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  1. library(tidyverse)
  2. # library(lubridate)
  3. # library(stringr)
  4. # library(forcats)
  5. # Load the csv data and tidy it ----
  6. read_csv("Data/.csv") %>%
  7. select() %>%
  8. filter() %>%
  9. mutate() %>%
  10. dmap_if(is.character, factor) -> df
  11. # Save the tidy-ed data ----
  12. save(df, file = "tidy.Rdata")