63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
import numpy as np
|
|
|
|
from pandas._typing import npt
|
|
|
|
def build_field_sarray(
|
|
dtindex: npt.NDArray[np.int64], # const int64_t[:]
|
|
reso: int, # NPY_DATETIMEUNIT
|
|
) -> np.ndarray: ...
|
|
def month_position_check(fields, weekdays) -> str | None: ...
|
|
def get_date_name_field(
|
|
dtindex: npt.NDArray[np.int64], # const int64_t[:]
|
|
field: str,
|
|
locale: str | None = ...,
|
|
reso: int = ..., # NPY_DATETIMEUNIT
|
|
) -> npt.NDArray[np.object_]: ...
|
|
def get_start_end_field(
|
|
dtindex: npt.NDArray[np.int64],
|
|
field: str,
|
|
freqstr: str | None = ...,
|
|
month_kw: int = ...,
|
|
reso: int = ..., # NPY_DATETIMEUNIT
|
|
) -> npt.NDArray[np.bool_]: ...
|
|
def get_date_field(
|
|
dtindex: npt.NDArray[np.int64], # const int64_t[:]
|
|
field: str,
|
|
reso: int = ..., # NPY_DATETIMEUNIT
|
|
) -> npt.NDArray[np.int32]: ...
|
|
def get_timedelta_field(
|
|
tdindex: npt.NDArray[np.int64], # const int64_t[:]
|
|
field: str,
|
|
reso: int = ..., # NPY_DATETIMEUNIT
|
|
) -> npt.NDArray[np.int32]: ...
|
|
def get_timedelta_days(
|
|
tdindex: npt.NDArray[np.int64], # const int64_t[:]
|
|
reso: int = ..., # NPY_DATETIMEUNIT
|
|
) -> npt.NDArray[np.int64]: ...
|
|
def isleapyear_arr(
|
|
years: np.ndarray,
|
|
) -> npt.NDArray[np.bool_]: ...
|
|
def build_isocalendar_sarray(
|
|
dtindex: npt.NDArray[np.int64], # const int64_t[:]
|
|
reso: int, # NPY_DATETIMEUNIT
|
|
) -> np.ndarray: ...
|
|
def _get_locale_names(name_type: str, locale: str | None = ...): ...
|
|
|
|
class RoundTo:
|
|
@property
|
|
def MINUS_INFTY(self) -> int: ...
|
|
@property
|
|
def PLUS_INFTY(self) -> int: ...
|
|
@property
|
|
def NEAREST_HALF_EVEN(self) -> int: ...
|
|
@property
|
|
def NEAREST_HALF_PLUS_INFTY(self) -> int: ...
|
|
@property
|
|
def NEAREST_HALF_MINUS_INFTY(self) -> int: ...
|
|
|
|
def round_nsint64(
|
|
values: npt.NDArray[np.int64],
|
|
mode: RoundTo,
|
|
nanos: int,
|
|
) -> npt.NDArray[np.int64]: ...
|