[hexbin-map-geographic] Hexagonal Binning Map

[MarkusNeusinger]

Description

A map with hexagonal binning that aggregates point data into hexagonal cells, showing density or aggregated values per cell.

Applications

• Urban data aggregation
• Spatial statistics visualization
• Taxi pickup/dropoff patterns
• Species observation density

Data

• lat, lon (numeric) - Point coordinates
• value (numeric, optional) - Value to aggregate
• Size: 1000+ points

Notes

• Configurable hexagon size
• Color by count or aggregated value (sum, mean)
• Sequential colormap with legend
• Overlay on base map
• Hover showing cell statistics

[claude]

✅ Spec ID: hexbin-map-geographic

Rationale: This combines hexagonal binning with geographic maps - distinct from hexbin-basic (non-geographic hexbin) and heatmap-geographic (KDE-based continuous density). The hex binning approach for geospatial aggregation is commonly used in urban analytics and spatial statistics.

Add label approved to begin generation.

[github-actions]

✅ Specification Ready: hexbin-map-geographic

PR: #3775

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specification.md

hexbin-map-geographic: Hexagonal Binning Map

Description

A geographic map visualization that aggregates point data into hexagonal cells, displaying density or aggregated values per cell using color intensity. Unlike continuous heatmaps that use kernel density estimation, hexbin maps provide discrete binning that clearly shows data aggregation boundaries. The hexagonal grid is superior to square grids due to isotropy (equal distance to neighboring cells) and better visual continuity, making it ideal for spatial statistics and urban data analysis.

Applications

• Aggregating taxi pickup/dropoff locations to identify transportation demand zones in urban mobility analysis
• Visualizing species observation density across geographic regions for ecological monitoring
• Displaying crime incident patterns with hexagonal aggregation for law enforcement resource allocation
• Mapping sensor readings or IoT device measurements aggregated into geographic zones

Data

• lat (numeric) - Latitude coordinate (-90 to 90)
• lon (numeric) - Longitude coordinate (-180 to 180)
• value (numeric, optional) - Value to aggregate per cell (defaults to count when not provided)
• Size: 1,000-100,000+ points (designed for large datasets where individual points would overlap)
• Example: GPS coordinates of events with optional measurement values, taxi trip endpoints, species sightings

Notes

• Hexagon size should be configurable to balance detail vs. aggregation (larger hexagons for overview, smaller for detailed patterns)
• Support aggregation methods: count (default), sum, and mean of values
• Use a sequential colormap (e.g., viridis, plasma, YlOrRd) with a color legend showing the scale
• Overlay hexagons on a base map showing geographic context (coastlines, country boundaries, or street map)
• Apply transparency to hexagons to allow base map features to show through
• For interactive libraries, enable hover tooltips showing cell statistics (count, sum, mean, coordinates)

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Next: Add approved label to merge this specification to main.

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🤖 spec-create workflow

[github-actions]

🚀 Specification Merged!

Specification: hexbin-map-geographic
PR: #3775 (merged)

The specification is now in main and synced to PostgreSQL.

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Next: Add generate:{library} labels to start generating implementations.

Available libraries: matplotlib, seaborn, plotly, bokeh, altair, plotnine, pygal, highcharts, letsplot

Or use workflow dispatch for bulk operations.

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🤖 spec-create workflow