Skip to main content
SimilarExport ZIP
100%

Activity6_task3.2

✓ Published0🌍 Public
AAnirudhaKulakarniKaranam@my.unt.edu
Last edited Apr 4, 2024
Created on Apr 4, 2024
Forked from Hello HTML

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 each species distinguished by a unique shape symbol. The visualization includes labeled axes and a custom legend that displays the shape-to-species mapping. Built with D3.js v7, it uses `scaleLinear` for the axes, `scaleOrdinal` with `symbolsFill` for shapes, and the `symbol` generator to draw the marks. Data is loaded asynchronously from a CSV file and parsed with `csvParse`.

AI-generated description

A bare minimum HTML page.

MIT Licensed

Similar vizzes

Loading thumbnail…

Activity6_Task3.1

This example shows an interactive scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with each species represented by a distinct symbol shape. The visualization uses D3.js v7 APIs including `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbolGenerator` to render the marks, while a custom shape legend displays the species categories. Data is loaded asynchronously from a GitHub-hosted CSV file using `fetch` and parsed with `csvParse`, with numerical fields coerced to numbers before plotting. The chart includes labeled axes and a legend, all rendered within an SVG canvas sized to the full viewport.

Bbudalavijay2001@gmail.com
95% match
Loading thumbnail…

Activity6_task3.2

This example shows a scatter plot of Iris flower measurements, mapping sepal length on the x-axis and petal length on the y-axis, with different symbol shapes representing species. The visualization also includes a custom shape legend identifying each species. The code uses d3.csvParse and d3.fetch to load a CSV dataset, then d3.scaleLinear for axes and d3.scaleOrdinal with d3.symbolsFill to assign distinct geometric markers. Axes are rendered via the d3.axisLeft and d3.axisBottom APIs, while a custom legend module draws symbols and text ticks.

Mmaneeshraja47@gmail.com
95% match
Loading thumbnail…

activity6_task3.2

This example visualizes the Iris dataset as a scatter plot, mapping sepal length and petal length on the axes while using different symbol shapes to distinguish between plant species. It uses D3 v7 APIs such as `scaleLinear`, `scaleOrdinal`, `symbol`, and `symbolsFill` to handle axes, scaling, and shape encoding. A custom legend is drawn using `shapeLegend`. Data is loaded asynchronously from a GitHub-hosted CSV file and parsed with `csvParse`.

Ggketan456@gmail.com
94% 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 shaped according to species. It renders vector graphics in an SVG canvas, loading data from a remote CSV via `fetch` and parsing it with `d3.csvParse`. The visualization uses D3 v7 APIs including `scaleLinear`, `scaleOrdinal`, `extent`, `symbolsFill`, and `symbol()` to position marks and generate shapes, while `axisLeft` and `axisBottom` from `d3` draw the axes. A custom legend displays the species-to-shape mapping.

Aanish6005@gmail.com
94% 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
94% match
Loading thumbnail…

Activity6_Task3

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 species of each flower indicated by a distinct symbol (circle, square, or triangle). A legend on the right identifies the species-to-shape mapping. The visualization is built using D3 v7, leveraging `scaleLinear` for the axes, `scaleOrdinal` with `symbolsFill` for the shapes, and D3's `symbol` generator to draw the marks. The data is loaded asynchronously from a GitHub-hosted CSV file, and the chart is rendered into an SVG canvas.

Mm.maanvireddt761@gmail.com
94% 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
94% match
Loading thumbnail…

activity 6 task3.2

This example shows the classic Iris dataset as a scatter plot of sepal length against petal length, with each species distinguished by a different symbol shape. A legend maps the species names to their corresponding shapes. The visualization is built with D3 v7, using scales like `scaleLinear` and `scaleOrdinal` along with `symbolGenerator` for shape rendering. The axes are drawn via `axisLeft` and `axisBottom`, and the data is loaded from a remote CSV file using `csvParse`.

Ssairamisetti3829@gmail.com
94% match