Relationship

Parallel sets plot

Shows frequencies across combinations of categorical dimensions using connected bands.

Plot
Relationship
Composition

What it answers

How are categories associated across multiple dimensions?

Shape: Categorical axes with width-scaled bands
What it shows: Frequent category combinations and transitions.

Example

The question

How do plan, region and renewal combine across our customers?

Customers by plan, region and renewal (parallel sets, hundreds)

Three category axes (plan, region, renewal) joined by bands sized by customers. Basic 55, Plus 34, Pro 11 hundred; Nordics 60, Baltics 40; 74 renewed and 26 left. Baltic customers leave more often (35% against 20%).

Illustrative data. It belongs to no company.

When to use it

Use it when

Multiway categorical composition.

Avoid it when

When numeric individual trajectories are required.

How to read it

Read category axes and track width-scaled bands across them.

Note

Different from parallel coordinates for numeric profiles.

The data you need

Layout: Wide path-count table
Fields: Stage1,Stage2...: category text; Count: nonnegative number
One row is: One category path across stages with its frequency. What is the grain?
Rules: Declare stage order and aggregate identical paths. Keep counts nonnegative.
Optional: Raw alternative: EntityID,Stage,Category. Edge-only data may lose complete path identity.
Preparation: Validate the input grain and missing values. Declare stage order and aggregate identical paths. Keep counts nonnegative.
Units: Use the measured variable's stated unit consistently. No denominator is implied unless the value is a rate or proportion.

A wide table: one row per item, with a separate column for each measure or period.

Worked example

Paths A-B-D30 and A-C-D20 create bands 30 and 20. B carries 60% of the total path count.

Stage1	Stage2	Stage3	Count
A	B	D	30
A	C	D	20

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