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This animated scatter plot visualizes the Iris flower dataset, cycling through four measurement columns as the x-axis every two seconds. Using D3 v6, it renders SVG circles and axes via a reusable scatterPlot function, scaling with the window dimensions. The visualization updates x-axis mappings via `setInterval`, calling the plot with new data accessors, while axes are redrawn using `axisBottom` and `axisLeft`.

Sskmriyaz0786@gmail.com

Fork of Reusable D3 Scatter Plot

A scatter plot visualizes the Iris Dataset, with points representing flowers and axes mapping petal width against sepal length. Built with D3 v6, it uses `scaleLinear`, `axisLeft`, and `axisBottom` to render axes and SVG circles for data marks. The x-axis mapping cycles through four dataset columns every two seconds via `setInterval`, animating the plot's perspective. The chart is implemented as a reusable function following the "Towards Reusable Charts" pattern, with animated updates triggered by re-calling the plot on the same SVG selection.

OOska Cheng

Fork of Reusable D3 Scatter Plot

This example shows the classic Iris Dataset as an animated scatter plot, cycling through four measured attributes every two seconds to compare sepal and petal dimensions. It uses `d3.scaleLinear`, `d3.extent`, `d3.axisLeft`, and `d3.axisBottom` to render axes and circles in SVG. A reusable chart function with getter/setter methods updates the x mapping in response to a `setInterval` timer, calling the plot again to refresh marks. Styling uses the Share Tech font with a full-window layout.

Ssirenajbpearl@gmail.com

Fork of Reusable D3 Scatter Plot

A reusable scatter plot displays the Iris Dataset, cycling through four measured attributes as the x-axis variable on a two-second interval. The visualization, built with D3 v6 and rendered as SVG, uses `scaleLinear` and `extent` for scales, `axisLeft` and `axisBottom` for axes, and `selection.join` to bind data to circles. The plot's dimensions adapt to the browser window, and its configuration is updated via a `setInterval` callback that changes the `xValue` accessor and re-invokes the chart function.

Bbepnye@gmail.com

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This interactive scatter plot animates through the four dimensions of the classic Iris Dataset, cycling the x-axis among petal width, sepal width, petal length, and sepal length every two seconds while keeping sepal length on the y-axis. The visualization uses D3 6.7.0 with a custom reusable `scatterPlot` module that leverages `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to render SVG circles and axes. A `setInterval` loop updates the x-value binding, redrawing the plot idempotently through the SVG `join` operation, while the Share Tech font styles the text.

Ssd2beatles

Fork of Reusable D3 Scatter Plot

This animated scatter plot cycles through four Iris dataset measurements, using petal width, sepal width, petal length, then sepal length as the x-axis. Built with D3.js, it uses `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` APIs. The SVG elements are joined and updated every two seconds via `setInterval`, re-calling the reusable scatter plot function. The Iris dataset is loaded as CSV from a GitHub gist, with axes and circles rendered in the Share Tech font.

Oowenking2710@gmail.com

Fork of Reusable D3 Scatter Plot

This is a reusable scatter plot that visualizes the Iris Dataset, cycling through different feature combinations every two seconds. The chart maps petal width against sepal length initially, then rotates through other attributes using a `setInterval`. Built with D3 v6, it uses `scaleLinear`, `extent`, and `axisLeft`/`axisBottom` to render axes, with circles positioned via the modular `scatterPlot()` function. The SVG output animates smoothly, updating both data mappings and axis scales with each interval.

JJetlinZ

Nnagasai.mandalapu@gmail.com

Fork of Reusable D3 Scatter Plot

This example shows the Iris Dataset as an animated scatter plot, cycling through different pairings of flower measurements every two seconds. The plot is built with D3 v6, using `scaleLinear` for axes, `axisLeft` and `axisBottom` for ticks, and a reusable chart function that updates circles and axes in response to changing data accessors. The visualization uses SVG rendering and a custom `setInterval` loop to switch between four measurement columns.