id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
326344778,MDU6SXNzdWUzMjYzNDQ3Nzg=,2183,converting int vars to floats when I where the enclosing ds?,1778852,open,0,,,5,2018-05-25T00:48:43Z,2022-04-09T02:14:23Z,,NONE,,,,"#### Code Sample
```python
test_ds = xr.Dataset()
test_ds['var1'] = xr.DataArray(np.arange(5))
test_ds['var2'] = xr.DataArray(np.ones(5))
assert(test_ds['var1'].dtype == np.int64)
assert(test_ds.where(test_ds['var2'] == 1)['var1'].dtype == np.int64)
```
#### Problem description
Second assert fails, which is a bit strange I think. Is that intended? If so, whats the reasoning?
#### Output of ``xr.show_versions()``
commit: None
python: 2.7.14.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.87-linuxkit-aufs
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: None
LOCALE: None.None
xarray: 0.10.3
pandas: 0.22.0
numpy: 1.14.3
scipy: 1.1.0
netCDF4: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
bottleneck: 1.2.1
cyordereddict: None
dask: None
distributed: None
matplotlib: 2.2.2
cartopy: None
seaborn: 0.8.1
setuptools: 39.1.0
pip: 10.0.1
conda: None
pytest: 3.5.1
IPython: 5.6.0
sphinx: None
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484699415,MDU6SXNzdWU0ODQ2OTk0MTU=,3256,.item() on a DataArray with dtype='datetime64[ns]' returns int,1778852,open,0,,,4,2019-08-23T20:29:50Z,2022-04-09T02:03:43Z,,NONE,,,,"#### MCVE Code Sample
```python
import datetime
import xarray as xr
test_da = xr.DataArray(datetime.datetime(2019, 1, 1, 1, 1))
test_da
#
# array('2019-01-01T01:01:00.000000000', dtype='datetime64[ns]')
test_da.item()
# 1546304460000000000
```
#### Expected Output
I would think it would be nice to get a `datetime` out of the `.item()` call then the nanosecond representation.
#### Output of ``xr.show_versions()``
When I call xr.show_versions() i get an error but im running xarray 0.12.3
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