BUG: Fix MultiIndex.at lookup with pd.NA in Int64Dtype level

Author: parthava-adabala

doc/source/whatsnew/v3.0.0.rst

@@ -1132,6 +1132,7 @@ Interval
 
 Indexing
 ^^^^^^^^
+- Bug in :func:`pandas.concat` incorrectly constructing the :class:`MultiIndex` when an inner level contained :obj:`pandas.NA` with :class:`pandas.Int64Dtype`, causing a :exc:`KeyError` on lookup (:issue:`62903`)
 - Bug in :meth:`DataFrame.__getitem__` returning modified columns when called with ``slice`` in Python 3.12 (:issue:`57500`)
 - Bug in :meth:`DataFrame.__getitem__` when slicing a :class:`DataFrame` with many rows raised an ``OverflowError`` (:issue:`59531`)
 - Bug in :meth:`DataFrame.__setitem__` on an empty :class:`DataFrame` with a tuple corrupting the frame (:issue:`54385`)

pandas/core/indexes/multi.py

@@ -3325,6 +3325,12 @@ def _maybe_to_slice(loc):
             try:
                 return self._engine.get_loc(key)
             except KeyError as err:
+                if any(isna(k) for k in key):
+                    loc, _ = self.get_loc_level(
+                        key, range(self.nlevels), drop_level=False
+                    )
+                    if lib.is_integer(loc):
+                        return loc
                 raise KeyError(key) from err
             except TypeError:
                 # e.g. test_partial_slicing_with_multiindex partial string slicing

pandas/tests/indexes/multi/test_indexing.py

@@ -710,6 +710,14 @@ def test_get_loc_nan(self, level, nulls_fixture):
         idx = MultiIndex.from_product(levels)
         assert idx.get_loc(tuple(key)) == 3
 
+    def test_multiindex_at_lookup_with_na_key(self):
+        index = MultiIndex(levels=[[1, 2], [2, pd.NA]], codes=[[0, 1], [0, 1]])
+        df = DataFrame({"a": [1, 2]}, index=index)
+        result = df.at[(2, pd.NA), "a"]
+        assert result == 2
+        loc_result = df.loc[(2, pd.NA), "a"]
+        assert loc_result == 2
+
     def test_get_loc_missing_nan(self):
         # GH 8569
         idx = MultiIndex.from_arrays([[1.0, 2.0], [3.0, 4.0]])