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rlubridate

Using lubridate with multiple date formats

I have a column of dates that was stored in the format 8/7/2001, 10/21/1990, etc. Two values are just four-digit years. I converted the entire column to class Date using the following code.

lubridate::parse_date_time(eventDate, orders = c('mdy', 'Y'))

It works great, except the values that were just years are converted to yyyy-01-01 and I want them to just be yyyy. Is there a way to keep lubridate from adding on any information that wasn't already there?

Edit: Code to create data frame

    id = (1:5)
    eventDate = c("10/7/2001", "1989", NA, "5/5/2016", "9/18/2011")
    df <- data.frame(id, eventDate)
Solution

  • I do not think is possible to convert your values to Dates, and keep the "yyyy" values intact. And by transforming your "yyyy" values into "yyyy-01-01" the lubridate is doing the right thing. Because dates have order, and if you have other values in your column that have days and months defined, all the other values needs to have these components too.

    For example. If I produce the data.frame below. If I ask R, to order the table, according to the date column, the date in the first line ("2020"), comes before the value in the second row ("2020-02-28")? Or comes after it? The value "2020" being the year of 2020, it can actually means every possible day in this year, so how R should treate it? By adding the first day of the year, lubridate is defining these components, and avoiding that R get confused by it.

    dates <- c("2020", "2020-02-28", "2020-02-20", "2020-01-10", "2020-05-12")
id <- 1:5

df <- data.frame(
  id,
  dates
)

  id      dates
1  1       2020
2  2 2020-02-28
3  3 2020-02-20
4  4 2020-01-10
5  5 2020-05-12

    So if you want to mantain the "yyyy" intact, is very likely that they should not rest in your eventDate column, with other values that are in a different structure ("dd/mm/yyyy"). Now if is really necessary to mantain these values intact, I think is best, to keep the values of eventDate column as characters, and store these values as Dates in another column, like this:

    df$as_dates <- lubridate::parse_date_time(df$eventDate, orders = c('mdy', 'Y'))

  id eventDate   as_dates
1  1 10/7/2001 2001-10-07
2  2      1989 1989-01-01
3  3      <NA>       <NA>
4  4  5/5/2016 2016-05-05
5  5 9/18/2011 2011-09-18