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Dual Axis Charts: Beyond Simple Visualization

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A dual axis chart also known as multiple axes chart, employs two axes to clearly depict the connections between two variables of varying magnitudes and scales of measurement. Correlation is the term used to describe the relationship between two variables.

A dual axis chart conveys a lot of information in a little amount of area.

What Is Dual Axis Chart?

When the data values in a chart differ significantly from one series to the next, or when you have mixed forms of data (for example, currencies and percentages), one or more data series can be shown on a secondary vertical (Y) axis. The supplementary Y-axis scale represents the values for the related data series.

While the secondary Y-axis can be used with any line or bar chart type, it is most typically employed with combination charts to assist differentiate the data series shown on the secondary Y-axis.

Dual axis charts are used to compare two trends to one another. These might be two separate data series with the same units but different magnitudes, or two other data series entirely.

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What Should The Dual Axis Combination Be?

It is entirely dependent on the requirements.

  • If you need to show two trend lines, both line charts will work. A combination of a bar chart and a line chart can also be used.
  • When you don’t need to illustrate the trend but only the frequency, you may utilize both charts as a bar chart.
  • When utilizing dual axis charts like bar charts, be sure to format both charts in terms of size and color. This allows the user to clearly examine the charts in both charts and make business decisions.

Uses Of Dual Axis Chart

Dual axis charts are frequently used to display two distinct data series with varying magnitude (=number range) and/or measure (GDP, life expectancy, etc.). Frequently, their purpose is to compare two trends.

  • Two data series having the same metric but different magnitudes, for example, global GDP on one axis and German GDP on the other:
  • Two data series displaying relative and absolute quantities of something, such as GDP per capita on one axis and absolute GDP on the other:
  • Two data series with completely distinct values, such as a country’s GDP on one axis and its life expectancy on the other:
  • One data series, but the y-axis has multiple scales, for example, values in Fahrenheit on one axis and values in Celsius on the other:

Best Practices To Use A Dual Axis Chart

  • To make it clear which data series relates to which axis by using color.
  • Crossing lines has no meaning.
  • It is not appropriate to compare the rate of change between the two series.
  • It is not appropriate to compare heights since the axes may be on different scales.
  • It is not necessary to change the scales of the axes in order to demonstrate correlation.

When To Synchronize The Axes And When Not To?

We must exercise extreme caution while synchronizing the axis. This can be beneficial to us at times, but it can also be detrimental to the user’s experience. For instance, we have the following requirements:

  • A daily wage
  • Every day clicks

These criteria might, as we suspected, come from an affiliate network. The affiliate network may like to show their publisher how much they make on a daily basis as well as how many clicks, they receive on a daily basis. In this situation, it is rather evident that the number of clicks will much outnumber the quantity of earnings. 

There may be a day when the number of clicks is 100 and the income is USD 1, and this tendency may continue.

If we synchronize our earning axis in this scenario, it will be approximately about the x-axis. And this may not be the best reporting habit. So, if we have one axis with a very large range and another with a smaller range, we should avoid synchronizing the axes.

 

When we have two majors with comparable units, such as profit and discount. We should think about synchronizing our axes in this scenario. Again, there is no hard and fast rule on when to synchronize and when not to. This is entirely dependent on your needs.

Consider altering the name of the other axis after we’ve synced it. This will assist the user in avoiding becoming confused by the name. In our scenario, after we’ve synced both the profit and sales axes, we may conceal one of them.

Assume we’re concealing the profit axis. The other axis will then say sales, which is not quite correct because that accepts will reflect both sales and profit. In this scenario, you may need to rename the axis. To rename an axis, just right-click on it and change the name.

Do’s And Don’ts Of Dual Axis Chart

Do Use Dual Axis Chart To:

Display Variables with Extremely Distinct Scales

It is much simpler to observe two variables with significantly different scales inside the same graph than it is to switch between two charts. It also takes up less room in PowerPoint presentations.

Display Variables in Various Numerical Units

A dual axis chart can also display two numerical values with distinct units, similar to the preceding approach. In the graphic below, for example, there is a link between the number of homes for sale and the average home price in California. This compares the value of a currency to the value of a rounded number.

Things To Avoid While Using Dual Axis Chart:

Don’t Overburden Your Charts

A chart can only carry so much information before becoming unwieldy. Keep your chart to one point by demonstrating the relationship between two variables. There are four lines in addition to the columns in the example below.

Switching back and forth between examining the legend and the chart becomes quite visually confusing. Because the axes are so dissimilar, the bottom line can only be seen through the triangles.

Don’t Forget to Track Best Practices

This one may appear apparent, yet it is easy to overlook. Simply because we have two axes does not mean that other charting recommended practices do not apply. A line chart, for example, is not the ideal approach to display categorical data. They’re best kept for long-term patterns.

Lines indicate a trend over time. As a result, the line in the figure above is perplexing since it represents a trend with categorical data.

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Advantages Of Dual Axis Chart

  • Multiple variables can be plotted in a single chart.
  • It is very easy to draw.
  • They can be easily compared. E.g., decoding values in an alternate unit of measure.

 

  • Visual estimation of possible relationship between two variables in different unit of measure or at different scales across a time scale.

Disadvantages Of Dual Axis Chart

Zero Baselines At Different Heights Can Mislead

In dual axis charts, the proportions of the two scales are frequently varied. The chart would be twice as lengthy if the left axis was set to zero. The chart would be nearly three times as lengthy if the right axis was set to zero. When we extend both axes to zero, they appear like this:

Even Zero Baselines At Same Height Can Mislead

The chart looks like this with the same baseline. In the best-case scenario, our readers will now think, “It appears that global GDP rose more than German GDP.” It appears that the German GDP was greater than the world GDP in the early years. Then, in 2011, the two GDPs were equal:

When items appear near on a chart, it might be difficult to recall that they are actually thousands of kilometers distant.

They Are Difficult To Read

2011 research backs up that assertion. Petra Isenberg, Anastasia Bilzerian, Pierre Dragicevic, and Jean-Daniel Fekete showed 15 participants four distinct charts with values of varying magnitudes and assessed how well they could understand the charts. One of these was a chart with a dual axis, dubbed a “superimposed chart” by the researchers. That’s what they discovered:

We found across the board that the superimposed chart performed poorly both in terms of accuracy and time. Participants’ feedback from the questionnaire was also clearly against the superimposed chart and it was ranked lowest by all but one participant. Participants called it very confusing and demanding too much concentration or reflection to decipher the non-monotonic and discontinuous nature of the two scales. 

– A Study on Dual-Scale Data Charts

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