Activity-6 Task-3.2

Activity6-Task3.2

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 the three iris species distinguished by different symbol shapes. The plot uses d3.scaleLinear for both axes, d3.scaleOrdinal with d3.symbolsFill to encode species, and includes axis labels and a shape legend. Data is loaded asynchronously from a GitHub-hosted CSV file using d3.csvParse, with numeric fields converted to numbers before rendering.

Mmeenam1106@gmail.com

Activity-6 Task3.1

This scatter plot visualizes the Iris dataset, showing sepal length against petal length for three flower species. Each species is distinguished by a distinct symbol shape, with a legend explaining the mapping. The visualization uses D3 v7's `scaleLinear`, `scaleOrdinal`, and `symbol` APIs to position points and generate shapes, with axes created via `axisLeft` and `axisBottom`. Data is loaded asynchronously from a CSV file and parsed with `csvParse`.

Hharshaps15@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. Each point represents a flower sample, with its species indicated by a distinct fill symbol—circles, squares, and diamonds—as defined by the `symbolsFill` palette. The chart includes labeled axes and a custom shape legend explaining the species-to-symbol mapping. The visualization uses D3.js version 7, leveraging `scaleLinear`, `scaleOrdinal`, and `symbol` to create the plot and its interactive legend.

Bbhargavr016@gmail.com

Activity6 task3.2

This scatter plot visualizes the Iris dataset, plotting sepal length against petal length. Each point is rendered as a distinct symbol—circle, cross, or square—to represent the three species of Iris flowers, categorized on a categorical color scale. The visualization is built using D3.js (v7), using the `scaleLinear` and `scaleOrdinal` APIs to map data to positions and symbols. Axes and a shape legend are drawn using custom `axes` and `shapeLegend` modules, which utilize D3’s `axisLeft` and `axisBottom` functions. Data is loaded from a remote CSV file and parsed with `csvParse`.

Hhkodiripaka15@gmail.com

Ppadiginetivishnupriya@gmail.com

Activity6_Task3.2

This scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis, petal length on the y-axis, and encoding species by symbol shape. It uses d3.scaleLinear for axes, d3.scaleOrdinal with symbolsFill for shapes, and a custom legend showing species markers. Data is loaded via fetch as CSV and parsed with d3.csvParse, with axes and legend rendered using d3.axisLeft, d3.axisBottom, and d3.symbol.

Kkondaveeti.bhargavi7780@gmail.com

Activity6_Task3.2

This scatter plot visualizes the relationship between sepal length and petal length in the Iris dataset, with each point's shape indicating the species. The visualization uses D3 v7's modular APIs including scaleLinear, scaleOrdinal, symbolsFill, and symbol for generating the scatter marks. Axes are rendered with axisLeft and axisBottom, while a custom shape legend maps species to distinct symbol types. The data is loaded from a GitHub-hosted CSV file and parsed using csvParse, with numeric fields converted from strings.

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.

Ssatishvelaga02@gmail.com

Activity6Task3.2

This interactive scatter plot visualizes the Iris dataset, mapping sepal length to the x-axis, petal length to the y-axis, and using different symbol shapes to distinguish species. A custom legend labels each shape with its corresponding species. The visualization loads the data from a raw CSV file, parses it with `d3.csvParse`, and renders the plot using `d3.scaleLinear`, `d3.scaleOrdinal`, and `d3.symbol`. Axes and labels are generated through a reusable module that calls `d3.axisLeft` and `d3.axisBottom`.