Skip to main content
SimilarExport ZIP
100%

Data Visualization Homework 2: Parallel Coordinate Plots

✓ Published4🌍 Public
Dderrick373519@gmail.com
Last edited Oct 6, 2023
Created on Sep 27, 2023

This parallel coordinate plot visualizes the classic Iris dataset, displaying four morphological measurements for three flower species. Each observation appears as a semi-transparent polyline crossing the vertical axes, with color encoding the species classification via a categorical color scale. The visualization supports interactive reordering by dragging axis headers, which triggers animated transitions repositioning the axes. Built with D3 v5, the implementation uses `d3.scaleLinear` for value mapping, `d3.scaleOrdinal` for color assignment, and `d3.line` for generating the polylines from the CSV data.

AI-generated description
MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Data Visualization Homework 2: Parallel Coordinate Plots

This interactive parallel coordinate plot visualizes the Iris flower dataset, showing measurements of sepal and petal length and width for three species. Using D3.js v5, it renders semi-transparent polylines colored by species class, with draggable vertical axes that can be reordered by the user. The chart employs D3's `scaleLinear` and `scalePoint` for mapping data, `drag` events for interactive axis manipulation, and a `colorLegend` to identify species. Data is loaded from the local `iris.csv` file.

EErfan Moeini
91% match
Loading thumbnail…

Iris Parallel Coordinate Plot

This visualization displays the classic Iris dataset as an interactive parallel coordinate plot, with each flower’s four measurements (sepal and petal length and width) connected as a colored polyline. Lines are colored by species using a scaleOrdinal mapping, and a side legend identifies the three classes. Using d3.csv to load data and d3.line to generate paths, users can drag any of the four axes horizontally to reorder dimensions, with d3.drag updating axis positions and sorting the column domain, followed by smooth transitions that animate the paths into their new arrangement.

Jjasonlovechu
90% match
Loading thumbnail…

Parallel Coordinate Plot

This interactive parallel coordinate plot visualizes the classic Iris dataset, showing how each flower’s sepal and petal measurements vary across three species. Users can drag any vertical axis horizontally to reorder the dimensions, with all connecting polylines smoothly updating via D3 transitions. The visualization uses D3 v5’s `scaleLinear`, `scaleOrdinal`, and `scalePoint` for positioning, while axes are rendered with `axisLeft` and drag behavior is implemented through `d3.drag()`. Data is loaded from a CSV file and plotted as semi-transparent SVG paths colored by species.

Ddaniel
89% match
Loading thumbnail…

Iris Parallel Corrdinate Plots

This example visualizes the classic Iris dataset using parallel coordinate plots, showing four flower measurements across vertical axes with polylines colored by species. Users can hover over lines to highlight all flowers of the same class while dimming others, or drag axis labels to reorder dimensions. The implementation uses d3.csv for data loading, d3.scaleLinear and d3.scalePoint for scales, d3.line for path generation, d3.axisLeft for axes, and d3.drag for interactive axis repositioning. Transitions animate the line redrawing during drag operations.

Sshialian
89% match
Loading thumbnail…

Parallel Coordinate Plots

This parallel coordinate plot visualizes the Iris flower dataset, displaying four morphological attributes (sepal length, sepal width, petal length, and petal width) for three species of iris. Each sample is represented as a polyline connecting its attribute values across parallel axes, with lines colored by species (setosa, versicolor, and virginica) using a D3 ordinal color scale. The visualization uses D3 v7 with an SVG rendering approach, employing native `d3.axisLeft` and `d3.line` APIs for constructing the axes and polylines. An interactive dropdown menu allows users to reorder the four axes, triggering a redraw of both the vertical axes and the connecting lines via a custom `redrawParallelCoordinates` function. The data is loaded from an external CSV file using `d3.csv`.

Hhuangweijie0310102@gmail.com
89% match
Loading thumbnail…

Iris Parallel Coordinate Plots

This visualization uses parallel coordinate plots to display the classic Iris flower dataset, with each of the 150 samples represented as a polyline across four axes: sepal length, sepal width, petal length, and petal width. The three Iris species are color-coded—red for setosa, green for versicolor, and blue for virginica—making species separation patterns visible. Built with D3 v3, the code uses `d3.svg.line`, `d3.svg.axis`, and an ordinal scale for axis positioning. Users can drag any axis title to reorder dimensions, which triggers a smooth 100-millisecond transition as the lines redraw. The data is loaded from a CSV file using `d3.csv`.

TTzuTing112200
89% match
Loading thumbnail…

Iris Parallel Coordinate Plots

This interactive visualization displays the classic Iris dataset through parallel coordinate plots, with each flower’s sepal and petal measurements drawn as a polyline across four vertical axes. The paths are colored by species, and hovering over a line highlights all specimens of that species while dimming the rest. Users can drag any axis horizontally to reorder the dimensions, which dynamically repositions the axes and rescales the connecting lines. Built with D3 v5, it uses scales, axes, and line generators, along with drag behavior and transitions to animate the reordering and highlighting effects.

Ccindy203cc
89% match
Loading thumbnail…

Iris Parallel Coordinate Plot

This interactive parallel coordinate plot visualizes the classic Iris dataset, showing four measured features (sepal and petal length/width) across three flower species. Each polyline represents one flower, with colors mapped to species via d3.scaleOrdinal and schemeCategory10. Users can drag the vertical axes to reorder dimensions, triggering smooth transitions with d3.transition(). The visualization uses d3.scalePoint for categorical axis positioning, d3.scaleLinear for value mapping, and axisLeft/axisBottom to render tick marks with SVG.

WWei-Che Chang
89% match