Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
## 1 ##
>>> import pandas as pd
>>> test = pd.DataFrame({"id":["a","b"]*3, "b":pd.date_range("2000-01-01","2000-01-03", freq="9H")})
>>> g = test.groupby([pd.Grouper(key='b', freq="D"), 'id'])
>>> g.groups
{(2000-01-01 00:00:00, 'a'): [0], (2000-01-02 00:00:00, 'b'): [1]}
>>> len(g.groups.keys())
2
>>> g.ngroups
4
>>> g.size()
b id
2000-01-01 a 2
b 1
2000-01-02 a 1
b 2
dtype: int64
## 2 ##
>>> test['date'] = test.b.dt.date
>>> g = test.groupby(['date', 'id'])
>>> g.groups
{(2000-01-01, 'a'): [0, 2], (2000-01-01, 'b'): [1], (2000-01-02, 'a'): [4], (2000-01-02, 'b'): [3, 5]}Issue Description
Using pd.Grouper with a datetime key in conjunction with another key creates a set of groups, but this does not seem to encompass all of the groups that need to be created, in my opinion.
g.groups shows only 2 groups when I expected 4 groups -- both "a" and "b" for each day, whereas g.ngroups and g.size() return the correct results.
I believe this issue is confined to using a datetime key as replacing the the datetime key with a categorical key, which is based off of the datetime key, produces the correct result (see ## 2 ##).
Expected Behavior
g.groups.keys() must show all 4 keys.
Installed Versions
INSTALLED VERSIONS
commit : 2e218d1
python : 3.10.8.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-58-generic
Version : #64-Ubuntu SMP Thu Jan 5 11:43:13 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.5.3
numpy : 1.24.1
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.1.0
pip : 23.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.9.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.3
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.0
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : 0.19.0
tzdata : 2022.7