Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
ts = pd.Series(1, pd.date_range("2022-10-28", "2022-11-10", tz="Atlantic/Azores", freq="15min"))
ts.resample("W").sum()Issue Description
Above code raises:
pytz.exceptions.AmbiguousTimeError: Cannot infer dst time from 2022-10-30 00:00:00, try using the 'ambiguous' argument
At first, I thought, maybe that's indeed not possible.
Expected Behavior
But then I saw that no error is raised when resampling to daily resolution:
import pandas as pd
ts = pd.Series(1, pd.date_range("2022-10-28", "2022-11-10", tz="Atlantic/Azores", freq="15min"))
ts.resample("D").sum()So, if resampling to daily works, shouldn't it also work when resampling to weekly?
Installed Versions
INSTALLED VERSIONS
commit : 2e218d1
python : 3.10.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Belgium.1252
pandas : 1.5.3
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.1.0
pip : 23.0
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.7
lxml.etree : 4.9.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : 1.3.6
brotli : None
fastparquet : 2023.1.0
fsspec : 2021.11.0
gcsfs : None
matplotlib : 3.6.2
numba : None
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2021.11.0
scipy : 1.10.0
snappy : None
sqlalchemy : None
tables : None
tabulate : 0.8.10
xarray : 2022.12.0
xlrd : None
xlwt : None
zstandard : None
tzdata : None