# Python: 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)] # Library: pandas, version: 1.2.4 # Module: pandas._libs.tslibs.timedeltas, version: unspecified import typing import builtins as _mod_builtins import datetime as _mod_datetime import importlib._bootstrap as _mod_importlib__bootstrap Components = _mod_importlib__bootstrap.Components class Timedelta(_Timedelta): "\n Represents a duration, the difference between two dates or times.\n\n Timedelta is the pandas equivalent of python's ``datetime.timedelta``\n and is interchangeable with it in most cases.\n\n Parameters\n ----------\n value : Timedelta, timedelta, np.timedelta64, str, or int\n unit : str, default 'ns'\n Denote the unit of the input, if input is an integer.\n\n Possible values:\n\n * 'W', 'D', 'T', 'S', 'L', 'U', or 'N'\n * 'days' or 'day'\n * 'hours', 'hour', 'hr', or 'h'\n * 'minutes', 'minute', 'min', or 'm'\n * 'seconds', 'second', or 'sec'\n * 'milliseconds', 'millisecond', 'millis', or 'milli'\n * 'microseconds', 'microsecond', 'micros', or 'micro'\n * 'nanoseconds', 'nanosecond', 'nanos', 'nano', or 'ns'.\n\n **kwargs\n Available kwargs: {days, seconds, microseconds,\n milliseconds, minutes, hours, weeks}.\n Values for construction in compat with datetime.timedelta.\n Numpy ints and floats will be coerced to python ints and floats.\n\n Notes\n -----\n The ``.value`` attribute is always in ns.\n\n If the precision is higher than nanoseconds, the precision of the duration is\n truncated to nanoseconds.\n " def __abs__(self) -> Timedelta: ... def __add__(self, other) -> Timedelta: ... __dict__: typing.Dict[str, typing.Any] def __divmod__(self, other) -> typing.Tuple[Timedelta, Timedelta]: ... def __floordiv__(self, other) -> int: ... def __init__(self, *args, **kwargs) -> None: "\n Represents a duration, the difference between two dates or times.\n\n Timedelta is the pandas equivalent of python's ``datetime.timedelta``\n and is interchangeable with it in most cases.\n\n Parameters\n ----------\n value : Timedelta, timedelta, np.timedelta64, str, or int\n unit : str, default 'ns'\n Denote the unit of the input, if input is an integer.\n\n Possible values:\n\n * 'W', 'D', 'T', 'S', 'L', 'U', or 'N'\n * 'days' or 'day'\n * 'hours', 'hour', 'hr', or 'h'\n * 'minutes', 'minute', 'min', or 'm'\n * 'seconds', 'second', or 'sec'\n * 'milliseconds', 'millisecond', 'millis', or 'milli'\n * 'microseconds', 'microsecond', 'micros', or 'micro'\n * 'nanoseconds', 'nanosecond', 'nanos', 'nano', or 'ns'.\n\n **kwargs\n Available kwargs: {days, seconds, microseconds,\n milliseconds, minutes, hours, weeks}.\n Values for construction in compat with datetime.timedelta.\n Numpy ints and floats will be coerced to python ints and floats.\n\n Notes\n -----\n The ``.value`` attribute is always in ns.\n\n If the precision is higher than nanoseconds, the precision of the duration is\n truncated to nanoseconds.\n " ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... def __inv__(self) -> typing.Any: ... def __mod__(self, other) -> Timedelta: ... def __mul__(self, other) -> Timedelta: ... def __neg__(self) -> Timedelta: ... def __pos__(self) -> Timedelta: ... def __radd__(self, other) -> Timedelta: ... def __rdivmod__(self, other) -> typing.Tuple[Timedelta, Timedelta]: ... def __reduce__(self) -> typing.Union[str, typing.Tuple[typing.Any, ...]]: ... def __rfloordiv__(self, other) -> Timedelta: ... def __rmod__(self, other) -> Timedelta: ... def __rmul__(self, other) -> Timedelta: ... def __rsub__(self, other) -> Timedelta: ... def __rtruediv__(self, other) -> Timedelta: ... def __setstate__(self, state) -> None: ... def __sub__(self, other) -> Timedelta: ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... def __truediv__(self, other) -> float: ... @property def __weakref__(self) -> typing.Any: 'list of weak references to the object (if defined)' ... def _round(self, freq, rounder) -> typing.Any: ... def ceil(self, freq) -> typing.Any: '\n Return a new Timedelta ceiled to this resolution.\n\n Parameters\n ----------\n freq : str\n Frequency string indicating the ceiling resolution.\n ' ... def floor(self, freq) -> typing.Any: '\n Return a new Timedelta floored to this resolution.\n\n Parameters\n ----------\n freq : str\n Frequency string indicating the flooring resolution.\n ' ... max: Timedelta min: Timedelta resolution: Timedelta def round(self, freq) -> typing.Any: '\n Round the Timedelta to the specified resolution.\n\n Parameters\n ----------\n freq : str\n Frequency string indicating the rounding resolution.\n\n Returns\n -------\n a new Timedelta rounded to the given resolution of `freq`\n\n Raises\n ------\n ValueError if the freq cannot be converted\n ' ... def __getattr__(self, name) -> typing.Any: ... class _Timedelta(_mod_datetime.timedelta): __array_priority__: int def __bool__(self) -> bool: 'self != 0' ... def __eq__(self, value) -> bool: 'Return self==value.' ... def __ge__(self, value) -> bool: 'Return self>=value.' ... def __gt__(self, value) -> bool: 'Return self>value.' ... def __hash__(self) -> int: 'Return hash(self).' ... def __init__(self, *args, **kwargs) -> None: ... @classmethod def __init_subclass__(cls) -> None: 'This method is called when a class is subclassed.\n\nThe default implementation does nothing. It may be\noverridden to extend subclasses.\n' ... def __le__(self, value) -> bool: 'Return self<=value.' ... def __lt__(self, value) -> bool: 'Return self bool: 'Return self!=value.' ... __pyx_vtable__: PyCapsule def __reduce_cython__(self) -> typing.Any: ... def __repr__(self) -> str: 'Return repr(self).' ... def __setstate_cython__(self) -> typing.Any: ... def __str__(self) -> str: 'Return str(self).' ... @classmethod def __subclasshook__(cls, subclass: typing.Any) -> bool: 'Abstract classes can override this to customize issubclass().\n\nThis is invoked early on by abc.ABCMeta.__subclasscheck__().\nIt should return True, False or NotImplemented. If it returns\nNotImplemented, the normal algorithm is used. Otherwise, it\noverrides the normal algorithm (and the outcome is cached).\n' ... @property def _d(self) -> typing.Any: ... def _ensure_components(self) -> typing.Any: '\n compute the components\n ' ... @property def _h(self) -> typing.Any: ... def _has_ns(self) -> typing.Any: ... @property def _m(self) -> typing.Any: ... @property def _ms(self) -> typing.Any: ... @property def _ns(self) -> typing.Any: ... def _repr_base(self) -> typing.Any: '\n\n Parameters\n ----------\n format : None|all|sub_day|long\n\n Returns\n -------\n converted : string of a Timedelta\n\n ' ... @property def _s(self) -> typing.Any: ... @property def _us(self) -> typing.Any: ... @property def asm8(self) -> typing.Any: "\n Return a numpy timedelta64 array scalar view.\n\n Provides access to the array scalar view (i.e. a combination of the\n value and the units) associated with the numpy.timedelta64().view(),\n including a 64-bit integer representation of the timedelta in\n nanoseconds (Python int compatible).\n\n Returns\n -------\n numpy timedelta64 array scalar view\n Array scalar view of the timedelta in nanoseconds.\n\n Examples\n --------\n >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')\n >>> td.asm8\n numpy.timedelta64(86520000003042,'ns')\n\n >>> td = pd.Timedelta('2 min 3 s')\n >>> td.asm8\n numpy.timedelta64(123000000000,'ns')\n\n >>> td = pd.Timedelta('3 ms 5 us')\n >>> td.asm8\n numpy.timedelta64(3005000,'ns')\n\n >>> td = pd.Timedelta(42, unit='ns')\n >>> td.asm8\n numpy.timedelta64(42,'ns')\n " ... @property def components(self) -> typing.Any: '\n Return a components namedtuple-like.\n ' ... @property def delta(self) -> typing.Any: "\n Return the timedelta in nanoseconds (ns), for internal compatibility.\n\n Returns\n -------\n int\n Timedelta in nanoseconds.\n\n Examples\n --------\n >>> td = pd.Timedelta('1 days 42 ns')\n >>> td.delta\n 86400000000042\n\n >>> td = pd.Timedelta('3 s')\n >>> td.delta\n 3000000000\n\n >>> td = pd.Timedelta('3 ms 5 us')\n >>> td.delta\n 3005000\n\n >>> td = pd.Timedelta(42, unit='ns')\n >>> td.delta\n 42\n " ... @property def freq(self) -> typing.Any: ... @property def is_populated(self) -> typing.Any: ... def isoformat(self) -> typing.Any: "\n Format Timedelta as ISO 8601 Duration like\n ``P[n]Y[n]M[n]DT[n]H[n]M[n]S``, where the ``[n]`` s are replaced by the\n values. See https://en.wikipedia.org/wiki/ISO_8601#Durations.\n\n Returns\n -------\n str\n\n See Also\n --------\n Timestamp.isoformat : Function is used to convert the given\n Timestamp object into the ISO format.\n\n Notes\n -----\n The longest component is days, whose value may be larger than\n 365.\n Every component is always included, even if its value is 0.\n Pandas uses nanosecond precision, so up to 9 decimal places may\n be included in the seconds component.\n Trailing 0's are removed from the seconds component after the decimal.\n We do not 0 pad components, so it's `...T5H...`, not `...T05H...`\n\n Examples\n --------\n >>> td = pd.Timedelta(days=6, minutes=50, seconds=3,\n ... milliseconds=10, microseconds=10, nanoseconds=12)\n\n >>> td.isoformat()\n 'P6DT0H50M3.010010012S'\n >>> pd.Timedelta(hours=1, seconds=10).isoformat()\n 'P0DT0H0M10S'\n >>> pd.Timedelta(hours=1, seconds=10).isoformat()\n 'P0DT0H0M10S'\n >>> pd.Timedelta(days=500.5).isoformat()\n 'P500DT12H0MS'\n " ... @property def nanoseconds(self) -> typing.Any: "\n Return the number of nanoseconds (n), where 0 <= n < 1 microsecond.\n\n Returns\n -------\n int\n Number of nanoseconds.\n\n See Also\n --------\n Timedelta.components : Return all attributes with assigned values\n (i.e. days, hours, minutes, seconds, milliseconds, microseconds,\n nanoseconds).\n\n Examples\n --------\n **Using string input**\n\n >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')\n\n >>> td.nanoseconds\n 42\n\n **Using integer input**\n\n >>> td = pd.Timedelta(42, unit='ns')\n >>> td.nanoseconds\n 42\n " ... @property def resolution_string(self) -> typing.Any: "\n Return a string representing the lowest timedelta resolution.\n\n Each timedelta has a defined resolution that represents the lowest OR\n most granular level of precision. Each level of resolution is\n represented by a short string as defined below:\n\n Resolution: Return value\n\n * Days: 'D'\n * Hours: 'H'\n * Minutes: 'T'\n * Seconds: 'S'\n * Milliseconds: 'L'\n * Microseconds: 'U'\n * Nanoseconds: 'N'\n\n Returns\n -------\n str\n Timedelta resolution.\n\n Examples\n --------\n >>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')\n >>> td.resolution_string\n 'N'\n\n >>> td = pd.Timedelta('1 days 2 min 3 us')\n >>> td.resolution_string\n 'U'\n\n >>> td = pd.Timedelta('2 min 3 s')\n >>> td.resolution_string\n 'S'\n\n >>> td = pd.Timedelta(36, unit='us')\n >>> td.resolution_string\n 'U'\n " ... def to_numpy(self) -> typing.Any: '\n Convert the Timedelta to a NumPy timedelta64.\n\n .. versionadded:: 0.25.0\n\n This is an alias method for `Timedelta.to_timedelta64()`. The dtype and\n copy parameters are available here only for compatibility. Their values\n will not affect the return value.\n\n Returns\n -------\n numpy.timedelta64\n\n See Also\n --------\n Series.to_numpy : Similar method for Series.\n ' ... def to_pytimedelta(self) -> typing.Any: '\n Convert a pandas Timedelta object into a python timedelta object.\n\n Timedelta objects are internally saved as numpy datetime64[ns] dtype.\n Use to_pytimedelta() to convert to object dtype.\n\n Returns\n -------\n datetime.timedelta or numpy.array of datetime.timedelta\n\n See Also\n --------\n to_timedelta : Convert argument to Timedelta type.\n\n Notes\n -----\n Any nanosecond resolution will be lost.\n ' ... def to_timedelta64(self) -> typing.Any: "\n Return a numpy.timedelta64 object with 'ns' precision.\n " ... @property def value(self) -> typing.Any: ... def view(self) -> typing.Any: '\n Array view compatibility.\n ' ... def __getattr__(self, name) -> typing.Any: ... __doc__: typing.Any __file__: str __name__: str __package__: str __pyx_capi__: dict def __pyx_unpickle_Enum() -> typing.Any: ... def __pyx_unpickle__Timedelta() -> typing.Any: ... __test__: dict def _binary_op_method_timedeltalike() -> typing.Any: ... _no_input: object def _op_unary_method() -> typing.Any: ... def array_to_timedelta64() -> typing.Any: "\n Convert an ndarray to an array of timedeltas. If errors == 'coerce',\n coerce non-convertible objects to NaT. Otherwise, raise.\n " ... def delta_to_nanoseconds() -> typing.Any: ... def ints_to_pytimedelta() -> typing.Any: '\n convert an i8 repr to an ndarray of timedelta or Timedelta (if box ==\n True)\n\n Parameters\n ----------\n arr : ndarray[int64_t]\n box : bool, default False\n\n Returns\n -------\n result : ndarray[object]\n array of Timedelta or timedeltas objects\n ' ... def parse_timedelta_unit() -> typing.Any: '\n Parameters\n ----------\n unit : str or None\n\n Returns\n -------\n str\n Canonical unit string.\n\n Raises\n ------\n ValueError : on non-parseable input\n ' ... def __getattr__(name) -> typing.Any: ...