Points on a Map

100%

Points on a Map

✓ Published1🌍 Public

Last edited Jan 15, 2022

Created on Jan 15, 2022

This example displays a world map with small, semi-transparent dots marking cities with populations over 50,000. The map is rendered as SVG using D3’s `geoNaturalEarth1` projection, with landmasses, graticules, and country interiors drawn via `geoPath`. City locations are projected from latitude and longitude coordinates loaded from a CSV file, with each point drawn as a circle. The React application uses custom hooks to fetch the world atlas and city data, with styling applied through CSS classes.

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 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

96% match

Loading thumbnail…

Points on a Map

A world map displays the locations of cities with populations over 50,000 as small semi-transparent dots, overlaid on landmasses with country borders and graticules. Using React, the visualization loads GeoJSON world-atlas topology and city data via D3’s `json` and `csv` methods, then projects coordinates with `geoNaturalEarth1` and renders SVG paths and circles through `geoPath`. The map’s gray land, interiors, and sphere are styled distinctly, while city points use D3’s `projection` to convert longitude and latitude into screen positions.

LLove Wessman

95% match

Loading thumbnail…

Points on a map

This example displays a world map with points representing cities, sized by population. The map is rendered as SVG using React, with D3's `geoNaturalEarth1` projection and `geoPath` drawing landmasses, graticules, and sphere outlines. City coordinates are projected onto the map, and circles are scaled with `scaleSqrt`. The code loads world topology from a JSON via `useWorldAtlas` and city data from a CSV using the `csv` utility, styling land areas and points with CSS.

SSai Phaltankar

95% 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

95% 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

93% 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 map of the world displays cities with populations over 50,000 as small translucent dots. The visualization uses a React component with D3’s `geoNaturalEarth1` projection and `geoPath` to render country boundaries, graticules, and the sphere outline. City coordinates are projected from latitude and longitude, with data loaded via `d3.csv` from the Simplemaps World Cities Database, while land and interior borders come from TopoJSON in the World Atlas TopoJSON dataset.

MMarco Malvicini

93% match

Loading thumbnail…

Points on a Map

This example displays world cities as scaled circles on a natural Earth projection, with each circle’s radius proportional to its population. The map renders landmasses, graticules, and interiors using `d3.geoPath` and `d3.geoNaturalEarth1`, while the city points are drawn as SVG circles with a square-root scale for size encoding. The visualization loads geographic topology from `world-atlas` and city CSV data via `d3.csv`, using React hooks (`useState`, `useEffect`) to manage the asynchronous data fetching and triggering re-renders.

NNikita Toropov

93% match