January 19th, 2023
“MakeoverMonday” is a simple idea: Each Sunday, give a whole community some chart data and let them build new charts with it. It’s fun to participate. But it’s also fun to see what other people have created, e.g. on the discussion page of data.world (where the data is hosted) or with the hashtag #makeovermonday. The project exists since 2016, so there are more than 100 weeks to explore. And at the end of each week, the organizers Eva Murray & Andy Kriebel, sum up their findings from each week.
The charts can be built with any data vis tool one likes to use or wants to learn. So I gave it a go.
This week, MakeoverMonday was about OECD data on paid maternity leave. Since this Weekly Chart comes out on Thursday, there were already dozens of interpretations of this data out there. It was interesting to browse them and to think: “How can I show the data differently to emphasize another point?” Seeing the other chart designs made me want to be innovative – but on a small scale: Many other people created a scatterplot with this data. So how could my scatterplot be just a little bit different? That’s my attempt:
We can see that all OECD nations, but the US offer mothers a paid leave but the length of the leave and the payment rate differs a lot in each country. For example, mothers in both Sweden and Bulgaria get a bit below 80% of their previous earnings during their maternity leave. But while Swedish mothers get that money for three months, Bulgarian mothers get it for ten months longer.
There’s lots of stuff worth discussing in this chart: annotations, colors, the quadrants, the opacity of the data symbols. But there are two design decisions I especially want to focus on today:
First, the margin between the quadrants and the axes. You can see that the chart doesn’t really start at zero/zero – because that’s where the United States data point is placed. I wanted some extra room around zero/zero to properly include it. But negative values don’t make sense for months nor payment rates! Readers should compare the data points with a zero/zero baseline. So…what to do? I experimented a bit and decided to start the axes at negative values (-0.4/-0.3), but the quadrants at zero/zero – which creates a margin and “inner ticks”. (Do you have a better idea? Let me know!)
The second, design decision deals with the labels in the quadrants: “less money & less time”, “less money but more time”, etc. If I wanted to be correct, they should all come with an additional “…than the OECD average”. But only one of them does. That’s due to space problems (the typeface needs to be way smaller to fit these extra words everywhere). But I like to see it as a feature, not a bug: The chart becomes a bit cleaner without this additional phrase. In the best case, the reader looks at the upper-right quadrant first and understands that “…than the OECD average” applies to all of the quadrants. Removing this phrase from every label but one removes unnecessary clutter.
If you want to learn how to design better charts, participating in MakeoverMonday is a good idea: Just in comparing your designs with other ones (that show the same data), you’ll get many new ideas for future charts. I’ll see you next week!
Since Andy and Eva are both close to Tableau, this tool tends to be used the most by MakeoverMonday attendees.↩︎