pandas.IntervalIndex.is_non_overlapping_monotonic — pandas 2.2.3 documentation (original) (raw)

IntervalIndex.is_non_overlapping_monotonic[source]#

Return a boolean whether the IntervalArray is non-overlapping and monotonic.

Non-overlapping means (no Intervals share points), and monotonic means either monotonic increasing or monotonic decreasing.

Examples

For arrays:

interv_arr = pd.arrays.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)]) interv_arr [(0, 1], (1, 5]] Length: 2, dtype: interval[int64, right] interv_arr.is_non_overlapping_monotonic True

interv_arr = pd.arrays.IntervalArray([pd.Interval(0, 1), ... pd.Interval(-1, 0.1)]) interv_arr [(0.0, 1.0], (-1.0, 0.1]] Length: 2, dtype: interval[float64, right] interv_arr.is_non_overlapping_monotonic False

For Interval Index:

interv_idx = pd.interval_range(start=0, end=2) interv_idx IntervalIndex([(0, 1], (1, 2]], dtype='interval[int64, right]') interv_idx.is_non_overlapping_monotonic True

interv_idx = pd.interval_range(start=0, end=2, closed='both') interv_idx IntervalIndex([[0, 1], [1, 2]], dtype='interval[int64, both]') interv_idx.is_non_overlapping_monotonic False