mutate() for new columns in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add a new column 'total' as the sum of 'x' and 'y'.

R Programming

library(dplyr)
data <- tibble(x = 1:3, y = 4:6)
data <- data %>% mutate(total = x [1] y)

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

A/

B-

C*

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using subtraction or multiplication instead of addition.

Forgetting to use mutate() to add a new column.

The mutate() function adds a new column. Using + sums the columns x and y.

2fill in blank

medium

Complete the code to create a new column 'ratio' as 'x' divided by 'y'.

R Programming

library(dplyr)
data <- tibble(x = 10:12, y = 2:4)
data <- data %>% mutate(ratio = x [1] y)

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

A/

B+

C*

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiplication or addition instead of division.

Mixing up the order of operands.

The / operator divides x by y to create the 'ratio' column.

3fill in blank

hard

Fix the error in the code to correctly add a new column 'diff' as the difference between 'a' and 'b'.

R Programming

library(dplyr)
data <- tibble(a = 5:7, b = 3:5)
data <- data %>% mutate(diff = a [1] b)

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

A-

B+

C*

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition or multiplication instead of subtraction.

Swapping the order of operands.

The difference is calculated by subtracting b from a using the - operator.

4fill in blank

hard

Fill both blanks to create a new column 'score' as the product of 'm' and 'n' plus 10.

R Programming

library(dplyr)
data <- tibble(m = 2:4, n = 5:7)
data <- data %>% mutate(score = m [1] n [2] 10)

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

A*

B+

C-

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition before multiplication without parentheses.

Using subtraction or division instead of addition.

First multiply m and n with *, then add 10 with +.

5fill in blank

hard

Fill all three blanks to create a new column 'result' as the uppercase of 'name', length of 'name', and check if length is greater than 4.

R Programming

library(dplyr)
data <- tibble(name = c('Anna', 'Brian', 'Clara'))
data <- data %>% mutate(result = list([1], [2], [3]))

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

Atoupper(name)

Bnchar(name)

Cnchar(name) > 4

Dtolower(name)

Attempts:

3 left

💡 Hint

Common Mistakes

Using tolower() instead of toupper().

Forgetting to compare length with a number.

Use toupper(name) for uppercase, nchar(name) for length, and nchar(name) > 4 to check if length is greater than 4.