Description
Pandas version checks
-
I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas.
-
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
timestr = '2023-11-05T08:30:00Z'
ts = pd.Timestamp.fromisoformat(timestr)
assert ts == pd.to_datetime(timestr)
timestr = '2023-11-05T08:30:00+0000'
ts = pd.Timestamp.fromisoformat(timestr)
assert ts == pd.to_datetime(timestr)
ts = pd.Timestamp.utcnow()
assert ts == pd.Timestamp.fromisoformat(ts.isoformat())
Issue Description
Timestamp.fromisoformat seems to ignore timezone offsets in the ISO 8601 formatted string, and returns a timezone-naive Timestamp. This issue does not seem to be present for pd.to_datetime, which does return the correct timezone-aware Timestamp. By consequence, the roundtrip conversion pd.Timestamp.fromisoformat(ts.isoformat()) loses the timezone information.
Expected Behavior
I would expect the Timestamp returned by fromisoformat to be time-zone aware, if the ISO string has UTC offset information. This is the behavior of the datetime.datetime objects from the standard library.
Installed Versions
INSTALLED VERSIONS
commit : 3d492f1
python : 3.11.6.final.0
python-bits : 64
OS : Linux
OS-release : 6.6.3-arch1-1
Version : #1 SMP PREEMPT_DYNAMIC Wed, 29 Nov 2023 00:37:40 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.utf8
LOCALE : en_US.UTF-8
pandas : 2.2.0.dev0+831.g3d492f1750
numpy : 1.26.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 65.5.0
pip : 23.2.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.17.2
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.3
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None