BUG: Index.get_loc(np.nan) non-unique non-monotonic

doc/source/whatsnew/v1.4.0.rst

@@ -431,7 +431,8 @@ Indexing
 - Bug in :meth:`DataFrame.drop` where the error message did not show missing labels with commas when raising ``KeyError`` (:issue:`42881`)
 - Bug in :meth:`DataFrame.query` where method calls in query strings led to errors when the ``numexpr`` package was installed. (:issue:`22435`)
 - Bug in :meth:`DataFrame.nlargest` and :meth:`Series.nlargest` where sorted result did not count indexes containing ``np.nan`` (:issue:`28984`)
-
+- Bug in indexing on a non-unique object-dtype :class:`Index` with an NA scalar (e.g. ``np.nan``) (:issue:`43711`)
+-
 
 Missing
 ^^^^^^^

pandas/_libs/index.pyx

@@ -34,7 +34,11 @@ from pandas._libs import (
     algos,
     hashtable as _hash,
 )
-from pandas._libs.missing import checknull
+
+from pandas._libs.missing cimport (
+    checknull,
+    is_matching_na,
+)
 
 
 cdef inline bint is_definitely_invalid_key(object val):
@@ -146,9 +150,17 @@ cdef class IndexEngine:
         cdef:
             ndarray[uint8_t, ndim=1, cast=True] indexer
 
-        indexer = self.values == val
+        indexer = self._get_bool_indexer(val)
         return self._unpack_bool_indexer(indexer, val)
 
+    cdef ndarray _get_bool_indexer(self, object val):
+        """
+        Return a ndarray[bool] of locations where val matches self.values.
+
+        If val is not NA, this is equivalent to `self.values == val`
+        """
+        raise NotImplementedError("Implemented by subclasses")
+
     cdef _unpack_bool_indexer(self,
                               ndarray[uint8_t, ndim=1, cast=True] indexer,
                               object val):
@@ -420,6 +432,25 @@ cdef class ObjectEngine(IndexEngine):
             raise KeyError(val) from err
         return loc
 
+    cdef ndarray _get_bool_indexer(self, object val):
+        # We need to check for equality and for matching NAs
+        cdef:
+            ndarray values = self.values
+
+        if not checknull(val):
+            return values == val
+
+        cdef:
+            ndarray[uint8_t] result = np.empty(len(values), dtype=np.uint8)
+            Py_ssize_t i
+            object item
+
+        for i in range(len(values)):
+            item = values[i]
+            result[i] = is_matching_na(item, val)
+
+        return result.view(bool)
+
 
 cdef class DatetimeEngine(Int64Engine):
 

pandas/_libs/index_class_helper.pxi.in

@@ -45,8 +45,7 @@ cdef class {{name}}Engine(IndexEngine):
     cdef void _call_map_locations(self, ndarray[{{dtype}}_t] values):
         self.mapping.map_locations(values)
 
-    cdef _maybe_get_bool_indexer(self, object val):
-        # Returns ndarray[bool] or int
+    cdef ndarray _get_bool_indexer(self, object val):
         cdef:
             ndarray[uint8_t, ndim=1, cast=True] indexer
             ndarray[{{dtype}}_t, ndim=1] values
@@ -71,6 +70,7 @@ cdef class {{name}}Engine(IndexEngine):
             #  when trying to cast it to ndarray
             raise KeyError(val)
 
-        return self._unpack_bool_indexer(indexer, val)
+        return indexer
+
 
 {{endfor}}

pandas/tests/indexes/base_class/test_indexing.py

@@ -2,7 +2,10 @@
 import pytest
 
 import pandas as pd
-from pandas import Index
+from pandas import (
+    Index,
+    NaT,
+)
 import pandas._testing as tm
 
 
@@ -56,3 +59,20 @@ def test_get_loc_tuple_monotonic_above_size_cutoff(self):
 
         res = oidx.get_loc(tup)
         assert res == loc
+
+    def test_get_loc_nan_object_dtype_nonmonotonic_nonunique(self):
+        # case that goes through _maybe_get_bool_indexer
+        idx = Index(["foo", np.nan, None, "foo", 1.0, None], dtype=object)
+
+        # we dont raise KeyError on nan
+        res = idx.get_loc(np.nan)
+        assert res == 1
+
+        # we only match on None, not on np.nan
+        res = idx.get_loc(None)
+        expected = np.array([False, False, True, False, False, True])
+        tm.assert_numpy_array_equal(res, expected)
+
+        # we don't match at all on mismatched NA
+        with pytest.raises(KeyError, match="NaT"):
+            idx.get_loc(NaT)