Bar plots (geom_bar, geom_col) in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a basic bar plot using ggplot2 with geom_bar.

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), count = c(10, 20, 15))
ggplot(data, aes(x = category)) + geom_bar(stat = [1])

Drag options to blanks, or click blank then click option'

A"identity"

B"mean"

C"sum"

D"count"

Attempts:

3 left

💡 Hint

Common Mistakes

Using stat = "identity" when data does not have y values.

geom_bar by default uses stat = "count" to count the number of cases for each category.

2fill in blank

medium

Complete the code to create a bar plot using geom_col with the height of bars from the count column.

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), count = c(10, 20, 15))
ggplot(data, aes(x = category, y = [1])) + geom_col()

Drag options to blanks, or click blank then click option'

Acount

Bcategory

Cx

Dy

Attempts:

3 left

💡 Hint

Common Mistakes

Mapping x to y aesthetic instead of count.

geom_col uses the y aesthetic to set the height of bars, so we map y to the count column.

3fill in blank

hard

Fix the error in the code to correctly plot counts of categories using geom_bar.

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'A', 'C', 'B', 'B'))
ggplot(data, aes(x = [1])) + geom_bar()

Drag options to blanks, or click blank then click option'

Acount

Bcategory

Cvalue

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Using stat = "identity" without y aesthetic.

When using geom_bar with stat = "identity", you must provide y values. Here, we want to count categories, so remove stat = "identity" or map x to category and use default stat.

4fill in blank

hard

Fill both blanks to create a bar plot with bars colored by category and width set to 0.5.

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'B', 'C'), count = c(5, 10, 7))
ggplot(data, aes(x = category, y = count, fill = [1])) + geom_col(width = [2])

Drag options to blanks, or click blank then click option'

Acategory

Bcount

C0.5

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using count for fill aesthetic.

Setting width to 1 when asked for 0.5.

We fill bars by category and set width to 0.5 for narrower bars.

5fill in blank

hard

Fill all three blanks to create a stacked bar plot showing counts by category and subgroup.

R Programming

library(ggplot2)
data <- data.frame(category = c('A', 'A', 'B', 'B'), subgroup = c('X', 'Y', 'X', 'Y'), count = c(3, 2, 5, 4))
ggplot(data, aes(x = [1], y = [2], fill = [3])) + geom_col()

Drag options to blanks, or click blank then click option'

Acategory

Bcount

Csubgroup

Dgroup

Attempts:

3 left

💡 Hint

Common Mistakes

Using group instead of subgroup for fill.

Mapping y to subgroup instead of count.

To create a stacked bar plot, map x to category, y to count, and fill to subgroup.