Description
-
I have checked that this issue has not already been reported.
-
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.
import pandas as pd
print(pd.__version__)
df_a = pd.DataFrame({"value": range(10), "idx1": [1] * 5 + [2] * 5, "idx2": [1, 2, 3, 4, 5] * 2}).set_index(["idx1", "idx2"])
df_b = pd.DataFrame({"value": range(5), "idx2": [1, 2, 3, 4, 5]}).set_index("idx2")
test = df_a.groupby(level=0).rolling(2).cov(df_b)
print(test)On pandas 1.3.1:
1.3.1
value
idx1 idx1 idx2
1 1 1 NaN
2 0.5
3 0.5
4 0.5
5 0.5
2 1 NaN
2 NaN
3 NaN
4 NaN
5 NaN
2 1 1 NaN
2 NaN
3 NaN
4 NaN
5 NaN
2 1 NaN
2 0.5
3 0.5
4 0.5
5 0.5On pandas 1.0.5:
1.0.5
value
idx1 idx1 idx2
1 1 1 NaN
2 0.5
3 0.5
4 0.5
5 0.5
2 2 1 NaN
2 0.5
3 0.5
4 0.5
5 0.51.0.5 has the correct expected output. In 1.3.1, everything in index 1/2/x and 2/1/x is useless and will always be NaN.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : c7f7443
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 : 1.3.1
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.2
pip : 21.1.2
setuptools : 54.1.2
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : 2.9.1 (dt dec pq3 ext lo64)
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 : 1.4.22
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : None