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After updating pandas from 1.5.3 to 2.1.2 the behaviour of DateOffset has changed. When executing datetime(2020, 1, 1) + pd.DateOffset(days=1.5) I obtain datetime(2020, 1, 2) rather than datetime(2020, 1, 2, 12) . In the latter case datetime(2020, 1, 1) + pd.DateOffset(hours=1.5) I obtain the expected datetime(2020, 1, 1, 1, 30).
Expected Behavior
The expected behaviour should either be an Exception, when executing pd.DateOffset(days=1.5) with a non-integer input or the datetime(2020, 1, 2, 12).
bisecting finds this first cropped up in this PR: 53681.
Summary: The line that causes this behaviour is this: offsets.pyx#L1356. This is due to how the relativedelta from dateutil handles multiplication incorrectly. I'm raising a bug report with them.
Tracing down, there is some interesting behaviour starting with the following setup:
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
After updating pandas from 1.5.3 to 2.1.2 the behaviour of DateOffset has changed. When executing
datetime(2020, 1, 1) + pd.DateOffset(days=1.5)
I obtaindatetime(2020, 1, 2)
rather thandatetime(2020, 1, 2, 12)
. In the latter casedatetime(2020, 1, 1) + pd.DateOffset(hours=1.5)
I obtain the expecteddatetime(2020, 1, 1, 1, 30)
.Expected Behavior
The expected behaviour should either be an Exception, when executing
pd.DateOffset(days=1.5)
with a non-integer input or thedatetime(2020, 1, 2, 12)
.Installed Versions
INSTALLED VERSIONS
commit : a60ad39
python : 3.9.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : de_DE.cp1252
pandas : 2.1.2
numpy : 1.26.1
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : 3.0.5
pytest : 7.4.3
hypothesis : None
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : 3.1.9
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.17.2
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.1
numba : 0.58.1
numexpr : 2.8.7
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 14.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.1
sqlalchemy : None
tables : 3.9.1
tabulate : 0.9.0
xarray : None
xlrd : 2.0.1
zstandard : None
tzdata : 2023.3
qtpy : 2.4.1
pyqt5 : None
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