pandas.arrays.IntervalArray

class pandas.arrays.IntervalArray

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

New in version 0.24.0.

Parameters:

data : array-like (1-dimensional)

Array-like 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.

dtype : dtype or None, default None

If None, dtype will be inferred.

New in version 0.23.0.

copy : bool, default False

Copy the input data.

verify_integrity : bool, default True

Verify that the IntervalArray is valid.

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]],
              closed='right',
              dtype='interval[int64]')

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

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

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(self, other)	Check elementwise if the Intervals contain the value.
overlaps(self, other)	Check elementwise if an Interval overlaps the values in the IntervalArray.
set_closed(self, closed)	Return an IntervalArray identical to the current one, but closed on the specified side
to_tuples(self[, na_tuple])	Return an ndarray of tuples of the form (left, right)