pandas.TimedeltaIndex

class pandas.TimedeltaIndex(data=None, freq=<no_default>, dtype=None, copy=None, name=None)

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.

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, default None

Whether to copy input data, only relevant for array, Series, and Index inputs (for other input, e.g. a list, a new array is created anyway). Defaults to True for array input and False for Index/Series. Set to False to avoid copying array input at your own risk (if you know the input data won’t be modified elsewhere). Set to True to force copying Series/Index input up front.

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	Return the inferred frequency of the index.

Methods

to_pytimedelta()	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(freq[, ambiguous, nonexistent])	Perform round operation on the data to the specified freq.
floor(freq[, ambiguous, nonexistent])	Perform floor operation on the data to the specified freq.
ceil(freq[, ambiguous, nonexistent])	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.

See also

Index

The base pandas Index type.

Timedelta

Represents a duration between two dates or times.

DatetimeIndex

Index of datetime64 data.

PeriodIndex

Index of Period data.

timedelta_range

Create a fixed-frequency TimedeltaIndex.

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[us]', 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')