Skip to main content
SimilarExport ZIP
100%

Task_3.2

✓ Published0🌍 Public
Rrakesh.kavuru@outlook.com
Last edited Apr 5, 2024
Created on Apr 5, 2024
Forked from Hello VizHub

This visualization shows a scatter plot of the Iris dataset, mapping sepal length on the x-axis against petal length on the y-axis, with points styled by species using different D3 symbols. The code loads data from a CSV file via the Fetch API and parses it with d3.csvParse, then renders the plot using d3.scaleLinear for axes, d3.scaleOrdinal with d3.symbolsFill for shape encoding, and d3.axisLeft/axisBottom via the custom axes module. A custom shape legend module displays the species categories using d3.symbol, while D3’s join pattern handles dynamic element updates.

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…

task3.2

This example demonstrates a scatter plot of the Iris dataset, mapping sepal length to the x-axis, petal length to the y-axis, and encoding species with distinct shapes. The visualization uses D3's `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbol` APIs to render the data points, while `axisLeft` and `axisBottom` from D3 handle the axes. A custom shape legend is built using the `symbol()` generator. The data is loaded asynchronously via `fetch` from a remote CSV file, then parsed with `csvParse` before being rendered.

Yyashwanthkirla95@gmail.com
95% match
Loading thumbnail…

Task3.2

This scatter plot visualizes the Iris dataset, showing sepal length against petal length. Points are colored and shaped by species, with a legend mapping shapes to the three iris species. The visualization is built using D3 v7, employing force-directed layout principles through `d3.scaleLinear` and `d3.scaleOrdinal` for scales. The chart fetches data from a remote CSV, parses it with `d3.csvParse`, and renders marks via `d3.symbol` with axes generated by `d3.axisLeft` and `d3.axisBottom`.

IIkram Mohammed
94% match
Loading thumbnail…

task 3.2

This example shows a scatter plot of the Iris dataset, with sepal length mapped to the x-axis, petal length to the y-axis, and species distinguished by different symbol shapes. A custom shape legend labels each species group. The visualization loads CSV data via `d3.csvParse` and uses D3 v7’s `scaleLinear`, `scaleOrdinal`, `symbol`, `symbolsFill`, and axis functions (`axisLeft`, `axisBottom`) to render marks and axes. A local ES6 module structure organizes the code into separate files for the chart, axes, and legend.

Jjangalaupender@my.unt.edu
94% match
Loading thumbnail…

Task-3

This scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with different agricultural species distinguished by distinct symbols. The visualization uses D3 v7's `scaleLinear` for axes scaling and `scaleOrdinal` with `symbolsFill` to map species categories to different shapes. A shape legend at the bottom right identifies each species, while the plot is rendered using `svg` paths with `symbol` generators. The data is loaded asynchronously from a CSV file fetched from GitHub, and axes are added via custom `axes` and `shapeLegend` functions.

Vvamsikrishnakanchukommala@my.unt.edu
93% match
Loading thumbnail…

Activity6_Task3.2

This scatter plot visualizes the Iris dataset, showing sepal length against petal length, with each species represented by a distinct symbol shape. The plot encodes the three Iris species through shape, using d3.scaleOrdinal with symbolsFill to assign different geometric marks, while a custom legend explains the species mapping. Axes are rendered via d3.axisLeft and d3.axisBottom, with labels for both dimensions. The data is loaded asynchronously from a GitHub-hosted CSV file using d3.csvParse, and the visualization updates through a state management pattern that handles loading and rendering.

Nnikhilthoutu24@gmail.com
93% match
Loading thumbnail…

task 3.2

This example displays a scatter plot of the Iris dataset, plotting sepal length against petal length. Points are colored and shaped according to species, with a custom legend identifying each species by its unique symbol. The visualization uses D3.js (v7) to fetch and parse the CSV data from a GitHub repository, then renders the plot within an SVG. It constructs axis scales with `scaleLinear`, applies shape encodings through `scaleOrdinal` and `symbolsFill`, and generates marks via `symbolGenerator`, with axes and legends created by custom functions.

Ssatvikreddy79@gmail.com
93% match
Loading thumbnail…

Activity6-Task3.2

This visualization displays the Iris dataset as a scatter plot, mapping sepal length on the x-axis and petal length on the y-axis, with the three iris species distinguished by different symbol shapes. The plot uses d3.scaleLinear for both axes, d3.scaleOrdinal with d3.symbolsFill to encode species, and includes axis labels and a shape legend. Data is loaded asynchronously from a GitHub-hosted CSV file using d3.csvParse, with numeric fields converted to numbers before rendering.

Mmeenam1106@gmail.com
93% match
Loading thumbnail…

Task3Ques

This scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with each species represented by a distinct symbol shape. A legend on the right identifies the three species categories. The visualization is built with D3 v7, using d3.scaleLinear for positioning, d3.scaleOrdinal with d3.symbolsFill for shape encoding, and d3.axisLeft and d3.axisBottom for the axes. Data is loaded from a remote CSV file and parsed with d3.csvParse.

IIkram Mohammed
93% match