Program 6

Author

Tejaswini Reddy U

6. Write a R script to construct a box plot showcasing the distribution of a continuous variable , grouped by a categorical variable , using ggplot2’s fill aesthetic.

Step1: Load Required Library

#Load ggplot2 package for visualization
library(ggplot2)

Step2: Explore the Inbuilt Dataset

# Use the built-in 'iris' dataset
# 'Petal.Width' is a continuous variable
# 'Species' is a categorical grouping variable

str(iris)  # View 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 sample 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: Construct Box Plot with Grouping

Step 3.1: Initialize ggplot with Aesthetic Mappings

Explanation:

  • x = Species: Grouping variable (categorical)

  • y = Petal.Width: Continuous variable to show distribution

  • fill = Species: Fill box colors by species

    # Initialize ggplot with data and aesthetic mappings

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

Step 3.2: Add Box Plot Layer

# Add title and labels and use a minimal theme
p <- p + labs(title = "Box Plot of Petal Width by Species",               x = "Species",               y = "Petal Width") +          theme_minimal()

Explanation:

  • labs() adds a descriptive title and axis labels.

  • theme_minimal() gives a clean, modern look.

Step 3.4: Display the Plot

# Render the final plot
p