HyukjinKwon commented on a change in pull request #34007:
URL: https://github.com/apache/spark/pull/34007#discussion_r709564361
##########
File path: python/pyspark/pandas/accessors.py
##########
@@ -230,28 +231,24 @@ def apply_batch(
To avoid this, specify return type in ``func``, for instance, as
below:
- >>> def plus_one(x) -> ps.DataFrame[float, float]:
+ >>> def plus_one(x) -> ps.DataFrame[int, [float, float]]:
... return x + 1
If the return type is specified, the output column names become
`c0, c1, c2 ... cn`. These names are positionally mapped to the
returned
DataFrame in ``func``.
- To specify the column names, you can assign them in a pandas
friendly style as below:
+ To specify the column names, you can assign them in a NumPy
compound type style
+ as below:
- >>> def plus_one(x) -> ps.DataFrame["a": float, "b": float]:
+ >>> def plus_one(x) -> ps.DataFrame[("index", int), [("a", float),
("b", float)]:
Review comment:
```suggestion
>>> def plus_one(x) -> ps.DataFrame[("index", int), [("a",
float), ("b", float)]]:
```
##########
File path: python/pyspark/pandas/accessors.py
##########
@@ -439,28 +447,24 @@ def transform_batch(
To avoid this, specify return type in ``func``, for instance, as
below:
- >>> def plus_one(x) -> ps.DataFrame[float, float]:
+ >>> def plus_one(x) -> ps.DataFrame[int, [float, float]]:
... return x + 1
If the return type is specified, the output column names become
`c0, c1, c2 ... cn`. These names are positionally mapped to the
returned
DataFrame in ``func``.
- To specify the column names, you can assign them in a pandas
friendly style as below:
+ To specify the column names, you can assign them in a NumPy
compound type style
+ as below:
- >>> def plus_one(x) -> ps.DataFrame['a': float, 'b': float]:
+ >>> def plus_one(x) -> ps.DataFrame[("index", int), [("a", float),
("b", float)]:
Review comment:
```suggestion
>>> def plus_one(x) -> ps.DataFrame[("index", int), [("a",
float), ("b", float)]]:
```
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