Introduction to Data Frames

The purpose of data frames is to arrange data with each row as an observation and each column representing a variable.

Hadley Wickham developed the dplyr package as an enhanced version of his original plyr package.

The select() function in dplyr extracts specific rows from a data frame based on given conditions.

To remove columns from a data frame, you can use the select() function with a minus sign (-) before the column names.

The arrange() function is used to rename variables in a data frame.

The mutate() function can add new variables or transform existing ones within a data frame.

Using summarize() in conjunction with group_by() allows for the calculation of summary statistics within defined groups of a data frame.

The %>% operator, known as the "pipe," is used to combine multiple dplyr functions in a sequence.

In dplyr, the rename() function has the new variable name on the right-hand side of the equal sign and the old name on the left.

The new name is on the left, and the old name is on the right​The filter() function in dplyr allows for complex logical sequences to be used for extracting data subsets.