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This visualization displays the relationship between car origin and horsepower, with each car represented as a circular mark and hover tooltips revealing the model name. The code uses the Vega-Lite API to define the scatterplot encoding, while D3’s `csv` function loads the auto-mpg dataset from a GitHub gist. The visualization renders as SVG with custom axis styling and tooltip handling via `vega-tooltip`, and it fits to the full window using autosize.

Vvigneswaran009

Fork of Vega-Lite API Template

This example visualizes automobile data by plotting car origins on the x-axis against horsepower on the y-axis, with the vehicle’s name available as a tooltip. Built using the vega-lite-api, it programs a scatter plot with semitransparent circular marks, configured to fit the entire viewport. The code loads an auto-mpg CSV dataset via D3’s `csv` method, registers Vega-Lite with a tooltip handler, and applies custom axis and label styling from a shared config module.

CChristian Rohrer

Fork of Vega-Lite API Template

This example visualizes the relationship between a car's country of origin and its horsepower using a scatter plot. Each point represents a car, with opacity applied to reveal overlapping data points, and a tooltip displays the car's name on hover. The visualization is built using the Vega-Lite API, which generates a specification rendered to SVG via Vega and Vega-Lite. It loads the Auto MPG dataset from the UCI Machine Learning Repository using `d3.csv`, and customizes axis styling and tooltip appearance through a configuration object.

Ww.fukuyama@gmail.com

Fork of Vega-Lite API Template

This example visualizes automotive data from the auto-mpg.csv dataset, plotting horsepower against year with a tooltip displaying vehicle names. The visualization is built using the Vega-Lite API, which programmatically constructs a scatter plot with semi-transparent points. The code leverages vega-lite-api, vega-lite, and vega-tooltip to render the chart as SVG, while D3.js fetches and parses the CSV data. Custom axis and label styling are applied via a shared configuration object to improve readability across the full browser window.

JJay M Gonzalez

Fork of Vega-Lite API Template

This example displays a scatter plot of car data, with each point representing a vehicle. The visualization uses a circular mark with low opacity to show the distribution of horsepower across different regions of origin, with tooltips revealing the car’s name. The chart is built using the Vega-Lite API, which programmatically defines the visualization, while D3’s `csv` method loads the dataset. The rendering is handled by Vega and Vega-Lite, with a custom tooltip handler and styling to improve readability.

Jjaowei

Fork of Vega-Lite API Template

This example visualizes the relationship between fuel efficiency (mpg) and horsepower for a collection of automobiles, with points colored by origin and sized by mpg, using a tooltip to display car names. It employs the Vega-Lite API to declaratively define the scatterplot, registered with Vega and Vega-Lite, and renders it as SVG within a full-window layout. Data is loaded asynchronously from a CSV file using D3’s `csv` method, while the built-in Vega Tooltip handler manages interactive hover details. The configuration customizes axis styles and label fonts for improved readability.

Wwy2010344

Fork of Vega-Lite API Template

This example displays a scatter plot of automobile displacement versus horsepower, with each circle representing a car model and tooltips revealing the vehicle name. The visualization is built using the Vega-Lite API, which constructs a declarative specification rendered through Vega, and loads data from a CSV file containing auto-mpg statistics. The code registers Vega-Lite and Vega Tooltip for interactive hover effects, while custom configuration options adjust axis labels, typography, and the dark color palette. D3 is used only for fetching the dataset via its csv method.

DDeepanshu

Fork of Vega-Lite API Template

This example shows a scatter plot of auto-mpg data, where each circle represents a vehicle’s origin and horsepower, with tooltips revealing the model name. The visualization is built using the Vega-Lite API, with D3.js (d3.csv) loading data from the UCI Machine Learning Repository’s Auto MPG dataset. The code registers Vega, Vega-Lite, and Vega-Tooltip, applies a custom configuration for axis and label styling, and renders the plot as an SVG that fits the browser window.

KKeyvan Rezaei