Scatter plot – an overview
What is it for?
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.