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Learning How to Use and Interpret a Radar Chart


 A radar chart is useful when:

  1. Comparing multiple entities across multiple variables – It visually displays strengths and weaknesses across categories.

  2. Identifying patterns and outliers – The shape of the plot helps quickly assess which variables perform well or poorly.

  3. Highlighting multi-dimensional data – Radar charts are effective in visualizing performance, competencies, or risk factors.

For example, in the chart above, we have five stocks (AAPL, MSFT, TSLA, AMZN, and NVDA) evaluated across five financial metrics:

•                 Revenue Growth

•                 Profit Margin

•                 Return on Equity (ROE)

•                 Debt-to-Equity Ratio

•                 Dividend Yield

A Radar chart of the five stocks would look like this:

# Chart generated with Python code using synthetic (fictional data)  generated by DeepSeek and plotted with online Python compiler trinket.io

How to Read and Interpret a Radar Chart

  1. Each axis represents a metric (e.g., Revenue Growth, Profit Margin, etc.).

  2. Each entity (e.g., stock) has a unique shape – Larger enclosed areas generally indicate better overall performance.

  3. Closer to the outer edge = stronger performance – The further from the centre, the better the stock performed in that metric.

  4. Overlapping areas – If two stocks have similar performance, their areas will be similar.

For example, in the chart:

  • MSFT has a high Profit Margin and Dividend Yield.

  • TSLA has the highest Debt-to-Equity ratio, indicating higher leverage risk.

  • AAPL is balanced but slightly weaker in Dividend Yield.

Interpreting the Radial Scale (0.2, 0.4, 0.6, 0.8):

Radial Scale Indicators: The numbers radiating out from the centre (0.2, 0.4, 0.6, 0.8) represent the scale of measurement for each metric. In this example, the values for each metric have been normalized between 0 and 1 for visualization purposes.  Since the data is normalized between 0 and 1, a value closer to 1 indicates stronger performance or a higher score in that metric, while values closer to 0 indicate weaker performance.

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