[R] change frequency of wind data correctly

Stefano Sofia @te|@no@@o||@ @end|ng |rom reg|one@m@rche@|t
Thu Dec 3 10:23:22 CET 2020


Thank you Jim for your solution.
I understood everything. As you say, splitting the POSIXct field is the key.

I apologise for not having used dput. I never used it but I will get aknowleged with it in a short time.

Thank you
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.sofia using regione.marche.it
---Oo---------oO----------------

________________________________________
Da: Jim Lemon [drjimlemon using gmail.com]
Inviato: giovedì 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 <drjimlemon using 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.sofia using 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.sofia using regione.marche.it
> > ---Oo---------oO----------------
> >
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