separate and unite in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of separate() with multiple separators

What is the output of this R code using separate() from tidyr?

R Programming

library(tidyr)
library(dplyr)
df <- tibble(id = 1:2, info = c("a-1_x", "b-2_y"))
df %>% separate(info, into = c("letter", "number", "extra"), sep = "[-_]")

A A tibble with columns: id, letter (a-1, b-2), number (x,y), extra (NA, NA)

B Error: unused argument sep

C A tibble with columns: id, letter (a, b), number (1_x, 2_y), extra (NA, NA)

D A tibble with columns: id, letter (a,b), number (1,2), extra (x,y)

💡 Hint

The separator can be a regular expression matching multiple characters.

The sep = "[-_]" means split at either '-' or '_'. So the string "a-1_x" splits into "a", "1", and "x".

❓ Predict Output

intermediate

Output of unite() with remove = FALSE

What is the output of this R code using unite() from tidyr?

R Programming

library(tidyr)
df <- tibble(x = c("a", "b"), y = c(1, 2))
df %>% unite("xy", x, y, sep = ":", remove = FALSE)

A A tibble with columns: x, y, xy (a:1, b:2)

B A tibble with columns: x, y, xy (a1, b2)

C A tibble with columns: xy (a:1, b:2) only

D Error: unused argument remove

💡 Hint

The argument remove = FALSE keeps the original columns.

The unite() function combines columns x and y into a new column xy separated by ':'. Because remove = FALSE, the original columns x and y remain.

🔧 Debug

advanced

Why does this separate() call fail?

Consider this code snippet:

library(tidyr)
df <- tibble(code = c("A-1", "B-2"))
df %>% separate(code, into = c("letter", "number"), sep = "-")

Why might this code fail if the input data changes to include "C1" (without a dash)?

R Programming

library(tidyr)
df <- tibble(code = c("A-1", "B-2", "C1"))
df %>% separate(code, into = c("letter", "number"), sep = "-")

A It raises an error because 'C1' does not contain the separator '-' and cannot be split into two parts.

B It works fine and splits 'C1' into 'C' and '1' automatically.

C It returns NA for both letter and number for 'C1' without error.

D It splits 'C1' into 'C1' and NA without error.

💡 Hint

The separate() function expects the separator to be present to split into all requested columns.

If the separator is missing in a string, separate() cannot split it into the requested number of columns and throws an error.

❓ Predict Output

advanced

Result of separate() with extra = 'merge'

What is the output of this R code?

R Programming

library(tidyr)
df <- tibble(id = 1, val = "a-b-c")
df %>% separate(val, into = c("one", "two"), sep = "-", extra = "merge")

A A tibble with one row: one = 'a', two = 'b'

B A tibble with one row: one = 'a', two = 'b-c'

C A tibble with one row: one = 'a-b', two = 'c'

D Error: unused argument extra

💡 Hint

The extra = 'merge' option merges leftover pieces into the last column.

Since there are more pieces than columns, extra = 'merge' joins the extra pieces into the last column.

🧠 Conceptual

expert

Understanding unite() with NA values

Given this R code, what is the value of the 'combined' column after running unite()?

R Programming

library(tidyr)
df <- tibble(a = c("x", NA), b = c("y", "z"))
df %>% unite("combined", a, b, sep = "-")

A combined = c("x-y", "-z")

B combined = c("x-y", NA)

C combined = c("x-y", "NA-z")

D combined = c("x-y", "z")

💡 Hint

unite() uses paste(collapse = sep) internally, which converts NA to the string "NA".

The unite() function combines columns using paste(collapse = "-"), which converts NA to the string "NA", resulting in "x-y" and "NA-z".