How do you compare multiple scatter plots in a dashboard or report?

1 Choose a consistent scale

One of the most important aspects of comparing scatter plots is to use a consistent scale for both the x-axis and the y-axis. This will help you avoid misleading or confusing your audience. For example, if you are comparing the income and happiness of different countries, you should use the same range of values for both variables across all the plots. Otherwise, you might create an impression that some countries are much richer or happier than they actually are.

2 Use different colors or symbols

Another way to enhance your scatter plots is to use different colors or symbols to represent different groups or categories in your data. For example, if you are comparing the performance of different products, you can use different colors to show the product type, or different symbols to show the customer segment. This will help you highlight the similarities and differences among the groups, and also make your plots more visually appealing.

3 Add trend lines or curves

Sometimes, you might want to show the overall direction or shape of the relationship between the variables in your scatter plots. For example, if you are comparing the sales and advertising of different products, you might want to show how the sales increase or decrease with the advertising. In this case, you can add trend lines or curves to your scatter plots, using linear or nonlinear models. This will help you summarize the data and identify the best fit for your analysis.

4 Use interactive features

If you are creating a dashboard or report with multiple scatter plots, you might want to add some interactive features to make your plots more engaging and dynamic. For example, you can use filters, sliders, tooltips, or zooming to allow your audience to explore the data and focus on the aspects that interest them. You can also use linked or synchronized plots to show how changing one variable affects the other variables in the other plots. This will help you create a more interactive and immersive experience for your audience.

5 Use annotations and labels

Finally, you might want to use annotations and labels to add some context and explanation to your scatter plots. For example, you can use text boxes, arrows, or markers to point out some interesting or important observations, such as outliers, clusters, or gaps. You can also use titles, legends, or axis labels to provide some information about the variables, units, or sources of your data. This will help you communicate your message and insights more clearly and effectively.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?