如何在R语言洛伦兹曲线图右下角添加Gini指数文本？

Hey there! The issue you’re facing with the text() function is likely because the Lorenz curve plot (from plot.Lc()) uses cumulative proportion axes (0 to 1 for both x and y) instead of your raw population/income values. If you tried using raw numbers like x=70093, that’s way outside the plot’s visible range, so the text never shows up.

Here are two reliable ways to add the Gini coefficient to the bottom-right corner of your plot:

Method 1: Use Relative Coordinates (Simplest) #

Since the plot’s axes are scaled to 0-1, you can pick a relative position near the bottom-right (e.g., x=0.9, y=0.1) and align the text properly:

# Load required package and create your data frame
library(ineq)

POPULATION = c(0,7009,14019,21028,28037,35047,42056,49065,56074,63084,70093)
INCOME = c(0,0,0,0,0,195680.26,550667.039999996,1034464.62,1821489.83,3360160.17999999,18979682.83)
DF = data.frame(POPULATION, INCOME)

# Calculate Gini coefficient
G = round(ineq(DF$INCOME, type="Gini"), 3)

# Plot the Lorenz curve
plot(Lc(DF$INCOME), col="darkred", lwd=2, main="Lorenz Curve", 
     xlab="Cumulative Population Proportion", ylab="Cumulative Income Proportion")

# Add Gini text to the bottom-right corner
text(x = 0.9, y = 0.1, labels = paste("Gini =", G), 
     adj = c(1, 0),  # Right-align x, bottom-align y for clean corner placement
     cex = 0.8)      # Adjust text size if needed

Method 2: Use Plot Boundaries (More Robust) #

If you want the text to stay anchored in the corner even if you adjust the plot’s axes, use par("usr") to get the exact boundaries of the plot area:

# After plotting the Lorenz curve:
usr_range = par("usr")  # Returns a vector: c(xmin, xmax, ymin, ymax)

# Place text at 90% of the x-axis width, 10% of the y-axis height from the bottom
text(x = usr_range[2] * 0.9, 
     y = usr_range[3] + (usr_range[4] - usr_range[3]) * 0.1, 
     labels = paste("Gini =", G), 
     adj = c(1, 0), 
     cex = 0.8)

Quick Notes: #

• The adj = c(1,0) parameter ensures the text sits neatly in the corner without overflowing the plot area.
• I updated the axis labels to reflect that they show cumulative proportions (standard for Lorenz curves) instead of raw population/income values, which makes the plot more interpretable.

内容的提问来源于stack exchange，提问作者Bruno Avila