Less smoke in the Western world

This week’s chart is short and simple…because summer is here! It’s a warm day in Berlin, refreshingly surprising after a long, long winter. Everybody’s sitting outside, drinking a beer, enjoying the sun, smoking a cigarette…well, but do they? When I was twelve years old, on average six cigarettes were sold to each German adult each day. Now, it’s a third less:

Developed countries must make the tobacco industry cry: Many of them experienced the peak in tobacco consumption between the 40s and 80s. During this time, the US had a higher cigarette consumption than Germany – by now, it’s less. Still: The current three to five cigarettes per adult per day seems a lot to me. And this chart just shows us some developed countries: In many developing countries, cigarette consumption is going up. Chinese adults bought more cigarettes each day in 2014 than US-Americans at the beginning of the 60s.

Chart Choices

In the chart title, I mention “developed countries”. I also show lots of them – but then I highlight just three countries, the United States, Germany and France. Why? Because the alternative would be to either give them all a different vibrant color or to leave them grey. Both would be harder to read. The lines would be a tangled mess in which it’s hard to see the trend. So in some cases, it can be a good idea to make one to three countries stand out of the chaos as examples of the trend.

Another small detail in this chart is to extend the y-axis to zero. Datawrapper line charts don’t automatically do that for good reasons. But when the y-axis comes close to zero anyway and the main statement is still visible, including the zero baseline increases readability and comparability by a lot. When creating a line chart, it’s a good idea to quickly check if including zero might be an option.

By the way: I silently recorded my process, showing how I got the data from an Our World in Data article into Datawrapper, via Google Sheets: Click here to watch the video on YouTube. You will see me use pivot tables (which I will explain in another blog post) & the filter option. See you next week!

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