Parsing a Date
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dta <- 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" ), levels = c("1000 mb", "1000 mb", "1000 mb", "1000 mb", "1000 mb" ), lon = c(-113.13, -113.111, -113.092, -112.987, -112.968), lat = c(33.6335, 33.5142, 33.3948, 33.6495, 33.5301), HGT = c(75.5519, 75.9582, 76.3957, 75.9269, 76.3019), RH = c(49.6484, 51.0234, 52.7734, 49.1484, 50.2734), TMP = c(305.495, 305.245, 305.057, 305.745, 305.495), UGRD = c(1.40155, 1.65155, 1.90155, 1.90155, 2.08905), VGRD = c(2.23264, 2.23264, 2.23264, 2.04514, 1.98264 )), .Names = c("forecast.date", "levels", "lon", "lat", "HGT", "RH", "TMP", "UGRD", "VGRD"), class = "data.frame", row.names = c(NA, -5L))
dta$Year <- as.integer( substr( dta$forecast.date, 1, 4 ) )
dta$Month <- as.integer( substr( dta$forecast.date, 6, 7 ) )
dta$Day <- as.integer( substr( dta$forecast.date, 9, 10 ) )
dta$Hour <- as.integer( substr( dta$forecast.date, 12, 13 ) )
dta
On August 2, 2020 9:24:24 AM PDT, Philip <herd_dog at cox.net> wrote:
Below is some Weather Service data. I would like to parse the forecast
date field into four different columns:
Year
Month
Day
Hour
I would like to drop the final four zeros. Any suggestions?
forecast.date levels lon lat HGT
RH TMP UGRD VGRD
1 2020-08-01 12:00:00 1000 mb -113.130 33.6335 75.5519 49.6484 305.495
1.40155 2.23264
2 2020-08-01 12:00:00 1000 mb -113.111 33.5142 75.9582 51.0234 305.245
1.65155 2.23264
3 2020-08-01 12:00:00 1000 mb -113.092 33.3948 76.3957 52.7734 305.057
1.90155 2.23264
4 2020-08-01 12:00:00 1000 mb -112.987 33.6495 75.9269 49.1484 305.745
1.90155 2.04514
5 2020-08-01 12:00:00 1000 mb -112.968 33.5301 76.3019 50.2734 305.495
2.08905 1.98264
Philip Heinrich
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