chabge _is_numeric_index to be an attribute

Author: topper-123

pandas/core/indexes/base.py

@@ -359,6 +359,9 @@ def _outer_indexer(
     _is_numeric_dtype: bool = False
     _can_hold_na: bool = True
     _can_hold_strings: bool = True
+    # Whether this index is a NumericIndex, but not a Int64Index, Float64Index,
+    # UInt64Index or RangeIndex
+    _is_numeric_index: bool = False
 
     _engine_type: type[libindex.IndexEngine] = libindex.ObjectEngine
     # whether we support partial string indexing. Overridden
@@ -437,7 +440,7 @@ def __new__(
             return Index._simple_new(data, name=name)
 
         # index-like
-        elif isinstance(data, Index) and data._is_numeric_index() and dtype is None:
+        elif isinstance(data, Index) and data._is_numeric_index and dtype is None:
             return type(data)(data, name=name, copy=copy)
         elif isinstance(data, (np.ndarray, Index, ABCSeries)):
 
@@ -5745,7 +5748,7 @@ def map(self, mapper, na_action=None):
             # empty
             attributes["dtype"] = self.dtype
 
-        if self._is_numeric_index() and is_numeric_dtype(new_values.dtype):
+        if self._is_numeric_index and is_numeric_dtype(new_values.dtype):
             return type(self)(new_values, **attributes)
 
         return Index(new_values, **attributes)

pandas/core/indexes/category.py

@@ -291,7 +291,7 @@ def astype(self, dtype, copy: bool = True) -> Index:
         # the super method always returns Int64Index, UInt64Index and Float64Index
         # but if e.g. the categories are a NumIndex with dtype float32, we want to
         # return an index with the same dtype as self.categories.
-        if categories._is_numeric_index():
+        if categories._is_numeric_index:
             assert isinstance(categories, NumericIndex)  # mypy complaint fix
             try:
                 categories._validate_dtype(dtype)

pandas/core/indexes/numeric.py

@@ -97,6 +97,7 @@ class NumericIndex(Index):
     )
     _is_numeric_dtype = True
     _can_hold_strings = False
+    _is_numeric_index: bool = True
 
     @cache_readonly
     def _can_hold_na(self) -> bool:
@@ -374,6 +375,8 @@ class IntegerIndex(NumericIndex):
     This is an abstract class for Int64Index, UInt64Index.
     """
 
+    _is_numeric_index: bool = False
+
     @property
     def asi8(self) -> np.ndarray:
         # do not cache or you'll create a memory leak
@@ -438,3 +441,4 @@ class Float64Index(NumericIndex):
     _engine_type = libindex.Float64Engine
     _default_dtype = np.dtype(np.float64)
     _dtype_validation_metadata = (is_float_dtype, "float")
+    _is_numeric_index: bool = False

pandas/core/indexes/range.py

@@ -101,6 +101,7 @@ class RangeIndex(NumericIndex):
     _engine_type = libindex.Int64Engine
     _dtype_validation_metadata = (is_signed_integer_dtype, "signed integer")
     _range: range
+    _is_numeric_index: bool = False
 
     # --------------------------------------------------------------------
     # Constructors

pandas/tests/base/test_unique.py

@@ -25,7 +25,7 @@ def test_unique(index_or_series_obj):
         expected = pd.MultiIndex.from_tuples(unique_values)
         expected.names = obj.names
         tm.assert_index_equal(result, expected, exact=True)
-    elif isinstance(obj, pd.Index) and obj._is_numeric_index():
+    elif isinstance(obj, pd.Index) and obj._is_numeric_index:
         expected = NumericIndex(unique_values, dtype=obj.dtype)
         tm.assert_index_equal(result, expected, exact=True)
     elif isinstance(obj, pd.Index):
@@ -66,7 +66,7 @@ def test_unique_null(null_obj, index_or_series_obj):
     unique_values_not_null = [val for val in unique_values_raw if not pd.isnull(val)]
     unique_values = [null_obj] + unique_values_not_null
 
-    if isinstance(obj, pd.Index) and obj._is_numeric_index():
+    if isinstance(obj, pd.Index) and obj._is_numeric_index:
         expected = NumericIndex(unique_values, dtype=obj.dtype)
         tm.assert_index_equal(result, expected, exact=True)
     elif isinstance(obj, pd.Index):

pandas/tests/indexes/common.py

@@ -665,7 +665,7 @@ def test_map_dictlike(self, mapper, simple_index):
         tm.assert_index_equal(result, expected)
 
         # empty mappable
-        if idx._is_numeric_index():
+        if idx._is_numeric_index:
             new_index_cls = NumericIndex
         else:
             new_index_cls = Float64Index

pandas/tests/indexes/test_base.py

@@ -713,7 +713,7 @@ def test_map_dictlike(self, index, mapper):
         if index.empty:
             # to match proper result coercion for uints
             expected = Index([])
-        elif index._is_numeric_index():
+        elif index._is_numeric_index:
             expected = type(index)(np.arange(len(index), 0, -1), dtype=index.dtype)
         else:
             expected = Index(np.arange(len(index), 0, -1))