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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.
import pandas as pd import pyarrow as pa pa_arr = pa.array([ datetime.date(2024, 1, 1), datetime.date(2024, 1, 2), datetime.date(2024, 1, 3), ]) ser = pd.Series(pa_arr, dtype=pd.ArrowDtype(pa.date32())) ser.iloc[0] = datetime.datetime(2024, 12, 31, 12, 20, 0)
Assigning a datetime value to a pyarrow date array type seems to implicitly drop the time components
Should raise TypeError
In [24]: pd.version Out[24]: '3.0.0.dev0+681.g434fda08cf'
In [25]: pa.version Out[25]: '15.0.0'
The text was updated successfully, but these errors were encountered:
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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
Issue Description
Assigning a datetime value to a pyarrow date array type seems to implicitly drop the time components
Expected Behavior
Should raise TypeError
Installed Versions
In [24]: pd.version
Out[24]: '3.0.0.dev0+681.g434fda08cf'
In [25]: pa.version
Out[25]: '15.0.0'
The text was updated successfully, but these errors were encountered: