Where a column of dates contains two distinct formats, is there a way to parse both such that I get 2 rows of 2012-04-01 rather than the result below?
# A tibble: 2 x 1
date
<date>
1 2012-04-01
2 NA
**Example Code**
library(tidyverse)
data <- read_csv("date\n01/04/12\n41000", col_types = cols_only("date" = col_date("%d/%m/%y")))
head(data)
janitor::convert_to_date handles a mix of Excel numeric values and date-formatted dates.
library(tidyverse)
library(janitor)
data <- read_csv("date,text\n01/04/12,a\n41000,b\n02/02/13,c")
data %>%
mutate(clean_date = convert_to_date(date,
character_fun = lubridate::dmy))
#> # A tibble: 3 x 3
#> date text clean_date
#> <chr> <chr> <date>
#> 1 01/04/12 a 2012-04-01
#> 2 41000 b 2012-04-01
#> 3 02/02/13 c 2013-02-02
Self-promotion disclaimer: I authored this package. But this function is built for precisely this use case so feels relevant to post here.