Gist 8393715

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.

82% match

Gist 9bd5ca69fc039cff50383b3a3459858b

This example shows how to render a spatial distribution of data points on a map using D3.js. It uses `d3.geoPath` to draw geographic boundaries and `d3.forceSimulation` to position overlapping points, while Canvas `getImageData` is used to read pixel data for collision detection. The visualization reads from a PGP-encrypted text file, suggesting the underlying dataset is not directly accessible. The code relies on D3’s selection and transition APIs to animate point movements, and it appears to use a projection to convert latitude and longitude coordinates into screen positions. The result is an interactive scatterplot overlaid on a map, with points dynamically adjusting to avoid overlap.

CCliffordAnderson

76% match

Gist bb974dcf54acc39a81cb60d79bf0aa5c

This example plots earthquake epicenters as points on a map using GeoJSON features. It renders the geographic coordinates with `d3.geoPath` and a map projection, while each point is positioned via `d3.forceSimulation` to avoid overlapping labels. The visualization shows five recent seismic events, with the primary ID as magnitude and the secondary ID as a location description. The code uses D3’s force-directed layout to spread the point markers, and the map background likely comes from a geographic shapefile or topojson layer, making the data immediately readable by region.

JJn1532

75% match

Gist 10676346

This map displays labeled points from a GeoJSON file, plotting locations like "Internet Archive," "China," and "New York" at their geographic coordinates. The visualization likely renders a large-scale point cloud, with overlapping labels suggesting a messy or aggregated dataset. Using a mapping library, likely D3.js with `d3.geoPath` for drawing map features and standard SVG or Canvas techniques for placing text labels, the code creates a simple geographical scatter plot. The rendering emphasizes the spatial distribution of these named places across the globe.

CCliffordAnderson

Gist 8394767

The visualization plots ancient Roman amphitheaters as points on a map, using circle size to encode seating capacity and position to show geographic spread. It renders the GeoJSON features with a geographic projection, likely via `d3.geoPath`, and applies a force simulation to avoid label overlap. The map background and points are drawn on a canvas, with hover interactions to reveal titles and details from the embedded properties.

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 8393657

This example maps two geographic points from a GeoJSON FeatureCollection onto a world map using D3’s `d3.geoPath` and a geographic projection. It then runs a force-directed simulation with `d3.forceSimulation`, treating the points as nodes that repel each other while being constrained by the map’s bounds. The visualization shows how the points drift and settle under the force layout, with their positions updated via D3’s data join. The code relies on the `Octomonster.geojson` file for the initial coordinates and uses Canvas rendering for the map and points.

Gist 6245338

This visualization maps three Spanish cities as individual points on a geographic projection, with each point represented by a small dot. It uses a custom map projection and renders the GeoJSON features as a filled landmass, while the city markers are drawn as circles. The code relies on `d3.geoPath` to project and draw the map geometry, and `d3.forceSimulation` is not used here; instead, the points are placed directly at their projected coordinates. The canvas API (`getContext('2d')`) handles all rendering, and the map’s geographic boundaries come from the embedded `map.geojson` FeatureCollection.

PPhilippe Rivière