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Explore the capabilities of SpatialDependence.jl for exploratory spatial data analysis in this 10-minute conference talk from JuliaCon 2024. Learn how to create and handle spatial weights matrices from polygon and point geometries, calculate spatial lags, test for spatial autocorrelation, and plot choropleth maps. Discover the package's architecture for managing spatial weight matrices and its integration with GeoInterface.jl for versatile data source compatibility. Gain insights into plotting techniques, including various classification algorithms for observations, and understand how global and local spatial autocorrelation statistics can identify clusters and similarities between geographically close observations. Get a brief, non-technical overview of the package's features and hear about the developer's experience creating it in the Julia programming language.
