BUG: Rolling.mean downcasts extension dtypes

[bollard]

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

ser = pd.Series([i / 10 for i in range(1, 20)]).astype(pd.Float64Dtype())
ser.rolling(2).mean().dtype # dtype('float64')

Issue Description

#Rolling.mean prematurely downcast from extension-array type dtypes

Expected Behavior

That (in this example) the Float64Dtype is preserved

Installed Versions

INSTALLED VERSIONS

commit : 8dab54d
python : 3.10.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : English_United Kingdom.1252

pandas : 1.5.2
numpy : 1.23.4
pytz : 2022.1
dateutil : 2.8.2
setuptools : 65.5.0
pip : 22.2.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.1
html5lib : None
pymysql : 1.0.2
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.6.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.3
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 9.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.39
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[phofl]

Hi, thanks for your report. This is already known and on our list. Rolling does not support extension arrays yet, hence we have to cast to numpy dtypes

[bollard]

Ah understood, thanks. Is there anywhere I can track this?

[phofl]

Not sure, if we have an appropriate issue about this. If not, a tracker issue like ENH: Add masked support for rolling operations would be welcome

[bollard]

Done #50449. Thanks!

[phofl]

Thx, this is more helpful than a couple of different issues where every one of them lists a different method