BUG: Setting closed='neither' for rolling function of Series leads to mean() producing nan values
- [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 numpy as np
import pandas as pd

series = pd.Series(np.arange(20), index=pd.date_range("2018-01-01", periods=20, freq="M"))
series.rolling(window=5, closed='neither').mean()
```

#### Problem description

In the current version of pandas, the call to mean() produces a series of nan-values. For pandas 1.1.5, the output was different providing valid values starting from the fifth entry of the series.

#### Expected Output

2018-01-31     NaN
2018-02-28     NaN
2018-03-31     NaN
2018-04-30     NaN
2018-05-31     2.0
2018-06-30     3.0
2018-07-31     4.0
2018-08-31     5.0
2018-09-30     6.0
2018-10-31     7.0
2018-11-30     8.0
2018-12-31     9.0
2019-01-31    10.0
2019-02-28    11.0
2019-03-31    12.0
2019-04-30    13.0
2019-05-31    14.0
2019-06-30    15.0
2019-07-31    16.0
2019-08-31    17.0
Freq: M, dtype: float64

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

<details>

INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.128-microsoft-standard
Version          : #1 SMP Tue Jun 23 12:58:10 UTC 2020
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.0
numpy            : 1.19.5
pytz             : 2020.5
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 50.3.0
Cython           : 0.29.17
pytest           : 6.0.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.0
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
