Bar Chart

Bar charts are one of the most fundamental and widely-used visualization types for comparing discrete categories. Each bar represents a category, with its length or height proportional to the value it represents. Bar charts are excellent for showing differences between groups, ranking items, and presenting survey results. They can be oriented horizontally or vertically, and extended to grouped or stacked variations for multi-dimensional comparisons.

Example Visualization

Bar chart comparing average scores across 5 groups with error bars

Try this prompt

"Create a publication-quality bar chart comparing 'Average Performance Scores' across 5 treatment groups (Control, Treatment A, Treatment B, Treatment C, Treatment D). Generate realistic data with n=30 samples per group, varying means (65-90 range), and different standard deviations. Add error bars showing standard deviation with caps. Sort bars by mean value descending. Use a professional color palette, add value labels above each bar, include a horizontal reference line at the grand mean, and add significance stars (* p<0.05) above bars that differ significantly from control."

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Python Code Example

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Common Use Cases

1Comparing performance across categories
2Displaying survey or poll results
3Showing sales by product or region
4Ranking items by value

Pro Tips

Sort bars by value for easier comparison unless categorical order is meaningful

Use horizontal bars when category labels exceed 10 characters

Add error bars with caps (capsize=5) for statistical measures

Include value labels positioned slightly above bars for quick reading