BUG: Incorrect timedelta with tz_localize and nonexistent times

[katbot99]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

---

Code Sample, a copy-pastable example

s = pd.Series(range(2),
              index=pd.DatetimeIndex(['2021-03-28 01:30:00',
                                      '2021-03-28 02:30:00']))
s.tz_localize('Europe/London', nonexistent=pd.Timedelta('1H'))

2021-03-28 03:30:00+01:00    0
2021-03-28 02:30:00+01:00    1
dtype: int64

Problem description

Using Timedelta with the nonexistent flag with tz_localize is adding 2 hours instead of 1 hour for nonexistent times in 'Europe/London' tz. DST started on 2021-03-28 when 59:59 > 02:00 so '2021-03-28 01:30:00' is nonexistent. When I run almost the same code from the docs with 'Europe/Warsaw' the bug does not occur:

s = pd.Series(range(2),
              index=pd.DatetimeIndex(['2021-03-28 02:30:00',
                                      '2021-03-28 03:30:00']))
s.tz_localize('Europe/Warsaw', nonexistent=pd.Timedelta('1H'))

2021-03-28 03:30:00+02:00    0
2021-03-28 03:30:00+02:00    1
dtype: int64

Expected Output

2021-03-28 02:30:00+01:00    0
2021-03-28 02:30:00+01:00    1
dtype: int64

Output of pd.show_versions()

INSTALLED VERSIONS

commit : f2c8480
python : 3.8.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252

pandas : 1.2.3
numpy : 1.19.5
pytz : 2020.5
dateutil : 2.8.1
pip : 20.3.3
setuptools : 51.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.6
pandas_gbq : None
pyarrow : 2.0.0
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

[mroeschke]

Thanks for the report. I suspect this has the same underlying issue as #40915

[thomie]

This issue, just like #40915, seems to be fixed (I only tested with version 2.3.1):

>>> s = pd.Series(range(2), index=pd.DatetimeIndex(['2021-03-28 01:30:00', '2021-03-28 02:30:00']))
>>> s.tz_localize('Europe/London', nonexistent=pd.Timedelta('1h'))
2021-03-28 02:30:00+01:00    0
2021-03-28 02:30:00+01:00    1
dtype: int64 

Output of pd.show_versions()

Details

INSTALLED VERSIONS

commit : c888af6
python : 3.12.11
python-bits : 64
OS : Linux
OS-release : 6.12.41
Version : #1-NixOS SMP PREEMPT_DYNAMIC Fri Aug 1 08:48:47 UTC 2025
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
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 : 9.4.0
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 : 20.0.0
pyreadstat : None
pytest : 8.4.1
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.42
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None