BUG: min_period not effecting rolling

[jamespreed]

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

x = pd.DataFrame({'x': range(20)})

for r in x.rolling(window=15, min_periods=15):
    print(r.shape)

# output:
(1, 1)
(2, 1)
(3, 1)
(4, 1)
(5, 1)
(6, 1)
(7, 1)
(8, 1)
(9, 1)
(10, 1)
(11, 1)
(12, 1)
(13, 1)
(14, 1)
(15, 1)
(15, 1)
(15, 1)
(15, 1)
(15, 1)
(15, 1)

Issue Description

I may be misunderstanding the documentation, but when using min_periods with an integer window value, I would expect that all of the windows would be at least as big as min_periods. Instead it starts with a windows of size 1 and goes up to window.

Expected Behavior

I expected that when window=15 and min_periods=15, that all windows would be of length 15.

(15, 1)
(15, 1)
(15, 1)
(15, 1)
(15, 1)
(15, 1)

Installed Versions

INSTALLED VERSIONS

commit : e86ed37
python : 3.10.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 151 Stepping 5, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.1.1
numpy : 1.26.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.0.0
pip : 23.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 8.15.0
pandas_datareader : None
bs4 : None
bottleneck : 1.3.5
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.0
numba : None
numexpr : 2.8.7
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[mroeschke]

Thanks but this is the expected behavior

Minimum number of observations in window required to have a value; otherwise, result is np.nan.

See the example in https://pandas.pydata.org/docs/user_guide/window.html#windowing-operations