CLN: remove methods of ExtensionIndex that duplicate base Index (#34163)

pandas/core/base.py

@@ -1257,8 +1257,7 @@ def value_counts(
     def unique(self):
         values = self._values
 
-        if hasattr(values, "unique"):
-
+        if not isinstance(values, np.ndarray):
             result = values.unique()
             if self.dtype.kind in ["m", "M"] and isinstance(self, ABCSeries):
                 # GH#31182 Series._values returns EA, unpack for backward-compat

pandas/core/indexes/extension.py

@@ -9,11 +9,7 @@
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly, doc
 
-from pandas.core.dtypes.common import (
-    ensure_platform_int,
-    is_dtype_equal,
-    is_object_dtype,
-)
+from pandas.core.dtypes.common import is_dtype_equal, is_object_dtype
 from pandas.core.dtypes.generic import ABCSeries
 
 from pandas.core.arrays import ExtensionArray
@@ -223,29 +219,14 @@ def __getitem__(self, key):
         deprecate_ndim_indexing(result)
         return result
 
-    def __iter__(self):
-        return self._data.__iter__()
-
     # ---------------------------------------------------------------------
 
-    def __array__(self, dtype=None) -> np.ndarray:
-        return np.asarray(self._data, dtype=dtype)
-
     def _get_engine_target(self) -> np.ndarray:
         # NB: _values_for_argsort happens to match the desired engine targets
         #  for all of our existing EA-backed indexes, but in general
         #  cannot be relied upon to exist.
         return self._data._values_for_argsort()
 
-    @doc(Index.dropna)
-    def dropna(self, how="any"):
-        if how not in ("any", "all"):
-            raise ValueError(f"invalid how option: {how}")
-
-        if self.hasnans:
-            return self._shallow_copy(self._data[~self._isnan])
-        return self._shallow_copy()
-
     def repeat(self, repeats, axis=None):
         nv.validate_repeat(tuple(), dict(axis=axis))
         result = self._data.repeat(repeats, axis=axis)
@@ -259,27 +240,6 @@ def _concat_same_dtype(self, to_concat, name):
         arr = type(self._data)._concat_same_type(to_concat)
         return type(self)._simple_new(arr, name=name)
 
-    @doc(Index.take)
-    def take(self, indices, axis=0, allow_fill=True, fill_value=None, **kwargs):
-        nv.validate_take(tuple(), kwargs)
-        indices = ensure_platform_int(indices)
-
-        taken = self._assert_take_fillable(
-            self._data,
-            indices,
-            allow_fill=allow_fill,
-            fill_value=fill_value,
-            na_value=self._na_value,
-        )
-        return type(self)(taken, name=self.name)
-
-    def unique(self, level=None):
-        if level is not None:
-            self._validate_index_level(level)
-
-        result = self._data.unique()
-        return self._shallow_copy(result)
-
     def _get_unique_index(self, dropna=False):
         if self.is_unique and not dropna:
             return self