Create pie charts from data with percentages, degree angles, SVG visualization, Herfindahl index, Shannon entropy, and cumulative breakdowns.
The Pie Chart Calculator transforms raw data into a fully visualized pie chart with percentages, degree angles, and comprehensive statistical analysis. Enter your category labels and values, and the tool generates an interactive SVG chart, sorted breakdown table, cumulative progression, and concentration metrics.
Beyond basic chart generation, this calculator also computes the Herfindahl-Hirschman Index (HHI) to measure how concentrated your data is across categories, and Shannon entropy to quantify the diversity of your distribution. These metrics are valuable in market analysis, portfolio diversification, and resource allocation studies.
Whether you're creating charts for presentations, analyzing budget allocations, tracking market share, or grading distributions, this tool provides instant visual output alongside the exact numbers you need. The preset examples cover common scenarios like budgets, market share, grades, and time allocation. Check the example with realistic values before reporting. Use the steps shown to verify rounding and units. Cross-check this output using a known reference case. Use the example pattern when troubleshooting unexpected results.
Pie charts are one of the most recognizable data visualizations, instantly communicating part-to-whole relationships. This calculator goes beyond simple chart drawing by providing the exact mathematics behind each slice — percentages, degrees, and cumulative distributions — plus advanced metrics like HHI and entropy that quantify the concentration of your data.
The tool is perfect for students learning about circle graphs, professionals preparing presentations, analysts tracking market share, or anyone who needs to convert raw numbers into visual proportions with mathematical precision.
Percentage = (Value / Total) × 100. Degrees = (Value / Total) × 360. HHI = Σ(share²) where share = percentage/100. Shannon Entropy = -Σ(p × log₂(p)). Effective N = 1/HHI.
Result: Housing 51.1% (183.8°), Food 17.0% (61.2°), Transport 12.8% (45.9°)
With a total of $2,350, Housing dominates at 51.1% (183.8°). The HHI of 0.324 indicates moderate concentration, and Shannon entropy of 2.26 bits suggests reasonable diversity.
A pie chart represents data as slices of a circle, where each slice's angle is proportional to the category's share of the total. The full circle (360°) represents 100% of the data. To convert a raw value to degrees: degrees = (value / total) × 360. To convert to percentage: percentage = (value / total) × 100. The area of each slice is also proportional because all slices share the same radius.
The visual power of pie charts comes from our ability to estimate angles and areas intuitively. However, this same property makes them poor for precise comparisons — research shows humans are better at comparing lengths (bar charts) than areas (pie charts). Use pie charts when the part-to-whole relationship is the key message.
The Herfindahl-Hirschman Index (HHI) is widely used in economics to measure market concentration. For a pie chart with n slices, HHI = Σ(sᵢ²) where sᵢ is each slice's share (as a fraction of 1). A market with one dominant player has HHI near 1, while a perfectly competitive market with many equal players has HHI near 1/n. The Effective Number of Categories (1/HHI) tells you how many equal-sized categories would produce the same concentration.
Start the first slice at 12 o'clock (0°) and proceed clockwise. Place the largest slice first for emphasis. Use distinct colors with sufficient contrast. Label slices directly when possible rather than using a distant legend. Avoid 3D pie charts — they distort the visual proportions and make accurate reading impossible. For data with many small categories, combine them into an "Other" slice.
Use Label:Value pairs separated by commas. For example: Apple:28, Samsung:22, Others:50. You can also enter just numbers without labels, and default labels will be generated.
HHI measures market concentration on a scale from 0 to 1 (or 0 to 10,000 in some formulations). Higher values indicate more concentration. An HHI above 0.25 is considered highly concentrated. Below 0.15 is competitive.
Shannon entropy measures how evenly distributed your data is. Higher entropy means more even distribution. Maximum entropy occurs when all slices are equal. It's measured in bits and is useful for comparing diversity across datasets.
Pie charts are poor for comparing similar-sized slices, showing more than 7-8 categories, displaying time series, or showing negative values. Use bar charts for comparisons and line charts for trends.
Yes, but the visualization works best with 12 or fewer categories. Additional categories will cycle through the color palette. For many categories, consider grouping small ones into "Other".
Arc length = 2πr × (degrees/360) = 2πr × (percentage/100). The calculator computes angles in both degrees and radians for each slice.