activity6_Task3.2

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.

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.

Ssaiteja.cse.rymec@gmail.com

Activity6_Task3.2

This example displays a scatter plot of the Iris dataset, mapping sepal length against petal length and encoding species with different point shapes. It uses D3 v7 to load data via CSV, construct linear scales, and render symbols from `symbolsFill`. The visualization includes axes and a custom legend built with reusable ES6 modules, demonstrating data fetching and modular code organization.

LLakshmiDeepikaPagadala@my.unt.edu

Activity6_Task3.2

This example shows a scatter plot of the Iris dataset, mapping sepal length to petal length and encoding species with distinct symbols. It uses D3 v7 modules such as `scaleLinear`, `scaleOrdinal`, `axisLeft`, `axisBottom`, and `symbol` to draw marks and axes. The visualization is built with modular ES6 imports for chart, axes, and legend components. Data is loaded asynchronously via `fetch` and parsed with `csvParse`, then rendered in an SVG that fills the window.

Activity6_Task3.2

This example demonstrates a scatter plot of iris flower measurements, encoding sepal and petal length on the axes and using different symbols to distinguish species. It loads the Iris dataset from a GitHub-hosted CSV file and parses it with `d3.csvParse`. The visualization is built with D3 v7, using `d3.scaleLinear` for axes, `d3.scaleOrdinal` with `d3.symbolsFill` for shape encoding, and modular ES6 imports for reusable axes and legend components. The legend is rendered with `d3.symbol` positioned at a fixed coordinate within the SVG canvas.

KKhushi Desai

Gganeshseeram5decem@gmail.com

Activity6_Task3.2

This interactive scatter plot visualizes the Iris dataset, mapping sepal length against petal length and distinguishing species by shape. It uses D3 v7, loaded via UNPKG, with imported utilities like `scaleLinear`, `scaleOrdinal`, and `symbol`. The chart fetches CSV data from a GitHub repository, parses it with `csvParse`, and renders axes, labels, and a custom shape legend. The code demonstrates modular ES6 imports and D3's join-based selection pattern for declarative updates.

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.

Activity 6_Task 3.2

This example displays a scatter plot of the Iris dataset, showing sepal length against petal length. Each point’s symbol (circle, triangle, or square) encodes the iris species, and a legend identifies these shapes. The visualization uses D3 v7 with `scaleLinear`, `scaleOrdinal`, and `symbol` to render marks, plus custom axis and legend modules. It loads the CSV data from GitHub, scales numeric fields on load, and renders interactively in the browser window.

DDipesh