Different behavior of DataFrame.resample() between pandas 0.16.2 and pandas 0.18.1

[adrien-pain-01]

I just upgraded my projects from pandas 0.16.2 to pandas 0.18.1, but I have a difference on some DataFrame.resample operations, with Weekly frequencies.

For instance, I want to resample daily data to weekly data (W-SUN), and apply an offset to the results, so each row will be a MONDAY and not a SUNDAY.

Code Sample

import pandas as pd
from datetime import timedelta
offset = +timedelta(days=1)

dates = pd.date_range("2001-01-01", freq="D", periods=18)]
a=pd.DataFrame(data=list(range(18)), columns=["value"], index=[dates])

a.resample("1W", how={"value": "sum"}, loffset=offset, closed="right", label="right")

Problem description

With pandas 0.16.2, I got this correct output:

            value
2001-01-08     21
2001-01-15     70
2001-01-22     62

ie, each row is a weekly aggregation of the data, and each date is a MONDAY

Resulting index is as follow:

a.index[0]
Timestamp('2001-01-08 00:00:00', offset='W-MON')

However, with pandas 0.18.1, I got this output:

            value
2001-01-07     21
2001-01-14     70
2001-01-21     62

each row is correctly aggregated, but the dates are SUNDAYs

Resulting index is as follow:

a.index[0]
Timestamp('2001-01-07 00:00:00', offset='W-SUN')

It's like the loffset parameter is not correctly taken into account in the new DataFrame.resample() implementation.

ie, the output with pandas 0.18.1 is the same as the one using pandas 0.16.2, but calling a.resample("1W", how={"value": "sum"}, loffset=None, closed="right", label="right")

Output of pd.show_versions()

pandas 0.16.1 installation:

INSTALLED VERSIONS
------------------
commit: None
python: 3.4.5.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-106-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.16.2
nose: 1.3.7
Cython: 0.22.1
numpy: 1.10.1
scipy: 0.16.0
statsmodels: 0.6.1
IPython: 3.2.1
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.7
bottleneck: 1.0.0
tables: 3.2.1
numexpr: 2.4.3
matplotlib: 1.5.0
openpyxl: 2.3.2
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.7
pymysql: 0.6.6.None
psycopg2: None

pandas 0.18.2 installation:

INSTALLED VERSIONS
------------------
commit: None
python: 3.4.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-57-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.22.1
numpy: 1.10.4
scipy: 0.16.0
statsmodels: 0.6.1
xarray: None
IPython: 3.2.1
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.6
blosc: None
bottleneck: 1.0.0
tables: 3.2.1
numexpr: 2.6.0
matplotlib: 1.4.3
openpyxl: 2.3.2
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.7
pymysql: 0.6.6.None
psycopg2: None
jinja2: 2.7.3
boto: None
pandas_datareader: None

[jreback]

duplicate of #13218

being addressed in #14213 expected to be in 0.20.0