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Chart best practice

General advice for data visualisation.

Please reach out to the contributors at the bottom of this page if you have any questions or feedback.

Reduce clutter

Only include what is necessary. Remove chart junk, e.g. backgrounds, redundant labels, unnecessary colours, effects, bold and heavy lines, etc.

Format for simplicity

Format your charts to make them easier to understand and more aesthetically pleasing.

Grid lines

Grid lines help the user compare key thresholds. Without them, the mind has to draw an imaginary line to make comparisons.

No grid lines.
No grid lines.
Grid lines.
Grid lines.

Labels

Labels supplement the visual representation by displaying exact values and are valuable for static charts that don’t have tooltips on hover.

No labels.
No labels.
Labels.
Labels.

Axes

Format axes to clearly show the scale and intervals of your charts. Make sure the axis labels and spacing are easy to read.

Add clarity

Make your chart easy to understand by clearly showing people what it represents.

Chart titles & descriptions

Use a title to frame a chart’s story, purpose, and meaning.

Use a subtitle/description to add additional context to your chart, e.g. how and when the data was collected.

Describe the query.
For monitoring data without bias.
Explain the insight.
Use data to tell a story.

Sorting

Sorting can help people make sense of your charts, by telling the story in a meaningful order.

Alphabetical.
Quickly find a category.
Ascending.
Tell a story.
Descending.
Compare categories.

Annotations & comments

Add context and perspective to your chart by annotating data or adding comments.

Highlight what’s important

Too much information can be overwhelming and hard to make sense of. Make critical insights and data points stand out by visually directing your audience’s attention to the most important part(s).

Conditional formatting.
Give data that is above or below defined thresolds a distinct colour.
Reference lines.
See if you are on target to reach a goal.
Highlight trends.
Show patterns in your data.
Project forecasts.
Predict what might happen next.

Directing attention to these methods can increase the ‘dwell time’ of your reports, leading to a better understanding of the story your data tells.

With contributions from:

Thomas Bove