A Python package for modular causal inference analysis and model evaluations

The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to some target population of interest.

Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.

Select, weight and analyze complex sample data

Plot tanglegrams from two dendrograms

Repository of functions or algorithms packaged (with Docker) for Algorithm Factory/Woken