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Pandas ExtensionArray for timedelta data.
.. versionadded:: 0.24.0
.. warning::
TimedeltaArray is currently experimental, and its API may change
without warning. In particular, :attr:`TimedeltaArray.dtype` is
expected to change to be an instance of an ``ExtensionDtype``
subclass.
Parameters
----------
values : array-like
The timedelta data.
dtype : numpy.dtype
Currently, only ``numpy.dtype("timedelta64[ns]")`` is accepted.
freq : Offset, optional
copy : bool, default False
Whether to copy the underlying array of data.
Attributes
----------
None
Methods
-------
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The dtype for the TimedeltaArray.
.. warning::
A future version of pandas will change dtype to be an instance
of a :class:`pandas.api.extensions.ExtensionDtype` subclass,
not a ``numpy.dtype``.
Returns
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z TimedeltaArray.__rfloordiv__�__mod__c C s* t |ttjtf�rt|�}| | | | S )N)rR r rW r� r r )r. r r2 r2 r3 r� � s zTimedeltaArray.__mod__�__rmod__c C s* t |ttjtf�rt|�}||| | S )N)rR r rW r� r r )r. r r2 r2 r3 r� � s zTimedeltaArray.__rmod__�
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Return total duration of each element expressed in seconds.
This method is available directly on TimedeltaArray, TimedeltaIndex
and on Series containing timedelta values under the ``.dt`` namespace.
Returns
-------
seconds : [ndarray, Float64Index, Series]
When the calling object is a TimedeltaArray, the return type
is ndarray. When the calling object is a TimedeltaIndex,
the return type is a Float64Index. When the calling object
is a Series, the return type is Series of type `float64` whose
index is the same as the original.
See Also
--------
datetime.timedelta.total_seconds : Standard library version
of this method.
TimedeltaIndex.components : Return a DataFrame with components of
each Timedelta.
Examples
--------
**Series**
>>> s = pd.Series(pd.to_timedelta(np.arange(5), unit='d'))
>>> s
0 0 days
1 1 days
2 2 days
3 3 days
4 4 days
dtype: timedelta64[ns]
>>> s.dt.total_seconds()
0 0.0
1 86400.0
2 172800.0
3 259200.0
4 345600.0
dtype: float64
**TimedeltaIndex**
>>> idx = pd.to_timedelta(np.arange(5), unit='d')
>>> idx
TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
dtype='timedelta64[ns]', freq=None)
>>> idx.total_seconds()
Float64Index([0.0, 86400.0, 172800.0, 259200.00000000003, 345600.0],
dtype='float64')
g��&� .>N)r) )r- r+ )r. r2 r2 r3 rB � s 7z TimedeltaArray.total_seconds)�returnc C s t j| j�S )z�
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objects.
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-------
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)r Zints_to_pytimedeltar+ )r. r2 r2 r3 rA ! s z TimedeltaArray.to_pytimedeltaz Number of days for each element.z>Number of seconds (>= 0 and less than 1 day) for each element.zFNumber of microseconds (>= 0 and less than 1 second) for each element.zJNumber of nanoseconds (>= 0 and less than 1 microsecond) for each element.c sj ddl m} ddddddd g� | j}|r6� fd
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Return a dataframe of the components (days, hours, minutes,
seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas.
Returns
-------
a DataFrame
r )� DataFramer= �hours�minutesr> Z millisecondsr? r@ c s t | �rtjgt� � S | jS )N)r rW r� r� �
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Parameters
----------
data : list-like
copy : bool, default False
unit : str, optional
The timedelta unit to treat integers as multiples of. For numeric
data this defaults to ``'ns'``.
Must be un-specified if the data contains a str and ``errors=="raise"``.
errors : {"raise", "coerce", "ignore"}, default "raise"
How to handle elements that cannot be converted to timedelta64[ns].
See ``pandas.to_timedelta`` for details.
Returns
-------
converted : numpy.ndarray
The sequence converted to a numpy array with dtype ``timedelta64[ns]``.
inferred_freq : Tick or None
The inferred frequency of the sequence.
Raises
------
ValueError : Data cannot be converted to timedelta64[ns].
Notes
-----
Unlike `pandas.to_timedelta`, if setting ``errors=ignore`` will not cause
errors to be ignored; they are caught and subsequently ignored at a
higher level.
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Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
the integers as multiples of the given timedelta unit.
Parameters
----------
data : numpy.ndarray with integer-dtype
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
Returns
-------
numpy.ndarray : timedelta64[ns] array converted from data
bool : whether a copy was made
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Convert a object-dtyped or string-dtyped array into an
timedelta64[ns]-dtyped array.
Parameters
----------
data : ndarray or Index
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
Must not be specified if the data contains a str.
errors : {"raise", "coerce", "ignore"}, default "raise"
How to handle elements that cannot be converted to timedelta64[ns].
See ``pandas.to_timedelta`` for details.
Returns
-------
numpy.ndarray : timedelta64[ns] array converted from data
Raises
------
ValueError : Data cannot be converted to timedelta64[ns].
Notes
-----
Unlike `pandas.to_timedelta`, if setting `errors=ignore` will not cause
errors to be ignored; they are caught and subsequently ignored at a
higher level.
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