⚠️ Watch out for Moiré effects! Make sure that the gap between the bars is significantly smaller than the bars themselves. Otherwise, it creates a distracting zebra-stripey pattern. For Edward Tufte, these unintentional patterns are one of the major sources of chartjunk. (3/4)

⚡ For #dataviz purists, a bar chart is not the ideal way of showing evolution - they would prefer a line chart - but I can appreciate it when the data is countable. You wouldn't use a bar chart for something that evolves continuously, e.g. weight, but for cars it works. (2/4)

Day 3 of exploring alternative chart types for the same dataset: a good old stacked bar chart! ✅ Enables us to see not only the evolution of the total, but also the breakdown by category, ánd the evolution for each category. Check, check and check. (1/4)

Pro #dataviz tip for stacked area charts: it's usually a safer bet to place your smallest categories at the bottom of the chart. (3/3)

This type of chart works best if you want focus on the breakdown of the total into different categories. For example, if you want to show that electric cars are still only a tiny fraction (<5%) of all registered cars. That's what's called a 'part-to-whole comparison'. (2/3)

Day 2 of exploring alternatives for this line chart: how about a stacked bar chart? ✅ Also shows the total number of cars, which might be interesting. ❌ I find it a bit harder to read values for intermediate years. (1/3)

Or we can make Edward Tufte proud and build a really clean and minimal slopegraph: (3/3)

Even if for some reason you need to add *all* data labels, the tool handles it graciously: (2/3)

In #dataviz@datawrapper.bsky.social, you now have more options to play with labels in line charts. For example, we could have this lightweight approach where only the first and last values are labeled: (1/3)

Day 1 of exploring alternative charts for this dataset! Let's start by simply optimizing the line chart. ✅ Categories are more easily distinguishable ✅ Extended data range gives more context, better ticks ✅ Direct labeling avoids legend, shows final values ❌ Total values are not visible #dataviz