def _flex_comp_method_FRAME(cls, op, special):
str_rep = _get_opstr(op)
op_name = _get_op_name(op, special)
default_axis = _get_frame_op_default_axis(op_name)
def na_op(x, y):
try:
with np.errstate(invalid="ignore"):
result = op(x, y)
except TypeError:
result = mask_cmp_op(x, y, op)
return result
doc = _flex_comp_doc_FRAME.format(op_name=op_name,
desc=_op_descriptions[op_name]["desc"])
@Appender(doc)
def f(self, other, axis=default_axis, level=None):
other = _align_method_FRAME(self, other, axis)
if isinstance(other, ABCDataFrame):
# Another DataFrame
if not self._indexed_same(other):
self, other = self.align(other,
"outer",
level=level,
copy=False)
return dispatch_to_series(self, other, na_op, str_rep)
elif isinstance(other, ABCSeries):
return _combine_series_frame(self,
other,
na_op,
fill_value=None,
axis=axis,
level=level)
else:
# in this case we always have `np.ndim(other) == 0`
return self._combine_const(other, na_op)
f.__name__ = op_name
return f
def flex_comp_method_FRAME(op):
op_name = op.__name__.strip("_")
default_axis = "columns" # because we are "flex"
doc = _flex_comp_doc_FRAME.format(
op_name=op_name, desc=_op_descriptions[op_name]["desc"]
)
@Appender(doc)
def f(self, other, axis=default_axis, level=None):
axis = self._get_axis_number(axis) if axis is not None else 1
self, other = align_method_FRAME(self, other, axis, flex=True, level=level)
new_data = self._dispatch_frame_op(other, op, axis=axis)
return self._construct_result(new_data)
f.__name__ = op_name
return f
def flex_comp_method_FRAME(cls: Type["DataFrame"], op, special: bool):
assert not special # "special" also means "not flex"
op_name = _get_op_name(op, special)
default_axis = "columns" # because we are "flex"
doc = _flex_comp_doc_FRAME.format(
op_name=op_name, desc=_op_descriptions[op_name]["desc"]
)
@Appender(doc)
def f(self, other, axis=default_axis, level=None):
axis = self._get_axis_number(axis) if axis is not None else 1
self, other = align_method_FRAME(self, other, axis, flex=True, level=level)
new_data = dispatch_to_series(self, other, op, axis=axis)
return self._construct_result(new_data)
f.__name__ = op_name
return f
def _flex_comp_method_FRAME(cls, op, special):
str_rep = _get_opstr(op)
op_name = _get_op_name(op, special)
default_axis = _get_frame_op_default_axis(op_name)
doc = _flex_comp_doc_FRAME.format(op_name=op_name,
desc=_op_descriptions[op_name]["desc"])
@Appender(doc)
def f(self, other, axis=default_axis, level=None):
other = _align_method_FRAME(self, other, axis)
if isinstance(other, ABCDataFrame):
# Another DataFrame
if not self._indexed_same(other):
self, other = self.align(other,
"outer",
level=level,
copy=False)
new_data = dispatch_to_series(self, other, op, str_rep)
return self._construct_result(new_data)
elif isinstance(other, ABCSeries):
axis = self._get_axis_number(axis) if axis is not None else 1
self, other = self.align(other,
join="outer",
axis=axis,
level=level,
copy=False)
return _combine_series_frame(self, other, op, axis=axis)
else:
# in this case we always have `np.ndim(other) == 0`
new_data = dispatch_to_series(self, other, op)
return self._construct_result(new_data)
f.__name__ = op_name
return f
