library(ggplot2)program10
Develop an R program to draw a density curve representing the probability density of a continuous variable, with separate curves for each group , using ggplot2.
Step 1: Load required library
Step 2: Define the function
plot_density_by_group <- function(data, continuous_var, group_var, fill_colors = NULL) {
# Check if the specified columns exist
if (!(continuous_var %in% names(data)) || !(group_var %in% names(data))) {
stop("Invalid column names. Make sure both variables exist in the dataset.")
}
# Create the ggplot object
p <- ggplot(data, aes_string(x = continuous_var, color = group_var, fill = group_var)) +
geom_density(alpha = 0.4) +
labs(title = paste("Density Plot of", continuous_var, "by", group_var),
x = continuous_var,
y = "Density") +
theme_minimal()
# Apply custom fill colors if provided
if (!is.null(fill_colors)) {
p <- p + scale_fill_manual(values = fill_colors) +
scale_color_manual(values = fill_colors)
}
# Return the plot
return(p)
}Step 3-Load Dataset
data(iris)
head(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
step 4-Call the Function with Example
# Basic usage
plot_density_by_group(iris, "Sepal.Length", "Species")Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
ℹ Please use tidy evaluation idioms with `aes()`.
ℹ See also `vignette("ggplot2-in-packages")` for more information.
Step 5: Example with Custom Colors
# Define custom colors
custom_colors <- c("setosa" = "steelblue",
"versicolor" = "forestgreen",
"virginica" = "darkorange")
# Plot with custom colors
plot_density_by_group(iris, "Petal.Length", "Species", fill_colors = custom_colors)