What happened?

The plot accessors i.e. dataarray.plot of type _PlotMethods are missing static typing especially of function attributes. See #6947 for an example.

The problem is that many plotting methods are added using hooks via decorators, something that mypy does not understand.

What did you expect to happen?

As a quick fix: type the plot accessors as _PlotMethods | Any to avoid false positives in mypy.

Better to either restructure the accessor with static methods instead of hooks or figure out another way of telling static type checkers about these methods.

Anyway: mypy should not complain.

Minimal Complete Verifiable Example

```Python import xarray as xr

da = xr.DataArray([[1,2,3], [4,5,6]], dims=["x", "y"]) da.plot.contourf(x="x", y="y")

mypy complains:

error: "_PlotMethods" has no attribute "contourf"

```

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, 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

On mobile, can edit it later if required. Newest xarray should have this problem, before the accessor was Any.

What happened: http://xarray.pydata.org/en/stable/generated/xarray.DataArray.rename.html#xarray.DataArray.rename states that:

Returns a new DataArray with renamed coordinates or a new name.

What you expected to happen: It should state: "Returns a new DataArray with renamed coordinates, dimensions or a new name." Since it definitely can do that.

Minimal example xr.DataArray([1, 2, 3]).rename({"dim_0": "new"})

Further While at it: Dataset.rename als does not mention explicitly that you can rename coordinates.

What happened?

I tried to reduce some dimensions using where (sel did not work in this case) and shorten the dimensions with "drop=True". This works fine on DataArrays and Datasets with only a single dimension but fails as soon as you have a Dataset with two dimensions on different variables. The dimensions are left untouched and you have NaNs in the data, just as if you were using "drop=False" (see example).

I am actually not sure what the expected behavior is, maybe I am wrong and it is correct due to some broadcasting rules?

What did you expect to happen?

I expected that relevant dims are shortened. If the ds.where with "drop=False" all variables along a dimenions have some NaNs, then using "drop=True" I expect these dimensions to be shortened and the NaNs removed.

Minimal Complete Verifiable Example

```python import xarray as xr

this works

ds = xr.Dataset({"a": ("x", [1, 2 ,3])}) ds.where(ds > 2, drop=True)

returns:

<xarray.Dataset>

Dimensions: (x: 1)

Dimensions without coordinates: x

Data variables:

a (x) float64 3.0

this doesn't

ds = xr.Dataset({"a": ("x", [1, 2 ,3]), "b": ("y", [2, 3, 4])}) ds.where(ds > 2, drop=True)

returns:

<xarray.Dataset>

Dimensions: (x: 3, y: 3)

Dimensions without coordinates: x, y

Data variables:

a (x) float64 nan nan 3.0

b (y) float64 nan 3.0 4.0

```

Relevant log output

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS

commit: None python: 3.9.1 (default, Jan 13 2021, 15:21:08) [GCC 4.8.5 20150623 (Red Hat 4.8.5-44)] python-bits: 64 OS: Linux OS-release: 3.10.0-1160.49.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.0 libnetcdf: 4.7.4

xarray: 0.20.2 pandas: 1.3.5 numpy: 1.21.5 scipy: 1.7.3 netCDF4: 1.5.8 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.5.1.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.5.1 cartopy: None seaborn: None numbagg: None fsspec: None cupy: None pint: None sparse: None setuptools: 49.2.1 pip: 22.0.2 conda: None pytest: 6.2.5 IPython: 8.0.0 sphinx: None