BUG: DateOffset default temporal pattern does not work as expected with DST

[ValentinBilla]

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

# https://www.timeanddate.com/time/change/belgium/brussels?year=2022
ts = pd.Timestamp("2022-10-30", tz="Europe/Brussels")

offset_explicit_keyword = ts + pd.offsets.DateOffset(days=1)
offset_default_value = ts + pd.offsets.DateOffset(1)

assert offset_explicit_keyword == offset_default_value

Issue Description

According to the documentation, pd.offsets.DateOffset(1) should be the same as pd.offsets.DateOffset(days=1)

During instanciation the following function is called :

pandas/pandas/_libs/tslibs/offsets.pyx

Lines 284 to 334 in bc6ad14

	cdef _determine_offset(kwds):
	if not kwds:
	# GH 45643/45890: (historically) defaults to 1 day
	return timedelta(days=1), False
	if "millisecond" in kwds:
	raise NotImplementedError(
	"Using DateOffset to replace `millisecond` component in "
	"datetime object is not supported. Use "
	"`microsecond=timestamp.microsecond % 1000 + ms * 1000` "
	"instead."
	)
	nanos = {"nanosecond", "nanoseconds"}
	# nanos are handled by apply_wraps
	if all(k in nanos for k in kwds):
	return timedelta(days=0), False
	kwds_no_nanos = {k: v for k, v in kwds.items() if k not in nanos}
	kwds_use_relativedelta = {
	"year", "month", "day", "hour", "minute",
	"second", "microsecond", "weekday", "years", "months", "weeks", "days",
	"hours", "minutes", "seconds", "microseconds"
	}
	# "weeks" and "days" are left out despite being valid args for timedelta,
	# because (historically) timedelta is used only for sub-daily.
	kwds_use_timedelta = {
	"seconds", "microseconds", "milliseconds", "minutes", "hours",
	}
	if all(k in kwds_use_timedelta for k in kwds_no_nanos):
	# Sub-daily offset - use timedelta (tz-aware)
	# This also handles "milliseconds" (plur): see GH 49897
	return timedelta(**kwds_no_nanos), False
	# convert milliseconds to microseconds, so relativedelta can parse it
	if "milliseconds" in kwds_no_nanos:
	micro = kwds_no_nanos.pop("milliseconds") * 1000
	kwds_no_nanos["microseconds"] = kwds_no_nanos.get("microseconds", 0) + micro
	if all(k in kwds_use_relativedelta for k in kwds_no_nanos):
	from dateutil.relativedelta import relativedelta
	return relativedelta(**kwds_no_nanos), True
	raise ValueError(
	f"Invalid argument/s or bad combination of arguments: {list(kwds.keys())}"
	)

For pd.offsets.DateOffset(1) it returns timedelta(days=1), False, whereas for pd.offsets.DateOffset(days=1) this returns relativedelta(days=1), True. This causes inconsistencies in the behavior of the two near DST transitions.

Expected Behavior

Either the doc can be changed or we ensure pd.offsets.DateOffset(1) equals pd.offsets.DateOffset(days=1) by my understanding this could be done in the following way

cdef _determine_offset(kwds):
     if not kwds:  
+        from dateutil.relativedelta import relativedelta 
+
         # GH 45643/45890: (historically) defaults to 1 day 
-        return timedelta(days=1), False 
+        return relativedelta(days=1), True

Installed Versions

INSTALLED VERSIONS

commit : c888af6
python : 3.12.10
python-bits : 64
OS : Darwin
OS-release : 24.5.0
Version : Darwin Kernel Version 24.5.0: Tue Apr 22 19:54:25 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8

pandas : 2.3.1
numpy : 2.3.1
pytz : 2025.2
dateutil : 2.9.0.post0
pip : None
Cython : None
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None