Free Pie Chart Generator – Create Proportional Charts Online

Show category proportions and part-to-whole relationships at a glance.

Display Options
Colors
Box Plot AI

Hi! I'm your Box Plot analysis assistant.

Analyze the data currently on your chart — I'll interpret min, Q1, median, Q3, max, IQR, and outliers • Generate sample data — e.g. "generate 10 datasets of monthly temperatures, 20 points each"Explain statistics — ask me "what does IQR tell me?" or "how to spot skewness in a box plot"

Try: "Analyze my current data" or "Generate temperature data for 12 cities, 15 points each"

How to Use This Free Pie Chart Generator – Create Proportional Charts Online

  1. Enter labels and values. Each line should be formatted as "Label: Value" — for example "Apple: 35".
  2. Click Generate. The tool calculates percentages and renders a proportional pie chart.
  3. Review proportions. Each slice size is proportional to its value relative to the total.

What is a Pie Chart?

A pie chart is a circular statistical graphic divided into slices to illustrate numerical proportion. Each slice's arc length is proportional to the quantity it represents.

Frequently Asked Questions

How do I format data for a pie chart?
Each line should be formatted as 'Label: Value'. For example: 'Apple: 35'. The tool automatically calculates percentages.
How many categories can I have?
Up to 10 categories for best readability. More than 10 slices can become hard to distinguish.

Key Terms

Proportion
The fraction of the total represented by each slice.
Category
Each distinct group shown as a colored slice.
Percentage
The proportion expressed as a percent of the total.

Computation Method

  • Quartiles are calculated using linear interpolation (method 7 from Hyndman & Fan, 1996), consistent with Python's NumPy and pandas defaults.
  • Outlier detection uses the Tukey fences method: lower fence = Q1 − 1.5 × IQR, upper fence = Q3 + 1.5 × IQR.
  • Chart scaling caps the display axis at the upper fence value so the visualization remains clear even when extreme outliers are present.

References