Heat maps are a great way to visually pick up on trends, patterns, or anomalies in your data. They’re also extremely easy to create in Tableau! In this blog, I will be taking you through the steps to create a heat map comparing profit across different months and years from the Superstore dataset in Tableau.


Step 1: Bring in your columns

This is what you want displayed across the top of your heat map. In this instance, I want the months across the top of my heatmap. I simply right-click on “order date” and drag it into columns. This will give me the option to select the type of date I want. Simply click on the blue “month” (to keep it as a dimension) and click OK. Also, make sure your marks tab is set to “square” (it will be on automatic by default). This is what your screen should look like:


Step 2: Bring in your rows

This is what you want displayed down the side of your heat map. In this instance I want the years displayed down the side (remember, I’m comparing months across different years). Right-click and drag in order date once again, this time into your rows section. This will bring up the same pop-up screen as before, but this time you want to select the blue “year”. This is what your screen should look like:


Step 3: Bring in your values

For this heatmap, we are looking at comparing profit, so we’re going to bring profit into our viz. Simply drag profit on to colour on the marks pane. This will colour your heatmap by this measure. The colours will change automatically, but you can change these to your liking.  Your heatmap should now be up and running, but with 1 issue; you can’t see how much profit each month made without hovering over that month, so we’re going to fix that by dragging profit into “text” on the marks pane. This will show the profit for each month as well as keep the colour. Your screen should look like this:


And there you have it! You’ve just created a heatmap in Tableau. Of course, there are many other customizable features of a heatmap, but I’ll leave that to you to change yourself. I hope this blog helped!

The Data School
Author: The Data School