Density Contours II

100%

Density Contours II

✓ Published0🌍 Public

Last edited Oct 20, 2018

Created on Oct 20, 2018

This example visualizes the density of diamonds by carat and price, using colored contour paths to show point density. It plots the data from `diamonds.tsv` on logarithmic x and y axes, with a gradient from YlGnBu. The code uses `d3.contourDensity` for kernel density estimation, `d3.geoPath` to render the contours as SVG paths, and `d3.axisBottom` and `d3.axisLeft` for axes. The chart also includes labeled axis text for "Carats" and "Price (USD)".

AI-generated description

An example of d3-contour for density estimation.

forked from <a href='http://bl.ocks.org/mbostock/'>mbostock</a>'s block: <a href='http://bl.ocks.org/mbostock/7f5f22524bd1d824dd53c535eda0187f'>Density Contours II</a>

gpl-3.0 Licensed

Similar vizzes

Loading thumbnail…

Density Contours II

This example demonstrates density estimation of diamond prices and weights using contour lines. The visualization shows the distribution of carat and price data points, with concentric filled contour regions colored on a yellow-green-blue sequential scale to represent point density. The code uses d3.contourDensity for density estimation and d3.geoPath to render the resulting contour polygons as SVG paths. Data is loaded from a TSV file, with logarithmic scales applied to both axes for carat and price.

Mmbostock

92% match

Loading thumbnail…

Diamonds

This scatter plot displays the relationship between diamond mass in carats and price in US dollars. The visualization uses a canvas overlay to draw semi-transparent blue circles that accumulate over time, creating a density effect where overlapping points become darker. A static SVG layer renders the grid and axes, with the x-axis labeled "Mass (carats)" and the y-axis labeled "Price (US$)". The code uses d3.tsv to load the data, d3.scaleLinear for both axes, and d3.axisLeft and d3.axisBottom for the grid and ticks. The data is shuffled and drawn progressively in batches of 500 using a d3.timer, with the canvas context employing a "multiply" composite operation to blend overlapping points.

Mmbostock

81% match

Loading thumbnail…

Diamonds II

This scatterplot of 1,200 diamonds reveals the distribution of carat mass against price in US dollars, using two logarithmic axes to accommodate the data’s wide range. The code first draws a white-lined grid and labeled axes via `d3.axisLeft`, `d3.axisBottom`, and the `d3.scaleLog` scale. It then animates the points: `d3.shuffle` randomizes the data, and a `d3.timer` loop repeatedly pops 500 diamonds per frame, drawing each as a fixed-size rectangle on the Canvas via `context.fillRect` with a multiplicative blend mode.

Mmbostock

79% match

Loading thumbnail…

Scatter Plot for the Diamond Data Set

This scatter plot visualizes the relationship between diamond carat and price, with each point colored by cut quality (Fair, Good, Very Good, Premium, Ideal). The code loads a CSV dataset from a GitHub gist and renders SVG circles using D3 v6’s `select`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom`. Axes labels for “Diamond_Carat” and “Diamond_Price” are appended as text elements, with a color mapping function defining per-cut hues.

KKevin Raj

78% match

Loading thumbnail…

Diamonds - d3fc version

This example visualizes 53,000 diamonds as a scatterplot of price against carat weight, rendered as red points on a Canvas. The d3fc library’s `seriesCanvasPoint` and `chartCartesian` components handle the plotting, with scales and extents from `d3.scaleLinear` and `fc.extentLinear`. Data from the diamonds.tsv file is batched into chunks of 500 points via a `d3.timer`, shuffling the dataset each frame to animate the progressive rendering. The chart re-renders responsively on window resize.

CColinEberhardt

77% match

Loading thumbnail…

Contour Plot II

This example visualizes the Goldstein-Price test function using a grid of 240 by 125 sampled values, displayed as a series of 20 logarithmic contour thresholds. The contours are rendered as filled SVG paths with a blue-green-yellow color scale. The code uses `d3.contours` to compute the isolines and `d3.geoPath` with `d3.geoIdentity` to project them, while `d3.scaleLog` and `d3.interpolateYlGnBu` define the color mapping. The data is generated procedurally from the mathematical function.

MMorganhaoyu

74% match

Loading thumbnail…

Contour Plot II

This example visualizes the Goldstein–Price function, a common test function for optimization, as a set of 20 logarithmic contour levels. The contours are drawn with SVG paths, each filled with a color from the YlGnBu interpolated color scale to indicate value. The underlying grid of 240×125 values is computed by sampling the function across its domain. The code uses `d3.contours` to generate the contour geometry, `d3.geoPath` with `d3.geoIdentity().scale()` to project the coordinates to the SVG canvas, and a `d3.scaleLog` for threshold mapping.

Mmbostock

71% match

Loading thumbnail…

Old Faithful Contour Plot

This contour plot visualizes the density distribution of data points using a white-to-teal gradient, with darker regions indicating higher point concentrations. It reads data from a CSV file and displays it as smooth, layered density contours over a coordinate grid. The visualization uses d3.contourDensity to compute density values, d3.geoPath to render the contour shapes, and d3.scaleLinear for the color mapping. The axes are generated with d3.axisBottom and d3.axisLeft, and the data is plotted in an SVG canvas.

PPatricijaC

71% match