BUG: Grouper: Origin param has no effect

Pandas version checks

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

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

df = pd.DataFrame([{"A": A, "datadate": datadate} 
                         for A in range(1,3) 
                         for datadate in pd.date_range(start='1/2/2022', end='2/1/2022', freq='D')])

ddg = df.groupby(["A", pd.Grouper(key="datadate", freq='W', origin='start')])

for i, dfg in ddg:
    print(dfg[["A", "datadate"]])
    print("-----------------------")


ddg = df.groupby(["A", pd.Grouper(key="datadate", freq='W', origin='1/5/2022')])

for i, dfg in ddg:
    print(dfg[["A", "datadate"]])
    print("-----------------------")

Issue Description

Whatever I set on the origin parameter of pd.Grouper, whether it is startor a date, it groups by starting on a Monday. If I remove the origin parameter, I get the same results.

Expected Behavior

The data are grouped weekly starting by the fixed timestamp provided by the origin parameter.

Installed Versions

INSTALLED VERSIONS

commit : e8093ba372f9adfe79439d90fe74b0b5b6dea9d6 python : 3.8.13.final.0 python-bits : 64 OS : Darwin OS-release : 21.5.0 Version : Darwin Kernel Version 21.5.0: Tue Apr 26 21:08:37 PDT 2022; root:xnu-8020.121.3~4/RELEASE_ARM64_T6000 machine : arm64 processor : arm byteorder : little LC_ALL : None LANG : None LOCALE : None.UTF-8

pandas : 1.4.3 numpy : 1.21.6 pytz : 2022.1 dateutil : 2.8.2 setuptools : 61.2.0 pip : 21.2.4 Cython : 0.29.30 pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : 4.9.0 html5lib : None pymysql : 1.0.2 psycopg2 : None jinja2 : 3.1.1 IPython : 8.2.0 pandas_datareader: None bs4 : 4.9.1 bottleneck : None brotli : None fastparquet : None fsspec : 2022.5.0 gcsfs : None markupsafe : 2.1.1 matplotlib : 3.5.2 numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 8.0.0 pyreadstat : None pyxlsb : None s3fs : 2022.5.0 scipy : 1.8.0 snappy : None sqlalchemy : 1.4.32 tables : None tabulate : 0.8.10 xarray : None xlrd : None xlwt : None zstandard : None

[houseofai]

@hamedgibago Yes, thanks

[houseofai]

@DBCerigo Thanks for pointing out, indeed W-TUE doesn’t raise an error.

ddg = df.groupby(["A", pd.Grouper(key="datadate", freq='W-TUE')])

for i, dfg in ddg:
    print(dfg[["A", "datadate"]])
    print("-----------------------")

Gives:

   A   datadate
0  1 2022-01-02
1  1 2022-01-03
2  1 2022-01-04
-----------------------
   A   datadate
3  1 2022-01-05
4  1 2022-01-06
5  1 2022-01-07
6  1 2022-01-08
7  1 2022-01-09
8  1 2022-01-10
9  1 2022-01-11
-----------------------

Note that the first date,2022-01-05, is a Wednesday.

The only way to start the week from the first date is to find the day of the first date (here 2022-01-02 - Sunday), and to set it to the day before:

ddg = df.groupby(["A", pd.Grouper(key="datadate", freq='W-SAT')])

 A   datadate
0  1 2022-01-02
1  1 2022-01-03
2  1 2022-01-04
3  1 2022-01-05
4  1 2022-01-06
5  1 2022-01-07
6  1 2022-01-08
-----------------------
    A   datadate
7   1 2022-01-09
8   1 2022-01-10
9   1 2022-01-11
...

Could you please confirm that is the expected behavior with the frequency parameter?

And I insist but the origin parameter doesn’t have any effect.