BUG: Can't interchange zero-sized dataframes with Arrow

[honno]

Pandas version checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandas.
• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example & Issue Description

We can interchange our own empty dataframes just fine.

>>> import pandas as pd
>>> from pandas.api.interchange import from_dataframe as pandas_from_dataframe
>>> orig_df = pd.DataFrame({})
>>> pandas_from_dataframe(orig_df)
Empty DataFrame
Columns: []
Index: []

But fail when roundtripping with pyarrow.

>>> from pyarrow.interchange import from_dataframe as pyarrow_from_dataframe
>>> arrow_df = pyarrow_from_dataframe(orig_df)
>>> pandas_from_dataframe(arrow_df)
ValueError: No objects to concatenate

Full traceback

../../../anaconda3/envs/df/lib/python3.9/site-packages/pandas/core/interchange/from_dataframe.py:54: in from_dataframe
    return _from_dataframe(df.__dataframe__(allow_copy=allow_copy))
../../../anaconda3/envs/df/lib/python3.9/site-packages/pandas/core/interchange/from_dataframe.py:85: in _from_dataframe
    pandas_df = pd.concat(pandas_dfs, axis=0, ignore_index=True, copy=False)
../../../anaconda3/envs/df/lib/python3.9/site-packages/pandas/core/reshape/concat.py:377: in concat
    op = _Concatenator(
../../../anaconda3/envs/df/lib/python3.9/site-packages/pandas/core/reshape/concat.py:440: in __init__
    objs, keys = self._clean_keys_and_objs(objs, keys)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <pandas.core.reshape.concat._Concatenator object at 0x7ff532e247c0>, objs = [], keys = None

    def _clean_keys_and_objs(
        self,
        objs: Iterable[Series | DataFrame] | Mapping[HashableT, Series | DataFrame],
        keys,
    ) -> tuple[list[Series | DataFrame], Index | None]:
        if isinstance(objs, abc.Mapping):
            if keys is None:
                keys = list(objs.keys())
            objs = [objs[k] for k in keys]
        else:
            objs = list(objs)

        if len(objs) == 0:
>           raise ValueError("No objects to concatenate")
E           ValueError: No objects to concatenate

This also happens for zero-row dataframes

>>> orig_df = pd.DataFrame({"a": []})
>>> arrow_df = pyarrow_from_dataframe(orig_df)
>>> pandas_from_dataframe(arrow_df)
ValueError: No objects to concatenate

See that a roundtrip for a non-empty df works fine.

>>> orig_df = arrow_from_dataframe(orig_df)
>>> arrow_df = pyarrow_from_dataframe(orig_df)
>>> pandas_from_dataframe(arrow_df)
   a
0  0
1  1
2  2
3  3
4  4

We also get the same issue if we interchange a pyarrow.Table.

>>> import pyarrow as pa
>>> orig_df = pa.from_dict({})
>>> pandas_from_dataframe(orig_df)
ValueError: No objects to concatenate

Expected Behavior

>>> orig_df = pd.DataFrame({})
>>> arrow_df = pyarrow_from_dataframe(orig_df)
>>> pandas_from_dataframe(arrow_df)
Empty DataFrame
Columns: []
Index: []

Installed Versions

pd.show_versions()

/home/honno/.local/share/virtualenvs/pandas-empty-df-GBPvUBxi/lib/python3.8/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils.
  warnings.warn("Setuptools is replacing distutils.")

INSTALLED VERSIONS
------------------
commit           : 37ea63d540fd27274cad6585082c91b1283f963d
python           : 3.8.12.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.19.0-41-generic
Version          : #42~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Apr 18 17:40:00 UTC 2
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_GB.UTF-8
LOCALE           : en_GB.UTF-8

pandas           : 2.0.1
numpy            : 1.24.3
pytz             : 2023.3
dateutil         : 2.8.2
setuptools       : 67.6.1
pip              : 23.0.1
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 8.12.2
pandas_datareader: None
bs4              : None
bottleneck       : None
brotli           : None
fastparquet      : None
fsspec           : None
gcsfs            : None
matplotlib       : None
numba            : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 12.0.0
pyreadstat       : None
pyxlsb           : None
s3fs             : None
scipy            : None
snappy           : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
zstandard        : None
tzdata           : 2023.3
qtpy             : None
pyqt5            : None

Also tried this with pandas nightly

$ pip install --pre --extra-index https://pypi.anaconda.org/scipy-wheels-nightly/simple pandas --ignore-installed --no-deps

pyarrow is from their nightly builds

$ pip install --extra-index-url https://pypi.fury.io/arrow-nightlies/ --prefer-binary --pre pyarrow