Faceting for subplots in R Programming - Mini Project: Build & Apply

Faceting for Subplots in R with ggplot2

📖 Scenario: You are a data analyst working with a dataset of car models and their fuel efficiency. You want to create separate plots for each car manufacturer to compare their fuel efficiency visually.

🎯 Goal: Build a faceted plot using ggplot2 in R that shows fuel efficiency for different car models, separated by manufacturer in subplots.

📋 What You'll Learn

Create a data frame called cars with columns manufacturer, model, and mpg with exact values

Create a ggplot object called p with model on x-axis and mpg on y-axis

Add points to the plot using geom_point()

Use facet_wrap() to create subplots by manufacturer

Print the plot object p

💡 Why This Matters

🌍 Real World

Faceting helps compare groups side-by-side in separate plots, useful in data analysis and reporting.

💼 Career

Data analysts and scientists use faceting to explore and present data clearly across categories.

1

Create the data frame

Create a data frame called cars with these exact columns and values:
manufacturer: 'Ford', 'Ford', 'Toyota', 'Toyota', 'Honda', 'Honda'
model: 'F-150', 'Mustang', 'Corolla', 'Camry', 'Civic', 'Accord'
mpg: 20, 25, 30, 28, 32, 31

R Programming

# Create the data frame cars with manufacturer, model, and mpg columns
# Your code here

Hint

Use data.frame() with vectors for each column named exactly manufacturer, model, and mpg.

2

Load ggplot2 library

Load the ggplot2 library by writing library(ggplot2)

R Programming

cars <- data.frame(
  manufacturer = c('Ford', 'Ford', 'Toyota', 'Toyota', 'Honda', 'Honda'),
  model = c('F-150', 'Mustang', 'Corolla', 'Camry', 'Civic', 'Accord'),
  mpg = c(20, 25, 30, 28, 32, 31)
)
# Load the ggplot2 library
# Your code here

Hint

Type library(ggplot2) to load the plotting package.

3

Create the faceted plot

Create a ggplot object called p using cars data, mapping model to x-axis and mpg to y-axis, add points with geom_point(), and use facet_wrap(~manufacturer) to create subplots by manufacturer

R Programming

cars <- data.frame(
  manufacturer = c('Ford', 'Ford', 'Toyota', 'Toyota', 'Honda', 'Honda'),
  model = c('F-150', 'Mustang', 'Corolla', 'Camry', 'Civic', 'Accord'),
  mpg = c(20, 25, 30, 28, 32, 31)
)
library(ggplot2)

# Create the ggplot object p with points and facet_wrap by manufacturer
# Your code here

Hint

Use ggplot() with aes(x = model, y = mpg), add geom_point(), then add facet_wrap(~manufacturer).

4

Display the faceted plot

Print the plot object p using print(p)

R Programming

cars <- data.frame(
  manufacturer = c('Ford', 'Ford', 'Toyota', 'Toyota', 'Honda', 'Honda'),
  model = c('F-150', 'Mustang', 'Corolla', 'Camry', 'Civic', 'Accord'),
  mpg = c(20, 25, 30, 28, 32, 31)
)
library(ggplot2)

p <- ggplot(cars, aes(x = model, y = mpg)) +
  geom_point() +
  facet_wrap(~manufacturer)

# Print the plot p
# Your code here

Hint

Use print(p) to display the plot.

Practice

1. What is the main purpose of faceting in R plotting with ggplot2?

easy

A. To save the plot as an image file

B. To change the color of points in a plot

C. To add titles to the plot

D. To split one plot into multiple smaller plots based on categories

Solution

1. Step 1: Understand faceting concept

   Faceting divides a single plot into multiple smaller plots based on categories in the data.

2. Step 2: Identify purpose in ggplot2

   In ggplot2, faceting helps compare groups by creating subplots for each category.

3. Final Answer:

   To split one plot into multiple smaller plots based on categories -> Option D

4. Quick Check:

   Faceting = split plot by category [OK]

Hint: Faceting means splitting plots by groups [OK]

Common Mistakes:

• Confusing faceting with coloring points
• Thinking faceting adds titles
• Believing faceting saves files

2. Which of the following is the correct syntax to create subplots by one variable using facet_wrap in ggplot2?

easy

A. ggplot(data) + geom_point() + facet_wrap(~ variable)

B. ggplot(data) + geom_point() + facet_grid(variable)

C. ggplot(data) + geom_point() + facet_wrap(variable)

D. ggplot(data) + geom_point() + facet_grid(~ variable)

Solution

1. Step 1: Recall syntax for facet_wrap

   facet_wrap requires a formula with tilde (~) and the variable name, like ~ variable.

2. Step 2: Check options

   ggplot(data) + geom_point() + facet_wrap(~ variable) uses facet_wrap(~ variable), which is correct syntax for faceting by one variable.

3. Final Answer:

   ggplot(data) + geom_point() + facet_wrap(~ variable) -> Option A

4. Quick Check:

   facet_wrap syntax = ~ variable [OK]

Hint: Use ~ before variable in facet_wrap() [OK]

Common Mistakes:

• Omitting the tilde (~) before variable
• Using facet_grid without formula
• Confusing facet_wrap and facet_grid syntax

3. What will be the result of this code?

library(ggplot2)
data <- data.frame(x=1:6, y=6:1, group=c('A','A','B','B','C','C'))
ggplot(data, aes(x, y)) + geom_point() + facet_wrap(~ group)

medium

A. A single plot with all points colored by group

B. Three separate plots, one for each group A, B, and C

C. An error because facet_wrap needs two variables

D. A plot with points connected by lines

Solution

1. Step 1: Understand data and faceting

   Data has groups A, B, and C. facet_wrap(~ group) creates one subplot per group.

2. Step 2: Predict output

   The code will produce three separate plots, each showing points for groups A, B, and C respectively.

3. Final Answer:

   Three separate plots, one for each group A, B, and C -> Option B

4. Quick Check:

   facet_wrap splits plot by group [OK]

Hint: facet_wrap(~ group) makes one plot per group [OK]

Common Mistakes:

• Expecting one combined plot with colors
• Thinking facet_wrap requires two variables
• Assuming points connect with lines

4. Identify the error in this code snippet:

ggplot(data, aes(x, y)) + geom_point() + facet_grid(group)

medium

A. facet_grid requires a formula with ~, like facet_grid(~ group)

B. geom_point() should come after facet_grid()

C. aes() must include color=group for faceting

D. facet_grid cannot be used with geom_point()

Solution

1. Step 1: Check facet_grid syntax

   facet_grid requires a formula input with tilde (~), e.g., facet_grid(~ group).

2. Step 2: Identify error in code

   The code uses facet_grid(group) without ~, causing a syntax error.

3. Final Answer:

   facet_grid requires a formula with ~, like facet_grid(~ group) -> Option A

4. Quick Check:

   facet_grid needs ~ before variable [OK]

Hint: Always use ~ in facet_grid() formula [OK]

Common Mistakes:

• Omitting ~ in facet_grid()
• Changing order of geom_point and facet_grid
• Adding unnecessary color aesthetic for faceting

5. You want to create a grid of plots faceted by two variables: gender (rows) and age_group (columns). Which code correctly does this in ggplot2?

hard

A. ggplot(data) + geom_point() + facet_wrap(~ gender + age_group)

B. ggplot(data) + geom_point() + facet_grid(~ gender + age_group)

C. ggplot(data) + geom_point() + facet_grid(gender ~ age_group)

D. ggplot(data) + geom_point() + facet_wrap(gender ~ age_group)

Solution

1. Step 1: Understand faceting by two variables

   facet_grid(rows ~ columns) creates a grid with rows and columns faceted by variables.

2. Step 2: Match variables to rows and columns

   gender should be rows, age_group columns, so syntax is facet_grid(gender ~ age_group).

3. Final Answer:

   ggplot(data) + geom_point() + facet_grid(gender ~ age_group) -> Option C

4. Quick Check:

   facet_grid(rows ~ columns) = gender ~ age_group [OK]

Hint: Use facet_grid(row ~ column) for two variables [OK]

Common Mistakes:

• Using facet_wrap for two variables as grid
• Swapping rows and columns in formula
• Omitting ~ or using wrong formula syntax