Tableau charts: Packed bubble chart
Updated: Sep 3, 2020
The series, Tableau charts has always focused on one thing, helping Tableau users learn how to create different charts and graphs hence equipping them with different techniques of telling each data story.
Inspired by the mission of this series, this post will show you how to build a bubble chart using Superstores data set pre-packaged with Tableau app. The goal here will be to visualize Sales and Profit performance for different product Sub-Category's.
If you check details on the Show Me tab of your Tableau screen.You will find that for you to create a bubble chart you'll need 1 or 2 dimensions against 1 or 2 measures.
In this article, I'll be using one dimension 'Sub-Category' against two measures 'Sales' and 'Profit' to build a bubble chart.
Building the Chart.
Drag dimension field 'Sub-category' to the Rows shelf.
Drag measure field 'Sales' and 'Profit' to the Columns shelf.
Under the Show Me tab, select Packed bubble , as shown below.
Executing above results to.
Note; Our resulting chart has three negative values. This is because the field Profit was added to the Size tab and you can't represent negative values using Size, to correct this I will change SUM(Profit) level of detail from Size to color and SUM(Sales) level of detail from color to Size. This can be done by selecting the highlighted icons above and choose the replacement. Swapping the fields we have.
Note; In our final chart. Sales have been presented using Size (Therefore, the bigger the bubble, the larger the amount of Sales generated) and Profits have been presented using Color (Therefore, dark blue color signifies huge profits while brown color represents losses). From this bubble chart, users can point out that Tables and Bookcases have made a significant amount in Sales but were not profitable unlike Paper which despite having few Sales remained profitable.
This could prompt the analytics team to conduct further analysis on to what could be the root cause of losses. Could it be the discount are very high, or the shipping is extremely high. I don't know. But conducting further analysis could probably find the answer to this question.
Thanks for reading.