How to Make a Clustered Column Chart in Tableau

Creating a chart that clearly compares sub-categories across different groups can be tricky, but a clustered column chart makes it easy. Unlike a standard bar chart, this format places bars side-by-side, perfect for visually measuring performance. This article will walk you through, step-by-step, how to build a clean and effective clustered column chart using Tableau.

What is a Clustered Column Chart, and Why Use One?

A clustered column chart (also known as a grouped bar chart) is a type of chart that displays more than one data series in clustered vertical columns. Each cluster represents a main category, and each column within the cluster represents a sub-category. This side-by-side comparison makes it incredibly useful for understanding relationships between different data points.

So, when should you use one? Clustered column charts are ideal when you want to:

Compare sub-groups directly: If you want to see how "Furniture" sales stack up against "Technology" sales specifically within the "East" region, a clustered chart is perfect. It removes the ambiguity that can come with stacked charts where you have to mentally subtract values to make a comparison.
Track performance across main categories: It allows you to quickly spot trends. For instance, you might see that while "Technology" is the top seller in most regions, "Office Supplies" outperforms it in one specific region.
Analyze a few categories at once: They work best with a limited number of sub-categories (usually 2 to 4) per cluster. Too many columns in a cluster can make the chart feel crowded and difficult to read.

For this tutorial, we will be using Tableau's built-in Sample - Superstore dataset to compare sales for different product categories across various regions.

Before You Start: Understanding Your Data Fields

To build a successful clustered column chart, you need three key ingredients from your data:

A Primary Dimension: This will form your main clusters or groups along the horizontal axis. In our Superstore example, this will be Region.
A Secondary Dimension (The Clustering Dimension): This dimension will be used to create the individual, color-coded columns within each cluster. We'll use Category for this.
A Measure: This is the numerical value you want to compare. It determines the height of your columns. We will use Sales.

Ensuring your data is structured with these clear categorical and numerical fields is the first step toward building a meaningful visualization.

Step-by-Step: Building Your Clustered Column Chart in Tableau

Once you have your data connected, building the chart is a simple drag-and-drop process. Let's walk through it together.

Step 1: Open Tableau and Connect to an Excel File

First, launch Tableau Desktop. On the start screen, under the "Connect" pane on the left, click on Microsoft Excel. Find and open the Sample - Superstore.xls file that comes with your Tableau installation. Once loaded, Tableau will show you the available sheets. Drag the "Orders" sheet onto the canvas.

Step 2: Add Your Main Category to the Columns Shelf

Navigate to a new worksheet. In the "Data" pane on the left, you'll see your dimensions and measures. Find the Region dimension and drag it onto the Columns shelf at the top of the workspace. You'll immediately see the four region names (Central, East, South, West) appear as column headers in your view.

Step 3: Add Your Measure to the Rows Shelf

Next, find the Sales measure in the "Data" pane. Drag Sales and drop it onto the Rows shelf. Tableau will automatically generate a simple vertical bar chart, showing the total sales for each region. Each region has one bar. This is a good start, but it doesn't break down sales by product category yet.

Step 4: Create the "Clusters" with Your Secondary Dimension

This is where the magic happens. Find the Category dimension in the "Data" pane. Drag it to the right of the Region pill on the Columns shelf. You'll notice that this creates separate sections within your chart, essentially giving you a bar chart for "Furniture," then "Office Supplies," then "Technology" within each region. This isn't quite the clustered view we want, but it's an important intermediary step.

Your current chart shows Sales for each Category within each Region, but they are laid out sequentially, not grouped under their respective region. The final step is to bring them together.

Step 5: Move the Clustering Dimension to the Color Mark

To transform the chart into a true clustered column chart, click and drag the Category pill from the Columns shelf directly onto the Color card in the Marks pane. The view will instantly update. Now, you have a distinct cluster of bars for each region. Within each cluster, you have three color-coded bars representing the "Furniture," "Office Supplies," and "Technology" categories. A color legend also appears on the right to explain what each color means.

And that's it! You've successfully created a clustered column chart in Tableau.

Customizing Your Chart for Clarity and Impact

A basic chart is good, but a well-formatted one is great. A few small tweaks can make your chart much easier to read and understand.

Add Data Labels

Displaying the exact sales figures on each column can add valuable detail. Drag the Sales measure from the "Data" pane and drop it onto the Label card in the Marks pane. The sales totals will appear on top of each bar. If the numbers look messy, you can format them by right-clicking the SUM(Sales) pill on the Rows shelf, selecting "Format," and then opening the "Pane" tab. Here you can change the number format to Currency and reduce decimal places.

Edit Colors and Titles

Tableau's default colors are good, but you may want to use your company's brand colors or a palette that's easier to distinguish. Click the Color card, then on "Edit Colors" to select a different palette or assign specific colors to each category.

Always give your chart a descriptive title. Double-click the sheet title ("Sheet 1") at the top and change it to something clearer, like "Sales Performance by Product Category and Region."

Enhance Your Tooltips

The tooltip is the little box of information that appears when you hover over a data point. You can add more context here without cluttering the main chart. For example, drag the Profit measure to the Tooltip card. Now, when you hover over a bar, you'll see both the total sales and the total profit for that category and region.

Common Challenges and Quick Fixes

As you're learning, you might run into a few common hurdles. Here’s how to quickly navigate them.

My chart is stacked, not clustered. What happened?

This is the most common mistake. A stacked bar chart is created when Tableau simply adds the second dimension (Category) to the color mark without it first being on a shelf. The fix is to make sure your primary dimension (Region) is on Columns and your measure (Sales) is on Rows first. Then, place your clustering dimension (Category) onto the Color card. The combination of these placements is what creates the side-by-side clustering effect.

The chart is too crowded.

This usually happens when there are too many items in your dimension. A clustered chart showing sales for 50 different product sub-categories would be unreadable. If your chart looks too busy, consider filtering your data to show only the top 5 or 10 items, or grouping items into a higher-level category.

Which dimension should go where?

The dimension you place on the Columns shelf first should be your broadest, top-level grouping (Region). The dimension you place on the Color card is the sub-group for comparison (Category). Reversing them can technically work, but it often produces a chart that's less intuitive to understand.

Final Thoughts

The clustered column chart is an excellent tool for making direct, side-by-side comparisons across categories. By placing a primary dimension on Columns, a measure on Rows, and a secondary dimension on the Color card, you can easily build this powerful visualization in Tableau to uncover deeper insights in your data.

Learning the workflow in tools like Tableau unlocks a tremendous amount of analytical power, but it often starts with manual clicking, dragging, and formatting. We built Graphed because we wanted to turn that hours-long setup process into a 30-second conversation. Instead of learning where to place each pill, you can simply ask, "Create a bar chart showing sales by category, grouped by region." We instantly generate the same report with your live data, allowing you to get answers and move on to the next question without breaking your train of thought.