BUG: df.groupy().rolling().cov() does not group properly and the cartesian product of all groups is returned instead · Issue #42915 · pandas-dev/pandas (original) (raw)

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 0.5

On 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 0.5

1.0.5 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