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Fork of Activity 6

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Bbhargavipagolu2025@gmail.com
Last edited Oct 30, 2025
Created on Oct 30, 2025

This scatter plot visualizes the Iris dataset, plotting sepal length against petal length and distinguishing species by shape. The visualization uses D3 v7's `scaleLinear` for axes, `scaleOrdinal` with `symbolsFill` for shape encoding, and a custom legend. Data is loaded asynchronously via `fetch` and parsed with `csvParse`, with numeric fields converted to numbers. The plot renders using SVG `path` marks positioned by D3 scales.

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Fork of Activity 6_task 3.2

This scatter plot visualizes the Iris dataset, showing sepal length against petal length with points colored by species. The chart uses D3 v7’s `scaleLinear` for axes, `scaleOrdinal` with `symbolsFill` to assign distinct shapes to each species, and a custom legend to map shapes to species names. Data is loaded from a remote CSV via `fetch` and parsed with `d3.csvParse`, with numeric fields coerced to numbers. The visualization updates reactively through a simple state management pattern, re-rendering the SVG on data arrival.

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This scatter plot visualizes the Iris dataset, plotting sepal length against petal length while encoding species by shape. Using D3 v7, it creates a linear x- and y-axis, with a custom shape legend explaining the species mapping. The implementation leverages D3’s `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbol` APIs to render the marks and legend. Data is loaded from a remote CSV, parsed with `csvParse`, and mapped to numeric fields before being passed to the plot.

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This scatter plot visualizes the Iris dataset, mapping sepal length against petal length and using distinct shapes to represent different iris species. The visualization loads data from a CSV file and displays it using D3 v7, leveraging the `scaleLinear` and `scaleOrdinal` scales to map data values to plot coordinates and shape encodings. Custom axis and legend modules render labeled axes and a shape legend, while the `symbol` API generates the species-specific markers. The plot dynamically fetches and parses the data via `csvParse`, updating the display once the dataset arrives.

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This scatter plot visualizes the Iris dataset, showing sepal length against petal length, with species distinguished by different d3 symbol shapes. A shape legend identifies the three species categories, while labeled axes display the quantitative measurements. Built with D3 v7, the visualization uses modular JavaScript functions including `scaleLinear`, `scaleOrdinal`, `symbolGenerator`, and custom axis and legend components. The data is loaded asynchronously from a remote CSV file and parsed using `csvParse`, with the plot rendering across the full browser window.

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Activity 6

This scatter plot visualizes the Iris dataset, showing sepal length against petal length, with points colored and shaped according to species. The visualization uses D3 v7’s `scaleLinear`, `scaleOrdinal`, `symbol` generator, and custom `axes` and `shapeLegend` modules to render the chart and its legend. Data is fetched from a raw CSV file on GitHub and parsed with `csvParse`. The plot updates responsively to the browser window size and includes labeled axes and a legend showing the three species categories.

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Fork of Activity_6_3-2

This interactive scatter plot displays the Iris dataset, showing sepal length against petal length, with each flower species distinguished by a unique symbol shape (circles, triangles, and diamonds) and a corresponding legend. Using D3 v7, the visualization implements a modular architecture with separate axes, shape legend, and scatter plot components. The code leverages D3 scales (scaleLinear, scaleOrdinal), symbol generators from d3-shape, and data-join patterns to render markers and update the visualization. Iris data is loaded asynchronously from a CSV file, parsed with d3.csvParse, and numeric fields are converted before rendering.

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This scatter plot visualizes the Iris dataset, mapping sepal length and petal length on the x- and y-axes, with species encoded by point shape. It uses D3 v7's `scaleLinear`, `scaleOrdinal`, and `symbolsFill` to create the visualization, rendering SVG paths via `symbol()`. Data loads from a CSV via `csvParse`, with axes and a shape legend generated using `axisLeft`, `axisBottom`, and custom legend code.

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This visualization displays the Iris dataset as a scatter plot, mapping sepal length on the x-axis and petal length on the y-axis, with points colored and shaped by species. It includes a custom shape legend for the three species. The implementation uses D3 v7 modules like `scaleLinear`, `scaleOrdinal`, and `symbol` to generate marks, while `axisLeft` and `axisBottom` handle the axes. Data is loaded asynchronously via `fetch` and parsed with `csvParse` from a GitHub-hosted CSV file. The chart is rendered into an SVG that fills the viewport.

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