Box plots and violin plots in R Programming - Mini Project: Build & Apply

Box plots and violin plots

📖 Scenario: You are a data analyst working with a dataset of students' test scores from different classes. You want to visualize the distribution of scores to understand how students performed in each class.

🎯 Goal: Build box plots and violin plots in R to compare the score distributions across classes.

📋 What You'll Learn

Create a data frame called scores with columns class and score using the exact data provided.

Create a variable called classes that stores the unique class names from the data frame.

Use a boxplot() function to create box plots of score grouped by class.

Use a vioplot::vioplot() function to create violin plots of score grouped by class.

Print the plots so they are visible in the R plotting window.

💡 Why This Matters

🌍 Real World

Box plots and violin plots are common ways to understand how data is spread out and where most values lie. They help compare groups easily.

💼 Career

Data analysts and scientists use these plots to summarize and communicate data insights clearly to teams and stakeholders.

1

Create the data frame with scores

Create a data frame called scores with two columns: class and score. Use these exact values: class contains "A", "A", "B", "B", "C", "C", "C" and score contains 85, 90, 78, 82, 88, 91, 85.

R Programming

# Create the data frame called scores with class and score columns
# Your code here

Need a hint?

Use data.frame() with two vectors named class and score.

2

Extract unique class names

Create a variable called classes that stores the unique class names from the class column of the scores data frame using the unique() function.

R Programming

scores <- data.frame(
  class = c("A", "A", "B", "B", "C", "C", "C"),
  score = c(85, 90, 78, 82, 88, 91, 85)
)
# Create a variable called classes with unique class names
# Your code here

Need a hint?

Use unique() on the class column of scores.

3

Create box plots for scores by class

Use the boxplot() function to create box plots of score grouped by class from the scores data frame. Use the formula score ~ class and set the main title to "Box plot of Scores by Class".

R Programming

scores <- data.frame(
  class = c("A", "A", "B", "B", "C", "C", "C"),
  score = c(85, 90, 78, 82, 88, 91, 85)
)
classes <- unique(scores$class)
# Create a box plot of score by class with a main title
# Your code here

Need a hint?

Use the formula score ~ class inside boxplot() and set main for the title.

4

Create violin plots for scores by class

Load the vioplot package using library(vioplot). Then use the vioplot() function to create violin plots for each class's scores. Use the exact order of classes stored in classes. Set the main title to "Violin plot of Scores by Class" and label the x-axis as "Class" and y-axis as "Score".

R Programming

scores <- data.frame(
  class = c("A", "A", "B", "B", "C", "C", "C"),
  score = c(85, 90, 78, 82, 88, 91, 85)
)
classes <- unique(scores$class)
boxplot(score ~ class, data = scores, main = "Box plot of Scores by Class")
# Load vioplot package and create violin plots for each class in classes
# Your code here

Need a hint?

Use library(vioplot) to load the package. Use vioplot() with scores filtered by class using scores$score[scores$class == classes[i]] for each class.