Description
Pandas version checks
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I have checked that this issue has not already been reported.
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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
s = pd.Series([1.2e+03, 1.3e+17, 1.5e+17, 1.995e+03, 1.990e+03])
s.rolling(2).std()Issue Description
The output is
0 NaN
1 9.192388e+16
2 1.414214e+16
3 1.060660e+17
4 0.000000e+00
dtype: float64
In fact, for any values afterwards with a similar magnitude (e.g., 1.234e+03), the rolling std is always 0.
Expected Behavior
0 NaN
1 9.192388e+16
2 1.414214e+16
3 1.060660e+17
4 3.535534e+00
dtype: float64
Installed Versions
INSTALLED VERSIONS
commit : 0f43794
python : 3.9.15.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.16.3-microsoft-standard-WSL2
Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.0.3
numpy : 1.25.1
pytz : 2023.3
dateutil : 2.8.2
setuptools : 68.0.0
pip : 23.1.2
Cython : None
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 : 8.7.0
pandas_datareader: None
bs4 : 4.12.2
bottleneck : None
brotli : 1.0.9
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : 2.3.1
pyqt5 : None