Data Science and Machine Learning with R - {dplyr}: The Mutate Verb

The video tutorial explores the 'mutate' verb in the deployer package, demonstrating its use in modifying and creating new columns in datasets. It covers basic and advanced techniques, using the Star Wars and Iris datasets as examples. The tutorial also introduces helper functions for applying operations across multiple columns, emphasizing the power and flexibility of the mutate verb in data manipulation.

What is the primary function of the mutate verb in dplyr?

• To filter rows based on conditions

• To summarize data

• To select specific columns

• To create or modify columns

Which dataset is used as an example to demonstrate the mutate verb?

• Iris dataset

• Star Wars dataset

• mtcars dataset

• Titanic dataset

How can you create a new column in a dataset using mutate?

• By using the select verb

• By using the arrange verb

• By using the mutate verb with a formula

• By using the filter verb

What is the purpose of using temporary columns in mutate?

• To perform operations without altering the original dataset

• To filter rows

• To permanently store data

• To delete unnecessary data

What does the across helper function in mutate allow you to do?

• Select columns based on a pattern

• Filter rows based on multiple conditions

• Apply a function to a single column

• Apply a function to multiple columns

Which helper function is used with mutate to apply a function to multiple columns?

• arrange

• across

• select

• filter

What is the result of using mutate with the across function?

• It deletes selected columns

• It filters rows based on conditions

• It applies a function to selected columns

• It creates a new dataset

What is a key benefit of using the mutate verb in data manipulation?

• It is used for data summarization

• It helps in sorting data

• It simplifies the process of creating or modifying columns

• It allows for data visualization

Why is it important to understand the mutate verb in dplyr?

• It is necessary for writing reports

• It is essential for data visualization

• It is crucial for data manipulation and preparation

• It is used for creating web applications

What should you do if you find the across function confusing?

• Use it without understanding

• Focus on understanding the basic mutate function first

• Skip learning dplyr altogether

• Ignore it completely