[R] Problem with diff(strptime(...

[Prof Brian Ripley]

You are throwing away the clue in your use of as.numeric.

First. strptime returns a POSIXlt value, which you will convert to POSIXct 
when you do arithetic (using diff()).  Why are you doing that?  So

> foodate<-factor(c("1/7/1991","1/8/1991","1/8/1991","3/8/1991"))
> diff(strptime(foodate,"%d/%m/%Y"))
Time differences in secs
[1] 2678400       0  172800
attr(,"tzone")
[1] ""

is correct.  I think you intended

diff(as.Date(foodate,"%d/%m/%Y"))/365.25

or even add as.numeric() inside diff().



On Thu, 20 Mar 2008, Jim Lemon wrote:

> Hi all,
>
> I have been chipping away at a problem I encountered in calculating
> rates per year from a moderately large data file (46412 rows). When I
> ran the following command, I got obviously wrong output:
>
> interval<-
>  c(NA,as.numeric(diff(
>  strptime(mkdf$MEAS_DATE,"%d/%m/%Y")))/365.25)
>
> The values in MEAS_DATE looked like this:
>
> mkdf$MEAS_DATE[1:10]
>  [1] 1/5/1962  1/5/1963  1/5/1964  1/3/1965  1/4/1966  1/4/1967
>  1/6/1968
>  [8] 25/3/1969 1/4/1971  1/2/1974
> 146 Levels: 10/10/1967 1/10/1947 1/10/1965 1/10/1967 1/10/1983 ... 9/1/1992
>
> To abbreviate three evenings of work, I finally found that values 17170
> and 17171 were the same. If I ran the entire set, or anything over
> 1:17170, I would get output like this:
>
> interval[1:10]
>  [1]        NA  86340.86  86577.41  71911.29  93673.92  86340.86
>  101006.98
>  [8]  70255.44 174337.58 245292.81
>
> If I ran any set of values up to 17170, I would get the correct output:
>
> interval[1:10]
>  [1]        NA 0.9993155 1.0020534 0.8323066 1.0841889 0.9993155
>  1.1690623
>  [8] 0.8131417 2.0177960 2.8390372
>
> If I changed value 17171 by one day (and added that level), the command
> worked correctly:
>
> interval[1:10]
>  [1]        NA 0.9993155 1.0020534 0.8323066 1.0841889 0.9993155
>  1.1690623
>  [8] 0.8131417 2.0177960 2.8390372
>
> There have been a few messages about this problem, but apparently no
> solution. The problem can be seen with these examples (I haven't
> included the real data as it is not mine):
>
> foodate<-c("1/7/1991","1/8/1991","1/8/1991","3/8/1991")
> as.numeric(diff(strptime(foodate,"%d/%m/%Y"))/365.25)
> [1] 7333.0595    0.0000  473.1006
>
> foodate<-factor(c("1/7/1991","1/8/1991","1/8/1991","3/8/1991"))
> as.numeric(diff(strptime(foodate,"%d/%m/%Y"))/365.25)
> [1] 7333.0595    0.0000  473.1006
>
> foodate<-factor(c("1/7/1991","1/8/1991","2/8/1991","3/8/1991"))
> > as.numeric(diff(strptime(foodate,"%d/%m/%Y"))/365.25)
> [1] 0.084873374 0.002737851 0.002737851
>
> Beats me.
>
> Jim
>
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> and provide commented, minimal, self-contained, reproducible code.
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595