BUG: to_datetime raises when errors=coerce and infer_datetime_format · Issue #48633 · pandas-dev/pandas (original) (raw)

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

pd.to_datetime(["200622-12-31", "111111-24-11"], errors='coerce', infer_datetime_format=True)

Issue Description

Traceback (most recent call last):
  File "t.py", line 7, in <module>
    pd.to_datetime(["200622-12-31", "111111-24-11"], errors='coerce', infer_datetime_format=True)
  File "/home/marcogorelli/pandas-dev/pandas/core/tools/datetimes.py", line 1124, in to_datetime
    result = convert_listlike(argc, format)
  File "/home/marcogorelli/pandas-dev/pandas/core/tools/datetimes.py", line 418, in _convert_listlike_datetimes
    format = _guess_datetime_format_for_array(arg, dayfirst=dayfirst)
  File "/home/marcogorelli/pandas-dev/pandas/core/tools/datetimes.py", line 132, in _guess_datetime_format_for_array
    return guess_datetime_format(arr[non_nan_elements[0]], dayfirst=dayfirst)
  File "pandas/_libs/tslibs/parsing.pyx", line 1029, in pandas._libs.tslibs.parsing.guess_datetime_format
    tokens[offset_index] = parsed_datetime.strftime("%z")
ValueError: offset must be a timedelta strictly between -timedelta(hours=24) and timedelta(hours=24).

Note that this is different from #46071, because here the error happens when pandas is still guessing the format

Expected Behavior

DatetimeIndex(['NaT', 'NaT'], dtype='datetime64[ns]', freq=None)

Installed Versions

Replace this line with the output of pd.show_versions()

INSTALLED VERSIONS

commit : bf856a8
python : 3.8.13.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.16.3-microsoft-standard-WSL2
Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 1.6.0.dev0+145.gbf856a85a3
numpy : 1.22.4
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.3
hypothesis : 6.54.5
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.5.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.3
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.5.3
numba : 0.55.2
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.8
pyarrow : 9.0.0
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.9.1
snappy :
sqlalchemy : 1.4.41
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : 0.18.0
tzdata : None
None