Grouped Bar Chart: Definition, Examples and Best Use Cases

A basic bar chart is one of the most popular chart types for showing a distribution of data points. You’ve seen them used everywhere, from your Microsoft Excel to data visualization tools such as Power BI or Tableau. A grouped bar chart is the upgraded version of this chart type.

Today, we’ll show you when to use bar charts, and what to avoid.

What is a grouped bar chart?

A grouped bar chart (also called a clustered bar chart or a grouped bar graph) is a visualization type that shows data using rectangular bars for multiple categorical variables instead of one. Multiple bars are grouped based on a particular category or group.

Every group represents a set of related data points, and within each group, bars are color-coded or shaded differently to designate a subgroup. The height or length of each bar represents its numeric value.

Best use cases for a grouped bar chart

Grouped bar charts are best for situations where you need to compare multiple categories and subcategories side by side. Here are some specific examples you can use to get inspired.

Comparing subcategories within categories

Comparing sales performance of different products (subcategories) across different regions (categories). Each group is a different region, while each bar in a group denotes one product and its sales performance.

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Tracking changes over time for multiple categories

Showing the annual growth of revenue for different product lines (subcategories) over several years (categories). Each group in a time series is a year, and bars are the different product lines.

Showing survey or feedback results

Showing customer satisfaction levels (e.g. satisfied, neutral, dissatisfied) across different service departments (categories). This chart shows how each department performs in terms of customer satisfaction.

Comparing performance metrics across departments or teams

Showing team performance based on different metrics such as productivity or efficiency (subcategories) compared across different teams (categories).

grouped bar chart

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Comparing different methods or techniques across several conditions

Displaying the effectiveness of different marketing strategies (subcategories) applied to different markets (categories).

Showing demographic comparisons

Showing a demographic breakdown (subcategories male and female) of customers or users across different regions or countries (categories).

Comparing test results across conditions

Showing student performance (subcategories: math, English, science, etc.) across different schools or grades (categories).

Financial data analysis

Comparing income streams from different sectors (subcategories) for different fiscal years (categories).

When not to use grouped bar charts

Like any other visualization type, grouped bar charts have their limitations. Here are the situations when you should avoid them.

With complex relationships

If you want to show complex correlations or hierarchical data, grouped bar charts won’t work as well. Instead, use a heatmap or a stacked bar chart.

When you have too many groups or bars

With too many categories or bars, seeing the individual values and metrics can be difficult. Instead, use a stacked bar chart or a dot plot.

When showing continuous data

If your dataset shows data in a continuous line, line charts or scatter plots are better for showing trends or relationships over time.

When you have too many data points per group

With too many bars in each group, it becomes difficult to distinguish between them, even with different bar colors. Instead, use a heatmap or a box plot.

For percentage-based comparisons

When you want to show parts of a whole in a side-by-side comparison, a pie chart or a stacked bar chart is a better choice.

Top tips for using grouped bar charts

If you want your grouped bar charts to communicate data clearly and effectively, here are some useful guidelines.

Limit the number of groups and categories

Keep the number of groups and bars for each chart to a handful. If you have too many, the chart won’t be readable.

Use contrasting colors

Each bar in a group should have different and contrasting colors. This allows the reader to differentiate between categories at a glance. Don’t worry about picking something for a color palette.

Add a clear legend

Explain to the reader what each color and bar means in a legend next to the chart. Alternatively, use a tooltip that shows once the reader hovers over the bars and numerical values.

Align axes and labels properly

Make sure that the x-axis and y-axis are aligned with the labels for groups and bars. It should be easy for the reader to follow horizontal and vertical axes.

Sort groups logically

Arrange the groups in a logical order, e.g. descending/ascending values or logical groupings. This makes it easier for the audience to compare values in similar groups.

Mind your spacing

Groups and categories should have enough space between them to avoid them from merging. The white space makes it easier to read the chart and avoids confusion.

Label your bars with values

Assign numerical values to your bars with actual data points to make the charts more readable.

Avoid having too many colors

Having too many colors in a grouped bar chart makes it difficult to read and understand. Stick to a handful of colors provided in the chart template in the visualization tool that you’re using.

Add relevant annotations

Add annotations for key data points and numeric values to draw the reader’s attention to information that they should not miss.

Use consistent bar widths

Each vertical and horizontal bar should have the same width to avoid confusing the reader.

Visualize your data with Luzmo

If you want to show dashboards in your software, there is no better choice than Luzmo. It’s not just our choice of visualization types, even though we have more than 50 you can use for different goals and data types.

Luzmo embeds directly in your product with a great API, connects to various data sources, and is easy to customize, so it looks and feels like it belongs in your tool. No Python or Javascript code required, no complex pricing and the setup takes just a few hours.

‍Book a free demo with our team to learn more!