Calculate the Gini Index
Use this tool to measure inequality in a set of values (for example: income, wealth, sales, or resource usage). Enter non-negative numbers only.
What is the Gini index?
The Gini index (or Gini coefficient) is a number between 0 and 1 that summarizes how unequal a distribution is. It is widely used in economics for income inequality, but you can apply it to any non-negative dataset.
- 0.00 means perfect equality (everyone has exactly the same value).
- 1.00 means extreme inequality (one observation has everything, others have nothing).
- Most real-world datasets fall somewhere in between.
How this calculator works
The calculator sorts your values from smallest to largest, builds a Lorenz curve, computes the area under that curve, and then converts that area into the Gini index. If you provide weights, each value contributes proportionally to its weight.
How to use the calculator correctly
1) Enter values
Paste values separated by commas, spaces, or line breaks. Examples: income by household, wealth by person, revenue by customer, or electricity usage by building.
2) Add optional weights
If each row represents multiple units, provide weights in the same order and same count as values. If omitted, all values receive equal weight of 1.
3) Click Calculate Gini
You’ll get the Gini index, percentage equivalent, inequality level, and basic summary statistics.
Interpreting your result
There is no universal “good” or “bad” threshold, but these rough guideposts are common:
- 0.00 – 0.24: Very low inequality
- 0.25 – 0.34: Relatively low inequality
- 0.35 – 0.49: Moderate inequality
- 0.50+: High inequality
Always interpret Gini in context: geography, time period, policy environment, and data quality all matter.
Example
Suppose six households earn: 1200, 1400, 1600, 2100, 3500, and 9000. The distribution is clearly skewed by one high value. The Gini index captures that imbalance in a single number.
Click Load Example in the calculator to test this instantly.
Common mistakes to avoid
- Including negative values without adjustment (standard Gini assumes non-negative data).
- Mixing units (e.g., monthly and annual income in one list).
- Using values with currency symbols or commas as thousand separators.
- Providing weights with a different count than the value list.
When to use another inequality metric
Gini is excellent for a quick summary, but sometimes you should also report:
- Palma ratio (top 10% share vs bottom 40% share)
- Theil index (decomposable across groups)
- Atkinson index (explicit inequality aversion parameter)
In professional reports, combining metrics gives a more complete view than any single index.