How to create a dot plot

Dot plots are a relatively new chart type. Pioneered by William Cleveland in the 1990s, their goal is to allow easy comparison of data with multiple values in one line. They are comparable with grouped bar charts, but more elegant.

  • You have two points that mark absolute quantities of two comparable categorical dimensions and
  • A connecting line between these points that indicates the quantitative difference

This guide will show you how to prepare data to create this chart type. 

1. Preparing and importing the data

Look at the bullet chart above, it shows what kind of information is needed for a similar dataset. If you want to try to create this chart type you can simply use data from the table below.

Tipp: You can copy this data into Datawrapper. Just make sure that you copy all fields. 

Education Men Women
Less than 9th grade 26789 20499
9th to 12 grade (no diploma) 31434 23351
High school graduate 42466 29410
Some college, no degree 48431 35916
Associate degree 51485 40463
Bachelor's degree 76749 53201
Master's degree 97038 63218
Doctorate 125393 91733

Source: sample data

How to format data for a dot plot:

  • One header row cintaining labels
  • The first column contains main categories
  • Two other columns are categorical dimensions containing values of comparable measures

In this case, we have nine different categories, i.e. different education levels. The dot plot will work just fine with one or more than four categories. Be aware that the cells of your table must contain values of the same measures. Each quantitative value will be represented by a dot and the difference of the two values in one row will be recalculated into the length of the connecting line automatically. Once your dataset looks like this, you can upload or copy & paste the table to Datawrapper.

2. Check & Describe

This is what the dataset looks like once it is uploaded into Datawrapper. Make sure that the box "First row as lable" is ticked so that Datawrapper correctly assigns the values to the labels.

One hint: This example is all about salaries, the pay gap between women and men. But note that we did not add a currency sign. It or course possible to add a $ sign, but why? This information would be redundant and clutter the chart. If all values are of the same type it is often much better mention this above the chart in a few words. 

Click on "Proceed" and Datawrapper will take you to the next step.

3. Visualize

Once you're in the " Visualize" tab, choose "Dot plot" and Datawrapper will create a first iteration of your data. Continue with the steps refineannotate, and design to finish your chart. We cover this in a separate short tutrial found here.

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