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.
Customer Reviews
There are no reviews.
