pandas._libs.tslibs.timestamps.py

from typing import *


class Timestamp:

    # usage.dask: 1
    __module__: ClassVar[object]

    # usage.dask: 1
    __name__: ClassVar[object]

    # usage.statsmodels: 4
    day: object

    # usage.dask: 1
    dtype: object

    # usage.dask: 1
    freq: object

    # usage.alphalens: 1
    # usage.pyjanitor: 1
    # usage.statsmodels: 5
    month: object

    # usage.dask: 4
    # usage.xarray: 1
    tz: object

    # usage.dask: 1
    # usage.statsmodels: 2
    # usage.xarray: 1
    value: object

    # usage.alphalens: 1
    # usage.prophet: 1
    # usage.pyjanitor: 1
    # usage.statsmodels: 5
    year: object

    @overload
    def __add__(self, _0: datetime.timedelta, /):
        """
        usage.koalas: 1
        """
        ...

    @overload
    def __add__(self, _0: pandas.core.indexes.timedeltas.TimedeltaIndex, /):
        """
        usage.xarray: 1
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.QuarterBegin, /):
        """
        usage.statsmodels: 3
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.YearEnd, /):
        """
        usage.statsmodels: 2
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.MonthBegin, /):
        """
        usage.statsmodels: 2
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.MonthEnd, /):
        """
        usage.statsmodels: 2
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.timedeltas.Timedelta, /):
        """
        usage.dask: 1
        usage.prophet: 4
        usage.statsmodels: 2
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.BQuarterEnd, /):
        """
        usage.statsmodels: 1
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.BusinessMonthEnd, /):
        """
        usage.statsmodels: 1
        """
        ...

    @overload
    def __add__(self, _0: Union[numpy.ndarray, numpy.timedelta64, numpy.int64], /):
        """
        usage.pandas: 23
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.Day, /):
        """
        usage.dask: 2
        """
        ...

    @overload
    def __add__(self, _0: pandas._libs.tslibs.offsets.Nano, /):
        """
        usage.dask: 1
        """
        ...

    def __add__(self, _0: object, /):
        """
        usage.dask: 4
        usage.koalas: 1
        usage.pandas: 23
        usage.prophet: 4
        usage.statsmodels: 13
        usage.xarray: 1
        """
        ...

    @overload
    def __eq__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.dask: 38
        usage.statsmodels: 4
        """
        ...

    @overload
    def __eq__(self, _0: Literal["1951-03-31T00:00:00"], /):
        """
        usage.statsmodels: 8
        """
        ...

    @overload
    def __eq__(self, _0: Literal["1958-12-31T00:00:00"], /):
        """
        usage.statsmodels: 8
        """
        ...

    @overload
    def __eq__(self, _0: Literal["start"], /):
        """
        usage.statsmodels: 3
        """
        ...

    @overload
    def __eq__(self, _0: Literal["end"], /):
        """
        usage.statsmodels: 3
        """
        ...

    @overload
    def __eq__(
        self, _0: Union[numpy.datetime64, numpy.float64, numpy.ndarray, numpy.int64], /
    ):
        """
        usage.pandas: 8
        """
        ...

    @overload
    def __eq__(self, _0: Literal["2000"], /):
        """
        usage.dask: 1
        """
        ...

    def __eq__(self, _0: object, /):
        """
        usage.dask: 39
        usage.pandas: 8
        usage.statsmodels: 26
        """
        ...

    def __floordiv__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 1
        """
        ...

    @overload
    def __ge__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.dask: 7
        usage.prophet: 2
        usage.statsmodels: 2
        """
        ...

    @overload
    def __ge__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 2
        """
        ...

    @overload
    def __ge__(self, _0: pandas.core.indexes.datetimes.DatetimeIndex, /):
        """
        usage.prophet: 2
        """
        ...

    @overload
    def __ge__(self, _0: pandas.core.series.Series, /):
        """
        usage.prophet: 4
        usage.pyjanitor: 1
        """
        ...

    @overload
    def __ge__(self, _0: numpy.datetime64, /):
        """
        usage.dask: 1
        """
        ...

    def __ge__(
        self,
        _0: Union[
            pandas._libs.tslibs.timestamps.Timestamp,
            numpy.datetime64,
            pandas.core.indexes.datetimes.DatetimeIndex,
            numpy.ndarray,
            pandas.core.series.Series,
        ],
        /,
    ):
        """
        usage.dask: 8
        usage.pandas: 2
        usage.prophet: 8
        usage.pyjanitor: 1
        usage.statsmodels: 2
        """
        ...

    @overload
    def __gt__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.dask: 20
        usage.prophet: 4
        usage.pyjanitor: 1
        usage.statsmodels: 2
        """
        ...

    @overload
    def __gt__(self, _0: pandas.core.indexes.datetimes.DatetimeIndex, /):
        """
        usage.dask: 1
        """
        ...

    def __gt__(
        self,
        _0: Union[
            pandas._libs.tslibs.timestamps.Timestamp,
            pandas.core.indexes.datetimes.DatetimeIndex,
        ],
        /,
    ):
        """
        usage.dask: 21
        usage.prophet: 4
        usage.pyjanitor: 1
        usage.statsmodels: 2
        """
        ...

    def __isub__(self, _0: pandas._libs.tslibs.timedeltas.Timedelta, /):
        """
        usage.prophet: 1
        """
        ...

    @overload
    def __le__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.dask: 7
        usage.prophet: 2
        usage.statsmodels: 2
        """
        ...

    @overload
    def __le__(self, _0: pandas.core.series.Series, /):
        """
        usage.dask: 1
        usage.pyjanitor: 1
        """
        ...

    @overload
    def __le__(self, _0: numpy.datetime64, /):
        """
        usage.dask: 1
        """
        ...

    def __le__(
        self,
        _0: Union[
            pandas.core.series.Series,
            pandas._libs.tslibs.timestamps.Timestamp,
            numpy.datetime64,
        ],
        /,
    ):
        """
        usage.dask: 9
        usage.prophet: 2
        usage.pyjanitor: 1
        usage.statsmodels: 2
        """
        ...

    @overload
    def __lt__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.dask: 20
        usage.prophet: 4
        usage.pyjanitor: 1
        usage.statsmodels: 2
        """
        ...

    @overload
    def __lt__(self, _0: pandas.core.indexes.datetimes.DatetimeIndex, /):
        """
        usage.dask: 1
        usage.prophet: 1
        usage.statsmodels: 1
        """
        ...

    @overload
    def __lt__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 1
        """
        ...

    @overload
    def __lt__(self, _0: pandas.core.series.Series, /):
        """
        usage.prophet: 2
        """
        ...

    def __lt__(
        self,
        _0: Union[
            pandas._libs.tslibs.timestamps.Timestamp,
            pandas.core.indexes.datetimes.DatetimeIndex,
            pandas.core.series.Series,
            numpy.ndarray,
        ],
        /,
    ):
        """
        usage.dask: 21
        usage.pandas: 1
        usage.prophet: 7
        usage.pyjanitor: 1
        usage.statsmodels: 3
        """
        ...

    def __mod__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 1
        """
        ...

    def __mul__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 1
        """
        ...

    @overload
    def __ne__(
        self, _0: Union[numpy.int64, numpy.ndarray, numpy.datetime64, numpy.float64], /
    ):
        """
        usage.pandas: 4
        """
        ...

    @overload
    def __ne__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.dask: 10
        """
        ...

    def __ne__(
        self,
        _0: Union[
            pandas._libs.tslibs.timestamps.Timestamp,
            numpy.float64,
            numpy.datetime64,
            numpy.ndarray,
            numpy.int64,
        ],
        /,
    ):
        """
        usage.dask: 10
        usage.pandas: 4
        """
        ...

    def __pow__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 1
        """
        ...

    @overload
    def __radd__(self, _0: pandas._libs.tslibs.timedeltas.Timedelta, /):
        """
        usage.xarray: 2
        """
        ...

    @overload
    def __radd__(self, _0: pandas.core.indexes.timedeltas.TimedeltaIndex, /):
        """
        usage.xarray: 1
        """
        ...

    @overload
    def __radd__(self, _0: pandas._libs.tslibs.nattype.NaTType, /):
        """
        usage.xarray: 2
        """
        ...

    @overload
    def __radd__(self, _0: Union[numpy.ndarray, numpy.int64, numpy.timedelta64], /):
        """
        usage.pandas: 7
        """
        ...

    def __radd__(self, _0: object, /):
        """
        usage.pandas: 7
        usage.xarray: 5
        """
        ...

    @overload
    def __rsub__(self, _0: databricks.koalas.series.Series, /):
        """
        usage.koalas: 1
        """
        ...

    @overload
    def __rsub__(self, _0: pandas.core.series.Series, /):
        """
        usage.koalas: 1
        usage.prophet: 2
        """
        ...

    @overload
    def __rsub__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.alphalens: 2
        usage.prophet: 4
        """
        ...

    @overload
    def __rsub__(self, _0: pandas.core.indexes.datetimes.DatetimeIndex, /):
        """
        usage.prophet: 1
        usage.xarray: 3
        """
        ...

    @overload
    def __rsub__(self, _0: Union[numpy.ndarray, numpy.int64, numpy.datetime64], /):
        """
        usage.pandas: 8
        """
        ...

    def __rsub__(self, _0: object, /):
        """
        usage.alphalens: 2
        usage.koalas: 2
        usage.pandas: 8
        usage.prophet: 7
        usage.xarray: 3
        """
        ...

    @overload
    def __sub__(self, _0: databricks.koalas.series.Series, /):
        """
        usage.koalas: 1
        """
        ...

    @overload
    def __sub__(self, _0: pandas.core.series.Series, /):
        """
        usage.koalas: 1
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.timestamps.Timestamp, /):
        """
        usage.alphalens: 2
        usage.prophet: 4
        """
        ...

    @overload
    def __sub__(self, _0: Union[numpy.ndarray, numpy.timedelta64, numpy.int64], /):
        """
        usage.pandas: 14
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.timedeltas.Timedelta, /):
        """
        usage.dask: 3
        usage.prophet: 2
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.offsets.Day, /):
        """
        usage.dask: 1
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.offsets.Hour, /):
        """
        usage.dask: 1
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.offsets.BusinessDay, /):
        """
        usage.dask: 1
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.offsets.Week, /):
        """
        usage.dask: 1
        """
        ...

    @overload
    def __sub__(self, _0: pandas._libs.tslibs.offsets.MonthEnd, /):
        """
        usage.dask: 1
        """
        ...

    def __sub__(self, _0: object, /):
        """
        usage.alphalens: 2
        usage.dask: 8
        usage.koalas: 2
        usage.pandas: 14
        usage.prophet: 6
        """
        ...

    def __truediv__(self, _0: numpy.ndarray, /):
        """
        usage.pandas: 1
        """
        ...

    @overload
    def ceil(self, /, freq: Literal["15s"]):
        """
        usage.dask: 1
        """
        ...

    @overload
    def ceil(self, /, freq: Literal["1M"]):
        """
        usage.dask: 1
        """
        ...

    def ceil(self, /, freq: Literal["1M", "15s"]):
        """
        usage.dask: 2
        """
        ...

    def date(self, /):
        """
        usage.alphalens: 1
        usage.modin: 2
        usage.prophet: 2
        """
        ...

    def round(self, /, freq: Literal["15s"]):
        """
        usage.dask: 1
        """
        ...

    @overload
    def strftime(self, _0: Literal["%Y-%m-%d %H:%M:%S.%f"], /):
        """
        usage.statsmodels: 1
        """
        ...

    @overload
    def strftime(self, _0: Literal["%Y-%m-%d"], /):
        """
        usage.statsmodels: 2
        """
        ...

    @overload
    def strftime(self, _0: Literal["%m-%d-%Y"], /):
        """
        usage.statsmodels: 2
        """
        ...

    def strftime(self, _0: Literal["%m-%d-%Y", "%Y-%m-%d", "%Y-%m-%d %H:%M:%S.%f"], /):
        """
        usage.statsmodels: 5
        """
        ...

    def time(self, /):
        """
        usage.modin: 2
        """
        ...

    def to_datetime64(self, /):
        """
        usage.xarray: 1
        """
        ...

    def to_period(self, /, *, freq: pandas._libs.tslibs.offsets.MonthEnd):
        """
        usage.statsmodels: 2
        """
        ...

    def to_pydatetime(self, /):
        """
        usage.statsmodels: 2
        usage.xarray: 1
        """
        ...

    def tz_convert(self, /, tz: None):
        """
        usage.xarray: 1
        """
        ...

    def tz_localize(self, /, tz: None):
        """
        usage.dask: 2
        """
        ...