Spenserrrr opened a new pull request, #58847: URL: https://github.com/apache/spark/pull/58847
### What changes were proposed in this pull request? Documents how pandas-on-Spark's NumPy compatibility mappings derive result types from their Spark SQL expressions. It also clarifies the pandas behavior used by the operand-type table and the different handling of boolean columns and Python boolean scalars. ### Why are the changes needed? The existing code does not explain why a float32 input can produce a float64 result for Spark-backed math functions such as `sqrt`, `modf`, and `frexp`. Recording the rationale near each mapping family helps distinguish expected result typing from operand casts that can change values or accepted inputs. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Verified with a focused runtime probe covering result dtypes, boolean dispatch, `fmod` coercion, and scalar overflow behavior; the PySpark pre-push checks also passed. ### Was this patch authored or co-authored using generative AI tooling? Generated-by: Codex (GPT-5) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
