About
What it is
webGeoDS brings spatial data analysis, interactive examples, and free tools together in one place — Python and R side by side, running entirely in your browser. Nothing to install, nothing uploaded anywhere.
Who it’s for
For anyone whose work touches spatial data: checking whether a dataset is actually correct, not just correctly shaped. Comparing how Python and R handle the same problem, instead of trusting one implementation blindly. Understanding a method well enough to know when it applies, not just how to call it.
You don’t need to be an expert programmer — the emphasis is on spatial reasoning you can actually verify, not just read about.
Why it’s different
Most spatial data resources pick a side: Python or R. webGeoDS treats them as complementary — the same problem, shown in both, using the tools each ecosystem actually uses (GeoPandas, Shapely, sf). Seeing where they agree, and where they don’t, teaches more than either one alone.
Your data stays yours. Where a tool runs in the browser, your file is processed locally — never uploaded, not even to us. That’s not a setting to enable; it’s how the tools are built.
What you can do here
Three things, connected:
Read — articles that explain a spatial problem properly, with interactive examples built in, not just diagrams.
Use — free standalone tools for the same checks, when you just need an answer, not the full explanation.
Learn more — the articles and tools are pieces of a larger, ongoing effort to teach spatial data science end to end. Where that leads next depends partly on what turns out to be useful — the newsletter below is the way to follow it.
Who’s behind it
Domenico Guadalupi, engineer and data scientist, working with geographic data from start to finish: managing and quality-checking spatial datasets, analysing them, and modelling what they show. My focus is geostatistics, machine learning on spatial data (GeoML), raster and remote-sensing analysis (band math, NDVI, terrain), and infrastructure networks.
webGeoDS is where that work becomes public: free tools anyone can try on their own data, and the code behind every result, in Python and in R, so nothing has to be taken on trust.
Contact: info@webgeods.com · LinkedIn: linkedin.com/in/guadalupi · Code: github.com/webGeoDS