BUG: Series rolling standard deviation gives zero for 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.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
s = pd.Series([5, 5, 6, 7, 5, 2, 5])
print("## Working sample:")
print(s.rolling(3).std())

s = pd.Series([5, 5, 6, 7, 5, 2, 5]) * 1e-8
print("## Doesn't work for small data:")
std = s.rolling(3).std()
print(std)

assert std.iloc[-2] == 0

data = list(s.rolling(3))[-2]
std_manual = data.std()
print("## Manually calculated std:", std_manual)

assert std.iloc[-2] == std_manual, "Rolling std and manually calculated rolling std do not match"

```

#### Problem description

I found that when the series consists of small floating numbers (about the order of 1e-8) the rolling standard deviation will be zero. If I use the same window and compute the standard deviation directly the output is non-zero. Is there an internal precision setting for the rolling `std` function?

#### Expected Output
```python
s = pd.Series([5, 5, 6, 7, 5, 2, 5]) * 1e-8
std = s.rolling(3).std()
```
`std` should be nonzero for the last few elements.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : f2c8480af2f25efdbd803218b9d87980f416563e
python           : 3.8.8.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United States.1252

pandas           : 1.2.3
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 49.6.0.post20210108
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.21.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.0
sqlalchemy       : None
tables           : None
tabulate         : 0.8.7
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.52.0

</details>
