We've all been there: you spend hours perfecting your data, only to present it in a chart that confuses your audience or worse, misrepresents your findings. The truth is, choosing the wrong chart type is one of the most common mistakes in data visualization—and it's costing you credibility.
The good news? Most visualization mistakes follow predictable patterns, and they're surprisingly easy to fix once you know what to look for.
In this guide, we'll expose the 5 most commonly misused chart types and show you exactly how to fix them. Whether you're creating reports for executives, social media infographics, or internal dashboards, these fixes will instantly make your visualizations clearer and more impactful.
1. Pie Charts: The Most Overused (and Misused) Chart Type
The Problem
Pie charts are everywhere, but they're being used in situations where they actively harm comprehension. The human eye struggles to compare angles and areas accurately, making pie charts terrible for precise comparisons.
Common mistakes:
- Using pie charts with more than 5-6 slices
- Trying to show changes over time with multiple pie charts
- Using 3D effects that distort slice sizes
- Displaying slices with similar percentages (like 23% vs 26%)
Why It's Wrong
Our brains are much better at comparing lengths (like in bar charts) than angles or areas. In their landmark 1984 study on graphical perception, Cleveland and McGill found that position along a common scale (bars) is decoded far more accurately than angles (pie slices).
The Fix
Replace with a bar chart when you have:
- More than 6 categories
- Values that are similar in size
- Any need for precise comparison
Keep the pie chart only when:
- You have 3-5 categories maximum
- One slice is significantly larger (showing dominance)
- You're emphasizing part-to-whole relationship over precise values
- The story is "more than half" or "less than a quarter"
How to fix it:
- Excel: Select pie chart → Chart Design → Change Chart Type → Bar → Format as horizontal → Right-click axis → Sort by value descending
- Google Sheets: Select chart → Chart editor → Setup → Chart type: Bar chart → Customize → Sort by: Total descending
- Tableau: Click Sort icon → Field: Measure → Descending
2. Line Charts for Unrelated Categories
The Problem
Line charts are being used to connect data points that have no continuous relationship. You'll often see this with categorical data like "Sales by Product Category" or "Performance by Department"—where the line connecting the points is mathematically meaningless.
Why It's Wrong
Lines suggest continuity and progression. When you connect "Shoes" to "Electronics" to "Food" with a line, you're implying a relationship between these categories that doesn't exist.
The Fix
Use a bar chart or column chart instead when:
- Your x-axis shows categories (not continuous time or numeric data)
- The order could be changed without losing meaning
- You're comparing independent groups
Keep the line chart only when:
- You're showing true time series data
- The x-axis represents a continuous scale (time, temperature, distance)
- The connection between points has mathematical meaning
3. Dual-Axis Charts That Deceive
The Problem
Dual-axis charts (charts with two different y-axes) are powerful but dangerous. They're frequently used to exaggerate correlations or create misleading comparisons between datasets with different scales.
Why It's Wrong
By adjusting the scales on each axis, you can make any two trends appear to move together—even if they're completely unrelated. Stephen Few, in his book Show Me the Numbers, recommends avoiding dual-axis charts entirely in favor of separate visualizations or small multiples.
The Fix
Use two separate charts when:
- The metrics have completely different units (dollars vs. percentage vs. count)
- There's no meaningful relationship between the datasets
- Your audience needs to understand each trend independently
Better alternative: Indexed Values
Instead of dual axes, convert both metrics to indexed values starting at 100. This shows relative change without scale manipulation.
Example calculation:
- Website traffic: Jan = 1,000 visitors (baseline = 100), Feb = 1,100 visitors (110), Mar = 1,250 visitors (125)
- Revenue: Jan = $50,000 (baseline = 100), Feb = $55,000 (110), Mar = $70,000 (140)
Now both metrics are on the same scale (indexed to 100), and you can see that revenue is growing faster (140) than traffic (125) without manipulating axes.
4. Stacked Bar Charts for Comparing Individual Categories
The Problem
Stacked bar charts look sophisticated and space-efficient, but they make it nearly impossible to compare individual segments across groups. Only the bottom segment has a common baseline—everything else is floating.
Why It's Wrong
When segment values aren't at the bottom of the stack, readers can't accurately judge their size because they lack a common baseline.
The Fix
Use grouped bar charts instead when:
- Comparing individual categories across groups is important
- Segment values are more important than totals
- You have fewer than 5-6 groups to compare
Keep stacked bars only when:
- The total is the main story (and you put that in a label)
- You're showing part-to-whole composition
- One segment (usually bottom) is the primary focus
Advanced tip: Use 100% stacked bars when you care about proportions, not absolute values.
5. 3D Charts That Distort Reality
The Problem
3D effects in charts might look impressive in a PowerPoint template, but they actively distort data by introducing perspective that makes values harder to read accurately.
Why It's Wrong
3D effects violate the fundamental principle of data visualization: accurate representation. A bar in the foreground appears larger than an identical bar in the background due to perspective. Edward Tufte, in his seminal work The Visual Display of Quantitative Information, famously criticized 3D charts as introducing "chartjunk."
The Fix
Always use 2D charts for business and analytical data. Period.
Modern data visualization tools and platforms—from Datawrapper to Flourish to Highcharts to Plotly to specialized platforms like 5of10.com—have largely removed or hidden 3D options by default. This isn't a trend; it's a recognition that accuracy and clarity always trump decorative effects.
If you want visual interest:
- Use color strategically to highlight key data
- Add annotations and labels
- Use interactive features (hover states, filtering)
- Employ thoughtful typography and spacing
- Create small multiples for comparisons
Key Takeaways
- Pie charts: Use only for 3-5 categories when showing part-to-whole relationships; otherwise, switch to bar charts
- Line charts: Reserve for time series and continuous data only; use bars for categorical comparisons
- Dual-axis charts: Avoid unless there's a genuine relationship; use separate charts or indexed values instead
- Stacked bars: Use only when totals matter; switch to grouped bars for category comparisons
- 3D effects: Eliminate entirely from your visualization toolkit
Quick Audit Checklist
If you're looking at a presentation or dashboard full of problematic charts, tackle them in this priority order:
- Remove ALL 3D effects (Easiest fix, zero exceptions, immediate credibility boost)
- Replace pie charts with >5 slices (Most common mistake, huge clarity improvement)
- Fix line charts with categorical x-axes (Quick conceptual shift from trend to comparison)
- Evaluate dual-axis charts (Can you split into two separate charts or use indexed values?)
- Review stacked bars (Are you comparing middle segments? Switch to grouped bars)
Conclusion
The right chart type can transform confusing data into instant clarity, while the wrong one can undermine even the most rigorous analysis. By recognizing these five common mistakes and applying the fixes above, you'll create visualizations that communicate clearly, maintain credibility, and actually help your audience make better decisions.
Your Next Steps:
- Audit your last 3 presentations using the Quick Audit Checklist above
- Start with the easiest wins: Remove 3D effects first (zero debate, instant improvement)
- Fix high-impact mistakes: Replace multi-slice pie charts with sorted bar charts
- Learn one advanced technique: Practice creating indexed-value charts for dual-axis situations
- Bookmark this guide: Reference it before finalizing your next dashboard or report
The goal isn't to make the fanciest chart—it's to make the clearest one. Your audience will thank you with better comprehension, faster decisions, and increased trust in your analysis.