Skip to main content
SimilarExport ZIP
100%

Assignment 2 task1

✓ Published0🌍 Public
BBhavana Sharma
Last edited Apr 9, 2024
Created on Apr 9, 2024
Forked from Hello VizHub

This interactive visualization displays the Iris dataset through a dynamic scatter plot, cycling through different feature pairs on the x-axis every few seconds. The code uses D3’s `scaleLinear`, `axisBottom`, and `axisLeft` to construct the plot, while circles are colored by species (setosa, versicolor, virginica) via a custom marker function. The animation leverages `setInterval` to update the x-axis mapping, with axes, labels, and a legend re-rendered through `selection.call`. Data loads from a CSV URL using D3’s `csv` parser, and the SVG graphic updates in place.

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

Similar vizzes

Loading thumbnail…

Assignment2

This example presents an interactive scatterplot of the Iris dataset, cycling through different flower measurements on the x-axis every few seconds. The visualization colors each of the three species—setosa, versicolor, and virginica—with distinct hues and includes a legend with labeled color swatches. Users see dynamically updated axes and titles as the displayed variable changes. The code loads data from a GitHub-hosted CSV and uses D3 v5’s `csv`, `scaleLinear`, `axisLeft`, `axisBottom`, and `selectAll` with `join` to render animated SVG circles.

VVishnu Mallampalli
90% match
Loading thumbnail…

Assignment-2 Task-1

This interactive scatter plot visualizes the Iris dataset, cycling through four different attribute pairs on the x-axis every few seconds while the y-axis remains fixed. Points are colored by species (setosa, versicolor, virginica) with a manually drawn legend. The visualization is built using D3 v6, leveraging `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` within a reusable `scatterPlot` function. Animated transitions are driven by `setInterval`, updating the x-axis mapping and re-rendering SVG circles, axes, and text labels dynamically.

Vvullihanumantharao@gmail.com
90% match
Loading thumbnail…

Assignment 2

An interactive scatter plot displays the Iris dataset, animating through different pairings of sepal and petal measurements while coloring points by species. The code uses D3.js with `csv` for data loading, `scaleLinear` and `extent` for axes, and `axisLeft`/`axisBottom` for ticks. A `setInterval` cycles the x-axis variable among four columns, while the scatterPlot module handles updates. SVG circles, custom labels, and a color legend render the visualization.

Hhaneesh@gctc.in
90% match
Loading thumbnail…

Assignment 2

This visualization presents an animated scatter plot of the Iris dataset, cycling through different feature pairs on the x-axis while keeping petal width on the y-axis. The project uses D3.js v6 to load CSV data, apply linear scales, and render axes with `axisLeft` and `axisBottom`. React manages the SVG rendering, while a `setInterval` timer triggers transitions between variable combinations. The chart also includes a custom color legend distinguishing three Iris species, with points colored skyblue, lightgreen, and orange. Bootstrap-like styling comes from CSS, with the Share Tech font loaded from Google Fonts.

Ppslharika@gmail.com
89% match
Loading thumbnail…

Assignment2_Q1

This animated scatter plot explores the Iris dataset, cycling through different x-axis attributes (petal width, sepal width, petal length, sepal length) every few seconds while keeping sepal length on the y-axis. Colored circles distinguish the three Iris species, with a legend and axis labels updating dynamically. The visualization loads data via `d3.csv` and renders SVG elements using D3 v5, building a reusable scatter plot component with `scaleLinear`, `axisLeft`, `axisBottom`, and `setInterval` for animation.

VVishnu Mallampalli
88% match
Loading thumbnail…

Assignment2

This interactive scatter plot visualizes the Iris dataset, displaying petal and sepal measurements with color-coded species markers. Using d3.csv and d3.scaleLinear, it creates an SVG visualization that animates through different measurement combinations on the x-axis every few seconds via setInterval. The code employs d3.axisBottom and d3.axisLeft for axes, while a custom legend labels species categories. The reusable scatterPlot function, defined with D3’s module pattern, accepts configurable accessors and margin settings, allowing dynamic updates as the selected measurement column changes.

1188r1a0559@gmail.com
88% match
Loading thumbnail…

Assignment2

This animated scatter plot visualizes the Iris flower dataset, cycling through four measurement combinations of petal and sepal dimensions. Colored circles represent three species (setosa, versicolor, virginica) with a legend and axis labels. The visualization uses a reusable D3 scatter plot module (`scatterPlot()`) with `scaleLinear`, `axisLeft`, and `axisBottom` for axes. Data is loaded via D3's `csv` parser from a GitHub-hosted CSV file, with the view updating every few seconds through `setInterval`. SVG circles and text elements render the animated chart.

1188r1a0559@gmail.com
87% match
Loading thumbnail…

Assignment-2

This interactive scatter plot animates through different pairings of Iris flower measurements, cycling the x-axis among petal width, sepal width, petal length, and sepal length while keeping sepal length on the y-axis. Points are colored by species—setosa, versicolor, and virginica—with a legend and fixed axes. Built with D3 v6, it uses `scaleLinear`, `axisLeft`, `axisBottom`, and `setInterval` to update the chart, loading data from a remote CSV. The SVG rendering includes custom text labels, a title, and a rotating axis label.

Vvaishnavi6gan@gmail.com
87% match