Patrons de visualisation de données cartographiques : cartes choroplèthes, cartes de chaleur, visualisations 3D, styles pilotés par les données et données animées.
Ce répertoire fournit un ensemble de patrons de conception pour la visualisation de données géospatiales avec Mapbox GL JS. Il couvre les techniques essentielles telles que les cartes choroplèthes (coloration par plages de valeurs), les cartes de chaleur (heatmaps), les visualisations 3D (extrusions de polygones), le style piloté par les données (data-driven styling) et l'animation de données temporelles. Le contenu détaille les types de couches (fill, line, circle, heatmap, fill-extrusion), les échelles de couleurs (color scales, y compris les palettes séquentielles, divergentes et qualitatives), et les bonnes pratiques d'optimisation des performances (tiling, simplification des géométries, réduction du nombre de couches). Destiné aux développeurs travaillant avec Mapbox GL JS, ce guide permet de créer des visualisations interactives, lisibles et performantes, tout en exploitant les capacités de rendu vectoriel de Mapbox. Les patrons sont agnostiques quant à la plateforme de déploiement (Web, mobile via GL Native) mais se concentrent sur l'API JavaScript. En résumé, c'est une référence pratique pour passer de données brutes à une carte élégante et informante.
npx skills add https://github.com/mapbox/mapbox-agent-skills/tree/main/skills/mapbox-data-visualization-patternsInstalled? Explore more Image skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →
Patrons de visualisation de données cartographiques, incluant les cartes choroplèthes, cartes de chaleur, visualisations 3D, styles pilotés par les données et données animées. Couvre les types de couches, les échelles de couleurs et l'optimisation des performances.
This repo contains 8 individual skills — each has its own dedicated page.
Expert guidance on map design principles, color theory, visual hierarchy, typography, and cartographic best practices for creating effective and beautiful maps with Mapbox. Use when designing map styles, choosing colors, or making cartographic decisions.
Expert guidance on choosing the right geospatial tool based on problem type, accuracy requirements, and performance needs
Complete workflow for implementing Mapbox search in applications - from discovery questions to production-ready integration with best practices
Common style patterns, layer configurations, and recipes for typical mapping scenarios including restaurant finders, real estate, data visualization, navigation, delivery/logistics, and more. Use when implementing specific map use cases or looking for proven style patterns.
Expert guidance on validating, optimizing, and ensuring quality of Mapbox styles through validation, accessibility checks, and optimization. Use when preparing styles for production, debugging issues, or ensuring map quality standards.
Security best practices for Mapbox access tokens, including scope management, URL restrictions, rotation strategies, and protecting sensitive data. Use when creating, managing, or advising on Mapbox token security.
Official integration patterns for Mapbox GL JS across popular web frameworks (React, Vue, Svelte, Angular). Covers setup, lifecycle management, token handling, search integration, and common pitfalls. Based on Mapbox's create-web-app scaffolding tool.
Performance optimization patterns for Mapbox GL JS web applications. Covers initialization waterfalls, bundle size, rendering performance, memory management, and web optimization. Prioritized by impact on user experience.
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Add documentation for a new AI provider — usage docs, env vars, Docker config, image resources.
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.