Interactive Notebooks

Learn CAIS through interactive Jupyter notebooks that you can run locally or in cloud environments. These notebooks provide step-by-step tutorials with executable code and detailed explanations.

Notebook Categories

Beginner Notebooks

  • Getting Started with CAIS

  • Your First Causal Analysis

  • Understanding CAIS Output

  • Common Data Preparation Steps

Intermediate Notebooks

  • Comparing Different Methods

  • Assumption Testing and Validation

  • Handling Missing Data

  • Sensitivity Analysis

Advanced Notebooks

  • Custom Method Implementation

  • Large-Scale Batch Processing

  • Integration with ML Pipelines

  • Performance Optimization

Running the Notebooks

Quick Start - Cloud Environments

  • Binder: |binder-badge| Launch all notebooks in an interactive environment

  • Google Colab: Click the “Open in Colab” button in each notebook

  • GitHub Codespaces: Open the repository in a cloud development environment

Local Installation

  1. Install CAIS: pip install causal-agent

  2. Install Jupyter: pip install jupyter notebook

  3. Download notebooks: All Notebooks (ZIP)

  4. Run: jupyter notebook

Individual Downloads

  • Education Analysis Tutorial

  • Healthcare Analysis Tutorial

  • Economics Analysis Tutorial

Requirements

  • Python 3.8+

  • CAIS package

  • Standard data science libraries (pandas, numpy, matplotlib, seaborn, scipy)

  • LLM provider API key (for full functionality)

Notebook Features

  • Interactive Code: Modify and run code cells to experiment

  • Rich Visualizations: Charts, plots, and diagnostic graphics

  • Downloadable Data: Practice datasets included with each notebook

  • Solution Cells: Compare your results with expected outcomes

  • Extension Exercises: Additional challenges to deepen learning