Canvas Scatterplot

100%

Canvas Scatterplot

✓ Published0🌍 Public

Last edited May 18, 2017

Created on May 18, 2017

This example shows a scatterplot of 20,000 randomly generated data points, each positioned on a two-dimensional Gaussian distribution. The visualization animates by redrawing the canvas for 300 milliseconds, creating a flickering effect as the points appear. The code uses the Canvas API directly with `getContext('2d')` for rendering, while employing a custom D3 selection abstraction to bind data to circle elements with `d3.range`, `d3.randomNormal`, and `d3.scaleLinear`. The points are drawn as steelblue circles via `context.arc` and `context.fill` within a repeated timer loop using `d3.timer`.

AI-generated description

Similar vizzes

Loading thumbnail…

Canvas Scatterplot

Two thousand normally distributed points render as a steelblue canvas scatterplot. The code generates data with d3.randomNormal, binds it to custom elements with a d3 data join, and draws the points using Canvas 2D context arcs. A d3.timer repeatedly calls the draw function for 300 milliseconds, clearing and repainting the canvas to animate the visualization. The example uses d3.v4, with linear scales mapping the domain from 2 to 8 onto a 1400 by 750 pixel canvas.

JJverma

91% match

Loading thumbnail…

Canvas Scatterplot

This example renders 20,000 randomly generated points as a Canvas scatterplot, with x, y, and radius values sampled from normal distributions. It demonstrates a color-picking technique for interaction: a hidden canvas draws each point in a unique RGB color, and the visible canvas draws them in steelblue. On mousemove, the code calls Canvas `getImageData` on the hidden canvas to identify the point under the cursor, then displays a tooltip with its coordinates and radius. It uses d3.scaleLinear for axes and d3.timer for a brief animation loop.

JJverma

91% match

Loading thumbnail…

Scatter Plot

This scatter plot displays ten randomly generated data points distributed across a two-dimensional plane, with each circle’s position determined by linear scales mapping the data range to pixel coordinates and its radius scaled proportionally. The visualization uses D3 v4 to create an SVG, with axes generated via `d3.axisBottom` and `d3.axisLeft`. The code applies `d3.scaleLinear` for both x and y positioning, `d3.scaleOrdinal` with `d3.schemeCategory20` for coloring each circle, and a separate radius scale. The data originates from `d3.range(10).map(Math.random)`, producing a simple, uncluttered chart that highlights basic scatter plot construction without external data files.

BBerengerCunillera

81% match

Loading thumbnail…

D3: Scatterplot!

This interactive scatterplot displays 50 random data points on Cartesian axes, with each circle colored blue or red depending on whether its x-coordinate falls in the left or right half of the plot. Clicking the “Randomize” button generates a fresh dataset and smoothly animates the points, axes, and color updates over two seconds. The visualization is built with D3 3.5.5, using the `d3.scale.linear`, `d3.svg.axis`, and `transition().duration(2000)` APIs, and renders entirely as SVG. The code derives from Scott Murray’s examples, forked from earlier gists by anonymous and jalapic.

MMissHanJ

81% match

Loading thumbnail…

Untitled

This example shows a simple scatter plot of 100 randomly generated points, each positioned on a 500-by-500 pixel SVG canvas. The visualization uses D3.js v4 scales and axes to map linear domains to screen coordinates, with red circles drawn for each point. The code appends an SVG group to the page, translates it by a 40-pixel margin, and uses `d3.scaleLinear` for both the x- and y-axes, which are rendered via `d3.axisBottom` and `d3.axisLeft`. Data is created in a loop using `Math.random()`.

Ffay Alomar

79% match

Loading thumbnail…

part 1, Zoom and Panning with D3.js and canvas,

This example shows a canvas-based scatter plot of 10,000 random data points, with the page built for future brushing interactions. It uses D3.js v4 to create SVG axes and labels, while rendering the points themselves on a separate HTML5 canvas element for performance. The code initializes linear scales for both x and y dimensions, draws the axes with `d3.axisBottom` and `d3.axisLeft`, and plots each point using the Canvas API’s `arc` and `fill` methods. The canvas is positioned over the SVG using CSS classes, demonstrating a hybrid rendering approach.

FFrissAnalytics

79% match

Loading thumbnail…

Scatterplot

A scatterplot displays 50 randomly generated data points, mapping each point’s x- and y-coordinates against linear scales with axis tick marks. The SVG rendering, created with D3.js, uses a linear scale for both axes and a third linear scale to map y-values to circle radius (ranging from 2 to 5 pixels). The visualization is animated, as the dataset is regenerated with new random values each time the page loads, and the circles are drawn without transitions between states. The code explicitly uses D3’s `d3.scale.linear` and `d3.svg.axis` APIs to construct the plot.

MMrajyalakshmi

79% match

Loading thumbnail…

Reusable scatter plot

This reusable scatter plot displays 200 randomly generated data points using D3.js v4, with interactive buttons that trigger animated transitions. The visualization initially renders normally distributed points as semi-transparent blue circles, while the "Change Data" button regenerates the dataset and smoothly transitions the circles to new positions with updated axes. The "Change Color" button toggles the circle fill between blue and red using D3's transition and ease functions. The example demonstrates reusable chart patterns with SVG rendering, including linear scales, axis generators, and data-binding techniques.

EEfratVil

79% match