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
1317320059,PR_kwDOAMm_X848ELIu,6825,Add docstring example for xr.open_mfdataset,8881170,closed,0,,,3,2022-07-25T20:17:31Z,2022-07-25T21:28:25Z,2022-07-25T21:28:25Z,CONTRIBUTOR,,0,pydata/xarray/pulls/6825,"This adds a short docstring example to `xr.open_mfdataset` to showcase how to pass arguments into `preprocess` for `xr.open_mfdataset`.

It wasn't very clear before how to do this, and this hopefully will show an easy and minimal pathway to doing so.

- [X] Closes https://github.com/pydata/xarray/discussions/6820
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6825/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
546451185,MDExOlB1bGxSZXF1ZXN0MzYwMTI2MDk4,3667,Add map_blocks example to docs,8881170,closed,0,,,6,2020-01-07T18:57:57Z,2020-01-15T00:24:03Z,2020-01-08T17:50:04Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3667,"This PR adds an example to the `xr.map_blocks()` docs. 

It is modeled off of @rabernat's example here: https://nbviewer.jupyter.org/gist/rabernat/30e7b747f0e3583b5b776e4093266114 and was encouraged to be opened via the gitter.

It might be slightly large for an example, but I think it shows an applied case to use this in and clears up some common pitfalls (e.g. how to pass args/kwargs).","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3667/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
548174850,MDExOlB1bGxSZXF1ZXN0MzYxNTI4NjA4,3682,Add map_blocks example to whats-new,8881170,closed,0,,,1,2020-01-10T16:32:16Z,2020-01-10T16:48:36Z,2020-01-10T16:48:32Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3682,This simply adds the `map_blocks` example from https://github.com/pydata/xarray/pull/3667 to the changelog.,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3682/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
477442608,MDExOlB1bGxSZXF1ZXN0MzA0NzY3MTE5,3188,Add climpred to related projects,8881170,closed,0,,,1,2019-08-06T15:16:44Z,2019-08-06T16:04:30Z,2019-08-06T16:02:20Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3188,This adds [`climpred`](https://climpred.readthedocs.io) to the `xarray` related projects page. ,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3188/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
445175953,MDU6SXNzdWU0NDUxNzU5NTM=,2969,`where` function mis-broadcasts and alters data type on dataset,8881170,closed,0,,,2,2019-05-16T21:52:58Z,2019-05-20T16:30:02Z,2019-05-20T16:30:02Z,CONTRIBUTOR,,,,"#### Code Sample, a copy-pastable example if possible

```python
import numpy as np

# generate data
dateVar = np.arange('2005-02', '2005-06', dtype='datetime64[D]')
t = len(dateVar)
floatVar = np.random.rand(t, 100)
indexVar = np.arange(100)
intVar = np.random.randint(1, high=10, size=(t, 100))

# create dataset
A = xr.DataArray(floatVar, dims=['time', 'N'])
A.name = 'floatVar'
B = xr.DataArray(indexVar, dims=['N'])
B.name = 'indexVar'
C = xr.DataArray(intVar, dims=['time', 'N'])
C.name = 'intVar'
D = xr.DataArray(dateVar, dims=['time'])
D.name = 'dateVar'
ds = xr.merge([A,B,C,D])
print(ds)

<xarray.Dataset>
Dimensions:   (N: 100, time: 120)
Dimensions without coordinates: N, time
Data variables:
    floatVar  (time, N) float64 0.4223 0.5019 0.8522 ... 0.9338 0.5833 0.09859
    indexVar  (N) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
    intVar    (time, N) int64 9 2 3 6 8 4 8 7 6 4 2 6 ... 3 1 8 3 8 3 5 3 1 6 7
    dateVar   (time) datetime64[ns] 2005-02-01 2005-02-02 ... 2005-05-31

# apply where function
ds.where(ds.indexVar > 50, drop=True)

<xarray.Dataset>
Dimensions:   (N: 49, time: 120)
Dimensions without coordinates: N, time
Data variables:
    floatVar  (time, N) float64 0.3381 0.04735 0.464 ... 0.5571 0.5297 0.8106
    indexVar  (N) float64 51.0 52.0 53.0 54.0 55.0 ... 95.0 96.0 97.0 98.0 99.0
    intVar    (time, N) float64 5.0 2.0 9.0 5.0 5.0 1.0 ... 1.0 6.0 5.0 4.0 3.0
    dateVar   (time, N) datetime64[ns] 2005-02-01 2005-02-01 ... 2005-05-31
```
#### Problem description

This is motivated by a use-case of dimensions (Time, nParticle) for a Lagrangian particle simulation. In the above code snippet, I filter by some condition on `indexVar` (e.g., some type of particle).

For variables that contain the same dimension as the one in `indexVar` (N), it broadcasts fine and there's no dimension changes. In the case of `dateVar`, which only has dimension `time`, there is a dim expansion to add N. 

Further, data-types are changed (`indexVar` and `intVar` from `int64` to `float64`). In my use-case, a variable of type `S64` was converted to `O`.

So the two major issues here:
1. `where` mis-broadcasts certain variables by adding the filtered dimension (in this case `N` to `dateVar`). It should instead ignore variables that don't contain the variable being filtered.
2. `where` changes data-types of variables after the filter is applied.

#### Expected Output

```python
<xarray.Dataset>
Dimensions:   (N: 49, time: 120)
Dimensions without coordinates: N, time
Data variables:
    floatVar  (time, N) float64 0.3381 0.04735 0.464 ... 0.5571 0.5297 0.8106
    indexVar  (N) int64 51 52 53 54 55 ... 95 96 97 98 99
    intVar    (time, N) int64 5 2 9 5 5 1 ... 1 6 5 4 3
    dateVar   (time) datetime64[ns] 2005-02-01 2005-02-02 ... 2005-05-31
```

#### Output of ``xr.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3 (default, Mar 27 2019, 16:54:48) 
[Clang 4.0.1 (tags/RELEASE_401/final)]
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.4
libnetcdf: 4.6.2

xarray: 0.12.1
pandas: 0.24.2
numpy: 1.16.3
scipy: 1.2.1
netCDF4: 1.4.2
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudonetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.2.1
dask: 1.2.2
distributed: 1.28.0
matplotlib: 3.0.3
cartopy: 0.17.0
seaborn: None
setuptools: 41.0.1
pip: 19.1.1
conda: None
pytest: 4.5.0
IPython: 7.5.0
sphinx: None
</details>","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2969/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue