What?

lvr tells you which causes provoke which effects:

>>> from lvr import Lvr
>>> values = [789, 621, 109, 65, 45, 30, 27, 15, 12, 9]
>>> Lvr(values).summary(guess=True)
{'causes': 0.2, 'effects': 0.8, 'entropy_ratio': 0.71, 'pareto': True}

Why?

Few values of high intensity distort the result of the arithmetic mean for most values of low intensity and vice versa.

Guided by the arithmetic mean one regularly misunderstands it as something like the most likely value where it would be better called the most unlikely value.

How?

A cause-effect relationship is easier to communicate yet preciser. As it unveils the true power behind things, it transforms resistance into pleasure for action. If you want to achieve more with less, this might be something for you.

lvr operationalises the entropy() model proposed by Ronen et al. [2007].

[2007]

Grosfeld-Nir, A.; Ronen, B.; Kozlovsky, N. The Pareto managerial principle: when does it apply?, International Journal of Production Research, Vol. 45, No. 10, 15 May 2007, 2317—2325