Untitled

100%

✓ Published1🌍 Public

Last edited Oct 15, 2020

Created on Oct 14, 2020

This visualization displays a parallel coordinates plot of automobile data from the cars.csv file, with each line representing a car and each vertical axis a numeric attribute such as economy, horsepower, or weight. The axes can be dragged to reorder dimensions, and brushing on an axis filters the foreground lines to highlight cars matching the selected range. The implementation uses D3 v3 with d3.svg.line for paths, d3.svg.axis for scales, and d3.svg.brush for interactive filtering, rendered as animated SVG.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

Untitled

This interactive parallel coordinates chart visualizes a dataset of cars and their specifications, such as fuel economy, horsepower, and weight. Each car is represented by a line connecting its attribute values across multiple vertical axes. Users can drag axes to reorder them and use brush controls on each axis to filter which vehicles remain highlighted, with the background context paths hidden while dragging. The visualization is built with D3.js v3, using SVG for rendering, `d3.svg.axis` for axes, and `d3.behavior.drag` and `d3.svg.brush` for interaction.

QqOp3

92% match

Loading thumbnail…

Untitled

This interactive parallel coordinates plot uses the D3.js v3 library to visualize a dataset of car characteristics, including fuel economy, engine displacement, power, weight, and acceleration. The SVG rendering shows each car as a polyline crossing multiple vertical axes, with steelblue foreground lines for focus and grey lines for background context. Users can drag the axis labels to reorder the dimensions and use the built-in brush component on each axis to filter the displayed cars dynamically, updating the foreground paths in real time.

Eeugene-gilmore

91% match

Loading thumbnail…

Parallel Coordinates

This interactive parallel coordinates visualization displays automotive data for cars from the 1970s and 1980s. Users can click and drag along any axis to brush and filter the dataset, or drag axis labels to reorder dimensions. Built with D3 v3, the SVG rendering uses `d3.svg.axis`, `d3.svg.line`, `d3.behavior.drag`, and `d3.svg.brush` to support filtering and dynamic reordering. The cars.csv dataset includes attributes like economy, cylinders, horsepower, and weight.

Mmbostock

88% match

Loading thumbnail…

Parallel Coordinates

This parallel coordinates visualization displays automotive data from the 1970s and 1980s, with each car represented as a line across seven dimensions such as fuel economy, horsepower, and weight. Users can drag axes to reorder dimensions and brush along an axis to filter which cars remain visible. Built with D3 v3, it uses `d3.svg.brush` for interactive filtering, `d3.svg.axis` for scales, and `d3.behavior.drag` to reposition axes. The SVG renders both background and foreground paths, with foreground lines dynamically hidden based on brush extents.

深深度碎片

87% match

Loading thumbnail…

Parallel Coordinates

This parallel coordinates visualization displays automotive data from the 1970s and 1980s, with each car represented as a polyline crossing seven axes for metrics like economy, cylinders, power, and weight. Using D3 v3, the SVG-based chart renders gray background lines for all cars and steelblue foreground lines that filter interactively. A d3.svg.brush component on each axis allows users to drag and select ranges along a dimension, dynamically hiding lines that fall outside the brushed extent. The code loads car data from a CSV file and applies linear scales with d3.scale.linear for normalization.

Mmbostock

87% match

Loading thumbnail…

Parallel Coordinates

This parallel coordinates visualization displays data for cars from the 1970s and 1980s from a CSV file, mapping each car as a polyline across vertical axes representing dimensions such as economy, cylinders, displacement, power, weight, and acceleration. The visualization allows users to interactively reorder axes and brush along any dimension to filter the dataset. Built with D3 v3, it uses `d3.svg.line()`, `d3.svg.axis()`, and `d3.svg.brush()` for rendering and interaction, with SVG paths for the background and foreground lines.

115Dkatz

86% match

Loading thumbnail…

Parallel Coordinates

This parallel coordinates visualization displays multivariate data from a cars dataset recorded in CSV format, with each row represented as a path crossing multiple vertical axes. Users can drag axes to reorder dimensions and brush along them to filter highlighted foreground lines, while gray background lines provide context. Built with D3 v3, the example uses SVG rendering, ordinal and linear scales, `d3.svg.axis`, `d3.svg.line`, `d3.behavior.drag`, and `d3.svg.brush`. Axes reorder smoothly with transitions, and brushing toggles focus based on selected extents.

BBBischof

85% match

Loading thumbnail…

Untitled

This example displays a scatterplot of automobile data, plotting engine horsepower against vehicle weight. Each point represents a car, with axes labeled clearly and a title reading "Bar chart of population." The visualization uses D3 v5 to load CSV data from an auto-mpg dataset, applying linear scales, axes with tick marks, and SVG circles for rendering. The code demonstrates axis customization, including rotated tick labels and grid lines with negative tick sizes.

AAbishek-Dulal

85% match