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Choosing the Right Chart Type (A Decision Tree That Helps)

Published 2026-03-20 \u00b7 4 min read

Bar or line? Pie or donut? Horizontal or vertical? Stacked or grouped? The number of chart options is overwhelming, and picking the wrong one can completely misrepresent your data. Here's a decision framework that actually helps.

The Chart Decision Tree

Start with one question: what relationship are you showing?

The AI Chart Generator automates this decision. Paste your data, describe what you want to show, and it selects the appropriate chart type and generates it.

The Pie Chart Debate

Pie charts are the most misused chart type in existence. According to Tableau's research, humans are terrible at comparing angles and areas — which is exactly what pie charts ask us to do.

When pie charts work: 2-3 segments where one is clearly dominant (like "75% yes, 25% no"). When they don't: anything with more than 4 segments, or when segments are similar in size.

Alternative: a horizontal bar chart sorted by value. Always clearer, always more precise.

Formatting Rules That Make Charts Readable

Common Mistakes

Truncated Y-axis: Starting the Y-axis at 50 instead of 0 makes a 5% change look like a 50% change. Always start at 0 for bar charts. Line charts can start higher if you note it clearly.

Dual Y-axes: Almost always misleading. Two different scales on the same chart lets you imply correlations that don't exist. Use two separate charts instead.

Too many colors: If your legend has more than 6 items, your chart has too many categories. Group the small ones into "Other."

Data Preparation

Good charts start with clean data. Use the Data Cleaning Tool to remove duplicates and fix formatting. The Data Visualizer can suggest the best chart type. For complex analysis, the Report Generator combines charts with narrative context.

As HBR's visualization guide puts it: "The goal of a chart is not to show data. It's to show an insight."

Generate the right chart for your data.

Try the Chart Generator →

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