mutate() for new columns in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the mutate() function do in R's dplyr package?

mutate() adds new columns or changes existing ones in a data frame without removing existing data.

beginner

How do you create a new column total as the sum of columns price and tax using mutate()?

df %>% mutate(total = price + tax)

beginner

Can mutate() use existing columns to create new ones?

Yes, mutate() can use existing columns to calculate values for new columns.

intermediate

What happens if you use mutate() to create a column with the same name as an existing one?

The existing column is replaced by the new values you provide.

beginner

Write a mutate() example that creates a new column discounted_price which is 10% less than price.

df %>% mutate(discounted_price = price * 0.9)

What is the main purpose of mutate() in dplyr?

A Filter rows based on conditions

B Summarize data by groups

C Sort rows by column values

D Add or modify columns in a data frame

mutate() is used to add new columns or change existing ones.

Which of the following creates a new column area as length * width using mutate()?

A df %>% mutate(area = length + width)

B df %>% filter(area = length * width)

C df %>% mutate(area = length * width)

D df %>% select(area = length * width)

Multiplying length and width inside mutate() creates the new column area.

If you want to replace an existing column score with its square, which is correct?

A df %>% mutate(new_score = score^2)

B df %>% mutate(score = score^2)

C df %>% filter(score = score^2)

D df %>% select(score = score^2)

Using the same column name in mutate() overwrites it.

Can mutate() create multiple new columns at once?

A Yes, by separating each new column with a comma

B No, only one column at a time

C Only if you use <code>summarize()</code> instead

D Only if you use <code>filter()</code> first

You can add many new columns in one mutate() call by separating them with commas.

What will this code do? df %>% mutate(new_col = NA)

A Create a new column <code>new_col</code> filled with missing values

B Delete the column <code>new_col</code>

C Filter rows where <code>new_col</code> is NA

D Rename <code>new_col</code> to NA

This creates a new column with all values set to missing (NA).

Explain how to use mutate() to add a new column based on existing columns in a data frame.

Think about how you create a new column that depends on others.

Describe what happens if you use mutate() to create a column with the same name as an existing one.

Consider how mutate handles column names.