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Tutorial-3

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Ssathvikavancha@my.unt.edu
Last edited Oct 21, 2024
Created on Oct 21, 2024

This scatter plot visualizes the Iris dataset, mapping petal and sepal dimensions with color-coded species. It loads the data via D3’s `csv` function from a GitHub gist and uses `scaleLinear`, `extent`, and `axisLeft`/`axisBottom` to build the axes. Circles are drawn in SVG with the `join` pattern, each colored by species (setosa, versicolor, or virginica). Axis labels are added as SVG text, with the visualization sized to the full window.

AI-generated description

An example showing the capabilities of VizHub:

  • Loads D3 via UNPKG.
  • Demonstrates use of import from "d3".
  • Demonstrates use of import from local ES6 modules.
MIT Licensed

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This scatter plot visualizes the Iris dataset, comparing petal length against petal width for individual flowers, with colors distinguishing the three species (setosa, versicolor, and virginica). It uses D3 v6 to load CSV data from a GitHub repository, scale linearly with `d3.scaleLinear`, and render circles in an SVG. The axes are drawn with `d3.axisLeft` and `d3.axisBottom`, while separate labels indicate the plotted variables, although the code also loads sepal dimensions without displaying them in the final chart.

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This scatter plot visualizes the Iris dataset, mapping petal length along the x-axis and petal width along the y-axis, with each of the three iris species (setosa, versicolor, and virginica) distinguished by a different fill color. Built with D3 version 6, the visualization uses `d3.csv` to load data from a remote GitHub source and `d3.scaleLinear` to create the axes’ scales. The SVG circles are drawn using `d3.select` and a data join, while `d3.axisLeft` and `d3.axisBottom` render the labeled axes, with additional text annotations for the axes.

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This scatter plot visualizes the Iris dataset, showing petal length against petal width with points colored by species (setosa, versicolor, and virginica) as skyblue, lightgreen, and orange. Circle markers also encode sepal dimensions through their `rx` and `ry` attributes, though they remain visually circular due to a fixed radius. The visualization loads data via `d3.csv` from a GitHub raw URL, uses linear scales (`scaleLinear`) with `extent` for domains, and renders axes with `axisLeft` and `axisBottom`. D3 v6 from UNPKG handles the SVG rendering and data joins.

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This example uses D3 v6 to create a scatter plot of the Iris dataset, loaded via CSV from a GitHub repository. It visualizes petal length on the x-axis and petal width on the y-axis, with circles colored by species (setosa, versicolor, virginica) using skyblue, lightgreen, and orange. The code employs `d3.csv` for parsing, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` for scales and axes. The SVG rendering uses `select` and `join` to bind data to circle elements.

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This interactive scatter plot visualizes the Iris dataset, displaying petal length against petal width for individual flowers, with colors indicating species. Rendered as SVG, the plot uses D3 v6 functions including `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to map data coordinates and draw axes. Data is loaded asynchronously from a CSV file via `d3.csv`, and each point is rendered as a circle with a fixed radius, colored by species. The chart fills the browser window and includes styled axis labels.

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