As discussed earlier, labeling specific points in a scatter plot is an essential feature in data visualization. In this article, we will explore two methods to achieve this using ggplot2 and base R.

Method 1: Using ggplot2 Package

The ggplot2 package provides a more flexible and customizable way of creating scatter plots with labeled points. The following code demonstrates how to do it:

library(ggplot2)

df <- data.frame(x = c(4, 8, 15, 20, 25),
 y = c(10, 12, 15, 18, 20),
 label = c("A", "B", "C", "D", "E"))

ggplot(aes(x = x, y = y, label = label), data = df) +
 geom_point() +
 geom_label()

In this example, we create a data frame df with three columns: x, y, and label. We then use the ggplot() function to create a scatter plot, specifying the aes() aesthetic mapping for the x and y coordinates, as well as the label. The geom_point() function creates the scatter plot, and the geom_label() function adds the labels.

Method 2: Using Base R

The base R package also provides a way to label specific points in a scatter plot using the text() function within the plot() function:

df <- data.frame(x = c(4, 8, 15, 20, 25),
 y = c(10, 12, 15, 18, 20),
 label = c("A", "B", "C", "D", "E"))

plot(df$x, df$y, pch = 19,
 xlab = "X-axis", ylab = "Y-axis")

text(df$x, df$y, labels = df.label, cex = 0.5)

In this example, we create a data frame df with three columns: x, y, and label. We then use the plot() function to create a scatter plot, specifying the x and y coordinates, as well as the point type (pch = 19). Finally, we use the text() function to add the labels to the points.

Customizing Labels

In both methods, you can customize the appearance of the labels by adjusting parameters such as font size (using cex), color, or position. For example:

• To change the font size of the labels in ggplot2, use the size argument within the geom_label() function.
• To change the font size of the labels in base R, use the cex argument within the text() function.

By using these methods and customizing the appearance of your labels, you can effectively communicate important information about specific points in your scatter plot.