Gist 9bd5ca69fc039cff50383b3a3459858b

100%

Gist 9bd5ca69fc039cff50383b3a3459858b

✓ Published0🌍 Public

Last edited Sep 27, 2018

Created on Sep 27, 2018

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.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 54a4da81bb77308303fc5537ac587fe5

This example creates a minimal map visualization using a single GeoJSON Point feature representing the Dinagat Islands, positioned at coordinates (-86.8098, 36.1442). It first renders the point’s geometry using `d3.geoPath` and a standard geographic projection, then applies `d3.forceSimulation` to animate the point’s position, demonstrating how a fixed geographic coordinate can be displaced by a force-directed layout. The code uses both Canvas and SVG elements, with the simulation updating the point’s screen location each tick while the underlying projection remains static.

CCliffordAnderson

84% match

Loading thumbnail…

Gist 34bad0b124f4effdf99d5555cb3222d8

This example shows how spatial relationships between geographic features can be explored through an interactive map. It uses D3.js with `d3.geoPath` to render country outlines from a GeoJSON source, while a force-directed layout via `d3.forceSimulation` positions non-overlapping markers for data points. The visualization computes marker placement on a Canvas, reading pixel colors with `getImageData` to detect land versus water and ensure points remain on landmasses. Hover interactions trigger a tooltip and highlight neighboring regions, with smooth transitions handled by `transition.attrTween`. The data originates from a public GitHub gist and is embedded in a Power BI report, where the canvas is updated on each zoom or pan event.

HHugoberry

83% match

Loading thumbnail…

Gist fdfc88707da3d0b9b203

This example shows the clustering and connection of points on a map based on their geographic proximity and shared attributes. It uses a force-directed layout via `d3.forceSimulation` to position nodes while links are drawn as curved paths, with a base projection provided by `d3.geoPath` and `d3.geoMercator`. The data is loaded from an external CSV file, and the visualization updates dynamically as the simulation runs, highlighting node neighborhoods and their interconnections.

MMSCAU

81% match

Loading thumbnail…

Gist 579bcba6019da7a932da70826f5d0c83

This interactive example visualizes the spatial layout of books from Project Gutenberg, mapping each title to a point based on its geographic coordinates and rendering them as a dense, globe-like scatter plot. Using D3.js’ `d3.forceSimulation` with gravitational and collision forces, the points are arranged into a spherical cluster, while user interaction—dragging or hovering—updates the positions in real time. The visualization employs `d3.forceX`, `d3.forceY`, and `d3.forceZ` to distribute points in three-dimensional space, and it relies on `d3.select` and event handlers to manage the dynamic behavior. The code uses a canvas-based rendering approach with `getImageData` for pixel-level color manipulation, giving the plot a glowing, heatmap-like appearance.

AAnaMal08

79% match

Loading thumbnail…

Gist 61957648a96af6b4167e

This example visualizes traffic crash records from a Gist file, mapping each participant’s location and attributes onto a canvas. It uses a force-directed layout with `d3.forceSimulation` to spatially arrange points, while `d3.geoPath` renders geographic features from the included geometry. The code reads the raw text data, parses fields like crash severity and participant details, and draws small circles colored by injury severity. It also employs Canvas `getImageData` for pixel-level rendering, and transitions with `transition.attrTween` to animate point movement. The result is an interactive scatterplot-style map of incident density and participant distribution.

CCaged

79% match

Loading thumbnail…

Gist fe5834a6c79855e23c3c7e3ae7e7f048

This example visualizes the distribution of a dataset through an interactive scatterplot, encoding three variables on the x- and y-axes and point size. The visualization uses D3.js with `d3.forceSimulation` to arrange overlapping points into a readable layout, while `d3.scaleLinear` and `d3.axisBottom` handle axis generation. Rendering is done via SVG circles, and transitions are applied using `transition.attrTween` to smoothly update positions when data changes. The underlying data originates from a static JSON array embedded in the gist, with no external data source, and the code includes hover tooltips via `d3.select().on("mouseover")` for individual point inspection.

AAlexDaGr8

79% match

Loading thumbnail…

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

79% match

Loading thumbnail…

Cloudant Post

This example visualizes the geographic distribution of user-uploaded content from a Cloudant database, rendered as an interactive map. It first retrieves raw GeoJSON data from the Cloudant API, then uses `d3.geoPath` to project and draw country outlines, while `d3.forceSimulation` positions individual point markers based on their latitude and longitude. The map’s tile layer is generated with Canvas `getImageData` to apply a custom color scale to population density, and user interactions trigger `transition.attrTween` for smooth panning and zooming. The code relies on Three.js for the underlying WebGL rendering of the base terrain.

CCliffordAnderson

79% match