program 5

Implement an R program to create a histogram illustrating the distribution of a continuous variable, with overlays of density curves for each group, using ggplot2

Step 1:Load Required Library

library(ggplot2)

Warning: package 'ggplot2' was built under R version 4.4.3

Step 2:Explore the Inbuilt Dataset

#use the built-in 'iris' dataset
#"Petal.length' is a continuous variable 
#'Species' is a categorical grouping variable

str(iris) #shows the structure of the dataset

'data.frame':   150 obs. of  5 variables:
 $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
 $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
 $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
 $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
 $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

head(iris) #view the first few rows of the data

  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 3: Create Histogram with Group-wise Density Curves

Step 3.1: Initialize the ggplot with aesthetic mappings

#start ggplot with iris dataset
#map Petal.length to x-axis and fill by species (grouping variable)

p <- ggplot(data = iris, aes(x = Petal.Length, fill = Species))
p

Step 3.2: Add Histogram layer

#Add histogram with density scaling

p <- p + geom_histogram(aes(y = ..density..),
                        alpha = 0.4, #Set transparency
                        position = "identity", #Overlap histograms
                        bins = 30) #Number of bins
p

Warning: The dot-dot notation (`..density..`) was deprecated in ggplot2 3.4.0.
ℹ Please use `after_stat(density)` instead.

Step 3.3:Add density curve layer

#Overlap density curves for each group

p <- p +
  geom_density(aes(color = Species), #LIne color by group
  size = 1.2) #Line thickness

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

p

Step 3.4:

p <- p + labs(
  title = "Distribution of Petal Length with group-wise Density Curves",
  x = "Petal Length",
  y = "Density") +
  theme_minimal()
p