Skip to main content
SimilarExport ZIP
100%

Activity6_Tu_3.2

✓ Published0🌍 Public
Aadapasaidivya99@gmail.com
Last edited Oct 21, 2024
Created on Oct 21, 2024
Forked from Hello VizHub

This example creates an interactive scatter plot of the Iris dataset, using sepal and petal lengths as axes and species as categorical shapes. It loads CSV data from a GitHub repository via `fetch` and `csvParse`, then renders the chart with D3 v7. The visualization includes custom axis labels, a shape legend, and uses `scaleLinear`, `scaleOrdinal`, `symbolsFill`, and `symbol` to map data points to distinct marker types. The code is modularized into separate ES6 modules for axes, scatter plot, and legend components.

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…

Activity_6_Tutorial 3.2

This example demonstrates a scatter plot of the Iris dataset, showing sepal length versus petal length with points shaped according to species. The visualization includes labeled axes and a shape legend for the three species categories. Built with D3 v7, the code creates linear scales, applies an ordinal color shape scale using `symbolsFill`, and renders SVG symbols via `symbolGenerator`. Data is loaded asynchronously from a GitHub-hosted CSV and parsed with `csvParse` before being passed to the chart.

HHarsha vardhan reddy Yarmareddy
92% match
Loading thumbnail…

Activity6_Tutorial3.2

This example presents a scatter plot of the Iris dataset, mapping sepal length to the x-axis, petal length to the y-axis, and using distinct symbols to represent the three species. The visualization loads data from a remote CSV file using `fetch` and `csvParse`. D3 v7 scales, including `scaleLinear` and `scaleOrdinal`, position the marks and determine their shapes, while `axisBottom` and `axisLeft` render the axes. A custom legend built with `symbolGenerator` and `symbolsFill` identifies each species. Code is modularized into local ES6 modules for axes, plotting, and legend components.

SShiva Sai Reddy
92% match
Loading thumbnail…

Activity_6 T3

This scatter plot visualizes the Iris dataset, mapping sepal length against petal length and encoding species identity through distinct point shapes. The visualization uses D3 v7's scaleLinear, scaleOrdinal, and symbolsFill APIs to construct the axes and shape-based legend. Data is loaded from a remote CSV file via csvParse and rendered into SVG paths using the symbol generator. The example demonstrates modular code organization with local ES6 modules for axes, scatter plot, and shape legend components.

Bbhavanadupati3@gmail.com
91% match
Loading thumbnail…

Activity 6 tutorial 3.2

This example shows an interactive scatter plot of the Iris dataset, plotting sepal length against petal length and distinguishing species by shape using symbols from `d3.symbol` and the `symbolsFill` scale. The visualization loads CSV data from a GitHub repository, parses it with `d3.csvParse`, and renders axes with `d3.axisLeft` and `d3.axisBottom`. A custom legend clarifies the species shapes. The code uses modular ES6 imports from D3 v7, including `d3.scaleLinear`, `d3.scaleOrdinal`, and `d3.extent`, built within a VizHub framework.

AAamani Chamarthi
91% match
Loading thumbnail…

Activity6_task3.2

This example creates an interactive scatter plot using D3 v7 that visualizes the Iris dataset loaded from a GitHub-hosted CSV file. The chart displays sepal length on the x-axis and petal length on the y-axis, with different symbols representing each iris species. The visualization uses `d3.scaleLinear` for axes, `d3.scaleOrdinal` with `d3.symbolsFill` for categorical shapes, and a custom legend built with `d3.symbol`. The code demonstrates modular ES6 imports, reusable chart components, and dynamic data fetching with `d3.csvParse` and `fetch`.

Iiftequaruddin883@gmail.com
91% match
Loading thumbnail…

Activity6_Tutorial3.2

This example demonstrates a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis. It visualizes the three iris species using distinct shapes via a categorical scale and includes a custom shape legend. The visualization loads CSV data from a GitHub repository, uses d3.csvParse to parse it, and builds the chart with d3.scaleLinear, d3.scaleOrdinal, d3.symbol, and d3.axisLeft/axisBottom. Axes and legend are modularized into reusable ES6 modules.

Ssaimanvith22@gmail.com
91% match
Loading thumbnail…

Activity6_tutorial3.2

This example shows a scatter plot of iris flower measurements, with sepal length on the x-axis and petal length on the y-axis. Each point uses a distinct symbol shape to encode the species of the flower, and a custom legend explains the shape-to-species mapping. The visualization loads CSV data from a remote GitHub repository, parses it with `d3.csvParse`, and renders the chart using modular D3 v7 functions such as `scaleLinear`, `scaleOrdinal`, `symbolsFill`, `axisLeft`, and `axisBottom`. The code organizes its layout through reusable modules for axes, scatter plot, and a shape legend.

Cchandrikachowdary867@gmail.com
91% match
Loading thumbnail…

activity6_t3.2

This interactive D3 v7 scatter plot visualizes the Iris dataset, plotting sepal length against petal length for individual flowers. The visualization encodes the categorical species variable through different point shapes, with a custom legend annotating each shape. Built using a modular structure with `scatterPlot`, `axes`, and `shapeLegend` modules, the example employs D3’s `scaleLinear`, `scaleOrdinal`, and `symbol` APIs to map data to positions and glyphs, while `csvParse` loads the remote CSV data. The chart updates dynamically within an SVG canvas sized to the browser window.

Llingaladineshteja23@gmail.com
91% match