A quick look at dplyr’s new across() function

The video tutorial introduces the new 'across' function in Dplyr 1.0, demonstrating its use for applying functions across multiple columns in a data frame. The instructor sets up the environment, loads necessary packages, and prepares a COVID-19 dataset for analysis. The tutorial covers basic and advanced usage of the 'across' function, including summarizing data and applying multiple functions like median and maximum. The video emphasizes the function's ability to simplify code by avoiding the need to name each column individually.

What is the primary purpose of the 'across' function introduced in Dplyr 1.0?

• To perform a function across multiple columns

• To visualize data in a data frame

• To analyze a single column in a data frame

• To sort data in a data frame

How can you access the new functions in Dplyr 1.0 before they are available on CRAN?

• By using an older version of Dplyr

• By downloading the development version from GitHub

• By using the base R functions

• By downloading the stable version from CRAN

What is the benefit of using 'across' when summing numeric columns in a data frame?

• It allows for reshaping the data

• It sorts the data alphabetically

• It eliminates the need to name each column individually

• It automatically visualizes the data

Which of the following is a feature of the 'across' function when applying multiple functions?

• It only works with character columns

• It allows applying a list of functions to each column

• It requires reshaping the data

• It can only apply one function at a time

What is the result of applying the 'across' function with median and maximum on a data frame?

• A reshaped data frame with all values

• A data frame with only the maximum values

• A summarized data frame with median and maximum for each date column

• A single column with the average value