brokenjacobs opened a new issue, #37110:
URL: https://github.com/apache/arrow/issues/37110
### Describe the bug, including details regarding any error messages,
version, and platform.
Pyarrow: 12.0.1
This is similar to #32366 but not exactly the same. I have a dataset where I
am trying to filter by a column in my parquet files that is a timestamp with
timezone type. Every way that I try to do the filter, pyarrow coerces the type
to a non-timestamp type and fails to convert to a table. For example:
```
(ds is my dataset)
>>> dt
datetime.datetime(2023, 6, 29, 4, 0, tzinfo=<UTC>)
>>> dcast = pa.scalar(dt, type=pa.timestamp('ms', tz='UTC')
>>> filter = (ds.field('readout_time')>dcast)
>>> df = dataset.to_table(filter=filter,columns=['readout_time',
'acceleration_x', 'acceleration_y', 'acceleration_z']).to_pandas()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pyarrow/_dataset.pyx", line 546, in pyarrow._dataset.Dataset.to_table
File "pyarrow/_dataset.pyx", line 3449, in
pyarrow._dataset.Scanner.to_table
File "pyarrow/error.pxi", line 144, in
pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Cannot compare timestamp with timezone to
timestamp without timezone, got: timestamp[ms, tz=UTC] and timestamp[ms]
```
This was just my latest attempt to use an actual arrow scaler with timezone,
and it still changes the type to a non timestamp type in the comparison. It
also fails using a datetime in the filter directly.
### Component(s)
Python
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