BUG: "min_period" and "min_periods" problem in df.groupby().rolling

[ZiyueWang25]

• [y] I have checked that this issue has not already been reported.

• [y] 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.

---

Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

# Your code here

import pandas as pd
name_l = ["Alice"] * 5 + ["Bob"] * 5 
val_l = [np.nan,np.nan,1,2,3]+[np.nan,1,2,3,4]
test_df = pd.DataFrame([name_l,val_l]).T
test_df.columns = ["name","val"]

# correct one
test_df.groupby("name")["val"].rolling(window=2,min_periods=1).sum()

# wrong one with "min_period” parameter 
test_df.groupby("name")["val"].rolling(window=2,min_period=1).sum() 

Problem description

The one with min_period does not work the same as min_periods and should not be allowed.

[this should explain why the current behaviour is a problem and why the expected output is a better solution]

Expected Output

The one with min_period as parameter should produce an error.

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.7.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.3.0-7629-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.0.3
numpy : 1.16.4
pytz : 2019.2
dateutil : 2.7.3
pip : 20.1
setuptools : 46.1.3
Cython : None
pytest : 5.4.1
hypothesis : None
sphinx : 2.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.2
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10
IPython : 7.11.1
pandas_datareader: None
bs4 : 4.8.2
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.4.2
matplotlib : 3.1.1
numexpr : None
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.4.1
pyxlsb : None
s3fs : None
scipy : 1.3.1
sqlalchemy : 1.3.12
tables : None
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
xlsxwriter : None
numba : 0.46.0

[gabrielvf1]

I was looking for a fix on this issue and i realize that doesnt matter if you put arguments that are invalid inside the rolling() that wont be checked, is that normal? or should this be checked? Like:
The output of this code:
rolling(window=2,teste="teste",min_periods=1)
Is the same as this:
rolling(window=2,min_periods=1).
I think that the best way is to check if all arguments are valid, no? Is there a reason to dont check it?
Im working on that one!

[ZiyueWang25]

This should be checked because people will input 'min_period' intended to achieve the functionality of 'min_periods', but it cannot be achieved. If we don't have 'groupby()' method before the rolling, then it will output "TypeError: rolling() got an unexpected keyword argument 'min_period'". I think this should apply to the case here as well. In short, we need a TypeError if we input min_period instead of min_periods.

[gabrielvf1]

I agree with you but lets see what @charlesdong1991 thinks just to check

[mroeschke]

This looks to raise an error correctly on master now. Could use a test

In [9]: test_df.groupby("name")["val"].rolling(window=2,min_period=1).sum()
TypeError: __init__() got an unexpected keyword argument 'min_period'

[horaceklai]

take