BUG: IntervalArray.__eq__ not deferring to Series

doc/source/whatsnew/v1.2.0.rst

@@ -368,6 +368,7 @@ Numeric
 - Bug in :class:`IntegerArray` multiplication with ``timedelta`` and ``np.timedelta64`` objects (:issue:`36870`)
 - Bug in :meth:`DataFrame.diff` with ``datetime64`` dtypes including ``NaT`` values failing to fill ``NaT`` results correctly (:issue:`32441`)
 - Bug in :class:`DataFrame` arithmetic ops incorrectly accepting keyword arguments (:issue:`36843`)
+- Bug in :class:`IntervalArray` comparisons with :class:`Series` not returning :class:`Series` (:issue:`36908`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/arrays/interval.py

@@ -48,6 +48,7 @@
 from pandas.core.construction import array, extract_array
 from pandas.core.indexers import check_array_indexer
 from pandas.core.indexes.base import ensure_index
+from pandas.core.ops import unpack_zerodim_and_defer
 
 if TYPE_CHECKING:
     from pandas import Index
@@ -519,6 +520,7 @@ def __setitem__(self, key, value):
         self._left[key] = value_left
         self._right[key] = value_right
 
+    @unpack_zerodim_and_defer("__eq__")
     def __eq__(self, other):
         # ensure pandas array for list-like and eliminate non-interval scalars
         if is_list_like(other):

pandas/core/indexes/base.py

@@ -27,7 +27,6 @@
 from pandas._libs.tslibs.period import IncompatibleFrequency
 from pandas._libs.tslibs.timezones import tz_compare
 from pandas._typing import AnyArrayLike, Dtype, DtypeObj, Label
-from pandas.compat import set_function_name
 from pandas.compat.numpy import function as nv
 from pandas.errors import DuplicateLabelError, InvalidIndexError
 from pandas.util._decorators import Appender, cache_readonly, doc
@@ -68,7 +67,6 @@
 from pandas.core.dtypes.concat import concat_compat
 from pandas.core.dtypes.generic import (
     ABCCategorical,
-    ABCDataFrame,
     ABCDatetimeIndex,
     ABCMultiIndex,
     ABCPandasArray,
@@ -122,22 +120,6 @@
 str_t = str
 
 
-def _make_arithmetic_op(op, cls):
-    def index_arithmetic_method(self, other):
-        if isinstance(other, (ABCSeries, ABCDataFrame, ABCTimedeltaIndex)):
-            return NotImplemented
-
-        from pandas import Series
-
-        result = op(Series(self), other)
-        if isinstance(result, tuple):
-            return (Index(result[0]), Index(result[1]))
-        return Index(result)
-
-    name = f"__{op.__name__}__"
-    return set_function_name(index_arithmetic_method, name, cls)
-
-
 _o_dtype = np.dtype(object)
 _Identity = object
 
@@ -5380,7 +5362,7 @@ def _cmp_method(self, other, op):
         Wrapper used to dispatch comparison operations.
         """
         if isinstance(other, (np.ndarray, Index, ABCSeries, ExtensionArray)):
-            if other.ndim > 0 and len(self) != len(other):
+            if len(self) != len(other):
                 raise ValueError("Lengths must match to compare")
 
         if is_object_dtype(self.dtype) and isinstance(other, ABCCategorical):

pandas/tests/arithmetic/test_interval.py

@@ -103,7 +103,10 @@ def elementwise_comparison(self, op, array, other):
         Helper that performs elementwise comparisons between `array` and `other`
         """
         other = other if is_list_like(other) else [other] * len(array)
-        return np.array([op(x, y) for x, y in zip(array, other)])
+        expected = np.array([op(x, y) for x, y in zip(array, other)])
+        if isinstance(other, Series):
+            return Series(expected, index=other.index)
+        return expected
 
     def test_compare_scalar_interval(self, op, array):
         # matches first interval
@@ -161,19 +164,19 @@ def test_compare_list_like_interval(self, op, array, interval_constructor):
         other = interval_constructor(array.left, array.right)
         result = op(array, other)
         expected = self.elementwise_comparison(op, array, other)
-        tm.assert_numpy_array_equal(result, expected)
+        tm.assert_equal(result, expected)
 
         # different endpoints
         other = interval_constructor(array.left[::-1], array.right[::-1])
         result = op(array, other)
         expected = self.elementwise_comparison(op, array, other)
-        tm.assert_numpy_array_equal(result, expected)
+        tm.assert_equal(result, expected)
 
         # all nan endpoints
         other = interval_constructor([np.nan] * 4, [np.nan] * 4)
         result = op(array, other)
         expected = self.elementwise_comparison(op, array, other)
-        tm.assert_numpy_array_equal(result, expected)
+        tm.assert_equal(result, expected)
 
     def test_compare_list_like_interval_mixed_closed(
         self, op, interval_constructor, closed, other_closed
@@ -183,7 +186,7 @@ def test_compare_list_like_interval_mixed_closed(
 
         result = op(array, other)
         expected = self.elementwise_comparison(op, array, other)
-        tm.assert_numpy_array_equal(result, expected)
+        tm.assert_equal(result, expected)
 
     @pytest.mark.parametrize(
         "other",