Relationship

Three-dimensional scatterplot

Positions observations with three numeric coordinates.

Plot
Relationship
Multivariate exploration

What it answers

Is there structure across three numeric dimensions?

Shape: Points on three numeric axes
What it shows: 3D clusters and spatial outliers.

Example

The question

How do price, rating and sales combine across our products?

Products by price, rating and units sold (3D scatter)

Points float above a price by rating floor, with a drop line showing units sold. Depth makes exact reading hard, so the table and rotation matter. Higher-rated, mid-priced products tend to sell most.

Illustrative data. It belongs to no company.

When to use it

Use it when

Exploring genuinely three-dimensional relationships.

Avoid it when

When a 2D projection answers the question or occlusion hides data.

How to read it

Rotate or inspect projections and read all three coordinate axes.

Note

Viewpoint and occlusion can hide patterns.

The data you need

Layout: Long table
Fields: X: number; Y: number; Z: number
One row is: One observation with three numeric coordinates. What is the grain?
Rules: Keep all coordinates paired. State units and coordinate conventions.
Optional: Optional ID,Group,Size.
Preparation: Align measurements by observation ID, select relevant variables and handle missingness. Scale or standardise only where the analytical method requires it.
Units: State the unit of every coordinate/variable. A unitless transformed or standardised scale must be identified; no common denominator is assumed.

A long table: one row per observation, few columns. New data adds rows.

Worked example

Points(2,10,5),(4,100,8),(6,50,6). The second has the largest Y and Z; confirm via labels or projections.

X	Y	Z
2	10	5
4	100	8
6	50	6

All charts in the library