Program 11

Generate a basic box plot using ggplot2, enhanced with notches and outliers, and grouped by a categorical variable using an in-built dataset in R.

Step 1: Load the required library

# Load the ggplot2 package
library(ggplot2)

Step 2: Load and explore the 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

str(iris)

'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 ...

Step 3: Create a Notched Box Plot Grouped by Species

ggplot(iris, aes(x = Species, y = Sepal.Length)) +
  geom_boxplot(
    notch = TRUE,
    notchwidth = 0.6,
    outlier.color = "red",
    outlier.shape = 16,
    fill = "skyblue",
    alpha = 0.7
  ) +
  labs(
    title = "Sepal Length Distribution by Iris Species",
    subtitle = "Box Plot with Notches and Outlier Highlighting",
    x = "Species",
    y = "Sepal Length (cm)"
  ) +
  theme_minimal()

• Box Plot: Each box summarizes the distribution of Sepal.Length for a species — showing the interquartile range (IQR), median, and potential outliers.

• Notches: The notches give a rough 95% confidence interval around the median. If notches of two boxes do not overlap, the medians are significantly different.

• Outliers: Points that fall outside 1.5 × IQR from the quartiles are considered outliers and shown in red.

• Grouping: The plot groups values based on the categorical variable Species, helping compare between groups.

• Aesthetics: theme_minimal() provides a clean background, while colors and transparency make the plot readable.