How to Convert Text Table to Heat Map in Tableau

A wall of numbers in a text table can be overwhelming. While precise, these tables make it difficult to spot trends, outliers, or performance hotspots at a glance. Converting that text table into a heat map is a simple but powerful way to transform raw data into an immediate, intuitive visual story. This guide will walk you through exactly how to do it in Tableau, step-by-step, to make your reports easier for anyone to understand.

Why Move Beyond a Plain Text Table?

Text tables, or crosstabs, are the default for many data tools. They're dense with information and great for looking up specific values. If you need to know exactly how many units of "Product B" were sold in the London office last quarter, a text table gives you a direct answer. However, they fall short when you're trying to understand the bigger picture.

Our brains are wired to process visual information like color and shape far more quickly than text. When you look at a table packed with numbers, you have to read each value, compare it to others, and mentally map out the highs and lows. It's slow, requires a lot of cognitive effort, and makes it easy to miss important patterns.

A heat map solves this problem by using color to represent value. Instantly, you can see:

• Hotspots: The highest-performing areas will pop with dark or intense colors.
• Coldspots: Underperforming areas are immediately identifiable with lighter shades.
• Overall Patterns: You can see trends across entire rows or columns without reading a single number.

Imagine you're a marketing manager looking at lead generation by campaign and region. A text table shows you a grid of numbers. A heat map instantly reveals that your "Summer Sale" campaign performed exceptionally well in California but flopped on the East Coast, an insight that might have taken minutes to dig out of a simple table.

Setting the Stage: Creating Your Base Text Table

Before we can transform a table, we need to build one. Let's start with a standard text table in Tableau. If you already have one, you can skip to the next section. For this example, we'll use Tableau’s Sample Superstore dataset to create a table showing Sales by Product Sub-Category across different Regions.

Step 1: Place Your Dimensions on Rows and Columns

Dimensions are your categorical data - they describe what you are measuring. In our example, Sub-Category and Region are dimensions.

• Find Sub-Category in the Dimensions list on the left-hand Data pane and drag it to the Rows shelf.
• Next, find Region in the same list and drag it to the Columns shelf.

You’ll now have a basic table structure with product sub-categories listed down the side and regions across the top, but the cells will be empty.

Step 2: Add Your Measure to the Text Mark

Measures are your numerical data - the things you can count, sum, or average. In our case, Sales is our measure.

• Find Sales in the Measures list on the Data pane.
• Drag it onto the Text square inside the Marks card.

Tableau will automatically populate the table with the sum of sales for each sub-category and region. You should now have a classic text table with neatly organized numbers filling the grid.

The Transformation: Turning Your Table into a Heat Map

This is where the magic happens. With just a few clicks, we’ll convert that grid of plain numbers into a vibrant, insightful heat map. The Marks card is the control center for this entire process.

Step 1: Switch the Mark Type from Text to Square

Right now, Tableau is configured to represent your data as text. The key to creating a heat map is to change this representation to a shape that can be colored.

• Locate the Marks panel, which is typically in the middle of the workspace.
• Click the dropdown menu that currently says Automatic. Because you have a measure on the Text mark, Tableau automatically defaults to 'Text'.
• From the dropdown list, select Square.

You'll notice your table changes. The numbers disappear, and you're left with an empty grid of small blue squares in each cell. Don't worry, this is exactly what's supposed to happen. You've just told Tableau, "Instead of showing me text, I want you to draw a square for each data point."

Step 2: Use Your Measure to Drive the Color

Now that we have shapes, we need to tell Tableau how to color them. We want the color to reflect the sales figures in each cell - higher sales should have a darker color, and lower sales a lighter color.

• Go to the Measures list in your Data pane and find Sales again.
• This time, drag and drop Sales directly onto the Color icon within the Marks pane.

Instantly, your grid of squares will be colored based on their corresponding sales values. Tableau automatically assigns a default continuous color palette (usually a light-to-dark blue). Just like that, you’ve created a basic heat map! You can already see which regions and sub-categories are your top performers.

Step 3: Add Labels Back for Extra Detail (Creating a Highlight Table)

A pure heat map is fantastic for spotting trends, but sometimes you still need to see the exact numbers. Tableau makes this easy to do, creating what's known as a "highlight table" - a perfect end to heat map visuals with text. To get the best of both worlds, just add the Sales values back as labels.

• Once more, drag Sales from the Measures list.
• Drop it onto the Label icon within the Marks pane.

The numbers will now reappear superimposed on top of each colored square. You now have a visually appealing table that not only highlights trends with color but also presents the precise numbers you need.

Final Touches for Better Clarity and Definition

To make your visualizations go from good to great, here are a few advanced tweaks that can add clarity to your heat map.

Adjusting Cell Size for Better Readability

If your table's cells are too small, you can adjust them to fill more space and make the data easier to read:

• Click on the Size icon in the Marks panel.
• Drag the slider to the right until the squares are just touching each other. This creates a more complete view without wasted space.

Using a Diverging Color Palette for Added Insight

Diverging colors can offer a powerful visual cue for quickly identifying both extremes and middle values. This is particularly insightful for financial data or profit, where understanding losses versus gains is crucial.

• Click the Color icon on the Marks panel.
• Select Edit Colors from the dropdown menu.
• Choose a Diverging palette which uses two contrasting colors – often red and green – to represent values above and below a center point, like zero.

Customizing Fonts and Borders for Better Definition

Tableau's default font may not perfectly match your data's importance or your reference Tableau for that matter. You have a lot of options to make it much more readable.

• Click on the Label icon, then click on Font in the formatting window.
• Here, you can change font size, color, and style. Making the labels larger and bolder can make everything easier to read, especially against a darker background.

When Dealing with Null Values

If your data includes null values (missing quantities), the colors might appear fragmented or misleading. Here’s how you can deal with those:

• In the Color window, click on the dropper in the lower-right hand corner, and select a specific color for null values, such as white or grey.

Conclusion

Converting a text table to a heat map in Tableau isn't just about making a chart prettier, it's a transformative way to visualize and analyze data in a manner that anyone can understand. A highlight table mixes the visual impact of colors with the legibility of text, providing a robust analytical tool for your team.

At the end, a hybrid presentation of summarized visualizations using these steps can make your Tableau dashboards much more informative and engaging. Use Graf to automate the visualization process, which saves your time and allows you to focus on insightful analysis and decision-making.