pivot_wider (long to wide) in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this pivot_wider code?

Given the following R code using pivot_wider, what will be the resulting data frame?

R Programming

library(tidyr)
library(dplyr)

long_df <- data.frame(
  id = c(1, 1, 2, 2),
  key = c("A", "B", "A", "B"),
  value = c(10, 20, 30, 40)
)

wide_df <- pivot_wider(long_df, names_from = key, values_from = value)
print(wide_df)

A An error because pivot_wider needs a grouping variable

B A tibble with columns: id, key, value; rows doubled

C A tibble with columns: id, A, B; rows: (1,10,20), (2,30,40)

D A tibble with columns: key, value; rows unchanged

💡 Hint

Think about how pivot_wider spreads key-value pairs into columns.

pivot_wider takes the unique values in 'key' and makes them column names, filling with corresponding 'value' entries for each 'id'.

❓ Predict Output

intermediate

What does this pivot_wider code produce?

Consider this R code snippet using pivot_wider. What is the output?

R Programming

library(tidyr)
long_df <- data.frame(
  person = c("Alice", "Alice", "Bob", "Bob"),
  measurement = c("height", "weight", "height", "weight"),
  value = c(165, 60, 180, 75)
)
wide_df <- pivot_wider(long_df, names_from = measurement, values_from = value)
print(wide_df)

A An error because 'value' column is numeric

B A tibble with columns: measurement, value; rows unchanged

C A tibble with columns: person, measurement, value; rows doubled

D A tibble with columns: person, height, weight; rows: (Alice,165,60), (Bob,180,75)

💡 Hint

pivot_wider reshapes long data by spreading measurement names into columns.

pivot_wider uses 'measurement' values as new column names and fills them with 'value' for each 'person'.

🔧 Debug

advanced

What error does this pivot_wider code raise?

What error will this R code produce when run?

R Programming

library(tidyr)
long_df <- data.frame(
  id = c(1, 1, 2),
  key = c("X", "X", "X"),
  value = c(5, 10, 15)
)

pivot_wider(long_df, names_from = key, values_from = value)

A Error: Values in 'value' are not uniquely identified; multiple rows per id-key pair

B No error; returns a wide data frame with columns id, X, Y

C Error: 'names_from' column 'key' not found

D Error: 'values_from' column 'value' is missing

💡 Hint

Check if each id-key pair has only one value.

pivot_wider requires unique combinations of id and key to fill values; duplicates cause an error.

❓ Predict Output

advanced

What is the output of pivot_wider with multiple value columns?

What will this R code output when run?

R Programming

library(tidyr)
long_df <- data.frame(
  id = c(1, 1, 2, 2),
  key = c("A", "B", "A", "B"),
  val1 = c(10, 20, 30, 40),
  val2 = c(100, 200, 300, 400)
)
wide_df <- pivot_wider(long_df, names_from = key, values_from = c(val1, val2))
print(wide_df)

A A tibble with columns: id, val1_A, val1_B, val2_A, val2_B; rows: (1,10,20,100,200), (2,30,40,300,400)

B A tibble with columns: id, A, B; rows with nested lists of val1 and val2

C Error: values_from must be a single column name

D A tibble with columns: id, key, val1, val2; rows unchanged

💡 Hint

pivot_wider can handle multiple value columns by creating multiple new columns per key.

pivot_wider creates new columns for each combination of value column and key, naming them like val1_A, val1_B, etc.

🧠 Conceptual

expert

How many rows are in the output after pivot_wider?

Given this long data frame with 6 rows and 3 unique ids, what will be the number of rows after applying pivot_wider with names_from = variable and values_from = value?

R Programming

library(tidyr)
long_df <- data.frame(
  id = c(1,1,2,2,3,3),
  variable = c("X", "Y", "X", "Y", "X", "Y"),
  value = c(5, 10, 15, 20, 25, 30)
)
wide_df <- pivot_wider(long_df, names_from = variable, values_from = value)

A 6

B 3

C 2

D 1

💡 Hint

pivot_wider groups by the columns not used in names_from or values_from.

Since there are 3 unique ids, pivot_wider will produce 3 rows, one per id.