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Reproducible Example

import pandas as pd
import numpy as np

df = pd.DataFrame([np.nan, 0, 1, 2,])

print(df.rolling(window=3, win_type="exponential", min_periods=0).sum(tau=1))
#           0
# 0       NaN
# 1       NaN
# 2       NaN
# 3  1.735759
print(df.rolling(window=3, min_periods=0).sum())
#      0
# 0  0.0
# 1  0.0
# 2  1.0
# 3  3.0
print(df.rolling(window=3, win_type="exponential", min_periods=0).mean(tau=1))
#      0
# 0  NaN
# 1  NaN
# 2  NaN
# 3  1.0
print(df.rolling(window=3, min_periods=0).mean())
#      0
# 0  NaN
# 1  0.0
# 2  0.5
# 3  1.0

Issue Description

When using weighted rolling aggregation and setting min_periods to 0 does not work and it is treated as None. Aggregations without weight work as expected.

Expected Behavior

Weighted and not-weighted rolling aggregations should behave the same way with min_periods=0 and fill NaN in the same positions.

Installed Versions

commit : 2e218d10984e9919f0296931d92ea851c6a6faf5 python : 3.11.1.final.0 python-bits : 64 OS : Linux OS-release : 5.10.102.1-microsoft-standard-WSL2 Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.5.3 numpy : 1.24.1 pytz : 2022.7.1 dateutil : 2.8.2 setuptools : 66.1.1 pip : 22.2.2 Cython : None pytest : 7.2.1 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.8.0 pandas_datareader: None bs4 : 4.11.1 bottleneck : None brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : 3.6.3 numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 10.0.1 pyreadstat : None pyxlsb : None s3fs : None scipy : 1.10.0 snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None tzdata : None

Comment From: Savlik

take