Branching from https://github.com/pydata/xarray/issues/3770

Here's the proposal: allow lambdas on methods where the primary argument is a single xarray object, and interpret lambas as though they'd be supplied in a pipe method followed by the current method. Taking the example from the linked issue:

```python

In [1]: import xarray as xr

In [2]: import numpy as np

In [3]: da = xr.DataArray(np.random.rand(2,3))

In [4]: da.where(da > 0.5)
Out[4]: <xarray.DataArray (dim_0: 2, dim_1: 3)> array([[ nan, 0.71442406, nan], [0.55748705, nan, nan]]) Dimensions without coordinates: dim_0, dim_1

this should be equivalent (currently not valid)

In [5]: da.where(lambda x: x > 0.5)

the longer version (currently works)

In [5]: da.pipe(lambda x: x.where(x > 0.5))

```

Others I miss from pandas: assign, and loc. I haven't gone through the list though assume there are others; we don't have to agree 100% on the list before starting with the most obvious ones, assuming we're in agreement with the principle.