Do you want to create a second axis in your Power BI chart?
Power BI, Microsoft’s powerful business intelligence tool, offers a plethora of features that empower users to transform raw data into insightful visualizations.
Among its versatile chart types, the dual axis chart stands out as a compelling tool for comparing and correlating two distinct measures within a single visualization.
Whether you want to highlight relationships, uncover patterns, or visualize the impact of multiple variables, the dual axis chart can be an invaluable asset.
Creating a chart with two axes in Power BI is a simple process. This post will guide you through the necessary steps to achieve it.
Why Use a Dual Axis Chart
A dual axis chart serves as a valuable tool in scenarios where the goal is to compare two different measures that possess distinct units of measurement or scales yet maintain a meaningful relationship or impact on each other.
By combining these measures into a single visualization, you can effectively highlight correlations, trends, and patterns that might otherwise remain unnoticed.
The dual axis chart grants the ability to visualize and analyze the intricate relationship between these measures, offering a comprehensive view of their interactions.
An example of a dual-axis chart is presented here. The Y axes depict measures on different scales while displaying the correlation between the bar and chart. This effectively illustrates how both measures fluctuate over the given period.
The process of creating this chart involves the following steps:
Step 1 – Identify the Appropriate Chart for Your Visual
In Power BI, various visuals offer support for a secondary Y axis, even though they may not always employ the same terminology to convey this functionality.
The charts that support the use of a secondary Y axis include the Line Chart, Area Chart, Line and Stacked Column Chart, and Line and Clustered Column Chart.
The Line Chart and Area Chart utilize the Secondary Y axis title, whereas the Line and Stacked Chart and Line and Clustered Column charts employ the Line Y axis titles to describe their secondary Y axis. This is because they combine both lines and bars in a single chart.
The Line and Clustered chart is selected to create the above visual.
Step 2 – Drag the Measures to their Desired Wells
After choosing the appropriate chart, drag the measures into the appropriate wells.
Here, the Year and Month dimensions are placed on the X-axis and the Revenue measure on the Column Y-axis. Finally, the Line Y-axis has the % of Profit to Revenue.
When you complete this step, you will get the chart’s default view. You can then customize every aspect of the chart using the Format Visual option.
Some Notes of Caution When Creating a Chart with Two Axis
When utilizing a secondary Y axis, it is crucial to ensure that the plotted values on both axes are distinct. This is of paramount importance because incorporating two Y axes in a visual representation can lead to misinterpretation or even confusion for users or yourself.
To accomplish this, leverage the formatting options within the visualization pane. It is crucial to emphasize distinct values on both axes using a variety of colors and formatting tools at your disposal.
Also, ensure that the title for each axis remains visible in the visual. Occasionally, Power BI may be disabled the secondary Y axis if its data range significantly overlaps with the primary Y axis.
To force the axis title to display, just click on the toggle beside the Secondary y-axis option in the Format your visual pane.
Using a dual axis chart in Power BI provides a robust way to compare and analyze two measures with different units or scales.
By combining these measures in a single visualization, you can effortlessly uncover correlations, patterns, and trends that might have otherwise gone unnoticed.
Also, if you ensure the axes appear as distinct as possible, the dual axis chart will become a formidable tool for illustrating complex relationships that might exist within the data.
Are you using dual axis charts? Let me know in the comments!