pivot_longer (wide to long) in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load the tidyr package.

R Programming

library([1])

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

Adplyr

Btidyr

Cggplot2

Dstringr

Attempts:

3 left

💡 Hint

Common Mistakes

Loading the wrong package like dplyr or ggplot2 instead of tidyr.

The tidyr package contains the pivot_longer() function used to reshape data from wide to long format.

2fill in blank

medium

Complete the code to reshape the data frame df from wide to long format using pivot_longer().

R Programming

df_long <- pivot_longer(df, cols = [1], names_to = "variable", values_to = "value")

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

Ac(col1, col2)

Bc(1, 2)

Ccol1:col2

Dc("col1", "col2")

Attempts:

3 left

💡 Hint

Common Mistakes

Using unquoted column names or numeric indices instead of strings.

The cols argument expects column names as strings inside a vector, so c("col1", "col2") is correct.

3fill in blank

hard

Fix the error in the code to correctly specify the columns to pivot.

R Programming

df_long <- pivot_longer(df, cols = [1], names_to = "variable", values_to = "value")

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

Acol1:col2

Bc(col1, col2)

Cc("col1", "col2")

Dc('col1', 'col2')

Attempts:

3 left

💡 Hint

Common Mistakes

Using unquoted column names or colon notation which is invalid here.

The columns must be specified as a character vector with double quotes, so c("col1", "col2") is correct. Single quotes also work in R but the question expects double quotes for consistency.

4fill in blank

hard

Fill both blanks to create a long format data frame with columns named "key" and "val".

R Programming

df_long <- pivot_longer(df, cols = [1], names_to = [2], values_to = "val")

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

Ac("A", "B")

B"variable"

C"key"

Dc("col1", "col2")

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the order of columns and names_to arguments.

The cols argument should be the columns to pivot, here c("col1", "col2"). The names_to argument sets the new column name for the original column names, here "key".

5fill in blank

hard

Fill all three blanks to pivot columns "X1" and "X2" into a long format with names in "variable" and values in "value".

R Programming

df_long <- pivot_longer(df, cols = [1], names_to = [2], values_to = [3])

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

Ac("X1", "X2")

B"value"

C"variable"

D"val"

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up the names_to and values_to argument values.

The columns to pivot are c("X1", "X2"). The new column for names is "variable" and for values is "value".

Practice

1. What does the pivot_longer() function do in R's tidyverse?

easy

A. It filters rows based on a condition.

B. It creates new columns by splitting existing ones.

C. It transforms wide data into long data by stacking columns into rows.

D. It sorts data by a specific column.

Solution

1. Step 1: Understand the purpose of pivot_longer()

   The function is designed to reshape data from wide format (many columns) to long format (fewer columns, more rows).

2. Step 2: Identify the correct description

   Among the options, only It transforms wide data into long data by stacking columns into rows. correctly describes stacking columns into rows, which is what pivot_longer does.

3. Final Answer:

   It transforms wide data into long data by stacking columns into rows. -> Option C

4. Quick Check:

   pivot_longer = wide to long [OK]

Hint: pivot_longer stacks columns into rows to tidy data [OK]

Common Mistakes:

• Confusing pivot_longer with filtering or sorting functions
• Thinking it splits columns instead of stacking
• Assuming it creates new columns instead of reshaping

2. Which of the following is the correct syntax to pivot columns Jan and Feb into longer format with new columns named Month and Sales?

easy

A. pivot_longer(data, cols = c(Jan, Feb), names_to = "Month", values_to = "Sales")

B. pivot_longer(data, columns = c(Jan, Feb), names = "Month", values = "Sales")

C. pivot_longer(data, cols = c("Jan", "Feb"), names_to = Month, values_to = Sales)

D. pivot_longer(data, cols = Jan, Feb, names_to = "Month", values_to = "Sales")

Solution

1. Step 1: Check argument names and syntax

   The correct argument names are cols, names_to, and values_to. Columns should be passed as symbols or strings inside c().

2. Step 2: Validate each option

   pivot_longer(data, cols = c(Jan, Feb), names_to = "Month", values_to = "Sales") uses correct argument names and syntax with symbols inside c(). pivot_longer(data, columns = c(Jan, Feb), names = "Month", values = "Sales") uses wrong argument names. pivot_longer(data, cols = c("Jan", "Feb"), names_to = Month, values_to = Sales) misses quotes around new column names. pivot_longer(data, cols = Jan, Feb, names_to = "Month", values_to = "Sales") incorrectly separates columns without c().

3. Final Answer:

   pivot_longer(data, cols = c(Jan, Feb), names_to = "Month", values_to = "Sales") -> Option A

4. Quick Check:

   Correct args: cols, names_to, values_to [OK]

Hint: Use cols = c(), names_to and values_to with quotes [OK]

Common Mistakes:

• Using wrong argument names like columns or names
• Forgetting quotes around new column names
• Not wrapping columns in c()

3. Given this data frame in R:

df <- data.frame(ID = 1:2, Jan = c(10, 20), Feb = c(15, 25))

What is the output of:

pivot_longer(df, cols = c(Jan, Feb), names_to = "Month", values_to = "Value")

medium

A. A data frame with columns ID, Month, and Value, where Jan and Feb values are stacked under Value.

B. A data frame with columns ID, Jan, Feb unchanged.

C. An error because cols argument is missing quotes.

D. A data frame with columns ID, Month, Value but values are all NA.

Solution

1. Step 1: Understand pivot_longer behavior on df

   The function stacks the Jan and Feb columns into two rows per ID, creating Month and Value columns.

2. Step 2: Predict the output structure

   The output will have 4 rows (2 IDs x 2 months) and columns: ID, Month (Jan or Feb), and Value (corresponding numbers).

3. Final Answer:

   A data frame with columns ID, Month, and Value, where Jan and Feb values are stacked under Value. -> Option A

4. Quick Check:

   pivot_longer stacks columns into rows [OK]

Hint: pivot_longer stacks selected columns into new key-value columns [OK]

Common Mistakes:

• Expecting original wide format unchanged
• Thinking it causes errors without quotes on cols
• Assuming values become NA

4. What is wrong with this code?

pivot_longer(df, cols = Jan, Feb, names_to = "Month", values_to = "Value")

medium

A. The function pivot_longer does not exist.

B. The cols argument should be a vector using c(), not separate arguments.

C. The values_to argument is missing.

D. The names_to argument should not be in quotes.

Solution

1. Step 1: Check the cols argument format

   The cols argument must be a vector of columns, written as cols = c(Jan, Feb). Passing them separately is invalid syntax.

2. Step 2: Verify other arguments

   names_to and values_to are correctly used with quotes. The function exists in the tidyverse package.

3. Final Answer:

   The cols argument should be a vector using c(), not separate arguments. -> Option B

4. Quick Check:

   cols = c(...) required [OK]

Hint: Wrap multiple columns in c() inside cols argument [OK]

Common Mistakes:

• Passing multiple columns without c()
• Removing quotes from names_to or values_to
• Assuming pivot_longer is not available

5. You have a data frame:

df <- data.frame(ID = 1:2, Q1_2019 = c(5, 6), Q2_2019 = c(7, 8), Q1_2020 = c(9, 10))

You want to pivot it longer so that the quarter and year are separate columns named Quarter and Year, and the values go into Score. Which code achieves this?

hard

A. pivot_longer(df, cols = c(Q1_2019, Q2_2019, Q1_2020), names_to = c("Quarter", "Year"), values_to = "Score")

B. pivot_longer(df, cols = c(Q1_2019, Q2_2019, Q1_2020), names_to = "Quarter_Year", values_to = "Score")

C. pivot_longer(df, cols = c(Q1_2019, Q2_2019, Q1_2020), names_to = c("Year", "Quarter"), names_sep = "_", values_to = "Score")

D. pivot_longer(df, cols = starts_with("Q"), names_to = c("Quarter", "Year"), names_sep = "_", values_to = "Score")

Solution

1. Step 1: Identify columns to pivot

   All columns starting with "Q" represent quarters and years, so starts_with("Q") selects them.

2. Step 2: Separate names into Quarter and Year

   Using names_to = c("Quarter", "Year") with names_sep = "_" splits the column names at underscore into two new columns.

3. Step 3: Assign values to Score

   The values_to = "Score" argument names the new value column.

4. Final Answer:

   pivot_longer(df, cols = starts_with("Q"), names_to = c("Quarter", "Year"), names_sep = "_", values_to = "Score") -> Option D

5. Quick Check:

   Use names_sep to split names_to vector [OK]

Hint: Use names_to vector and names_sep to split column names [OK]

Common Mistakes:

• Not using names_sep to split names into multiple columns
• Swapping order of Quarter and Year in names_to
• Not selecting all relevant columns with starts_with