pandas.Interval.is_empty#
- Interval.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
orIntervalIndex
, 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 booleanndarray
positionally indicating if anInterval
in anIntervalArray
orIntervalIndex
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
orIntervalIndex
returns a booleanndarray
positionally indicating if anInterval
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])