move to v1.4.0 whatsnew, declare type before if

doc/source/whatsnew/v1.3.0.rst

@@ -700,8 +700,6 @@ Other API changes
 ^^^^^^^^^^^^^^^^^
 - Partially initialized :class:`CategoricalDtype` objects (i.e. those with ``categories=None``) will no longer compare as equal to fully initialized dtype objects (:issue:`38516`)
 - Accessing ``_constructor_expanddim`` on a :class:`DataFrame` and ``_constructor_sliced`` on a :class:`Series` now raise an ``AttributeError``. Previously a ``NotImplementedError`` was raised (:issue:`38782`)
-- Added new ``engine`` and ``**engine_kwargs`` parameters to :meth:`DataFrame.to_sql` to support other future "SQL engines". Currently we still only use ``SQLAlchemy`` under the hood, but more engines are planned to be supported such as ``turbodbc`` (:issue:`36893`)
-- Calling ``hash`` on non-hashable pandas objects will now raise ``TypeError`` with the built-in error message (e.g. ``unhashable type: 'Series'``). Previously it would raise a custom message such as ``"'Series' objects are mutable, thus they cannot be hashed"`` (:issue:`40013`)
 - Added new ``engine`` and ``**engine_kwargs`` parameters to :meth:`DataFrame.to_sql` to support other future "SQL engines". Currently we still only use ``SQLAlchemy`` under the hood, but more engines are planned to be supported such as `turbodbc <https://turbodbc.readthedocs.io/en/latest/>`_ (:issue:`36893`)
 - Removed redundant ``freq`` from :class:`PeriodIndex` string representation (:issue:`41653`)
 - :meth:`ExtensionDtype.construct_array_type` is now a required method instead of an optional one for :class:`ExtensionDtype` subclasses (:issue:`24860`)

doc/source/whatsnew/v1.4.0.rst

@@ -87,7 +87,7 @@ See :ref:`install.dependencies` and :ref:`install.optional_dependencies` for mor
 
 Other API changes
 ^^^^^^^^^^^^^^^^^
--
+- Calling ``hash`` on non-hashable pandas objects will now raise ``TypeError`` with the built-in error message (e.g. ``unhashable type: 'Series'``). Previously it would raise a custom message such as ``"'Series' objects are mutable, thus they cannot be hashed"`` (:issue:`40013`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/frame.py

@@ -6181,8 +6181,9 @@ def f(vals) -> tuple[np.ndarray, int]:
             labels, shape = algorithms.factorize(vals, size_hint=len(self))
             return labels.astype("i8", copy=False), len(shape)
 
+        subset_iterable: Iterable
         if subset is None:
-            subset_iterable: Iterable = self.columns
+            subset_iterable = self.columns
         elif (
             not np.iterable(subset)
             or isinstance(subset, str)