BUG: Series constructor raising with NA and bools and Int dtype (#50328)

phofl · mroeschke · web-flow · commit 901501375bd4 · 2022-12-19T11:28:49.000-08:00
* BUG: Series constructor raising with NA and bools and Int dtype

* Fix test

* Split tests

* Update doc/source/whatsnew/v2.0.0.rst

Co-authored-by: Matthew Roeschke &lt;10647082+mroeschke@users.noreply.github.com&gt;
diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
@@ -815,6 +815,7 @@ Numeric
 Conversion
 ^^^^^^^^^^
 - Bug in constructing :class:`Series` with ``int64`` dtype from a string list raising instead of casting (:issue:`44923`)
+- Bug in constructing :class:`Series` with masked dtype and boolean values with ``NA`` raising (:issue:`42137`)
 - Bug in :meth:`DataFrame.eval` incorrectly raising an ``AttributeError`` when there are negative values in function call (:issue:`46471`)
 - Bug in :meth:`Series.convert_dtypes` not converting dtype to nullable dtype when :class:`Series` contains ``NA`` and has dtype ``object`` (:issue:`48791`)
 - Bug where any :class:`ExtensionDtype` subclass with ``kind="M"`` would be interpreted as a timezone type (:issue:`34986`)
diff --git a/pandas/core/arrays/numeric.py b/pandas/core/arrays/numeric.py
@@ -172,9 +172,7 @@ def _coerce_to_data_and_mask(values, mask, dtype, copy, dtype_cls, default_dtype
     inferred_type = None
     if is_object_dtype(values.dtype) or is_string_dtype(values.dtype):
         inferred_type = lib.infer_dtype(values, skipna=True)
-        if inferred_type == "empty":
-            pass
-        elif inferred_type == "boolean":
+        if inferred_type == "boolean" and dtype is None:
             name = dtype_cls.__name__.strip("_")
             raise TypeError(f"{values.dtype} cannot be converted to {name}")
 
diff --git a/pandas/tests/series/test_constructors.py b/pandas/tests/series/test_constructors.py
@@ -1987,6 +1987,21 @@ def test_constructor_mismatched_null_nullable_dtype(
             with pytest.raises(TypeError, match=msg):
                 func([null, 1.0, 3.0], dtype=any_numeric_ea_dtype)
 
+    def test_series_constructor_ea_int_from_bool(self):
+        # GH#42137
+        result = Series([True, False, True, pd.NA], dtype="Int64")
+        expected = Series([1, 0, 1, pd.NA], dtype="Int64")
+        tm.assert_series_equal(result, expected)
+
+        result = Series([True, False, True], dtype="Int64")
+        expected = Series([1, 0, 1], dtype="Int64")
+        tm.assert_series_equal(result, expected)
+
+    def test_series_constructor_ea_int_from_string_bool(self):
+        # GH#42137
+        with pytest.raises(ValueError, match="invalid literal"):
+            Series(["True", "False", "True", pd.NA], dtype="Int64")
+
 
 class TestSeriesConstructorIndexCoercion:
     def test_series_constructor_datetimelike_index_coercion(self):
