Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] 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
In [57]: import pandas
In [58]: pandas.to_datetime("2023-01-01T15:58:12+09:00", format="%Y-%m-%dT%H:%M:%S.%f%z")
---------------------------------------------------------------------------
ValueError: time data "2023-01-01T15:58:12+09:00" doesn't match format "%Y-%m-%dT%H:%M:%S.%f%z", at position 0. You might want to try:
- passing `format` if your strings have a consistent format;
- passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format;
- passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this.
Issue Description
The above code had ValueError in pandas 2.0.1. But in pandas 1.5.3, the above code had not error.
The above code raised a ValueError in pandas 2.0.1. However, there were no errors in the same code when run with pandas 1.5.3.
Expected Behavior
I expect the above code to not have any errors.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 37ea63d540fd27274cad6585082c91b1283f963d
python : 3.11.2.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-70-generic
Version : #77-Ubuntu SMP Tue Mar 21 14:02:37 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : ja_JP.UTF-8
LOCALE : ja_JP.UTF-8
pandas : 2.0.1
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 65.5.0
pip : 23.0.1
Cython : None
pytest : 7.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.11.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None
Comment From: MarcoGorelli
thanks for the report
the datetime string you posted doesn't have subseconds (%f), but your format string does. it was wrong in 1.5.3 to parse this
closing for now then