BUG: wrong result in rolling mean\sum (possibly related with cython implementation)
- [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.

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

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
# Your code here
df = pd.Series(np.random.random(20), dtype='float64')

df[:10] *= 1e6
df[-10:] = 0
df
Out[124]: 
0     235266.408832
1     979278.480747
2     242108.917259
3     513980.266425
4      44316.957433
5     408655.731842
6     490360.015982
7     855399.526047
8     321975.011810
9     831082.388210
10         0.000000
11         0.000000
12         0.000000
13         0.000000
14         0.000000
15         0.000000
16         0.000000
17         0.000000
18         0.000000
19         0.000000
dtype: float64

df.rolling(6).mean()
Out[126]: 
0              NaN
1              NaN
2              NaN
3              NaN
4              NaN
5     2.682618e+05
6     2.723245e+05
7     2.937347e+05
8     3.589816e+05
9     2.737199e+05
10    2.429527e+05
11    2.411146e+05
12    1.258042e+05
13    9.726441e+04
14    1.032524e+04
15    2.546585e-11
16    2.546585e-11
17    2.546585e-11
18    2.546585e-11
19    2.546585e-11
dtype: float64

df.rolling(6).sum()
Out[127]: 
0              NaN
1              NaN
2              NaN
3              NaN
4              NaN
5     1.609571e+06
6     1.633947e+06
7     1.762408e+06
8     2.153889e+06
9     1.642319e+06
10    1.457716e+06
11    1.446688e+06
12    7.548251e+05
13    5.835865e+05
14    6.195146e+04
15    1.527951e-10
16    1.527951e-10
17    1.527951e-10
18    1.527951e-10
19    1.527951e-10
dtype: float64
```

#### Problem description

if the head is substantially larger than the 0s in the tail, then rolling mean\sum will not generate correct results. I roughly looked into the source code and guess maybe it's related to cython "rolling_mean"

#### Expected Output

0 in row 15 to 20, not 2.546585e-11

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

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-112-generic
Version          : #113-Ubuntu SMP Thu Jul 9 23:41:39 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.4
dateutil         : 2.8.1
pip              : 20.3.1
setuptools       : 51.0.0.post20201207
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.1
html5lib         : None
pymysql          : 0.9.2
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: 0.9.0
bs4              : None
bottleneck       : None
fsspec           : 0.8.4
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.5
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.4
sqlalchemy       : None
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.2

</details>
