ICE7

ICE-7

This interactive scatter plot displays 120 car records from a CSV file, plotting attributes like horsepower, MPG, weight, and displacement against each other. Users can dynamically select which numeric column drives the x-axis, y-axis, point size, and categorical color (cylinders, origin, or year) via dropdown menus. The visualization, rendered as an SVG using D3 version 7, updates axes, gridlines, and legends in real time. Point radius is scaled with `d3.scaleSqrt` to encode area proportionally, while a hover tooltip shows details about individual cars.

92% match

Scatter plot ICE-7

This is a reusable scatter plot built with D3 v7 that visualizes 120 car records from a CSV file, showing relationships between four numeric variables (horsepower, MPG, weight, displacement) with matching dropdown controls. Users can reassign each axis, the color encoding (by cylinders, origin, or year), and the point size (by weight, horsepower, or displacement) dynamically. The point areas are scaled via `d3.scaleSqrt`, colors use `d3.scaleOrdinal` with Tableau schemes, and SVG dots update with data joins, grid lines, axes, and an interactive tooltip.

88% match

ICE_7 Scatter Plot

This animated scatter plot uses D3.js to visualize relationships among numeric car attributes, cycling through pairs of columns like horsepower, price, curb weight, city mpg, engine size, and highway mpg every 3.5 seconds. Circles are colored by drive wheel type via a categorical scale, with axes, labels, and a title updating smoothly through D3 transitions. The data comes from a remote CSV file, and the visualization fills the browser window, using D3 scales, axes, and ordinal color encoding to render the SVG animation.

AAbhiramPudi@my.unt.edu

88% match

ICE-7

This interactive scatter plot compares car models by horsepower, MPG, weight, and origin, using drop-down menus to switch the x- and y-axis variables and toggle point size encoding. D3 v7 builds the SVG visualization, applying scaleLinear, scaleSqrt, and scaleOrdinal with a Tableau10 color scheme to map data attributes. Points animate in via transition, and hover tooltips, powered by mouseover events, reveal car details. The legend groups points by origin, while drop-down selections trigger chart redraws through reusable configuration accessors.

88% match

scatter plot ICE-7

A scatter plot of 120 cars from the classic fuel-economy dataset, with axes, color, and point size mapped to numeric and categorical columns via dropdown menus. The D3 v7 reusable component uses `d3.scaleLinear`, `d3.scaleSqrt`, and `d3.scaleOrdinal` with `d3.schemeTableau10`, rendering SVG circles with animated transitions. Grid lines, axes, tooltips, and legends update dynamically when the user selects different columns.

ICE-7

This animated scatter plot visualizes used car data, comparing selling price against various attributes including maximum power, mileage, and kilometers driven. The visualization cycles through different x-axis variables every two seconds, allowing viewers to explore correlations between car characteristics and market value. Built with D3.js, the chart uses a reusable scatter plot function with linear scales for both axes, implementing smooth transitions through a `setInterval` callback. The SVG rendering incorporates the Share Tech font and displays data points as circles, with axis labels updating dynamically to reflect the currently selected variable.

RRaajithaSabbineni

Ssrinathkarumuru@my.unt.edu

ICE7

This scatter plot maps car engine size against price using the d3.csv loader and a linear scale for each axis. The SVG rendering includes axes formatted with currency ticks and labeled plot areas, with data points drawn as steel-blue circles. The chart filters out rows with invalid or zero values before plotting, and the dataset is loaded from a remote CSV file.

ICE 7 Reusable scatter plot (Sai Kaushik Ganji)

This interactive scatter plot shows car sales data, displaying price in thousands of USD against horsepower for individual vehicles, with point size reflecting engine size and color/shape encoding vehicle type. The visualization uses D3.js v7’s `d3.csv` to load and parse the Car_sales dataset, and employs `d3.scaleLinear`, `d3.scaleSqrt`, and `d3.scaleOrdinal` to map numeric and categorical variables. Marks are generated using `d3.symbol()` with varying symbol shapes, including circles, crosses, and triangles, demonstrating a reusable charting function that separates configuration from rendering.

SSai Kaushik Ganji