DOC: Replace @appender decorator with inline docstrings for Index.take, Index.repeat, and Index.get_indexer_non_unique

Author: mateomramos

pandas/core/indexes/base.py

@@ -71,7 +71,7 @@
     InvalidIndexError,
 )
 from pandas.util._decorators import (
-    Appender,
+    Appender
     cache_readonly,
     doc,
     set_module,
@@ -1170,8 +1170,16 @@ def astype(self, dtype: Dtype, copy: bool = True):
             result._references.add_index_reference(result)
         return result
 
-    _index_shared_docs["take"] = """
-        Return a new %(klass)s of the values selected by the indices.
+    def take(
+        self,
+        indices,
+        axis: Axis = 0,
+        allow_fill: bool = True,
+        fill_value=None,
+        **kwargs,
+    ) -> Self:
+        """
+        Return a new Index of the values selected by the indices.
 
         For internal compatibility with numpy arrays.
 
@@ -1189,7 +1197,7 @@ def astype(self, dtype: Dtype, copy: bool = True):
               :func:`numpy.take`.
 
             * True: negative values in `indices` indicate
-              missing values. These values are set to `fill_value`. Any other
+              missing values. These values are set to `fill_value`. Any
               other negative values raise a ``ValueError``.
 
         fill_value : scalar, default None
@@ -1215,16 +1223,6 @@ def astype(self, dtype: Dtype, copy: bool = True):
         >>> idx.take([2, 2, 1, 2])
         Index(['c', 'c', 'b', 'c'], dtype='str')
         """
-
-    @Appender(_index_shared_docs["take"] % _index_doc_kwargs)
-    def take(
-        self,
-        indices,
-        axis: Axis = 0,
-        allow_fill: bool = True,
-        fill_value=None,
-        **kwargs,
-    ) -> Self:
         if kwargs:
             nv.validate_take((), kwargs)
         if is_scalar(indices):
@@ -1272,26 +1270,27 @@ def _maybe_disallow_fill(self, allow_fill: bool, fill_value, indices) -> bool:
             allow_fill = False
         return allow_fill
 
-    _index_shared_docs["repeat"] = """
-        Repeat elements of a %(klass)s.
+    def repeat(self, repeats, axis: None = None) -> Self:
+        """
+        Repeat elements of a Index.
 
-        Returns a new %(klass)s where each element of the current %(klass)s
+        Returns a new Index where each element of the current Index
         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
-            %(klass)s.
+            Index.
         axis : None
             Must be ``None``. Has no effect but is accepted for compatibility
             with numpy.
 
         Returns
         -------
-        %(klass)s
-            Newly created %(klass)s with repeated elements.
+        Index
+            Newly created Index with repeated elements.
 
         See Also
         --------
@@ -1308,9 +1307,6 @@ def _maybe_disallow_fill(self, allow_fill: bool, fill_value, indices) -> bool:
         >>> idx.repeat([1, 2, 3])
         Index(['a', 'b', 'b', 'c', 'c', 'c'], dtype='object')
         """
-
-    @Appender(_index_shared_docs["repeat"] % _index_doc_kwargs)
-    def repeat(self, repeats, axis: None = None) -> Self:
         repeats = ensure_platform_int(repeats)
         nv.validate_repeat((), {"axis": axis})
         res_values = self._values.repeat(repeats)
@@ -5940,15 +5936,18 @@ def _should_fallback_to_positional(self) -> bool:
             "complex",
         }
 
-    _index_shared_docs["get_indexer_non_unique"] = """
+    def get_indexer_non_unique(
+        self, target
+    ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]:
+        """
         Compute indexer and mask for new index given the current index.
 
         The indexer should be then used as an input to ndarray.take to align the
         current data to the new index.
 
         Parameters
         ----------
-        target : %(target_klass)s
+        target : Index
             An iterable containing the values to be used for computing indexer.
 
         Returns
@@ -5992,11 +5991,6 @@ def _should_fallback_to_positional(self) -> bool:
         >>> index.get_indexer_non_unique(['f', 'b', 's'])
         (array([-1,  1,  3,  4, -1]), array([0, 2]))
         """
-
-    @Appender(_index_shared_docs["get_indexer_non_unique"] % _index_doc_kwargs)
-    def get_indexer_non_unique(
-        self, target
-    ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]:
         target = self._maybe_cast_listlike_indexer(target)
 
         if not self._should_compare(target) and not self._should_partial_index(target):