Data processing in R

Training agenda

Part one: Let’s get it started

• Importing data to RStudio using readr and haven
• Data structure and operations on types of data
• %>% – alternative solution to handle nested functions

Part two: The basics of the basics – introduction to dplyr

• Data filtering
• Data grouping and aggregation
• String and time data manipulation using lubridate and stringr packages

Part three: Shape up – introduction to tidyr

• Tidy data – methods of changing the size of data frame

Part four: Through hardships to the stars

• Advanced aggregation and data manipulation using purrr

Part five: Repeatability is the key – introduction to tidyeval

• Creating functions for data processing automation