diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index f5f793c507480..22ba317e78e63 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -505,9 +505,8 @@ def _get_attributes_dict(self):
         """
         return {k: getattr(self, k, None) for k in self._attributes}
 
-    _index_shared_docs[
-        "_shallow_copy"
-    ] = """
+    def _shallow_copy(self, values=None, **kwargs):
+        """
         Create a new Index with the same class as the caller, don't copy the
         data, use the same object attributes with passed in attributes taking
         precedence.
@@ -519,9 +518,6 @@ def _get_attributes_dict(self):
         values : the values to create the new Index, optional
         kwargs : updates the default attributes for this Index
         """
-
-    @Appender(_index_shared_docs["_shallow_copy"])
-    def _shallow_copy(self, values=None, **kwargs):
         if values is None:
             values = self.values
 
@@ -659,9 +655,8 @@ def view(self, cls=None):
             result._id = self._id
         return result
 
-    _index_shared_docs[
-        "astype"
-    ] = """
+    def astype(self, dtype, copy=True):
+        """
         Create an Index with values cast to dtypes. The class of a new Index
         is determined by dtype. When conversion is impossible, a ValueError
         exception is raised.
@@ -683,9 +678,6 @@ def view(self, cls=None):
         Index
             Index with values cast to specified dtype.
         """
-
-    @Appender(_index_shared_docs["astype"])
-    def astype(self, dtype, copy=True):
         if is_dtype_equal(self.dtype, dtype):
             return self.copy() if copy else self
 
@@ -823,9 +815,8 @@ def repeat(self, repeats, axis=None):
     # --------------------------------------------------------------------
     # Copying Methods
 
-    _index_shared_docs[
-        "copy"
-    ] = """
+    def copy(self, name=None, deep=False, dtype=None, **kwargs):
+        """
         Make a copy of this object.  Name and dtype sets those attributes on
         the new object.
 
@@ -844,9 +835,6 @@ def repeat(self, repeats, axis=None):
         In most cases, there should be no functional difference from using
         ``deep``, but if ``deep`` is passed it will attempt to deepcopy.
         """
-
-    @Appender(_index_shared_docs["copy"])
-    def copy(self, name=None, deep=False, dtype=None, **kwargs):
         if deep:
             new_index = self._shallow_copy(self._data.copy())
         else:
@@ -1537,9 +1525,8 @@ def droplevel(self, level=0):
                 verify_integrity=False,
             )
 
-    _index_shared_docs[
-        "_get_grouper_for_level"
-    ] = """
+    def _get_grouper_for_level(self, mapper, level=None):
+        """
         Get index grouper corresponding to an index level
 
         Parameters
@@ -1558,9 +1545,6 @@ def droplevel(self, level=0):
         uniques : Index or None
             Index of unique values for level.
         """
-
-    @Appender(_index_shared_docs["_get_grouper_for_level"])
-    def _get_grouper_for_level(self, mapper, level=None):
         assert level is None or level == 0
         if mapper is None:
             grouper = self
@@ -2156,9 +2140,8 @@ def notna(self):
 
     notnull = notna
 
-    _index_shared_docs[
-        "fillna"
-    ] = """
+    def fillna(self, value=None, downcast=None):
+        """
         Fill NA/NaN values with the specified value.
 
         Parameters
@@ -2175,9 +2158,6 @@ def notna(self):
         -------
         filled : Index
         """
-
-    @Appender(_index_shared_docs["fillna"])
-    def fillna(self, value=None, downcast=None):
         self._assert_can_do_op(value)
         if self.hasnans:
             result = self.putmask(self._isnan, value)
@@ -2187,9 +2167,8 @@ def fillna(self, value=None, downcast=None):
                 return Index(result, name=self.name)
         return self._shallow_copy()
 
-    _index_shared_docs[
-        "dropna"
-    ] = """
+    def dropna(self, how="any"):
+        """
         Return Index without NA/NaN values.
 
         Parameters
@@ -2202,9 +2181,6 @@ def fillna(self, value=None, downcast=None):
         -------
         valid : Index
         """
-
-    @Appender(_index_shared_docs["dropna"])
-    def dropna(self, how="any"):
         if how not in ("any", "all"):
             raise ValueError(f"invalid how option: {how}")
 
@@ -2215,9 +2191,8 @@ def dropna(self, how="any"):
     # --------------------------------------------------------------------
     # Uniqueness Methods
 
-    _index_shared_docs[
-        "index_unique"
-    ] = """
+    def unique(self, level=None):
+        """
         Return unique values in the index. Uniques are returned in order
         of appearance, this does NOT sort.
 
@@ -2237,9 +2212,6 @@ def dropna(self, how="any"):
         unique
         Series.unique
         """
-
-    @Appender(_index_shared_docs["index_unique"] % _index_doc_kwargs)
-    def unique(self, level=None):
         if level is not None:
             self._validate_index_level(level)
         result = super().unique()
@@ -2625,9 +2597,9 @@ def _union(self, other, sort):
     def _wrap_setop_result(self, other, result):
         return self._constructor(result, name=get_op_result_name(self, other))
 
-    _index_shared_docs[
-        "intersection"
-    ] = """
+    # TODO: standardize return type of non-union setops type(self vs other)
+    def intersection(self, other, sort=False):
+        """
         Form the intersection of two Index objects.
 
         This returns a new Index with elements common to the index and `other`.
@@ -2661,10 +2633,6 @@ def _wrap_setop_result(self, other, result):
         >>> idx1.intersection(idx2)
         Int64Index([3, 4], dtype='int64')
         """
-
-    # TODO: standardize return type of non-union setops type(self vs other)
-    @Appender(_index_shared_docs["intersection"])
-    def intersection(self, other, sort=False):
         self._validate_sort_keyword(sort)
         self._assert_can_do_setop(other)
         other = ensure_index(other)
@@ -2868,9 +2836,8 @@ def _convert_can_do_setop(self, other):
     # --------------------------------------------------------------------
     # Indexing Methods
 
-    _index_shared_docs[
-        "get_loc"
-    ] = """
+    def get_loc(self, key, method=None, tolerance=None):
+        """
         Get integer location, slice or boolean mask for requested label.
 
         Parameters
@@ -2907,9 +2874,6 @@ def _convert_can_do_setop(self, other):
         >>> non_monotonic_index.get_loc('b')
         array([False,  True, False,  True], dtype=bool)
         """
-
-    @Appender(_index_shared_docs["get_loc"])
-    def get_loc(self, key, method=None, tolerance=None):
         if method is None:
             if tolerance is not None:
                 raise ValueError(
@@ -3121,19 +3085,15 @@ def _filter_indexer_tolerance(
     # --------------------------------------------------------------------
     # Indexer Conversion Methods
 
-    _index_shared_docs[
-        "_convert_scalar_indexer"
-    ] = """
+    def _convert_scalar_indexer(self, key, kind=None):
+        """
         Convert a scalar indexer.
 
         Parameters
         ----------
         key : label of the slice bound
         kind : {'loc', 'getitem', 'iloc'} or None
-    """
-
-    @Appender(_index_shared_docs["_convert_scalar_indexer"])
-    def _convert_scalar_indexer(self, key, kind=None):
+        """
         assert kind in ["loc", "getitem", "iloc", None]
 
         if kind == "iloc":
@@ -3171,9 +3131,8 @@ def _convert_scalar_indexer(self, key, kind=None):
 
         return key
 
-    _index_shared_docs[
-        "_convert_slice_indexer"
-    ] = """
+    def _convert_slice_indexer(self, key: slice, kind=None):
+        """
         Convert a slice indexer.
 
         By definition, these are labels unless 'iloc' is passed in.
@@ -3183,10 +3142,7 @@ def _convert_scalar_indexer(self, key, kind=None):
         ----------
         key : label of the slice bound
         kind : {'loc', 'getitem', 'iloc'} or None
-    """
-
-    @Appender(_index_shared_docs["_convert_slice_indexer"])
-    def _convert_slice_indexer(self, key: slice, kind=None):
+        """
         assert kind in ["loc", "getitem", "iloc", None]
 
         # validate iloc
@@ -3266,9 +3222,8 @@ def _convert_listlike_indexer(self, keyarr, kind=None):
         indexer = self._convert_list_indexer(keyarr, kind=kind)
         return indexer, keyarr
 
-    _index_shared_docs[
-        "_convert_arr_indexer"
-    ] = """
+    def _convert_arr_indexer(self, keyarr):
+        """
         Convert an array-like indexer to the appropriate dtype.
 
         Parameters
@@ -3279,16 +3234,12 @@ def _convert_listlike_indexer(self, keyarr, kind=None):
         Returns
         -------
         converted_keyarr : array-like
-    """
-
-    @Appender(_index_shared_docs["_convert_arr_indexer"])
-    def _convert_arr_indexer(self, keyarr):
+        """
         keyarr = com.asarray_tuplesafe(keyarr)
         return keyarr
 
-    _index_shared_docs[
-        "_convert_index_indexer"
-    ] = """
+    def _convert_index_indexer(self, keyarr):
+        """
         Convert an Index indexer to the appropriate dtype.
 
         Parameters
@@ -3299,15 +3250,11 @@ def _convert_arr_indexer(self, keyarr):
         Returns
         -------
         converted_keyarr : Index (or sub-class)
-    """
-
-    @Appender(_index_shared_docs["_convert_index_indexer"])
-    def _convert_index_indexer(self, keyarr):
+        """
         return keyarr
 
-    _index_shared_docs[
-        "_convert_list_indexer"
-    ] = """
+    def _convert_list_indexer(self, keyarr, kind=None):
+        """
         Convert a list-like indexer to the appropriate dtype.
 
         Parameters
@@ -3319,10 +3266,7 @@ def _convert_index_indexer(self, keyarr):
         Returns
         -------
         positional indexer or None
-    """
-
-    @Appender(_index_shared_docs["_convert_list_indexer"])
-    def _convert_list_indexer(self, keyarr, kind=None):
+        """
         if (
             kind in [None, "iloc"]
             and is_integer_dtype(keyarr)
@@ -3502,9 +3446,8 @@ def _reindex_non_unique(self, target):
     # --------------------------------------------------------------------
     # Join Methods
 
-    _index_shared_docs[
-        "join"
-    ] = """
+    def join(self, other, how="left", level=None, return_indexers=False, sort=False):
+        """
         Compute join_index and indexers to conform data
         structures to the new index.
 
@@ -3522,9 +3465,6 @@ def _reindex_non_unique(self, target):
         -------
         join_index, (left_indexer, right_indexer)
         """
-
-    @Appender(_index_shared_docs["join"])
-    def join(self, other, how="left", level=None, return_indexers=False, sort=False):
         self_is_mi = isinstance(self, ABCMultiIndex)
         other_is_mi = isinstance(other, ABCMultiIndex)
 
@@ -4033,9 +3973,8 @@ def memory_usage(self, deep: bool = False) -> int:
         result += self._engine.sizeof(deep=deep)
         return result
 
-    _index_shared_docs[
-        "where"
-    ] = """
+    def where(self, cond, other=None):
+        """
         Return an Index of same shape as self and whose corresponding
         entries are from self where cond is True and otherwise are from
         other.
@@ -4049,9 +3988,6 @@ def memory_usage(self, deep: bool = False) -> int:
         -------
         Index
         """
-
-    @Appender(_index_shared_docs["where"])
-    def where(self, cond, other=None):
         if other is None:
             other = self._na_value
 
@@ -4146,9 +4082,8 @@ def is_type_compatible(self, kind) -> bool:
         """
         return kind == self.inferred_type
 
-    _index_shared_docs[
-        "contains"
-    ] = """
+    def __contains__(self, key: Any) -> bool:
+        """
         Return a boolean indicating whether the provided key is in the index.
 
         Parameters
@@ -4177,9 +4112,6 @@ def is_type_compatible(self, kind) -> bool:
         >>> 6 in idx
         False
         """
-
-    @Appender(_index_shared_docs["contains"] % _index_doc_kwargs)
-    def __contains__(self, key: Any) -> bool:
         hash(key)
         try:
             return key in self._engine
@@ -5020,9 +4952,8 @@ def _validate_indexer(self, form: str_t, key, kind: str_t):
         else:
             self._invalid_indexer(form, key)
 
-    _index_shared_docs[
-        "_maybe_cast_slice_bound"
-    ] = """
+    def _maybe_cast_slice_bound(self, label, side: str_t, kind):
+        """
         This function should be overloaded in subclasses that allow non-trivial
         casting on label-slice bounds, e.g. datetime-like indices allowing
         strings containing formatted datetimes.
@@ -5041,9 +4972,6 @@ def _validate_indexer(self, form: str_t, key, kind: str_t):
         -----
         Value of `side` parameter should be validated in caller.
         """
-
-    @Appender(_index_shared_docs["_maybe_cast_slice_bound"])
-    def _maybe_cast_slice_bound(self, label, side: str_t, kind):
         assert kind in ["loc", "getitem", None]
 
         # We are a plain index here (sub-class override this method if they
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 235d1856a2d0b..d556c014467cf 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -277,7 +277,7 @@ def _simple_new(cls, values, name=None, dtype=None):
 
     # --------------------------------------------------------------------
 
-    @Appender(_index_shared_docs["_shallow_copy"])
+    @Appender(Index._shallow_copy.__doc__)
     def _shallow_copy(self, values=None, dtype=None, **kwargs):
         if dtype is None:
             dtype = self.dtype
@@ -392,7 +392,7 @@ def _wrap_setop_result(self, other, result):
         #  (which uses _constructor) in order to preserve dtype.
         return self._shallow_copy(result, name=name)
 
-    @Appender(_index_shared_docs["contains"] % _index_doc_kwargs)
+    @Appender(Index.__contains__.__doc__)
     def __contains__(self, key: Any) -> bool:
         # if key is a NaN, check if any NaN is in self.
         if is_scalar(key) and isna(key):
@@ -405,7 +405,7 @@ def __array__(self, dtype=None) -> np.ndarray:
         """ the array interface, return my values """
         return np.array(self._data, dtype=dtype)
 
-    @Appender(_index_shared_docs["astype"])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         if is_interval_dtype(dtype):
             from pandas import IntervalIndex
@@ -424,7 +424,7 @@ def _isnan(self):
         """ return if each value is nan"""
         return self._data.codes == -1
 
-    @Appender(ibase._index_shared_docs["fillna"])
+    @Appender(Index.fillna.__doc__)
     def fillna(self, value, downcast=None):
         self._assert_can_do_op(value)
         return CategoricalIndex(self._data.fillna(value), name=self.name)
@@ -437,7 +437,7 @@ def _engine(self):
         codes = self.codes
         return self._engine_type(lambda: codes, len(self))
 
-    @Appender(_index_shared_docs["index_unique"] % _index_doc_kwargs)
+    @Appender(Index.unique.__doc__)
     def unique(self, level=None):
         if level is not None:
             self._validate_index_level(level)
@@ -523,7 +523,7 @@ def get_value(self, series: AnyArrayLike, key: Any):
         # we might be a positional inexer
         return super().get_value(series, key)
 
-    @Appender(_index_shared_docs["where"])
+    @Appender(Index.where.__doc__)
     def where(self, cond, other=None):
         # TODO: Investigate an alternative implementation with
         # 1. copy the underlying Categorical
@@ -673,7 +673,7 @@ def get_indexer_non_unique(self, target):
         indexer, missing = self._engine.get_indexer_non_unique(codes)
         return ensure_platform_int(indexer), missing
 
-    @Appender(_index_shared_docs["_convert_scalar_indexer"])
+    @Appender(Index._convert_scalar_indexer.__doc__)
     def _convert_scalar_indexer(self, key, kind=None):
         if kind == "loc":
             try:
@@ -682,7 +682,7 @@ def _convert_scalar_indexer(self, key, kind=None):
                 self._invalid_indexer("label", key)
         return super()._convert_scalar_indexer(key, kind=kind)
 
-    @Appender(_index_shared_docs["_convert_list_indexer"])
+    @Appender(Index._convert_list_indexer.__doc__)
     def _convert_list_indexer(self, keyarr, kind=None):
         # Return our indexer or raise if all of the values are not included in
         # the categories
@@ -699,7 +699,7 @@ def _convert_list_indexer(self, keyarr, kind=None):
 
         return self.get_indexer(keyarr)
 
-    @Appender(_index_shared_docs["_convert_arr_indexer"])
+    @Appender(Index._convert_arr_indexer.__doc__)
     def _convert_arr_indexer(self, keyarr):
         keyarr = com.asarray_tuplesafe(keyarr)
 
@@ -708,7 +708,7 @@ def _convert_arr_indexer(self, keyarr):
 
         return self._shallow_copy(keyarr)
 
-    @Appender(_index_shared_docs["_convert_index_indexer"])
+    @Appender(Index._convert_index_indexer.__doc__)
     def _convert_index_indexer(self, keyarr):
         return self._shallow_copy(keyarr)
 
@@ -721,7 +721,7 @@ def take_nd(self, *args, **kwargs):
         )
         return self.take(*args, **kwargs)
 
-    @Appender(_index_shared_docs["_maybe_cast_slice_bound"])
+    @Appender(Index._maybe_cast_slice_bound.__doc__)
     def _maybe_cast_slice_bound(self, label, side, kind):
         if kind == "loc":
             return label
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index 0f385d9aba9c5..dd15b6e09f354 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -153,7 +153,7 @@ def equals(self, other) -> bool:
 
         return np.array_equal(self.asi8, other.asi8)
 
-    @Appender(_index_shared_docs["contains"] % _index_doc_kwargs)
+    @Appender(Index.__contains__.__doc__)
     def __contains__(self, key: Any) -> bool:
         hash(key)
         try:
@@ -443,7 +443,7 @@ def isin(self, values, level=None):
 
         return algorithms.isin(self.asi8, values.asi8)
 
-    @Appender(_index_shared_docs["where"] % _index_doc_kwargs)
+    @Appender(Index.where.__doc__)
     def where(self, cond, other=None):
         values = self.view("i8")
 
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index fd812b17fb37c..6a3e808ab9821 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -349,7 +349,7 @@ def from_tuples(
 
     # --------------------------------------------------------------------
 
-    @Appender(_index_shared_docs["_shallow_copy"])
+    @Appender(Index._shallow_copy.__doc__)
     def _shallow_copy(self, left=None, right=None, **kwargs):
         result = self._data._shallow_copy(left=left, right=right)
         attributes = self._get_attributes_dict()
@@ -419,7 +419,7 @@ def __reduce__(self):
         d.update(self._get_attributes_dict())
         return _new_IntervalIndex, (type(self), d), None
 
-    @Appender(_index_shared_docs["astype"])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         with rewrite_exception("IntervalArray", type(self).__name__):
             new_values = self.values.astype(dtype, copy=copy)
@@ -527,7 +527,7 @@ def is_overlapping(self) -> bool:
         # GH 23309
         return self._engine.is_overlapping
 
-    @Appender(_index_shared_docs["_convert_scalar_indexer"])
+    @Appender(Index._convert_scalar_indexer.__doc__)
     def _convert_scalar_indexer(self, key, kind=None):
         if kind == "iloc":
             return super()._convert_scalar_indexer(key, kind=kind)
@@ -536,7 +536,7 @@ def _convert_scalar_indexer(self, key, kind=None):
     def _maybe_cast_slice_bound(self, label, side, kind):
         return getattr(self, side)._maybe_cast_slice_bound(label, side, kind)
 
-    @Appender(_index_shared_docs["_convert_list_indexer"])
+    @Appender(Index._convert_list_indexer.__doc__)
     def _convert_list_indexer(self, keyarr, kind=None):
         """
         we are passed a list-like indexer. Return the
@@ -894,7 +894,7 @@ def _convert_slice_indexer(self, key: slice, kind=None):
             raise ValueError("cannot support not-default step in a slice")
         return super()._convert_slice_indexer(key, kind)
 
-    @Appender(_index_shared_docs["where"])
+    @Appender(Index.where.__doc__)
     def where(self, cond, other=None):
         if other is None:
             other = self._na_value
@@ -1055,7 +1055,7 @@ def equals(self, other) -> bool:
             and self.closed == other.closed
         )
 
-    @Appender(_index_shared_docs["intersection"])
+    @Appender(Index.intersection.__doc__)
     @SetopCheck(op_name="intersection")
     def intersection(
         self, other: "IntervalIndex", sort: bool = False
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 02db7be1ddf41..889622f44bbb7 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -972,7 +972,7 @@ def _shallow_copy_with_infer(self, values, **kwargs):
             )
         return self._shallow_copy(values, **kwargs)
 
-    @Appender(_index_shared_docs["contains"] % _index_doc_kwargs)
+    @Appender(Index.__contains__.__doc__)
     def __contains__(self, key: Any) -> bool:
         hash(key)
         try:
@@ -981,7 +981,7 @@ def __contains__(self, key: Any) -> bool:
         except (LookupError, TypeError, ValueError):
             return False
 
-    @Appender(_index_shared_docs["_shallow_copy"])
+    @Appender(Index._shallow_copy.__doc__)
     def _shallow_copy(self, values=None, **kwargs):
         if values is not None:
             names = kwargs.pop("names", kwargs.pop("name", self.names))
@@ -1231,7 +1231,7 @@ def _set_names(self, names, level=None, validate=True):
         fset=_set_names, fget=_get_names, doc="""\nNames of levels in MultiIndex.\n"""
     )
 
-    @Appender(_index_shared_docs["_get_grouper_for_level"])
+    @Appender(Index._get_grouper_for_level.__doc__)
     def _get_grouper_for_level(self, mapper, level):
         indexer = self.codes[level]
         level_index = self.levels[level]
@@ -1448,7 +1448,7 @@ def fillna(self, value=None, downcast=None):
         """
         raise NotImplementedError("isna is not defined for MultiIndex")
 
-    @Appender(_index_shared_docs["dropna"])
+    @Appender(Index.dropna.__doc__)
     def dropna(self, how="any"):
         nans = [level_codes == -1 for level_codes in self.codes]
         if how == "any":
@@ -1585,7 +1585,7 @@ def get_level_values(self, level):
         values = self._get_level_values(level)
         return values
 
-    @Appender(_index_shared_docs["index_unique"] % _index_doc_kwargs)
+    @Appender(Index.unique.__doc__)
     def unique(self, level=None):
 
         if level is None:
@@ -3310,7 +3310,7 @@ def difference(self, other, sort=None):
         else:
             return MultiIndex.from_tuples(difference, sortorder=0, names=result_names)
 
-    @Appender(_index_shared_docs["astype"])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
         if is_categorical_dtype(dtype):
diff --git a/pandas/core/indexes/numeric.py b/pandas/core/indexes/numeric.py
index f7af82920adb1..4d3d560aaa688 100644
--- a/pandas/core/indexes/numeric.py
+++ b/pandas/core/indexes/numeric.py
@@ -32,12 +32,7 @@
 
 from pandas.core import algorithms
 import pandas.core.common as com
-from pandas.core.indexes.base import (
-    Index,
-    InvalidIndexError,
-    _index_shared_docs,
-    maybe_extract_name,
-)
+from pandas.core.indexes.base import Index, InvalidIndexError, maybe_extract_name
 from pandas.core.ops import get_op_result_name
 
 if TYPE_CHECKING:
@@ -103,14 +98,14 @@ def _validate_dtype(cls, dtype: Dtype) -> None:
                 f"Incorrect `dtype` passed: expected {expected}, received {dtype}"
             )
 
-    @Appender(_index_shared_docs["_maybe_cast_slice_bound"])
+    @Appender(Index._maybe_cast_slice_bound.__doc__)
     def _maybe_cast_slice_bound(self, label, side, kind):
         assert kind in ["loc", "getitem", None]
 
         # we will try to coerce to integers
         return self._maybe_cast_indexer(label)
 
-    @Appender(_index_shared_docs["_shallow_copy"])
+    @Appender(Index._shallow_copy.__doc__)
     def _shallow_copy(self, values=None, **kwargs):
         if values is not None and not self._can_hold_na:
             # Ensure we are not returning an Int64Index with float data:
@@ -257,7 +252,7 @@ def asi8(self) -> np.ndarray:
         # do not cache or you'll create a memory leak
         return self.values.view(self._default_dtype)
 
-    @Appender(_index_shared_docs["_convert_scalar_indexer"])
+    @Appender(Index._convert_scalar_indexer.__doc__)
     def _convert_scalar_indexer(self, key, kind=None):
         assert kind in ["loc", "getitem", "iloc", None]
 
@@ -311,7 +306,7 @@ class UInt64Index(IntegerIndex):
     _engine_type = libindex.UInt64Engine
     _default_dtype = np.dtype(np.uint64)
 
-    @Appender(_index_shared_docs["_convert_arr_indexer"])
+    @Appender(Index._convert_arr_indexer.__doc__)
     def _convert_arr_indexer(self, keyarr):
         # Cast the indexer to uint64 if possible so that the values returned
         # from indexing are also uint64.
@@ -323,7 +318,7 @@ def _convert_arr_indexer(self, keyarr):
 
         return com.asarray_tuplesafe(keyarr, dtype=dtype)
 
-    @Appender(_index_shared_docs["_convert_index_indexer"])
+    @Appender(Index._convert_index_indexer.__doc__)
     def _convert_index_indexer(self, keyarr):
         # Cast the indexer to uint64 if possible so
         # that the values returned from indexing are
@@ -373,7 +368,7 @@ def inferred_type(self) -> str:
         """
         return "floating"
 
-    @Appender(_index_shared_docs["astype"])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
         if needs_i8_conversion(dtype):
@@ -388,7 +383,7 @@ def astype(self, dtype, copy=True):
             return Int64Index(arr)
         return super().astype(dtype, copy=copy)
 
-    @Appender(_index_shared_docs["_convert_scalar_indexer"])
+    @Appender(Index._convert_scalar_indexer.__doc__)
     def _convert_scalar_indexer(self, key, kind=None):
         assert kind in ["loc", "getitem", "iloc", None]
 
@@ -397,7 +392,7 @@ def _convert_scalar_indexer(self, key, kind=None):
 
         return key
 
-    @Appender(_index_shared_docs["_convert_slice_indexer"])
+    @Appender(Index._convert_slice_indexer.__doc__)
     def _convert_slice_indexer(self, key: slice, kind=None):
 
         if kind == "iloc":
@@ -460,7 +455,7 @@ def __contains__(self, other: Any) -> bool:
 
         return is_float(other) and np.isnan(other) and self.hasnans
 
-    @Appender(_index_shared_docs["get_loc"])
+    @Appender(Index.get_loc.__doc__)
     def get_loc(self, key, method=None, tolerance=None):
         if is_bool(key):
             # Catch this to avoid accidentally casting to 1.0
diff --git a/pandas/core/indexes/period.py b/pandas/core/indexes/period.py
index 4438573cb9067..75c100c9d2c08 100644
--- a/pandas/core/indexes/period.py
+++ b/pandas/core/indexes/period.py
@@ -355,7 +355,7 @@ def _engine(self):
         period = weakref.ref(self)
         return self._engine_type(period, len(self))
 
-    @Appender(_index_shared_docs["contains"])
+    @Appender(Index.__contains__.__doc__)
     def __contains__(self, key: Any) -> bool:
         if isinstance(key, Period):
             if key.freq != self.freq:
@@ -440,7 +440,7 @@ def asof_locs(self, where, mask):
 
         return result
 
-    @Appender(_index_shared_docs["astype"])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True, how="start"):
         dtype = pandas_dtype(dtype)
 
diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
index 340397b69c624..d6752da6bc58f 100644
--- a/pandas/core/indexes/range.py
+++ b/pandas/core/indexes/range.py
@@ -340,7 +340,7 @@ def __contains__(self, key: Any) -> bool:
             return False
         return key in self._range
 
-    @Appender(_index_shared_docs["get_loc"])
+    @Appender(Int64Index.get_loc.__doc__)
     def get_loc(self, key, method=None, tolerance=None):
         if method is None and tolerance is None:
             if is_integer(key) or (is_float(key) and key.is_integer()):
@@ -384,7 +384,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
     def tolist(self):
         return list(self._range)
 
-    @Appender(_index_shared_docs["_shallow_copy"])
+    @Appender(Int64Index._shallow_copy.__doc__)
     def _shallow_copy(self, values=None, **kwargs):
         if values is None:
             name = kwargs.get("name", self.name)
@@ -393,7 +393,7 @@ def _shallow_copy(self, values=None, **kwargs):
             kwargs.setdefault("name", self.name)
             return self._int64index._shallow_copy(values, **kwargs)
 
-    @Appender(ibase._index_shared_docs["copy"])
+    @Appender(Int64Index.copy.__doc__)
     def copy(self, name=None, deep=False, dtype=None, **kwargs):
         self._validate_dtype(dtype)
         if name is None:
@@ -615,7 +615,7 @@ def _union(self, other, sort):
                     return type(self)(start_r, end_r + step_o, step_o)
         return self._int64index._union(other, sort=sort)
 
-    @Appender(_index_shared_docs["join"])
+    @Appender(Int64Index.join.__doc__)
     def join(self, other, how="left", level=None, return_indexers=False, sort=False):
         if how == "outer" and self is not other:
             # note: could return RangeIndex in more circumstances
diff --git a/pandas/core/indexes/timedeltas.py b/pandas/core/indexes/timedeltas.py
index 8691f0a2a1178..08a07e8d30348 100644
--- a/pandas/core/indexes/timedeltas.py
+++ b/pandas/core/indexes/timedeltas.py
@@ -19,12 +19,7 @@
 from pandas.core.arrays import datetimelike as dtl
 from pandas.core.arrays.timedeltas import TimedeltaArray
 import pandas.core.common as com
-from pandas.core.indexes.base import (
-    Index,
-    InvalidIndexError,
-    _index_shared_docs,
-    maybe_extract_name,
-)
+from pandas.core.indexes.base import Index, InvalidIndexError, maybe_extract_name
 from pandas.core.indexes.datetimelike import (
     DatetimeIndexOpsMixin,
     DatetimeTimedeltaMixin,
@@ -212,7 +207,7 @@ def _formatter_func(self):
 
     # -------------------------------------------------------------------
 
-    @Appender(_index_shared_docs["astype"])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
         if is_timedelta64_dtype(dtype) and not is_timedelta64_ns_dtype(dtype):