pandas.interval_range — pandas 0.24.0rc1 documentation (original) (raw)
pandas. interval_range(start=None, end=None, periods=None, freq=None, name=None, closed='right')[source]¶
Return a fixed frequency IntervalIndex
| Parameters: | start : numeric or datetime-like, default None Left bound for generating intervals end : numeric or datetime-like, default None Right bound for generating intervals periods : integer, default None Number of periods to generate freq : numeric, string, or DateOffset, default None The length of each interval. Must be consistent with the type of start and end, e.g. 2 for numeric, or ‘5H’ for datetime-like. Default is 1 for numeric and ‘D’ for datetime-like. name : string, default None Name of the resulting IntervalIndex closed : {‘left’, ‘right’, ‘both’, ‘neither’}, default ‘right’ Whether the intervals are closed on the left-side, right-side, both or neither. |
|---|---|
| Returns: | rng : IntervalIndex |
See also
An Index of intervals that are all closed on the same side.
Notes
Of the four parameters start, end, periods, and freq, exactly three must be specified. If freq is omitted, the resultingIntervalIndex will have periods linearly spaced elements betweenstart and end, inclusively.
To learn more about datetime-like frequency strings, please see this link.
Examples
Numeric start and end is supported.
pd.interval_range(start=0, end=5) IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]] closed='right', dtype='interval[int64]')
Additionally, datetime-like input is also supported.
pd.interval_range(start=pd.Timestamp('2017-01-01'), end=pd.Timestamp('2017-01-04')) IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03], (2017-01-03, 2017-01-04]] closed='right', dtype='interval[datetime64[ns]]')
The freq parameter specifies the frequency between the left and right. endpoints of the individual intervals within the IntervalIndex. For numeric start and end, the frequency must also be numeric.
pd.interval_range(start=0, periods=4, freq=1.5) IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]] closed='right', dtype='interval[float64]')
Similarly, for datetime-like start and end, the frequency must be convertible to a DateOffset.
pd.interval_range(start=pd.Timestamp('2017-01-01'), periods=3, freq='MS') IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01], (2017-03-01, 2017-04-01]] closed='right', dtype='interval[datetime64[ns]]')
Specify start, end, and periods; the frequency is generated automatically (linearly spaced).
pd.interval_range(start=0, end=6, periods=4) IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]] closed='right', dtype='interval[float64]')
The closed parameter specifies which endpoints of the individual intervals within the IntervalIndex are closed.
pd.interval_range(end=5, periods=4, closed='both') IntervalIndex([[1, 2], [2, 3], [3, 4], [4, 5]] closed='both', dtype='interval[int64]')