Pandas version checks
-
[x] I have checked that this issue has not already been reported.
-
[x] I have confirmed this bug exists on the latest version of pandas.
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[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
df = pd.DataFrame(
{
"a": [4,2,3,None,1,2,3],
"g": [1, 1, 1, 1, 1, 1, 1],
}
).convert_dtypes(dtype_backend='pyarrow')
df['i'] = 1
print(df.groupby('g')['a'].transform('cumsum', skipna=True))
Issue Description
On linux i get
0 4
1 6
2 9
3 <NA>
4 10
5 12
6 15
Name: a, dtype: int64[pyarrow]
on window:
0 4
1 5
2 8
3 <NA>
4 9
5 11
6 14
Name: a, dtype: int64[pyarrow]
Expected Behavior
same on windows and linux
Installed Versions
INSTALLED VERSIONS
------------------
commit : 4665c10899bc413b639194f6fb8665a5c70f7db5
python : 3.11.9
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.26100
machine : AMD64
processor : Intel64 Family 6 Model 141 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 2.3.2
numpy : 2.3.3
pytz : 2025.2
dateutil : 2.9.0.post0
pip : None
Cython : None
sphinx : None
IPython : 9.4.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : 6.140.2
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 21.0.0
pyreadstat : None
pytest : 8.4.2
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None
Comment From: MarcoGorelli
maybe related to https://github.com/pandas-dev/pandas/issues/61896