Description
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I have confirmed this bug exists on the latest version 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
data = {'group':['g1', 'g1', 'g1', np.nan, 'g1', 'g1', 'g2', 'g2', 'g2', 'g2', np.nan],
'A':[3, 1, 8, 2, 6, -1, 0, 13, -4, 0, 1],
'B':[5, 2, 3, 7, 11, -1, 4,-1, 1, 0, 2]}
df = pd.DataFrame(data)
df.groupby('group',dropna=False)['A'].rolling(1,min_periods=1).mean()
#### Output
group
g1 0 3.0
1 1.0
2 8.0
4 6.0
5 -1.0
g2 6 0.0
7 13.0
8 -4.0
9 0.0
Name: A, dtype: float64Problem description
In Pandas 1.1.0, dropna=False is introduced as argument in groupby to allow for NA in group keys. However, we do not see this behaviour with rolling groupby. NA is not added to group key.
Expected Output
Nan group key
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