separate and unite in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to separate the 'date' column into 'year', 'month', and 'day'.

R Programming

library(tidyr)
data <- data.frame(date = c('2023-06-01', '2023-06-02'))
separated <- separate(data, col = [1], into = c('year', 'month', 'day'), sep = '-')

Drag options to blanks, or click blank then click option'

Aday

Byear

Cmonth

Ddate

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name like 'year' instead of 'date'.

Forgetting to specify the column to separate.

The 'separate' function needs the name of the column to split, which is 'date' here.

2fill in blank

medium

Complete the code to unite the 'year', 'month', and 'day' columns into a single 'date' column separated by '-'.

R Programming

library(tidyr)
data <- data.frame(year = c('2023', '2023'), month = c('06', '06'), day = c('01', '02'))
united <- unite(data, col = [1], year, month, day, sep = '-')

Drag options to blanks, or click blank then click option'

Ayear

Bday

Cdate

Dmonth

Attempts:

3 left

💡 Hint

Common Mistakes

Using an existing column name like 'year' as the new column name.

Not specifying the new column name correctly.

The 'unite' function needs the name of the new column to create, which is 'date' here.

3fill in blank

hard

Fix the error in the code to separate the 'datetime' column into 'date' and 'time'.

R Programming

library(tidyr)
data <- data.frame(datetime = c('2023-06-01 12:00', '2023-06-02 13:30'))
separated <- separate(data, col = [1], into = c('date', 'time'), sep = ' ')

Drag options to blanks, or click blank then click option'

Adatetime

Bdate

Ctime

Ddatetime_col

Attempts:

3 left

💡 Hint

Common Mistakes

Using a column name that does not exist in the data frame.

Misspelling the column name.

The 'separate' function requires the exact column name to split, which is 'datetime'.

4fill in blank

hard

Fill both blanks to separate the 'full_name' column into 'first' and 'last' names using space as separator.

R Programming

library(tidyr)
data <- data.frame(full_name = c('John Doe', 'Jane Smith'))
separated <- separate(data, col = [1], into = c([2], 'last'), sep = ' ')

Drag options to blanks, or click blank then click option'

Afull_name

Bfirst

Cname

Dlast_name

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong column names for splitting.

Mixing up the order of new column names.

The first blank is the column to split: 'full_name'. The second blank is the first new column name: 'first'.

5fill in blank

hard

Fill all three blanks to unite 'city', 'state', and 'zip' columns into 'address' separated by commas.

R Programming

library(tidyr)
data <- data.frame(city = c('Austin', 'Boston'), state = c('TX', 'MA'), zip = c('73301', '02101'))
united <- unite(data, col = [1], [2], [3], sep = ', ')

Drag options to blanks, or click blank then click option'

Aaddress

Bcity

Cstate

Dzip

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong column names or missing one of the columns.

Not specifying the new column name correctly.

The first blank is the new column name 'address'. The next blanks are the columns to unite: 'city' and 'state'. The last column 'zip' is already in the data frame and will be united automatically.

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