A scatter plot is one of the most powerful and commonly used charts in data analysis. In tools like Tableau, scatter plots help us visualize the relationship between two variables in a simple, visual way.
Many data analysts use scatter plots to identify patterns, trends, and insights from large datasets.
While working as a sales analyst for a retail company, I analyzed sales data to determine whether our high sales were translating into strong profits across product categories.
To visualize this data, I created a Tableau scatter plot. In this, I plotted sales on the X-axis and Profit on the Y-axis, then added Sub-Category to the detail.
From the scatter plot, I noticed that some items, such as tables, had high sales but were actually showing a loss, while others, such as phones, had both high sales and profits. This helped identify which products are generating profit or loss.
In this article, we will learn everything about Tableau scatter plots. We will cover below topics:
- What a scatter plot is
- How to create it in Tableau,
- Real-time examples, types of correlation, use cases,
- Advantages, limitations, and best practices.
By the end of this guide, you will have a clear understanding of how to use scatter plots in real-world scenarios.
What is a Scatter Plot in Tableau?
A scatter plot is a type of chart that uses dots to represent data points. Each dot represents a pair of values—one on the X-axis and one on the Y-axis. These values help us understand the relationship between two numerical variables.
In Tableau, scatter plots are created by placing one measure on the Columns shelf (X-axis) and another measure on the Rows shelf (Y-axis). This allows users to compare two different metrics and identify patterns or relationships in the data.
For example, you can compare:
- Sales vs Profit
- Marketing Cost vs Revenue
- Temperature vs Ice Cream Sales
Each dot in a scatter plot represents a single data point, making it easy to visualize large datasets.
Check out: Tableau Bubble Chart
Key Components of Scatter Plot
A scatter plot contains the following main elements:
- X-Axis (Independent Variable)
- This is the horizontal axis. It represents the input or independent variable.
- Y-Axis (Dependent Variable)
- This is the vertical axis. It represents the output or dependent variable.
- Data Points
- Each point represents a combination of X and Y values.
- Correlation
- Scatter plots help identify how variables are related.
Why Use Scatter Plot in Tableau?
Scatter plots are useful because:
- They show relationships between variables
- They help identify trends and patterns
- They detect outliers easily
- They simplify complex data
Scatter plots are widely used in:
- Business analysis
- Marketing analytics
- Finance
- Data science
How to Create a Scatter Plot in Tableau
In the scatter plot below, we will display the sales profit statistics for product categories across various regions.
Connect with the data source and follow the steps below to create a scatter plot in Tableau.
- Drag the dimensions Sales to the Columns and Profit to the Rows.
- Here, we need to show sales profit by region. For this, we will add the Region to the Color card in the Marks section.
To relate sales by category in each region, add the Category to the details card.
- In the Marks section, change the type from Automatic to Circle.
- To show the Sales categories on the Sales data point, add Sales to the Label card.
Here, when we hover the cursor over the data points, it shows the data for Category, Region, Profit, and Sales.
For example, when I select the color assigned to the Central region (blue), it shows the sales and profit for that specific category.
- To add the grid lines in the Scatter plot, right-click on the scatter plot and select Trend Lines > Show Trend Lines.
After this, you will see grid lines on the Scatter plot, connecting the data points.
This way, we can create a Scatter plot in Tableau by following the above steps.
Check out: Create Area Chart in Tableau
Create a Scatter Plot Using Dual Axis in Tableau
Let’s take another example, where we can compare two sets of measures on the same data point in the Tableau Scatter plot.
In this example, we will create a scatter plot to compare Sales and Profit, and also track the Discount on the same plot.
Connect the data with the Tableau superstore data and follow the steps below to create a Scatter plot using dual axes in Tableau.
- Drag the Sales to Column and Profit to Rows.
- In the Marks section, change the type to Circle. After this, drag the Region to the Color card and Category to the Detail card.
- Drag the Discount to the Size card to visualize the effect of discounting. Here, the larger circle indicates a higher discount.
- Now, add the Quantity to the Rows; this will duplicate the Scatter plot chart to show profit and quantity.
- Click on the dropdown of the Quantity and select Dual Axis.
- With this, you will see the data points of both Profit and Quantity in the same scatter plot.
- To differentiate the Profit and Quantity data points, we will change the type of the Quantity axis.
Now, we can see and differentiate the data points for Quantity and Profit by product category for each region.
With this Tableau Scatter plot, we can analyze the relationship between sales and profits and identify which items are frequently discounted or ordered in high quantities, providing an analysis for multiple data values.
Check out: Create a Radar Chart in Tableau
This way, we can create a Scatter plot in Tableau using the dual axis.
Scatter Plot vs Other Charts
| Chart Type | Use Case |
|---|---|
| Scatter Plot | Relationship between variables |
| Bar Chart | Comparison |
| Line Chart | Trend over time |
Conclusion
Scatter plots in Tableau are powerful tools for analyzing relationships between data variables. They help businesses and analysts understand patterns, trends, and insights quickly.
By using features like trend lines, colors, and labels, you can create meaningful visualizations that support better decision-making.
If used correctly, scatter plots can transform raw data into valuable insights and improve business performance.
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