How to Create Bins in Tableau

When you have a column of continuous numbers - like sales figures, customer ages, or product discounts - it can be tough to see the bigger picture. Creating 'bins' is how you group that data into more manageable chunks, and this article will walk you through exactly how to do it in Tableau.

What Exactly Are Bins in Tableau?

Think of bins as buckets. You have a long list of individual customer ages: 23, 47, 31, 25, 28, 52, and so on. Bins let you automatically create buckets (like 20-29, 30-39, 40-49) and then count how many customers fall into each one. Instead of looking at hundreds of individual data points, you're looking at a handful of organized groups.

In technical terms, bins convert a continuous measure (a field with a range of numeric values) into a discrete dimension (a field with a finite number of distinct groups). This is the secret behind building a histogram - one of the most common and useful chart types for understanding data distribution.

Why Should I Use Bins? The Practical Benefits

Creating bins isn't just a technical exercise, it's a fundamental analysis technique that helps you answer important business questions quickly. Here’s why it’s so valuable:

• See the Distribution Clearly: The primary use for bins is creating histograms to visualize the frequency distribution of your data. This immediately shows you where your data is concentrated. Are most of your customers in their 30s? Are the majority of your sales between $50 and $100? A histogram makes an immediate visual impact.
• Simplify Complex Data: A table with 10,000 unique sales values is almost impossible to interpret just by looking at it. By grouping those sales into bins (e.g., $0-$100, $101-$200), you can instantly simplify the data into a more digestible format.
• Identify Patterns and Outliers: Bins make it easy to spot trends - or the lack thereof. You might discover an unexpected cluster of activity in a certain range or notice significant gaps. You can also quickly see outliers, that one customer who placed a $10,000 order will stand out when most orders fall into the $50-$150 bin.

Method 1: The Easy Way to Create Bins in Tableau

Tableau has a built-in feature that makes creating uniform bins incredibly simple. This is the perfect method when you want to group your data into equal-sized ranges.

Let's use an example. Imagine you have a dataset with a continuous measure called [Age] for your customers, and you want to create a histogram to see the age distribution.

Step-by-Step Instructions

1. Locate Your Measure

In the Data pane on the left side of your screen, find the continuous measure you want to bin. In our case, it's [Age]. You can identify it by the green # icon.

2. Create the Bins

Right-click on the measure and navigate to Create > Bins...

3. Configure the Bin Size

A dialog box will pop up. Here's what the options mean:

• New field name: Tableau will automatically suggest a name like "Age (bin)". It’s a good practice to keep this naming convention so you can easily identify your binned fields.
• Size of bins: This is the most important setting. You can either enter a specific number or use a parameter for dynamic sizing. Tableau will often suggest a size based on the range of your data. For our age example, let's set the size to 10. This will create groups like 0-9, 10-19, 20-29, and so on.

Once you click OK, you'll see a new field in your Data pane under "Dimensions": Age (bin). Notice it has a blue histogram icon, indicating it’s a binned dimension.

4. Build Your Visualization (A Histogram)

Now you can use your new binned dimension to create a histogram.

1. Drag the new Age (bin) dimension onto the Columns shelf.
2. To see how many customers are in each bin, you need a count. You can do this by dragging the original [Age] measure to the Rows shelf. By default, Tableau might sum it (SUM[Age]), which isn't what we want.
3. Right-click the SUM(Age) pill on the Rows shelf, and change the aggregation to Count or Count (Distinct). COUNTD is great if you have a unique customer ID field to count instead.

And just like that, you have a histogram showing you the distribution of customer data in a clear, easy-to-read chart.

Method 2: The Flexible Way with Calculated Fields

The standard binning feature is fantastic, but it has one limitation: all bins must be the same size. What if you want to create custom, unequal groups? For example:

• Grouping small sales values together ("Under $50") but giving larger values their own specific ranges ("$500-$1000", "Over $1000").
• Creating demographic groups like "Gen Z," "Millennial," and "Gen X" based on specific age ranges.

For this kind of flexibility, you need a calculated field.

Step-by-Step Instructions

Let's use an example where we want to bin sales data from a [Sales] measure into custom tiers: 'Small', 'Medium', 'Large', and 'Extra Large'.

1. Create a Calculated Field

In the top menu, go to Analysis > Create Calculated Field... Or, right-click anywhere in the empty space in the white area of the Data pane and select Create Calculated Field…

2. Write the Binning Logic

Give your calculated field a clear name, like "Sales Tiers". Now, you'll use an IF/ELSEIF statement to define your logic. Here’s how you could structure it:

IF [Sales] < 50 THEN 'Small (Under $50)'
ELSEIF [Sales] >= 50 AND [Sales] < 250 THEN 'Medium ($50 - $249)'
ELSEIF [Sales] >= 250 AND [Sales] < 1000 THEN 'Large ($250 - $999)'
ELSE 'Extra Large ($1000+)'
END

This formula checks each sales value and assigns it to a bucket you’ve defined. You can have as many ELSEIF lines as you need for your groups.

3. Use Your New Dimension

When you click OK, you'll see your new [Sales Tiers] dimension appear in the Data pane. You can now drag and drop this field just like the automatically generated bin from Method 1 to see how many orders fall into each of your custom categories.

Tips for Working with Bins Like a Pro

Once you’ve mastered the basics, here are a few expert tips to keep in mind:

• Choosing the Right Bin Size Matters: The bin size you pick can dramatically change the story your data tells.
• Show Empty Bins: Sometimes, the absence of data is just as insightful as the data itself. In your chart, right-click the binned field on the Columns shelf and select Show Missing Values to display these gaps.
• Handling Nulls: If your measure contains null values, they will be grouped into a "Null" category at the very bottom of any filter of your view. You can either filter these out or keep them to understand how much data is missing.

Final Thoughts

You’ve now learned what bins are, why a good visualization must go beyond just raw numbers, and walked through the two primary methods for creating histogram charts in Tableau. Whether you use the simple, built-in bin creator for uniform groups or write IF/ELSEIF logic inside a custom calculated field, binning is a powerful step toward building an analytics skill that every team cherishes.

Creating these kinds of charts and reports from scratch inside powerful - but complex - BI dashboards highlights the valuable time it takes when sometimes all you want to do is ask a quick question to explore your business operations. I faced this very same headache manually combining different sheets with their own column orders, so that's actually the reason we made Graphed the way it is. Instead of digging through menus and submenus to create charts and custom bin sizes, or any of the other common business analysis workflows, I can just ask a question like "show me our top five countries with monthly sales" in normal human language. When I describe what a 'large sale' or 'key deal flow' means to me as a single-person team with my own preferences, our AI data analyst learns and handles the SQL queries behind the scenes so you are always interacting with the real-time truth from whatever source you have connected.