Fork of Activity6_Task3_Tutorial 3.2

Activity6_Task3.2

This interactive scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with species distinguished by different symbol shapes. The visualization uses D3.js v7, employing `scaleLinear` for both axes, `scaleOrdinal` with `symbolsFill` for shape encoding, and a custom shape legend component. Data is loaded asynchronously from a GitHub-hosted CSV file using `d3.csvParse`. The chart responds to window resizing by redrawing within the full viewport, with axes and labels generated through reusable `axes.js` and `scatterPlot.js` modules.

VVidya Lakshmi Chitturi

Activity6_Task3_Tutorial 3.2

This scatter plot visualizes the Iris dataset, showing sepal length against petal length for three flower species distinguished by different filled symbols. The visualization uses an ordinal scale with D3’s `symbolsFill` to assign shapes to species and includes a custom legend via `shapeLegend`. Axes are generated using `d3.axisLeft` and `d3.axisBottom`, with data loaded asynchronously from a GitHub CSV and parsed by `d3.csvParse`. The plot renders within a full-window SVG.

Nnavyabade05@gmail.com

Ccharankumarreddyveeramreddy@my.unt.edu

Activity 6_Task 3.2 Tutorial

This interactive scatter plot visualizes the Iris dataset, mapping sepal length against petal length. Different species are represented by distinct D3 symbols, such as circles and crosses, with a legend annotating each shape. Built with D3 v7, it uses `csvParse` to load data and `scaleLinear` for axes. The code generates the plot using reusable modules for rendering axes (`axisLeft`, `axisBottom`) and the shape legend, with rendering triggered by a simple state-based update cycle.

Fork of Activity6_Task3.2

This scatter plot visualizes the Iris dataset, mapping sepal length against petal length and using distinct shapes to represent different iris species. The visualization loads data from a CSV file and displays it using D3 v7, leveraging the `scaleLinear` and `scaleOrdinal` scales to map data values to plot coordinates and shape encodings. Custom axis and legend modules render labeled axes and a shape legend, while the `symbol` API generates the species-specific markers. The plot dynamically fetches and parses the data via `csvParse`, updating the display once the dataset arrives.

MMallikarjun Narra

Activity6_Task3.1

This interactive scatter plot visualizes the Iris dataset, showing petal length against sepal length for different Iris species. The visualization uses distinct shapes (circles, squares, and triangles) to differentiate species, with a dedicated shape legend positioned on the right side of the chart. Built with D3.js v7, the code employs `d3.scaleLinear` for axes scaling and `d3.scaleOrdinal` with `d3.symbolsFill` to map species categories to symbol types. Data is loaded asynchronously from a GitHub-hosted CSV file, with axes labeled and styled through custom `d3.axisLeft` and `d3.axisBottom` calls.

SSowjanya Devupalli

Rrayavarapulokesh3@gmail.com

Activity6_Task3.2

This interactive scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis while distinguishing species through different symbols. The chart uses D3 v7’s `scaleLinear` for axes, `scaleOrdinal` with `symbolsFill` for shape encoding, and a custom legend module. Data is loaded asynchronously via `fetch` and parsed with `csvParse`, with axes rendered using `axisLeft` and `axisBottom`. The visualization updates dynamically as the data arrives, demonstrating categorical shape encoding for multivariate comparison.

Aanusha.chilkamarri26@gmail.com

Fork of activity 6_tutorial 3.2

This scatter plot visualizes the Iris dataset, showing sepal length against petal length, with species distinguished by different d3 symbol shapes. A shape legend identifies the three species categories, while labeled axes display the quantitative measurements. Built with D3 v7, the visualization uses modular JavaScript functions including `scaleLinear`, `scaleOrdinal`, `symbolGenerator`, and custom axis and legend components. The data is loaded asynchronously from a remote CSV file and parsed using `csvParse`, with the plot rendering across the full browser window.

Activity6_Task3(tutorial 3.2)

This scatter plot visualizes the Iris dataset, mapping sepal length against petal length and encoding species with distinct marker shapes. It loads data from a CSV file hosted on GitHub, parsing and converting numeric fields. The visualization uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, `symbolsFill`, `axisLeft`, and `axisBottom` to construct the plot, axes, and a custom shape legend. The chart updates dynamically as data loads, demonstrating modular ES6 imports and a state-based rendering pattern.

Gguruabhay294@gmail.com