pandas.rolling.max() shut down reopen

[kid3night]

Code Sample, a copy-pastable example if possible

# 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()

[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

[WillAyd]

If you could make your code self-contained and copy/pastable would make it much easier for someone to take a look

[kid3night]

If you could make your code self-contained and copy/pastable would make it much easier for someone to take a look

No problem, I have updated it.

[kid3night]

If you could make your code self-contained and copy/pastable would make it much easier for someone to take a look

Is there any info needed right now?

[WillAyd]

Have you tried on master? IIRC we fixed something similar for windows recently

[kid3night]

Have you tried on master? IIRC we fixed something similar for windows recently

I just updated and tried again. The problem still exist.

[WillAyd]

Hmm I couldn't reproduce so likely a Windows issue. Let's see if someone else can

[kid3night]

Hmm I couldn't reproduce so likely a Windows issue. Let's see if someone else can
Yea, I tried the same thing one my Mac and the problem doesn't exist.

[kid3night]

Hmm I couldn't reproduce so likely a Windows issue. Let's see if someone else can

I want update one info:
If I use delete the closed='left', then the code will not crash. It seems that the problem exist in the boundary part.

[timhunderwood]

Hello,

I was able to reproduce this on Windows.

From some debugging, the issue occurs when you get to:

pandas.core.window._Rolling#_apply

When it tries to call:

return cfunc(arg, window, minp, indexi, closed, **kwargs)

with cfunc refering to "roll_max".

I think something goes wrong in:
pandas._libs.window#_roll_min_max

I can reproduce the issue by running the below:

import pandas._libs.window
import numpy

values = numpy.linspace(0, 1, 5)
window = 2
minp = 1
index = numpy.array(range(5)).astype(numpy.int64)
closed = "left"

pandas._libs.window.roll_max(values, window, minp, index, closed)

The issue does not occur if closed="right" or closed="both" or closed=None.

Let me know if I can help debug/resolve.

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.7.2.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.23.4
pytest: None
pip: 18.1
setuptools: 40.6.3
Cython: None
numpy: 1.15.4
scipy: 1.2.0
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[WillAyd]

@timhunderwood investigation and PRs are always welcome!