polars qcut for dataframe
Bin continuous values into discrete categories based on their quantiles for a series.
Signature
> polars qcut {flags} (quantiles)
Flags
--labels, -l {list<string>}: Names of the categories. The number of labels must be equal to the number of cut points plus one.--left_closed, -c: Set the intervals to be left-closed instead of right-closed.--include_breaks, -b: Include a column with the right endpoint of the bin each observation falls in. This will change the data type of the output from a Categorical to a Struct.--allow_duplicates, -d: If set, duplicates in the resulting quantiles are dropped, rather than raising an error. This can happen even with unique probabilities, depending on the data.
Parameters
quantiles: Either a list of quantile probabilities between 0 and 1 or a positive integer determining the number of bins with uniform probability.
Input/output types:
| input | output |
|---|---|
| polars_dataframe | polars_dataframe |
| polars_lazyframe | polars_lazyframe |
Examples
Divide a column into three categories according to pre-defined quantile probabilities.
> [-2, -1, 0, 1, 2] | polars into-df | polars qcut [0.25, 0.75] --labels ["a", "b", "c"]