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question 2

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Ppavithranamburi24@gmail.com
Last edited Nov 6, 2024
Created on Nov 6, 2024

This example displays petal length distribution across iris species using a stacked area chart. It loads data from a remote CSV file and renders an SVG visualization. The code imports D3 functions including `csv`, `scaleBand`, `scaleLinear`, `stack`, and `area`. It constructs an area generator with band scale positioning, adds axes via `axisBottom` and `axisLeft`, and labels the chart with a title. The visualization shows how petal lengths vary among species, with steelblue filling for the area.

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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Activity 7.1 question 2

This example visualizes the distribution of petal length across iris species using a stacked area chart. It loads CSV data from a GitHub gist via D3’s `csv` method, then applies `scaleBand` for species categories and `scaleLinear` for petal length values. The chart uses `stack` and `area` generators to render a single filled area, with `axisBottom` and `axisLeft` for axes, and a title annotation. SVG output is produced through D3 selections.

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question_2

This example visualizes the classic Iris flower dataset, plotting petal and sepal lengths for each species along a horizontal axis. It uses D3.js v7 with a band scale for the categorical species on the y-axis and a linear scale for length. Circles are rendered in SVG, with petal lengths in steel blue and sepal lengths in green. Hovering changes a circle's fill color. The code loads data via `d3.csv` and uses `d3.scaleLinear`, `d3.scaleBand`, `d3.axisBottom`, and `d3.axisLeft` to construct the chart.

Eeedaraajay02@gmail.com
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question 2

This visualization displays the Iris dataset as a stacked bar chart, breaking down sepal and petal measurements for each species. It uses D3 v6 functions `d3.csv`, `d3.stack`, `scaleBand`, and `scaleLinear` to aggregate and position the bars. The SVG output is rendered with `d3.select` and the `join` operator, while axes are drawn using `d3.axisBottom` and `d3.axisLeft`. A linear color scale maps attribute indices to a two-tone palette, distinguishing the four measurement categories.

SSreeKohaliPatel@my.unt.edu
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question 3

This visualization displays the Iris dataset as a D3 scatter plot, mapping petal width against sepal length for individual flower samples. The code uses d3.csv to load the data from a GitHub Gist, then applies scaleLinear, scaleOrdinal, axisLeft, and axisBottom to construct the chart. Each data point is rendered as a distinct SVG symbol generated with d3.symbol and colored by species. The visualization includes labeled axes and is implemented as a reusable scatterPlot component.

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Task8_Activity2

This example visualizes the distribution of petal lengths across three Iris species using a stacked bar chart with tooltips. The code loads data from a local CSV file and renders the chart as SVG using D3 v7. It employs `d3.stack()` to create stacked segments, `d3.scaleBand()` for the categorical species axis, and `d3.scaleLinear()` for the continuous petal length axis. Interactive mouseover events display tooltips showing the exact petal length for each species and segment.

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activity7_question2

This stacked area chart visualizes the distribution of sepal width, petal length, and petal width across different sepal length values, using the classic Iris dataset. The chart shows how these three flower measurements contribute proportionally to the total across the range of sepal lengths, with color-coded categories shown in a legend. The visualization is built with D3.js (v7) and renders as an SVG, using `d3.stack()` for the stacked data, `d3.area()` for the area path generation, and `d3.scaleOrdinal()` for color mapping. The code reads data from a local CSV file and includes custom styling with fonts from Google Fonts.

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question2.1

This visualization shows a stacked bar chart of the Iris dataset, displaying the total sepal and petal measurements for each species. The chart uses d3.stack() to aggregate the four numerical attributes into color-coded segments per species, with a tooltip showing individual segment values on hover. The visualization renders with SVG, using d3.scaleOrdinal for colors, d3.scaleBand for the species axis, and d3.scaleLinear for the measurement axis. A legend identifies each attribute, and the data is loaded from an external CSV file using d3.csv.

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activity6_question3

This visualization shows the Iris dataset as a scatter plot, mapping petal length on the x-axis and petal width on the y-axis, with points colored by species (setosa, versicolor, and virginica). Using D3 v6, it loads CSV data via `d3.csv`, scales the coordinates with `scaleLinear` and `extent`, and renders circles on an SVG canvas. It also includes axes via `axisLeft` and `axisBottom`, with inverted y-axis scaling and labeled axes. The code processes raw numeric fields—sepal and petal measurements—to position each data point.

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