BUG: skipna keyword no longer accepted by rolling().sum()

[LeoLi2002]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
import numpy as np
a = pd.Series([1,2,3,4,5,6])
a.iloc[3] = np.nan
print(a.rolling(2).sum(skipna=True))

Issue Description

At precvious version, the rolling.sum can use the keyword skipna to exclude nan when calculating, but in this version the parameter have benn removed and the funcation can not work even use .apply(np.nansum)

Expected Behavior

import pandas as pd
import numpya as np
a = pd.Series([1,2,3,4,5,6])
a.iloc[3] = np.nan
print(a.rolling(2).sum(skipna=True))

Installed Versions

pandas : 2.1.0
numpy : 1.25.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.0
pip : 23.2.1
Cython : 3.0.2
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : None
pandas_datareader : None
bs4 : None
bottleneck : None
dataframe-api-compat: None
fastparquet : 2023.8.0
fsspec : 2023.9.2
gcsfs : None
matplotlib : 3.8.0
numba : None
numexpr : 2.8.6
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.2
sqlalchemy : None
tables : 3.8.0
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report. Can you give this issue an informative title; it is currently BUG:.

In what version of pandas could you specify skipna?

[jorisvandenbossche]

In what version of pandas could you specify skipna?

This "worked" in pandas 1.x, but we were giving a deprecation warning. Running the above snippet with pandas 1.5:

In [5]: print(a.rolling(2).sum(skipna=True))
<ipython-input-5-e7a76e200cf6>:1: FutureWarning: Passing additional kwargs to Rolling.sum has no impact on the result and is deprecated. This will raise a TypeError in a future version of pandas.
  print(a.rolling(2).sum(skipna=True))
0     NaN
1     3.0
2     5.0
3     NaN
4     NaN
5    11.0
dtype: float64

Note that also then this keyword didn't have any affect, AFAIK, and the default is also True, so no need to specify skipna=True.

The reason you get NaNs in the result is because of min_periods (minimum of valid (non-NaN) values present in the window) defaulting to the window size. If you reduce that, you get no NaNs:

In [9]: a.rolling(2, min_periods=0).sum()
Out[9]: 
0     1.0
1     3.0
2     5.0
3     3.0
4     5.0
5    11.0
dtype: float64

[rhshadrach]

Thanks @jorisvandenbossche. I think this is resolved then. @LeoLi2002 - if you think anything was missed please comment here and we can reopen.