Numerical issue with rolling cov and corr
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
import pandas as pd
a = pd.Series([1e5, 0, 0, 0, 0])
b = pd.Series([9.45] * 5)
c1 = a.rolling(5).corr(b).iloc[4]
c2 = a.corr(b)
v1 = a.rolling(5).cov(b).iloc[4]
v2 = a.cov(b)
assert c1 == c2
assert v1 == v2
```
#### Problem description

I came across a strange behavior of Pandas rolling correlation. In the code snippet below, I'd assume v1 == v2 is true but it turns out not. This causes inf in rolling correlation (c1 vs. c2, where c2 is fine but c1 is "wrong" in my opinion). Since the standard deviation of a constant sequence is 0, the correlation between it and any other sequence would be a 0/0. Returning a nan as what the vanilla corr does is fine, but returning inf is annoying and misleading

#### Expected Output
assertions pass

#### Output of ``pd.show_versions()``
<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.0.final.0
python-bits: 64
OS: Darwin
OS-release: 18.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: en_US.UTF-8
pandas: 0.23.4
pytest: 4.0.0
pip: 18.1
setuptools: 40.6.2
Cython: 0.29
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 7.1.1
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: None
numexpr: 2.6.8
feather: None
matplotlib: None
openpyxl: 2.5.9
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.14
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
