IntervalArray.is_empty
Indicates if an interval is empty, meaning it contains no points.
New in version 0.25.0.
Returns: |
|
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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