How to create a dot plot
Dot plots are a relatively new chart type. William Cleveland created them in the 1990s. Dot plots show one or multiple dots on one line. If your emphasis is on the gap between these dots rather than the dots, then a range plot is the better choice. If you want to show how a data point has changed over two years, then choose an arrow plot.
That's what every dot plot shows:
- At least one dot on each line. It's possible to have many dots on one line, but we recommend to have a maximum of three of them. In exceptional cases, five dots can be ok.
- If you have more than one dot on a line, a connecting line between these points appears that indicates the quantitative difference.
- A color key indicates what each dot is showing.
This guide will show you how to prepare data to create this chart type.
Preparing and importing the data
If you want to try to create this chart type, your data needs to be in a certain format. You'll need:
- One header row contains labels
- The first column contains main categories. Each main category will appears as a line.
- At least one other column contains numeric values. Each of the numeric columns is represented by one dot on the line. Remember, you can have as many columns as you like, but the more dots you have on the lines, the harder it gets to read.
That's how the data looks like for the chart you can see above. (You can simply copy the data to recreate the chart. Just make sure you copy all the rows and columns.)
Country Total Male Female 1st: Monaco 52.4 51.1 53.7 2nd: Japan 46.9 45.6 48.3 3rd: Germany 46.8 45.7 47.9 Europe 42.7 41.3 44.1 United Kingdom 40.5 39.3 41.7 Australia 38.6 37.8 39.4 United States 37.9 36.6 39.3 New Zealand 37.8 36.9 38.7 China 37.1 36.2 38.1 World 30.1 29.4 30.9
In this case, we have ten different categories, i.e. countries. Be aware that the cells of your table must contain values of the same measures. Each quantitative value will be represented by a dot. Once your dataset looks like this, you can upload or copy & paste the table to Datawrapper.
Check & Describe
This is what the dataset looks like once it is uploaded into Datawrapper. Make sure that the box "First row as
label" is ticked so that Datawrapper correctly assigns the values to the labels.
Click on "Proceed" and Datawrapper will take you to the next step
Once you're in the "Visualize" tab, choose "Dot Plot" and Datawrapper will create the first iteration of your data. Continue with the steps refine, annotate, and design to finish your chart. We'll cover this in a separate short tutorial.