[I] Table.from_arrow can't import nan values into a non-null float column [arrow]

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

lord opened a new issue, #41812:
URL: https://github.com/apache/arrow/issues/41812

   ### Describe the bug, including details regarding any error messages, version, and platform.
   
   This small examples fails with `ValueError: Field pyarrow.Field<a: double not null> was non-nullable but pandas column had 1 null values` on 16.1.0.
   
   ```
   import pandas as pd
   import pyarrow as pa
   
   df = pd.DataFrame({"a": [1.0, float("nan")]})
   schema = pa.schema([pa.field('a', pa.float64(), nullable=False)])
   pa.Table.from_pandas(df, schema=schema)
   ```
   
   I guess this seems like a bug to me, but I'm no pandas expert. It does feel like this makes roundtripping a non-null float column through pandas impossible?
   
   ### Component(s)
   
   Python


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Re: [I] Table.from_arrow can't import nan values into a non-null float column [arrow]

["tlm365 (via GitHub)" <gi...@apache.org>]

tlm365 commented on issue #41812:
URL: https://github.com/apache/arrow/issues/41812#issuecomment-2131154054

   @lord You just need to change the parameter `nullable` to `True`, then it will work.
   ```python
   schema = pa.schema([pa.field('a', pa.float64(), nullable=True)])
   ```
   


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