HyukjinKwon commented on a change in pull request #34058:
URL: https://github.com/apache/spark/pull/34058#discussion_r714712795
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File path: python/pyspark/pandas/typedef/typehints.py
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@@ -690,98 +696,146 @@ def create_tuple_for_frame_type(params: Any) -> object:
Typing data columns with an index:
>>> ps.DataFrame[int, [int, int]] # doctest: +ELLIPSIS
- typing.Tuple[...IndexNameType, int, int]
+ typing.Tuple[...IndexNameType, ...NameType, ...NameType]
>>> ps.DataFrame[pdf.index.dtype, pdf.dtypes] # doctest: +ELLIPSIS
- typing.Tuple[...IndexNameType, numpy.int64]
+ typing.Tuple[...IndexNameType, ...NameType]
>>> ps.DataFrame[("index", int), [("id", int), ("A", int)]] #
doctest: +ELLIPSIS
typing.Tuple[...IndexNameType, ...NameType, ...NameType]
>>> ps.DataFrame[(pdf.index.name, pdf.index.dtype), zip(pdf.columns,
pdf.dtypes)]
... # doctest: +ELLIPSIS
typing.Tuple[...IndexNameType, ...NameType]
+
+ Typing data columns with an Multi-index:
+ >>> arrays = [[1, 1, 2], ['red', 'blue', 'red']]
+ >>> idx = pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
+ >>> pdf = pd.DataFrame({'a': range(3)}, index=idx)
+ >>> ps.DataFrame[[int, int], [int, int]] # doctest: +ELLIPSIS
+ typing.Tuple[...IndexNameType, ...IndexNameType, ...NameType,
...NameType]
+ >>> ps.DataFrame[pdf.index.dtypes, pdf.dtypes] # doctest: +ELLIPSIS
+ typing.Tuple[...IndexNameType, ...NameType]
+ >>> ps.DataFrame[[("index-1", int), ("index-2", int)], [("id", int),
("A", int)]]
+ ... # doctest: +ELLIPSIS
+ typing.Tuple[...IndexNameType, ...IndexNameType, ...NameType,
...NameType]
+ >>> ps.DataFrame[zip(pdf.index.names, pdf.index.dtypes),
zip(pdf.columns, pdf.dtypes)]
+ ... # doctest: +ELLIPSIS
+ typing.Tuple[...IndexNameType, ...NameType]
"""
return Tuple[extract_types(params)]
# TODO(SPARK-36708): numpy.typing (numpy 1.21+) support for nested types.
def extract_types(params: Any) -> Tuple:
Review comment:
feel free to name it `_extract_types`.
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