Clearer Vectorized Indexing example

[max-sixty]

• Passes isort . && black . && mypy . && flake8
• User visible changes (including notable bug fixes) are documented in whats-new.rst

I found the existing example not that clear as to why it was selecting [[1,1],[5,5]], I think this is more obvious (open to disagreement of course!)

Before

In [37]: da = xr.DataArray(
   ....:     np.arange(12).reshape((3, 4)),
   ....:     dims=["x", "y"],
   ....:     coords={"x": [0, 1, 2], "y": ["a", "b", "c", "d"]},
   ....: )
   ....: 

In [38]: da
Out[38]: 
<xarray.DataArray (x: 3, y: 4)>
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
Coordinates:
  * x        (x) int64 0 1 2
  * y        (y) <U1 'a' 'b' 'c' 'd'

In [39]: da[[0, 1], [1, 1]]
Out[39]: 
<xarray.DataArray (x: 2, y: 2)>
array([[1, 1],
       [5, 5]])
Coordinates:
  * x        (x) int64 0 1
  * y        (y) <U1 'b' 'b'

After:

In [4]:     da[[1, 2, 2], [0, 3]]
Out[4]:
<xarray.DataArray (x: 3, y: 2)>
array([[ 4,  7],
       [ 8, 11],
       [ 8, 11]])
Coordinates:
  * x        (x) int64 1 2 2
  * y        (y) <U1 'a' 'd'`

[alexamici]

Yes, please.

Minor: also I'd personally find even more intuitive the selection da[[0, 2, 2], [1, 3]] that still shows you can repeat indexes, but somewhat looks more like a downsampling. Your call.

[dcherian]

Thanks @max-sixty

[dcherian]

& @alexamici for suggestions!