DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Example notebook is based on synthetic data to first quantify sales attribution to different drivers, and then conduct interventions to calculate incremental return on investment
Example notebook is based on synthetic data to first quantify sales attribution to different drivers, and then conduct interventions to calculate incremental return on investment