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Fork of Iris Dataset Scatter Plot

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SSnigdha6698
Last edited Mar 6, 2022
Created on Mar 6, 2022

This scatter plot visualizes the Iris Dataset, mapping petal length and width to the x- and y-axes while coloring each point by species (setosa, versicolor, virginica). Circles are rendered using D3 v6’s `scaleLinear`, `axisLeft`, and `axisBottom` APIs, with the sepal measurements stored as unused `rx` and `ry` attributes. The SVG fills the window, and data is loaded asynchronously via `d3.csv` from a GitHub gist. The view includes 24-pixel tick labels and no interactivity.

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A vanilla HTML implementation of a D3 scatter plot. Shows the Iris Dataset.

MIT Licensed

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Fork of Iris Dataset Scatter Plot

This scatter plot visualizes the Iris Dataset, mapping petal length and width as x and y coordinates while coloring each point by species (setosa, versicolor, or virginica). It also stores sepal measurements as data attributes on each circle, though these are not used for positioning. The implementation uses D3 v6 APIs including `csv`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to load data, scale axes, and render an SVG with circles. Data is fetched from a GitHub Gist, and the viewport fills the browser window.

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This scatter plot visualizes the Iris Dataset, mapping petal length on the x-axis and petal width on the y-axis. Each point is colored by species (setosa, versicolor, or virginica), though the code also loads sepal dimensions without displaying them. Built with D3 v6, it uses `d3.csv` to load data, `scaleLinear` for axes, and `axisLeft`/`axisBottom` for tick marks. Circles are rendered as SVG elements with `selectAll` and `join`, with axis labels added via SVG text elements.

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This scatter plot visualizes the Iris Dataset, mapping petal length and petal width on the x- and y-axes while coloring each point by species (setosa, versicolor, or virginica). The SVG rendering uses D3 v6 APIs including `csv`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom`. Though the circles include `rx` and `ry` attributes, the visual output remains circular with a fixed radius. Data loads from a GitHub-hosted CSV, and the chart fills the browser window with no explicit legend, relying on orange, purple, and green markers to distinguish species.

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