quantile_biner

[tatasz]

Instructions

Quantile biner creates an extra class either for min or for max.

Code sample

test = pd.DataFrame({
    "id": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
    "value": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
})

transformation.quantile_biner(test, columns_to_bin=['value'], q=2, right=False)[1]

Problem description

This will result in 3 classes, with the min value in a separate class if right=True, and max value in a separate class otherwise.

If fact, it creates an extra class for min or max for all the values of q (both int and list of quantiles).

Expected behavior

Behave like pd.qcut, when setting q=n will create exactly n classes.

Possible solutions

include min and max values in the extreme intervals, regardless the right setting.