Clean sanction dates

Usage

clean_dates(df, date_col, split = "updated", pattern = "original")

Arguments

df: processed USADA dataset with messy dates
date_col: sanction date column (usually sanction_announced)
split: regex to pass to split argument of strsplit() (defaults to "updated")
pattern: regex for other non-date pattern (defaults to "original")

Value

tibble with cleaned dates

Examples

sanction_dates <- data.frame(
  athlete = c("doe, jane", "roe, richard"),
  ugly_dates = c(
    "original: 01/01/2020 updated: 02/15/2021",
    "original: 03/03/2019 updated: 04/04/2020"
  )
)
sanction_dates
#>        athlete                               ugly_dates
#> 1    doe, jane original: 01/01/2020 updated: 02/15/2021
#> 2 roe, richard original: 03/03/2019 updated: 04/04/2020

clean_dates(
df = sanction_dates,
date_col = "ugly_dates",
split = "updated",
pattern = "original")
#>        athlete                               ugly_dates pattern_date split_date
#> 1    doe, jane original: 01/01/2020 updated: 02/15/2021   2020-01-01 2021-02-15
#> 2 roe, richard original: 03/03/2019 updated: 04/04/2020   2019-03-03 2020-04-04