Skip to main content
SimilarExport ZIP
100%

Gist 6112837

✓ Published0🌍 Public
IIanHopkinson
Last edited Jul 30, 2013
Created on Jul 30, 2013

This example visualizes the 2008 cohort of vehicle test records from a gist, mapping individual vehicles as nodes in a force-directed network. The visualization uses d3.forceSimulation to compute node positions based on shared attributes like make and fuel type, while d3.geoPath renders a geographic backdrop for postcode regions. Canvas getImageData samples pixel colors for a density heatmap overlay, and transition.attrTween animates node movements during filtering. The schema.ini file defines the pipe-delimited data structure, and the code reads the CSV directly from the gist to drive the interactive layout.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 6716af5ab2fd2c7d25baee69dc577448

This gallery example visualizes a subset of the classic “car.csv” automobile dataset, plotting fuel economy against model year. Each car is drawn as a small circle, positioned by its year and economy values, with the point’s color encoding the car’s brand. The implementation uses the D3.js library, specifically `d3.forceSimulation` to arrange overlapping labels or points and `d3.geoPath` for any map projection, though the core scatter plot is rendered via standard SVG circles. The visualization is built entirely from client-side JavaScript, directly parsing the CSV file to drive the animated layout.

JJulioTJ
79% match
Loading thumbnail…

Gist 449c2fd0db4f7c31adc4c7cd995fece0

The visualization maps car models from the classic “cars.json” dataset, plotting each vehicle by its weight and horsepower. It uses a D3 force-directed layout, likely with `d3.forceSimulation`, to position points without overlap, while color and size encode the number of cylinders and miles per gallon. The rendering relies on SVG paths generated by `d3.geoPath` for the background map of the United States, highlighting each car’s origin region. The data comes directly from the provided JSON file, with missing values for miles per gallon handled as `null`, and the chart emphasizes broad trends between engine displacement, fuel efficiency, and vehicle class.

AAlainRo
76% 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
76% match
Loading thumbnail…

Gist db32a113f546aa03b43c0e1f84f80d28

The visualization shows a force-directed network graph of GitHub gist data, with nodes representing individual gists and links showing relationships between them. It uses d3.forceSimulation to compute the layout, with node size encoding gist size and color indicating file type or language. The rendering relies on SVG elements updated per tick via the simulation’s tick event. The code loads a static JSON file containing preprocessed gist metadata, and does not use canvas or WebGL. The visualization highlights clustering patterns among related gists, revealing emergent communities in the dataset.

335degrees
74% 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
74% match
Loading thumbnail…

Gist 484101

This visualization shows an interactive network of interconnected nodes, with each node representing a person and links showing connections between them. It reveals the structure of social ties, likely from a GitHub collaboration graph, by grouping related clusters. The rendering uses a canvas-based `d3.forceSimulation` with custom collision and link forces to position nodes, while a custom `d3.geoPath`-style projection maps node positions onto a projected sphere. The code also employs Canvas `getImageData` to detect node boundaries for hover interactions, and uses `transition.attrTween` for smooth link animations. The underlying data is loaded from a Gist, and the visualization runs entirely client-side without external data files.

DDylanFM
74% match
Loading thumbnail…

Network Graph ICE 8

This network graph visualizes vehicle data from a CSV file, organizing vehicles into a hierarchical structure by Make, Model, Fuel Type, and Transmission. It uses d3.forceSimulation to position nodes in a dynamic layout, with circles colored by depth level and labeled accordingly. The graph is rendered as SVG using d3.v7, with links connecting parent and child nodes to show the relationships between vehicle attributes.

Ssaisathwikaguntupalli@gmail.com
74% match
Loading thumbnail…

Network Graph ICE 8

This network graph visualizes vehicle data from a CSV file, organizing vehicles into a hierarchical structure by Make, Model, Fuel Type, and Transmission. It uses d3.forceSimulation to position nodes in a dynamic layout, with circles colored by depth level and labeled accordingly. The graph is rendered as SVG using d3.v7, with links connecting parent and child nodes to show the relationships between vehicle attributes.

Ssaisathwikaguntupalli@gmail.com
74% match