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sequence explorer - small multiples

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EEE2dev
Last edited Dec 19, 2017
Created on Jan 22, 2017

This example uses small multiples to compare state sequences across regions and age groups. Each panel shows a horizontal Sankey-style flow from source to target, with line thickness proportional to the value column. Transitions are encoded with color-coded ribbons linking categorical states (weather, sports, health, travel), and the small-multiple layout lets viewers scan differences in flow volume across the United States, India, Germany, and the United Kingdom, split by age bands. Built with D3 v4, it reads the CSV from a gist.

AI-generated description

Sequence explorer

This is an example showing the features of sequence explorer. With .percentages([]) (documentation) you can specify different percentages. It affects the tooltip percentages shown. Also the first element in the array determines the percentages shown when you click on a label of the y axis.

More examples

Link to sequence explorer on github.


  • example data (simulated) contains user click stream data by age and continent. Node info contains information about clients environment (browser, operating system, device)
  • you can zoom in into one chart by clicking on it
  • to go back, click again
  • tooltip of nodes additionally show 4 percentages

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Sequence explorer - single chart (with JSON file)

This example demonstrates a single-chart sequence explorer visualization built with D3 v4, loaded from an external JSON file. The chart visualizes sequential event flows, with events ordered along the y-axis using the `eventOrder` method (home, product, search, account, other) and the x-axis labeled as "visit" via the `sequenceName` setting. The JSON data defines a directed graph of transitions between events, with values representing the volume of each step. The visualization is instantiated by calling `sequenceExplorer.chart("sequence1.json")` and rendered into a div in the body. This approach highlights the sequence explorer's ability to depict multi-step event pathways, similar to a sunburst but in a linear, flow-based layout, making it easy to compare pros and cons against alternative visualization methods for the same dataset. The data is derived from Kerry Rodden's sunburst example, and the chart is configured to reorder event categories on the y-axis and customize tooltip labels. The single chart version keeps all event sequences in one view, useful for tracking navigation flows or funnel analysis.This example demonstrates how to create a **single-chart sequence explorer** using D3 v4 and data loaded from an external JSON file. The chart visualizes sequential categorical data—here, sequences of website events such as "home", "product", "search", and "account"—as a Sankey-style flow diagram. Each row represents a step in the sequence, and the width of the links corresponds to the number of visits, making it easy to identify common paths and drop-off points. The code shows how to initialize the chart with a JSON file, customize the event order on the y-axis, and rename the x-axis for tooltips. The data is derived from Kerry Rodden’s sunburst example, allowing for a direct comparison between the two visualization approaches for the same dataset.

EEE2dev
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