ICE 7

ICE7-1-VarshaG

This interactive scatter plot explores the relationship between fuel efficiency (mpg) and horsepower across vehicles, with color mapped to origin and point size to weight. It renders the 398 cars from the UCI Auto MPG dataset using the vega-lite-api library, building a single circle mark with tooltips for names. The visualization adapts to the full viewport, and the accompanying vega-tooltip handler displays each vehicle's details on hover.

91% match

ICE6 - Avinash Chinta

This interactive scatter plot explores the relationship between miles per gallon, horsepower, and weight across different regions of origin, using data from the UCI Machine Learning Repository's Auto MPG dataset. Each circle’s size encodes vehicle weight, while color distinguishes the car’s origin, and hovering reveals the model name. Built with the Vega-Lite API, the visualization registers Vega, Vega-Lite, and Vega-Tooltip to enable interactive tooltips and responsive rendering. The underlying data is fetched asynchronously via d3.csv, with axes configured to exclude the domain line and styled with custom fonts and colors for readability.

Aavinashchinta99

88% match

ICE_7 Cars horsepower and miles per gallon(mpg)

This scatter plot visualizes the relationship between horsepower and miles per gallon for various car models, with each point colored by the car’s origin and sized by its weight. The visualization is built using the Vega-Lite API, which constructs the chart specification in `viz.js`, while the data is loaded via `d3.csv` from a Gist derived from the UCI Auto MPG dataset. The rendering pipeline registers Vega and Vega-Lite, applies a custom config for axis and label styling, and adds interactive tooltips through the Vega-Tooltip handler.

SShishiraRudrabhatla

88% match

VarshaICE7

This visualization uses a scatter plot to explore the relationship between fuel efficiency (mpg) and horsepower across vehicles, with color indicating origin and point size encoding weight. Built with the vega-lite-api library and rendered using vega-lite and vega, the plot loads data from the UCI Auto MPG dataset via d3.csv. A tooltip from vega-tooltip displays each car’s name on hover. The visualization fits the entire browser window, and axis labels are styled with a custom configuration for improved readability.

Fork of ICE7-1-VarshaG

This visualization explores the relationship between fuel efficiency, horsepower, weight, and origin in the Auto MPG dataset from the UCI Machine Learning Repository. A scatter plot positions each car by miles per gallon and horsepower, with color encoding the region of origin, while the size of each circle encodes vehicle weight. Tooltips reveal the car name on hover. The chart is built with the vega-lite-api, which registers Vega and Vega-Lite, and loads the CSV data using d3.csv. Custom configuration adjusts axis labels, tick colors, and font sizes for improved readability.

ICE7-1-VarshaG

This scatter plot visualizes automobile data, mapping engine displacement and horsepower to the x and y axes while encoding weight through circle size and origin through color. The visualization is built using Vega-Lite’s declarative grammar via the `vega-lite-api` wrapper, with `markCircle` and encodings for quantitative and nominal fields. Data is loaded from a CSV file using d3’s `csv` method, and the chart is rendered as an interactive SVG with tooltips provided by `vega-tooltip`.

Fork of VarshaICE7

This visualization displays automobile data from the UCI Machine Learning Repository’s Auto MPG dataset as a scatter plot, mapping fuel efficiency (mpg) against horsepower, with point size encoding vehicle weight and color marking the country of origin. The chart is built using the vega-lite-api library, which wraps Vega-Lite and Vega, and renders interactively with tooltips showing car names. Data is loaded asynchronously via d3.csv from a remote Gist, while the visualization is configured with custom fonts and axes for improved readability. The layout fits the browser window, adjusting dynamically to viewport dimensions.