Gist 8393718

Gist 8393666

This visualization plots bicycle shops in Glasgow using GeoJSON data from OpenStreetMap, with point and polygon features representing shop locations and building footprints. It shows the geographic distribution of bike retailers across the city, from central shops like Billy Bilsland to suburban outlets such as Clarkston Cycle Centre. The example uses D3.js with `d3.geoPath` to render the map shapes and likely employs a geographic projection to convert latitude-longitude coordinates into screen positions. The code processes the FeatureCollection to draw each shop as a distinct visual element, highlighting the spatial clustering of cycling-related businesses.

76% match

Gist 8393664

This visualization maps thousands of point features from a GeoJSON dataset of Bern, Switzerland, using D3.js. It shows the spatial distribution of automotive-related locations, including parking areas, fuel stations, and pedestrian crossings. The code loads the GeoJSON with `d3.json` and renders the points as small dots, likely using `d3.geoPath` to project coordinates onto a map canvas. The visualization relies on D3's projection and path APIs to display the geographic context.

75% match

Gist 6ce6b2a6ecda4579b64f

This visualization uses a Vue.js interface to display a list of city and state locations, likely from a dataset of place names. It shows a static, text-based table of these locations, with no visible map or chart. The code relies on standard DOM rendering through Vue’s template system, without additional data-viz libraries like D3 or Three.js. The rendering approach is a simple list, and the data source appears to be a CSV of location strings. No interactive or dynamic behavior is evident beyond the initial display.

CCaged

73% match

Gist 8393725

The visualization displays a GeoJSON point dataset of named locations—such as Traino, Cascata, and Neviera—near a specific area in Italy, each with a YouTube link. It uses D3.js with a force-directed simulation (`d3.forceSimulation`) to position the points on a map, while `d3.geoPath` renders the geographic features. The points are colored and labeled, and hovering or clicking likely reveals the associated video link. The code relies on the GeoJSON structure for both location data and map boundaries.

72% match

Gist 32329a8557135f11cb5656e3bfd4d35c

A WebGL map visualizes the locations of French tobacco shops, using points to show their distribution. The code geocodes addresses from an official customs dataset via the data.gouv.fr API, then processes the CSV with the `requests` library. It uses a Vue.js front-end to render the points in a 3D space, allowing users to explore the spatial patterns of the shops.

TThomasG77

Gist 8393692

This example displays two geolocated markers on a map, each with a title and description of a building. It uses a `map.geojson` file as the data source, containing point features with custom properties for labels and colors. The visualization renders the map using D3’s `d3.geoPath` to draw the geographic features, while the markers are positioned based on their coordinates. The code relies on D3’s force simulation (`d3.forceSimulation`) to potentially handle marker placement or interaction, though the static view shows the two points plotted directly.

Gist 8393709

This visualization displays a world map rendered from GeoJSON data using D3.js, with country polygons colored according to a categorical scale. The map focuses on named regions and includes a legend and hover interactions, allowing viewers to explore geographic boundaries and associated metadata such as country names and people listed in the properties.

Gist 1438976

This example visualizes the spread of points across a map using a force-directed layout. It shows how simulated particles or nodes distribute themselves over geographic boundaries, revealing spatial clustering and density patterns. The code employs `d3.forceSimulation` to animate node positions and `d3.geoPath` to render map shapes, likely from a GeoJSON source. It also uses JavaScript’s Canvas API for drawing, with the simulation running in a loop to update the visualization in real time. The underlying data appears to be generated programmatically rather than sourced from an external dataset.

Aabernier