BUG: to_datetime raises "AttributeError: 'NoneType' object has no attribute 'total_seconds'" even with errors='coerce'

[enemyleft]

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Reproducible Example

import pandas as pd
# next line OK
date = pd.to_datetime("Wed, 1 Dec 2021 08:00:00 -0600 (CST)", errors='coerce', utc=True, format='mixed')
# next line raises Exception -> AttributeError: 'NoneType' object has no attribute 'total_seconds'
date = pd.to_datetime("Sun, 14 Apr 2024 20:00:00 +0200 (CET)", errors='coerce', utc=True, format='mixed')

Issue Description

I have many dates to parse, some have a TimeZone like "(CET)", "(CST)" and much others, some not. The format is not predictable, so I cannot pass a predefined format string. The shown examples may be similar here, but this is not the case in real life. After some hours of analysis I finally found one specific date, which actually raises an exception.

Sun, 14 Apr 2024 20:00:00 +0200 (CET)

Expected Behavior

First I would expect that with errors='coerce' no error will be raised even the format is completely wrong, it should instead return "NaT", as the documentation suggests.

Second to me there is no "big" difference between the working date string Wed, 1 Dec 2021 08:00:00 -0600 (CST) and the one that raises an error Sun, 14 Apr 2024 20:00:00 +0200 (CET). I.e. both have the same format, the biggest difference is the TimeZone abbreviation, which is present in both cases, but different. In fact, if I omit (CET), the string can be parsed correctly.

As a workaround I could manually check whether a TimeZone abbreviation is present and remove it prior to call to_datetime. Especially when the time offset is present as well, this information is kind of redundant, i.e. it should not even be of interest for to_datetime. But this workaround should not be necessary in my opinion, as I think this is a bug and should be resolved in "to_datetime".

See also a similar issue here: #54479. Although I cannot reproduce this in my environment.

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.12.5.final.0
python-bits : 64
OS : Linux
OS-release : 6.10.7-arch1-1
Version : #1 SMP PREEMPT_DYNAMIC Thu, 29 Aug 2024 16:48:57 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.2
numpy : 2.1.1
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : None
pip : 24.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : None
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report, I cannot reproduce on 64-bit linux, pandas 2.2.2 nor pandas 2.2.x, with the same versions of NumPy, pytz, and dateutil. Can you post a full stack trace of the error.

[enemyleft]

Thanks for the reply. I just reproduced it with a colleague, which is using MacOS and he also run into the same error. Here is the stack trace of MacOS:

test/import pandas as pd.py:10: FutureWarning: Parsing 'CET' as tzlocal (dependent on system timezone) is deprecated and will raise in a future version. Pass the 'tz' keyword or call tz_localize after construction instead
date = pd.to_datetime("Sun, 14 Apr 2024 20:00:00 +0200 (CET)", errors='coerce', utc=True, format=None)
/Users/test/import pandas as pd.py:10: UserWarning: Could not infer format, so each element will be parsed individually, falling back to dateutil. To ensure parsing is consistent and as-expected, please specify a format.
date = pd.to_datetime("Sun, 14 Apr 2024 20:00:00 +0200 (CET)", errors='coerce', utc=True, format=None)
Traceback (most recent call last):
File "/Users/test/import pandas as pd.py", line 10, in
date = pd.to_datetime("Sun, 14 Apr 2024 20:00:00 +0200 (CET)", errors='coerce', utc=True, format=None)
File "/Users/test/.venv/lib/python3.9/site-packages/pandas/core/tools/datetimes.py", line 1099, in to_datetime
result = convert_listlike(argc, format)
File "/Users/test/.venv/lib/python3.9/site-packages/pandas/core/tools/datetimes.py", line 435, in _convert_listlike_datetimes
result, tz_parsed = objects_to_datetime64(
File "/Users/test/.venv/lib/python3.9/site-packages/pandas/core/arrays/datetimes.py", line 2398, in objects_to_datetime64
result, tz_parsed = tslib.array_to_datetime(
File "tslib.pyx", line 414, in pandas._libs.tslib.array_to_datetime
File "tslib.pyx", line 578, in pandas._libs.tslib.array_to_datetime
AttributeError: 'NoneType' object has no attribute 'total_seconds'

[rhshadrach]

Thanks, from the Python docs the call to utcoffset here:

pandas/pandas/_libs/tslib.pyx

Line 578 in d9cdd2e

nsecs = tz.utcoffset(None).total_seconds()

can return None if the UTC offset isn't known. I'm not sure when this might happen, but it appears the logic should handle this case.

cc @jbrockmendel