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Fork of Scatter Plot

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PPoojaThandra
Last edited Mar 10, 2023
Created on Mar 10, 2023
Forked from Scatter Plot

A scatter plot visualizes the classic Iris Dataset, showing sepal length against petal length for 150 flowers across three species. Circles are plotted without color or legend, with fixed 10-pixel radii. The visualization uses d3-fetch’s `csvParse` to load and parse the data, d3-scale’s `scaleLinear` for axes, and d3-axis’s `axisLeft` and `axisBottom` for labeled axes. The implementation is modular, with separate files for axes, scatter plot, and main visualization logic.

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A scatter plot of the Iris Dataset.

MIT Licensed

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This visualization displays the classic Iris Dataset as a scatter plot, mapping sepal length on the x-axis against petal length on the y-axis, with each of the 150 flowers represented as a circle. The code uses D3 v7’s `scaleLinear`, `extent`, and `axisLeft`/`axisBottom` functions to position points and render labeled axes. Data is loaded from an external CSV file and parsed with `csvParse`, then rendered using D3’s data join pattern with circles.

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This scatter plot displays the classic Iris dataset, mapping sepal length along the x-axis and petal length along the y-axis. Each flower specimen is rendered as a circle, with all 150 data points plotted without axes or gridlines. The visualization uses D3 v7, loading data via a CSV fetch and parsing it with `csvParse`. The `scatterPlot` module constructs linear scales using `scaleLinear` and `extent`, then positions circles using the `join` API based on the selected measurement columns.

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This example plots sepal length against petal length for the Iris Dataset, with each flower represented as a circle. The visualization demonstrates a reusable scatter plot module composed with custom axis and labeling functions. It uses D3 v7 APIs including `scaleLinear`, `extent`, `axisLeft`, `axisBottom`, and data joins via `selectAll` and `join`. The code loads the CSV data with `fetch` and `csvParse`, then renders the plot across the full browser window, coloring points by species.

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A scatter plot of the Iris Dataset uses sepal length on the x-axis and petal length on the y-axis, with circles colored and positioned by species. No axes are rendered. The visualization loads data from a CSV file using the Fetch API and `d3.csvParse`, then applies `d3.scaleLinear` and `d3.extent` to map data values to pixel coordinates. Each data point is rendered as a circle with a fixed radius via `d3.selectAll` and `join`.

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This scatter plot visualizes the Iris Dataset, showing the relationship between sepal length and petal length across three species. The chart displays colored circles without axes, using D3 v7's `scaleLinear` and `extent` functions to map data values to SVG coordinates. The visualization is made responsive by applying a `viewBox` attribute instead of fixed width and height, while CSS `clamp` controls the SVG's displayed size. Data is loaded from a CSV file and parsed with `csvParse` before rendering.

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Fork of Scatter Plot Simple

This example visualizes the Iris Dataset as a scatter plot, mapping sepal length to the x-axis and petal length to the y-axis, with each flower represented by a fixed-radius circle. The plot has no axes, so it focuses purely on the distribution and clustering of the three species. The visualization uses D3 v7, loading data with `csvParse`, mapping values to pixel coordinates via `scaleLinear` and `extent`, and rendering circles through `selection.selectAll` with a `join`. The chart spans the full browser window, with data fetched asynchronously on initial render.

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This scatter plot visualizes the Iris dataset, showing sepal length on the x-axis and petal length on the y-axis, with each flower species represented as a circle. The visualization uses d3.scaleLinear for axis scaling and d3.extent to compute data domains. Axes are drawn with d3.axisLeft and d3.axisBottom, while the SVG circles are created dynamically through data joins. Data is loaded asynchronously via fetch and parsed with d3.csvParse.

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Fork of scatter plot

This scatter plot visualizes the Iris dataset, showing sepal length on the x-axis and petal length on the y-axis, with each flower species represented as a circle. The visualization uses d3.scaleLinear for axis scaling and d3.extent to compute data domains. Axes are drawn with d3.axisLeft and d3.axisBottom, while the SVG circles are created dynamically through data joins. Data is loaded asynchronously via fetch and parsed with d3.csvParse.

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