BUG: groupby.ohlc returns Series rather than DataFrame if input is empty

[batterseapower]

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandas. (tested 1.3.1)
• (optional) I have confirmed this bug exists on the master branch of pandas.

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Code Sample, a copy-pastable example

# This returns a pd.Series with 0 items
pd.DataFrame.from_dict({
    'timestamp': pd.DatetimeIndex([]),
    'symbol': np.array([], dtype=object),
    'price': np.array([], dtype='f4'),
}).set_index('timestamp').groupby('symbol').resample('D', closed='right')['price'].ohlc()

# This returns a pd.DataFrame with columns open, high, low, close and a single row (index=[(ABC, 2021-01-01)])
pd.DataFrame.from_dict({
    'timestamp': pd.DatetimeIndex(['2021-01-01']),
    'symbol': np.array(['ABC'], dtype=object),
    'price': np.array([100], dtype='f4'),
}).set_index('timestamp').groupby('symbol').resample('D', closed='right')['price'].ohlc()

Problem description

It is surprising that groupby.ohlc returns different data types depending on whether or not there are zero rows.

Expected Output

I think it would be more sensible for the zero row case to return a DataFrame with columns open/high/low/close, but with zero rows. Returning a Series as a special case doesn't make sense.

Output of pd.show_versions()

(This failed with an error about llvmlite.dll in the environment with pandas 1.3.1 installed, so this output is actually from a slightly earlier install of Pandas which still exhibits the bug.)

INSTALLED VERSIONS ------------------ commit : 2cb9652 python : 3.8.10.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.18363 machine : AMD64 processor : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United Kingdom.1252

pandas : 1.2.4
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.1
setuptools : 52.0.0.post20210125
Cython : 0.29.23
pytest : 6.2.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.0
IPython : 7.22.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 0.9.0
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : None
tables : None
tabulate : None
xarray : 0.18.0
xlrd : 2.0.1
xlwt : None
numba : 0.53.0

[rhshadrach]

Thanks for the report - agreed and confirmed on master. Further investigations and a PR to fix is most welcome.

[ndtretyak]

SeriesGroupBy._wrap_applied_output is used here to create the resulting object

pandas/pandas/core/groupby/groupby.py

Lines 1304 to 1306 in 860ff03

	return self._wrap_applied_output(
	data, keys, values, not_indexed_same=not_indexed_same
	)

However, if the initial dataframe is empty, then there is no group keys and _wrap_applied_output just returns an empty Series

pandas/pandas/core/groupby/generic.py

Lines 444 to 451 in 860ff03

	if len(keys) == 0:
	# GH #6265
	return self.obj._constructor(
	[],
	name=self.obj.name,
	index=self.grouper.result_index,
	dtype=data.dtype,
	)

[jbrockmendel]

Looks like we have several incorrect tests in tests.resample.test_base testing for the wrong behavior here