pandas.Interval

class pandas.Interval

Immutable object implementing an Interval, a bounded slice-like interval.

New in version 0.20.0.

Parameters:

left : orderable scalar

Left bound for the interval.

right : orderable scalar

Right bound for the interval.

closed : {‘left’, ‘right’, ‘both’, ‘neither’}, default ‘right’

Whether the interval is closed on the left-side, right-side, both or neither.

closed : {‘right’, ‘left’, ‘both’, ‘neither’}, default ‘right’

Whether the interval is closed on the left-side, right-side, both or neither. See the Notes for more detailed explanation.

See also

IntervalIndex
An Index of Interval objects that are all closed on the same side.
cut
Convert continuous data into discrete bins (Categorical of Interval objects).
qcut
Convert continuous data into bins (Categorical of Interval objects) based on quantiles.
Period
Represents a period of time.

Notes

The parameters left and right must be from the same type, you must be able to compare them and they must satisfy left <= right.

A closed interval (in mathematics denoted by square brackets) contains its endpoints, i.e. the closed interval [0, 5] is characterized by the conditions 0 <= x <= 5. This is what closed='both' stands for. An open interval (in mathematics denoted by parentheses) does not contain its endpoints, i.e. the open interval (0, 5) is characterized by the conditions 0 < x < 5. This is what closed='neither' stands for. Intervals can also be half-open or half-closed, i.e. [0, 5) is described by 0 <= x < 5 (closed='left') and (0, 5] is described by 0 < x <= 5 (closed='right').

Examples

It is possible to build Intervals of different types, like numeric ones:

>>> iv = pd.Interval(left=0, right=5)
>>> iv
Interval(0, 5, closed='right')

You can check if an element belongs to it

>>> 2.5 in iv
True

You can test the bounds (closed='right', so 0 < x <= 5):

>>> 0 in iv
False
>>> 5 in iv
True
>>> 0.0001 in iv
True

Calculate its length

>>> iv.length
5

You can operate with + and * over an Interval and the operation is applied to each of its bounds, so the result depends on the type of the bound elements

>>> shifted_iv = iv + 3
>>> shifted_iv
Interval(3, 8, closed='right')
>>> extended_iv = iv * 10.0
>>> extended_iv
Interval(0.0, 50.0, closed='right')

To create a time interval you can use Timestamps as the bounds

>>> year_2017 = pd.Interval(pd.Timestamp('2017-01-01 00:00:00'),
...                         pd.Timestamp('2018-01-01 00:00:00'),
...                         closed='left')
>>> pd.Timestamp('2017-01-01 00:00') in year_2017
True
>>> year_2017.length
Timedelta('365 days 00:00:00')

And also you can create string intervals

>>> volume_1 = pd.Interval('Ant', 'Dog', closed='both')
>>> 'Bee' in volume_1
True

Attributes

closed Whether the interval is closed on the left-side, right-side, both or neither
closed_left Check if the interval is closed on the left side.
closed_right Check if the interval is closed on the right side.
left Left bound for the interval
length Return the length of the Interval
mid Return the midpoint of the Interval
open_left Check if the interval is open on the left side.
open_right Check if the interval is open on the right side.
right Right bound for the interval

© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.Interval.html