Which of the following is a common data visualization pitfall?

• A. Misleading axes and truncated scales.
• B. Using multiple sources.
• C. Providing clear axis labels.
• D. Using appropriate chart types.

Answer: (A)

A common pitfall in data visualization is how the axes and scales are set, because that directly shapes how the data’s differences are perceived. If an axis is shortened or starts away from zero, it can make small changes look much bigger than they are, and gaps can seem more dramatic than the underlying data justify. This kind of truncation or misleading scaling nudges the viewer toward a false impression of the magnitude or trend, even though the data may tell a more modest story. The best charts avoid this by choosing scales that honestly reflect the data, starting at a meaningful baseline when appropriate, keeping intervals consistent, and clearly noting any deviations from standard scaling.

For perspective, the other statements don’t describe a visualization pitfall. Using multiple sources is about data provenance rather than charting technique. Providing clear axis labels and using appropriate chart types are good practices that help readers understand the data, not common traps.