polars.Series.entropy#

Series.entropy(base: float = 2.718281828459045, normalize: bool = False) float | None[source]#

Computes the entropy.

Uses the formula -sum(pk * log(pk) where pk are discrete probabilities.

Parameters:
base

Given base, defaults to e

normalize

Normalize pk if it doesn’t sum to 1.

Examples

>>> a = pl.Series([0.99, 0.005, 0.005])
>>> a.entropy(normalize=True)
0.06293300616044681
>>> b = pl.Series([0.65, 0.10, 0.25])
>>> b.entropy(normalize=True)
0.8568409950394724