startingMonth ignored on non-unitary Quarter periods

[aulemahal]

Code Sample

import pandas as pd
import numpy as np

d = pd.Series(data=np.zeros(365), 
                       index=pd.date_range('1950-01-01', '1950-12-31', freq='D'))
d.resample('2QS-MAR').mean()

returns:

1949-12-01    0.0
1950-06-01    0.0
1950-12-01    0.0
Freq: 2QS-MAR, dtype: float64

But as I explicitly asked for 2 Quarters starting in March, I expected:

1949-09-01    0.0
1950-03-01    0.0
1950-09-01    0.0
Freq: 2QS-MAR, dtype: float64

So, when specifying a multiple, the first time still goes to the closest single quarter before.

Not really a duplicate, but closely related to #22362.

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : None python : 3.7.3.final.0 python-bits : 64 OS : Linux OS-release : 4.15.0-66-generic machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : fr_CA.UTF-8 LOCALE : fr_CA.UTF-8

pandas : 0.25.3
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.1
pip : 9.0.1
setuptools : 39.0.1
Cython : None
pytest : 5.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : 0.999999999
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.8.1
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : None
tables : None
xarray : 0.13.0
xlrd : None
xlwt : None
xlsxwriter : None

[mroeschke]

This looks to work on main now. Could use a test

[idor980]

take

[idor980]

This looks to work on main now. Could use a test

I am currently using version 2.0.1 of Pandas and this specific problem isn’t fixed.

[joshdelg]

take

[quangngd]

Did some digging and i think it is because of the implementation of offset. rollback and rollforward do not take n into account.

offset = QuarterBegin(startingMonth=1, n=2) #2QS
dt = pd.Timestamp("1950-01-02")
offset.rollback(dt), offset.rollforward(dt)

and

offset = QuarterBegin(startingMonth=1, n=1) #QS
dt = pd.Timestamp("1950-01-02")
offset.rollback(dt), offset.rollforward(dt)

both return (Timestamp('1950-01-01 00:00:00'), Timestamp('1950-04-01 00:00:00')).

@mroeschke please confirm if this is expected or not.

[KatsiarynaDzibrova]

take