Points On A Map

Points on a Map

This example renders a world map with city populations using a natural Earth projection. The visualization uses D3’s `geoNaturalEarth1` projection and `geoPath` to draw landmasses, graticules, and country interiors, while scaled circles overlaid onto the map encode each city’s population with a square-root scale. The data comes from the Data Canvas Sense Your City dataset, loaded via `d3.csv`. The React application asynchronously fetches the world atlas and city data, then renders the visualization as an SVG.

TThomas Cormican

Points on a map

This example displays a world map with city points scaled by population using a square-root scale. The map is rendered with D3’s `geoNaturalEarth1` projection and `geoPath`, showing land masses, interiors, graticule, and sphere outlines. City circles are positioned via the projection and styled with opacity, while the component structure uses React with custom hooks to load TopoJSON world data and CSV city data. The visualization clearly communicates population distribution across the globe.

Ccynichole

Points on a Map

This map visualization plots world city populations using circles projected onto a Natural Earth base. It uses D3 v5’s `geoNaturalEarth1` and `geoPath` to render landmasses, graticules, and country interiors, while a sqrt scale maps population values to circle radii. The React-based component loads city data from a CSV and renders SVG marks, using a world atlas TopoJSON for geographic context.

Ttrissentety

Points on a Map

This example visualizes the global distribution of cities, with circle size encoding each city’s population using a square-root scale. A Natural Earth projection renders landmasses, graticules, and country borders via `d3.geoPath` and `geoNaturalEarth1`, while city points are positioned using the same projection. Data comes from a CSV of world cities and TopoJSON world-atlas geometry, all drawn as SVG within a React component.

KKtuzinowski

Points on a Map

This example displays a world map with points representing cities, with circle sizes scaled by population using a square-root scale. It shows a natural Earth projection with graticules and country boundaries overlaid. The visualization uses React to manage state and rendering, while D3 v5 provides `geoNaturalEarth1`, `geoPath`, `geoGraticule`, and `scaleSqrt`. City data comes from a CSV file, and world geography is loaded as TopoJSON. Circles are semi-transparent teal, plotted via projected longitude and latitude coordinates.

Aazharahmad0

Points on a Map

This visualization maps global cities as points on a natural Earth projection, with circle size encoding population. It uses React for rendering SVG elements, D3 v5 for geographical projections and scales, and loads world atlas TopoJSON data plus city CSV data from external URLs. The code employs d3.geoPath, d3.geoNaturalEarth1, and d3.geoGraticule to draw landmasses, graticules, and sphere outlines, while d3.scaleSqrt maps population values to circle radii.

LLawrence Liu

Points on a Map

This example visualizes global population distribution by plotting cities as semi-transparent points on a natural Earth projection map. The map includes graticules, landmasses, and country borders, with each circle’s radius scaled proportionally to its city’s population using `d3.scaleSqrt`. The visualization uses `d3.geoNaturalEarth1`, `d3.geoPath`, and `d3.geoGraticule` for geographic rendering, with React managing state and SVG elements for drawing. The underlying city data comes from the Data Canvas Sense Your City dataset, loaded via `d3.csv`, while world topology is fetched from the World Atlas TopoJSON file and processed with `topojson.feature` and `topojson.mesh`.

AAudrey

Points on a Map

This example displays a world map with city points scaled by population, using a natural Earth projection. The visualization layers graticules, land masses, and country borders beneath translucent teal circles. React components manage the rendering, while D3 utilities handle geographic projections and data loading. The size of each circle is determined by a square root scale mapping population values to a maximum radius of 15 pixels, with city data sourced from a CSV of world cities and geographic features from a TopoJSON world atlas.

LLaura Johnson