Fix dtype coercion

doc/source/whatsnew/v0.22.0.txt

@@ -169,7 +169,7 @@ Conversion
 ^^^^^^^^^^
 
 - Bug in :class:`Index` constructor with `dtype='uint64'` where int-like floats were not coerced to :class:`UInt64Index` (:issue:`18400`)
--
+- Bug in :class:`Block` where math operations on a `DataFrame` containing `bool` as elements are coerced to `bool` in :meth:`coerce_to_target_dtype`.
 -
 
 Indexing

pandas/core/internals.py

@@ -1026,7 +1026,7 @@ def f(m, v, i):
 
  return [self.make_block(new_values, fastpath=True)]
 
- def coerce_to_target_dtype(self, other):
+ def coerce_to_target_dtype(self, other, force_coericion=False):
  """
  coerce the current block to a dtype compat for other
  we will return a block, possibly object, and not raise
@@ -1042,8 +1042,10 @@ def coerce_to_target_dtype(self, other):
  return self
 
  if self.is_bool or is_object_dtype(dtype) or is_bool_dtype(dtype):
- # we don't upcast to bool
- return self.astype(object)
+ if force_coericion and is_float_dtype(dtype) or is_integer_dtype(dtype):
+ return self.astype(dtype)
+ else:
+ return self.astype(object)
 
  elif ((self.is_float or self.is_complex) and
  (is_integer_dtype(dtype) or is_float_dtype(dtype))):
@@ -1324,7 +1326,7 @@ def eval(self, func, other, errors='raise', try_cast=False, mgr=None):
  values, values_mask, other, other_mask = self._try_coerce_args(
  transf(values), other)
  except TypeError:
- block = self.coerce_to_target_dtype(orig_other)
+ block = self.coerce_to_target_dtype(orig_other, True)
  return block.eval(func, orig_other,
  errors=errors,
  try_cast=try_cast, mgr=mgr)

pandas/tests/frame/test_dtypes.py

@@ -669,6 +669,19 @@ def test_arg_for_errors_in_astype(self):
 
  df.astype(np.int8, errors='ignore')
 
+ from operator import (add, mul, floordiv, sub)
+
+ @pytest.mark.parametrize("num", [1.0, 1])
+ @pytest.mark.parametrize("struct", [pd.Series, pd.DataFrame])
+ @pytest.mark.parametrize('op', [add, mul, floordiv, sub])
+ def test_assert_list_and_bool_coerce(self, num, struct, op):
+ # issue 18549
+ target_type = np.array([op(num, num)]).dtype
+ res = op(struct([True]), num).dtypes
+ if isinstance(res, pd.Series):
+ res = res[0]
+ assert target_type == res
+
 
 class TestDataFrameDatetimeWithTZ(TestData):