Activity6-Task 3.2

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Activity6-Task 3.2

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Last edited Apr 6, 2025

Created on Apr 6, 2025

This scatter plot visualizes the Iris dataset, showing petal length against sepal length, with each point’s shape encoding the flower species (setosa, versicolor, virginica). The plot uses D3’s `scaleLinear` for axes and `scaleOrdinal` with `symbolCircle`, `symbolCross`, and `symbolDiamond` to differentiate species. A custom `shapeLegend` displays these symbols, while the axes are labeled via `axisBottom` and `axisLeft`. Data is loaded from a remote CSV.

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Activity6_task3.2

This scatter plot visualizes the Iris dataset, showing petal length against sepal length for three species of iris flowers. Each species is represented by a distinct shape and color: circles for setosa, squares for versicolor, and triangles for virginica. The visualization uses D3 v6 with SVG rendering, employing `d3.scaleLinear` for axes, custom symbol generators from `d3.symbol`, and a legend built with `d3.symbolCircle`, `d3.symbolSquare`, and `d3.symbolTriangle`. Data is loaded from an external CSV file, and axes are labeled with "Sepal Length" and "Petal Length" in centimeters.

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This scatter plot visualizes the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis while encoding the species of each flower using different d3.symbol shapes (from symbolsFill). The legend, built with a custom shapeLegend function, lists species and their corresponding markers. The visualization uses D3 v7's scaleLinear for axes, scaleOrdinal for shape mapping, and d3.axisLeft/axisBottom for rendering the chart, with data loaded asynchronously from a CSV file via fetch and d3.csvParse.

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This scatter plot visualizes the Iris dataset, showing sepal length against petal length, with each species represented by a distinct symbol shape. The plot encodes the three Iris species through shape, using d3.scaleOrdinal with symbolsFill to assign different geometric marks, while a custom legend explains the species mapping. Axes are rendered via d3.axisLeft and d3.axisBottom, with labels for both dimensions. The data is loaded asynchronously from a GitHub-hosted CSV file using d3.csvParse, and the visualization updates through a state management pattern that handles loading and rendering.

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