Introduction to making charts with datawrapper

Chris Knox

04 July, 2021


Datawrapper is

widely used by journalists
, and was created by journalists, to

Enrich your stories with charts, maps, and tables.

  • It’s
    (there is a paid plan but it targets larger organisations)
  • It provides well
    designed and sensible
    defaults making it easy to create a good-looking chart
  • Charts will
    continue online
    is you close your account
  • Fantastic blog
    - well worth reading to get you started thinking about what makes a good chart

Datawrapper has been seen in the wild in the New Zealand Herald, Stuff, RNZ, Newsroom, and The Spinoff. So it’s a useful skill to have in the New Zealand market.

(Yes I know these examples are slightly misleading - exactly why is left as an exercise for the reader)

Get some data

Go to Figure.NZ and search for Teenage fertility and go to this page

A line graph of the teenage fertility rate in New Zealand from 1962 until 2020. It is highest in 1972 and then drops dramatically until the mid-1980s after which it moves up and down a but generally falls

Remember the /data.csv trick - convert the url to

Get the data to Datawrapper

  • You can just upload - or even
    - your data into Datawrapper
  • But Figure.NZ + /data.csv lets us use Datawrapper’s Link external dataset feature

Screenshot of linking a Figure.NZ dataset into Datawrapper

Check & Describe

  • Click through to the
    Check & Describe

The Check & Describe tab is often where things go wrong

But the easiest way to see if they are correct is just to carry on

Screenshot of Datawrapper's Check & Describe tab showing the teenage fertility data from Figure.NZ

  • As the prompt says make sure your dates are green and your numbers are blue


Screenshot of a broken line chart in Datawrapper. Extra data has been included in the plot.

Head back to Check & Describe and look for columns called Cell X and Cell Y

Screen of Datawrapper Check & Describe tab showing additional Figure.NZ metadata

The Datawrapper extract includes some meta-data to keep track of where the data came from.

Hide those columns

Screenshot of Datawrapper Check & Describe showing how to hide columns

And head back to the Visualize tab


That looks more like it

Screenshot of Figure.NZ teenage fertility chart reproduced in Datawrapper

Writing time

  • Getting the data into a chart is
    only the beginning
  • There are things to play with the improve the visual appearance of your chart
    • Or to make it worse or misleading
  • But
    focus on your words
    • Why
      should readers look at this chart?
    • What
      story is the chart telling?

Start with the alt text

Screenshot of title and text annotations in Datawrapper

The finished product