Scatter plot – an overview

What is it for? 

The scatter plot is a powerful and multifunctional template for creating two-dimensional scatter plots, bubble charts, Hans Rosling charts, box plots, beeswarm charts and violin plots.

It's ideal for showing correlation, trends and outliers, and extra information can be encoded using colour, shape and size. Data can also be divided into multiple smaller datasets using the Grid of charts feature.

How to get started

    To make a simple scatter chart, all you need is two columns of data: one for the x (horizontal) axis and one for the y (vertical) axis. Each row is plotted as a dot, and the spread of dots on the chart shows the relationship between the two metrics. Addition columns can be used to set the colour, size and shape of the dots, or to create interactive controls and custom popups.
    Name Category to colour by X values Y values Category or value to size by
    Hong Kong SAR, China East Asia & Pacific 42351.0246 84.27804878 7305700
    Japan East Asia & Pacific 34474.13736 83.84365854 127141000
    Macao SAR, China East Asia & Pacific 75573.48071 83.59490244 600942
    Italy Europe & Central Asia 30049.14755 83.4902439 60730582
    Spain Europe & Central Asia 25683.84565 83.3804878 46447697

    If your data has a column with years or dates, you can create an animated scatter showing change over time. Select a Time column in the Select columns to visualise panel to create a slider and choose one or more Name columns so the template knows which rows represent the same thing. Read more about creating an animated scatter plot here.

    If you're overwhelmed by the number of points, you can choose a Filter column to create a menu to switch between subsets of the data.  Read more about creating a scatter plot with a filter here.

    You can include as many Info columns as you like to display inside your popups, and advanced users can even use HTML and CSS to pull in pictures or videos from a column of image or video URLs. Read more about adding custom popups here.