dgd-contributor commented on a change in pull request #33858:
URL: https://github.com/apache/spark/pull/33858#discussion_r703242599
##########
File path: python/pyspark/pandas/series.py
##########
@@ -4475,6 +4477,146 @@ def replace(
return self._with_new_scol(current) # TODO: dtype?
+ def combine(
+ self,
+ other: "Series",
+ func: Callable,
+ fill_value: Optional[Any] = None,
+ return_type: Union[Union[AtomicType, str], ArrayType] = "string",
+ ) -> "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
+
+ 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.
+ fill_value : scalar, optional
+ The value to assume when an index is missing from
+ one Series or the other. The default specifies to use the
+ appropriate NaN value for the underlying dtype of the Series.
+ return_type : :class:`pyspark.sql.types.DataType` or str
+ the return type of the output Series. The value can be either a
+ :class:`pyspark.sql.types.DataType` object or a DDL-formatted type
string.
Review comment:
thank for you comments, I have learned a lot. If I have
``` python
>>> pdf = pd.DataFrame({"s1": [1, 2, 3], "s2": [4, 5, 6]})
>>> psdf = ps.from_pandas(pdf)
>>> def true_div(s1: int, s2: int) -> float:
>>> return s1 / s2
>>> pdf["s1"].combine(pdf["s2"], true_div),
0 0.25
1 0.40
2 0.50
dtype: float64
float64
>>> psdf["s1"].combine(psdf["s2"], true_div),
0 0
1 0
2 0
dtype: int64
int64
```
I think the output's dtype should not be the self's dtype. I stuck with
this.
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