id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
943112510,MDU6SXNzdWU5NDMxMTI1MTA=,5598,Conversion to pandas for zero-dimensional Data(Set|Array),7611856,open,0,,,2,2021-07-13T10:07:38Z,2021-07-14T08:05:38Z,,NONE,,,,"**What happened**:
Conversion to a pandas `DataFrame` of a zero dimensional `DataArray` or `Dataset` fails.

**What you expected to happen**:
I would expect it to return a trivial `DataFrame` with one row and the respective coordinate / data set columns.
However, I am not sure if that conflicts with potential other round trips between xarray and pandas - e.g. for one-dimensional 1-sized data arrays.

**Minimal Complete Verifiable Example**:

```python
da = DataArray([1, 2, 3], dims=(""x"",), coords=dict(x=[1, 2, 3]))
# I don't know of a way to construct such data array without the isel.
# Essentially, below also works for higher dimensional data arrays and
# results in a zero dimensional data array with all the coordinates of
# the found minimum.
da = da.isel(**da.argmin(dim=(""x"",)))
ds = Dataset({'a': da})
# fails with ValueError: cannot convert a scalar to a DataFrame
# from xarray/core/dataarray.py"", line 2664, in to_dataframe
da.to_dataframe(name=""foo"")
# Expected: a DataFrame with two columns (x and foo) and one row

# fails with ValueError: no valid index for a 0-dimensional object
# from xarray/core/coordinates.py"", line 106, in to_index
ds.to_dataframe()
# Expected: a DataFrame with two columns (x and a) and one row
```

**Anything else we need to know?**:
I tested a little bit and got what I want with simply removing the 

```python
def to_dataframe(...):
    ...
    if self.ndim == 0:
        raise ValueError(""cannot convert a scalar to a DataFrame"")
```

block from `dataarray.py` and changing 

```python
def to_index(self, ordered_dims: Sequence[Hashable] = None) -> pd.Index:
   ...
    if len(ordered_dims) == 0:
       return pd.Index([0])
      #  raise ValueError(""no valid index for a 0-dimensional object"")
```
to not raise and instead return a trivial index in `coordinates.py`.

I that would be considered reasonable behavior I am happy to contribute the respective unit test and changes!



**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.5 (default, May 19 2021, 11:32:47) 
[GCC 10.2.0]
python-bits: 64
OS: Linux
OS-release: 5.8.0-59-generic
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: 0.17.0
pandas: 1.2.4
numpy: 1.20.2
scipy: 1.6.3
netCDF4: 1.5.6
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.4.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.4.1
cartopy: None
seaborn: None
numbagg: None
pint: None
setuptools: 56.0.0
pip: 21.0.1
conda: None
pytest: 6.2.3
IPython: 7.24.0
sphinx: None
</details>
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