How to Build a Curvy Bump Chart with Bars

This step-by-step tutorial walks through how to create a Bump Chart with Bars and Curved Lines. It was originally published by Brian Moore in the "Totally Useless Charts" series of his blog Do Mo(o)re With Data on January 25, 2022. It's cross-posted here with his permission. Brian is a Tableau Visionary and Tableau Evangelist for Cleartelligence.

Ok, so this chart may not be totally useless, but I’m going to keep it in this category because it’s something I would never build at work. I love a good bump chart, but there is one major limitation with traditional bump charts. They are great for displaying changes in rankings over time, but what about the data driving those rankings. How much has a value changed from one period to the next? How much separation is there between #1 and #2? Surely a bar chart would be better for that type of insight right? Well, in this tutorial, we’re going to walk through building a chart that combines all of the benefits of bump charts and bar charts, and with some fancy curves to boot.

I’m sure I’m not the first to build this type of chart, but the first time I used it was in my 2020 Iron Viz Submission to show Happiness Scores by continent over time.

Looking back, there are definitely some things I would change about this, and I’m going to address those in the chart we are about to build. The data we’re going to be using for today’s walkthrough is on Browser Usage Share over the last 13 Years (showing usage at every 3-year increment). You can find the sample data here, and the sample workbook here. This is what we’re going to build.

Building Your Data Source

Our data source (on the Data tab in the sample file) contains 5 fields. We have a Time Period (our Year field), a Dimension (the Browser), and a Value (the Share of Usage). There are also 2 calculated fields in this file. These could be calculated in Tableau using table calcs, but because of the complexity of some of the other calculations, we’re going to make it as easy as possible and calculate these in the data source. The [Period] field, is just a sequential number, starting at 1, and it is related to the Date field. The [Rank] field is the ranking of each Browser within that period.

On the next tab (Densification), we have our densification data. There is a [Type] field, which will allow us to apply different calculations, in the same view, for our bars and our lines. There is a [Points] field, which will be used to calculate the coordinates for all points for both the bars and the lines. And there is a [T] field, which will be used to draw the sigmoid curves connecting each of the bars.

If you are building this with a different set of data, just replace the Date, Browser, and Share fields in the Data Tab. The calculated fields should update automatically.

Now for joining this data. We are going to do two joins in the Physical layer in Tableau. We are going to do a self-join on the Data to bring in the rank for the next period, and we’re going to join to our densification data using a join calc.

To get started, connect to the Sample Data in Tableau and bring out the Data table. Then double-click to go into the physical layer. Now drag out the Data table again. First, join on [Browser]. Then create a join calculation on the left side of the join, [Period]+1 and join that to [Period]. Then set it as a Left Join. It should look something like this.

Now bring out your Densification table, and join that to the Data Table using a join calculation, with a value of 1 on both sides of the join. Like this.

Now go to a new worksheet and rename the following fields.

Period(Data1) change to Next Period

Rank(Data1) change to Next Rank

I would also recommend hiding all other fields from the Data1 table to avoid confusion later on.

Building the Bars

To build the bars in this chart, we are going to use polygons. So we’ll need to calculate the coordinates for all 4 corners for each of our bars. Let’s start with Y, since that one is a little easier.