BUG: IntervalIndex.get_indexer with non-unique side (#62825)

Author: jbrockmendel

doc/source/whatsnew/v3.0.0.rst

@@ -1043,6 +1043,7 @@ Interval
 - :meth:`Index.is_monotonic_decreasing`, :meth:`Index.is_monotonic_increasing`, and :meth:`Index.is_unique` could incorrectly be ``False`` for an ``Index`` created from a slice of another ``Index``. (:issue:`57911`)
 - Bug in :class:`Index`, :class:`Series`, :class:`DataFrame` constructors when given a sequence of :class:`Interval` subclass objects casting them to :class:`Interval` (:issue:`46945`)
 - Bug in :func:`interval_range` where start and end numeric types were always cast to 64 bit (:issue:`57268`)
+- Bug in :meth:`IntervalIndex.get_indexer` and :meth:`IntervalIndex.drop` when one of the sides of the index is non-unique (:issue:`52245`)
 
 Indexing
 ^^^^^^^^

pandas/core/indexes/interval.py

@@ -712,7 +712,10 @@ def _get_indexer(
             # -> at most one match per interval in target
             # want exact matches -> need both left/right to match, so defer to
             # left/right get_indexer, compare elementwise, equality -> match
-            indexer = self._get_indexer_unique_sides(target)
+            if self.left.is_unique and self.right.is_unique:
+                indexer = self._get_indexer_unique_sides(target)
+            else:
+                indexer = self._get_indexer_pointwise(target)[0]
 
         elif not (is_object_dtype(target.dtype) or is_string_dtype(target.dtype)):
             # homogeneous scalar index: use IntervalTree

pandas/tests/indexes/interval/test_indexing.py

@@ -503,6 +503,25 @@ def test_get_indexer_read_only(self):
         result = idx.get_indexer_non_unique(arr)[0]
         tm.assert_numpy_array_equal(result, expected, check_dtype=False)
 
+    def test_get_indexer_non_unique_right(self):
+        # GH#52245
+        data = [
+            Interval(Timestamp("2020-05-26"), Timestamp("2020-05-27")),
+            Interval(Timestamp("2020-05-27"), Timestamp("2020-05-27")),
+        ]
+
+        index = IntervalIndex(data)
+
+        result = index.get_indexer([index[0]])
+        expected = np.array([0], dtype=np.intp)
+        tm.assert_numpy_array_equal(result, expected)
+
+        # GH#52245 OP is about drop so we test that here, but the underlying
+        #  problem is in get_indexer.
+        result = index.drop(index[0])
+        expected = index[1:]
+        tm.assert_index_equal(result, expected)
+
 
 class TestSliceLocs:
     def test_slice_locs_with_interval(self):