HW2_move2

DV_HW2

This interactive parallel coordinate plot visualizes the Iris dataset, with each of the 150 flowers represented as a polyline spanning four axes: sepal length, sepal width, petal length, and petal width. Lines are colored by class (setosa, versicolor, virginica) and rendered as semi-transparent SVG paths with a 0.35 opacity. Users can drag any axis horizontally to reorder the dimensions, using d3.drag and d3.line to update paths and axis positions dynamically. A legend identifies the three classes, and axis labels are added via d3.axisLeft.

93% match

HW2_move1

This example presents an interactive parallel coordinate plot for the Iris dataset, showing four measured attributes (sepal length, sepal width, petal length, petal width) across three flower species. Each polyline is colored by species using a scaleOrdinal mapping. Users can drag any vertical axis to reorder the dimensions; the lines and axes update live via d3.drag, while a smooth transition after release repositions everything to their new sorted order. The visualization uses D3 v5 with SVG rendering, scalePoint and scaleLinear for axes, and a legend highlighting species colors.

92% match

HW2

This interactive parallel coordinate plot visualizes the Iris dataset, with each flower represented as a polyline connecting measurement values across four axes: sepal length, sepal width, petal length, and petal width. Lines are color-coded by species, and each axis includes its own scale and label. Using d3.drag, users can reposition the axes horizontally to reorder dimensions, which dynamically reshapes the polylines in response to the new axis placements. The visualization is rendered as SVG, with d3.scalePoint, d3.scaleLinear, and d3.line used to construct the plot.

Yyujun12689

91% match

0616027_hw2

This interactive parallel coordinates plot visualizes the Iris dataset, with each polyline representing a flower sample and colored by species (setosa, versicolor, virginica). The chart shows four dimensions—sepal length, sepal width, petal length, and petal width—on vertical axes. Users can drag axes to reorder dimensions and brush along any axis to filter which lines remain visible. Built with D3 v3 in a React framework, it uses `d3.svg.axis`, `d3.svg.line`, `d3.behavior.drag`, and `d3.svg.brush` to enable these interactions, rendering polylines as SVG paths with animated transitions during axis dragging.

Yyixinxu2020

HW2 v2

This interactive parallel coordinate plot visualizes the Iris dataset, with each polyline representing a flower and color-coded by species. Users can drag the four axes (sepal length, sepal width, petal length, petal width) horizontally to reorder dimensions, with smooth transitions animating the paths and axes into their new positions. The visualization is built using React and D3 v5, leveraging `scalePoint`, `scaleLinear`, `axisLeft`, and `line` for rendering, while `drag` and `event` handle the interaction. A legend and side panel identify the three species, and the SVG output includes hover cursors and opacity styling for the polylines.

Nnathanowen06

HW2_example

This interactive parallel coordinate plot visualizes the Iris dataset, displaying 150 samples across four dimensions: sepal length, sepal width, petal length, and petal width. Each polyline represents a single flower, color-coded by species (setosa, versicolor, virginica) using a fixed color map. Users can drag the vertical axes to reorder dimensions, dynamically updating the line paths and axis positions with smooth transitions. Built with D3 v5 and React, the visualization uses `select`, `scalePoint`, `scaleLinear`, `line`, and `drag` APIs to render SVG paths and support the reordering interaction.

HW2_move1

This interactive parallel coordinate plot visualizes the Iris dataset, showing four measured attributes for three flower species. Users can drag any vertical axis horizontally to reorder the dimensions, with all data lines smoothly animating to reflect the new arrangement. Built with D3 v5 in React, the visualization uses SVG paths with `d3.line` and `d3.scalePoint`, while drag interactions rely on the `d3.drag` behavior. The axes re-sort via `d3.scalePoint` domain updates, and transitions use D3’s `transition` method for animated re-rendering.

hw2

This interactive parallel coordinate plot visualizes the Iris dataset, displaying four measured features for three flower species. Users can drag any vertical axis horizontally to reorder the dimensions, and the polyline paths connecting each flower’s measurements update in real time. The visualization uses d3.scalePoint for axis positioning, d3.drag for interactivity, and d3.line for path generation, with data loaded from a remote CSV. Axes are labeled, and a color-coded legend distinguishes the three Iris species.

Yyujun12689