pandas.interval_range¶
-
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’ (calendar daily) for datetime-like.
name : string, default None
Name of the resulting IntervalIndex
closed : string, default ‘right’
options are: ‘left’, ‘right’, ‘both’, ‘neither’
Returns: rng : IntervalIndex
See also
IntervalIndex
- an Index of intervals that are all closed on the same side.
Notes
Of the three parameters:
start
,end
, andperiods
, exactly two must be specified.Examples
Numeric
start
andend
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 theIntervalIndex
. For numericstart
andend
, 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
andend
, 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]]')
The
closed
parameter specifies which endpoints of the individual intervals within theIntervalIndex
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]')