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 <IntervalArray> [(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 <IntervalArray> [(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
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