pandas.IntervalIndex#

classpandas.IntervalIndex(data,closed=None,dtype=None,copy=False,name=None,verify_integrity=True)[source]#

Immutable index of intervals that are closed on the same side.

Parameters:

dataarray-like (1-dimensional)

Array-like (ndarray,DateTimeArray,TimeDeltaArray) containingInterval objects from which to build the IntervalIndex.

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

Whether the intervals are closed on the left-side, right-side, both orneither.

dtypedtype or None, default None

If None, dtype will be inferred.

copybool, default False

Copy the input data.

nameobject, optional

Name to be stored in the index.

verify_integritybool, default True

Verify that the IntervalIndex is valid.

Attributes

closed	String describing the inclusive side the intervals.
is_empty	Indicates if an interval is empty, meaning it contains no points.
is_non_overlapping_monotonic	Return a boolean whether the IntervalArray is non-overlapping and monotonic.
is_overlapping	Return True if the IntervalIndex has overlapping intervals, else False.
values	Return an array representing the data in the Index.

left
right
mid
length

Methods

from_arrays(left, right[, closed, name, ...])	Construct from two arrays defining the left and right bounds.
from_tuples(data[, closed, name, copy, dtype])	Construct an IntervalIndex from an array-like of tuples.
from_breaks(breaks[, closed, name, copy, dtype])	Construct an IntervalIndex from an array of splits.
contains(*args, **kwargs)	Check elementwise if the Intervals contain the value.
overlaps(*args, **kwargs)	Check elementwise if an Interval overlaps the values in the IntervalArray.
set_closed(*args, **kwargs)	Return an identical IntervalArray closed on the specified side.
to_tuples(*args, **kwargs)	Return an ndarray (if self is IntervalArray) or Index (if self is IntervalIndex) of tuples of the form (left, right).

See also

Index

The base pandas Index type.

Interval

A bounded slice-like interval; the elements of an IntervalIndex.

interval_range

Function to create a fixed frequency IntervalIndex.

cut

Bin values into discrete Intervals.

qcut

Bin values into equal-sized Intervals based on rank or sample quantiles.

Notes

See theuser guidefor more.

Examples

A newIntervalIndex is typically constructed usinginterval_range():

>>>pd.interval_range(start=0,end=5)IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],              dtype='interval[int64, right]')

It may also be constructed using one of the constructormethods:IntervalIndex.from_arrays(),IntervalIndex.from_breaks(), andIntervalIndex.from_tuples().

See further examples in the doc strings ofinterval_range and thementioned constructor methods.