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Mapbox Data Visualization Patterns

by @mapbox

Patterns for visualizing data on maps including choropleth maps, heat maps, 3D visualizations, data-driven styling, and animated data. Covers layer types, co...

Versionv1.0.0
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πŸ“– About This Skill


name: mapbox-data-visualization-patterns description: Patterns for visualizing data on maps including choropleth maps, heat maps, 3D visualizations, data-driven styling, and animated data. Covers layer types, color scales, and performance optimization.

Data Visualization Patterns Skill

Comprehensive patterns for visualizing data on Mapbox maps. Covers choropleth maps, heat maps, 3D extrusions, data-driven styling, animated visualizations, and performance optimization for data-heavy applications.

When to Use This Skill

Use this skill when:

  • Visualizing statistical data on maps (population, sales, demographics)
  • Creating choropleth maps with color-coded regions
  • Building heat maps or clustering for density visualization
  • Adding 3D visualizations (building heights, terrain elevation)
  • Implementing data-driven styling based on properties
  • Animating time-series data
  • Working with large datasets that require optimization
  • Visualization Types

    Choropleth Maps

    Best for: Regional data (states, counties, zip codes), statistical comparisons

    Pattern: Color-code polygons based on data values

    map.on('load', () => {
      // Add data source (GeoJSON with properties)
      map.addSource('states', {
        type: 'geojson',
        data: 'https://example.com/states.geojson' // Features with population property
      });

    // Add fill layer with data-driven color map.addLayer({ id: 'states-layer', type: 'fill', source: 'states', paint: { 'fill-color': [ 'interpolate', ['linear'], ['get', 'population'], 0, '#f0f9ff', // Light blue for low population 500000, '#7fcdff', 1000000, '#0080ff', 5000000, '#0040bf', // Dark blue for high population 10000000, '#001f5c' ], 'fill-opacity': 0.75 } });

    // Add border layer map.addLayer({ id: 'states-border', type: 'line', source: 'states', paint: { 'line-color': '#ffffff', 'line-width': 1 } });

    // Add hover effect with reusable popup const popup = new mapboxgl.Popup({ closeButton: false, closeOnClick: false });

    map.on('mousemove', 'states-layer', (e) => { if (e.features.length > 0) { map.getCanvas().style.cursor = 'pointer';

    const feature = e.features[0]; popup .setLngLat(e.lngLat) .setHTML(

    ${feature.properties.name}

    Population: ${feature.properties.population.toLocaleString()}

    ) .addTo(map); } });

    map.on('mouseleave', 'states-layer', () => { map.getCanvas().style.cursor = ''; popup.remove(); }); });

    > step vs interpolate: The example above uses interpolate for smooth color gradients. For discrete color buckets (e.g., "low / medium / high"), use ['step', ['get', 'population'], '#f0f0f0', 500000, '#fee0d2', 2000000, '#fc9272', 10000000, '#de2d26'] instead. Prefer step when data has natural categories or when exact boundary values matter.

    Color Scale Strategies:

    // Linear interpolation (continuous scale)
    'fill-color': [
      'interpolate',
      ['linear'],
      ['get', 'value'],
      0, '#ffffcc',
      25, '#78c679',
      50, '#31a354',
      100, '#006837'
    ]

    // Step intervals (discrete buckets) 'fill-color': [ 'step', ['get', 'value'], '#ffffcc', // Default color 25, '#c7e9b4', 50, '#7fcdbb', 75, '#41b6c4', 100, '#2c7fb8' ]

    // Case-based (categorical data) 'fill-color': [ 'match', ['get', 'category'], 'residential', '#ffd700', 'commercial', '#ff6b6b', 'industrial', '#4ecdc4', 'park', '#45b7d1', '#cccccc' // Default ]

    Heat Maps

    Best for: Point density, event locations, incident clustering

    Pattern: Visualize density of points

    map.on('load', () => {
      // Add data source (points)
      map.addSource('incidents', {
        type: 'geojson',
        data: {
          type: 'FeatureCollection',
          features: [
            {
              type: 'Feature',
              geometry: {
                type: 'Point',
                coordinates: [-122.4194, 37.7749]
              },
              properties: {
                intensity: 1
              }
            }
            // ... more points
          ]
        }
      });

    // Add heatmap layer map.addLayer({ id: 'incidents-heat', type: 'heatmap', source: 'incidents', maxzoom: 15, paint: { // Increase weight based on intensity property 'heatmap-weight': ['interpolate', ['linear'], ['get', 'intensity'], 0, 0, 6, 1], // Increase intensity as zoom level increases 'heatmap-intensity': ['interpolate', ['linear'], ['zoom'], 0, 1, 15, 3], // Color ramp for heatmap 'heatmap-color': [ 'interpolate', ['linear'], ['heatmap-density'], 0, 'rgba(33,102,172,0)', 0.2, 'rgb(103,169,207)', 0.4, 'rgb(209,229,240)', 0.6, 'rgb(253,219,199)', 0.8, 'rgb(239,138,98)', 1, 'rgb(178,24,43)' ], // Adjust radius by zoom level 'heatmap-radius': ['interpolate', ['linear'], ['zoom'], 0, 2, 15, 20], // Decrease opacity at higher zoom levels 'heatmap-opacity': ['interpolate', ['linear'], ['zoom'], 7, 1, 15, 0] } });

    // Add circle layer for individual points at high zoom map.addLayer({ id: 'incidents-point', type: 'circle', source: 'incidents', minzoom: 14, paint: { 'circle-radius': ['interpolate', ['linear'], ['zoom'], 14, 4, 22, 30], 'circle-color': '#ff4444', 'circle-opacity': 0.8, 'circle-stroke-color': '#fff', 'circle-stroke-width': 1 } }); });

    Best Practices

    Color Accessibility

    // Use ColorBrewer scales for accessibility
    // https://colorbrewer2.org/

    // Good: Sequential (single hue) const sequentialScale = ['#f0f9ff', '#bae4ff', '#7fcdff', '#0080ff', '#001f5c'];

    // Good: Diverging (two hues) const divergingScale = ['#d73027', '#fc8d59', '#fee08b', '#d9ef8b', '#91cf60', '#1a9850'];

    // Good: Qualitative (distinct categories) const qualitativeScale = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00'];

    // Avoid: Red-green for color-blind accessibility // Use: Blue-orange or purple-green instead

    Error Handling

    // Handle missing or invalid data
    map.on('load', () => {
      map.addSource('data', {
        type: 'geojson',
        data: dataUrl
      });

    map.addLayer({ id: 'data-viz', type: 'fill', source: 'data', paint: { 'fill-color': [ 'case', ['has', 'value'], // Check if property exists ['interpolate', ['linear'], ['get', 'value'], 0, '#f0f0f0', 100, '#0080ff'], '#cccccc' // Default color for missing data ] } });

    // Handle map errors map.on('error', (e) => { console.error('Map error:', e.error); }); });

    Data Size Rule

  • < 1 MB: Use GeoJSON directly
  • 1–10 MB: Consider either GeoJSON or vector tiles depending on complexity
  • > 10 MB: Use vector tiles (upload to Mapbox as tileset)
  • See references/performance.md for implementation details.

    Reference Files

    For additional visualization patterns, load the relevant reference file:

  • references/clustering.md β€” Point clustering, custom cluster properties, clustering vs heatmap comparison
  • references/3d-extrusions.md β€” 3D building extrusions, custom data sources, data-driven heights
  • references/circles-lines.md β€” Circle/bubble maps, line data visualization, traffic flow styling
  • references/animation.md β€” Time-series animation, real-time data updates, smooth transitions
  • references/performance.md β€” Vector tiles vs GeoJSON, feature state, filtering, progressive loading
  • references/legends-use-cases.md β€” Legend UI, data inspector, data preprocessing, election/COVID/real-estate examples
  • Resources

  • Mapbox Expression Reference
  • ColorBrewer - Color scales for maps
  • Turf.js - Spatial analysis
  • Simple Statistics - Data classification
  • Data Visualization Tutorials
  • πŸ“‹ Tips & Best Practices

    Color Accessibility

    // Use ColorBrewer scales for accessibility
    // https://colorbrewer2.org/

    // Good: Sequential (single hue) const sequentialScale = ['#f0f9ff', '#bae4ff', '#7fcdff', '#0080ff', '#001f5c'];

    // Good: Diverging (two hues) const divergingScale = ['#d73027', '#fc8d59', '#fee08b', '#d9ef8b', '#91cf60', '#1a9850'];

    // Good: Qualitative (distinct categories) const qualitativeScale = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00'];

    // Avoid: Red-green for color-blind accessibility // Use: Blue-orange or purple-green instead

    Error Handling

    // Handle missing or invalid data
    map.on('load', () => {
      map.addSource('data', {
        type: 'geojson',
        data: dataUrl
      });

    map.addLayer({ id: 'data-viz', type: 'fill', source: 'data', paint: { 'fill-color': [ 'case', ['has', 'value'], // Check if property exists ['interpolate', ['linear'], ['get', 'value'], 0, '#f0f0f0', 100, '#0080ff'], '#cccccc' // Default color for missing data ] } });

    // Handle map errors map.on('error', (e) => { console.error('Map error:', e.error); }); });