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Data Visualisation Guide

Preserving scales for comparisons

2 minutes read

Pitfalls in dataviz: scales

Small multiples is a visualisation technique in which small copies of the same chart showing different partitions of the data are arranged in a grid. They can be a great way to avoid packing too much data into a single, overcrowded visualisation.

Small multiple line charts showing the share of renewables in household energy consumption in the EU and its member states. Source: buildingsdashboard.eu

But in order to make accurate and meaningful comparisons, the y axis on the small multiples should be kept constant. Otherwise readers not paying attention to the labels on the y axis will quickly draw false conclusions from the small multiples.

Here is an example of the BBC falling into this pitfall.

4 charts showing the Covid hospital patients in England, Scotland, Wales and Northern Ireland. All charts have a different y axis

Source: @RobDunsmore

Keeping the x axis constant on all small multiples should be obvious, but this rule is not always respected, as this example shows:

6 small multiple line charts showing vaccination rates in different age classes in England. The x axis is different for every chart

Source: One in four elderly black people in England still not vaccinated, theguardian.com

Related pages

Breaking scales

Scales in line charts

Width to height ratio

Respecting proportions

Line charts: double y axes

Starting bars at zero

Pitfalls in dataviz: scales