BUG: Closed parameter in rolling function producing ValueError

[nrcjea001]

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• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

# Your code here
df = pd.DataFrame({"column1": range(6), 
                   "column2": range(6), 
                   'group': 3*['A','B'], 
                   'date':pd.date_range("20190101", periods=6)})
df.loc[:,'date']=df.loc[0,'date']
df
### Output
   column1  column2 group       date
0        0        0     A 2019-01-01
1        1        1     B 2019-01-01
2        2        2     A 2019-01-01
3        3        3     B 2019-01-01
4        4        4     A 2019-01-01
5        5        5     B 2019-01-01

df.groupby('group').rolling('1D',on='date',closed='left')['column1'].sum()
### Output
ValueError: closed only implemented for datetimelike and offset based windows

Problem description

Closed parameter not producing the result as it should. Only closed='both' is working.

Current workaround as follows (but considerably slower):

df.groupby('group').apply(lambda x: x.rolling('1D',on='date',closed='left')['column1'].sum())

Expected Output

group  date      
A      2019-01-01    NaN
       2019-01-01    0.0
       2019-01-01    2.0
B      2019-01-01    NaN
       2019-01-01    1.0
       2019-01-01    4.0
Name: column1, dtype: float64

Name: column1, dtype: float64

Output of pd.show_versions()

INSTALLED VERSIONS

commit : d9fff27
python : 3.8.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 11, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 1.1.0
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.1
setuptools : 49.2.1.post20200802
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.17.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.0
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.48.0