My First interaction with Vega-Lite API

Vega-Lite API Template Practice

This example demonstrates how to use the Vega-Lite API to create an interactive scatter plot of automotive data, mapping origin, horsepower, weight, and acceleration to visual channels. The visualization renders as an SVG. The code imports data from a CSV file via `d3.csv` and constructs the chart using `vega-lite-api` methods such as `markCircle` and `encode`, with `vega` and `vega-lite` registered for chart compilation. Tooltips are added through the `vega-tooltip` library, and the chart is configured to fit the browser window.

JJames Rhodes

Vega-Lite API Template

This example visualizes automobile data from the UCI Machine Learning Repository’s Auto MPG dataset, plotting origin on the x-axis, horsepower on the y-axis, and encoding mpg as circle size with tooltips showing car names. Built with the Vega-Lite API, it registers vega, vega-lite, and vega-tooltip in index.js, loads CSV data via d3.csv, and renders an interactive SVG chart configured with custom axis and label styling from config.js. The visualization updates dynamically to fit the browser window.

JJohn Lewis

Vega-Lite API Template

This visualization displays automobile data from a CSV file, plotting horsepower against origin with points colored by year and labeled by name. It demonstrates the vega-lite-api library, which programmatically constructs Vega-Lite specifications using JavaScript method chaining. The code registers Vega, Vega-Lite, and the API with vega-tooltip, then renders an interactive SVG chart that adapts to the window size. Custom axis and label styles in config.js improve readability against a dark theme.

NNadir-Zenith

Vega-Lite API exploration

This visualization explores the Vega-Lite API by rendering an interactive scatter plot of automobile data from a CSV file, showing the relationship between miles per gallon and horsepower, colored by country of origin. The code uses the `vega-lite-api` library alongside `vega` and `vega-lite` to construct the chart declaratively, with `d3` for data loading. It renders as SVG, applies a custom configuration for axis styling, and includes tooltips via `vega-tooltip` to display car names on hover.

AAleksandra Timofejeva

Ep18: Vega-Lite API

This visualization displays automobile data from a CSV file, plotting engine origin, horsepower, weight, and miles per gallon as a scatter plot with circles of varying size and color. The example highlights the convenience of the Vega-Lite API (vl) for declarative charting, which constructs and renders the specification. It uses vega-lite and vega to compile the spec, d3.csv for data ingestion, and vega-tooltip to provide interactive tooltips on hover. The chart is configured to fit the browser window.

SStoo Sepp

Vega-Lite API Example

This example uses the Vega-Lite API to create a scatter plot of automobile data from a CSV file. The visualization encodes miles per gallon, horsepower, origin, and weight into position, color, and size, with a tooltip revealing the car name. It leverages vega-lite-api, vega, and vega-lite to generate an SVG chart, and d3.csv for data loading. The chart uses overlaid translucent circles and a custom config to improve label readability.

Bbakstorage00001

Vega-Lite API Template

This example visualizes automobile performance data from a CSV file, plotting engine displacement against horsepower with circles colored by origin and sized by weight. Tooltips reveal car names on hover. The visualization is built using the Vega-Lite API, which registers Vega and Vega-Lite libraries, loads data with d3.csv, and renders an SVG chart configured with custom axis styling and a dark color scheme. The code demonstrates programmatic chart construction through vl.markCircle and vl.encode methods.

CCurran Kelleher

Vega-Lite API Template - Part 1

This example demonstrates a scatter plot of automotive data, showing the relationship between horsepower and acceleration, with tooltips displaying car names. Built using the Vega-Lite API, it loads the auto-mpg dataset via D3’s `csv` function. The visualization uses `vl.markPoint`, `vl.x().fieldQ`, and `vl.y().fieldQ` to encode quantitative fields, with a custom config adjusting axis and font styles. Rendered through Vega-Lite’s SVG output, it integrates vega-tooltip for interactive hover details.

JJohn Jeevasaeyan