pandas.Interval

class pandas.Interval

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

属性

左	区间的左边界。
右	区间的右边界。
closed	描述区间包含的边的字符串。

另请参阅

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

表示一个时间段。

注意

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')。

示例

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')

属性

closed	描述区间包含的边的字符串。
closed_left	检查区间左侧是否包含。
closed_right	检查区间右侧是否包含。
is_empty	指示区间是否为空，意味着它不包含任何点。
左	区间的左边界。
length	返回区间的长度。
中间	返回区间的中间点。
open_left	检查区间左侧是否开放。
open_right	检查区间右侧是否开放。
右	区间的右边界。

Methods

overlaps(other)

检查两个 Interval 对象是否重叠。