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Geospatial Visualisation with Python, Web Scraping, and Folium

Event artwork for Geospatial Visualisation with Python, Web Scraping, and Folium

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About this event

What to expect

Discover how to turn web data into compelling interactive maps using Python in this practical online session from PyData Milton Keynes. This talk demonstrates a complete workflow for geospatial storytelling — from scraping data off the web to creating rich, interactive visualizations that reveal real-world patterns and spatial connections.

What You'll Learn

Hugh will guide you through a real-world project showcasing how to:

  • Scrape and collect data from web sources
  • Process and geocode location information
  • Build interactive geographic visualizations using Folium
  • Combine multiple Python libraries into a cohesive data pipeline
  • Transform raw location data into clear, engaging visual insights

The session covers the complete technical workflow — from initial data collection through processing and geocoding, all the way to creating interactive map outputs that help audiences understand distributed networks and location-based datasets.

Who Should Attend

This talk is ideal for data enthusiasts, Python developers, and anyone working with location-based data. Whether you're looking to add geospatial capabilities to your projects, interested in web scraping techniques, or want to improve your data visualization skills, you'll gain practical knowledge you can apply immediately.

No prior experience with mapping libraries is required, though basic Python knowledge will help you follow along with the technical demonstrations.

Format

This is an online event hosted via video conference. The session will include a practical walkthrough of the project workflow, highlighting useful techniques, lessons learned from real implementation, and demonstrating how these tools work together in practice. You'll see how geospatial visualization can make complex distributed data more accessible and understandable.

The talk covers big data handling, data analytics workflows, and open-source tools that enable powerful geospatial analysis without expensive software licenses. You'll leave with concrete examples of how Python's ecosystem supports end-to-end data projects from collection to visualization.

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