Messy maps to make sense of a complex world
summary
Builds dot‑density maps of Sydney to show income by self‑reported ancestry, using one dot per person to reveal clustering across suburbs and coastal corridors. Compares QGIS styling (easy but requires separate layers per class) with the Python library englewood (single non‑colliding layer, per‑dot colors). Notes practical limits: too many classes makes colors indistinguishable, sparse regions get evenly sprinkled dots, and interactivity stalled when vector tiles ballooned to 30 million points, so the final delivery uses raster tiles.
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chapters (6)
- 0:00Introduction
- 4:54Quick start question
- 8:03Dot density maps
- 11:49Opensource software
- 13:49Density maps
- 16:04Barriers to obtaining data
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