Gist fdfc88707da3d0b9b203

100%

Gist fdfc88707da3d0b9b203

✓ Published0🌍 Public

Last edited May 10, 2014

Created on May 10, 2014

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.

AI-generated description

Here is some explanatory text.

Similar vizzes

Loading thumbnail…

Gist f8b83c150e82b21c7d6fcadc802fb986

This example visualizes a network of interconnected nodes and links, revealing the structure of a graph through spatial clustering and connective pathways. It uses a force-directed layout powered by `d3.forceSimulation` to position nodes, with `d3.drag` enabling interactive repositioning. The rendering relies on SVG elements for both nodes and links, with node fill colors and radii encoding categorical data and degree. The underlying dataset is a static JSON structure of nodes and edges, drawn using standard SVG `circle` and `line` primitives within a responsive viewBox.

PPeleke

82% match

Loading thumbnail…

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

81% match

Loading thumbnail…

Gist f52706b726949be61205fcf8133a66e7

This example visualizes a dynamic network of interconnected nodes, showing how forces shape a cluster’s layout over time. It uses a force-directed simulation via `d3.forceSimulation` with charge, link, and collision forces to position nodes, while links are drawn as straight lines. The rendering relies on SVG paths updated each tick, and the code includes a custom drag interaction using `d3.drag` to let viewers manually reposition nodes. The underlying data structure is a small JavaScript array of objects representing nodes and links, likely sourced from a static inline dataset. The visualization emphasizes real-time interaction rather than geographic or spatial data, focusing on emergent clustering behavior.

11wheel

81% match

Loading thumbnail…

Gist 5a40403d5dadf54225cee084d8fb8b15

This example visualizes geospatial relationships using a D3.js force-directed graph overlaid on a map. The notebook configures an interactive simulation where interconnected nodes are positioned based on proximity and links, while geographic boundaries serve as a contextual base layer. It employs `d3.forceSimulation` for the physics engine, `d3.geoPath` to render map regions, and Jupyter’s inline display for rendering. The data appears to be custom-generated, with node connections defined programmatically in the notebook rather than sourced from an external file. The visualization emphasizes network topology against a spatial backdrop, allowing users to explore clustering patterns and geographic anchor points.

MMistyBlunch

81% match

Loading thumbnail…

Gist 8c07c4405dfafcf9d164e5f519f62a05

This example visualizes categorical groupings through a force-directed network layout, using node positions and connecting edges to reveal clusters and their interconnections. The code employs D3.js’s `d3.forceSimulation` for physics-based layout and `d3.geoPath` to render curved links, while node styling relies on the Canvas API’s `getImageData` for pixel-level detail. Data originates from a Gist, processed as JSON. The scene updates each tick, smoothly adjusting to simulated forces, which portrays the structural relationships among items.

PPeleke

81% match

Loading thumbnail…

Gist 703

This example uses a force-directed graph layout to show the clustering of related items. The visualization relies on `d3.forceSimulation` to position nodes, with links drawn between connected points. The code applies a custom styling reset and uses SVG elements for rendering, while the underlying data comes from a gist. The layout emphasizes spatial grouping, with node positions determined by simulated physics rather than a fixed coordinate system.

DDylanFM

81% match

Loading thumbnail…

MIT-License

This visualization uses a physics-based simulation to cluster and connect nodes in a network. It shows a dynamic system of points that repel each other while links pull them together, creating an organic, ever-shifting layout. The code leverages d3.forceSimulation to model the forces and d3.geoPath for rendering the curved edges. Built on a gist of public data, the example demonstrates real-time interaction with the simulation, offering a clear view of how force-directed algorithms explore spatial arrangements.

11wheel

80% match

Loading thumbnail…

Gist 41688f44df38ac0b35d9

This example shows a force-directed network graph where nodes are connected by curved links, with a color scheme that differentiates clusters. The visualization uses D3.js’s `forceSimulation` API to compute the physics-based layout, while the links are drawn as Bézier curves using the `d3.geoPath` generator. Node positions and link paths are updated iteratively in a custom simulation loop, with the rendering performed on an HTML5 Canvas element. The code reads a static JSON dataset embedded within the HTML file, providing the node and link definitions for the graph.

MMyoshu

80% match