Description
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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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(optional) I have confirmed this bug exists on the master branch of pandas.
import pandas as pd
import numpy as np
df = pd.DataFrame(np.zeros(1000))
df.iloc[0] = 1000
df.rolling(10).std()
Out[124]:
0
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
.. ...
995 0.000004
996 0.000004
997 0.000004
998 0.000004
999 0.000004
[1000 rows x 1 columns]Problem description
If we have a relatively big number at the top, and the remaining is zeros, then the rolling result is not zero
Expected Output
df.iloc[0] = 0
df.rolling(10).std()
Out[125]:
0
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
.. ...
995 0.0
996 0.0
997 0.0
998 0.0
999 0.0
[1000 rows x 1 columns]Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2cb9652
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.8.0-53-generic
Version : #60-Ubuntu SMP Thu May 6 07:46:32 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.4
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : None
pytest : 6.2.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.2
html5lib : None
pymysql : 0.9.3
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : 3.0.0
IPython : 7.23.1
pandas_datareader: 0.9.0
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 4.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : 1.4.15
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.53.1