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pandas.TimedeltaIndex — pandas 2.3.1 documentation

class pandas.TimedeltaIndex(data=None, unit=<no_default>, freq=<no_default>, closed=<no_default>, dtype=None, copy=False, name=None)[source]#

Immutable Index of timedelta64 data.

Represented internally as int64, and scalars returned Timedelta objects.

Parameters:

dataarray-like (1-dimensional), optional

Optional timedelta-like data to construct index with.

unit{‘D’, ‘h’, ‘m’, ‘s’, ‘ms’, ‘us’, ‘ns’}, optional

The unit of data.

Deprecated since version 2.2.0: Use pd.to_timedelta instead.

freqstr or pandas offset object, optional

One of pandas date offset strings or corresponding objects. The string 'infer' can be passed in order to set the frequency of the index as the inferred frequency upon creation.

dtypenumpy.dtype or str, default None

Valid numpy dtypes are timedelta64[ns], timedelta64[us], timedelta64[ms], and timedelta64[s].

copybool

Make a copy of input array.

nameobject

Name to be stored in the index.

Attributes

days

Number of days for each element.

seconds

Number of seconds (>= 0 and less than 1 day) for each element.

microseconds

Number of microseconds (>= 0 and less than 1 second) for each element.

nanoseconds

Number of nanoseconds (>= 0 and less than 1 microsecond) for each element.

components

Return a DataFrame of the individual resolution components of the Timedeltas.

inferred_freq

Tries to return a string representing a frequency generated by infer_freq.

Methods

to_pytimedelta(*args, **kwargs)

Return an ndarray of datetime.timedelta objects.

to_series([index, name])

Create a Series with both index and values equal to the index keys.

round(*args, **kwargs)

Perform round operation on the data to the specified freq.

floor(*args, **kwargs)

Perform floor operation on the data to the specified freq.

ceil(*args, **kwargs)

Perform ceil operation on the data to the specified freq.

to_frame([index, name])

Create a DataFrame with a column containing the Index.

mean(*[, skipna, axis])

Return the mean value of the Array.

Notes

To learn more about the frequency strings, please see this link.

Examples

>>> pd.TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'])
TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
               dtype='timedelta64[ns]', freq=None)

We can also let pandas infer the frequency when possible.

>>> pd.TimedeltaIndex(np.arange(5) * 24 * 3600 * 1e9, freq='infer')
TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],
               dtype='timedelta64[ns]', freq='D')

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