pandas.IntervalIndex.is_non_overlapping_monotonic#

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
<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
```