Is there a more elegant way to convert two-digit years to four-digit years with lubridate?

Question

If a date vector has two-digit years, mdy() turns years between 00 and 68 into 21st Century years and years between 69 and 99 into 20th Century years. For example:

library(lubridate)    
mdy(c("1/2/54","1/2/68","1/2/69","1/2/99","1/2/04"))

gives the following output:

Multiple format matches with 5 successes: %m/%d/%y, %m/%d/%Y.
Using date format %m/%d/%y.
[1] "2054-01-02 UTC" "2068-01-02 UTC" "1969-01-02 UTC" "1999-01-02 UTC" "2004-01-02 UTC"

I can fix this after the fact by subtracting 100 from the incorrect dates to turn 2054 and 2068 into 1954 and 1968. But is there a more elegant and less error-prone method of parsing two-digit dates so that they get handled correctly in the parsing process itself?

Update: After @JoshuaUlrich pointed me to strptime I found this question, which deals with an issue similar to mine, but using base R.

It seems like a nice addition to date handling in R would be some way to handle century selection cutoffs for two-digit dates within the date parsing functions.

Solution 1

Here is a function that allows you to do this:

library(lubridate)
x <- mdy(c("1/2/54","1/2/68","1/2/69","1/2/99","1/2/04"))


foo <- function(x, year=1968){
  m <- year(x) %% 100
  year(x) <- ifelse(m > year %% 100, 1900+m, 2000+m)
  x
}

Try it out:

x
[1] "2054-01-02 UTC" "2068-01-02 UTC" "1969-01-02 UTC" "1999-01-02 UTC"
[5] "2004-01-02 UTC"

foo(x)
[1] "2054-01-02 UTC" "2068-01-02 UTC" "1969-01-02 UTC" "1999-01-02 UTC"
[5] "2004-01-02 UTC"

foo(x, 1950)
[1] "1954-01-02 UTC" "1968-01-02 UTC" "1969-01-02 UTC" "1999-01-02 UTC"
[5] "2004-01-02 UTC"

---

The bit of magic here is to use the modulus operator %% to return the fraction part of a division. So 1968 %% 100 yields 68.

Solution 2

I just experienced this exact same bug / feature.

I ended up writing the following two quick functions to help convert from excel-type dates (which is where i get this most) to something R can use.

There's nothing wrong with the accepted answer -- it's just that i prefer not to load up on packages too much.

First, a helper to split and replace the years ...

year1900 <- function(dd_y, yrFlip = 50)
{
    dd_y <- as.numeric(dd_y)
    dd_y[dd_y > yrFlip] <- dd_y[dd_y > yrFlip] + 1900
    dd_y[dd_y < yrFlip] <- dd_y[dd_y < yrFlip] + 2000
    return(dd_y)
}

which is used by a function that 'fixes' your excel dates, depending on type:

XLdate <- function(Xd, type = 'b-Y')
{
    switch(type,
        'b-Y' = as.Date(paste0(substr(Xd, 5, 9), "-", substr(Xd, 1, 3), "-01"), format = "%Y-%b-%d"),
        'b-y' = as.Date(paste0(year1900(substr(Xd, 5, 6)), "-", substr(Xd, 1, 3), "-01"), 
                        format = "%Y-%b-%d"),
        'Y-b' = as.Date(paste0(substr(Xd, 1, 3), "-", substr(Xd, 5, 9), "-01"), format =     "%Y-%b-%d")
        )
}

Hope this helps.

Comments

[eipi10]

Nice! Just noticed your answer. Thanks for your help.