This textbook serves as an interactive resource for courses across various disciplines. By leveraging Jupyter Notebooks and MyST Markdown, this collection provides hands-on, code-driven explanations of key concepts in data science, economics, environmental science, and more. Each chapter is designed to be accessible, engaging, and reproducible, ensuring students can experiment with real-world datasets and computational models while learning.
Contributions¶
To contribute to this collection, please submit a pull request to textbook.notebooks. See instructions for contribution here, and the pull request template here.
Use¶
While browsing the available notebooks, this site allows for static viewing of the notebooks. For additional interaction, you can view the toolbar in the top right corner of the screen. The play icon will allow you to launch the notebook in your format of choice, either on a private Jupyter Hub (e.g. jupyter
You can also download a PDF of the notebook by clicking on the page icon or view the source of the site by clicking the GitHub icon.
- Modules Showcase
- JupyterCon Demo
- City Planning
- Economics
- Environmental Science, Policy, and Management
- Engineering
- Ethnic Studies
- Geography
- Meteorology
- Anthropology
- Data Science
- Psychology
- Cognitive Science
- Political Science
- Legal Studies