Spine Chart in Tableau
Updated: May 17
What is a spine chart?
Spine chart is a visualization that shows at a glance how one area compares with others across a range of indicators. Summary statistics of each measure such as the average are aligned to form one central line or ‘spine’ on the chart. This spine is the comparator and is usually the national or regional average to which local area values are compared. Most often the vertebrae show the range of values – the minimum, maximum, 25th and 75th percentiles. Area specific values are placed on top of these summaries, allowing the viewer to understand how the area compares with the rest of areas for that measure. Most often, color is applied on the area specific values to represent significance of its value compared to the comparator.
Example of a spine chart.
How do you create a spine chart in Tableau?
Using OECD data on old age dependency ratio computed from people aged 65 and more and people aged 15 to 64. I will show you how to create a spine chart in Tableau. Get the data here to follow along.
Connect to the data to Tableau and pivot it to create the ‘Year’ and ‘Dependency ratio’ columns.
Drag dimension ‘City’ to the rows shelf and measure field ‘Dependency ratio’ to the columns – AVG(Dependency ratio).
Choose ‘Circles’ under marks.
You can filter a single ‘Country’ to minimize the view –have filtered ‘Italy’ for this example.
Compute Country’s average, Max, Min , Lower quantile and Upper quantile of each city as follows;
Drag all the five calculations above to the detail shelf.
Right click on the axis to add the first reference line 'Countries average' as follows;
Next add a second reference line – inform of a band to show the Min and Max values
Executing this we’ve;
Adding the third reference line- inform of a band to show the Upper and Lower quantiles.
Color can be added to show significance of values being compared with the comparator. In this case, have used the following calculation to show cities whose average is above or below country's average.
Adding this calculation to color shelf we’ve;
For more details, you can interact with the live dashboard embedded below.
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