Question

我在lubridate包中偶然发现了一种奇怪的行为：dmy(NA)拖欠错误而不是仅返回NA。当我想要转换一个包含一些元素为NA的列以及一些通常在没有问题时转换的日期字符串时，这会导致我出现问题。

这是最小的例子：

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

总结一下，我有两个问题：1）为什么dmy（NA）不起作用？基于大多数其他函数，我认为良好的编程习惯是NA的每个转换（例如dmy（））再次返回NA（就像2 + NA那样）？如果出现此问题，如何通过data.frame函数转换包含NA的{{1}}列？

Answer 1

Error in function (..., sep = " ", collapse = NULL) : invalid separator由lubridate:::guess_format()函数引起。在NA的来电中，sep正在paste()传递，特别是在fmts <- unlist(mlply(with_seps, paste))。您可以改进lubridate:::guess_format()来解决此问题。

否则，您是否可以将NA更改为字符（"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

由于您的日期采用了相当直接的格式，因此使用as.Date并指定适当的format参数可能要简单得多：

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

要查看as.Date使用的格式代码列表，请参阅?strptime

为什么rubridate包中的dmy（）不适用于NA？什么是好的解决方法？

2 个答案: