pandas.IntervalIndex¶

class pandas.IntervalIndex(data, closed=None, dtype=None, copy: bool = False, name=None, verify_integrity: bool = True)[source]¶

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

New in version 0.20.0.

Parameters

dataarray-like (1-dimensional): Array-like containing Interval 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 or neither.
dtypedtype or None, default None: If None, dtype will be inferred.

New in version 0.23.0.
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.

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 the user guide for more.

Examples

A new IntervalIndex is typically constructed using interval_range():

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

It may also be constructed using one of the constructor methods: IntervalIndex.from_arrays(), IntervalIndex.from_breaks(), and IntervalIndex.from_tuples().

See further examples in the doc strings of interval_range and the mentioned constructor methods.

Attributes

`left`	Return the left endpoints of each Interval in the IntervalArray as an Index.
`right`	Return the right endpoints of each Interval in the IntervalArray as an Index.
`closed`	Whether the intervals are closed on the left-side, right-side, both or neither.
`mid`	Return the midpoint of each Interval in the IntervalArray as an Index.
`length`	Return an Index with entries denoting the length of each Interval in the IntervalArray.
`is_empty`	Indicates if an interval is empty, meaning it contains no points.
`is_non_overlapping_monotonic`	Return True if the IntervalArray is non-overlapping (no Intervals share points) and is either monotonic increasing or monotonic decreasing, else False.
`is_overlapping`	Return True if the IntervalIndex has overlapping intervals, else False.
`values`	Return the IntervalIndex’s data as an IntervalArray.

Methods

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

pandas.CategoricalIndex.equals pandas.IntervalIndex.left