Radar Chart Maker Online
Compare multiple variables on a radar chart. Visualize strengths and weaknesses across different categories for analysis and presentation.
Enter data as comma-separated values (subject, value1, value2, value3), one per line
Performance Comparison
Series Statistics
Employee A
Employee B
Data Summary
| Subject | Employee A | Employee B |
|---|---|---|
| 0 | 85 | 75 |
| 0 | 90 | 80 |
| 0 | 78 | 85 |
| 0 | 88 | 70 |
| 0 | 92 | 88 |
| 0 | 80 | 90 |
How it works
Enter your variables and their values. Each variable becomes an axis radiating from the center. Values are plotted on their axis and connected to form a polygon shape.
Multiple data series can be overlaid for comparison. Each series gets a different color. The resulting shapes show strengths and weaknesses across all dimensions at once.
Data format:
Variable, Product A, Product B Performance, 85, 72 Design, 90, 65 Value, 70, 88 Support, 75, 80 Features, 88, 75
The chart renders with concentric grid lines showing value levels. Interactive tooltips display exact values. Compare shapes to see which excels in which areas.
When You'd Actually Use This
Product comparison matrices
Compare products across multiple attributes. See which product excels where. Consumers make informed decisions based on their priorities.
Employee performance reviews
Show performance across competencies. Managers and employees see strengths and development areas. Career planning becomes data-driven.
Video game character stats
Display character attributes: strength, speed, intelligence, etc. Gamers compare characters. Game balance becomes visible.
Restaurant review scoring
Rate food, service, ambiance, value, location. Diners see overall profile. Restaurants identify improvement areas.
Skills assessment visualization
Map individual skills across categories. Job seekers show capabilities. Employers assess candidate fit across dimensions.
Country development indicators
Compare nations across GDP, education, health, freedom, etc. Policymakers see relative standing. International comparisons become clear.
What to Know Before Using
All axes should use the same scale.Variables must be comparable (0-100, 1-5, etc.). Different scales distort the shape. Normalize data if scales differ.
Axis order affects shape appearance.Adjacent variables connect directly. Different ordering creates different shapes from same data. Order logically or alphabetically.
Area doesn't equal overall score.A larger polygon doesn't necessarily mean better. A balanced profile may have smaller area than a spiky one. Consider average too.
Too many variables creates clutter.5-8 variables work well. More than 10 becomes hard to read. Group related variables or create multiple charts.
Pro tip: Use transparency for overlapping series. This lets viewers see all shapes clearly. 50-70% opacity works well for 2-3 series.
Common Questions
How many variables work best?
5-7 variables is ideal. 3-4 works but looks sparse. 8-10 is the practical maximum. More becomes visually overwhelming.
Can I compare many series?
2-4 series overlay well. More than that becomes confusing. For many series, use small multiples or interactive highlighting.
What's the difference from spider charts?
They're the same thing. "Radar chart", "spider chart", and "web chart" are different names for the same visualization.
Should I connect the last point to first?
Yes, radar charts are closed polygons. The last variable connects back to the first. This creates the characteristic web shape.
How do I handle missing data?
Gaps in the polygon indicate missing values. Or use zero/null and note it in legend. Don't interpolate missing values without noting it.
Can I use non-numeric data?
No, radar charts require numeric values. Convert ratings (poor/fair/good) to numbers (1/2/3) first. Ordinal data works with numeric mapping.
When should I use bar charts instead?
Bar charts are better for precise value comparison. Radar charts show overall profiles. Use bars for accuracy, radar for patterns.
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