pandas.IntervalIndex.is_empty

property IntervalIndex.is_empty

Indicates if an interval is empty, meaning it contains no points.

An interval is considered empty if its left and right endpoints are equal, and it is not closed on both sides. This means that the interval does not include any real points. In the case of an pandas.arrays.IntervalArray or IntervalIndex, the property returns a boolean array indicating the emptiness of each interval.

Returns:

bool or ndarray

A boolean indicating if a scalar Interval is empty, or a boolean ndarray positionally indicating if an Interval in an IntervalArray or IntervalIndex is empty.

See also

Interval.length

Return the length of the Interval.

Examples

An Interval that contains points is not empty:

>>> pd.Interval(0, 1, closed='right').is_empty
False

An Interval that does not contain any points is empty:

>>> pd.Interval(0, 0, closed='right').is_empty
True
>>> pd.Interval(0, 0, closed='left').is_empty
True
>>> pd.Interval(0, 0, closed='neither').is_empty
True

An Interval that contains a single point is not empty:

>>> pd.Interval(0, 0, closed='both').is_empty
False

An IntervalArray or IntervalIndex returns a boolean ndarray positionally indicating if an Interval is empty:

>>> ivs = [pd.Interval(0, 0, closed='neither'),
...        pd.Interval(1, 2, closed='neither')]
>>> pd.arrays.IntervalArray(ivs).is_empty
array([ True, False])

Missing values are not considered empty:

>>> ivs = [pd.Interval(0, 0, closed='neither'), np.nan]
>>> pd.IntervalIndex(ivs).is_empty
array([ True, False])