def arithmetic_op(
left: Union[np.ndarray, ABCExtensionArray],
right: Any,
op,
str_rep: str,
eval_kwargs: Mapping[str, bool],
):
"""
Evaluate an arithmetic operation `+`, `-`, `*`, `/`, `//`, `%`, `**`, ...
Parameters
----------
left : np.ndarray or ExtensionArray
right : object
Cannot be a DataFrame or Index. Series is *not* excluded.
op : {operator.add, operator.sub, ...}
Or one of the reversed variants from roperator.
str_rep : str
Returns
-------
ndarrray or ExtensionArray
Or a 2-tuple of these in the case of divmod or rdivmod.
"""
from pandas.core.ops import maybe_upcast_for_op
keep_null_freq = isinstance(
right,
(
ABCDatetimeIndex,
ABCDatetimeArray,
ABCTimedeltaIndex,
ABCTimedeltaArray,
Timestamp,
),
)
# NB: We assume that extract_array has already been called on `left`, but
# cannot make the same assumption about `right`. This is because we need
# to define `keep_null_freq` before calling extract_array on it.
lvalues = left
rvalues = extract_array(right, extract_numpy=True)
rvalues = maybe_upcast_for_op(rvalues, lvalues.shape)
if should_extension_dispatch(left, rvalues) or isinstance(
rvalues, (ABCTimedeltaArray, ABCDatetimeArray, Timestamp)):
# TimedeltaArray, DatetimeArray, and Timestamp are included here
# because they have `freq` attribute which is handled correctly
# by dispatch_to_extension_op.
res_values = dispatch_to_extension_op(op, lvalues, rvalues,
keep_null_freq)
else:
with np.errstate(all="ignore"):
res_values = na_arithmetic_op(lvalues, rvalues, op, str_rep,
eval_kwargs)
return res_values
def arithmetic_op(left: Union[np.ndarray, ABCExtensionArray], right: Any, op,
str_rep: str):
"""
Evaluate an arithmetic operation `+`, `-`, `*`, `/`, `//`, `%`, `**`, ...
Parameters
----------
left : np.ndarray or ExtensionArray
right : object
Cannot be a DataFrame or Index. Series is *not* excluded.
op : {operator.add, operator.sub, ...}
Or one of the reversed variants from roperator.
str_rep : str
Returns
-------
ndarrray or ExtensionArray
Or a 2-tuple of these in the case of divmod or rdivmod.
"""
from pandas.core.ops import maybe_upcast_for_op
# NB: We assume that extract_array has already been called
# on `left` and `right`.
lvalues = left
rvalues = right
rvalues = maybe_upcast_for_op(rvalues, lvalues.shape)
if should_extension_dispatch(left, rvalues) or isinstance(
rvalues,
(ABCTimedeltaArray, ABCDatetimeArray, Timestamp, Timedelta)):
# TimedeltaArray, DatetimeArray, and Timestamp are included here
# because they have `freq` attribute which is handled correctly
# by dispatch_to_extension_op.
# Timedelta is included because numexpr will fail on it, see GH#31457
res_values = dispatch_to_extension_op(op, lvalues, rvalues)
else:
with np.errstate(all="ignore"):
res_values = na_arithmetic_op(lvalues, rvalues, op, str_rep)
return res_values