pandas.arrays.IntervalArray#

class pandas.arrays.IntervalArray(data, closed=None, dtype=None, copy=False, verify_integrity=True)[source]#

Pandas array for interval data that are closed on the same side.

Parameters:

dataarray-like (1-dimensional): Array-like (ndarray, DateTimeArray, TimeDeltaArray) containing Interval objects from which to build the IntervalArray.
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.
copybool, default False: Copy the input data.
verify_integritybool, default True: Verify that the IntervalArray is valid.

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`	String describing the inclusive side the intervals.
`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.
`is_empty`	Indicates if an interval is empty, meaning it contains no points.
`is_non_overlapping_monotonic`	Return a boolean whether the IntervalArray/IntervalIndex is non-overlapping and monotonic.

Methods

`from_arrays`(left, right[, closed, copy, dtype])	Construct from two arrays defining the left and right bounds.
`from_tuples`(data[, closed, copy, dtype])	Construct an IntervalArray from an array-like of tuples.
`from_breaks`(breaks[, closed, copy, dtype])	Construct an IntervalArray from an array of splits.
`contains`(other)	Check elementwise if the Intervals contain the value.
`overlaps`(other)	Check elementwise if an Interval overlaps the values in the IntervalArray.
`set_closed`(closed)	Return an identical IntervalArray closed on the specified side.
`to_tuples`([na_tuple])	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 IntervalArray.
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 IntervalArray can be constructed directly from an array-like of Interval objects:

>>> pd.arrays.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
<IntervalArray>
[(0, 1], (1, 5]]
Length: 2, dtype: interval[int64, right]