type dataframe.transpose (#1136)

* type transpose

* remove undocumented methods, use *args: Any instead of undocumented axes

Author: MarcoGorelli

pandas-stubs/core/arrays/sparse/array.pyi

@@ -53,7 +53,6 @@ class SparseArray(ExtensionArray, ExtensionOpsMixin):
     def sum(self, axis: int = ..., *args, **kwargs): ...
     def cumsum(self, axis: int = ..., *args, **kwargs): ...
     def mean(self, axis: int = ..., *args, **kwargs): ...
-    def transpose(self, *axes): ...
     @property
     def T(self): ...
     def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): ...

pandas-stubs/core/base.pyi

@@ -44,7 +44,6 @@ class SelectionMixin(Generic[NDFrameT]):
 
 class IndexOpsMixin(OpsMixin, Generic[S1]):
     __array_priority__: int = ...
-    def transpose(self, *args, **kwargs) -> Self: ...
     @property
     def T(self) -> Self: ...
     @property

pandas-stubs/core/frame.pyi

@@ -656,7 +656,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         show_counts: bool | None = ...,
     ) -> None: ...
     def memory_usage(self, index: _bool = ..., deep: _bool = ...) -> Series: ...
-    def transpose(self, *args, copy: _bool = ...) -> Self: ...
+    def transpose(self, *args: Any, copy: _bool = ...) -> Self: ...
     @property
     def T(self) -> Self: ...
     def __getattr__(self, name: str) -> Series: ...

pandas-stubs/core/series.pyi

@@ -1535,7 +1535,6 @@ class Series(IndexOpsMixin[S1], NDFrame):
         bins: int | None = ...,
         dropna: _bool = ...,
     ) -> Series[float]: ...
-    def transpose(self, *args, **kwargs) -> Series[S1]: ...
     @property
     def T(self) -> Self: ...
     # The rest of these were left over from the old

tests/test_frame.py

@@ -4005,6 +4005,13 @@ def test_hashable_args() -> None:
 class GeoAccessor: ...
 
 
+def test_transpose() -> None:
+    df = pd.DataFrame({"a": [1, 1, 2], "b": [4, 5, 6]})
+    check(assert_type(df.transpose(), pd.DataFrame), pd.DataFrame)
+    check(assert_type(df.transpose(None), pd.DataFrame), pd.DataFrame)
+    check(assert_type(df.transpose(copy=True), pd.DataFrame), pd.DataFrame)
+
+
 def test_combine() -> None:
     df1 = pd.DataFrame({"A": [0, 0], "B": [4, 4]})
     df2 = pd.DataFrame({"A": [1, 1], "B": [3, 3]})