Backport PR #48380 on branch 1.5.x (DOC: Clarify that objects dtype takes precedence in where) (#48445)

* Backport PR #48380: DOC: Clarify that objects dtype takes precedence in where

* Update generic.py

Co-authored-by: Patrick Hoefler <[email protected]>

Author: meeseeksmachine

doc/source/whatsnew/v1.5.0.rst

@@ -308,6 +308,7 @@ Other enhancements
 - Implemented a complex-dtype :class:`Index`, passing a complex-dtype array-like to ``pd.Index`` will now retain complex dtype instead of casting to ``object`` (:issue:`45845`)
 - :class:`Series` and :class:`DataFrame` with :class:`IntegerDtype` now supports bitwise operations (:issue:`34463`)
 - Add ``milliseconds`` field support for :class:`.DateOffset` (:issue:`43371`)
+- :meth:`DataFrame.where` tries to maintain dtype of :class:`DataFrame` if fill value can be cast without loss of precision (:issue:`45582`)
 - :meth:`DataFrame.reset_index` now accepts a ``names`` argument which renames the index names (:issue:`6878`)
 - :func:`concat` now raises when ``levels`` is given but ``keys`` is None (:issue:`46653`)
 - :func:`concat` now raises when ``levels`` contains duplicate values (:issue:`46653`)

pandas/core/generic.py

@@ -9876,6 +9876,9 @@ def where(
         For further details and examples see the ``{name}`` documentation in
         :ref:`indexing <indexing.where_mask>`.
 
+        The dtype of the object takes precedence. The fill value is casted to
+        the object's dtype, if this can be done losslessly.
+
         Examples
         --------
         >>> s = pd.Series(range(5))