Program 5

Author

Tejaswini Reddy U

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)

step 2: Explore the Inbuilt dataset

str(iris) # shows structure of 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)
  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 : Intialize 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

p<- ggplot(data=iris, aes(x= Petal.Length, fill = Species))
p<- p+geom_histogram(aes(y=..density..),
                     alpha=0.4,
                     position = "identity",
                     bins=30)

Step 3.3: Add Density Curve Layer

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

Step 3.4: Add Labels and Theme

# Add title and axis labels, and apply clean theme

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

p

Step 3.5: Display the Plot

p