How to Make an X Y Graph in Google Sheets

Trying to spot a relationship between two different sets of numbers can feel like staring at a spreadsheet full of static. An XY graph, also known as a scatter plot, is the perfect tool for cutting through that noise. This article will show you exactly how to create, customize, and interpret a powerful XY graph in Google Sheets to find the hidden patterns in your data.

What is an XY Graph?

An XY graph, or scatter plot, is a chart that displays the relationship between two numerical variables. Each dot on the graph represents a single data point, with its position determined by its value on the horizontal X-axis (the independent variable) and the vertical Y-axis (the dependent variable). Think of it as a way to visually answer the question: "When X changes, what happens to Y?"

When Should You Use an XY Graph?

You should use a scatter plot when you want to discover or demonstrate a correlation between two sets of data. It's the go-to chart for visualizing trends, patterns, and relationships. Common scenarios include:

Marketing Analysis: Is there a relationship between our daily ad spend (X) and the number of website conversions (Y)?
Sales Performance: Does the number of sales calls an agent makes (X) affect their total monthly sales volume (Y)?
E-commerce trends: Does the average customer review score for a product (X) correlate with its total units sold (Y)?
Academic Research: Is there a connection between the hours a student studies (X) and their final exam score (Y)?

In all these cases, a scatter plot instantly makes the relationship - or lack thereof - obvious just by looking at how the dots cluster together on the chart.

Ready Your Data: The Foundation of a Great Graph

Before you create your graph, your data needs to be structured properly within your Google Sheet. For an XY graph, this is very straightforward. You just need two columns of numerical data sitting side-by-side.

The standard convention is to place your independent variable (X) in the first column and your dependent variable (Y) in the second column.

Your independent variable (X) is the one you control, manipulate, or believe influences the other. For example, Ad Spend.
Your dependent variable (Y) is the one you are observing or measuring as a result. For example, Sales Revenue.

Let's use a simple example of monthly advertising spend versus sales revenue. Arrange your data in two columns, just like this, with clear headers:

A: Ad Spend ($)B: Sales Revenue ($)

Make sure your spreadsheet looks clean and contains only the headers and the corresponding number pairs you want to plot.

Creating Your XY Graph (Scatter Plot) in 4 Simple Steps

With your data organized, you can build your initial chart in under a minute. Follow these simple steps.

Step 1: Select Your Data

Click and drag your mouse to highlight all the cells containing your data, including the headers for Column A and Column B. This tells Google Sheets exactly what information you want to visualize.

Step 2: Insert the Chart

With your data selected, navigate to the menu at the top of the screen and click on Insert > Chart. Google Sheets will instantly analyze your data and create a chart for you.

Step 3: Choose the Right Chart Type

Often, Google Sheets is smart enough to guess that you want a scatter plot. However, it sometimes defaults to a line chart or something else. Don't worry, this is easy to fix.

In the Chart editor pane that appears on the right side of your screen, go to the Setup tab. Find the Chart type dropdown menu and scroll until you find and select Scatter chart. This will turn your data into a proper XY graph.

Step 4: Admire Your Basic Graph

You now have a basic but functional XY graph! Google Sheets uses your column headers to automatically label the axes. You can already start to see a potential pattern in your data just by looking at the arrangement of the dots. But to make this graph truly useful, we need to customize it.

How to Customize Your XY Graph for Clarity and Impact

A default chart is a great start, but customization is what turns raw data into a clear story. The Chart editor > Customize tab is where you can refine and polish your graph. Let's walk through the most important adjustments.

1. Fortify Your Titles and Axis Labels

Clear labels are non-negotiable. They provide the context your audience needs to understand what they're looking at. In the Chart editor, click on the Customize tab, and open the Chart & axis titles section.

Chart Title Text: Change the default title to something descriptive, like "Relationship Between Ad Spend and Sales Revenue."
Horizontal axis title (X-axis): Your header should already be here ("Ad Spend ($)"), but you can edit it for more clarity if needed.
Vertical axis title (Y-axis): Adjust the label for your Y-axis ("Sales Revenue ($)") as necessary.

Accurate titles prevent confusion and make your chart immediately understandable on its own.

2. Tweak the Data Points (Series)

Next, let's adjust how the actual data points look. Under Customize > Series, you have a few options to make your data pop:

Color: Change the color of your data points to match your brand or presentation theme.
Point size: If your dots are too small to see clearly, increase the point size from the default 7px to 10px or 14px.
Point shape: You can also change the shape from a circle to a star, triangle, or other options, which can be helpful if you plan on adding a second data series to the same chart later on.

3. Add a Trendline to Reveal a Pattern

This is one of the most powerful features of an XY graph. A trendline is a straight or curved line that shows the general direction or pattern in your data. It visually represents the correlation, making the relationship unmistakable.

In the Customize > Series section, scroll down and check the box next to Trendline. A line will instantly appear overlaid on your data points.

In our example, you will likely see an upward-sloping line, visually confirming that as Ad Spend increases, Sales Revenue also tends to increase. For most business use cases, the default Linear trendline type is all you need.

4. Quantify the Relationship with R² and an Equation

For a more advanced analysis, you can display the mathematical formula of your trendline and its R-squared (R²) value. The R² value is a statistical measure from 0 to 1 that tells you how well your data points fit the trendline - essentially, how strong the correlation is.

Under the Trendline options in the Series menu, find the Label dropdown and select Use Equation. Then, check the box for Show R² value.

A high R² value (e.g., 0.95) means your variables have a very strong relationship. In our example, an R² of 0.95 would mean that 95% of the variation in sales revenue can be explained by changes in your ad spend.
A low R² value (e.g., 0.15) suggests there's a very weak or no relationship between the variables.

Adding these elements doesn't just make your chart look more professional, it replaces guesswork with a clear, quantitative measure of the relationship's strength.

5. Adjust the Axis Scale and Gridlines

Finally, to really zoom in on your data, you might want to adjust the scale of your axes. If your data points are clustered in a small area of the chart, it creates a lot of empty white space.

Head to Customize > Vertical axis (and Horizontal axis afterwards). Here, you can manually set the Min and Max values. For example, if your lowest sales figure is $12,000, you could set the vertical axis minimum to $10,000 instead of 0 to get a more detailed view of the data cluster.

You can also use the Customize > Gridlines and ticks section to add more or fewer gridlines (Major step), giving your chart a cleaner look and feel.

After a few customizations, you've transformed a simple set of dots into a compelling, insightful data story.

Final Thoughts

Creating an XY graph in Google Sheets is a simple but incredibly effective way to uncover the relationships hiding within your numbers. By structuring your spreadsheet correctly and using the customization options to add things like titles, a trendline, and an R² value, you can build clear and persuasive charts that help you make smarter, data-driven decisions.

While mastering Google Sheets is a valuable skill, much of the reporting process still involves a lot of manual work - downloading CSVs, cleaning data, and rebuilding the same reports every week. We built Graphed to automate that entire cycle. Instead of wrestling with spreadsheet cells, you can just ask questions in plain English like, “show me ad spend vs revenue from Google Ads this quarter” and get a real-time, interactive dashboard that is always up-to-date and ready to share.