I have the following dates:
my_dataset <- tibble(my_date = c("03-05-2020", "04-05-2020", "05-05-2020", "06-05-2020"))
I would like to create a new column called nice_dates which has the date format as: dd/mm/yyyy format, so I would end up with something like this:
my_date | nice_dates
03-05-2020 | 03/05/2020
04-05-2020 | 04/05/2020
05-05-2020 | 05/05/2020
06-05-2020 | 06/05/2020
I have tried using the lubridate pacakge but get stuck when defining the new format i know it should be "%d/%m/%Y" however using as.Date() yields NA.
Should i just use gsub instead?
@ThoVu is almost there. So for completeness, a much simpler answer with only base R.
Code## input data as before
df <- data.frame(my_date = c("03-05-2020", "04-05-2020",
"05-05-2020", "06-05-2020"))
## create Date objects using base R
df$parsed <- strptime(df$my_date, "%d-%m-%Y")
## format them to spec
df$nice_dates <- format(df$parsed, "%d/%m/%Y")
R> df <- data.frame(my_date = c("03-05-2020", "04-05-2020",
"05-05-2020", "06-05-2020"))
R> df$parsed <- strptime(df$my_date, "%d-%m-%Y")
R> df$nice_dates <- format(df$parsed, "%d/%m/%Y")
R> df
my_date parsed nice_dates
1 03-05-2020 2020-05-03 03/05/2020
2 04-05-2020 2020-05-04 04/05/2020
3 05-05-2020 2020-05-05 05/05/2020
4 06-05-2020 2020-05-06 06/05/2020
R>
My general recommendation is to never ever use string manipulations or regular expressions on date inputs when you could use proper date parsers.