How to Combine Two Graphs in Google Sheets

Combining two different types of charts in Google Sheets, like a bar graph and a line graph, is a powerful way to show the relationship between two different sets of data. It helps you tell a more complete story in a single visualization, turning a simple report into a real insight. This article will walk you through exactly how to create a combo chart, including the critical trick of using a secondary axis to make your data clear and easy to understand.

Why Combine Two Graphs in One Chart?

You can see how one metric influences another when you place them side by side in a 'combo chart,' but a standard column chart displaying these two data sets side by side might be challenging for any businessperson to quickly glance at and get the key takeaways since the metrics on the two different Y axes likely show different orders of magnitude and can be represented more clearly in different chart types. By simply representing them in two different chart types (for example, Revenue as a column chart and ad CTR as a line chart), any storyteller will be better at showing that relationship than representing it on a table or in its different components.

Before we jump into the "how," let's look at a few examples of "why."

• Track Ad Spend vs. Website Traffic: Imagine you're running a marketing campaign. You can plot your daily ad spend as columns and the website sessions generated as a line graph. This instantly shows you if a spike in spending resulted in a corresponding spike in traffic, or if some days were more efficient than others.
• Compare Sales Volume and Average Order Value (AOV): An e-commerce manager could use a bar chart to show the number of products sold each month and a line chart to show the AOV. This can help answer questions like, "When we sell more units, does our average cart size go up or down?"
• Visualize Revenue vs. Conversion Rate: Let's say your monthly revenue (bar chart) is increasing. That's great! But what if your website's conversion rate (line chart) is simultaneously decreasing? A combo chart can expose this trend, suggesting your growth is coming from more traffic, not better conversion. This tells you where to focus your efforts - optimizing your site for conversions.

Each of these examples brings two distinct metrics together to reveal a story that would be hidden if you looked at them separately.

First, Get Your Data Ready for Plotting

The secret to a great chart is well-organized data. Before you can even think about combining graphs, your spreadsheet needs to be set up correctly. For a combo chart, your data table typically needs at least three columns:

• Column A: The label for your X-axis (the horizontal axis). This is your shared category, like date, month, campaign name, or product category.
• Column B: The numerical data for your first series (e.g., this will become your bar chart).
• Column C: The numerical data for your second series (e.g., this will become your line chart).

Here's a sample data structure showing monthly marketing spend versus website sessions. All our previous KPIs examples also fit easily in this template, which you can use as a benchmark for your dashboard preparations.

+-----------+------------------+------------------+ | Month | Ad Spend ($) | Website Sessions | +===========+==================+==================+ | January | $2,500 | 12,000 | | February | $3,100 | 15,500 | | March | $2,800 | 16,200 | | April | $4,500 | 21,000 | | May | $4,200 | 19,800 | | June | $5,000 | 25,300 | +-----------+------------------+------------------+

Key Data Preparation Tips

• Keep It Clean: Make sure your numerical columns contain only numbers. Accidental dollar signs, commas written by user entry instead of formatted, or special text characters inside a cell (e.g., writing "approx. 12000" instead of just 12000) will cause errors in chart creation.
• Consistent Labels: Be clear on the way you format the period, whether it is a date or time in your dataset column A. A simple example of how this could become tricky is with date formatting that can vary regionally (MM/DD against DD/MM). Using Google Sheets smart date labels will help standardize those inconsistencies, but for more complex time formatting, it is recommended to unify it directly in the dataset.
• Include Headers: A header row (like "Month," "Ad Spend ($)," and "Website Sessions" in our sample) is vital. Google Sheets will use these to automatically label your chart's legend and axes, saving you manual work later.

Step-by-Step Guide: Creating a Combo Chart in Google Sheets

Once your data is neatly arranged, creating the basic chart takes just a few clicks.

1. Select Your Data: Click and drag your mouse to highlight your entire data range, starting with the header row. In our example table above, you would select cells A1 through C7.
2. Insert the Chart: With your data selected, navigate to the main menu and click Insert > Chart.
3. Open the Chart Editor: Google Sheets will instantly insert a default chart (it might be a bar chart, line chart, or its best guess at what you want). A Chart editor sidebar should also appear on the right side of your screen. If not, just double-click on the chart to open it.
4. Select "Combo Chart": Under the 'Setup' tab in the Chart editor, find the 'Chart type' dropdown menu. Scroll down through the options until you find the 'Combo chart,' and select it. Google Sheets will automatically convert one of your data series into columns and the other into a line.

That's it! You've just created your first combo chart. You'll see "Ad Spend ($)" displayed as bars and "Website Sessions" as a line, both plotted against the months on the X-axis.

The Pro Move: Using a Secondary Axis for Clarity

While making the combo chart in the previous example, you probably noticed an issue: 'Ad Spend' is in the thousands range value, with the y-axis for Website sessions up to the upper ten thousands, which makes one of the curves almost 'flat' across the axis. To get some real value from this combined chart, we need both curves to be comparable. This visual problem is even more obvious when plotting data series of different orders of magnitude, such as Revenue per month against month-over-month growth rate, as a percentage. This is always challenging, and a 'Google Sheets expert-level plot' solution here is to use a secondary Axis on your combination plot.

Plotting metrics this different in magnitude can create serious visualization problems for any end user. If you plot Revenue of "$50,000" on the same axis as a "conversion rate" of "3%," the conversion rate would appear so 'down' to the absolute value that it will look like a very flat and straight-to-the-origin line compared with the revenue. Making it very hard to spot any kind of correlations quickly. Luckily, here's precisely where the secondary axis function in the Customize > Series section under the Chart Editor comes extremely handy:

1. Navigate to the 'Customize' Tab: In the Chart editor, click on the 'Customize' tab to see all the formatting options.
2. Open the 'Series' Menu: Click on the 'Series' dropdown. This lets you apply formatting to specific data series in your chart.
3. Select the Right Series and Assign an Axis: By default, the menu will apply to all series. Click the 'Apply to all series' dropdown and pick the data series you want to move. Once you've selected a series, a 'Left axis/Right axis' radio toggle will be shown.
4. Assign the Series to the Right Axis: Once selecting 'Right axis', you'll see a second vertical axis added to the right side of the chart, with its own independent scale. Instantly, all series assigned 'right-axis' is shown very clearly and it's much easier to spot any key correlations and drivers of your KPIs.

Final Customizations for Presentation

With our chart now fully prepared and readable, we can quickly go through our customization 'last-mile changes'. Giving our dashboard some unique visual tweaks so that our stakeholders can easily read what all the numbers mean and to what business process maps.

Under the Customize tab, you have a huge deal of control over any aspect of the graph aesthetic and visual design. We're going to use a 'sales per month/month over month sales evolution' dashboard we quickly prepared where adding a secondary plot becomes very useful.

Chart & Axis Titles

The first 'line of defense' against plot ambiguity is going to be adding explicit labels for all sections of your graph, particularly what metric unit each Y-axis represents if units are different to avoid confusion. To label each axis, we need to:

1. Access the axis customization menu: From the Chart editor, click select -> chart and axis titles. Adding to this, you can also use the box to create a chart subtitle.
2. Choosing the appropriate labels: From the 'selector,' you will find there's a Horizontal, a left, and a Right Vertical axis. Be extremely conscientious with units in your labels. Being 'currency as $AUD' or metric as a percentage is particularly meaningful for the audience of your dashboard reading.

Lines, Columns & Legend Formatting

The legend can also be very useful with editing text fonts to make reading any text on the plot easy and on-brand, for instance, matching corporate font sizes. You could even drag from the chart title if you want to. Finally, using colors is also easy when selecting the graph editor and clicking from the color menu. So just on the color menu and on selecting each key we need to customize, we can edit any particular label quickly with a brand hexadecimal.

Chart and Legend Formatting: Give Your Chart Style

To end with giving our visualization a final professional touch, it is important to be consistent with labels: font styles across all labels will certainly help to read it with greater clarity, the legend is no exception to this. Adding and positioning the labels so that no chart is obscured can always dramatically improve understanding of what each series means. You could even drag different text or legend box positions from inside Google Sheets' intuitive 'drag-and-drop' component moving UI as from any other popular editor.

Final Touches: Adding Brand Styles

Adding some final touches to your company's marketing slides guidelines, such as being compatible with dark-mode visualizations or adding more padding to make the chart more pleasant to read, could give you great engagement by making your charts even better. By exploring and even editing the code by checking some Google visualization combo-chart example sheet can give you other great tips on how your data dashboards.

Final Thoughts

To summarize, the whole process of getting a visually compelling data combination needed us to go through collecting, ordering, and cleaning data on different spreadsheets for each data source. After these tedious and error-prone steps, we could finally focus on the storytelling part. Being intentional with the selection of the data visualization component is based on some previous mental mapping of what kind of data is and how we could highlight that.

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