DOC: inline docstring for ExtensionArray.repeat

pandas/core/arrays/base.py

@@ -30,8 +30,6 @@
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import (
-    Appender,
-    Substitution,
     cache_readonly,
 )
 from pandas.util._validators import (
@@ -1669,9 +1667,48 @@ def factorize(
         Categories (3, str): ['a', 'b', 'c']
         """
 
-    @Substitution(klass="ExtensionArray")
-    @Appender(_extension_array_shared_docs["repeat"])
     def repeat(self, repeats: int | Sequence[int], axis: AxisInt | None = None) -> Self:
+        """
+        Repeat elements of an ExtensionArray.
+
+        Returns a new ExtensionArray where each element of the current ExtensionArray
+        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
+            ExtensionArray.
+        axis : None
+            Must be ``None``. Has no effect but is accepted for compatibility
+            with numpy.
+
+        Returns
+        -------
+        ExtensionArray
+            Newly created ExtensionArray with repeated elements.
+
+        See Also
+        --------
+        Series.repeat : Equivalent function for Series.
+        Index.repeat : Equivalent function for Index.
+        numpy.repeat : Similar method for :class:`numpy.ndarray`.
+        ExtensionArray.take : Take arbitrary positions.
+
+        Examples
+        --------
+        >>> cat = pd.Categorical(["a", "b", "c"])
+        >>> cat
+        ['a', 'b', 'c']
+        Categories (3, str): ['a', 'b', 'c']
+        >>> cat.repeat(2)
+        ['a', 'a', 'b', 'b', 'c', 'c']
+        Categories (3, str): ['a', 'b', 'c']
+        >>> cat.repeat([1, 2, 3])
+        ['a', 'b', 'b', 'c', 'c', 'c']
+        Categories (3, str): ['a', 'b', 'c']
+        """
         nv.validate_repeat((), {"axis": axis})
         ind = np.arange(len(self)).repeat(repeats)
         return self.take(ind)