[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36452: [SPARK-39109][PYTHON] Adjust `GroupBy.mean/median` to match pandas 1.4

[GitBox <gi...@apache.org>]

xinrong-databricks commented on code in PR #36452:
URL: https://github.com/apache/spark/pull/36452#discussion_r867029180


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python/pyspark/pandas/groupby.py:
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@@ -2673,7 +2682,7 @@ def get_group(self, name: Union[Name, List[Name]]) -> FrameLike:
 
         return self._cleanup_and_return(DataFrame(internal))
 
-    def median(self, numeric_only: bool = True, accuracy: int = 10000) -> FrameLike:
+    def median(self, numeric_only: Optional[bool] = True, accuracy: int = 10000) -> FrameLike:

Review Comment:
   
   - DataFrameGroupBy
   numeric_only=True/False/None -converts to-> numeric_only=True
   
   In pandas, when numeric_only is False/None, a FutureWarning will be raised, and then numeric_only is converted to True.
   
   **So I think setting True as the default value in pandas-on-Spark for numeric_only makes sense in this case**.
   
   - SeriesGroupBy
   numeric_only=None -converts to-> numeric_only=False
   
   **So setting False as the default value in pandas-on-Spark for numeric_only seems fine**.
   
   How do you think about that? @HyukjinKwon @Yikun 



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