CS50R - Lecture 2 - Transforming Data

The lecture focuses on transforming data in R, specifically addressing outliers and subsetting. It begins by demonstrating how to identify and remove outliers from a dataset of average January temperatures using indexing and logical expressions. The discussion then shifts to subsetting data frames, using a dataset of baby chick weights to illustrate how to extract specific subsets based on feed type. Logical operators and functions like `which`, `any`, and `all` are introduced to facilitate data filtering. The lecture also covers handling missing data (`NA` values) and introduces the `subset` function for more streamlined data extraction. Finally, it touches on combining data from multiple sources using `rbind` and categorizing data based on conditions with `if-else`.