itholic commented on a change in pull request #34212:
URL: https://github.com/apache/spark/pull/34212#discussion_r769173394
##########
File path: python/pyspark/pandas/series.py
##########
@@ -4485,6 +4489,170 @@ def replace(
return self._with_new_scol(current) # TODO: dtype?
+ def combine(
+ self,
+ other: "Series",
+ func: Callable,
+ fill_value: Optional[Any] = None,
+ ) -> "Series":
+ """
+ Combine the Series with a Series or scalar according to `func`.
+
+ Combine the Series and `other` using `func` to perform elementwise
+ selection for combined Series.
+ `fill_value` is assumed when value is missing at some index
+ from one of the two objects being combined.
+
+ .. versionadded:: 3.3.0
+
+ .. note:: this API executes the function once to infer the type which
is
+ potentially expensive, for instance, when the dataset is created
after
+ aggregations or sorting.
+
+ To avoid this, specify return type in ``func``, for instance, as
below:
+
+ >>> def foo(x, y) -> np.int32:
+ ... return x * y
+
+ pandas-on-Spark uses return type hint and does not try to infer
the type.
+
+ Parameters
+ ----------
+ other : Series or scalar
+ The value(s) to be combined with the `Series`.
+ func : function
+ Function that takes two scalars as inputs and returns an element.
+ Note that type hint for return type is required.
Review comment:
I think it's not "required", but "strongly recommended" ?
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