Sized Points on a Map

Sized Points on a Map

This example visualizes global cities with populations over 50,000 using sized points on a natural Earth projection. City locations and population data come from a Simplemaps world cities CSV, while country boundaries are rendered from World Atlas TopoJSON. The React app uses `d3.geoNaturalEarth1` and `d3.geoPath` to draw graticules, landmasses, and interiors as SVG paths, then scales circle radii with `d3.scaleSqrt` based on population. Semi-transparent circles encode population density, creating a clear global distribution pattern.

TTexGal

Sized Points on a Map

This visualization displays a world map with cities of populations exceeding 50,000, using sized points to represent population magnitude. Natural Earth projection via `d3.geoNaturalEarth1` and `d3.geoPath` render landmasses, graticules, and country interiors from TopoJSON data. Circles are positioned through projection of latitude and longitude coordinates, with radius determined by a square-root scale (`d3.scaleSqrt`) mapping population values to a maximum radius of 15 pixels. The React-based implementation loads city data from a CSV using `d3.csv` and renders all elements as SVG marks.

JJCarpenter-WPI

Sized Points on a Map

This example displays cities with populations exceeding 50,000 as sized points on a world map, using the natural Earth projection. Country boundaries and graticules appear beneath the points. The visualization uses React with D3 v5, including `geoNaturalEarth1`, `geoPath`, and `geoGraticule`. City population data is loaded from a CSV via `d3.csv`, while land and interior boundaries come from World Atlas TopoJSON, processed with `topojson.feature` and `topojson.mesh`. Circle radii are scaled by population values.

Fftjyangf

Kknut_ivar_osvoll@hotmail.com

Sized Points on a Map

This visualization displays world cities with populations exceeding 50,000 as sized points on a natural Earth projection. Circle radii encode population using a square root scale, with data sourced from the Simplemaps World Cities Database. The map renders via React and SVG, using d3.geoNaturalEarth1, d3.geoPath, and d3.geoGraticule to draw country boundaries and graticules, while TopoJSON provides land and interior mesh geometry.

Sized Points on a Map

This example displays cities with populations over 50,000 as sized points on a world map, using a square-root scale to encode population by circle radius. The map renders with the `geoNaturalEarth1` projection and `geoPath` in React, showing graticules and country boundaries from World Atlas TopoJSON. City data comes from Simplemaps via CSV, loaded with `d3.csv`. Circles are drawn with SVG, styled with a teal fill and 0.3 opacity.

Eerahma

Sized Points on a Map

A world map displays cities with populations exceeding 50,000, using circle size to encode population magnitude. The visualization renders geographic context via d3.geoNaturalEarth1 projection and d3.geoPath for landmasses, graticules, and country boundaries. City positions are projected from latitude and longitude coordinates, with circle radii scaled by a d3.scaleSqrt function representing population values. Data comes from the Simplemaps World Cities Database and World Atlas TopoJSON, while React components manage the SVG rendering.

Nnkohdatavis

Sized Points on a Map

Nnkohdatavis

Sized Points on a Map

This example displays a world map with sized points representing cities, where the circle radius encodes each city's population using a square root scale with a maximum radius of 15 pixels. It renders the Natural Earth projection via d3.geoPath, including graticules and land boundaries from Topojson World Atlas data. City coordinates and population values come from a CSV dataset, and the visualization uses React for component structure alongside D3 v6 for geographic projections and scales, with all marks drawn as SVG elements.

WWolfgang