School/.venv/lib/python3.9/site-packages/pandas/_libs/tslibs/parsing.pyi
Kristofers Solo 1e065cc4b2 Updated .venv
2021-11-22 17:11:45 +02:00

62 lines
1.8 KiB
Python

from datetime import datetime
import numpy as np
from pandas._libs.tslibs.offsets import BaseOffset
class DateParseError(ValueError): ...
def parse_datetime_string(
date_string: str,
dayfirst: bool = ...,
yearfirst: bool = ...,
**kwargs,
) -> datetime: ...
def parse_time_string(
arg: str,
freq: BaseOffset | str | None = ...,
dayfirst: bool | None = ...,
yearfirst: bool | None = ...,
) -> tuple[datetime, str]: ...
def _does_string_look_like_datetime(py_string: str) -> bool: ...
def quarter_to_myear(year: int, quarter: int, freq: str) -> tuple[int, int]: ...
def try_parse_dates(
values: np.ndarray, # object[:]
parser=...,
dayfirst: bool = ...,
default: datetime | None = ...,
) -> np.ndarray: ... # np.ndarray[object]
def try_parse_date_and_time(
dates: np.ndarray, # object[:]
times: np.ndarray, # object[:]
date_parser=...,
time_parser=...,
dayfirst: bool = ...,
default: datetime | None = ...,
) -> np.ndarray: ... # np.ndarray[object]
def try_parse_year_month_day(
years: np.ndarray, # object[:]
months: np.ndarray, # object[:]
days: np.ndarray, # object[:]
) -> np.ndarray: ... # np.ndarray[object]
def try_parse_datetime_components(
years: np.ndarray, # object[:]
months: np.ndarray, # object[:]
days: np.ndarray, # object[:]
hours: np.ndarray, # object[:]
minutes: np.ndarray, # object[:]
seconds: np.ndarray, # object[:]
) -> np.ndarray: ... # np.ndarray[object]
def format_is_iso(f: str) -> bool: ...
def guess_datetime_format(
dt_str,
dayfirst: bool = ...,
dt_str_parse=...,
dt_str_split=...,
) -> str | None: ...
def concat_date_cols(
date_cols: tuple,
keep_trivial_numbers: bool = ...,
) -> np.ndarray: ... # np.ndarray[object]
def get_rule_month(source: str) -> str: ...