pandas.TimedeltaIndex

class pandas.TimedeltaIndex(data=None, unit=None, freq=NoDefault.no_default, closed=None, dtype=dtype('<m8[ns]'), copy=False, name=None)

Immutable ndarray of timedelta64 data, represented internally as int64, and which can be boxed to timedelta objects.

Parameters

dataarray-like (1-dimensional), optional

Optional timedelta-like data to construct index with.

unitunit of the arg (D,h,m,s,ms,us,ns) denote the unit, optional

Which is an integer/float number.

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.

copybool

Make a copy of input ndarray.

nameobject

Name to be stored in the index.

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.

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 components (days, hours, minutes, seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas.
inferred_freq	Tries to return a string representing a frequency guess, generated by infer_freq.

Methods

to_pytimedelta(*args, **kwargs)	Return Timedelta Array/Index as object 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(*args, **kwargs)	Return the mean value of the Array.

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