Geospatial Analysis with Python & Jupyter Notebooks

This tutorial provides detailed walk-throughs of how to use Jupyter Notebooks and open-source Python libraries to perform geospatial analysis.

Learning Goals

  • Understand the fundamentals of GIS Programming and its implementations in a geographic context
  • Perform different spatial operations using open-source Python libraries
  • Setting up a Python GIS Environment
  • Using UofT’s UTOR JupyterHub

This tutorial and its contents are hosted on the Map and Data Library’s GitHub account. You can download it here: https://github.com/MDLutoronto/SpatialAnalysisJupyter/tree/main

Technique: Spatial Analysis | Tools: Python

First created: May 29, 2025
Last updated: October 20, 2026

Tutorial maintained by Cole White.

Tutorial created by Cole White, Ryan Siu.

The content of these tutorials, guides, and any other Map & Data Library pages on our Learn@MDL site, shall not be ingested into or used for training of any large language models (or other artificial intelligence/machine learning models) without contacting the Map & Data Library for consent first.

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