task 3 tutorial3.2

Jjyothirmaijyothi2017@gmail.com

Task8_Tutorial3.2

This scatter plot displays the Iris dataset, plotting sepal length against petal length and using different point shapes to distinguish between the three iris species. The visualization uses D3 v7 to create the plot, with a categorical shape scale assigning distinct symbols (from `symbolsFill`) to each species. Axes are rendered using D3's `axisLeft` and `axisBottom` functions, while a custom legend wizard communicates the shape-to-species mapping. Data is fetched asynchronously from a remote CSV file and parsed with `csvParse` before being passed to the chart.

task 3.2

This example displays a scatter plot of the Iris dataset, plotting sepal length against petal length. Points are colored and shaped according to species, with a custom legend identifying each species by its unique symbol. The visualization uses D3.js (v7) to fetch and parse the CSV data from a GitHub repository, then renders the plot within an SVG. It constructs axis scales with `scaleLinear`, applies shape encodings through `scaleOrdinal` and `symbolsFill`, and generates marks via `symbolGenerator`, with axes and legends created by custom functions.

Ssatvikreddy79@gmail.com

Task8_Tutorial3.2

This visualization displays an interactive scatter plot of the Iris dataset, mapping sepal length against petal length. Each of the three iris species is represented by a distinct symbol shape, with a custom legend identifying the species categories. The implementation uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, and `symbol` to generate the marks, while `axisLeft` and `axisBottom` render the labeled axes. Data is loaded asynchronously from a CSV file via `csvParse` and rendered within a full-window SVG canvas.

KKeerthi

Task8_tutorial3

This scatter plot visualizes the Iris dataset, showing the relationship between sepal length and petal length. Each point is shaped according to the iris species—setosa, versicolor, or virginica—with a legend mapping shapes to species. Built with D3 v7, the code uses `scaleLinear` and `scaleOrdinal` to map data to positions and shapes, while `axisLeft` and `axisBottom` render the axes. Data is loaded via `fetch` and parsed with `csvParse`.

Ppogirimayoor@gmail.com

LLakshmiPrasannaValdas@my.unt.edu

Task 8_tutorial3.2

This scatter plot visualizes the Iris dataset, comparing sepal length against petal length for different iris species. The chart encodes each data point as a distinct shape, using the `d3.symbol` API with a `symbolsFill` scale to differentiate species, and includes a shape legend generated via `shapeLegend`. The visualization uses `d3.scaleLinear` for axes and `d3.scaleOrdinal` for species mapping, with custom axis and legend utilities built on D3's selection join pattern. Data is fetched as CSV from a GitHub repository and parsed with `d3.csvParse`.

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

Task3.2

This scatter plot visualizes the Iris dataset, showing sepal length against petal length. Points are colored and shaped by species, with a legend mapping shapes to the three iris species. The visualization is built using D3 v7, employing force-directed layout principles through `d3.scaleLinear` and `d3.scaleOrdinal` for scales. The chart fetches data from a remote CSV, parses it with `d3.csvParse`, and renders marks via `d3.symbol` with axes generated by `d3.axisLeft` and `d3.axisBottom`.

IIkram Mohammed

Tutorial 3.2

This scatter plot visualizes the Iris dataset, showing the relationship between sepal and petal length for three species. The d3.js code uses `scaleLinear` for the x- and y-axes, and `scaleOrdinal` with `symbolsFill` to distinguish species by shape (circles, squares, and other symbols). A custom legend component displays the symbol-to-species mapping, while the `axes` module renders labeled axes using `axisBottom` and `axisLeft`. Data is loaded asynchronously from a CSV file and parsed with `csvParse`.

Ppnamitha46@gmail.com