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
2228373305,I_kwDOAMm_X86E0kc5,8915,"Weird behavior of DataSet.where(... , drop=True)",22961670,closed,0,,,4,2024-04-05T16:03:05Z,2024-04-08T09:32:48Z,2024-04-08T09:32:48Z,NONE,,,,"### What happened?

I work with an aircraft emission dataset that is freely available online: [emission dataset](https://zenodo.org/records/10818082)

During my calculations I eventually convert the `DataSet` to a `DataFrame`. My motivation is to avoid unnecessary rows in the DataFrame. Doing some calculations my code returned unexpected results. Eventually I could narrow it down to a `DataSet.where(... , drop=True)` argument I added along the way, which introduces differences in the data. Here are two examples:

**Example 1:** Along some dimensions data points vanished if `drop=True`
![grafik](https://github.com/pydata/xarray/assets/22961670/a57f6c63-4927-442f-a7a0-71e1d524a706)

**Example 2:** For other dimensions (these?) data points appeared elsewhere if `drop=True`
![grafik](https://github.com/pydata/xarray/assets/22961670/6e80986a-f81f-4524-bc56-56d81ddf2bd9)


### What did you expect to happen?

I expect for my calculations to return the same results, regardless of whether drop=True is active or not.

### Minimal Complete Verifiable Example

```Python
!wget  ""https://zenodo.org/records/10818082/files/Emission_Inventory_H2O_Optimized_v0.1_MR3_Fleet_BRU-MYA_2075.nc""

import matplotlib.pyplot as plt
import xarray as xr

nc_file = xr.open_dataset('Emission_Inventory_H2O_Optimized_v0.1_MR3_Fleet_BRU-MYA_2075.nc')

fig, axs = plt.subplots(1,2,figsize=(10,4))

nc_file.H2O.where(nc_file.H2O!=0, drop=True).sum(('lon','time')).plot.contour(x='lat',ax=axs[0])
axs[0].set_xlim(-50,90)
axs[0].set_title('With drop=True')

nc_file.H2O.where(nc_file.H2O!=0, drop=False).sum(('lon','time')).plot.contour(x='lat',ax=axs[1])
axs[1].set_xlim(-50,90)
axs[1].set_title('With drop=False')

plt.tight_layout()
plt.show()

fig, axs = plt.subplots(1,2,figsize=(10,4))

nc_file.H2O.where(nc_file.H2O!=0, drop=True).sum(('lat','time')).plot.contour(x='lon',ax=axs[0])
axs[0].set_title('With drop=True')

nc_file.H2O.where(nc_file.H2O!=0, drop=False).sum(('lat','time')).plot.contour(x='lon',ax=axs[1])
axs[1].set_title('With drop=False')

plt.tight_layout()
plt.show()
```


### MVCE confirmation

- [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.
- [ ] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

### Relevant log output

_No response_

### Anything else we need to know?

_No response_

### Environment

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.10.9 | packaged by Anaconda, Inc. | (main, Mar  1 2023, 18:18:15) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('en_US', 'ISO8859-1')
libhdf5: 1.14.0
libnetcdf: 4.9.2

xarray: 2022.11.0
pandas: 1.5.3
numpy: 1.23.5
scipy: 1.13.0
netCDF4: 1.6.5
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.3
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: None
distributed: None
matplotlib: 3.7.0
cartopy: 0.21.1
seaborn: 0.12.2
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.6.3
pip: 22.3.1
conda: None
pytest: None
IPython: 8.10.0
sphinx: None

</details>
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