GIS for Data Scientists — The Spatial Concepts That Actually Trip You Up
Data scientists encounter GIS when spatial data shows up in a project: a dataset with latitude/longitude columns, a shapefile from a government portal, a GeoJSON file someone dropped in the repo. The first few operations usually work. Then something breaks silently — a spatial join returns an empty DataFrame, a buffer produces geometry the size of a continent, or exported shapefiles arrive at the lab with every field name truncated. ...