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REF: remove unused variable and checks #59463

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Merged
merged 3 commits into from
Aug 13, 2024
Merged

REF: remove unused variable and checks #59463

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3f602f1
REF: removed unused convert keyword
jbrockmendel Aug 9, 2024
ce11d42
REF: remove unhit field checks
jbrockmendel Aug 9, 2024
1f7305f
REF: inline _object_ops
jbrockmendel Aug 13, 2024
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14 changes: 3 additions & 11 deletions pandas/core/arrays/datetimes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,15 +158,8 @@ def f(self):
# these return a boolean by-definition
return result

if field in self._object_ops:
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Can _object_ops be in-lined in _datetimelike_ops now since this usage is removed?

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I think so. Will update.

result = fields.get_date_name_field(values, field, reso=self._creso)
result = self._maybe_mask_results(result, fill_value=None)

else:
result = fields.get_date_field(values, field, reso=self._creso)
result = self._maybe_mask_results(
result, fill_value=None, convert="float64"
)
result = fields.get_date_field(values, field, reso=self._creso)
result = self._maybe_mask_results(result, fill_value=None, convert="float64")

return result

Expand Down Expand Up @@ -243,7 +236,6 @@ def _scalar_type(self) -> type[Timestamp]:
"is_year_end",
"is_leap_year",
]
_object_ops: list[str] = ["freq", "tz"]
_field_ops: list[str] = [
"year",
"month",
Expand All @@ -264,7 +256,7 @@ def _scalar_type(self) -> type[Timestamp]:
]
_other_ops: list[str] = ["date", "time", "timetz"]
_datetimelike_ops: list[str] = (
_field_ops + _object_ops + _bool_ops + _other_ops + ["unit"]
_field_ops + _bool_ops + _other_ops + ["unit", "freq", "tz"]
)
_datetimelike_methods: list[str] = [
"to_period",
Expand Down
8 changes: 2 additions & 6 deletions pandas/core/arrays/string_.py
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Expand Up @@ -354,9 +354,7 @@ def _str_map(
self, f, na_value=None, dtype: Dtype | None = None, convert: bool = True
):
if self.dtype.na_value is np.nan:
return self._str_map_nan_semantics(
f, na_value=na_value, dtype=dtype, convert=convert
)
return self._str_map_nan_semantics(f, na_value=na_value, dtype=dtype)

from pandas.arrays import BooleanArray

Expand Down Expand Up @@ -431,9 +429,7 @@ def _str_map_str_or_object(
# -> We don't know the result type. E.g. `.get` can return anything.
return lib.map_infer_mask(arr, f, mask.view("uint8"))

def _str_map_nan_semantics(
self, f, na_value=None, dtype: Dtype | None = None, convert: bool = True
):
def _str_map_nan_semantics(self, f, na_value=None, dtype: Dtype | None = None):
if dtype is None:
dtype = self.dtype
if na_value is None:
Expand Down
3 changes: 1 addition & 2 deletions pandas/core/arrays/timedeltas.py
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Expand Up @@ -152,9 +152,8 @@ def _scalar_type(self) -> type[Timedelta]:
# define my properties & methods for delegation
_other_ops: list[str] = []
_bool_ops: list[str] = []
_object_ops: list[str] = ["freq"]
_field_ops: list[str] = ["days", "seconds", "microseconds", "nanoseconds"]
_datetimelike_ops: list[str] = _field_ops + _object_ops + _bool_ops + ["unit"]
_datetimelike_ops: list[str] = _field_ops + _bool_ops + ["unit", "freq"]
_datetimelike_methods: list[str] = [
"to_pytimedelta",
"total_seconds",
Expand Down
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