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Activity 6_Task 3.1_Tutorial

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Ccharankumarreddyveeramreddy@my.unt.edu
Last edited Oct 19, 2024
Created on Oct 19, 2024

This scatter plot visualizes the Iris dataset, mapping petal length and width for each flower sample. Points are colored by species, with setosa in blue, versicolor in green, and virginica in red. The code loads the CSV data via d3.csv, then uses d3.scaleLinear with d3.extent to establish the x and y scales, and renders circles with d3.selectAll and .join. Axes are generated using d3.axisLeft and d3.axisBottom, with custom labels added as SVG text elements. The visualization fills the browser window using window.innerWidth and window.innerHeight.

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We are Displaying the IRIS dataset using Scatter plot.

MIT Licensed

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Activity 6_Task 3.1_Tutorial

This scatter plot visualizes the Iris dataset, mapping petal length and width as the x- and y-axes, with each point colored by species (setosa, versicolor, or virginica). D3 v6 loads the CSV via `d3.csv`, and uses `d3.scaleLinear`, `d3.extent`, and `d3.axisLeft`/`d3.axisBottom` to render axes. Circles are drawn with SVG, and their radii are fixed, but the `rx` and `ry` attributes are set to sepal length and width, creating elliptical markers. Data is sourced from a GitHub-hosted CSV file.

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This scatter plot visualizes the Iris dataset, mapping petal length and width for each flower sample. Points are color-coded by species (setosa, versicolor, virginica) using skyblue, lightgreen, and orange fills. The visualization uses D3 v6 APIs including `csv` for data loading, `scaleLinear` for axis scaling, and `axisLeft`/`axisBottom` for rendering axes. SVG circles represent data points, with axis labels styled in green. The chart renders full-window with margins, displaying sepal dimensions as dataset attributes alongside the plotted petal measurements.

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This scatter plot visualizes the Iris dataset, mapping petal length and width for each flower sample. Circles are colored by species—sky blue for setosa, light green for versicolor, and orange for virginica—revealing distinct clusters. The example loads data from a remote CSV file using the `d3.csv` function, then renders the chart as an SVG. It uses `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, and `d3.axisBottom` to create the scales and axes, with the `select` and `join` pattern to bind data to circle elements.

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This example visualizes the Iris dataset as a scatter plot, mapping petal length and width on the axes while coloring each point by species (setosa, versicolor, or virginica). The chart uses D3 v6 to load CSV data, apply linear scales, and render SVG circles with custom fill colors. Axis labels are added using d3.axisLeft and d3.axisBottom, and the graphic fills the browser window. The code imports specific D3 modules via destructuring and uses scaleLinear, extent, and join for efficient data binding.

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