Bar plots (geom_bar, geom_col) in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of geom_bar with default stat

What is the output of this R code using ggplot2?

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'A', 'C', 'B', 'A'))
ggplot(data, aes(x = category)) + geom_bar()

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'A', 'C', 'B', 'A'))
ggplot(data, aes(x = category)) + geom_bar()

A A bar plot with bars showing counts: A=3, B=2, C=1

B A bar plot with bars showing sum of category values

C A scatter plot with points at categories A, B, C

D An error because y aesthetic is missing

💡 Hint

geom_bar by default counts the number of occurrences of each x value.

geom_bar() without specifying y uses stat='count' which counts how many times each x value appears. Here, 'A' appears 3 times, 'B' 2 times, and 'C' once.

❓ Predict Output

intermediate

Difference between geom_bar and geom_col

Given this data and code, what does the plot show?

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), value = c(5, 3, 8))
ggplot(data, aes(x = category, y = value)) + geom_col()

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), value = c(5, 3, 8))
ggplot(data, aes(x = category, y = value)) + geom_col()

A A bar plot with bars heights exactly 5, 3, and 8 for A, B, and C

B A bar plot counting occurrences of each category ignoring value

C A line plot connecting points (A,5), (B,3), (C,8)

D An error because geom_col requires stat='count'

💡 Hint

geom_col uses the y aesthetic as the bar height directly.

geom_col() uses the y values directly for bar heights, unlike geom_bar() which counts occurrences by default.

🔧 Debug

advanced

Error in geom_bar with y aesthetic

What error does this code produce and why?

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), value = c(2, 4, 6))
ggplot(data, aes(x = category, y = value)) + geom_bar()

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), value = c(2, 4, 6))
ggplot(data, aes(x = category, y = value)) + geom_bar()

A Plot shows bars with heights 2, 4, and 6.

B Error: stat_count() must not be used with a y aesthetic.

C Error: object 'value' not found.

D No error; bars show counts ignoring y values.

💡 Hint

geom_bar by default uses stat='count' which does not accept y values.

geom_bar() with default stat='count' cannot use y aesthetic. To use y, you must use geom_col() or specify stat='identity'.

🧠 Conceptual

advanced

When to use geom_col instead of geom_bar

Which situation best describes when geom_col() should be used instead of geom_bar()?

A When you want to count the number of occurrences of each category.

B When you want to create a scatter plot with bars.

C When you want to plot pre-summarized values as bar heights.

D When you want to plot a line graph connecting categories.

💡 Hint

Think about whether your data already has the values to plot or if you want to count.

geom_col() uses the y values directly as bar heights, so it is used when data already contains summarized values. geom_bar() counts occurrences by default.

❓ Predict Output

expert

Bar plot with grouped data and position dodge

What does this code produce?

library(ggplot2)
data <- data.frame(
  group = rep(c('G1', 'G2'), each = 3),
  category = rep(c('A', 'B', 'C'), 2),
  value = c(2, 5, 3, 4, 1, 6)
)
ggplot(data, aes(x = category, y = value, fill = group)) + geom_col(position = 'dodge')

R Programming

library(ggplot2)
data <- data.frame(
  group = rep(c('G1', 'G2'), each = 3),
  category = rep(c('A', 'B', 'C'), 2),
  value = c(2, 5, 3, 4, 1, 6)
)
ggplot(data, aes(x = category, y = value, fill = group)) + geom_col(position = 'dodge')

A A line plot connecting values for each group across categories

B A stacked bar plot with bars for G1 and G2 stacked in each category

C An error because position='dodge' is invalid

D A grouped bar plot with side-by-side bars for G1 and G2 in each category with heights from value

💡 Hint

position='dodge' places bars side by side instead of stacking.

geom_col() with position='dodge' creates grouped bars side by side for each fill group within each x category.