Using Points on a World Map

100%

Using Points on a World Map

✓ Published0🌍 Public

Last edited May 25, 2021

Created on May 25, 2021

This visualization displays a world map with points marking cities that have populations greater than 50,000, sourced from the Simplemaps World Cities Database. Using d3.geoNaturalEarth1 and d3.geoPath, it renders land masses, graticules, and country interiors as SVG paths, with city coordinates projected onto the map. The React-based code loads TopoJSON world atlas data via d3.json and mesh, while city data is fetched as CSV. Circles are drawn with low opacity to reveal dense urban clusters across continents.

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…

world ma Points on a Map

This visualization displays a world map with points marking cities whose population exceeds 50,000, sourced from the Simplemaps World Cities Database. It uses a Natural Earth projection via d3.geoNaturalEarth1 and d3.geoPath to render land, graticules, interiors, and a sphere outline from World Atlas TopoJSON data. City points are projected and drawn as semi-transparent circles. The React-based implementation, using d3.v5 and SVG rendering, creates a clean, minimal aesthetic with light gray landmasses and teal city markers.

Ssagar limbu

95% 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

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

A world map populated with semi-transparent circles representing the populations of cities from a cleaned World Cities dataset. The visualization uses a Natural Earth projection rendered with `d3.geoPath`, layering graticules, land masses, and country borders beneath the points. Circle radii are scaled with `d3.scaleSqrt` based on population, capped at a maximum radius of 15 pixels. The React component fetches TopoJSON world atlas data and CSV city data, then renders the SVG marks with D3 v5.

Wwindwaver

94% 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_

93% match

Loading thumbnail…

Points on a Map

A world map displays cities with populations over 50,000 as semi-transparent dots. The visualization uses a natural Earth projection via d3.geoNaturalEarth1 and renders geographic features with d3.geoPath, including land masses and graticules. City coordinates are projected from latitude and longitude into SVG circle positions. The map loads country boundaries from World Atlas TopoJSON and city data from a Simplemaps CSV, with React managing the data-fetching hooks and rendering the SVG marks.

GGeniXiong

93% match

Loading thumbnail…

Points on a Map

This visualization displays world cities with populations exceeding 50,000 as semi-transparent teal points on an SVG map. The map uses a Natural Earth projection via d3.geoNaturalEarth1, with landmasses, graticules, and interiors rendered using d3.geoPath. City locations are projected from latitude and longitude coordinates, then drawn as small circles. The underlying city data comes from Simplemaps, while country boundaries come from the World Atlas TopoJSON, both loaded asynchronously with d3.csv and d3.json. The React component structure uses custom hooks for data fetching.

SSabin Bhandari

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