Experiment utils

Generic functions for PySpark experiment analysis and design

• Experiment utils
• Installation
• How to use it
  • Experiment Analyzer
  • Power Analysis

Installation

pip install git+https://github.com/sdaza/experiment-utils.git

How to use it

Experiment Analyzer

The DataFrame df is a PySpark DataFrame. If it's a Pandas DataFrame, it will transform automatically.

analyzer = ExperimentAnalyzer(
    df,
    treatment_col="treatment",
    outcomes=['registrations', 'visits'],
    covariates=covariates,
    experiment_identifier=["campaign_key"],
    adjustment=None)

analyzer.get_effects()
analyzer.results

Power Analysis

from experiment_utils import PowerSim
p = PowerSim(metric='proportion', relative_effect=False,
	variants=1, nsim=1000, alpha=0.05, alternative='two-tailed')

p.get_power(baseline=[0.33], effect=[0.03], sample_size=[3000])