Activity6_Task 3.2

Llikhitha.sarahah01@gmail.com

Activity6_Task3.2

This example demonstrates a scatter plot of the Iris dataset, mapping sepal length against petal length and distinguishing species by shape. It loads data from a CSV file and uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `csvParse`. The visualization includes custom axes and a shape legend, built with reusable local ES6 modules.

Activity6_Task3.2

This example builds an interactive scatter plot of the Iris dataset, showing sepal length against petal length with points shaped by species. It loads data via `fetch` and `csvParse` from D3, then uses `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbol` to map values to positions and shapes. The visualization includes custom axis labels and a shape legend, all rendered with D3 v7 selections and data joins, with layout sized to the viewport.

Nnikhithadadi@my.unt.edu

Activity 6_Task 3.2

This interactive scatter plot visualizes the Iris dataset, mapping sepal length against petal length. Each point is colored and shaped by species, with a custom legend explaining the symbols. The visualization uses D3 version 7, employing the `symbol()` API from `d3` to generate distinct mark shapes, `scaleLinear` for axes, and `scaleOrdinal` for the categorical species mapping. Data is loaded from a remote GitHub CSV file and parsed with `csvParse`. The chart is rendered using an SVG canvas.

Mmsnikhil2608@gmail.com

Gguttavenkata745@gmail.com

Activity6_Task3.2

This example demonstrates a scatter plot of the Iris dataset, showing sepal length versus petal length with different point shapes representing species. The visualization loads data from a GitHub-hosted CSV file, parses it with `d3.csvParse`, and renders points using D3 v7's `scaleLinear`, `scaleOrdinal`, and `symbol` generators. A custom shape legend, implemented as an ES6 module, displays the three species with matching symbols. Axes are drawn using `axisLeft` and `axisBottom`, with labels positioned via D3 selection methods.

Kkowshiksamudrala08@gmail.com

Activity6_Task3-2

This scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with species encoded by different symbol shapes. The visualization loads the data from a remote CSV file using `d3.csvParse` and renders it using D3 v7. It employs `scaleLinear` for axes, `scaleOrdinal` for shape mapping, and `axisLeft`/`axisBottom` for tick marks. A custom shape legend, built with `d3.symbol`, displays the species labels.

Bbudalavijay2001@gmail.com

Activity6_Task3.2

This example displays a scatter plot of the Iris dataset, showing sepal length against petal length with points colored and shaped by species. It loads the CSV from a GitHub repository using `d3.csvParse`. The visualization uses D3 v7 scales including `scaleLinear` and `scaleOrdinal` with `symbolsFill` to differentiate species, while a custom legend built with `symbolGenerator` lists the categories. Axes are generated via `axisLeft` and `axisBottom` with explicit labels for each measurement.

Kkeerthana11.mcs@gmail.com

Activity6_Task3.2

This example presents a scatter plot of the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, while using different marker shapes to distinguish the three flower species. The visualization imports D3 v7 modules such as `scaleLinear`, `scaleOrdinal`, `symbol`, and `axisLeft`/`axisBottom` to build the chart and axes. It also includes a custom shape legend rendered via `symbolGenerator`. Data is loaded asynchronously from a CSV file using `csvParse`, with numeric fields parsed before the plot is updated.

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.