Why dplyr simplifies data wrangling in R Programming - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the column 'mpg' from the mtcars dataset.

R Programming

library(dplyr)
result <- mtcars %>% select([1])
print(result)

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

Ampg

Bcyl

Cgear

Dhp

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a column name that does not exist in the dataset.

The select() function chooses columns by name. Here, 'mpg' is the correct column to select.

2fill in blank

medium

Complete the code to filter rows where 'cyl' equals 6.

R Programming

library(dplyr)
result <- mtcars %>% filter([1] == 6)
print(result)

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

Ampg

Bcyl

Cgear

Dhp

Attempts:

3 left

💡 Hint

Common Mistakes

Filtering on a wrong column like 'mpg' or 'gear'.

The filter() function keeps rows where the condition is true. Here, we want rows with 6 cylinders, so we use 'cyl'.

3fill in blank

hard

Fix the error in the code to arrange the dataset by 'hp' in descending order.

R Programming

library(dplyr)
result <- mtcars %>% arrange([1](hp))
print(result)

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Aasc

Border

Cdesc

Dsort

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'asc' for descending order or using base R functions like 'order' or 'sort' inside arrange.

The arrange() function orders rows. To sort descending, use desc() around the column name.

4fill in blank

hard

Fill both blanks to create a new column 'power_to_weight' as hp divided by wt.

R Programming

library(dplyr)
result <- mtcars %>% mutate(power_to_weight = [1] / [2])
print(result$power_to_weight)

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

Ahp

Bmpg

Cwt

Dcyl

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong columns like 'mpg' or 'cyl' in the calculation.

The mutate() function adds new columns. Here, 'power_to_weight' is horsepower divided by weight ('wt').

5fill in blank

hard

Fill both blanks to create a summary with average mpg for cars with more than 4 gears.

R Programming

library(dplyr)
summary <- mtcars %>% filter([1] > 4) %>% summarise(avg_mpg = mean([2]))
print(summary)

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

Agear

Bmpg

Ccyl

Dhp

Attempts:

3 left

💡 Hint

Common Mistakes

Filtering on wrong columns or calculating mean of wrong columns.

First, filter cars with more than 4 gears using 'gear'. Then calculate the average mpg with mean(mpg).