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".

Practice

1. What does the separate function do in R's tidyr package?

easy

A. It removes missing values from a dataset.

B. It combines multiple columns into one column.

C. It splits one column into multiple columns based on a separator.

D. It sorts the rows of a data frame.

Solution

1. Step 1: Understand the purpose of separate

   The separate function is designed to split a single column into multiple columns by using a separator like a comma or space.

2. Step 2: Compare with other options

   unite does the opposite by joining columns, and other options do unrelated tasks.

3. Final Answer:

   It splits one column into multiple columns based on a separator. -> Option C

4. Quick Check:

   separate splits columns [OK]

Hint: Remember: separate = split one column into many [OK]

Common Mistakes:

• Confusing separate with unite
• Thinking separate removes rows
• Assuming separate combines columns

2. Which of the following is the correct syntax to unite columns first and last into a new column full_name using tidyr?

easy

A. unite(data, full_name, first & last, sep = " ")

B. unite(data, first, last, full_name, sep = " ")

C. unite(data, full_name, first + last, sep = " ")

D. unite(data, full_name, first, last, sep = " ")

Solution

1. Step 1: Recall unite function syntax

   The correct syntax is unite(data, new_column, col1, col2, sep = "separator").

2. Step 2: Match options with syntax

   unite(data, full_name, first, last, sep = " ") matches the syntax exactly, specifying the data, new column name, columns to unite, and separator.

3. Final Answer:

   unite(data, full_name, first, last, sep = " ") -> Option D

4. Quick Check:

   unite syntax = unite(data, new_col, cols...) [OK]

Hint: unite(data, new_col, col1, col2, sep) is correct [OK]

Common Mistakes:

• Mixing order of arguments
• Using + instead of commas
• Passing columns as a vector incorrectly

3. Given the data frame df with a column date containing values like "2024-06-15", what will be the result of separate(df, date, into = c("year", "month", "day"), sep = "-")?

medium

A. A data frame with columns year, month, day split from the date string.

B. An error because sep must be a space.

C. The original data frame unchanged.

D. A single column with dates joined by dashes.

Solution

1. Step 1: Understand separate with sep = "-"

   The function splits the date column at each dash, creating three new columns named year, month, and day.

2. Step 2: Confirm output structure

   The output will be a data frame with these three new columns containing parts of the original date string.

3. Final Answer:

   A data frame with columns year, month, day split from the date string. -> Option A

4. Quick Check:

   separate splits by given separator [OK]

Hint: sep argument splits string at given character [OK]

Common Mistakes:

• Assuming sep must be space
• Expecting a single combined column
• Not naming the new columns correctly

4. What is wrong with this code snippet?

unite(full_name, first, last)

It produces an error.

medium

A. The data frame df is not specified.

B. Missing the separator argument sep.

C. The columns first and last must be in a vector.

D. The new column name full_name must be quoted.

Solution

1. Step 1: Check unite function syntax

   The unite function requires the data frame as the first argument.

2. Step 2: Identify the issue

   In the code, full_name is the first argument, which is the new column name, not a data frame. The data frame (e.g., df) is missing.

3. Final Answer:

   The data frame df is not specified. -> Option A

4. Quick Check:

   unite(dataframe, new_col, cols...) [OK]

Hint: Data frame must be first argument in unite [OK]

Common Mistakes:

• Forgetting to pass data frame first
• Not quoting new column name
• Passing columns as vector incorrectly

5. You have a data frame df with columns location containing "city,state" strings. How do you split location into two columns city and state, then combine them back into location separated by a comma and space?

hard

A. Use unite(df, location, city, state, sep = ",") then separate(df, location, into = c("city", "state"), sep = ", ").

B. Use separate(df, location, into = c("city", "state"), sep = ",") then unite(df, location, city, state, sep = ", ").

C. Use separate(df, location, into = c("city", "state"), sep = ", ") then unite(df, location, city, state, sep = ",").

D. Use separate(df, location, into = c("city", "state"), sep = ",") then unite(df, location, city, state, sep = ",").

Solution

1. Step 1: Separate location by comma

   Use separate with sep = "," to split "city,state" into two columns.

2. Step 2: Unite city and state with comma and space

   Use unite with sep = ", " to join city and state back with a comma and space.

3. Final Answer:

   Use separate with sep="," then unite with sep=", " -> Option B

4. Quick Check:

   Separate splits, unite joins with correct separators [OK]

Hint: Match separators exactly when separating and uniting [OK]

Common Mistakes:

• Mixing separator strings between separate and unite
• Using wrong order of functions
• Not matching spaces in separators