select() for column selection in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the column 'mpg' from the mtcars dataset using dplyr's select().

R Programming

library(dplyr)
selected_data <- mtcars %>% select([1])
print(selected_data)

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

Acyl

Bmpg

Cgear

Dhp

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a column name that is not in the dataset.

Using quotes around the column name inside select(), which is not needed in tidyverse syntax.

The select() function chooses columns by their names. Here, we want to select the 'mpg' column.

2fill in blank

medium

Complete the code to select columns 'mpg' and 'cyl' from mtcars using select() with the colon operator.

R Programming

library(dplyr)
selected_data <- mtcars %>% select([1])
print(selected_data)

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

Ampg:cyl:gear

Bmpg,cyl

Cmpg:cyl

Dmpg-cyl

Attempts:

3 left

💡 Hint

Common Mistakes

Using commas inside select() without c(), which is not correct in tidyverse select.

Using dashes or extra colons which are invalid syntax.

The colon operator mpg:cyl selects all columns from 'mpg' to 'cyl' inclusive in their order in the dataset.

3fill in blank

hard

Fix the error in the code to select columns 'mpg' and 'hp' from mtcars using select().

R Programming

library(dplyr)
selected_data <- mtcars %>% select([1])
print(selected_data)

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

Ampg, hp

B"mpg", "hp"

Cc(mpg, hp)

Dmpg hp

Attempts:

3 left

💡 Hint

Common Mistakes

Using quotes around column names inside select().

Using c() to combine columns inside select(), which is not needed.

In select(), column names are unquoted and separated by commas without c(). So mpg, hp is correct.

4fill in blank

hard

Fill both blanks to select columns from 'mpg' to 'hp' and exclude 'cyl' from mtcars.

R Programming

library(dplyr)
selected_data <- mtcars %>% select([1]) %>% select(-[2])
print(selected_data)

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

Ampg:hp

Bcyl

Cgear

Dhp

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to exclude columns before selecting the range.

Not using the minus sign to exclude a column.

First, select columns from 'mpg' to 'hp' using mpg:hp. Then exclude 'cyl' by using -cyl.

5fill in blank

hard

Fill all three blanks to select columns starting with 'd' and ending with 'q' and exclude 'drat' from mtcars.

R Programming

library(dplyr)
selected_data <- mtcars %>% select(starts_with([1]), ends_with([2])) %>% select(-[3])
print(selected_data)

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

A"d"

B"q"

Cdrat

Dgear

Attempts:

3 left

💡 Hint

Common Mistakes

Not using quotes inside starts_with or ends_with.

Trying to exclude columns without the minus sign.

Use starts_with("d") and ends_with("q") to select columns starting and ending with those letters. Then exclude 'drat' with -drat.

Practice

1. What does the select() function do in R's dplyr package?

easy

A. It adds new columns to the data frame.

B. It filters rows based on conditions.

C. It chooses specific columns from a data frame.

D. It sorts the data frame by a column.

Solution

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

   The select() function is designed to pick columns from a data frame, not rows or sorting.

2. Step 2: Compare with other functions

   Functions like filter() handle rows, arrange() sorts, and mutate() adds columns, so these are not what select() does.

3. Final Answer:

   It chooses specific columns from a data frame. -> Option C

4. Quick Check:

   select() = pick columns [OK]

Hint: Remember: select() picks columns, filter() picks rows [OK]

Common Mistakes:

• Confusing select() with filter()
• Thinking select() sorts data
• Assuming select() adds columns

2. Which of the following is the correct syntax to select columns name and age from a data frame df using dplyr?

easy

A. select(name, age)

B. df.select(name, age)

C. select(name, age, df)

D. df %>% select(name, age)

Solution

1. Step 1: Recall dplyr pipe syntax

   In dplyr, the pipe operator %>% passes df as the first argument to select().

2. Step 2: Check each option

   A: select(name, age) misses the data frame df. B: df %>% select(name, age) uses pipe correctly. C: select(name, age, df) has wrong argument order. D: df.select(name, age) is not valid R syntax.

3. Final Answer:

   df %>% select(name, age) -> Option D

4. Quick Check:

   Use pipe %>% then select columns [OK]

Hint: Use pipe %>% before select() for clean code [OK]

Common Mistakes:

• Wrong argument order in select()
• Using dot notation like df.select()
• Forgetting to load dplyr package

3. Given the data frame df with columns id, name, age, and score, what will be the output of this code?

library(dplyr)
df %>% select(name, score)

medium

A. A data frame with only columns name and score.

B. A data frame with all columns except name and score.

C. An error because select() needs row filtering.

D. A data frame with columns id and age only.

Solution

1. Step 1: Understand select() behavior

   The select() function picks only the columns named inside it, here name and score.

2. Step 2: Confirm output columns

   The output will be a data frame with just these two columns, dropping id and age.

3. Final Answer:

   A data frame with only columns name and score. -> Option A

4. Quick Check:

   select(name, score) = only those columns [OK]

Hint: select() keeps only listed columns, drops others [OK]

Common Mistakes:

• Thinking select() drops listed columns
• Expecting row filtering from select()
• Confusing select() with filter()

4. Identify the error in this code snippet:

library(dplyr)
df %>% select('name', 'age')

medium

A. Missing pipe operator before select().

B. Using quotes around column names causes an error.

C. select() cannot be used with dplyr.

D. The data frame df is not defined.

Solution

1. Step 1: Check column name syntax in select()

   In dplyr's select(), column names should be unquoted bare names, not strings.

2. Step 2: Understand consequences of quotes

   Using quotes treats them as strings, causing select() to fail to find columns and throw an error.

3. Final Answer:

   Using quotes around column names causes an error. -> Option B

4. Quick Check:

   Column names unquoted in select() [OK]

Hint: Do not put quotes around column names in select() [OK]

Common Mistakes:

• Quoting column names inside select()
• Forgetting to load dplyr
• Assuming select() filters rows

5. You have a data frame df with columns name, age, score, and grade. You want to select only name and score but rename score to points in the output. Which code does this correctly?

hard

A. df %>% select(name, points = score)

B. df %>% select(name, score = points)

C. df %>% rename(points = score) %>% select(name, score)

D. df %>% select(name, score) %>% mutate(points = score)

Solution

1. Step 1: Understand renaming in select()

   dplyr allows renaming columns inside select() by using new_name = old_name syntax.

2. Step 2: Check each option

   A: df %>% rename(points = score) %>% select(name, score) renames score to points, then selects score which no longer exists, error. B: df %>% select(name, score = points) reverses names, no points column exists, error. C: df %>% select(name, points = score) correctly selects name and renames score to points. D: df %>% select(name, score) %>% mutate(points = score) adds points but keeps score.

3. Final Answer:

   df %>% select(name, points = score) -> Option A

4. Quick Check:

   Rename inside select() with new = old [OK]

Hint: Rename columns inside select() using new_name = old_name [OK]

Common Mistakes:

• Swapping new and old names
• Using rename() without dropping old column
• Using mutate() instead of select() for renaming