Iris_Parallel_Coor_P

Iris_Parallel_Coor_P

This parallel coordinate plot uses D3 v6 within a React framework to visualize the classic Iris dataset. It displays four measured attributes (sepal and petal length and width) as vertical axes, with each iris flower represented as a colored line connecting its values. The lines are colored by species using `scaleOrdinal`, and hovering over a line highlights that flower while dimming all others. The visualization includes axis labels, a legend, and uses SVG paths generated via `line()` and `scalePoint` for layout.

Iris_Parallel_Coor_P

Iris_Parallel_Coor_P

This interactive visualization presents the classic Iris dataset as a parallel coordinate plot, with each of the 150 flowers represented as a colored line traversing four parallel axes for sepal and petal lengths and widths. D3.js v6 constructs the chart using `scaleLinear`, `scalePoint`, and `line`, while the React dropdown library loads the dataset. The legend circles classify the three Iris species. Users can hover over any line to highlight all flowers of that class while dimming the others, revealing clustering patterns across the four dimensions.

Pplchao

Iris parallel coordinate plot

This visualization displays the classic Iris dataset as an interactive parallel coordinate plot, using D3.js v4. Each polyline represents a flower sample, colored red, green, or blue according to its species. The four axes correspond to sepal and petal length and width. Users can click and drag axis labels to reorder the dimensions, which triggers a dynamic swap of axes and updates the paths via the `d3.drag` and `path` functions. Hovering over any line highlights all flowers of that species while dimming others, using CSS transitions.

Ddrean205287

Iris Parallel Coordinate Plot_hw2

This interactive parallel coordinate plot visualizes the Iris dataset, displaying four measured attributes (sepal length, sepal width, petal length, petal width) as parallel axes with colored polylines representing three Iris species. Users can click and drag axis labels to reorder the dimensions, with lines smoothly animating to their new positions. The visualization is built with d3.v5, using `scalePoint` and `scaleLinear` for positioning, `axisLeft` for tick marks, and the `drag` interaction module to handle axis movement. Data is loaded from a CSV file via `d3.csv`, and the SVG rendering includes a legend identifying each species by color.

JJuliachien

Iris parallel coordinate plot ref 3

This interactive parallel coordinate plot visualizes the Iris dataset, with each line representing a flower and colored by species (setosa, versicolor, virginica). Users can hover over lines to highlight a selected species while dimming others, and drag the axis titles to reorder dimensions. Built with D3 v4, it uses `d3.scaleLinear`, `d3.scalePoint`, `d3.axisLeft`, and `d3.drag` to handle axis repositioning, while `d3.line` generates the polylines. The SVG rendering includes static axis labels and color-coded legend swatches.

Iris Parallel Coordinate Plots

This interactive parallel coordinate plot visualizes the Iris flower dataset, displaying four measurements (sepal length, sepal width, petal length, petal width) as vertical axes with polylines colored by species. Users can drag any axis to reorder the dimensions, which immediately redraws the paths and scales. Built with D3 v4 (d3.scaleLinear, d3.scalePoint, d3.axisLeft, d3.drag), the SVG rendering uses data from iris.csv, with distinct colors for Iris-setosa, Iris-versicolor, and Iris-virginica.

Wwusushi

Iris Parallel Coordinate Plots ref 4

This parallel coordinate plot visualizes the Iris flower dataset, with each line representing a sample and colored by species using a d3.scaleOrdinal. The code uses d3.scaleLinear and d3.scalePoint to position axes for sepal and petal measurements. Users can drag any axis to reorder the dimensions, triggering an event handler that removes and redraws the paths. The SVG rendering relies on d3.axisLeft for axis ticks and labels, with data loaded from the iris.csv file using d3.csv.