Skip to main content
SimilarExport ZIP
100%

Activity6_Task3.2

✓ Published0🌍 Public
Gguttavenkata745@gmail.com
Last edited Oct 18, 2024
Created on Oct 18, 2024
Forked from Hello VizHub

This example demonstrates a scatter plot of the Iris dataset, showing sepal length versus petal length with different point shapes representing species. The visualization loads data from a GitHub-hosted CSV file, parses it with `d3.csvParse`, and renders points using D3 v7's `scaleLinear`, `scaleOrdinal`, and `symbol` generators. A custom shape legend, implemented as an ES6 module, displays the three species with matching symbols. Axes are drawn using `axisLeft` and `axisBottom`, with labels positioned via D3 selection methods.

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…

Activity6_Task3.2

This example visualizes the Iris dataset as a scatter plot of sepal length against petal length, with the three species distinguished by different symbol shapes. A shape legend identifies each species, and the plot includes styled axes with labels. The visualization is built using D3 v7, employing `scaleLinear` for the x and y scales, `scaleOrdinal` with `symbolsFill` for the shapes, and the `csvParse` method to load data from a GitHub-hosted CSV file. The `axes` and `shapeLegend` modules handle the axis and legend rendering.

Nnsairitwikreddy@gmail.com
96% match
Loading thumbnail…

Activity6_Task3.2

This example shows a scatter plot of the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with points colored and shaped by species. A custom shape legend displays the species categories. The visualization uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, and `symbol` to render the marks, with axis and legend components built as reusable functions. The dataset is loaded as a CSV from a GitHub URL, parsed with `csvParse`, and numeric columns are converted before rendering. The plot updates responsively to the window size.

Vvarun.mahankali39@gmail.com
96% match
Loading thumbnail…

Activity6_task3.2

This example shows a scatter plot of the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with species indicated by different symbols and a legend. The visualization loads the data from a GitHub CSV file, parses it with `d3.csvParse`, and uses D3 v7’s `d3.scaleLinear`, `d3.scaleOrdinal`, `d3.symbolsFill`, and `d3.axisBottom`/`d3.axisLeft` for scales and axes. The code employs a `join`-based declarative grammar to build SVG elements, with a custom `shapeLegend` for symbol encoding. The plot adapts to the window size and updates dynamically as data loads.

RRJVENKATESH789@GMAIL.COM
96% match
Loading thumbnail…

Activity6_Task3.2

This example demonstrates a scatter plot of the classic Iris dataset, showing sepal length against petal length, with each point’s shape indicating its species. It uses D3 v7 with the `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbol` APIs to create the plot and a custom shape legend. The visualization loads the CSV data via a remote URL, parses it with `csvParse`, and renders the chart using an SVG canvas. The code organizes chart components into local ES6 modules for axes, scatter plot, and legend, imported through `import` statements.

Rrakshithareddy217@gmail.com
96% match
Loading thumbnail…

Activity6_Task3.2

This example displays a scatter plot of the Iris dataset, showing sepal length against petal length with points colored and shaped by species. It loads the CSV from a GitHub repository using `d3.csvParse`. The visualization uses D3 v7 scales including `scaleLinear` and `scaleOrdinal` with `symbolsFill` to differentiate species, while a custom legend built with `symbolGenerator` lists the categories. Axes are generated via `axisLeft` and `axisBottom` with explicit labels for each measurement.

Bbudalavijay2001@gmail.com
96% match
Loading thumbnail…

Activity6_Task3.2

This example demonstrates a scatter plot of the Iris dataset, mapping sepal length against petal length and distinguishing species by shape. It loads data from a CSV file and uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `csvParse`. The visualization includes custom axes and a shape legend, built with reusable local ES6 modules.

Llikhitha.sarahah01@gmail.com
96% match
Loading thumbnail…

Activity 6_Task3.2

This example shows a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with the three flower species distinguished by different symbol shapes (circles, crosses, and diamonds) via a shape legend. The visualization is built with D3 v7, using `scaleLinear`, `scaleOrdinal`, `symbol`, and `symbolsFill` to position and style the marks. It fetches the CSV data from a GitHub repository and renders it in an SVG sized to the window. A modular structure separates the axes, legend, and plot logic into reusable functions.

SSiva Kishore Reddy
95% match
Loading thumbnail…

Activity6_Task3.2

This example visualizes the Iris dataset as a scatter plot, mapping sepal length along the x-axis and petal length along the y-axis. The visualization uses distinct shapes to represent the three species of iris flowers, with a shape legend positioned to the right of the plot. Built with d3.v7, the code leverages d3.csvParse to load data from a GitHub repository, d3.scaleLinear for axis scaling, and d3.scaleOrdinal with d3.symbolsFill to assign different symbol types to each species. The SVG rendering includes custom axis labels and a shape legend created through d3 selection joins.

Mmaneeshraja47@gmail.com
95% match