jorisvandenbossche opened a new issue, #51302:
URL: https://github.com/apache/arrow/issues/51302

   Pandas has deprecated certain aspects of `.values` (when it looses 
information), which our pandas->pyarrow conversion currently relies upon, so in 
the tests with pandas nightly we are seeing a lot of warnings because of that 
(https://github.com/ursacomputing/crossbow/actions/runs/34548523730/job/103106277981).
   
   Small illustration:
   
   ```python
   >>> import pandas as pd
   >>> import pyarrow as pa
   >>> ser = pd.Series(pd.date_range("2025-01-01", periods=3, tz="UTC"))
   >>> pa.array(ser)
   <python-input-4>:1: Pandas4Warning: Series.values returning an ndarray that 
drops timezone information for DatetimeTZDtype is deprecated. In a future 
version, this will return the underlying DatetimeArray instead. Use 
'Series.to_numpy()' to get a NumPy array, or 'Series.array' to get the 
ExtensionArray.
   <pyarrow.lib.TimestampArray object at 0x7ff624fb1a20>
   [
     2025-01-01 00:00:00.000000Z,
     2025-01-02 00:00:00.000000Z,
     2025-01-03 00:00:00.000000Z
   ]
   ```
   
   This is caused by our handling of a Series object in `pa.array(..)`:
   
   
https://github.com/apache/arrow/blob/07be48c5402adedb68c510531939a907ffbac237/python/pyarrow/array.pxi#L5396-L5407
   
   and
   
   
https://github.com/apache/arrow/blob/07be48c5402adedb68c510531939a907ffbac237/python/pyarrow/pandas-shim.pxi#L231-L242
   
   So we already have some custom handling for Period/Interval, but that will 
also be needed for DatetimeTZDtype


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