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To apply color codes to individual variables in a regression plot using ggplot, you can use the color aesthetic and set it equal to the name of the variable that you want to color code by. The following example uses the iris dataset to create a scatterplot of petal length and width, with the regression line color-coded by species:

library(ggplot2)

# Load the iris dataset
data(iris)

# Create a scatterplot of petal length and width, with a regression line
ggplot(iris, aes(x = Petal.Length, y = Petal.Width)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, aes(color = Species))

# Color code the legend
+ scale_color_manual(name = "Species", 
                     values = c("setosa" = "red", "versicolor" = "blue", "virginica" = "green"))

In this example, aes(color = Species) specifies that points and the regression line should be color-coded by species, and scale_color_manual is used to create a legend that maps color codes to species names. The resulting plot will show a different colored regression line for each species, making it easier to visualize how the relationship between petal length and width differs between species.