BUG: Series construction with EA dtype and index but no data fails

doc/source/whatsnew/v1.1.0.rst

@@ -737,7 +737,7 @@ ExtensionArray
 ^^^^^^^^^^^^^^
 
 - Fixed bug where :meth:`Series.value_counts` would raise on empty input of ``Int64`` dtype (:issue:`33317`)
--
+- Fixed bug in :class:`Series` construction with EA dtype and index but no data or scalar data fails (:issue:`26469`)
 
 
 Other

pandas/core/construction.py

@@ -450,6 +450,11 @@ def sanitize_array(
         subarr = _try_cast(arr, dtype, copy, raise_cast_failure)
     elif isinstance(data, abc.Set):
         raise TypeError("Set type is unordered")
+    elif lib.is_scalar(data) and index is not None and dtype is not None:
+        data = maybe_cast_to_datetime(data, dtype)
+        if not lib.is_scalar(data):
+            data = data[0]
+        subarr = construct_1d_arraylike_from_scalar(data, len(index), dtype)
     else:
         subarr = _try_cast(data, dtype, copy, raise_cast_failure)
 
@@ -516,7 +521,7 @@ def _try_cast(
 
     Parameters
     ----------
-    arr : ndarray, list, tuple, iterator (catchall)
+    arr : ndarray, scalar, list, tuple, iterator (catchall)
         Excludes: ExtensionArray, Series, Index.
     dtype : np.dtype, ExtensionDtype or None
     copy : bool

pandas/core/dtypes/cast.py

@@ -1384,7 +1384,9 @@ def maybe_cast_to_datetime(value, dtype, errors: str = "raise"):
                         pass
 
         # coerce datetimelike to object
-        elif is_datetime64_dtype(value) and not is_datetime64_dtype(dtype):
+        elif is_datetime64_dtype(
+            getattr(value, "dtype", None)
+        ) and not is_datetime64_dtype(dtype):
             if is_object_dtype(dtype):
                 if value.dtype != DT64NS_DTYPE:
                     value = value.astype(DT64NS_DTYPE)

pandas/tests/extension/arrow/test_bool.py

@@ -55,6 +55,16 @@ def test_from_dtype(self, data):
     def test_from_sequence_from_cls(self, data):
         super().test_from_sequence_from_cls(data)
 
+    @pytest.mark.xfail(reason="pa.NULL is not recognised as scalar, GH-33899")
+    def test_series_constructor_no_data_with_index(self, dtype, na_value):
+        # pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays
+        super().test_series_constructor_no_data_with_index(dtype, na_value)
+
+    @pytest.mark.xfail(reason="pa.NULL is not recognised as scalar, GH-33899")
+    def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
+        # pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays
+        super().test_series_constructor_scalar_na_with_index(dtype, na_value)
+
 
 class TestReduce(base.BaseNoReduceTests):
     def test_reduce_series_boolean(self):

pandas/tests/extension/base/constructors.py

@@ -33,6 +33,31 @@ def test_series_constructor(self, data):
         assert result2.dtype == data.dtype
         assert isinstance(result2._mgr.blocks[0], ExtensionBlock)
 
+    def test_series_constructor_no_data_with_index(self, dtype, na_value):
+        result = pd.Series(index=[1, 2, 3], dtype=dtype)
+        expected = pd.Series([na_value] * 3, index=[1, 2, 3], dtype=dtype)
+        self.assert_series_equal(result, expected)
+
+        # GH 33559 - empty index
+        result = pd.Series(index=[], dtype=dtype)
+        expected = pd.Series([], index=pd.Index([], dtype="object"), dtype=dtype)
+        self.assert_series_equal(result, expected)
+
+    def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
+        result = pd.Series(na_value, index=[1, 2, 3], dtype=dtype)
+        expected = pd.Series([na_value] * 3, index=[1, 2, 3], dtype=dtype)
+        self.assert_series_equal(result, expected)
+
+    def test_series_constructor_scalar_with_index(self, data, dtype):
+        scalar = data[0]
+        result = pd.Series(scalar, index=[1, 2, 3], dtype=dtype)
+        expected = pd.Series([scalar] * 3, index=[1, 2, 3], dtype=dtype)
+        self.assert_series_equal(result, expected)
+
+        result = pd.Series(scalar, index=["foo"], dtype=dtype)
+        expected = pd.Series([scalar], index=["foo"], dtype=dtype)
+        self.assert_series_equal(result, expected)
+
     @pytest.mark.parametrize("from_series", [True, False])
     def test_dataframe_constructor_from_dict(self, data, from_series):
         if from_series:

pandas/tests/extension/json/test_json.py

@@ -150,6 +150,21 @@ def test_from_dtype(self, data):
         # construct from our dtype & string dtype
         pass
 
+    @pytest.mark.xfail(reason="RecursionError, GH-33900")
+    def test_series_constructor_no_data_with_index(self, dtype, na_value):
+        # RecursionError: maximum recursion depth exceeded in comparison
+        super().test_series_constructor_no_data_with_index(dtype, na_value)
+
+    @pytest.mark.xfail(reason="RecursionError, GH-33900")
+    def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
+        # RecursionError: maximum recursion depth exceeded in comparison
+        super().test_series_constructor_scalar_na_with_index(dtype, na_value)
+
+    @pytest.mark.xfail(reason="collection as scalar, GH-33901")
+    def test_series_constructor_scalar_with_index(self, data, dtype):
+        # TypeError: All values must be of type <class 'collections.abc.Mapping'>
+        super().test_series_constructor_scalar_with_index(data, dtype)
+
 
 class TestReshaping(BaseJSON, base.BaseReshapingTests):
     @pytest.mark.skip(reason="Different definitions of NA")

pandas/tests/extension/test_numpy.py

@@ -151,6 +151,11 @@ def test_array_from_scalars(self, data):
         # ValueError: PandasArray must be 1-dimensional.
         super().test_array_from_scalars(data)
 
+    @skip_nested
+    def test_series_constructor_scalar_with_index(self, data, dtype):
+        # ValueError: Length of passed values is 1, index implies 3.
+        super().test_series_constructor_scalar_with_index(data, dtype)
+
 
 class TestDtype(BaseNumPyTests, base.BaseDtypeTests):
     @pytest.mark.skip(reason="Incorrect expected.")

pandas/tests/series/test_constructors.py

@@ -1444,3 +1444,9 @@ def test_constructor_datetime64(self):
 
         series = Series(dates)
         assert np.issubdtype(series.dtype, np.dtype("M8[ns]"))
+
+    def test_constructor_datetimelike_scalar_to_string_dtype(self):
+        # https://github.com/pandas-dev/pandas/pull/33846
+        result = Series("M", index=[1, 2, 3], dtype="string")
+        expected = pd.Series(["M", "M", "M"], index=[1, 2, 3], dtype="string")
+        tm.assert_series_equal(result, expected)