def na_op(x, y):
try:
result = op(x, y)
except TypeError:
if isinstance(y, list):
y = lib.list_to_object_array(y)
if isinstance(y, (np.ndarray, pd.Series)):
if (is_bool_dtype(x.dtype) and is_bool_dtype(y.dtype)):
result = op(x, y) # when would this be hit?
else:
x = com._ensure_object(x)
y = com._ensure_object(y)
result = lib.vec_binop(x, y, op)
else:
try:
# let null fall thru
if not isnull(y):
y = bool(y)
result = lib.scalar_binop(x, y, op)
except:
raise TypeError("cannot compare a dtyped [{0}] array with "
"a scalar of type [{1}]".format(
x.dtype, type(y).__name__))
return result
def na_op(x, y):
try:
result = op(x, y)
except TypeError:
if isinstance(y, list):
y = lib.list_to_object_array(y)
if isinstance(y, (np.ndarray, pd.Series)):
if (x.dtype == np.bool_
and y.dtype == np.bool_): # pragma: no cover
result = op(x, y) # when would this be hit?
else:
x = com._ensure_object(x)
y = com._ensure_object(y)
result = lib.vec_binop(x, y, op)
else:
try:
# let null fall thru
if not isnull(y):
y = bool(y)
result = lib.scalar_binop(x, y, op)
except:
raise TypeError("cannot compare a dtyped [{0}] array with "
"a scalar of type [{1}]".format(
x.dtype,
type(y).__name__))
return result
