What am I looking at? Imagine every school district in Texas walked into one giant gymnasium and sat down next to the districts most like them. Big city districts sat together. Small country districts sat together. Fast-growing suburbs found each other.
That's this picture. Each dot is one district. Dots that sit near each other are alike — same size, same growth, same kind of funding. The bigger the dot, the more students. The darker the blue, the more it spends per student.
So what? When two dots sit right next to each other but one is pale and one is dark, two very similar districts are spending very differently. That's a question worth asking.
Try this: type your district's name in the box above and press Enter — we'll find its seat and show you who's sitting next to it. On a phone: tap a dot to open it, drag to move around, pinch to zoom in.
Horizontal axis: … · vertical axis: …
(principal components of the exogenous feature space; together ≈ of structural variance).
Built by scripts/graph_insights.py; edges from the k-NN similarity graph
(scripts/build_similarity_graph.py). Source: TEA Summarized PEIMS Actual Financial Data.
Independent transparency tool, not an official TEA product. API · dashboard.