# How to Calculate Gini Coefficient in R (With Example)

Named after Italian statistician Corrado Gini, the Gini coefficient is a way to measure the income distribution of a population.

The value for the Gini coefficient ranges from 0 to 1 where higher values represent greater income inequality and where:

• 0 represents perfect income equality (everyone has the same income)
• 1 represents perfect income inequality (one individual has all the income)

You can find a list of Gini coefficients by country here.

The following examples show two ways to calculate a Gini coefficient in R by using the Gini() function from the DescTools package.

### Example 1: Calculate Gini Coefficient Using Individual Incomes

Suppose we have the following list of annual incomes for 10 individuals:

Income: \$50k, \$50k, \$70k, \$70k, \$70k, \$90k, \$150k, \$150k, \$150k, \$150k

The following code shows how to use the Gini() function to calculate the Gini coefficient for this population:

```library(DescTools)

#define vector of incomes
x <- c(50, 50, 70, 70, 70, 90, 150, 150, 150, 150)

#calculate Gini coefficient
Gini(x, unbiased=FALSE)

[1] 0.226```

The Gini coefficient turns out to be 0.226.

Note: In a real-world scenario there would be hundreds of thousands of different incomes for individuals in a certain country, but in this example we used 10 individuals as a simple illustration.

### Example 2: Calculate Gini Coefficient Using Frequencies

Suppose we have the following frequency table that shows the number of individuals in a certain population with specific incomes:

The following code shows how to use the Gini() function to calculate the Gini coefficient for this population:

```library(DescTools)

#define vector of incomes
x <- c(10, 20, 25, 55, 70, 90, 110, 115, 130)

#define vector of frequencies
n <- c(6, 7, 7, 14, 22, 20, 8, 4, 1)

#calculate Gini coefficient
Gini(x, n, unbiased=FALSE)

[1] 0.2632289
```

The Gini coefficient turns out to be 0.26232.

Note: You can find the complete documentation for the Gini() function from the DescTools package here.