Map each value to the index of the bin it falls into. Mirrors numpy.digitize.
Indices are 0-based; values below the first edge return -1.
Count how many values fall in each bin. Mirrors numpy.histogram.
Generate evenly-spaced sequences, mirroring numpy.linspace and numpy.arange.
Compute what percentile a given score falls at within a dataset.
Mirrors scipy.stats.percentileofscore.
Transform values to zero mean and unit variance. Mirrors scipy.stats.zscore.
Missing values are propagated; zero-variance data returns all NaN.
Scale all values to the interval [0, 1] (or a custom range).
Mirrors sklearn MinMaxScaler.
Dimensionless measure of dispersion: std / |mean|.
Useful for comparing spread across datasets with different units.