BUG: support casting from bool array to EA Integer dtype

pandas/core/series.py

@@ -22,8 +22,7 @@
     _is_unorderable_exception, ensure_platform_int, is_bool,
     is_categorical_dtype, is_datetime64_dtype, is_datetimelike, is_dict_like,
     is_extension_array_dtype, is_extension_type, is_hashable, is_integer,
-    is_iterator, is_list_like, is_scalar, is_sparse, is_string_like,
-    is_timedelta64_dtype)
+    is_iterator, is_list_like, is_scalar, is_string_like, is_timedelta64_dtype)
 from pandas.core.dtypes.generic import (
     ABCDataFrame, ABCDatetimeArray, ABCDatetimeIndex, ABCSeries,
     ABCSparseArray, ABCSparseSeries)
@@ -2635,30 +2634,29 @@ def combine(self, other, func, fill_value=None):
                 rv = other.get(idx, fill_value)
                 with np.errstate(all='ignore'):
                     new_values.append(func(lv, rv))
+            new_dtype = type(func(lv, rv))
         else:
             # Assume that other is a scalar, so apply the function for
             # each element in the Series
             new_index = self.index
             with np.errstate(all='ignore'):
                 new_values = [func(lv, other) for lv in self._values]
             new_name = self.name
+            new_dtype = type(func(self._values[0], other))
 
         if is_categorical_dtype(self.values):
             pass
-        elif is_bool(new_values[0]) and not is_sparse(self.values):
-            pass
         elif is_extension_array_dtype(self.values):
             # The function can return something of any type, so check
             # if the type is compatible with the calling EA.
             try:
-                new_values = self._values._from_sequence(new_values)
+                new_values = self._values._from_sequence(new_values, dtype=new_dtype)
             except Exception:
                 # https://github.com/pandas-dev/pandas/issues/22850
                 # pandas has no control over what 3rd-party ExtensionArrays
                 # 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/extension/base/methods.py

@@ -163,13 +163,15 @@ def test_combine_add(self, data_repeated):
             expected = pd.Series(
                 orig_data1._from_sequence([a + b for (a, b) in
                                            zip(list(orig_data1),
-                                               list(orig_data2))]))
+                                               list(orig_data2))],
+                                               dtype=s1.dtype))
         self.assert_series_equal(result, expected)
 
         val = s1.iloc[0]
         result = s1.combine(val, lambda x1, x2: x1 + x2)
         expected = pd.Series(
-            orig_data1._from_sequence([a + val for a in list(orig_data1)]))
+            orig_data1._from_sequence([a + val for a in list(orig_data1)],
+            dtype=s1.dtype))
         self.assert_series_equal(result, expected)
 
     def test_combine_first(self, data):