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activity_6_task3_questions

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HHarinathChakali33@gmail.com
Last edited Apr 11, 2024
Created on Apr 11, 2024
Forked from Hello VizHub

This example shows a scatter plot of iris flower measurements, mapping sepal length on the x-axis and petal length on the y-axis, with species encoded by symbol shapes and a legend. The visualization is built using D3 v7, employing `scaleLinear` for axes, `scaleOrdinal` with `symbolsFill` for shape encoding, and `symbolGenerator` to render marks. Data is loaded asynchronously from a CSV file via `csvParse`, and the chart includes custom axes and shape legend modules. The rendering updates when the window resizes.

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activity 6 Task 3 question

This example displays a scatter plot of iris flower measurements, plotting sepal length against petal length while encoding species through distinct symbol shapes. The visualization loads CSV data from a GitHub gist and parses it with `d3.csvParse`. It uses `d3.scaleLinear` for both axes, `d3.scaleOrdinal` with `d3.symbolsFill` for shape encoding, and `d3.axisLeft` and `d3.axisBottom` for axes. A custom legend, built with `d3.symbol`, shows the mapping between species and symbol types.

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Activity6_task3.2

This example shows a scatter plot of Iris flower measurements, mapping sepal length on the x-axis and petal length on the y-axis, with different symbol shapes representing species. The visualization also includes a custom shape legend identifying each species. The code uses d3.csvParse and d3.fetch to load a CSV dataset, then d3.scaleLinear for axes and d3.scaleOrdinal with d3.symbolsFill to assign distinct geometric markers. Axes are rendered via the d3.axisLeft and d3.axisBottom APIs, while a custom legend module draws symbols and text ticks.

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Activity6_task3.2

This example displays a scatter plot of iris flower measurements, mapping sepal length to the x-axis and petal length to the y-axis. Each species is distinguished by a different symbol shape, with a legend identifying the species categories. The visualization is built using D3 v7, employing `scaleLinear` for positioning, `scaleOrdinal` for shape encoding, and `symbolGenerator` to render distinct markers. Data is loaded asynchronously from a remote CSV file and parsed using `csvParse`.

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Activity6_Task3.2

This example shows an interactive scatter plot of iris flower measurements, mapping sepal length against petal length with species indicated by different symbol shapes. The visualization uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, `symbol`, and `axisLeft`/`axisBottom` to construct the plot and its legend. Data is loaded asynchronously from a remote CSV file using `csvParse` and fetched via the Fetch API, with numeric fields coerced to numbers. The chart displays three shapes from `symbolsFill`, with axes labeled and a custom shape legend positioned within the SVG.

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Activity6_Question3

This scatter plot visualizes the Iris flower dataset, mapping sepal length on the x-axis and petal length on the y-axis, with three species distinguished by distinct symbol shapes. It loads data from a remote CSV, parses it with `d3.csvParse`, and renders marks using `d3.scaleLinear`, `d3.scaleOrdinal`, and the `symbol` generator. The chart includes labeled axes via custom D3 axes modules and a shape legend, all built with D3 v7 selections and joins.

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Activity6_task 3 .2

This example displays a scatter plot of Iris flower measurements, showing sepal length against petal length for three species. The visualization uses distinct symbols for each species, with a shape legend positioned in the upper right corner to identify the categories. Built with D3 v7, the code imports specific modules such as `scaleLinear`, `scaleOrdinal`, `symbol`, and `symbolsFill` for scaling and symbol generation. The plot loads data from a CSV file hosted on GitHub, parsing it with `csvParse` and converting numeric fields before rendering. Axes and labels are created using reusable axis functions.

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This example shows a scatter plot of iris flower measurements, mapping sepal length to the x-axis, petal length to the y-axis, and encoding species with different symbol shapes. The visualization includes labeled axes generated with `d3.axisLeft` and `d3.axisBottom`, plus a custom shape legend built from `d3.symbol` with `symbolsFill`. Data loads asynchronously from a CSV file via `d3.csvParse`, and the plot uses `d3.scaleLinear` and `d3.scaleOrdinal`, with marks rendered as SVG paths via `symbolGenerator`.

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This example shows a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with the three flower species distinguished by different symbol shapes (circles, crosses, and diamonds) via a shape legend. The visualization is built with D3 v7, using `scaleLinear`, `scaleOrdinal`, `symbol`, and `symbolsFill` to position and style the marks. It fetches the CSV data from a GitHub repository and renders it in an SVG sized to the window. A modular structure separates the axes, legend, and plot logic into reusable functions.

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