Inzynierka/Lib/site-packages/pandas/_libs/tslibs/vectorized.pyi

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2023-06-02 12:51:02 +02:00
"""
For cython types that cannot be represented precisely, closest-available
python equivalents are used, and the precise types kept as adjacent comments.
"""
from datetime import tzinfo
import numpy as np
from pandas._libs.tslibs.dtypes import Resolution
from pandas._typing import npt
def dt64arr_to_periodarr(
stamps: npt.NDArray[np.int64],
freq: int,
tz: tzinfo | None,
reso: int = ..., # NPY_DATETIMEUNIT
) -> npt.NDArray[np.int64]: ...
def is_date_array_normalized(
stamps: npt.NDArray[np.int64],
tz: tzinfo | None,
reso: int, # NPY_DATETIMEUNIT
) -> bool: ...
def normalize_i8_timestamps(
stamps: npt.NDArray[np.int64],
tz: tzinfo | None,
reso: int, # NPY_DATETIMEUNIT
) -> npt.NDArray[np.int64]: ...
def get_resolution(
stamps: npt.NDArray[np.int64],
tz: tzinfo | None = ...,
reso: int = ..., # NPY_DATETIMEUNIT
) -> Resolution: ...
def ints_to_pydatetime(
arr: npt.NDArray[np.int64],
tz: tzinfo | None = ...,
box: str = ...,
reso: int = ..., # NPY_DATETIMEUNIT
) -> npt.NDArray[np.object_]: ...
def tz_convert_from_utc(
stamps: npt.NDArray[np.int64],
tz: tzinfo | None,
reso: int = ..., # NPY_DATETIMEUNIT
) -> npt.NDArray[np.int64]: ...