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BUG: df.resample('MS', closed='right') incorrectly places bins #55271
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Thanks @dalejung for the report, will take a look Cc @natmokval we'll need to investigate this |
I'm not seeing this: In [1]: from pandas.tseries.frequencies import (
...: is_subperiod,
...: is_superperiod,
...: )
In [2]: is_superperiod('MS', 'D')
Out[2]: False EDITAh I see what you mean In [2]: from pandas.tseries.offsets import MonthBegin
In [3]: from pandas.tseries.frequencies import (
...: is_subperiod,
...: is_superperiod,
...: )
In [4]: is_superperiod(MonthBegin(), 'D')
Out[4]: True Indeed, this looks wrong - EDIT2Just noticed that this isn't a regression since 2.1, as the |
thanks, I'll take a look at it |
Right, this has lead me to uncover #55281 too... |
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
Issue Description
df.resample('MS', closed='right')
now includes a whole days worth of extra minutes.Notice the last time for 2020-01-01 lands on the last minute of the next day.
Previously this would show
2020-02-01 00:00:00
.This appears to the recent M => ME work.
is_superperiod("MS", "D")
now returns True where it used to be False. Granted that might be correct, but it triggers logic in_adjust_bin_edges
that gives us the erroneous results.Expected Behavior
Should land on midnight.
closed
semantics just chose which side the bin edges are placed in. It shouldn't shift the binedges 23 hours.Installed Versions
INSTALLED VERSIONS
commit : 86ecf05
python : 3.11.3.final.0
python-bits : 64
OS : Linux
OS-release : 6.4.12-arch1-1
Version : #1 SMP PREEMPT_DYNAMIC Thu, 24 Aug 2023 00:38:14 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.2.0dev0+278.g86ecf054a1
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : 0.29.33
pytest : 7.4.0
hypothesis : 6.47.1
sphinx : 6.2.1
blosc : 1.11.1
feather : None
xlsxwriter : 3.1.0
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : 1.0.3
psycopg2 : 2.9.6
jinja2 : 3.1.2
IPython : 8.16.0.dev
pandas_datareader : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : 2023.4.0
fsspec : 2023.5.0
gcsfs : 2023.5.0
matplotlib : 3.7.1
numba : 0.57.0
numexpr : 2.8.4
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 14.0.0.dev183+gaae5438eb
pyreadstat : 1.2.1
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2023.5.0
scipy : 1.10.1
sqlalchemy : 2.0.14
tables : 3.8.0
tabulate : 0.9.0
xarray : 2023.5.0
xlrd : 2.0.1
zstandard : 0.21.0
tzdata : 2023.3
qtpy : None
pyqt5 : None
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