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Simple comparisons Clustered bar chart

A clustered bar chart uses side-by-side bars of different colours to show values for different series within categories.

Important information:

Visual styles for clustered bar charts are detailed in our chart style guide on Notion (opens in a new tab) .

An example of a clustered bar chart with two series.

When to use a clustered bar chart

You can use this type of chart for comparing a small number of series across several categories.

Warning:

Clustered bar charts can become difficult to interpret when they include too many categories within each cluster.

Limit the number of categories to a maximum of five per cluster, especially if the data in these categories is not continuous.

Deciding primary and secondary categories

In clustered bar charts, it is easier to compare values within the same cluster than across different clusters.

When structuring your chart, cluster together the bars that you want your audience to compare or that have the smallest differences between values.

For example:

  • if you are comparing life expectancy for males and females across the four nations of the UK, you could group bars by sex or by nation
  • to focus on comparing males and females within each nation, you could group the data by nation, with separate bars for male and female within each cluster
  • to focus on comparing life expectancy across nations, you could group the data by sex, with each bar representing a different nation within each cluster

Example of a clustered bar chart focusing on comparing between sex

Example of a clustered bar chart focused on comparing between nations

Continuous data

Avoid using clustered bar charts to plot continuous variables, such as age, on the axis. This can make it harder to see trends in the continuous data.

If you are showing continuous data, consider alternative chart types, such as a stacked bar chart or range plot.

This does not apply to plotting continuous variables within each cluster of your chart.

Ordering

Arrange both the clusters and the bars within them in a logical order.

Read our Ordering in charts guidance (opens in a new tab)  for further instructions.

Alternatives

Before choosing a clustered bar chart, consider if your data could be presented more clearly using an alternative chart type.

Warning:

Some of these alternative charts are currently not available in the ONS Chartbuilder tool. If you are interested in using one in your publication, let us know during an initial content support meeting (CSM).

When showing parts of a whole

If your categories represent components of a total, a stacked bar chart may be easier for users to interpret the data. For more information, read our Stacked bar charts guidance. (opens in a new tab) 

When comparing two series

If you are using a chart to compare two series, there are many options that may be more appropriate than a clustered bar chart.

A range plot

A range plot highlights differences between two values while also showing the absolute values. A variation of a range plot, called a comet plot, can be used to display changes over time.

A bar chart with reference marker

You should use this when one series is an average or reference value.

A bar chart showing deviation

You can use a bar chart to plot the difference between two values across categories. This emphasises the difference between two values, though it does not show the absolute values. This is an example of a derived variable.

For more information on derived variables, read our Data visualisation principles guidance (opens in a new tab) .

When comparing a large number of categories for two or three series

You should use a split bar chart to compare a large number of values across two or three series.

When comparing a large number of series

To compare a large number of values for four or more series, use a small multiple bar chart or column chart.