[GitHub] [arrow] jorisvandenbossche commented on issue #35717: [Python] pa.array([Decimal("nan")]) raises

["jorisvandenbossche (via GitHub)" <gi...@apache.org>]

jorisvandenbossche commented on issue #35717:
URL: https://github.com/apache/arrow/issues/35717#issuecomment-1560707158

   Yes, for a generic sequence of python objects, we currently just check if an object is "null" or not using:
   
   https://github.com/apache/arrow/blob/53c0d338e6e45cb28a3c1973522da1257eaea761/python/pyarrow/src/arrow/python/helpers.cc#L359-L372
   
   but once we determined an object to be null, we don't take the actual type of object into account for the type inference.
   
   So that also means that currently you could mix all kinds of null-likes together when specifying `from_pandas=True` (also for cases where pandas would not allow this), for example:
   
   ```
   In [18]: pa.array([1, pd.NaT], from_pandas=True)
   Out[18]: 
   <pyarrow.lib.Int64Array object at 0x7fcb37d62ec0>
   [
     1,
     null
   ]
   ```


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