BUG: rolling std can't handle mixture of (relatively) big and small numbers
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

```python
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
```python
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()``

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
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

</details>
