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Radar Chart Maker

Created:August 13, 2025
Last Updated:September 8, 2025

Create professional radar charts (also known as spider charts or star charts) to compare multiple variables across different categories. Perfect for performance analysis, competitive comparisons, and multi-dimensional data visualization.

Try it out!

  1. Click here to load the sample data
  2. For Category column, select category
  3. For each trace, select value as the Value column
  4. Set Filter Column to product and choose different filter values for each trace
  5. Click Generate Radar Chart to visualize the data
  6. Try adding a trace for "Car C" to see how it compares!

Calculator

1. Load Your Data

2. Select Category Column & Configure Traces

Data Traces

Trace 1

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Learn More

Radar Charts: Definition, Uses, and Interpretation

What is a Radar Chart?

A radar chart (also known as a spider chart, star chart, or polar chart) is a graphical method of displaying multivariate data in the form of a two-dimensional chart. Each variable is represented on its own axis that starts from the center of the chart, and all axes are arranged radially around the center point.

Common Uses of Radar Charts

  • Performance analysis and employee evaluations
  • Product comparison across multiple features
  • Sports analytics and player comparison
  • Market research and competitive analysis
  • Risk assessment across different categories
  • Quality metrics and KPI dashboards

Interpreting Radar Charts

When analyzing a radar chart, consider the following:

  • The area enclosed by each trace indicates overall performance
  • Distance from center shows the value for each category
  • Irregular shapes indicate strengths and weaknesses across categories
  • Overlapping areas show where different traces perform similarly

Best Practices for Radar Charts

  • Limit the number of variables to 3-8 for readability
  • Use consistent scales across all axes
  • Arrange variables in a logical order around the chart
  • Use different colors or line styles for multiple traces
  • Consider the order of variables to avoid misleading visual impressions
  • Include clear labels and legends for all traces and axes