Energy Infrastructure Mapping with Python and GeoPandas

Energy infrastructure forms the backbone of global economics and geopolitics, yet analyzing these complex networks requires specialized technical skills. Understanding how to visualize and model pipelines, power grids, and international corridors is essential for modern energy analysts and planners. This text-based course guides you through the fundamentals of geospatial analysis tailored specifically for the energy sector. You will transition from writing basic Python scripts to developing sophisticated maps of global energy networks, giving you the tools to extract strategic insights from spatial data. What you'll learn: - Understand the foundational concepts of geospatial data, coordinate reference systems, and spatial data structures. - Map global gas pipelines and electricity interconnectors using GeoPandas and Python. - Model international energy corridors and cross-border networks with advanced visualization libraries like Folium. - Apply modern Python packaging tools and virtual environments to build reproducible geospatial workflows. - Optimize data performance using modern storage formats like GeoParquet for large-scale infrastructure datasets. - Analyze the intersection of technical physical networks and regional geopolitical contexts. The course starts with essential terminology and environment setup before progressing through step-by-step written guides and code walkthroughs for mapping pipelines, grids, and complex nodes. You will practice through structured written exercises designed to reinforce your spatial analysis skills. This course is designed for beginners, energy analysts, policy advisors, and researchers who want to apply Python to energy geography. No advanced programming or GIS background is required. Start building your energy mapping toolkit today.