# matheusfacure/python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Repository: https://github.com/matheusfacure/python-causality-handbook
Canonical: https://ross.abutalabs.com/products/python-causality-handbook
Homepage: https://matheusfacure.github.io/python-causality-handbook/landing-page.html
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: causal-inference, python, causality, data-science, econometrics, impact-estimation, harmless-econometrics
Last push: 2026-07-08T23:15:31+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 8, longevity 100
- inputs: {"age_days": 2331, "days_push": 56, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3443, forks 615 (observed 2026-08-28T04:08:05.145524+00:00)

## What it is
An open online textbook, 'Causal Inference for the Brave and True', teaching causal inference and impact estimation in Python with Jupyter notebooks. It covers potential outcomes, causal graphs, and CATE models in a rigorous yet light-hearted style.

## Use cases
- learn causal inference in python
- understand impact estimation methods
- study econometrics with jupyter notebooks
- learn about causal graphs and potential outcomes
- estimate heterogeneous treatment effects with CATE models
- self-study causal inference for data science

## When to choose
- you want a free, rigorous introduction to causal inference with Python code
- you prefer learning through runnable Jupyter notebooks
- you need both foundational theory and industry applications like CATE estimation

## When to avoid
- you need production-ready causal inference software rather than educational material
- you want a formal textbook without informal tone and memes
- you need a language other than Python

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, machine-learning
- domain: data-science, education, tutorials
- platform: python, cross-platform
- tags: causal-inference, econometrics, jupyter-notebook, impact-estimation, open-textbook, sensitivity-analysis, statistics

## Member repositories
- matheusfacure/python-causality-handbook (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:05.145524+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:37:37.953077+00:00, confidence not recorded.
  - readme: https://github.com/matheusfacure/python-causality-handbook (fetched 2026-08-28T04:08:05.145524+00:00, sha 23cb22e7c545)
  - homepage: https://matheusfacure.github.io/python-causality-handbook/landing-page.html (fetched 2026-08-29T09:31:32.686649+00:00, sha 8b67bc3f0a9d)
- Data as of 2026-08-30T08:39:29.467469+00:00.