Idea in short

A Bump Chart is a special form of a line plot. This chart is well-suited for exploring changes in rank over time. Using this chart, you can easily compare the position, performance or rankings of multiple observations with respect to each other rather than the actual values itself.
Bump Chart
These charts are relatively similar to line charts. However, instead of plotting some measures on the y-axis, these charts show the rank. Bump charts have been around for a while, but recently there is an increased interest in these charts. The name originated from a boat race where each boat tries to bump their boat and move up in their respective standing. Bump charts are very useful to compactly highlight trends.

Interpreting a Bump Chart

When a line crosses another line, that is indicative of a change in rank. In other words, a crisscross in a bump chart indicates one entity has surpassed other in absolute terms even when comparison is based on relative ranks. Rank is a powerful feature for any visualization. It is very effective to understand how each of the categorical members perform against the same measure.

When to use this chart?

Ultimately, you could use Bump charts to communicate changes in ranks amongst your dimensions. Likewise, if you wish to show the magnitude and relationships among your dimensions, you can use these charts. If rank is very important, then a Bump chart is the better option. However, if actual and relative magnitudes are more important, then you are better off with a different type of visualisation, such as a line or area chart. In situations where both are important, a sized bump chart is better suited. In practise, you can use a Bump chart can be used to visualise data from social media sources to identify trending topics.


The source code from R-Bloggers was used to create the visualisation.

Think Insights (November 21, 2023) Bump Chart In Data Visualization. Retrieved from
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"Bump Chart In Data Visualization." Think Insights - Accessed November 21, 2023.
"Bump Chart In Data Visualization." Think Insights [Online]. Available: [Accessed: November 21, 2023]