Merge branch 'main' of https://github.com/pandas-dev/pandas into feature/44764_perf_issue_new_period

# Conflicts:
#	doc/source/whatsnew/v2.1.0.rst

Author: Sylvain MARIE

doc/source/_static/css/getting_started.css

@@ -236,11 +236,11 @@ ul.task-bullet > li > p:first-child {
 
 .tutorial-card .card-header {
   cursor: pointer;
-  background-color: white;
+  background-color: transparent;
 }
 
 .tutorial-card .card-body {
-  background-color: #F0F0F0;
+  background-color: transparent;
 }
 
 .tutorial-card .badge {

doc/source/whatsnew/v2.1.0.rst

@@ -86,7 +86,7 @@ See :ref:`install.dependencies` and :ref:`install.optional_dependencies` for mor
 
 Other API changes
 ^^^^^^^^^^^^^^^^^
--
+- :class:`~arrays.ArrowExtensionArray` comparison methods now return data with :class:`ArrowDtype` with ``pyarrow.bool_`` type instead of ``"boolean"`` dtype (:issue:`51643`)
 -
 
 .. ---------------------------------------------------------------------------
@@ -115,6 +115,7 @@ Performance improvements
 - Performance improvement in :meth:`~arrays.ArrowExtensionArray.isna` when array has zero nulls or is all nulls (:issue:`51630`)
 - Performance improvement when parsing strings to ``boolean[pyarrow]`` dtype (:issue:`51730`)
 - Performance improvement when searching an :class:`Index` sliced from other indexes (:issue:`51738`)
+- Performance improvement in :meth:`Series.combine_first` (:issue:`51777`)
 - :class:`Period`'s default formatter (`period_format`) is now significantly
   (~twice) faster. This improves performance of ``str(Period)``, ``repr(Period)``, and
   :meth:`Period.strftime(fmt=None)`, as well as ``PeriodArray.strftime(fmt=None)``,
@@ -208,7 +209,9 @@ Groupby/resample/rolling
 
 Reshaping
 ^^^^^^^^^
+- Bug in :meth:`DataFrame.stack` losing extension dtypes when columns is a :class:`MultiIndex` and frame contains mixed dtypes (:issue:`45740`)
 - Bug in :meth:`DataFrame.transpose` inferring dtype for object column (:issue:`51546`)
+- Bug in :meth:`Series.combine_first` converting ``int64`` dtype to ``float64`` and losing precision on very large integers (:issue:`51764`)
 -
 
 Sparse

pandas/_testing/__init__.py

@@ -1028,8 +1028,8 @@ def shares_memory(left, right) -> bool:
         left = cast("ArrowExtensionArray", left)
         if isinstance(right, ExtensionArray) and right.dtype == "string[pyarrow]":
             right = cast("ArrowExtensionArray", right)
-            left_pa_data = left._data
-            right_pa_data = right._data
+            left_pa_data = left._pa_array
+            right_pa_data = right._pa_array
             left_buf1 = left_pa_data.chunk(0).buffers()[1]
             right_buf1 = right_pa_data.chunk(0).buffers()[1]
             return left_buf1 == right_buf1