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pandas.arrays.IntervalArray.is_empty

IntervalArray.is_empty

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

New in version 0.25.0.

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.

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])

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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.arrays.IntervalArray.is_empty.html