Activity6_task3

Ssaishruthik2361@gmail.com

Activity6_Task3

This scatter plot visualizes the Iris dataset, mapping petal length and width on the axes while coloring each point by species (setosa, versicolor, or virginica). It uses D3 v6 with scaleLinear for scales, extent for domains, and axisLeft/axisBottom for ticks. The SVG is sized to the full window, and circles are joined via selectAll and data. The plot also misapplies rx/ry attributes to circles, which have no visual effect. Data loads from a GitHub-hosted CSV via d3.csv.

Ddineshreddy.ravula@gmail.com

Activity6_task3

This scatter plot visualizes the Iris dataset, mapping petal length on the x-axis and petal width on the y-axis, while coloring each circle by species (setosa, versicolor, and virginica). The chart displays all 150 data points using SVG circles, with species-specific colors applied via a switch function. Built with D3 v6, the visualization uses `d3.csv` to load data from a GitHub-hosted CSV, `scaleLinear` for axes, and `axisLeft`/`axisBottom` for tick marks. Axis labels are styled with green text for petal length and sepal length.

Vvishnutejareddyambati@my.unt.edu

Activity6 task3

This scatter plot visualizes the Iris dataset, mapping petal length and width for each sample while coloring points by species (setosa, versicolor, and virginica) using D3 v6. The SVG rendering uses `scaleLinear` for both axes, `extent` to set domains, and `axisLeft`/`axisBottom` for tick marks. Data is loaded asynchronously from a GitHub CSV via `d3.csv`, with each circle assigned a radius of 5 and a species-specific fill color from a simple switch statement.

Activity6_Task3.1

This scatter plot visualizes the Iris dataset, mapping petal length and petal width as x and y coordinates while coloring each point by species (setosa, versicolor, or virginica). It loads CSV data from a GitHub URL and renders circles with D3 v6, using `d3.csv`, `scaleLinear`, `extent`, and `axisLeft`/`axisBottom` to construct axes. The SVG-based visualization labels both axes and includes a fixed point radius, with species-specific colors applied via a switch statement.

Vvemulasai306@gmail.com

KKondreddy Saikiran reddy

Activity6_Task3

This scatter plot visualizes the iris dataset, showing petal length on the x-axis and petal width on the y-axis, with each point colored by species (setosa, versicolor, or virginica). The visualization uses D3.js v6, loading data from a GitHub CSV file via `d3.csv`. It employs `d3.scaleLinear` for both axes, `d3.extent` for domain calculation, and `d3.axisLeft` and `d3.axisBottom` for chart axes. The SVG circles have a fixed radius but their `rx` and `ry` attributes are set to sepal measurements, though these do not affect circular rendering.

SSaiKiranReddyKancharla@my.unt.edu

Activity6_Task3.1

This scatter plot visualizes the Iris dataset, mapping petal length and width on the x- and y-axes while coloring each point by species (setosa, versicolor, and virginica). The visualization uses D3 v6, loading data via `d3.csv` from a GitHub Gist and rendering with SVG. The chart employs `d3.scaleLinear` for axes, `d3.extent` for domain calculation, and `d3.axisLeft`/`d3.axisBottom` for tick marks, with circle marks sized uniformly and colored via a custom switch function.

Kkowshiksamudrala08@gmail.com

Activity6_Task3

This scatter plot visualizes the Iris dataset, showing petal length on the x-axis and petal width on the y-axis, with each point colored by species (skyblue for setosa, lightgreen for versicolor, orange for virginica). The visualization uses D3 v6 with `d3.csv`, `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, and `d3.axisBottom` to load data from a GitHub-hosted CSV and render SVG circles. Axis labels for petal length and sepal length are added with lower-case text, using a green font.

Activity6_Task3

This scatter plot visualizes the Iris dataset, showing petal length against petal width, with circles colored by species (setosa, versicolor, virginica). It uses d3.v6’s `csv` loader, `scaleLinear`, `axisLeft`, and `axisBottom` to build the SVG visualization. The plot reads data from a GitHub-hosted CSV, maps each row to circle positions via x and y scales, and renders colored markers with fixed radius.

VVidya Lakshmi Chitturi