On 2020-08-02 09:24 -0700, Philip wrote:
| Below is some Weather Service data.  I 
| would like to parse the forecast date 
| field into four different columns: 
| Year, Month, Day, Hour

Dear Philip,

I'm largely re-iterating Eric and Jeff's 
excellent solutions:

        > dat <- structure(list(forecast.date =
        + c("2020-08-01 12:00:00",
        + "2020-08-01 12:00:00",
        + "2020-08-01 12:00:00",
        + "2020-08-01 12:00:00",
        + "2020-08-01 12:00:00"
        + ), TMP = c("305.495", "305.245",
        + "305.057", "305.745", "305.495"
        + )), row.names = c(NA, 5L),
        + class = "data.frame")
        > t(apply(simplify2array(
        +   strsplit(dat$forecast.date, "-| |:")),
        +   2, as.numeric))
             [,1] [,2] [,3] [,4] [,5] [,6]
        [1,] 2020    8    1   12    0    0
        [2,] 2020    8    1   12    0    0
        [3,] 2020    8    1   12    0    0
        [4,] 2020    8    1   12    0    0
        [5,] 2020    8    1   12    0    0
        > simplify2array(parallel::mclapply(c(
        +   lubridate::year,
        +   lubridate::month,
        +   lubridate::day,
        +   lubridate::hour), function(FUN, x) {
        +     FUN(x)
        +   }, x=dat$forecast.date))
             [,1] [,2] [,3] [,4]
        [1,] 2020    8    1   12
        [2,] 2020    8    1   12
        [3,] 2020    8    1   12
        [4,] 2020    8    1   12
        [5,] 2020    8    1   12

V

r

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