Maarten Lambrechts is a data journalist I closely follow online, with great delight. Recently, he shared on Twitter his slidedeck on the 18 most common data visualization pitfalls. You will probably already be familiar with most, but some (like #14) were new to me:
Save pies for dessert Don’t cut bars Don’t cut time axes Label directly Use colors deliberately Avoid chart junk Scale circles by area Avoid double axes Correlation is no causality Don’t do 3D Sort on the data Tell the story 1 chart, 1 message Common scales on small mult’s #Endrainbow Normalise data on maps Sometimes best map is no map All maps lie
Even though most of these 18 rules below seem quite obvious, even the European Commissions seems to break them every now and then:
Can you spot what’s wrong with this graph?
In a world where data really matters, we all want to create effective charts. But data visualization is rarely taught in schools, or covered in on-the-job training. Most of us learn as we go along, and therefore we often make choices or mistakes that confuse and disorient our audience.
From overcomplicating or overdressing our charts, to conveying an entirely inaccurate message, there are common design pitfalls that can easily be avoided. We’ve put together these pointers to help you create simpler charts that effectively get across the meaning of your data. Geckoboard
Based on work by experts such as Stephen Few, Dona Wong, Albert Cairo, Cole Nussbaumer Knaflic, and Andy Kirk, the authors at Geckoboard wrote down a
list of recommendations which I summarize below: Present the facts
Start your axis at zero whenever possible, to prevent misinterpretation. Particularly bar charts. The width and height of line and scatter plots influence its messages. Area and size are hard to interpret. Hence, there’s often a better alternative to the pie chart. Read also this. Less is more
Use colors for communication, not decoration. Diminish non-data ink, to draw attention to that which matters. Do not use the third dimension, unless you are plotting it. Avoid overselling numerical accuracy with precise decimal values. Keep it simple
Annotate your plots; include titles, labels or scales. Avoid squeezing too much information in a small space. For example, avoid a second x- or y-axis whenever possible. Align your numbers right, literally. Don’t go for fancy; go for clear. If you have few values, just display the values. Infographic summary