make NumericIndex fail with float16 dtype

Author: Terji Petersen

pandas/core/indexes/numeric.py

@@ -176,7 +176,7 @@ def _ensure_array(cls, data, dtype, copy: bool):
         subarr = np.asarray(subarr)
         if subarr.dtype == "float16":
             # float16 not supported (no indexing engine)
-            subarr = subarr.astype("float32")
+            raise TypeError("float16 indexes are not supported")
 
         return subarr
 
@@ -202,9 +202,9 @@ def _ensure_dtype(cls, dtype: Dtype | None) -> np.dtype | None:
             return cls._default_dtype
 
         dtype = pandas_dtype(dtype)
-        if dtype == np.float16:
+        if dtype == "float16":
             # float16 not supported (no indexing engine)
-            dtype = np.dtype(np.float32)
+            raise TypeError("float16 indexes are not supported")
         assert isinstance(dtype, np.dtype)
 
         if cls._is_backward_compat_public_numeric_index:

pandas/tests/indexes/numeric/test_numeric.py

@@ -557,13 +557,8 @@ class TestFloat16Index:
     # GH 49535
     def test_array(self):
         arr = np.array([1, 2, 3], dtype=np.float16)
-        result = NumericIndex(arr)
-
-        expected = NumericIndex([1, 2, 3], dtype=np.float32)
-        tm.assert_index_equal(result, expected, check_exact=True)
-
-        result = NumericIndex([1, 2, 3], dtype=np.float16)
-        tm.assert_index_equal(result, expected, check_exact=True)
+        with pytest.raises(TypeError, match="float16 indexes are not supported"):
+            result = NumericIndex(arr)
 
 
 class TestUIntNumericIndex(NumericInt):