Handle dtype correctly

Author: TomAugspurger

pandas/core/series.py

@@ -41,7 +41,11 @@
     maybe_cast_to_datetime, maybe_castable,
     construct_1d_arraylike_from_scalar,
     construct_1d_object_array_from_listlike)
-from pandas.core.dtypes.missing import isna, notna, remove_na_arraylike
+from pandas.core.dtypes.missing import (
+    isna,
+    notna,
+    remove_na_arraylike,
+    na_value_for_dtype)
 
 from pandas.core.index import (Index, MultiIndex, InvalidIndexError,
                                Float64Index, _ensure_index)
@@ -219,7 +223,7 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
             elif isinstance(data, dict):
                 # Same as previous block, but special cased for data=None,
                 # for performance when creating empty arrays.
-                data = np.nan
+                data = na_value_for_dtype(dtype)
 
             elif isinstance(data, SingleBlockManager):
                 if index is None:

pandas/tests/series/test_constructors.py

@@ -122,6 +122,17 @@ def test_constructor_nan(self, input_arg):
 
         assert_series_equal(empty, empty2, check_index_type=False)
 
+    @pytest.mark.parametrize('dtype', [
+        'f8', 'i8', 'M8[ns]', 'm8[ns]', 'category', 'object',
+        'datetime64[ns, UTC]',
+    ])
+    @pytest.mark.parametrize('index', [None, pd.Index([])])
+    def test_constructor_dtype_only(self, dtype, index):
+        # GH-20865
+        result = pd.Series(dtype=dtype, index=index)
+        assert result.dtype == dtype
+        assert len(result) == 0
+
     def test_constructor_series(self):
         index1 = ['d', 'b', 'a', 'c']
         index2 = sorted(index1)