CS50R - Lecture 4 - Tidying Data

This podcast episode focuses on tidying data in R using the tidyverse package. It introduces the concept of tidy data, emphasizing that each observation should be a row, each variable a column, and each value a cell. The discussion covers the dplyr package, including functions like select, filter, arrange, distinct, group by, and summarize, using a storms dataset as an example. The pipe operator is introduced as a way to chain functions for more readable code. Additionally, the podcast explores the tidyr package, particularly the pivot_wider function, to reshape data for better analysis, and stringr package to clean messy data values.