R: readxl and date format - r

Question

I read in an excel file, where 1 column contains dates in different format: excel format (e.g. 43596) and text (e.g. "01.01.2020").
To convert excel format one can use as.Date(as.numeric(df$date), origin = "1899-12-30")
to convert text one can use as.Date(df$date, format = "%d.%m.%Y")
These work for individual values, but when I try ifelse as:
df$date <- ifelse(length(df$date)==5,
as.Date(as.numeric(df$date), origin = "1899-12-30"),
as.Date(df$date, format = "%d.%m.%Y"))
or a for loop:
for (i in length(x)) {
if(nchar(x[i])==5) {
y[i] <- as.Date(as.numeric(x[i]), origin = "1899-12-30")
} else {x[i] <- as.Date(x[i], , format = "%d.%m.%Y"))}
} print(x)
It does not work because of:
"character string is not in a standard unambiguous format"
Maybe you could advice a better solution to convert/ replace different date formats in the appropriate one?

Answer 1

I have 2 solutions for it.
Changing the code, which I don't like because you are depending on xlsx date formats:
> df <- tibble(date = c("01.01.2020","43596"))
>
> df$date <- as.Date(ifelse(nchar(df$date)==5,
+ as.Date(as.numeric(df$date), origin = "1899-12-30"),
+ as.Date(df$date, format = "%d.%m.%Y")), origin = "1970-01-01")
Warning message:
In as.Date(as.numeric(df$date), origin = "1899-12-30") :
NAs introducidos por coerción
>
> df$date
[1] "2020-01-01" "2019-05-11"
>
Save the document as CSV and use read_csv() function from readr package. That solves everything !!!!

Answer 2

You could use sapply to apply ifelse to each value:
df$date <- as.Date(sapply(df$date,function(date) ifelse(nchar(date)==5,
as.Date(as.numeric(date), origin = "1899-12-30"),
as.Date(date, format = "%d.%m.%Y"))),
origin="1970-01-01")
df
# A tibble: 6 x 2
contract date
<dbl> <date>
1 231429 2019-05-11
2 231437 2020-01-07
3 231449 2021-01-01
4 231459 2020-03-03
5 231463 2020-10-27
6 231466 2011-03-17

Answer 3

A tidyverse solution using rowwise
library(dplyr)
library(lubridate)
df %>%
rowwise() %>%
mutate(date_new=as.Date(ifelse(grepl("\\.",date),
as.character(dmy(date)),
as.character(as.Date(as.numeric(date), origin="1899-12-30"))))) %>%
ungroup()
# A tibble: 6 × 3
contract date date_new
<dbl> <chr> <date>
1 231429 43596 2019-05-11
2 231437 07.01.2020 2020-01-07
3 231449 01.01.2021 2021-01-01
4 231459 03.03.2020 2020-03-03
5 231463 44131 2020-10-27
6 231466 40619 2011-03-17