Bob Green schrieb:
>
> > dates <- read.csv("c:\\dates.csv",header=T)
> > dates
> v1 v2
> 1 12/12/1978 12/12/2005
> 2 23/01/1965 23/09/2001
> 3 24/12/2004 16/03/2007
> 4 3/03/2003 4/04/2004
> 5 8/11/2006 1/05/2007
>
> > class(dates$v1)
> [1] "factor"
> > class(dates$v2)
> [1] "factor"
>
>
What about chron library:
dts <- dates(c("02/27/92", "02/27/92", "01/14/92",
"02/28/92", "02/01/92"))
dts
# [1] 02/27/92 02/27/92 01/14/92 02/28/92 02/01/92
tms <- times(c("23:03:20", "22:29:56", "01:03:30",
"18:21:03", "16:56:26"))
tms
# [1] 23:03:20 22:29:56 01:03:30 18:21:03 16:56:26
x <- chron(dates = dts, times = tms)
x
# [1] (02/27/92 23:03:19) (02/27/92 22:29:56) (01/14/92 01:03:30)
# [4] (02/28/92 18:21:03) (02/01/92 16:56:26)
# We can add or subtract scalars (representing days) to dates or
# chron objects:
c(dts[1], dts[1] + 10)
# [1] 02/27/92 03/08/92
dts[1] - 31
# [1] 01/27/92
Knut
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