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Task 9&10 Q2

This visualization displays the Iris dataset, showing the sepal and petal measurements for each of the three iris species. Four overlapping area charts are rendered as SVG paths, each filled with a different color to represent the sepal length, sepal width, petal length, and petal width. The visualization uses d3.area to construct the paths, with xScale and yScale from d3.scaleBand and d3.scaleLinear respectively. The data is loaded from a remote CSV file via d3.csv. A legend and axis labels are included for clarity.

Task 9&10 Q1

Task 9&10

Q4

Q3

Q2

This stacked horizontal bar chart displays the average values for horsepower, torque, and highway MPG across 27 car manufacturers. The chart uses D3 v7’s `d3.stack` and `d3.scaleOrdinal` to segment each manufacturer’s bar into three colored sections, with a legend identifying each attribute. Data is loaded from a local CSV file and rendered as SVG. The horizontal axis is scaled linearly, while the vertical axis lists car makes, with axis labels rotated for readability.

Question1(2)

Question 1

This chart displays the populations of ten countries in the year 2000, sorted vertically with horizontal bars whose lengths represent population values. The visualization uses React to render SVG elements, with D3 scales and format utilities, specifically `scaleBand` for the categorical y-axis and `scaleLinear` for the numeric x-axis. Data is loaded from a CSV source and processed before display. Axis labels and tick marks are generated via custom React components, with population values formatted in billions using the `format('.2s')` API.

Activity 6

Activity6_Task4

Activity6_Task3.2

This example visualizes the Iris dataset as a scatter plot of sepal length against petal length, with the three species distinguished by different symbol shapes. A shape legend identifies each species, and the plot includes styled axes with labels. The visualization is built using D3 v7, employing `scaleLinear` for the x and y scales, `scaleOrdinal` with `symbolsFill` for the shapes, and the `csvParse` method to load data from a GitHub-hosted CSV file. The `axes` and `shapeLegend` modules handle the axis and legend rendering.

Activity6_Task3

Activity6_Task2

A stacked bar chart shows the percentage distribution of IMDb ratings across six movie genres, with each bar divided into five rating intervals from "below 5.0" to "above 8.5." The visualization uses d3.stack() to aggregate the data, d3.scaleBand() for the categorical genre axis, and d3.scaleLinear() for the percentage axis. Hovering over a segment displays a tooltip with the exact percentage via d3.select and mouse events. The SVG rendering applies a color scale with five distinct hues and reads data from a CSV file.

5 Buddhas

5 Buddhas is a generative visualization that arranges thousands of small rotated polygons in a five-by-five grid, with each cell repeating the same noisy, abstract pattern to form a larger symmetrical mosaic. The SVG is rendered with React, using nested array maps to create hundreds of semi-transparent triangles whose positions, sizes, and colors are randomly computed — producing a vibrant, kaleidoscopic effect. Overlaid at the center is a single orange Buddhist figure in profile, drawn from path data, which anchors the chaotic color field with a recognizable silhouette. The piece merges algorithmic noise with a sacred icon, creating a tension between chance and intention.