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Sequence explorer - main example (with JSON file)

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EEE2dev
Last edited Dec 19, 2017
Created on Dec 18, 2017

This example uses the D3.js-based sequence explorer library to visualize event sequences from a Meetup group's attendance records. The small-multiple Sankey charts show how different member cohorts (grouped by join time) respond to meetup announcements over time. Each row represents a member subset, while each column shows responder timing. Interactions include clicking to enlarge a chart, toggling percentage views via axis labels, and animating along selected paths. Custom styling highlights members who responded but did not show up in red. The JSON input configures the chart with custom event ordering, corresponding events, and a person-shaped particle animation.

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Sequence explorer

This is the main example showing the features of sequence explorer.

More examples

Link to sequence explorer on github.


The example data contains the attendence record of a data visualization meetup in Munich. The group of members who despite responding didn't show up are custom styled and represented by a red rectangle.

The visualization

The small multiples give you an overview over the data waiting to be explored. Each row corresponds to a subset of members based on their time they joined the group:

  • top row all members
  • second row all members who joined the group before the first meetup took place
  • third row all member who joined the group after the first but before the second meetup took place
  • ...

Each column corresponds to a subset of members based on the time of responding to the meetup announcement. This is just based on the forth meetup response reaction. The fourth meetup was announed three weeks before the actual date:

  • first column all members
  • second column - early responders: members who RSVP'ed yes more than 2 weeks before the meetup
  • third column - normal responders: members who RSVP'ed yes later than 2 weeks before but more than 1 week before the meetup
  • fourth column - very late responders: members who RSVP'ed yes later than 1 week before but more than 3 days before the meetup

The interaction

  • click on one sankey chart to display it in its original size.
  • click again to go back
  • click on the sankey chart at the top left corner (all members - all responders)
  • click on options from the menu on the left to display addition node information or to animate along selected paths (Note that you have to deselect all paths in order to continue interactive exploration.)
  • click on the labels at the x- or y-axis to transition to a percentage view

In this example, a subset of events are specified with correspondingEvents([]) resulting in:

  1. The percentage shown in the tooltip is based on just the specified events

  2. clicking on a (event) label on the y axis shows percentages based on the specified events (in this case: no-show rate). The other labels on the y axis are not selectable.

  3. clicking on a sequence label on the x axis displays a stack bar chart with just the specified events. The remaining labels are not included.

Similar vizzes

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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.

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