BUG: support casting from bool array to EA Integer dtype (#25265)

Author: vladserkoff

doc/source/whatsnew/v0.25.0.rst

@@ -309,8 +309,9 @@ Numeric
 - Bug in :meth:`Series.divmod` and :meth:`Series.rdivmod` which would raise an (incorrect) ``ValueError`` rather than return a pair of :class:`Series` objects as result (:issue:`25557`)
 - Raises a helpful exception when a non-numeric index is sent to :meth:`interpolate` with methods which require numeric index. (:issue:`21662`)
 - Bug in :meth:`~pandas.eval` when comparing floats with scalar operators, for example: ``x < -0.1`` (:issue:`25928`)
+- Fixed bug where casting all-boolean array to integer extension array failed (:issue:`25211`)
+-
 -
-
 
 Conversion
 ^^^^^^^^^^

pandas/core/arrays/integer.py

@@ -188,6 +188,9 @@ def coerce_to_array(values, dtype, mask=None, copy=False):
             raise TypeError("{} cannot be converted to an IntegerDtype".format(
                 values.dtype))
 
+    elif is_bool_dtype(values) and is_integer_dtype(dtype):
+        values = np.array(values, dtype=int, copy=copy)
+
     elif not (is_integer_dtype(values) or is_float_dtype(values)):
         raise TypeError("{} cannot be converted to an IntegerDtype".format(
             values.dtype))

pandas/core/series.py

@@ -2670,7 +2670,6 @@ def combine(self, other, func, fill_value=None):
                 # do in _values_from_sequence. We still want ops to work
                 # though, so we catch any regular Exception.
                 pass
-
         return self._constructor(new_values, index=new_index, name=new_name)
 
     def combine_first(self, other):

pandas/tests/arrays/test_integer.py

@@ -613,6 +613,19 @@ def test_to_integer_array_float():
     assert result.dtype == Int64Dtype()
 
 
+@pytest.mark.parametrize(
+    'bool_values, int_values, target_dtype, expected_dtype',
+    [([False, True], [0, 1], Int64Dtype(), Int64Dtype()),
+     ([False, True], [0, 1], 'Int64', Int64Dtype()),
+     ([False, True, np.nan], [0, 1, np.nan], Int64Dtype(), Int64Dtype())])
+def test_to_integer_array_bool(bool_values, int_values, target_dtype,
+                               expected_dtype):
+    result = integer_array(bool_values, dtype=target_dtype)
+    assert result.dtype == expected_dtype
+    expected = integer_array(int_values, dtype=target_dtype)
+    tm.assert_extension_array_equal(result, expected)
+
+
 @pytest.mark.parametrize(
     'values, to_dtype, result_dtype',
     [