issues: 489825483

Hi, I wrote a helper function which allows to concatenate arrays like xr.combine_nested with the difference that it only supports xr.DataArrays, concatenates them by axis position similar to np.concatenate and overwrites all dimension names.

I often need this to combine very different feature types.

```python from typing import Union, Tuple, List import numpy as np import xarray as xr

def concat_by_axis( darrs: Union[List[xr.DataArray], Tuple[xr.DataArray]], dims: Union[List[str], Tuple[str]], axis: int = None, **kwargs ): """ Concat arrays along some axis similar to np.concatenate. Automatically renames the dimensions to dims. Please note that this renaming happens by the axis position, therefore make sure to transpose all arrays to the correct dimension order.

:param darrs: List or tuple of xr.DataArrays
:param dims: The dimension names of the resulting array. Renames axes where necessary.
:param axis: The axis which should be concatenated along
:param kwargs: Additional arguments which will be passed to `xr.concat()`
:return: Concatenated xr.DataArray with dimensions `dim`.
"""

# Get depth of nested lists. Assumes `darrs` is correctly formatted as list of lists.
if axis is None:
    axis = 0
    l = darrs
    # while l is a list or tuple and contains elements:
    while isinstance(l, List) or isinstance(l, Tuple) and l:
        # increase depth by one
        axis -= 1
        l = l[0]
    if axis == 0:
        raise ValueError("`darrs` has to be a (possibly nested) list or tuple of xr.DataArrays!")

to_concat = list()
for i, da in enumerate(darrs):
    # recursive call for nested arrays;
    # most inner call should have axis = -1,
    # most outer call should have axis = - depth_of_darrs
    if isinstance(da, list) or isinstance(da, tuple):
        da = concat_axis(da, dims=dims, axis=axis + 1, **kwargs)

    if not isinstance(da, xr.DataArray):
        raise ValueError("Input %d must be a xr.DataArray" % i)
    if len(da.dims) != len(dims):
        raise ValueError("Input %d must have the same number of dimensions as specified in the `dims` argument!" % i)

    # force-rename dimensions
    da = da.rename(dict(zip(da.dims, dims)))

    to_concat.append(da)

return xr.concat(to_concat, dim=dims[axis], **kwargs)

```

Would it make sense to include this in xarray?