separate and unite in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the separate() function do in R's tidyr package?

It splits one column into multiple columns based on a separator, like splitting a full name into first and last names.

beginner

What is the purpose of the unite() function in R?

It combines multiple columns into one column by joining their values with a separator, like merging first and last names into a full name.

intermediate

Which argument in separate() controls the character used to split the column?

The sep argument specifies the separator character or regular expression to split the column.

intermediate

How do you prevent separate() from dropping the original column after splitting?

Use the argument remove = FALSE to keep the original column in the data frame.

intermediate

What happens if you use unite() with remove = FALSE?

The original columns are kept along with the new united column, so no data is lost.

What does separate() do in R's tidyr package?

A Filters rows based on a condition

B Combines multiple columns into one

C Splits one column into multiple columns

D Sorts data frame rows

separate() splits a single column into multiple columns based on a separator.

Which argument in unite() sets the character between combined values?

A into

B remove

C fill

D sep

The sep argument defines the separator between combined values in unite().

If you want to keep the original columns after using unite(), which argument should you use?

A remove = FALSE

B keep = TRUE

C preserve = TRUE

D retain = FALSE

Setting remove = FALSE keeps the original columns after uniting.

What type of value does the sep argument accept in separate()?

A Logical TRUE or FALSE

B Character string or regular expression

C Data frame

D Numeric index

sep accepts a character string or regular expression to split the column.

Which package provides the separate() and unite() functions?

A tidyr

B ggplot2

C dplyr

D stringr

separate() and unite() are part of the tidyr package.

Explain how you would split a column of full names into first and last names using R.

Think about the separator between first and last names.

Describe how to combine two columns, like city and state, into one column in R.

Consider how to join values with a character.

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