Activity6_Task3.2

Bbudalavijay2001@gmail.com

Activity6_Task3.1

This example shows an interactive scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with each species represented by a distinct symbol shape. The visualization uses D3.js v7 APIs including `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbolGenerator` to render the marks, while a custom shape legend displays the species categories. Data is loaded asynchronously from a GitHub-hosted CSV file using `fetch` and parsed with `csvParse`, with numerical fields coerced to numbers before plotting. The chart includes labeled axes and a legend, all rendered within an SVG canvas sized to the full viewport.

Activity 6_Task3.2

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.

SSiva Kishore Reddy

RRJVENKATESH789@GMAIL.COM

Activity6_task3.2

This example shows a scatter plot of the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with species indicated by different symbols and a legend. The visualization loads the data from a GitHub CSV file, parses it with `d3.csvParse`, and uses D3 v7’s `d3.scaleLinear`, `d3.scaleOrdinal`, `d3.symbolsFill`, and `d3.axisBottom`/`d3.axisLeft` for scales and axes. The code employs a `join`-based declarative grammar to build SVG elements, with a custom `shapeLegend` for symbol encoding. The plot adapts to the window size and updates dynamically as data loads.

Rrakshithareddy217@gmail.com

Activity6_Task3.2

This example demonstrates a scatter plot of the classic Iris dataset, showing sepal length against petal length, with each point’s shape indicating its species. It uses D3 v7 with the `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbol` APIs to create the plot and a custom shape legend. The visualization loads the CSV data via a remote URL, parses it with `csvParse`, and renders the chart using an SVG canvas. The code organizes chart components into local ES6 modules for axes, scatter plot, and legend, imported through `import` statements.

Vvarshithainaganti@gmail.com

Activity6_Task3.2

This example shows a scatter plot of the Iris dataset, mapping sepal length and petal length along the x- and y-axes. It uses D3 v7 to load and parse the data via `csvParse`, and renders marks with `scaleLinear` and an ordinal shape scale using the symbols from `symbolsFill`. A custom legend displays the three species categories. The visualization is drawn in an SVG container sized to the window, with axes and labels generated by custom `axes` and `shapeLegend` modules.

Ssasidhharreddy@gmail.com

Activity6_Task3.2

This example demonstrates a scatter plot of the Iris dataset, encoding sepal length and petal length on the x- and y-axes while using distinct symbol shapes to represent species. The visualization loads CSV data from a remote source, parses it with `d3.csvParse`, and renders marks using the `symbol` generator from D3 v7. A custom legend built with D3's `scaleOrdinal` and `symbolsFill` maps species names to shapes, with axes created via `axisLeft` and `axisBottom`. The code is modularized into local ES6 modules for the scatter plot, axes, and legend.

Activity6_Task3.2

This example demonstrates a scatter plot of the Iris dataset, encoding sepal length on the x-axis, petal length on the y-axis, and species as symbol shapes (circles, triangles, and squares) with a custom legend. It uses d3.scaleLinear for axes, d3.scaleOrdinal with d3.symbolsFill for shape mapping, and d3.axisLeft/axisBottom via a reusable axes module. The data loads asynchronously as CSV from a GitHub repository and is parsed with d3.csvParse. The visualization builds its SVG using d3.select and join patterns, with local ES6 modules for modular structure.

DDeekshitha Annreddy

Kkrishnavisheshkatta@my.unt.edu

Activity6_Task3.2

This example displays a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with species encoded by distinct symbols and a corresponding legend. It uses D3 v7’s `scaleLinear`, `scaleOrdinal`, and `symbol` APIs to position marks and generate shapes. Data is loaded from a remote CSV via `csvParse` and fetched asynchronously. The visualization also demonstrates modular ES6 imports for reusable axis and legend components.