cartography-geoviz

# Cartography & Geovisualization Purpose: maps that communicate honestly. Cartographic choices (class breaks, ramps, normalization, projection) can manufacture or hide patterns; this skill treats them as analytical decisions with stated rationale, not styling. ## The first three questions 1. **What's the message?** One map = one message. If two variables compete, consider small multiples or a bivariate scheme — not twelve legend classes. 2. **Normalized?** Choropleths of raw counts are population maps in disguise. Rates, densities, or per-capita for area-based color; raw magnitudes → proportional symbols instead. 3. **Static or interactive?** Print/PDF/paper → matplotlib/QGIS layout; exploration/stakeholders → Folium/MapLibre; big point data → Kepler.gl/deck.gl (GPU). ## Thematic map type selection | Data | Map type | |---|---| | Rate/ratio by polygon | Choropleth | | Count/magnitude by place | Proportional/graduated symbols | | Two related rates | Bivariate choropleth (3×3 max) | | Individual-level density | Dot density or KDE surface (label bandwidth) | | Continuous field (raster) | Classified or stretched render + hillshade context | | Movement/OD | Flow map (width∝volume), aggregate to avoid hairballs | | Change over time | Small multiples > animation for analysis; animation for outreach | ## Classification — the honesty lever - **Natural breaks (Jenks)**: default for skewed data; breaks are data-specific, so NOT comparable across maps/dates. - ...