issues

Is your feature request related to a problem? Please describe.

The xarray plotting interface supports coordinates containing pandas.Interval iff those intervals contain numbers. It fails when those intervals contain pandas.Timedelta:

```python import numpy as np import pandas as pd import xarray as xr

da = xr.DataArray( np.arange(10), dims=("x",), coords={"x": [pd.Interval(i, i+1) for i in range(10)]}) da.plot() # works

da = xr.DataArray( np.arange(10), dims=("x",), coords={"x": [pd.Interval( d-pd.Timestamp("2000-01-01"), d-pd.Timestamp("2000-01-01")+pd.Timedelta("1H")) for d in pd.date_range("2000-01-01", "2000-01-02", 10)]}) da.plot() # fails ```

The latter fails with:

Traceback (most recent call last): File "mwe82.py", line 18, in <module> da.plot() # fails File "/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/plot/plot.py", line 446, in __call__ return plot(self._da, **kwargs) File "/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/plot/plot.py", line 200, in plot return plotfunc(darray, **kwargs) File "/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/plot/plot.py", line 302, in line _ensure_plottable(xplt_val, yplt_val) File "/data/gholl/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/plot/utils.py", line 551, in _ensure_plottable raise TypeError( TypeError: Plotting requires coordinates to be numeric or dates of type np.datetime64, datetime.datetime, cftime.datetime or pd.Interval.

This error message is somewhat confusing, because the coordinates are "dates of type (...) pd.Interval", but perhaps a timedelta is not considered a date.

Describe the solution you'd like

I would like that I can use the xarray plotting interface for any pandas.Interval coordinate, including pandas.Timestamp and pandas.Timedelta.

Describe alternatives you've considered

I'll "manually" calculate the midpoints and use those as a timedelta coordinate instead.

Additional context

It seems that regular timedeltas aren't really supported either, although they don't cause an error message, they rather produce incorrect results. There's probably a related issue somewhere, but I can't find it now.

In the example below, the dimensionality for data variable y grows from (b) to (b, a) after calling the dataset where method. This behaviour does not appear to be documented. Is it a bug?

``` In [46]: ds = xarray.Dataset({"x": (("a", "b"), arange(25).reshape(5,5)+100), "y": ("b", arange(5)-100)}, {"a": arange(5), "b": arange(5)*2, "c": (("a",), list("ABCDE"))})

In [47]: print(ds)
<xarray.Dataset>
Dimensions:  (a: 5, b: 5)
Coordinates:
  * b        (b) int64 0 2 4 6 8
    c        (a) <U1 'A' 'B' 'C' 'D' 'E'
  * a        (a) int64 0 1 2 3 4
Data variables:
    x        (a, b) int64 100 101 102 103 104 105 106 107 108 109 110 111 ...
    y        (b) int64 -100 -99 -98 -97 -96

In [69]: ds.where((ds.c>='A') & (ds.c<='C'))
Out[69]: 
<xarray.Dataset>
Dimensions:  (a: 5, b: 5)
Coordinates:
  * b        (b) int64 0 2 4 6 8
    c        (a) <U1 'A' 'B' 'C' 'D' 'E'
  * a        (a) int64 0 1 2 3 4
Data variables:
    x        (a, b) float64 100.0 101.0 102.0 103.0 104.0 105.0 106.0 107.0 ...
    y        (b, a) float64 -100.0 -100.0 -100.0 nan nan -99.0 -99.0 -99.0 ...

```