Yicong-Huang opened a new pull request, #53310:
URL: https://github.com/apache/spark/pull/53310
### What changes were proposed in this pull request?
This PR fixes SPARK-54579: `createDataFrame` incorrectly handles NaN in
pandas DataFrame when arrow-optimization is enabled. Also re-enabled
`test_with_none_and_nan` for SPARK-54575.
1. For floating-point Arrow types (float32, float64):
- For object dtype Series: Track positions that were originally `None`,
convert the Series to float64, then create a mask that only masks those
original `None` positions (not NaN positions)
- For float64 dtype Series: Don't mask NaN values (use an all-False mask)
to preserve NaN
2. For non-floating types: Continue to mask both `None` and `NaN` as before
### Why are the changes needed?
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