Skip to main content

effectus tells you which minority of causes provokes which majority of effects.

Project description

Pypi version Python versions Windows Built Status Code coverage

What?

You provide it with a series of numbers. It tells you whether a pareto distribution is present.

Why?

Mean, Median and Most likely value regularly hide that a minority of causes provokes a majority of effects.

The Fallacy of the Arithmetic Mean explains the situation in-depth.

How?

First, install it:

$ pip3 install effectus

Then, in your Python shell do:

from effectus import Effects
Effects([789, 621, 109, 65, 45, 30, 27, 15, 12, 9])
<pareto present [0.707]: 1/5 causes => 4/5 effects [total : 2.3 %]>

If you want 80% of results, you need only 20% of causes.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for effectus, version 1.0.0.dev4
Filename, size File type Python version Upload date Hashes
Filename, size effectus-1.0.0.dev4.macosx-10.11-x86_64.tar.gz (220.8 kB) File type Source Python version None Upload date Hashes View hashes
Filename, size effectus-1.0.0.dev4-py2.py3-none-any.whl (212.7 kB) File type Wheel Python version py2.py3 Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page