Python Use Cases

Practical examples for querying, analyzing, and visualizing GJD data with Python

Welcome

This section contains reproducible Python examples that demonstrate how to work with the Green Jurisdiction Database (GJD). Each use case is a Jupyter notebook (.ipynb) that you can run locally in JupyterLab, VS Code, Google Colab, or any notebook environment.

What you’ll find here

  • Get Started — Everything you need to set up your Python environment.
  • API Authentication — How to register and configure your API key.
  • Use Cases — Step-by-step notebooks covering real-world scenarios with GJD data.

How it works

Every example is written as a standard Jupyter notebook. The code actually executes when the site is built via Quarto, so the outputs (tables, plots, statistics) are always up to date.

You can:

  1. Browse online — Read the rendered HTML pages right here.
  2. Clone and run — Clone the repo, open any .ipynb file in Jupyter or VS Code, and run it.
  3. Open in Colab — Upload the notebook to Google Colab for a zero-install experience.
  4. Adapt — Use the examples as templates for your own analysis.

Head over to Get Started to set up your environment.

Use Cases

# Use Case Description
01 Forest Cover in Caquetá Query forest cover data for Caquetá, Colombia (2010–2019), visualize with bar charts, and compare with Putumayo.
02 Deforestation in Acre Query deforestation data for Acre, Brazil (2010–2019) using PRODES, and compare across data sources.