Why does dmy() in the lubridate package not work with NAs? What is a good workaround?

Question

I stumbled across a peculiar behavior in the lubridate package: dmy(NA) trows an error instead of just returning an NA. This causes me problems when I want to convert a column with some elements being NAs and some date-strings that are normally converted without problems.

Here is the minimal example:

library(lubridate)
df <- data.frame(ID=letters[1:5],
              Datum=c("01.01.1990", NA, "11.01.1990", NA, "01.02.1990"))
df_copy <- df
#Question 1: Why does dmy(NA) not return NA, but throws an error?
df$Datum <- dmy(df$Datum)
Error in function (..., sep = " ", collapse = NULL)  : invalid separator
df <- df_copy
#Question 2: What's a work around?
#1. Idea: Only convert those elements that are not NAs
#RHS works, but assigning that to the LHS doesn't work (Most likely problem::
#column "Datum" is still of class factor, while the RHS is of class POSIXct)
df[!is.na(df$Datum), "Datum"] <- dmy(df[!is.na(df$Datum), "Datum"])
Using date format %d.%m.%Y.
Warning message:
In `[<-.factor`(`*tmp*`, iseq, value = c(NA_integer_, NA_integer_,  :
invalid factor level, NAs generated
df #Only NAs, apparently problem with class of column "Datum"
ID Datum
1  a  <NA>
2  b  <NA>
3  c  <NA>
4  d  <NA>
5  e  <NA>
df <- df_copy
#2. Idea: Use mapply and apply dmy only to those elements that are not NA
df[, "Datum"] <- mapply(function(x) {if (is.na(x)) {
                                 return(NA)
                               } else {
                                 return(dmy(x))
                               }}, df$Datum)
df #Meaningless numbers returned instead of date-objects
ID     Datum
1  a 631152000
2  b        NA
3  c 632016000
4  d        NA
5  e 633830400

To summarize, I have two questions: 1) Why does dmy(NA) not work? Based on most other functions I would assume it is good programming practice that every transformation (such as dmy()) of NA returns NA again (just as 2 + NA does)? If this behavior is intended, how do I convert a data.frame column that includes NAs via the dmy() function?

Answer 1

The Error in function (..., sep = " ", collapse = NULL) : invalid separator is being caused by the lubridate:::guess_format() function. The NA is being passed as sep in a call to paste(), specifically at fmts <- unlist(mlply(with_seps, paste)). You can have a go at improving the lubridate:::guess_format() to fix this.

Otherwise, could you just change the NA to characters ("NA")?

require(lubridate)
df <- data.frame(ID=letters[1:5],
    Datum=c("01.01.1990", "NA", "11.01.1990", "NA", "01.02.1990")) #NAs are quoted
df_copy <- df

df$Datum <- dmy(df$Datum)

Answer 2

Since your dates are in a reasonably straight-forward format, it might be much simpler to just use as.Date and specify the appropriate format argument:

df$Date <- as.Date(df$Datum, format="%d.%m.%Y")
df

  ID      Datum       Date
1  a 01.01.1990 1990-01-01
2  b       <NA>       <NA>
3  c 11.01.1990 1990-01-11
4  d       <NA>       <NA>
5  e 01.02.1990 1990-02-01

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To see a list of the formatting codes used by as.Date, see ?strptime