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
1537068105,I_kwDOAMm_X85bncxJ,7450,Backend array documentation typo,14371165,open,0,,,0,2023-01-17T21:37:26Z,2023-01-17T21:56:12Z,,MEMBER,,,,"### What happened?

https://docs.xarray.dev/en/stable/internals/how-to-add-new-backend.html#indexing-examples

I believe there's a typo in the BASIC indexing support example:
```python
# shall support integers
backend_array._raw_indexing_method(1, 1)
```

Should be:
```python
# shall support integers
backend_array._raw_indexing_method((1, 1))
```

Suggestion of possible fixes:
* Make sure it is a typo.
* Create a valid custom MyBackendArray and initialize it. So it is easier to tell if it's a typo.
* Add type hinting so mypy can easier catch these errors.

### What did you expect to happen?

_No response_

### Minimal Complete Verifiable Example

_No response_

### 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.
- [ ] 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.
- [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

### Relevant log output

_No response_

### Anything else we need to know?

_No response_

### Environment

<details>



</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7450/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
1376776178,I_kwDOAMm_X85SD-_y,7049,Backend entrypoints not public?,14371165,closed,0,,,0,2022-09-17T13:41:13Z,2022-10-26T16:01:06Z,2022-10-26T16:01:06Z,MEMBER,,,,"### What is your issue?

As I've understood it `ZarrBackendEntrypoint` is the engine used when loading zarr-files. But for some reason we show `ZarrStore` in `xr.backends`. 
I believe the `ZarrStore` class is supposed to be just a implementation detail, right?

```python
# The available engines:
xr.backends.list_engines()
Out[23]: 
{'netcdf4': <xarray.backends.netCDF4_.NetCDF4BackendEntrypoint object at 0x00000296D05D11F0>,
 'h5netcdf': <xarray.backends.h5netcdf_.H5netcdfBackendEntrypoint object at 0x00000296D05D14C0>,
 'scipy': <xarray.backends.scipy_.ScipyBackendEntrypoint object at 0x00000296D05D11C0>,
 'pseudonetcdf': <xarray.backends.pseudonetcdf_.PseudoNetCDFBackendEntrypoint object at 0x00000296D05D1430>,
 'pydap': <xarray.backends.pydap_.PydapBackendEntrypoint object at 0x00000296D05D1310>,
 'store': <xarray.backends.store.StoreBackendEntrypoint object at 0x00000296D05D1340>,
 'zarr': <xarray.backends.zarr.ZarrBackendEntrypoint object at 0x00000296D05D12E0>}

# The public class is ZarrStore instead of ZarrBackendEntrypoint, how come?
dir(xr.backends)
Out[22]: 
['AbstractDataStore',
 'BackendArray',
 'BackendEntrypoint',
 'CachingFileManager',
 'CfGribDataStore',
 'DummyFileManager',
 'FileManager',
 'H5NetCDFStore',
 'InMemoryDataStore',
 'NetCDF4DataStore',
 'NioDataStore',
 'PseudoNetCDFDataStore',
 'PydapDataStore',
 'ScipyDataStore',
 'ZarrStore',
 '__all__',
 '__builtins__',
 '__cached__',
 '__doc__',
 '__file__',
 '__loader__',
 '__name__',
 '__package__',
 '__path__',
 '__spec__',
 'api',
 'cfgrib_',
 'common',
 'file_manager',
 'h5netcdf_',
 'list_engines',
 'locks',
 'lru_cache',
 'memory',
 'netCDF4_',
 'netcdf3',
 'plugins',
 'pseudonetcdf_',
 'pydap_',
 'pynio_',
 'rasterio_',
 'scipy_',
 'store',
 'zarr']
```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7049/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
1410534774,I_kwDOAMm_X85UEw12,7170,Scatter plots overlap in facetgrid in 3d,14371165,open,0,,,0,2022-10-16T16:06:56Z,2022-10-16T16:08:55Z,,MEMBER,,,,"### What happened?

Any matplotlib gurus have any ideas how to nicely fit 3d plots in facetgrid?
```python
ds = xr.tutorial.scatter_example_dataset(seed=42)
fg = ds.plot.scatter(x=""A"", y=""B"", z=""z"", hue=""y"", markersize=""x"", row=""x"", col=""w"")
```
![image](https://user-images.githubusercontent.com/14371165/196045673-ad6322d4-63f4-4f94-aca6-a4cfdc682fea.png)

2d looks fine:
```python
fg = ds.plot.scatter(x=""A"", y=""B"", hue=""y"", markersize=""x"", row=""x"", col=""w"")
```
![image](https://user-images.githubusercontent.com/14371165/196045774-5d850317-c58a-4fac-ae4b-04660a140fd1.png)


### What did you expect to happen?

No plots overlapping each other, even if rotating the plots.

### Minimal Complete Verifiable Example

_No response_

### MVCE confirmation

- [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [x] 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.

### Relevant log output

_No response_

### Anything else we need to know?

_No response_

### Environment

<details>

xr.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:30:19) [MSC v.1929 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: ('Swedish_Sweden', '1252')
libhdf5: 1.12.2
libnetcdf: 4.8.1

xarray: 2022.9.1.dev266+gbd01f9cc.d20221006
pandas: 1.5.0
numpy: 1.23.3
scipy: 1.9.1
netCDF4: 1.6.1
pydap: installed
h5netcdf: 1.0.2
h5py: 3.7.0
Nio: None
zarr: 2.13.2
cftime: 1.6.2
nc_time_axis: 1.4.1
PseudoNetCDF: 3.2.2
rasterio: 1.3.2
cfgrib: None
iris: 3.3.0
bottleneck: 1.3.5
dask: 2022.9.2
distributed: 2022.9.2
matplotlib: 3.6.0
cartopy: 0.21.0
seaborn: 0.12.0
numbagg: 0.2.1
fsspec: 2022.8.2
cupy: None
pint: 0.19.2
sparse: 0.13.0
flox: 0.5.10.dev21+g91b6e19
numpy_groupies: 0.9.19
setuptools: 65.4.1
pip: 22.2.2
conda: None
pytest: 7.1.3
IPython: 7.33.0
sphinx: 5.2.3
C:\Users\J.W\anaconda3\envs\xarray-tests\lib\site-packages\_distutils_hack\__init__.py:33: UserWarning: Setuptools is replacing distutils.
  warnings.warn(""Setuptools is replacing distutils."")

</details>
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7170/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
778083748,MDU6SXNzdWU3NzgwODM3NDg=,4761,Dataset.interp drops boolean variables,14371165,closed,0,,,0,2021-01-04T13:09:56Z,2021-05-13T15:28:15Z,2021-05-13T15:28:15Z,MEMBER,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**:
`Dataset.interp` silently drops boolean variables.

**What you expected to happen**:
If I'm interpolating a group of variables I expect to get all of them back in the correct shape with relevant values in them.

If the variables are boolean or object arrays I don't expect it to do linear interpolation because it doesn't make sense but stepwise interpolation like nearest or zero order interpolation should be fine to expect.

**Minimal Complete Verifiable Example**:

```python
import numpy as np
a = np.arange(0, 5)
b = np.core.defchararray.add(""long_variable_name"", a.astype(str))
coords = dict(time=da.array([0, 1]))
data_vars = dict()
for v in b:
    data_vars[v] = xr.DataArray(
        name=v,
        data=np.array([0, 1]).astype(bool),
        dims=[""time""],
        coords=coords,
    )
ds1 = xr.Dataset(data_vars)

# Print raw data:
print(ds1)
Out[3]: 
<xarray.Dataset>
Dimensions:              (time: 2)
Coordinates:
  * time                 (time) int32 0 1
Data variables:
    long_variable_name0  (time) bool False True
    long_variable_name1  (time) bool False True
    long_variable_name2  (time) bool False True
    long_variable_name3  (time) bool False True
    long_variable_name4  (time) bool False True

# Interpolate:
ds1 = ds1.interp(
    time=da.array([0, 0.5, 1, 2]),
    assume_sorted=True,
    method=""nearest"",
    kwargs=dict(fill_value=""extrapolate""),
)

# Print interpolated data:
<xarray.Dataset>
Dimensions:  (time: 4)
Coordinates:
  * time     (time) float64 0.0 0.5 1.0 2.0
Data variables:
    *empty*
```

**Anything else we need to know?**:
`ds.interp_like `use `ds.reindex` in these cases which seems like a good choice in `ds.interp` as well. But I think that both `ds.interp` and `ds.interp_like` should fill by default with nearest value instead of np.nan because we're still requesting interpolation.

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>

xr.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.8.5 (default, Sep  3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
libhdf5: 1.10.4
libnetcdf: None

xarray: 0.16.2
pandas: 1.1.5
numpy: 1.17.5
scipy: 1.4.1
netCDF4: None
pydap: None
h5netcdf: None
h5py: 2.10.0
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2020.12.0
distributed: 2020.12.0
matplotlib: 3.3.2
cartopy: None
seaborn: 0.11.1
numbagg: None
pint: None
setuptools: 51.0.0.post20201207
pip: 20.3.3
conda: 4.9.2
pytest: 6.2.1
IPython: 7.19.0
sphinx: 3.4.0


</details>
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791725552,MDU6SXNzdWU3OTE3MjU1NTI=,4838,Simplify adding custom backends,14371165,closed,0,,,0,2021-01-22T06:02:53Z,2021-04-15T02:02:03Z,2021-04-15T02:02:03Z,MEMBER,,,,"<!-- Please do a quick search of existing issues to make sure that this has not been asked before. -->

**Is your feature request related to a problem? Please describe.**
I've been working on opening custom hdf formats in xarray, reading up on the apiv2 it is currently only possible to declare a new external plugin in setup.py but that doesn't seem easy or intuitive to me.

**Describe the solution you'd like**
Why can't we simply be allowed to add functions to the engine parameter? Example:
```python
from custom_backend import engine

ds = xr.load_dataset(filename, engine=engine)
```
This seems like a small function change to me from my initial _quick_ look because there's mainly a bunch of string checks in the normal case until we get to the registered backend functions, if we send in a function instead in the engine-parameter we can just bypass those checks.
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