Common Chart Design Pitfalls: Dual Y-Axis Charts

Here are some common issues with dual Y-axis charts and how to address them effectively.   

Challenges of using dual Y-axis charts: 

  1. Confusion about which axis to read: In a dual Y-axis chart, viewers may have trouble understanding which axis corresponds to which data series, especially if the chart is cluttered.
  2. Patterns dependent on scales: The visual relationship between the two data series depends on the chosen scales for each Y-axis. Changing the scale can alter the perceived correlations or trends.
  3. Scales are arbitrary: Choosing appropriate scales for dual Y-axis charts can be subjective and arbitrary, potentially leading to misinterpreted data.
  4. Zero baselines at different heights: Having different zero baselines on each Y-axis can make it challenging to compare the starting points of both series.
  5. Implied relationship between data series: Dual Y-axis charts may imply a relationship between two data series when there may be none, potentially creating a false narrative.


Ways to address these issues and create effective, easy-to-understand charts: 

  1. Shared X-axis: Use a shared X-axis for both data series to establish a standard reference point and ensure comparability.
  2. Use the same unit of measurement: If possible, convert the two data series to the same unit of measurement, allowing you to use a single Y-axis scale. For example, instead of comparing revenue in dollars and profit margin percentage, you could convert both to dollars to simplify the chart.
  3. Use an indexed chart: One way to address scale issues is by using an indexed chart, which shows the percentage change of each data series relative to a specific start point. This can help emphasize the trends rather than the absolute values.
  4. Replace the least important series with data labels: If one of the data series is less important or secondary, you can consider using data labels or annotations instead of a second Y-axis to emphasize the primary data series.



Suppose you want to visualize the relationship between a company’s advertising spend (in dollars) and website traffic (number of visits). A dual Y-axis chart may falsely suggest a correlation that isn’t there, depending on the chosen scales. Instead, you could use an indexed chart to show the percentage change in both advertising spend and website traffic over time, maintaining a shared X-axis for clarity. This way, your audience can focus on the trends without getting lost in the nuances of two different scales.