Why does Pandas display intervals with mixed parentheses and brackets?
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MellowCedar42
When creating an IntervalArray in Pandas with values such as pd.Interval(0, 1) and pd.Interval(1, 5), the output is displayed as [(0, 1], (1, 5]]. Why does each interval use a parenthesis on the left and a square bracket on the right, and what do those symbols mean?
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Pandas commonly uses right-closed intervals so adjacent bins don't overlap. For example, (0, 10] and (10, 20] give each boundary value a single bin. This is especially useful with functions such as pd.cut and pd.qcut, where values are assigned to ranges.
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Intervals let Pandas represent ranges and test membership without expanding every possible value. Instead of storing ranges as strings and manually parsing their endpoints, an IntervalArray can directly determine whether a value belongs to a particular interval.
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This is standard mathematical interval notation. A parenthesis means the endpoint is excluded, while a square bracket means it is included. Therefore, (0, 1] means values greater than 0 and less than or equal to 1.
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MellowCedar42: That makes sense—thanks for explaining it clearly. I hadn't encountered this notation before.