summarise() with group_by() in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of summarise() with group_by() on mtcars

What is the output of this R code snippet?

R Programming

library(dplyr)
result <- mtcars %>% group_by(cyl) %>% summarise(avg_mpg = mean(mpg))
print(result)

A

A tibble: 3 × 2
    cyl avg_mpg
  <dbl>   <dbl>
1     4    26.7
2     6    19.7
3     8    15.1

B

A tibble: 32 × 2
    cyl avg_mpg
  <dbl>   <dbl>
1     6    20.1
2     4    22.8
3     8    15.0
... (repeated for each row)

C

A tibble: 3 × 1
    avg_mpg
    <dbl>
1    20.1
2    22.8
3    15.0

D Error in summarise(): object 'mpg' not found

💡 Hint

Think about how group_by() splits data and summarise() calculates one value per group.

The code groups the mtcars dataset by the number of cylinders (cyl) and calculates the average miles per gallon (mpg) for each group. The result is a tibble with 3 rows, one for each unique cyl value, and two columns: cyl and avg_mpg.

❓ Predict Output

intermediate

Result of summarise() without group_by()

What will this R code output?

R Programming

library(dplyr)
result <- mtcars %>% summarise(avg_hp = mean(hp))
print(result)

A

A tibble: 32 × 1
  avg_hp
   <dbl>
1   110
2   110
... (repeated for each row)

B

A tibble: 1 × 1
  avg_hp
   <dbl>
1   146.7

C Error: summarise() requires grouping variables

D

A tibble: 1 × 2
  cyl avg_hp
  <dbl>  <dbl>
1    NA   146.7

💡 Hint

summarise() without group_by() returns one summary row for the whole dataset.

Without grouping, summarise() calculates the mean horsepower (hp) for all rows combined, returning a single-row tibble with one column avg_hp.

🧠 Conceptual

advanced

Understanding summarise() with multiple summaries

What does this code produce?

R Programming

library(dplyr)
result <- mtcars %>% group_by(cyl) %>% summarise(avg_mpg = mean(mpg), max_hp = max(hp))
print(result)

A A tibble with 32 rows, each showing avg_mpg and max_hp repeated for each car

B A tibble with 3 rows and 2 columns: avg_mpg and max_hp only, no cyl column

C Error: summarise() can only return one summary column

D A tibble with 3 rows and 3 columns: cyl, avg_mpg, max_hp showing average mpg and max hp per cylinder group

💡 Hint

summarise() can create multiple summary columns at once.

The code groups mtcars by cyl and calculates two summaries per group: average mpg and maximum hp. The output includes the grouping column cyl plus the two summaries.

🔧 Debug

advanced

Identify the error in summarise() with group_by()

What error does this code produce?

R Programming

library(dplyr)
result <- mtcars %>% group_by(cyl) %>% summarise(avg_mpg = mean(miles_per_gallon))
print(result)

A Error: object 'miles_per_gallon' not found

B Error: group_by() requires a grouping variable

C No error, outputs average mpg per cyl

D Error: summarise() cannot be used after group_by()

💡 Hint

Check if the column name used in mean() exists in mtcars.

The mtcars dataset does not have a column named 'miles_per_gallon'. Using a non-existent column in summarise() causes an error.

🚀 Application

expert

Count unique gear values per cylinder group

Which code correctly counts the number of unique gear values for each cylinder group in mtcars?

A mtcars %>% summarise(unique_gears = n_distinct(gear)) %>% group_by(cyl)

B mtcars %>% group_by(cyl) %>% summarise(unique_gears = length(unique(gear)))

C mtcars %>% group_by(cyl) %>% summarise(unique_gears = n_distinct(gear))

D mtcars %>% group_by(gear) %>% summarise(unique_cyl = n_distinct(cyl))

💡 Hint

Use group_by() first, then summarise() with n_distinct() to count unique values per group.

Option C groups by cyl and then counts distinct gear values per group correctly. Option C is close but length(unique()) inside summarise() works but n_distinct() is preferred and more efficient. Option C groups after summarise, which is incorrect. Option C groups by gear, not cyl.