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CLN: remove _combine_series_frame #34374

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Merged
merged 1 commit into from
May 26, 2020
Merged

CLN: remove _combine_series_frame #34374

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2 changes: 1 addition & 1 deletion pandas/core/computation/expressions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -223,7 +223,7 @@ def evaluate(op, a, b, use_numexpr: bool = True):
use_numexpr : bool, default True
Whether to try to use numexpr.
"""
op_str = _op_str_mapping.get(op, None)
op_str = _op_str_mapping[op]
if op_str is not None:
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Isnt this always true, so you can drop the if statement now?

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it is not always true, some entries in _op_str_mapping give None

use_numexpr = use_numexpr and _bool_arith_check(op_str, a, b)
if use_numexpr:
Expand Down
42 changes: 7 additions & 35 deletions pandas/core/ops/__init__.py
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Expand Up @@ -280,9 +280,8 @@ def dispatch_to_series(left, right, func, axis=None):
bm = left._mgr.operate_blockwise(right._mgr, array_op)
return type(left)(bm)

elif isinstance(right, ABCSeries) and axis == "columns":
# We only get here if called via _combine_series_frame,
# in which case we specifically want to operate row-by-row
elif isinstance(right, ABCSeries) and axis == 1:
# axis=1 means we want to operate row-by-row
assert right.index.equals(left.columns)

if right.dtype == "timedelta64[ns]":
Expand All @@ -292,6 +291,8 @@ def dispatch_to_series(left, right, func, axis=None):
right = np.asarray(right)
else:
right = right._values
# maybe_align_as_frame ensures we do not have an ndarray here
assert not isinstance(right, np.ndarray)

arrays = [array_op(l, r) for l, r in zip(left._iter_column_arrays(), right)]

Expand Down Expand Up @@ -440,35 +441,6 @@ def flex_wrapper(self, other, level=None, fill_value=None, axis=0):
# DataFrame


def _combine_series_frame(left, right, func, axis: int):
"""
Apply binary operator `func` to self, other using alignment and fill
conventions determined by the axis argument.

Parameters
----------
left : DataFrame
right : Series
func : binary operator
axis : {0, 1}

Returns
-------
result : DataFrame or Dict[int, Series[]]
"""
# We assume that self.align(other, ...) has already been called

rvalues = right._values
assert not isinstance(rvalues, np.ndarray) # handled by align_series_as_frame

if axis == 0:
new_data = dispatch_to_series(left, right, func)
else:
new_data = dispatch_to_series(left, right, func, axis="columns")

return new_data


def _align_method_FRAME(
left, right, axis, flex: Optional[bool] = False, level: Level = None
):
Expand Down Expand Up @@ -671,7 +643,7 @@ def f(self, other, axis=default_axis, level=None, fill_value=None):

elif isinstance(other, ABCSeries):
axis = self._get_axis_number(axis) if axis is not None else 1
new_data = _combine_series_frame(self, other, op, axis=axis)
new_data = dispatch_to_series(self, other, op, axis=axis)
else:
# in this case we always have `np.ndim(other) == 0`
if fill_value is not None:
Expand Down Expand Up @@ -707,7 +679,7 @@ def f(self, other, axis=default_axis, level=None):

elif isinstance(other, ABCSeries):
axis = self._get_axis_number(axis) if axis is not None else 1
new_data = _combine_series_frame(self, other, op, axis=axis)
new_data = dispatch_to_series(self, other, op, axis=axis)
else:
# in this case we always have `np.ndim(other) == 0`
new_data = dispatch_to_series(self, other, op)
Expand All @@ -730,7 +702,7 @@ def f(self, other):
self, other, axis=None, level=None, flex=False
)

axis = "columns" # only relevant for Series other case
axis = 1 # only relevant for Series other case
# See GH#4537 for discussion of scalar op behavior
new_data = dispatch_to_series(self, other, op, axis=axis)
return self._construct_result(new_data)
Expand Down
27 changes: 18 additions & 9 deletions pandas/core/ops/array_ops.py
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Expand Up @@ -85,13 +85,7 @@ def masked_arith_op(x: np.ndarray, y, op):
yrav = y.ravel()
mask = notna(xrav) & ymask.ravel()

if yrav.shape != mask.shape:
# FIXME: GH#5284, GH#5035, GH#19448
# Without specifically raising here we get mismatched
# errors in Py3 (TypeError) vs Py2 (ValueError)
# Note: Only = an issue in DataFrame case
raise ValueError("Cannot broadcast operands together.")

# See GH#5284, GH#5035, GH#19448 for historical reference
if mask.any():
with np.errstate(all="ignore"):
result[mask] = op(xrav[mask], yrav[mask])
Expand Down Expand Up @@ -378,13 +372,28 @@ def get_array_op(op):
# TODO: avoid getting here
return op

op_name = op.__name__.strip("_")
op_name = op.__name__.strip("_").lstrip("r")
if op_name == "arith_op":
# Reached via DataFrame._combine_frame
return op

if op_name in {"eq", "ne", "lt", "le", "gt", "ge"}:
return partial(comparison_op, op=op)
elif op_name in {"and", "or", "xor", "rand", "ror", "rxor"}:
return partial(logical_op, op=op)
else:
elif op_name in {
"add",
"sub",
"mul",
"truediv",
"floordiv",
"mod",
"divmod",
"pow",
}:
return partial(arithmetic_op, op=op)
else:
raise NotImplementedError(op_name)


def maybe_upcast_datetimelike_array(obj: ArrayLike) -> ArrayLike:
Expand Down