Data visualization is a powerful tool to communicate complex information in an engaging way. By visualizing information, our brains can synthesize and retain content more effectively, increasing its impact. But if data isn’t properly visualized, it can do more damage than good. The wrong presentation can diminish the data’s message or, worse, misrepresent it entirely.
Here are 10 data visualization mistakes you’re probably making and the quick fixes to remedy them.
1) Misordering Pie Segments
Pie charts are some of the most simple visualizations, but they are often over-complicated.
2) Using Non-Solid Lines in a Line Chart
Dashed and dotted lines can be distracting. Instead, use a solid line and colors that are easy to distinguish from each other.
3) Arranging Data Non-Intuitively
Your content should be presented in a logical and intuitive way to guide readers through the data. Order categories alphabetically, sequentially, or by value.
4) Obscuring Your Data
Make sure no data is lost or obstructed by design. For example, use transparency in a standard area chart to make sure the viewer can see all data.
5) Making the Reader Do More Work
Make it as easy as possible to understand data by aiding the reader with graphic elements. For example, add a trendline to a scatterplot to highlight trends.
6) Misrepresenting Data
Makes sure all representations are accurate. For example, bubbles should be scaled according to area, not diameter.
7) Using Different Colors on a Heat Map
Some colors stand out more than others, giving unnecessary weight to that data. Instead, use a single color with varying shades or a spectrum between two analogous colors to show intensity.
8) Making Bars Too Wide or Too Thin
It’s tempting to get creative with your presentation, but keeping things consistent helps your viewer. The space between bars in a bar chart should be ½ bar width.
9) Making it Hard to Compare Data
Comparison is a valuable way to showcase differences, but it’s useless if your viewer can’t easily compare.
10) Using 3D Charts
Though they may look exciting, 3D shapes can distort perception and therefore skew data. Stick with 2D shapes to ensure data is presented accurately.
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