kolmogorov-abacus 0.0.6

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Description:

kolmogorovabacus 0.0.6

ABacus: fast hypothesis testing and experiment design solution
ABacus is a Python library developed for A/B experimentation and testing.
It includes versatile instruments for different experimentation tasks like
prepilot, sample size determination, results calculation, visualisations and reporting.
Important features

Experiment design: type I and II errors, effect size, sample size simulations.
Groups splitting with flexible configuration and stratification.
A/A test and evaluation of splitter accuracy.
Evaluation of experiment results with various statistical tests and approaches.
Sensitivity increasing techniques like stratification, CUPED and CUPAC.
Visualisation of experiment.
Reporting in a human-readable format.

Installation
You can use pip to install ABacus directly from PyPI:
pip install kolmogorov-abacus

or right from GitHub:
pip install pip+https://github.com/kolmogorov-lab/abacus

Note the requirement of Python 3.8+.
Quick example
To define an experiment and analyse it is as easy as to describe your experiment and data:
from abacus.auto_ab.abtest import ABTest
from abacus.auto_ab.params import ABTestParams, DataParams, HypothesisParams

data_params = DataParams(...)
hypothesis_params = HypothesisParams(...)
ab_params = ABTestParams(data_params, hypothesis_params)

data = pd.read_csv('abtest_data.csv')

ab_test = ABTest(data, ab_params)

ab_test.report()

The result of code execution is the following:

Documentation and Examples
Detailed documentation and examples are available for your usage.
Communication
Authors and developers:

Vadim Glukhov
Egor Shishkovets
Dmitry Zabavin

License:

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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