create_lorenz: Calculate the Lorenz Curve and Gini Coefficient in a Person...

In vivainsights: Analyze and Visualize Data from 'Microsoft Viva Insights'

Calculate the Lorenz Curve and Gini Coefficient in a Person Query

Description

This function computes the Gini coefficient and plots the Lorenz curve based on a selected metric from a Person Query data frame. It provides a way to measure inequality in the distribution of the selected metric.This function can be integrated into a larger analysis pipeline to assess inequality in metric distribution.

Usage

create_lorenz(data, metric, return = "plot")

Arguments

data	Data frame containing a Person Query.
metric	Character string identifying the metric to be used for the Lorenz curve and Gini coefficient calculation.
return	Character string identifying the return type. Options are: "gini" - Numeric value representing the Gini coefficient. "table" - Data frame containing a summary table of population share and value share. "plot" (default) - ggplot object representing a plot of the Lorenz curve.

Gini coefficient

The Gini coefficient is a measure of statistical dispersion most commonly used to represent income inequality within a population. It is calculated as the ratio of the area between the Lorenz curve and the line of perfect equality (the 45-degree line) to the total area under the line of perfect equality. It has a range of 0 to 1, where 0 represents perfect equality and 1 represents perfect inequality. It can be applied to any Viva Insights metric where inequality is of interest.

Examples

create_lorenz(data = pq_data, metric = "Emails_sent", return = "gini")

create_lorenz(data = pq_data, metric = "Emails_sent", return = "plot")

create_lorenz(data = pq_data, metric = "Emails_sent", return = "table")

vivainsights documentation built on April 3, 2025, 9:25 p.m.