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
- What's the message? One map = one message. If two variables compete, consider small multiples or a bivariate scheme — not twelve legend classes.
- Normalized? Choropleths of raw counts are population maps in disguise. Rates, densities, or per-capita for area-based color; raw magnitudes → proportional symbols instead.
- 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.
- Quantiles: guaranteed color balance; can split near-identical values.
- Equal interval: comparable and intuitive; fails on skew.
- Manual/defined: the ONLY correct choice for map series (same breaks across all dates/regions) and for domain thresholds (WHO limits, slope classes).
- 5±2 classes; show the histogram with breaks in the workflow; state the scheme in the caption/metadata. Try two schemes — if the story changes materially, the story is the classification, and the reader must be told.
Color
- Ramps from ColorBrewer/
cmcrameri/viridis family: sequential (ordered), diverging (meaningful midpoint — zero, mean, threshold), qualitative (categories, ≤ 8). - Colorblind-safe by default (~8% of male readers); never red-green diverging without checking a CVD simulator.
- NoData ≠ zero: render as neutral gray with its own legend entry, never the ramp's low end.
- Muted basemaps (CartoDB Positron) under thematic layers — the basemap must never win.
Projection for display
- Web tiles = Web Mercator: fine for city scale; area comparisons at continental scale on Mercator are visual lies — use equal-area projections (Albers, Mollweide, Equal Earth) for static thematic maps of large extents.
- National mapping → the national grid; polar work → polar stereographic.
- Label the projection on publication maps.
Required furniture (publication static maps)
Title (the message, not the filename), legend (units!, sensible number formatting), scale bar (projected CRS only — degrees have no fixed scale), north arrow (only when north isn't up or the audience expects it), data source + date + projection + author, and an inset locator map for unfamiliar regions.
# GeoPandas static map core
ax = gdf.plot(column="rate_per_1k", scheme="naturalbreaks", k=5,
cmap="YlGnBu", legend=True, edgecolor="white", linewidth=0.3,
missing_kwds={"color": "#d9d9d9", "label": "No data"})
ax.set_axis_off()
Export: 300 dpi PNG/PDF for print; SVG when editors will touch it; COG + style for GIS handoff.
Interactive maps
- Folium/MapLibre: tooltips with formatted values, layer control, sensible
initial bounds (
fit_bounds), legend included (Folium needs a manual HTML/branca legend — don't ship without one). - Performance: >~50k vector features → tile it (tippecanoe → PMTiles) or switch to deck.gl/Kepler; never dump 500k GeoJSON features into Leaflet.
- Every popup number formatted (thousands separators, units, rounding matched to precision honesty).
Verification protocol
- Squint test: does the message survive at thumbnail size?
- CVD simulation pass.
- Legend audit: units, rounding, class edges non-overlapping.
- Cross-check 3 features' rendered values against the attribute table (classification bugs are silent).
- For map series: identical breaks, ramp, and extent across panels.
Pitfalls checklist
- Raw-count choropleth (population in disguise).
- Jenks breaks compared across two dates.
- Red-green diverging ramp, unlabeled midpoint.
- NoData painted as the lowest class.
- Scale bar on an unprojected (degree) map.
- Continental-area comparisons on Web Mercator.
- Interactive map with no legend or units.
Execution contract
- Workflow: inspect audience, data semantics, scale, and output medium; select projection, normalization, classification, and visual hierarchy; render; verify; export.
- Decision rules: choose map type from the analytical question, normalize counts when exposure differs, and keep breaks fixed for comparisons.
- Verification protocol: run the five checks above and reconcile rendered values, units, class edges, and missing-data treatment against the source.
- Failure modes: stop or qualify delivery when denominators, CRS, units, accessibility, or cross-panel comparability are unresolved.
- Deliverables: final map, legend and units, data/source note, projection and classification rationale, accessibility note, and reproducible style or code.
- Source freshness: consult the authoritative source registry before using version-sensitive APIs and record the checked date.