Merge branch 'main' into main

Author: sanjanam1998

.github/workflows/unit-tests.yml

@@ -181,8 +181,7 @@ jobs:
     timeout-minutes: 90
     strategy:
       matrix:
-        # Note: Don't use macOS latest since macos 14 appears to be arm64 only
-        os: [macos-13, macos-14, windows-2025]
+        os: [macos-15-intel, macos-15, windows-2025]
         env_file: [actions-311.yaml, actions-312.yaml, actions-313.yaml]
       fail-fast: false
     runs-on: ${{ matrix.os }}

.github/workflows/wheels.yml

@@ -98,10 +98,9 @@ jobs:
         - [ubuntu-24.04, musllinux_x86_64]
         - [ubuntu-24.04-arm, manylinux_aarch64]
         - [ubuntu-24.04-arm, musllinux_aarch64]
-        - [macos-13, macosx_x86_64]
-        # Note: M1 images on Github Actions start from macOS 14
-        - [macos-14, macosx_arm64]
-        - [windows-2022, win_amd64]
+        - [macos-15-intel, macosx_x86_64]
+        - [macos-15, macosx_arm64]
+        - [windows-2025, win_amd64]
         - [windows-11-arm, win_arm64]
         python: [["cp311", "3.11"], ["cp312", "3.12"], ["cp313", "3.13"], ["cp313t", "3.13"], ["cp314", "3.14"], ["cp314t", "3.14"]]
         include:

asv_bench/benchmarks/ctors.py

@@ -23,7 +23,7 @@ def gen_of_str(arr):
 
 
 def arr_dict(arr):
-    return dict(zip(range(len(arr)), arr))
+    return dict(zip(range(len(arr)), arr, strict=True))
 
 
 def list_of_tuples(arr):

asv_bench/benchmarks/series_methods.py

@@ -16,7 +16,7 @@ def setup(self):
         self.idx = date_range(
             start=datetime(2015, 10, 26), end=datetime(2016, 1, 1), freq="50s"
         )
-        self.data = dict(zip(self.idx, range(len(self.idx))))
+        self.data = dict(zip(self.idx, range(len(self.idx)), strict=True))
         self.array = np.array([1, 2, 3])
         self.idx2 = Index(["a", "b", "c"])
 
@@ -407,7 +407,9 @@ def setup(self, num_to_replace):
         self.to_replace_list = np.random.choice(self.arr, num_to_replace)
         self.values_list = np.random.choice(self.arr1, num_to_replace)
 
-        self.replace_dict = dict(zip(self.to_replace_list, self.values_list))
+        self.replace_dict = dict(
+            zip(self.to_replace_list, self.values_list, strict=True)
+        )
 
     def time_replace_dict(self, num_to_replace):
         self.ser.replace(self.replace_dict)

pandas/core/indexes/multi.py

@@ -52,7 +52,6 @@
     UnsortedIndexError,
 )
 from pandas.util._decorators import (
-    Appender,
     cache_readonly,
     doc,
     set_module,
@@ -101,7 +100,6 @@
 import pandas.core.indexes.base as ibase
 from pandas.core.indexes.base import (
     Index,
-    _index_shared_docs,
     ensure_index,
     get_unanimous_names,
 )
@@ -2290,7 +2288,6 @@ def _getitem_slice(self: MultiIndex, slobj: slice) -> MultiIndex:
             verify_integrity=False,
         )
 
-    @Appender(_index_shared_docs["take"] % _index_doc_kwargs)
     def take(
         self: MultiIndex,
         indices,
@@ -2299,6 +2296,51 @@ def take(
         fill_value=None,
         **kwargs,
     ) -> MultiIndex:
+        """
+        Return a new MultiIndex of the values selected by the indices.
+
+        For internal compatibility with numpy arrays.
+
+        Parameters
+        ----------
+        indices : array-like
+            Indices to be taken.
+        axis : int, optional
+            The axis over which to select values, always 0.
+        allow_fill : bool, default True
+            How to handle negative values in `indices`.
+
+            * False: negative values in `indices` indicate positional indices
+            from the right (the default). This is similar to
+            :func:`numpy.take`.
+
+            * True: negative values in `indices` indicate
+            missing values. These values are set to `fill_value`. Any other
+            other negative values raise a ``ValueError``.
+
+        fill_value : scalar, default None
+            If allow_fill=True and fill_value is not None, indices specified by
+            -1 are regarded as NA. If Index doesn't hold NA, raise ValueError.
+        **kwargs
+            Required for compatibility with numpy.
+
+        Returns
+        -------
+        Index
+            An index formed of elements at the given indices. Will be the same
+            type as self, except for RangeIndex.
+
+        See Also
+        --------
+        numpy.ndarray.take: Return an array formed from the
+            elements of a at the given indices.
+
+        Examples
+        --------
+        >>> idx = pd.Index(["a", "b", "c"])
+        >>> idx.take([2, 2, 1, 2])
+        Index(['c', 'c', 'b', 'c'], dtype='str')
+        """
         nv.validate_take((), kwargs)
         indices = ensure_platform_int(indices)
 
@@ -2454,8 +2496,43 @@ def argsort(
         keys = [lev.codes for lev in target._get_codes_for_sorting()]
         return lexsort_indexer(keys, na_position=na_position, codes_given=True)
 
-    @Appender(_index_shared_docs["repeat"] % _index_doc_kwargs)
     def repeat(self, repeats: int, axis=None) -> MultiIndex:
+        """
+        Repeat elements of a MultiIndex.
+
+        Returns a new MultiIndex where each element of the current MultiIndex
+        is repeated consecutively a given number of times.
+
+        Parameters
+        ----------
+        repeats : int or array of ints
+            The number of repetitions for each element. This should be a
+            non-negative integer. Repeating 0 times will return an empty
+            MultiIndex.
+        axis : None
+            Must be ``None``. Has no effect but is accepted for compatibility
+            with numpy.
+
+        Returns
+        -------
+        MultiIndex
+            Newly created MultiIndex with repeated elements.
+
+        See Also
+        --------
+        Series.repeat : Equivalent function for Series.
+        numpy.repeat : Similar method for :class:`numpy.ndarray`.
+
+        Examples
+        --------
+        >>> idx = pd.Index(["a", "b", "c"])
+        >>> idx
+        Index(['a', 'b', 'c'], dtype='object')
+        >>> idx.repeat(2)
+        Index(['a', 'a', 'b', 'b', 'c', 'c'], dtype='object')
+        >>> idx.repeat([1, 2, 3])
+        Index(['a', 'b', 'b', 'c', 'c', 'c'], dtype='object')
+        """
         nv.validate_repeat((), {"axis": axis})
         # error: Incompatible types in assignment (expression has type "ndarray",
         # variable has type "int")