def na_op(x, y):
# TODO:
# should have guarantees on what x, y can be type-wise
# Extension Dtypes are not called here
if is_object_dtype(x.dtype):
result = comp_method_OBJECT_ARRAY(op, x, y)
else:
method = getattr(x, op_name)
with np.errstate(all="ignore"):
result = method(y)
if result is NotImplemented:
return invalid_comparison(x, y, op)
return result
def wrapper(self, other):
res_name = get_op_result_name(self, other)
# TODO: shouldn't we be applying finalize whenever
# not isinstance(other, ABCSeries)?
finalizer = (lambda x: x.__finalize__(self)
if isinstance(other, (np.ndarray, ABCIndexClass)) else x)
if isinstance(other, ABCDataFrame): # pragma: no cover
# Defer to DataFrame implementation; fail early
return NotImplemented
if isinstance(other, ABCSeries) and not self._indexed_same(other):
raise ValueError(
"Can only compare identically-labeled Series objects")
other = lib.item_from_zerodim(other)
if isinstance(other, list):
# TODO: same for tuples?
other = np.asarray(other)
if isinstance(other, (np.ndarray, ABCExtensionArray, ABCIndexClass)):
# TODO: make this treatment consistent across ops and classes.
# We are not catching all listlikes here (e.g. frozenset, tuple)
# The ambiguous case is object-dtype. See GH#27803
if len(self) != len(other):
raise ValueError("Lengths must match to compare")
lvalues = extract_array(self, extract_numpy=True)
rvalues = extract_array(other, extract_numpy=True)
if should_extension_dispatch(lvalues, rvalues):
res_values = dispatch_to_extension_op(op, lvalues, rvalues)
elif is_scalar(rvalues) and isna(rvalues):
# numpy does not like comparisons vs None
if op is operator.ne:
res_values = np.ones(len(lvalues), dtype=bool)
else:
res_values = np.zeros(len(lvalues), dtype=bool)
elif is_object_dtype(lvalues.dtype):
res_values = comp_method_OBJECT_ARRAY(op, lvalues, rvalues)
else:
op_name = "__{op}__".format(op=op.__name__)
method = getattr(lvalues, op_name)
with np.errstate(all="ignore"):
res_values = method(rvalues)
if res_values is NotImplemented:
res_values = invalid_comparison(lvalues, rvalues, op)
if is_scalar(res_values):
raise TypeError(
"Could not compare {typ} type with Series".format(
typ=type(rvalues)))
result = self._constructor(res_values, index=self.index)
result = finalizer(result)
# Set the result's name after finalizer is called because finalizer
# would set it back to self.name
result.name = res_name
return result
