BUG: pd.infer_freq incompatible with Series["timestamp[s][pyarrow]"].

[randolf-scholz]

Pandas version checks

• I have checked that this issue has not already been reported.

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Reproducible Example

import pandas as pd

data = ["2022-01-01T10:00:00", "2022-01-01T10:00:30", "2022-01-01T10:01:00"]
pd_series = pd.Series(data).astype("timestamp[s][pyarrow]")
pd_index = pd.Index(data).astype("timestamp[s][pyarrow]")
assert pd.infer_freq(pd_index.values) == "30s"  # ✅
assert pd.infer_freq(pd_series.values) == "30s"  # ✅
assert pd.infer_freq(pd_index) == "30s"  # ✅
assert pd.infer_freq(pd_series) == "30s"  # ❌

Issue Description

TypeError: cannot infer freq from a non-convertible dtype on a Series of timestamp[s][pyarrow]

However, it works with Index-objects of this dtype, or if we call .values (which converts it to list[pd.Timedelta])

Expected Behavior

There should be no TypeError here, especially since it works with Index objects of this dtype.

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.11.7.final.0
python-bits : 64
OS : Linux
OS-release : 6.5.0-28-generic
Version : #29~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Thu Apr 4 14:39:20 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 69.5.1
pip : 24.0
Cython : None
pytest : 8.1.1
hypothesis : 6.100.1
sphinx : 7.3.7
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.23.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.3.1
gcsfs : None
matplotlib : 3.8.4
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 16.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.13.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None