Description
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I have confirmed this bug exists on the latest version of pandas.
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When grouping a DataFrame which has a MultiIndex using the level parameter for groupby, performing any rolling operation will cause all MultiIndex levels except the one it was grouped by to be lost. This bug has been present since at least 1.1.5.
import pandas as pd
print(pd.__version__)
df = pd.DataFrame({"idx1": [1] * 5 + [2] * 5, "idx2": range(10), "value": range(10)})
df = df.set_index(["idx1", "idx2"])
test = df.groupby(level=0).rolling(2).mean()
print(test.index)On version 1.2.4:
>>>1.2.4
>>>MultiIndex([(1,),
(1,),
(1,),
(1,),
(1,),
(2,),
(2,),
(2,),
(2,),
(2,)],
names=['idx1'])On version 1.0.5:
>>>1.0.5
>>>MultiIndex([(1, 1, 0),
(1, 1, 1),
(1, 1, 2),
(1, 1, 3),
(1, 1, 4),
(2, 2, 5),
(2, 2, 6),
(2, 2, 7),
(2, 2, 8),
(2, 2, 9)],
names=['idx1', 'idx1', 'idx2'])Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2cb9652
python : 3.9.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.4
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 54.1.2
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 1.4.13
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None