BUG: float16 index

pandas/core/indexes/numeric.py

@@ -75,8 +75,8 @@ class NumericIndex(Index):
     Notes
     -----
     An NumericIndex instance can **only** contain numpy int64/32/16/8, uint64/32/16/8 or
-    float64/32/16 dtype. In particular, ``NumericIndex`` *can not* hold Pandas numeric
-    dtypes (:class:`Int64Dtype`, :class:`Int32Dtype` etc.).
+    float64/32 dtype. In particular, ``NumericIndex`` *can not* hold numpy float16
+    dtype or Pandas numeric dtypes (:class:`Int64Dtype`, :class:`Int32Dtype` etc.).
     """
 
     _typ = "numericindex"
@@ -175,6 +175,10 @@ def _ensure_array(cls, data, dtype, copy: bool):
             raise ValueError("Index data must be 1-dimensional")
 
         subarr = np.asarray(subarr)
+        if subarr.dtype == "float16":
+            # float16 not supported (no indexing engine)
+            subarr = subarr.astype("float32")
+
         return subarr
 
     @classmethod
@@ -199,6 +203,9 @@ def _ensure_dtype(cls, dtype: Dtype | None) -> np.dtype | None:
             return cls._default_dtype
 
         dtype = pandas_dtype(dtype)
+        if dtype == np.float16:
+            # float16 not supported (no indexing engine)
+            dtype = np.dtype(np.float32)
         assert isinstance(dtype, np.dtype)
 
         if cls._is_backward_compat_public_numeric_index:

pandas/tests/indexes/test_numpy_compat.py

@@ -82,9 +82,15 @@ def test_numpy_ufuncs_basic(index, func):
             assert type(result) is NumericIndex
             if is_complex_dtype(index):
                 assert result.dtype == "complex64"
-            elif index.dtype in ("bool", "int8", "uint8", "float16"):
-                assert result.dtype == "float16"
-            elif index.dtype in ("int16", "uint16", "float32"):
+            elif index.dtype in {
+                "bool",
+                "int8",
+                "int16",
+                "uint8",
+                "uint16",
+                "float16",
+                "float32",
+            }:
                 assert result.dtype == "float32"
             else:
                 assert result.dtype == "float64"