How to reshape data with tidyr’s new pivot functions

This video tutorial introduces the new pivot functions in TidyR, replacing the older gather and spread functions. It explains the differences between wide and long data formats and demonstrates how to use the pivot_longer and pivot_wider functions to reshape data. The tutorial also covers the syntax and arguments for these functions, highlighting their flexibility and ease of use.

What is the main reason for transitioning from gather and spread to pivot_longer and pivot_wider?

• Pivot functions are faster in execution.

• The new functions are more intuitive and user-friendly.

• Gather and spread are not compatible with new R versions.

• Gather and spread are being deprecated immediately.

Which of the following best describes a wide data set?

• Multiple data points are stored in a single row.

• Data is stored in a single column.

• Each column represents a different data set.

• Each row contains a single data point.

What is the purpose of the 'names_to' argument in the pivot_longer function?

• To rename the original data frame.

• To determine the data type of the new columns.

• To specify the new column names for the pivoted data.

• To filter out unwanted columns.

In the pivot_wider function, what does the 'names_from' argument specify?

• The default value for missing data.

• The ID of the data frame.

• The data type of the new columns.

• The column to use for new column names.

Why is it important to explicitly state the 'names_from' and 'values_from' arguments in pivot_wider?

• To increase the speed of the function.

• To ensure the function knows which columns to pivot.

• To maintain backward compatibility with older R versions.

• To avoid errors in data type conversion.