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  • stack casts int32 dtype coordinate to int64 · 3 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1313866757 https://github.com/pydata/xarray/issues/7250#issuecomment-1313866757 https://api.github.com/repos/pydata/xarray/issues/7250 IC_kwDOAMm_X85OUAQF benbovy 4160723 2022-11-14T14:45:39Z 2022-11-14T14:45:39Z MEMBER

That's a bug in this method: https://github.com/pydata/xarray/blob/6f9e33e94944f247a5c5c5962a865ff98a654b30/xarray/core/indexing.py#L1528-L1532

Xarray array wrappers for pandas indexes keep track of the original dtype and should restore it when converted into numpy arrays. Something like this should work for the same method:

python def __array__(self, dtype: DTypeLike = None) -> np.ndarray: if dtype is None: dtype = self.dtype if self.level is not None: return np.asarray( self.array.get_level_values(self.level).values, dtype=dtype ) else: return super().__array__(dtype)

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  stack casts int32 dtype coordinate to int64 1433998942
1302258508 https://github.com/pydata/xarray/issues/7250#issuecomment-1302258508 https://api.github.com/repos/pydata/xarray/issues/7250 IC_kwDOAMm_X85NnuNM dcherian 2448579 2022-11-03T15:10:46Z 2022-11-03T15:10:46Z MEMBER

Ah very good find! Thanks.

maybe this can be fixed, or at least made more consistent. I think .values is pulling out of the pandas index (so is promoted) while we do actually have an underlying int32 array.

``` python

ds.stack(b=('a',))['a'].dtype #== ds.stack(b=('a',))['a'].values.dtype dtype('int32')

ds.stack(b=('a',))['a'].values.dtype dtype('int64') ```

cc @benbovy

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  stack casts int32 dtype coordinate to int64 1433998942
1302239394 https://github.com/pydata/xarray/issues/7250#issuecomment-1302239394 https://api.github.com/repos/pydata/xarray/issues/7250 IC_kwDOAMm_X85Nnpii dcherian 2448579 2022-11-03T14:57:16Z 2022-11-03T14:57:34Z MEMBER

Unfortunately this is a pandas thing, so we can't fix it. Pandas only provides Int64Index so everything gets cast to that. Fixing that is on the roadmap for pandas 2.0 I think (See https://github.com/pandas-dev/pandas/pull/44819#issuecomment-999790361)

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  stack casts int32 dtype coordinate to int64 1433998942

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