Concepts

Understand the core concepts behind spatial data in Python before diving into tasks and workflows.

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Every practical GIS workflow rests on a small set of foundational ideas. What is a GeoDataFrame? What does a CRS actually do? How do raster and vector data differ, and when should you use each? These guides answer those questions directly — without padding, without assumed expertise.

If you're just starting with Python GIS, work through these pages first. They'll give you the vocabulary and mental models that make all the how-to guides easier to follow. If you're already working in the field, these pages make useful references when a concept needs refreshing.

The collection now runs the length of the learning paths. Alongside the starting points — GeoPandas, Shapely, CRS, EPSG codes, Rasterio, vector versus raster — you will find the concepts that decide whether a workflow survives production: what makes a geometry valid, why slivers and gaps appear, how doubles store coordinates, what GDAL actually is, how a spatial index makes a join fast, what the GIL does and does not block, what a pipeline is made of, and how the QGIS Processing framework and its data providers fit together.

Browse by topic

The fastest way in. Each topic page pairs these concepts with the tasks that use them and the errors they cause.

Fundamentals What the objects, files and libraries actually are.
Geometry & space The shapes themselves, where they sit on the earth, and how they relate.
Imagery & point clouds Data that arrives as measurements of a surface rather than as features on it.
Analysis Getting from a raw download to something you can put in front of someone.
Modelling & prediction Predicting values where nobody measured them, and deciding where things should go — with the limits of each model attached.
Production Work that runs without you watching it.
Delivery & sharing Handing the work to someone else: an API, an app, a link that keeps working.
Governance & trust What a dataset is allowed to say, who it is allowed to say it about, and how anyone proves where it came from.
Tools The other software in a Python GIS stack, driven from Python.

See every topic, including the concepts and fixes →

Or follow a learning path Curated routes in the order that builds on itself — concepts first, then each task, then the errors it produces.

Every concept, A–Z

Page 1 — use the page links below, or browse by topic above.

Ready to apply these concepts?

Once you are comfortable with the concepts, the how-to guides walk through specific tasks step by step — from reading a shapefile to running a spatial join.

Follow a Learning Path 📚 Browse How-To Guides ⚙️ Fix an Issue 🔧