I have a time series dataset for several meteorological variables. The time data is logged in three separate columns:
It looks like the
timeDate package can handle gregorian time frames. I haven't used it personally but it looks straightforward. There is a
shift argument in some methods that allow you to set the offset from your data.
Because you mentioned it, I thought I'd show the actual code to merge together separate columns. When you have the values you need in separate columns you can use
paste to bring them together and
lubridate::mdy to parse them.
library(lubridate) col.month <- "Jan" col.year <- "2012" col.day <- "23" date <- mdy(paste(col.month, col.day, col.year, sep = "-"))
Lubridate is a great package, here's the official page: https://github.com/hadley/lubridate
And here is a nice set of examples: http://www.r-statistics.com/2012/03/do-more-with-dates-and-times-in-r-with-lubridate-1-1-0/