How to Create and Use Tableau Dual Axis Charts Effectively?


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Tableau charts make information easier to see. These are data visuals that help you track figures, compare trends, prepare future business plans, and make the right decisions. Charts in Tableau also save the time of having to manually sift through excel sheets or databases. They assist you in preparing data models and evaluating your business performance smoothly and efficiently.

A combined view of two or more measures in a single chart is called a dual axis chart. Tableau dual axis charts combine two or more Tableau measures and plot relationships between them, for quick data insights and comparison. 

This article explains Tableau dual axis charts, their pros, and cons, along with steps you can use to create dual axis charts in Tableau. We’ll also share some antidotes to shortcomings in Tableau dual axis charts, i.e., by using the right scales and adjusting their visual appeal, just like your dual axis chart excel.

Table of Contents

What is Tableau?

Data-driven decision-making demands insights into what’s happening around.

Sure do every company gets bombarded with tons of data, and unless they really know how to put it to use, every attempt to solve a problem is a wild goose chase.

Tableau makes decision-making easier by visualizing your data in seconds. A market leader in the Data Analytics and Business Intelligence industry, Tableau has garnered the likes of Nike, Coca-Cola, Skype, The World Bank, The New York Times, and many more.

Tableau can readily connect to your data source/files- be it excel sheets, database applications, cloud-based data warehouses, or big data storage. Whether you are an analyst, data scientist, student, teacher, executive, or business user, Tableau’s fast-to-deploy and an easy-to-learn interface can create highly simplified graphs or charts for any set of complex data. 

Tableau’s user-first philosophy takes this application far ahead of the pack. Gartner’s Magic Quadrant has lauded Tableau as a leader in Analytics & BI Platforms, for nine consecutive years. With thriving possibilities in the data analytics space, and its strong collaboration with its parent, Salesforce, Tableau is on a road to a shining future. 

Business Benefits of Using Tableau

  • One Source of Truth: Separate data silos with different BI applications are a thing of the past. Using Tableau you can bring in data from multiple sources like excel, SQL databases, CRMs like Salesforce without having to write any code.
  • Instant & Automated Reporting: Tableau is an interactive data visualization software that helps you build informative and eye-catching reports quickly. These include pie charts, bar charts, bullet charts, gantt charts, boxplots, and a ton more which can be automated to bring in new data visualizations.
  • Advanced Dashboards: Do you prefer advanced dashboards for complex datasets? Tableau dashboards provide an in-depth view of your data using advanced visualizations. With Tableau dashboards, you get to visualize data in multiple views and objects, and in a variety of layouts and formats to choose from.
  • Natural Language Processing: Using Tableau’s natural language processing, you can simply type in “What is the average revenue generated last quarter?”, and Tableau will return you detailed answers in an instant. 
  • Robust Security: Tableau uses strict measures to ensure your users’ data and business data are secured. It houses a security system based on permission and authentication mechanisms for refined user access and data connections.
  • Tableau Community: You gain immense benefits when you join the Tableau Community. Being a member, you can upskill, build powerful connections, get inspired by the community, and offer mentorship to newcomers.

For further information on Tableau Dashboards, read more here- What is Tableau Dashboard and How to Build it?. To know more about building reports in Tableau, have a look at Building Tableau Reports: A Comprehensive Guide.

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A Brief Information About Types of Charts in Tableau

Tableau offers numerous graphs & options to visualize your data and make inferences. Picking the best representation for your data ensures a clear understanding and faster data interpretation, which is particularly helpful for executives and decision-makers who are pressed for time. Using Tableau charts, your teams can check business trends, analyze KPIs, forecast metrics, and create dashboards to collect, display and compare data.

Here is a brief overview of the different types of charts offered in the Tableau Business Intelligence Application:

  • Bar Chart: A bar chart or bar graph is a routinely used chart that features rectangular bars or columns to represent numerical data. The length of bars is made in proportion to the values they represent, with the width remaining constant. These charts are helpful in comparing different sets of data among different groups like a dual axis chart excel with the number of products manufactured (with multiple subcategories) in different months of the year. 
  • Line Chart: A line chart or line graph represents a collection of data points as one continuous line. These are useful for tracking variations or trends over time like monthly sales in a year, or gross profit margin over a course of five years.
  • Pie Chart: Pie charts are pictorial representations of data in the form of a circular chart or pie. These are usually employed when you want to represent the relationship of parts to a whole. Pie charts, for example, can be used to represent the distribution of your monthly expenditure across Sales, Marketing, Support, and other departments.
  • Maps: Tableau maps are geographical maps for representing continents, countries, states, or cities. You can for instance use Tableau maps to determine how much sales income is generated by each state in the United States.
  • Density Maps: Density maps or heat maps depict the magnitude of a certain metric in relation to its position on the geographical map. Density maps are useful for revealing hidden patterns or relative concentrations that get neglected in geographical maps. One popular use case of density maps is identifying popular regions for taxi pickups in a city.
  • Scatter Plot: Scatter plot or scattergram is a collection of discrete data points on a cartesian plane. When you have an exhaustive relationship between two variables, scatter plots are the best way to represent your data. Examples of scatter plots include plotting height vs weight for a large group of children in a city.  
  • Gantt Chart: Gantt charts are ubiquitous in project management tools. It is a type of bar chart with timelines associated with each task. In Tableau, gantt charts help you track and manage your project deadlines by specifying the start and finish dates, along with milestones, and additional dependencies between tasks. 
  • Bubble Chart: Analogous to scatter plots, bubble charts are magnified dots placed discretely on a plane. These data visualizations are used to conceive a data set with two to four dimensions wherein you can compare multiple data points with varying dot sizes. 
  • Treemap: Treemaps are logical representations of data with a hierarchy structure (tree-structure). In treemaps, the data visualization space is split up into multiple rectangles with varying sizes and categories according to their scale. An example of a treemap is when you display land areas of various countries present in the Asian continent. 

What is a Tableau Dual Axis Chart? (With Benefits)

Dual axis charts or combo charts in Tableau are your silver bullets. They help save space and the effort for back and forth referrals. You may wonder how.

Tableau dual axis charts plot relationships of one variable with two or more variables, all in the same visual- bar chart, pie chart, line graph, or any other, just as your regular dual axis chart excel. This level of visualization provides more versatility to your business decision-makers and gives them the ability to plot multiple data points and series on the same chart, saving space and time for referring back and forth.

Using tableau dual axis charts, you can compare data series measured in different units or with separate scales of comparison. If you wish to visualize multiple data points on the same scale, you can do so and synchronize axes for greater clarity. 

When you create dual axis charts, you choose to display plenty of information in one space, which at times can feel jammed or too crowded for interpretation. Hence, we recommend you only build dual axis charts when there arises a need. Otherwise, it’s better to keep your trends and data points separate (we have talked about the cons of using dual axis charts, and methods to resolve them in the upcoming sections- Tableau Dual Axis Chart: Synchronize Axes For Clarity and Tableau Dual Axis Chart: Intermix Charts For Distinctness).

How to Create a Tableau Dual Axis Chart?

To begin creating your first Tableau dual axis chart, we’ll start with a basic line graph for Sales, Discount, and Order Date. Here we have sorted the measure Order Date by month and assigned it to Columns. In Rows, we’ve appointed the measures Sales and Discount.

Step 1: To enable Tableau dual axis in your chart, right-click on the Discount measure in your Row field and select the option Dual Axis

A new tableau dual axis chart will be generated that will label both your Sales and Discount measures on the Y-axis and Order Date on the X-axis. Here’s a snapshot of what your new graph will look like:

Step 2: For more clarity, we’ll convert this graph into a bar chart. To access the option for graph conversion, you can visit the dropdown list under the Marks tab and select Bar Chart

Notice that our Discount measure overlaps monthly Sales when stacked along with Sales measures, making it indistinct and fuzzy to comprehend. To display our data distinctly, we would need to separate these two rows.

Step 3: To fit and visualize our data correctly, we will use the field Measure Names. Measure Names is an option in Tableau that captures all measures in your data, organized into a single field with discrete values. 

You can drag the Measure Names field from the Measure tab and drop it into your Columns field to split up your overlapping bars. Here’s a preview of what your Tableau dual axis chart would look like:

Step 4 (Optional): For more granular information, i.e. let’s say, you want to know region-wise discount and category wise sales split in your existing data visualization, you can enter your fields SUM(Sales) and AVG(Discount) individually and drag inside all split parameters like Region or Category from the Measures pane as shown in the image below:

With this, you’ll have a more profound visualization of your data with all the required metrics and their distribution in a single canvas. 

Tableau Dual Axis Chart: Synchronize Axes For Clarity

Analogous to dual axis chart excel, Tableau dual axis charts also suffer from a major drawback- your eyes might misinterpret crossing lines or data trends when the scales on both axes are different. 

Here’s one example to explain our idea. Consider the following plot for Global GDP and Indian GDP on the Y-axes and Year on the X-axis. 

A quick glance at this chart reveals that Indian GDP grew at the same rate as the rest of the globe from 2000 to 2009. That conclusion is incorrect because the scales on both axes are different, and so are their rates of change. If we calculate the percentage change in global GDP from 2000-2009, it comes as 70%, whereas Indian GDP grew by a massive 186% for the same time period. 

Such misconstructions can be of harm to decision-makers. Small neglect of the eye can create problems. Hence, we recommend you check and evaluate your Tableau dual axis chart after construction and synchronize axes for enhanced clarity.

To uniformize your scales, follow these steps:

Step 1: Hover your mouse over to any Y-axis or Row field axis.

Step 2: Right-click on the axis name and select synchronize axis from the menu.

This way you introduce consistency in both axes by presenting the same scale or rate of change for those fields for better data visualization.

Tableau Dual Axis Chart: Intermix Charts For Distinctness

In some cases, having two bar charts may seem less important. For example, you may feel that the profit ratio is not important at the next sales meeting, but you may need it, albeit a little less than the sales chart. Using Tableau dual axis charts functionality of intermixing charts, you can choose to subside one measure when put against the other.

Here’s a depiction of what your new data visualization may look like

Instead of plotting the profit ratio as a distinct bar graph, the graph uses a line chart which comes as a subtle measure. Doing so is a very simple process. All you need to do is visit your Marks pane and change the type of chart associated with that measure.

In the Marks area, you can not only customize the chart type associated with your metric but also set colors and other options in the Settings area.

This brings us to the end of this blog. We hope this blog clarified all your questions about Tableau dual axis charts and equipped you with all the knowledge to create your own Tableau dual axis charts. 

To pique your interest we have a few more blogs to help better your use with Tableau:


Dual axis charts help map relationships between two or more variables in a single canvas. These can be customized to display plenty of information in a limited space and can prove beneficial for individuals to quickly analyze data points or trends and make decisions. 

Tableau is a world-class data visualization software that extracts actionable insights from your commonly used data sources like Microsoft Excel, Database Management Platforms like MySQL, PostgreSQL, MongoDB, and CRMs, and Support tools like HubSpot, Salesforce, Zendesk, etc. Migrating all your data into Tableau can get challenging especially when you have a mammoth of data and data sources to pick from. When you choose a reliable, fast, and loss-free ETL platform like Hevo, you get to be as cool as a cucumber. 

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If you have any questions on Tableau dual axis charts, do let us know in the comment section below. Also, share any other topics pertaining to the Tableau Business Intelligence application you’d like us to cover. We’d be happy to hear your opinions.

Divyansh Sharma
Content Manager, Hevo Data

With a background in marketing research and campaign management at Hevo Data and myHQ Workspaces, Divyansh specializes in data analysis for optimizing marketing strategies. He has experience writing articles on diverse topics such as data integration and infrastructure by collaborating with thought leaders in the industry. The impact he can make in data professionals' day to day life drive him create more content.

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