Activity 3 Task 3.2

Bbhargavireddy4016@gmail.com

Activity-6 Task-3.2

This visualization displays a scatter plot of the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis. Each point is rendered as a distinct symbol shape representing the species of iris flower. The chart uses D3.js v7 with `scaleLinear` for the axes, `scaleOrdinal` with `symbolsFill` for shape encoding, and a custom legend showing the species symbols. Data is loaded as CSV and parsed with `csvParse` before being plotted.

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

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

Activity 6_task 3.2

This visualization displays the Iris dataset as a scatter plot, mapping sepal length on the x-axis and petal length on the y-axis. Each data point appears as a distinct symbol shape corresponding to the iris species, with a legend identifying the species categories. The implementation uses D3 v7 APIs including `scaleLinear` for axes, `scaleOrdinal` for shape encoding, `symbol` for rendering marks, and asynchronous `csvParse` to load data from a remote CSV file. Custom modules handle axis generation and the shape legend with pattern-matched transitions.

Jjampani921@gmail.com

Activity6_Task3.2

This visualization displays the Iris dataset using a D3.js scatter plot, mapping sepal length to the x-axis and petal length to the y-axis. Each data point is rendered as a path with a distinct symbol from `symbolsFill`, where the species determines its shape. It loads CSV data via `d3.csvParse` from a remote GitHub source and uses `scaleLinear` for positioning and `scaleOrdinal` for shape encoding. A custom legend shows the species labels, and the axes are drawn with `axisLeft` and `axisBottom`.

SSeema Shrestha

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.

Rrahulnathmukkolla@gmail.com

Activity 6 Task 3.2

This interactive scatter plot visualizes the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis while encoding species through distinct symbol shapes. The visualization uses D3 v7’s `scaleLinear`, `scaleOrdinal`, and `symbol` APIs to render marks and a custom shape legend. Data is loaded asynchronously from a GitHub-hosted CSV file using `d3.csvParse`, with axis labels generated via reusable `axisLeft` and `axisBottom` functions. Each point is drawn as a `path` element, and the legend displays the three species categories.

Activity 6_Task-3.2

This scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with each species distinguished by a unique symbol shape and a corresponding legend. The visualization uses d3.scaleLinear for axes, d3.scaleOrdinal with symbolsFill for shape encoding, and d3.symbol to render the marks. Axes and labels are drawn via custom functions. Data is loaded asynchronously using d3.csvParse from a remote CSV file, and the plot updates responsively to the window size.

Rrajkodavati7@gmail.com