][ps] fix error personal information docs pandas community introduce buggy dtype conversions pandas master branch original code tree comment metadata assignees import pandas projects milestone 1 passing dtype=np astype return error nano datetime64/timedelta64 latest version nanosecond resolution type series astype numpy pull request type projects datetime64[ns] triage issue bug exists passing dtype = numpy accepts pandas return dtl nanosecond resolution 5 closed main branch expect behavior issue astype support cast datetimearray dti/dta accept bc worth defaulting special-casing 100% complete relationships copy=false feature disable github error numpy removed dtype= dtype datetime64 datetime64[ nano behavior astype nanosecond

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DiscussionForumPosting:
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      headline:DOCS: series.astype return error when a datetime64 (unitless) series astype numpy.datetime64
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [X] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python 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](https://github.com/pandas-dev/pandas/commit/67e8c4c3761ab1da4b0a341a472c0fe2ea393e8b) . 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 <details> pandas-1.5.0.dev0+1135.gc711be009b </details>
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      headline:DOCS: series.astype return error when a datetime64 (unitless) series astype numpy.datetime64
      articleBody:### Pandas version checks - [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas. - [X] I have confirmed this bug exists on the main branch of pandas. ### Reproducible Example ```python 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](https://github.com/pandas-dev/pandas/commit/67e8c4c3761ab1da4b0a341a472c0fe2ea393e8b) . 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 <details> pandas-1.5.0.dev0+1135.gc711be009b </details>
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