zhengruifeng commented on code in PR #52393:
URL: https://github.com/apache/spark/pull/52393#discussion_r2373755031
##########
python/pyspark/pandas/frame.py:
##########
@@ -11201,8 +11208,14 @@ def any(self, axis: Axis = 0, bool_only:
Optional[bool] = None) -> "Series":
applied: List[PySparkColumn] = []
for label in column_labels:
scol = self._internal.spark_column_for(label)
- any_col = F.max(F.coalesce(scol.cast("boolean"), F.lit(False)))
- applied.append(F.when(any_col.isNull(), False).otherwise(any_col))
+ if skipna:
+ # When skipna=True, nulls count as False
+ any_col = F.max(F.coalesce(scol.cast("boolean"), F.lit(False)))
+ applied.append(F.when(any_col.isNull(),
False).otherwise(any_col))
+ else:
+ # When skipna=False, nulls count as True
+ any_col = F.max(scol.cast("boolean"))
Review Comment:
I still feel it is a bit weird to use function `max` here, which relies on
the ordering of `null/true/false`.
maybe we can use function `some/bool_or` instead.
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