Visualizing Distributions

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Visualizing Distributions

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Last edited Oct 22, 2018

Created on Oct 22, 2018

This example compares four chart types for visualizing a single data distribution: swarm plot, pile plot, histogram, and boxplot. Using d3.forceChart, the swarm and pile plots position individual data points with a force-directed layout, while the histogram aggregates counts into bins via d3.layout.histogram, and the boxplot summarizes quartiles using d3.scale.quantile. All charts render as SVG within a shared grid, sharing the same y-axis scale for direct comparison. The underlying data comes from 700 random log-normal values.

AI-generated description

A few ways to visualize 1D distributions.

Swarm and pile plots show all the data points but can't be used when there are a lot of data points. Histograms and boxplots work for any number of data points since they are visualizing summary statistics. Histograms provide more information than a boxplot. Boxplots fit in small spaces, making them nice for comparing many distributions side-by-side.

Other chart types for 1D distributions: violin plot, kernel density, empirical CDF.

The d3.forceChart() plugin is used for the swarm and pile plots; d3.layout.histogram() for the histogram; d3.scale.quantile() for the quartile summary statistics used in the boxplot.

forked from <a href='http://bl.ocks.org/armollica/'>armollica</a>'s block: <a href='http://bl.ocks.org/armollica/0f28622e38434b04907d768df6cec684'>Visualizing Distributions</a>

mit Licensed

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