How to Remove Secondary Y Axis in Power BI

A second y-axis in a Power BI chart can seem like a good idea when you need to plot data with different scales, but it often makes your visualization more confusing than insightful. Getting rid of it is simpler than you might think. This guide will walk you through exactly how to remove that secondary y-axis, clean up your charts, and build more effective reports in Power BI.

What is a Secondary Y-Axis and Why Would You Have One?

The secondary y-axis, sometimes called the secondary vertical axis, is the vertical axis that appears on the right side of a combo chart. A "combo chart" is any visualization that combines two chart types, like a line chart and a column chart, into a single visual. Power BI popular combo charts include:

• Line and stacked column chart
• Line and clustered column chart

You most often see a secondary y-axis when the data series you're plotting have vastly different scales. Imagine you're a marketer at a software company tracking website traffic and new signups by month. Website traffic would be in the tens of thousands, while signups might be in the hundreds. Here's what would happen if you were putting these figures together in a single graph:

• Traffic: Plot on the left y-axis with a scale from 0 to 50,000
• Signups: On the right y-axis, using a scale from 0 to 500

Without the secondary axis on the right, your Signups would appear flat at the bottom of the chart. It's hard to see the visualization. So the secondary scale lets both trends show up without overpowering each other, making your visualization accessible so the user can see everything that's going on at a glance.

When Does Removing a Secondary Y-Axis Make Sense?

Even if you know using two axes looks a bit confusing, you will lose some flexibility. But there are two main situations where making this move will improve how you communicate insights:

• Keeping Scales Consistent: In situations where you are measuring related metrics like sales and profit, a secondary axis will create confusion. So you want to stick to one standard scale to remove any user's guesswork and show it how it is.
• Minimizing Unnecessary Clutter: If two metrics, while showing the same tendency, can be on the left y-axis, it's better. What I used to do at my previous job is create two visualizations to have simple charts that the user can understand in seconds. If you're struggling to simplify your visualizations, start a free account with Graphed here to start a clean visualization workflow, no-code!

5 Steps to Removing the Secondary Y-Axis in Power BI Desktop Version

Step 1: Choose your Combo Chart

Select your combo chart so the Format visualization options become active.

Step 2: Start Formatting by Pressing the Brush Icon

Find the brush icon and go into the “Format your visual” tab in the Visualization area and access all the formatting options by clicking on it.

Step 3: Find Your Secondary Y-Axis Options

Scroll down your formatting options until you find "secondary Y-axis". Click there to expand that option.

Step 4: Hide the Secondary Axis

Here you get multiple options to control the axis. I use three main options with a flick of a finger:

• Hide the secondary axis by switching the on and off toggle. The most popular option
• Choose values for the start and end values with the Range option, where you customize the minimum/maximum settings
• Value setting: If I deal with big numbers, use the Display setting here. Thousands, millions, etc.

Step 5 (Optional but Highly Recommended): Clean Up Your Chart

Once you remove the secondary axis, make this double step to increase readability:

• Update Titles and Legends: Now that it's all under a single metric, update your chart's title and legend. Make it clearer and simple. Example: a title like "Sales ($5M) and Profit ($302)" tells you what happened without looking anywhere else.
• Play Around With Your Data Labels: Turn on data labels so it's easy to see which dataset you're looking at.
• Check Your Chart Scale Again: With the new setting, there's a good chance that some elements might sit outside of the graph range now. Tweak your minimum and maximum settings of the y-axis until all data appears on your charts.

Protip: If a KPI you're measuring suddenly disappears after changes you applied, you might need to select another formatting type due to visual limitations with only one axis available. Some visualizations are simpler and clearer than others when using only a single axis.

You Did It and Wonder... Where Did My Bar Chart Go!?

With the second y-axis removed, some visuals don't play nicely. In cases where small datasets share visuals with more massive data, your first series might seem to disappear. Two choices: make the visuals separate (my pick!) or adjust your y-axis settings so the new data sources are visible.

Best Practices for Better Chart Readability

With this knowledge, getting a clean dashboard in Power BI is as simple as one, two, three:

• Turn off your chart data labels if these numbers don't add enough value. Less is better when making visuals.
• Make your legend reflect what the user is looking at. Instead of a single sales metric, spell it out more precisely like "Monthly sales." This adds context without extra layers or elements.
• Use your judgment for elements with noise potential on your chart and hide them, like chart borders or backgrounds. Your main goal is that your audience gets your message quickly!

Final Thoughts

In the end, by hiding that secondary axis, you now know how easy it is to handle axis visuals with a click. It's important to build less confusing and easily digestible visuals.

With Graphed, where we love working with AI data, we can sync more than a dozen data sources like GA4, Shopify, Facebook Ads, Sheets, and more at your fingertips. We create dashboards that don't need a manual, using everyday language to create and interact with them. For example, you can get insights out of massive databases by asking, "show me sales-pipeline line from your Salesforce," and Graphed takes care of generating charts in any data visualization format. This allows you and your team to get all the insights without getting stuck wrangling data.