pandas.Interval

class pandas.Interval

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

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, or if it contains another interval:

>>> 2.5 in iv
True
>>> pd.Interval(left=2, right=5, closed='both') 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')

Attributes

left	Left bound for the interval.
right	Right bound for the interval.
closed	String describing the inclusive side the intervals.

Attributes

closed	String describing the inclusive side the intervals.
closed_left	Check if the interval is closed on the left side.
closed_right	Check if the interval is closed on the right side.
is_empty	Indicates if an interval is empty, meaning it contains no points.
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.

Methods

overlaps(other)

Check whether two Interval objects overlap.