pandas.rolling.max() shut down reopen
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
import pandas as pd

a = [0, 100900, 101000, 101000, 101000, 100900, 100900, 100900, 
	 100900, 100900, 100900, 100900, 100900, 100900, 100900, 
	 100900, 100900, 100900, 100900, 100900, 0, 100900, 100900, 
	 100900, 100900, 100900, 100900, 0, 0, 0, 101000, 0, 0, 0, 
	 101000, 100900, 100900, 100900, 100900, 100900, 100900, 
	 100900, 0, 101000, 101000, 101000, 101000, 0, 0, 0, 100900, 
	 100900, 100900, 100900, 100900, 100900, 100900, 100900, 
	 100900, 100900]

ix = pd.DatetimeIndex(['2018-06-01 09:33:49', '2018-06-01 09:33:50',
	               '2018-06-01 09:33:50', '2018-06-01 09:33:52',
	               '2018-06-01 09:33:52', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:53',
	               '2018-06-01 09:33:53', '2018-06-01 09:33:54',
	               '2018-06-01 09:33:54', '2018-06-01 09:33:54',
	               '2018-06-01 09:33:54', '2018-06-01 09:33:54',
	               '2018-06-01 09:33:55', '2018-06-01 09:33:55',
	               '2018-06-01 09:33:55', '2018-06-01 09:33:55',
	               '2018-06-01 09:33:55', '2018-06-01 09:33:55',
	               '2018-06-01 09:33:55', '2018-06-01 09:33:55',
	               '2018-06-01 09:33:55', '2018-06-01 09:33:55',
	               '2018-06-01 09:33:55', '2018-06-01 09:33:56',
	               '2018-06-01 09:33:56', '2018-06-01 09:33:56',
	               '2018-06-01 09:33:57', '2018-06-01 09:33:57',
	               '2018-06-01 09:33:57', '2018-06-01 09:33:57',
	               '2018-06-01 09:33:58', '2018-06-01 09:33:58',
	               '2018-06-01 09:33:58', '2018-06-01 09:33:58',
	               '2018-06-01 09:33:58', '2018-06-01 09:33:58',
	               '2018-06-01 09:33:58', '2018-06-01 09:33:58',
	               '2018-06-01 09:33:58', '2018-06-01 09:33:58'],
	              dtype='datetime64[ns]', name='0', freq=None)

series = pd.Series(a, index=ix)
series.rolling('3S', closed='left').max()
```
#### Problem description
I got a sample data and want to use it to get the rolling max, min, sum etc.
But every time I did rolling max/min on it, the python kernal would shut down and shows 'python.exe has stopped working' 

#### Expected Output

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0
pytest: 3.5.1
pip: 10.0.1
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.4
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: 0.1.6
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
