REF: share more methods in ExtensionIndex

pandas/core/indexes/category.py

@@ -6,15 +6,13 @@
 from pandas._config import get_option
 
 from pandas._libs import index as libindex
-from pandas._libs.hashtable import duplicated_int64
 from pandas._libs.lib import no_default
 from pandas._typing import ArrayLike, Label
 from pandas.util._decorators import Appender, cache_readonly, doc
 
 from pandas.core.dtypes.common import (
     ensure_platform_int,
     is_categorical_dtype,
-    is_list_like,
     is_scalar,
 )
 from pandas.core.dtypes.dtypes import CategoricalDtype
@@ -226,9 +224,14 @@ def _simple_new(cls, values: Categorical, name: Label = None):
 
     # --------------------------------------------------------------------
 
+    # error: Argument 1 of "_shallow_copy" is incompatible with supertype
+    #  "ExtensionIndex"; supertype defines the argument type as
+    #  "Optional[ExtensionArray]"  [override]
     @doc(Index._shallow_copy)
-    def _shallow_copy(
-        self, values: Optional[Categorical] = None, name: Label = no_default
+    def _shallow_copy(  # type:ignore[override]
+        self,
+        values: Optional[Categorical] = None,
+        name: Label = no_default,
     ):
         name = self.name if name is no_default else name
 
@@ -247,6 +250,10 @@ def _is_dtype_compat(self, other) -> Categorical:
         provide a comparison between the dtype of self and other (coercing if
         needed)
 
+        Parameters
+        ----------
+        other : Index
+
         Returns
         -------
         Categorical
@@ -263,8 +270,6 @@ def _is_dtype_compat(self, other) -> Categorical:
                 )
         else:
             values = other
-            if not is_list_like(values):
-                values = [values]
 
             cat = Categorical(other, dtype=self.dtype)
             other = CategoricalIndex(cat)
@@ -358,11 +363,6 @@ def values(self):
         """ return the underlying data, which is a Categorical """
         return self._data
 
-    @property
-    def _has_complex_internals(self) -> bool:
-        # used to avoid libreduction code paths, which raise or require conversion
-        return True
-
     @doc(Index.__contains__)
     def __contains__(self, key: Any) -> bool:
         # if key is a NaN, check if any NaN is in self.
@@ -399,11 +399,6 @@ def unique(self, level=None):
         #  of result, not self.
         return type(self)._simple_new(result, name=self.name)
 
-    @doc(Index.duplicated)
-    def duplicated(self, keep="first"):
-        codes = self.codes.astype("i8")
-        return duplicated_int64(codes, keep)
-
     def _to_safe_for_reshape(self):
         """ convert to object if we are a categorical """
         return self.astype("object")
@@ -482,7 +477,7 @@ def reindex(self, target, method=None, level=None, limit=None, tolerance=None):
         new_target = np.asarray(new_target)
         if is_categorical_dtype(target):
             new_target = Categorical(new_target, dtype=target.dtype)
-            new_target = target._shallow_copy(new_target, name=self.name)
+            new_target = type(self)._simple_new(new_target, name=self.name)
         else:
             new_target = Index(new_target, name=self.name)
 
@@ -506,7 +501,7 @@ def _reindex_non_unique(self, target):
             # .reindex returns normal Index. Revert to CategoricalIndex if
             # all targets are included in my categories
             new_target = Categorical(new_target, dtype=self.dtype)
-            new_target = self._shallow_copy(new_target)
+            new_target = type(self)._simple_new(new_target, name=self.name)
 
         return new_target, indexer, new_indexer
 

pandas/core/indexes/datetimelike.py

@@ -10,7 +10,6 @@
 from pandas._libs.tslibs import BaseOffset, Resolution, Tick
 from pandas._typing import Callable, Label
 from pandas.compat.numpy import function as nv
-from pandas.errors import AbstractMethodError
 from pandas.util._decorators import Appender, cache_readonly, doc
 
 from pandas.core.dtypes.common import (
@@ -124,16 +123,6 @@ def _simple_new(
     def _is_all_dates(self) -> bool:
         return True
 
-    def _shallow_copy(self, values=None, name: Label = lib.no_default):
-        name = self.name if name is lib.no_default else name
-
-        if values is not None:
-            return self._simple_new(values, name=name)
-
-        result = self._simple_new(self._data, name=name)
-        result._cache = self._cache
-        return result
-
     # ------------------------------------------------------------------------
     # Abstract data attributes
 
@@ -399,7 +388,7 @@ def _format_with_header(
 
     @property
     def _formatter_func(self):
-        raise AbstractMethodError(self)
+        return self._data._formatter()
 
     def _format_attrs(self):
         """
@@ -692,6 +681,11 @@ def _with_freq(self, freq):
         arr = self._data._with_freq(freq)
         return type(self)._simple_new(arr, name=self.name)
 
+    @property
+    def _has_complex_internals(self) -> bool:
+        # used to avoid libreduction code paths, which raise or require conversion
+        return False
+
     # --------------------------------------------------------------------
     # Set Operation Methods
 

pandas/core/indexes/datetimes.py

@@ -20,11 +20,8 @@
 
 from pandas.core.dtypes.common import (
     DT64NS_DTYPE,
-    is_datetime64_any_dtype,
     is_datetime64_dtype,
     is_datetime64tz_dtype,
-    is_float,
-    is_integer,
     is_scalar,
 )
 from pandas.core.dtypes.missing import is_valid_nat_for_dtype
@@ -354,8 +351,6 @@ def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
         """
         Can we compare values of the given dtype to our own?
         """
-        if not is_datetime64_any_dtype(dtype):
-            return False
         if self.tz is not None:
             # If we have tz, we can compare to tzaware
             return is_datetime64tz_dtype(dtype)
@@ -720,9 +715,6 @@ def _maybe_cast_slice_bound(self, label, side: str, kind):
         """
         assert kind in ["loc", "getitem", None]
 
-        if is_float(label) or isinstance(label, time) or is_integer(label):
-            self._invalid_indexer("slice", label)
-
         if isinstance(label, str):
             freq = getattr(self, "freqstr", getattr(self, "inferred_freq", None))
             parsed, reso = parsing.parse_time_string(label, freq)
@@ -739,6 +731,9 @@ def _maybe_cast_slice_bound(self, label, side: str, kind):
             return lower if side == "left" else upper
         elif isinstance(label, (self._data._recognized_scalars, date)):
             self._deprecate_mismatched_indexing(label)
+        else:
+            self._invalid_indexer("slice", label)
+
         return self._maybe_cast_for_get_loc(label)
 
     def _get_string_slice(self, key: str):

pandas/core/indexes/extension.py

@@ -1,10 +1,12 @@
 """
 Shared methods for Index subclasses backed by ExtensionArray.
 """
-from typing import List, TypeVar
+from typing import List, Optional, TypeVar
 
 import numpy as np
 
+from pandas._libs import lib
+from pandas._typing import Label
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly, doc
@@ -211,6 +213,24 @@ class ExtensionIndex(Index):
     __le__ = _make_wrapped_comparison_op("__le__")
     __ge__ = _make_wrapped_comparison_op("__ge__")
 
+    @doc(Index._shallow_copy)
+    def _shallow_copy(
+        self, values: Optional[ExtensionArray] = None, name: Label = lib.no_default
+    ):
+        name = self.name if name is lib.no_default else name
+
+        if values is not None:
+            return self._simple_new(values, name=name)
+
+        result = self._simple_new(self._data, name=name)
+        result._cache = self._cache
+        return result
+
+    @property
+    def _has_complex_internals(self) -> bool:
+        # used to avoid libreduction code paths, which raise or require conversion
+        return True
+
     # ---------------------------------------------------------------------
     # NDarray-Like Methods
 
@@ -251,7 +271,7 @@ def _get_engine_target(self) -> np.ndarray:
     def repeat(self, repeats, axis=None):
         nv.validate_repeat(tuple(), dict(axis=axis))
         result = self._data.repeat(repeats, axis=axis)
-        return self._shallow_copy(result)
+        return type(self)._simple_new(result, name=self.name)
 
     def insert(self, loc: int, item):
         # ExtensionIndex subclasses must override Index.insert

pandas/core/indexes/interval.py

@@ -320,19 +320,6 @@ def from_tuples(
 
     # --------------------------------------------------------------------
 
-    @Appender(Index._shallow_copy.__doc__)
-    def _shallow_copy(
-        self, values: Optional[IntervalArray] = None, name: Label = lib.no_default
-    ):
-        name = self.name if name is lib.no_default else name
-
-        if values is not None:
-            return self._simple_new(values, name=name)
-
-        result = self._simple_new(self._data, name=name)
-        result._cache = self._cache
-        return result
-
     @cache_readonly
     def _engine(self):
         left = self._maybe_convert_i8(self.left)
@@ -373,11 +360,6 @@ def values(self) -> IntervalArray:
         """
         return self._data
 
-    @property
-    def _has_complex_internals(self) -> bool:
-        # used to avoid libreduction code paths, which raise or require conversion
-        return True
-
     def __array_wrap__(self, result, context=None):
         # we don't want the superclass implementation
         return result
@@ -893,7 +875,7 @@ def delete(self, loc):
         new_left = self.left.delete(loc)
         new_right = self.right.delete(loc)
         result = IntervalArray.from_arrays(new_left, new_right, closed=self.closed)
-        return self._shallow_copy(result)
+        return type(self)._simple_new(result, name=self.name)
 
     def insert(self, loc, item):
         """
@@ -915,7 +897,7 @@ def insert(self, loc, item):
         new_left = self.left.insert(loc, left_insert)
         new_right = self.right.insert(loc, right_insert)
         result = IntervalArray.from_arrays(new_left, new_right, closed=self.closed)
-        return self._shallow_copy(result)
+        return type(self)._simple_new(result, name=self.name)
 
     # --------------------------------------------------------------------
     # Rendering Methods

pandas/core/indexes/multi.py

@@ -3629,7 +3629,7 @@ def astype(self, dtype, copy=True):
             return self._shallow_copy()
         return self
 
-    def _validate_insert_value(self, item):
+    def _validate_fill_value(self, item):
         if not isinstance(item, tuple):
             # Pad the key with empty strings if lower levels of the key
             # aren't specified:
@@ -3652,7 +3652,7 @@ def insert(self, loc: int, item):
         -------
         new_index : Index
         """
-        item = self._validate_insert_value(item)
+        item = self._validate_fill_value(item)
 
         new_levels = []
         new_codes = []

pandas/core/indexes/period.py

@@ -251,11 +251,6 @@ def __new__(
     def values(self) -> np.ndarray:
         return np.asarray(self)
 
-    @property
-    def _has_complex_internals(self) -> bool:
-        # used to avoid libreduction code paths, which raise or require conversion
-        return True
-
     def _maybe_convert_timedelta(self, other):
         """
         Convert timedelta-like input to an integer multiple of self.freq
@@ -307,10 +302,6 @@ def _mpl_repr(self):
         # how to represent ourselves to matplotlib
         return self.astype(object)._values
 
-    @property
-    def _formatter_func(self):
-        return self._data._formatter(boxed=False)
-
     # ------------------------------------------------------------------------
     # Indexing
 

pandas/core/indexes/timedeltas.py

@@ -157,13 +157,6 @@ def __new__(
         )
         return cls._simple_new(tdarr, name=name)
 
-    # -------------------------------------------------------------------
-    # Rendering Methods
-
-    @property
-    def _formatter_func(self):
-        return self._data._formatter()
-
     # -------------------------------------------------------------------
 
     @doc(Index.astype)