I usually roll my own:
-----------
Sys.setenv( TZ = "GMT" )
ssdf$Dtm <- with( ssdf
, as.POSIXct( paste( date_POSIX, time_POSIX ) )
)
ceiling_dtmN <- function( dtm, mins ) {
tm_base <- as.POSIXct( trunc( min( dtm ), units = "days" ) )
x <- as.numeric( dtm - tm_base, units = "mins" )
xceil <- ceiling( x %/% mins ) * mins
tm_base + as.difftime( xceil, units = "mins" )
}
ssdf$Dtm30 <- ceiling_dtmN( ssdf$Dtm, mins = 30 )
ssdf
-----------
On Sun, 6 Dec 2020, Stefano Sofia wrote:
Hi Jim.
I studied and implemented your solution in details. The idea is great, but after a sharp revision I
came to the conclusion that unfortunately it des not work correctly: for the "am" side
(10, 20, 30 minutes) it works well because the hour is exactly the same, while for the
"pm" side (40, 50, 00) the algorithm it doesn't because the hour related to 40 and 50
minutes is different from the hour related to 00 (which is the following one). Am I wrong?
I tried to fix it keeping the easy structure of the algorithm, but with no
success.
Any hint for that?
Thank you for your attention and your help
Stefano
(oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.so...@regione.marche.it
---Oo---------oO----------------
________________________________________
Da: Jim Lemon [drjimle...@gmail.com]
Inviato: gioved? 3 dicembre 2020 4.41
A: Stefano Sofia
Cc: r-help mailing list
Oggetto: Re: [R] change frequency of wind data correctly
Hi again,
Didn't realize that the example didn't even span a full day.
ssdf<-read.table(text="date_POSIX time_POSIX vmax
2018-02-01 00:00:00 27
2018-02-01 00:10:00 41
2018-02-01 00:20:00 46
2018-02-01 00:30:00 39
2018-02-01 00:40:00 34
2018-02-01 00:50:00 32
2018-02-01 01:00:00 37
2018-02-01 01:10:00 31
2018-02-01 01:20:00 26
2018-02-01 01:30:00 29
2018-02-01 01:40:00 24
2018-02-01 01:50:00 35",
header=TRUE,stringsAsFactors=FALSE)
# extract the hour
ssdf$hour<-
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",1)))
# get the time of day as seconds from the time field
ssdf$mins<-
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",2)))
# create an AM/PM variable
ssdf$ampm<-ifelse(ssdf$mins > 0 & ssdf$mins <= 30,"am","pm")
# drop first row
ssdf<-ssdf[-1,]
means<-aggregate(vmax~hour+ampm,ssdf,mean)
This does a full day. To do more, add the date_POSIX field to the
aggregate command. If you have the date and time in one field you'll
have to split that. That will distinguish the AM/PM means in each day
as well as hour.
Jim
On Thu, Dec 3, 2020 at 2:10 PM Jim Lemon <drjimle...@gmail.com> wrote:
Hi Stefano,
I read in your date-time as two separate fields for convenience. You
can split your single field at the space to get the same result.
ssdf<-read.table(text="date_POSIX time_POSIX vmax
2018-02-01 00:00:00 27
2018-02-01 00:10:00 41
2018-02-01 00:20:00 46
2018-02-01 00:30:00 39
2018-02-01 00:40:00 34
2018-02-01 00:50:00 32",
header=TRUE,stringsAsFactors=FALSE)
# get the time of day as seconds from the time field
ssdf$seconds<-as.numeric(strptime(ssdf$time_POSIX,"%H:%M:%S"))
# subtract whatever current date strptime guesses for the date
ssdf$seconds<-ssdf$seconds-min(ssdf$seconds)
# create an AM/PM variable
ssdf$ampm<-ifelse(ssdf$seconds > 0 & ssdf$seconds <= 1800,"am","pm")
means<-aggregate(vmax~ampm,ssdf,mean)
Jim
On Thu, Dec 3, 2020 at 4:55 AM Stefano Sofia
<stefano.so...@regione.marche.it> wrote:
Dear list users,
I have wind data with frequency of 10 minutes (three years data). For
simplicity let me use only max wind speed.
I need to reduce the frequency to 30 minutes, at 00 (taking the mean of data
at 40, 50 and 00 minutes) and at 30 (taking the mean of data at 10, 20 and 30
minutes) of each hour.
The simple code here reported works well, but the column "interval" groups data
forward, not backward:
init_day <- as.POSIXct("2018-02-01-00-00", format="%Y-%m-%d-%H-%M",
tz="Etc/GMT-1")
fin_day <- as.POSIXct("2018-02-01-02-00", format="%Y-%m-%d-%H-%M",
tz="Etc/GMT-1")
mydf <- data.frame(data_POSIX=seq(init_day, fin_day, by="10 mins"))
mydf$vmax <- round(rnorm(13, 35, 10))
mydf$interval <- cut(mydf$data_POSIX, , breaks="30 min")
means <- aggregate(vmax ~ interval, mydf, mean)
data_POSIX vmax interval
1 2018-02-01 00:00:00 27 2018-02-01 00:00:00
2 2018-02-01 00:10:00 41 2018-02-01 00:00:00
3 2018-02-01 00:20:00 46 2018-02-01 00:00:00
4 2018-02-01 00:30:00 39 2018-02-01 00:30:00
5 2018-02-01 00:40:00 34 2018-02-01 00:30:00
6 2018-02-01 00:50:00 32 2018-02-01 00:30:00
...
I should work with
data_POSIX vmax interval
1 2018-02-01 00:00:00 27 2018-02-01 00:00:00
2 2018-02-01 00:10:00 41 2018-02-01 00:30:00
3 2018-02-01 00:20:00 46 2018-02-01 00:30:00
4 2018-02-01 00:30:00 39 2018-02-01 00:30:00
5 2018-02-01 00:40:00 34 2018-02-01 00:00:00
6 2018-02-01 00:50:00 32 2018-02-01 00:00:00
...
Is there a way to modify this code to groupp data correctly? (I would prefer
using only the base package)
Thank you for your help
Stefano
(oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.so...@regione.marche.it
---Oo---------oO----------------
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