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
A = [0.00000000e+00, 0.00000000e+00, 3.16188252e-18, 2.95781651e-16,
2.23153542e-51, 0.00000000e+00, 0.00000000e+00, 5.39943432e-48,
1.38206260e-73, 0.00000000e+00]
ts = pd.DataFrame(A)
print(ts.rolling(window=3, center=True).var(ddof=1))Issue Description
I am trying to compute a rolling variance and for some reasons, some of the values I obtain are negative. For example, running the code above gives me:
0
0 NaN
1 3.332500e-36
2 2.885385e-32
3 2.885385e-32
4 2.916226e-32
5 -5.473822e-48
6 -5.473822e-48
7 -5.473822e-48
8 -5.473822e-48
9 NaN
Expected Behavior
All values should be positive and match following array (with the exception of NaN values at the beginning and the end):
[0.00000000e+000 3.33250036e-036 2.88538519e-032 2.88538519e-032
2.91622617e-032 1.65991678e-102 9.71796366e-096 9.71796366e-096
9.71796366e-096 6.36699010e-147]
Right now, only the value from index 1 to 4 seem to be correct.
Installed Versions
INSTALLED VERSIONS
commit : 4c07e07
python : 3.10.6.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.0-38-generic
Version : #39~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 17 21:16:15 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.0.dev0+408.g4c07e0769c
numpy : 1.24.2
pytz : 2023.3
dateutil : 2.8.2
setuptools : 59.6.0
pip : 22.0.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
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 : None
pyqt5 : None