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Showing content from https://github.com/pandas-dev/pandas/issues/52284 below:

Cannot access Timedelta properties with Arrow Backend · Issue #52284 · pandas-dev/pandas · GitHub

• 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.

>>> td = pd.Series([pd.Timedelta(seconds=30)], dtype=pd.ArrowDtype(pa.duration("us")))
>>> td
0    0:00:30
dtype: duration[us][pyarrow]
>>> td.dt.seconds
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\ps_0310_is\lib\site-packages\pandas\core\generic.py", line 5973, in __getattr__
    return object.__getattribute__(self, name)
  File "C:\ps_0310_is\lib\site-packages\pandas\core\accessor.py", line 224, in __get__
    accessor_obj = self._accessor(obj)
  File "C:\ps_0310_is\lib\site-packages\pandas\core\indexes\accessors.py", line 577, in __new__
    raise AttributeError("Can only use .dt accessor with datetimelike values")
AttributeError: Can only use .dt accessor with datetimelike values
>>>

.dt should be supported with datetime and timedeltas. With numpy, the code above would work.

>>> td = pd.Series([pd.Timedelta(seconds=30)])
>>> td.dt.seconds
0    30
dtype: int32
>>>

pd.show_versions()

commit : 1a2e300
python : 3.8.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.0.0rc0
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.2.0
pip : 22.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : 2023.2.0
fsspec : 2023.3.0
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 : None
qtpy : None
pyqt5 : None

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