D3 Example

100%

✓ Published0🌍 Public

Last edited May 14, 2015

Created on May 12, 2015

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.

AI-generated description

This is a scatter plot of the Iris data set.

The purpose of this example is to show one approach for using Model.js to make reusable visualization modules. This also introduces a way to isolate reusable reactive flows that are reusable between visualizations.

Notice that if you open this in a new window, it responds when you resize the browser window. This is coded in such a way that the visualization size can be controlled via CSS.

This example is a lead-in to The Reactivis Concept, which takes generalization of D3 patterns further.

The code for this is derived from example 106 of the screencast Introduction to D3.js.

Similar vizzes

Loading thumbnail…

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.

CCurran Kelleher

94% match

Loading thumbnail…

D3 Example

This example visualizes the classic Iris dataset as a scatter plot using SVG, with axes and interactive hover effects that highlight individual points. The visualization is built using a reusable reactive architecture called Reactivis, which leverages D3’s data joins and scales to map sepal/petal measurements to x and y positions. It responds fluidly to browser resizing, as the layout dimensions are driven by CSS and propagated through the reactive data flow. The plot is styled with a dotted border, white background, and Poiret One font, and includes axis labels and tick formatting. The code is derived from a screencast tutorial and demonstrates how to structure D3 visualizations for reusability.

CCurran Kelleher

93% match

Loading thumbnail…

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.

CCurran Kelleher

92% match

Loading thumbnail…

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)".

CCurran Kelleher

91% match

Loading thumbnail…

D3 Example

A scatter plot of the Iris dataset displays sepal length against petal length, with point size mapped to sepal width and color mapped to species. The visualization shows how D3.js (version 3.5.5) dynamically styles axes through JavaScript, applying custom font, size, and stroke properties to tick labels, axis labels, and axis lines using `d3.selectAll` and `.style()`. Data is loaded from a CSV file via `d3.csv`, and the SVG rendering uses `d3.scale.linear` and `d3.svg.axis` for scaling and axis generation.

AAndresAnayaIsaza

90% match

Loading thumbnail…

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.

CCurran Kelleher

90% match

Loading thumbnail…

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

90% match

Loading thumbnail…

D3 Scatter Plot

This example visualizes the classic Iris dataset as a D3.js scatter plot, mapping sepal length on the y-axis and petal length on the x-axis. The chart renders as an SVG with circles positioned via linear scales, while axes are drawn using `d3.axisLeft` and `d3.axisBottom`. The code fetches CSV data asynchronously, parses numeric columns, and dynamically resizes the plot to the full window. It customizes tick label styling through CSS and uses a React starter environment.

TTheo-0201

89% match