D3 Example

D3 Example

This example visualizes the classic Iris dataset as a scatter plot, mapping sepal length, petal length, and sepal width to the x-axis, y-axis, and circle radius, respectively, with species encoded by color. It demonstrates how to dynamically style D3.js axes via JavaScript by selecting SVG elements and applying font, size, and stroke properties. The approach enables axis styling without requiring external CSS, and is built on an earlier D3 tutorial example. The visualization uses D3’s linear scales and SVG rendering to draw the plot, with axes configured to use compact notation and custom tick counts.

91% match

D3 Example

This scatter plot visualizes the classic Iris dataset, mapping sepal length to the x-axis, petal length to the y-axis, sepal width to the circle radius, and species to color. Rendered as an SVG using D3.js, the chart features axis labels, tick formatting, and a color scale with three categories. The visualization demonstrates a clean, readable design with Poiret One font styling, and the axes include labels for "Sepal Length (cm)" and "Petal Length (cm)".

91% match

D3 Example

This interactive scatter plot visualizes the classic Iris dataset, mapping sepal and petal measurements to positions and size. The visualization is built using D3.js and Model.js to create a reusable, reactive module, with SVG rendering. It responds to window resizing, adjusting its dimensions via CSS while maintaining a dotted border and hover effects on data points. Axis labels and tick formatting are configurable, and the chart is derived from example 106 of the "Introduction to D3.js" screencast series.

D3 Example

This scatter plot of the Iris dataset maps sepal and petal measurements, encoding species with color and sepal width with point radius. It demonstrates a reactive data-joining architecture where scales and axes update automatically via D3’s data binding, with the SVG visualization responding to browser resizing through CSS-controlled dimensions.

D3 Scatterplot

This example visualizes the Iris dataset as a scatterplot, mapping petal length on the x-axis and sepal length on the y-axis. Each flower is rendered as a circle using D3’s selection and data-join methods. The code loads the data via `d3.csv`, scales positions with `d3.scaleLinear`, and adds axes through `d3.axisLeft` and `d3.axisBottom`. The SVG is sized to the full window, and the plot includes customizable margins and tick font sizing.

Aajoua

D3 Scatter Plot

This example displays the classic Iris dataset as a scatter plot, mapping petal length on the x-axis and sepal length on the y-axis. The visualization uses D3 v7’s `select`, `csv`, `scaleLinear`, `extent`, `axisBottom`, and `axisLeft` APIs to load the data, compute scales, and render SVG circles and axes. The plot fills the browser window, with bold tick labels, and the code demonstrates a straightforward data-ink pipeline from CSV parsing to interactive-free SVG rendering.

WWaseem Medhat

D3 Scatter Plot

This example visualizes the Iris dataset as a scatter plot, mapping petal length on the x-axis and sepal length on the y-axis. Each flower is represented by a circle, with positions scaled linearly using d3.scaleLinear and extents from the data. The visualization renders in SVG, drawing circles directly onto an appended svg element. Axes are generated with d3.axisLeft and d3.axisBottom, styled with a 20px font size for tick labels. Data is loaded asynchronously using d3.csv from a remote Gist URL, with numeric parsing applied to all four measurement columns.

Ttverdone

D3 Example

This example visualizes the classic Iris dataset as a scatter plot, encoding sepal length, petal length, and sepal width on the x-, y-, and radius scales, while color encodes species. It demonstrates a “popping effect” by using the CSS `currentColor` keyword so that each circle’s semi-transparent fill and opaque stroke share the same data-driven color, revealing overlaps between marks. Built with D3 v4 and rendered as SVG, the code uses `d3.scaleLinear`, `d3.scaleOrdinal`, `d3.axisBottom`, and `d3.csv` for data loading and scales.