Faceting for subplots in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of basic facet_wrap usage

What will be the output of this R code using ggplot2's facet_wrap?

R Programming

library(ggplot2)
data <- data.frame(x = 1:6, y = c(2,3,5,7,11,13), group = rep(c('A','B'), each=3))
ggplot(data, aes(x, y)) + geom_point() + facet_wrap(~group)

A Two separate plots side by side, one for group A and one for group B

B A single plot with all points combined, no separation by group

C Two plots stacked vertically, one for group A and one for group B

D Error: facet_wrap requires a numeric variable

💡 Hint

facet_wrap splits data into multiple plots based on a factor variable.

facet_wrap(~group) creates separate plots for each unique value in 'group'. Since 'group' has 'A' and 'B', two plots appear side by side.

❓ Predict Output

intermediate

Effect of facet_grid on plot layout

What is the layout of plots produced by this code?

R Programming

library(ggplot2)
data <- data.frame(x = 1:4, y = c(10,20,30,40), type = c('X','X','Y','Y'), category = c('M','N','M','N'))
ggplot(data, aes(x, y)) + geom_point() + facet_grid(type ~ category)

A A single plot with all points combined

B Error: facet_grid requires numeric variables for rows and columns

C Two plots stacked vertically for 'type', ignoring 'category'

D A 2x2 grid of plots with rows for 'type' and columns for 'category'

💡 Hint

facet_grid uses two variables to create a grid of plots.

facet_grid(type ~ category) creates a grid with rows for each 'type' and columns for each 'category', resulting in 4 plots arranged 2 by 2.

🔧 Debug

advanced

Identify the error in facet_wrap usage

This code produces an error. What is the cause?

R Programming

library(ggplot2)
data <- data.frame(x = 1:5, y = c(5,4,3,2,1), group = c('A','B','C','D','E'))
ggplot(data, aes(x, y)) + geom_point() + facet_wrap(group)

A SyntaxError: facet_wrap requires a formula, e.g., ~group

B Error: group variable must be numeric

C Error: geom_point missing aesthetic mapping

D No error, code runs fine

💡 Hint

Check how facet_wrap expects its argument.

facet_wrap expects a formula like ~group, not just the variable name.

❓ Predict Output

advanced

Number of plots created by facet_grid

How many individual plots will this code create?

R Programming

library(ggplot2)
data <- data.frame(x = 1:8, y = rnorm(8), type = rep(c('A','B'), 4), category = rep(c('X','Y'), each=4))
ggplot(data, aes(x, y)) + geom_point() + facet_grid(type ~ category)

A 2

B 4

C 8

D 1

💡 Hint

Count unique values in 'type' and 'category'.

There are 2 unique 'type' values and 2 unique 'category' values, so 2x2=4 plots are created.

🧠 Conceptual

expert

Understanding free scales in faceting

What is the effect of setting scales = 'free' in facet_wrap or facet_grid?

A Only the x axis scales vary, y axis scales remain fixed

B All subplots share the same x and y axis scales

C Each subplot can have its own x and y axis scales independently

D The plot will show only one subplot ignoring others

💡 Hint

Think about axis scaling flexibility across subplots.

Setting scales = 'free' allows each subplot to adjust its axis scales independently, useful when data ranges differ.

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