Points on a Map

100%

Points on a Map

✓ Published0🌍 Public

Last edited Dec 24, 2021

Created on Dec 23, 2021

This example visualizes cities with populations over 50,000 as semi-transparent circles on a natural Earth projection. The map displays country boundaries, interiors, graticules, and a sphere outline, with circle size scaled by population using `d3.scaleSqrt`. The React-based visualization uses `d3.geoPath` for geographic rendering and `d3.geoNaturalEarth1` for projection, with city data loaded from Simplemaps via CSV and country shapes from World Atlas TopoJSON.

AI-generated description

A world map showing cities with population greater than 50,000. City data from Simplemaps: World Cities Database.

Country boundaries from World Atlas TopoJSON, polished for visual style, including graticules.

MIT Licensed

Similar vizzes

Loading thumbnail…

Points on a Map

This visualization displays a world map with circles marking cities whose population exceeds 50,000, using the Natural Earth projection via `d3.geoNaturalEarth1` and `d3.geoPath`. The map includes graticules and country boundaries from World Atlas TopoJSON, with city data sourced from Simplemaps. Circle radii are scaled by population using `scaleSqrt`, rendered as semi-transparent SVG elements in React. The implementation leverages React hooks for data loading and D3 v5 for geographic projections and CSV parsing.

Zzyniax

96% match

Loading thumbnail…

Points on a Map

This example displays a world map with cities whose populations exceed 50,000, plotted as semi-transparent circles. The map uses a Natural Earth projection via `d3.geoNaturalEarth1`, with landmasses, graticules, and country interiors drawn using `d3.geoPath` from the World Atlas TopoJSON dataset. City coordinates are projected from latitude and longitude into SVG circle positions, with the data loaded from a Simplemaps CSV via `d3.csv`. The rendering is handled in React, producing a clean, styled SVG visualization.

GGiovanniD_

95% match

Loading thumbnail…

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

94% match

Loading thumbnail…

Points on a Map

A world map displays cities with populations over 50,000 as semi-transparent points. The visualization uses D3’s `geoNaturalEarth1` projection and `geoPath` to render landmasses, country interiors, and graticules from TopoJSON data. City coordinates are projected and drawn as SVG circles, with data loaded from a CSV via `d3.csv` in React hooks. The map prioritizes geographic context over point density, using a light gray palette for boundaries and teal circles for city locations.

FFonda Irena Santoso

94% match

Loading thumbnail…

Points on a Map

This example displays a world map with dots marking cities that have populations exceeding 50,000. The map uses a Natural Earth projection and renders land masses, graticules, and country borders as SVG paths. City positions are projected from longitude and latitude coordinates using `d3.geoPath` with `geoNaturalEarth1`, and each city is drawn as a semi-transparent circle. The visualization loads world atlas TopoJSON data and a city CSV dataset, with React managing the component lifecycle.

CCurran Kelleher

93% match

Loading thumbnail…

Points on a map

This example displays a world map with cities plotted as semi-transparent circles, where circle size reflects each city’s population. It uses a natural Earth projection via `d3.geoNaturalEarth1` and `d3.geoPath` to render land, graticules, and country borders from TopoJSON data. City coordinates and populations come from a CSV loaded with `d3.csv`, and circle radii are scaled with `d3.scaleSqrt`. The visualization is built with React hooks for data fetching and renders as SVG.

LLewis Ward

93% match

Loading thumbnail…

Points on a Map

This visualization displays world cities as semi-transparent circles overlaid on a natural Earth projection map, with circle size encoding population via a square root scale. The map includes land masses, country borders, graticules, and a sphere outline. React manages the component structure, while D3 v7 handles geo projection and path generation through `d3.geoNaturalEarth1` and `d3.geoPath`. City data comes from a CSV loaded with `d3.csv`, and world geography uses TopoJSON from the world-atlas package, rendered as SVG.

KK3zter

93% match

Loading thumbnail…

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

93% match