[R] cumulative data monthly

[Diego Avesani]

Dear  Jeff, Dear Rui, Dear all,

I will try Rui's solution as soon as possible.
If I could ask:
As a first step, I would like to follow Jeff's suggestion. I will represent
the precipitation data with a cumulative distribution, one for each year.
This follow that I would like to select the starting date and the ending
date properly form dati$DATA in order to perform the cumulative function.

Could you help me on that.

Again, really really thanks

Diego



On Sun, 27 Jan 2019 at 21:37, Jeff Newmiller <jdnewmil using dcn.davis.ca.us>
wrote:

> Very succinct, Rui!
>
> One warning to Diego.... automatic data recorders tend to use the local
> standard timezone year-round. R by default assumes that timestamps
> converted from character to POSIXct using the current timezone on your
> computer... which may not be in the same zone that the logger was in but
> even more commonly the computer follows daylight savings time. This leads
> to NAs showing up in your converted timestamps in spring and duplicated
> values in autumn as the data are misinterpreted. The easiest solution can
> be to use
>
> Sys.setenv( TZ="GMT" )
>
> though if you need the actual timezone you can use a zone name of the form
> "Etc/GMT+5" (5 hrs west of GMT).
>
> Note that Rui's solution will only work correctly near the month
> transition if you pretend the data timezone is GMT or UTC. (Technically
> these are different so your mileage may vary but most implementations treat
> them as identical and I have not encountered any cases where they differ.)
>
> On January 27, 2019 10:03:44 AM PST, Rui Barradas <ruipbarradas using sapo.pt>
> wrote:
> >Hello,
> >
> >See if the following can get you started.
> >It uses package CRAN zoo, function as.yearmon.
> >
> >dati$MES <- zoo::as.yearmon(dati$DATAORA)
> >PMES <- ave(dati$PREC, dati$MES, FUN = cumsum)
> >
> >plot(dati$DATAORA, PMES)
> >
> >
> >Hope this helps,
> >
> >Rui Barradas
> >
> >Às 15:25 de 27/01/2019, Diego Avesani escreveu:
> >> Dear all,
> >>
> >> I have a set of data with has hourly value:
> >>
> >> # ID
> >> # Lo
> >> # L
> >> # Q
> >> Time,    T, RH,PSFC,DIR,VEL10, PREC, RAD, CC,FOG
> >> yyyy-mm-dd hh:mm,   °C,  %, hPa, °N,  m/s, mm/h,W/m²,  %,-
> >> 2012-01-01 06:00, -0.1,100, 815,313,  2.6,  0.0,   0,  0,0
> >> 2012-01-01 07:00, -1.2, 93, 814,314,  4.8,  0.0,   0,  0,0
> >> 2012-01-01 08:00,  1.7, 68, 815,308,  7.5,  0.0,  41, 11,0
> >> 2012-01-01 09:00,  2.4, 65, 815,308,  7.4,  0.0, 150, 33,0
> >> .....
> >> .....
> >>
> >> I was able to read it,  create my-own data frame and to plot the
> >total
> >> cumulative function.
> >> This is basically what I have done:
> >>
> >> dati <- read.csv(file="116.txt", header=FALSE, sep="," ,
> >> na.strings="-999",skip = 6)
> >> colnames(dati)=c("DATAORA","T", "RH","PSFC","DIR","VEL10", "PREC",
> >"RAD",
> >> "CC","FOG")
> >>
> >> dati$DATAORA<-as.POSIXct(strptime(dati$DATAORA,format="%Y-%m-%d
> >%H:%M"))
> >>
> >>
> >> P <- cumsum(dati$PREC)
> >> plot(dati$DATAORA, P)
> >>
> >> I would like to select the data according to an starting and ending
> >date.
> >> In addition, I would like to plot the monthly and not the total one.
> >> I mean, I would like to have a cumulative plot for each month of the
> >> selected year.
> >>
> >> I am struggling with "ddply" but probably it is the wrong way.
> >>
> >> Could someone help me?  Really Really thanks,
> >>
> >>
> >> Diego
> >>
> >>      [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> >http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >
> >______________________________________________
> >R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >https://stat.ethz.ch/mailman/listinfo/r-help
> >PLEASE do read the posting guide
> >http://www.R-project.org/posting-guide.html
> >and provide commented, minimal, self-contained, reproducible code.
>
> --
> Sent from my phone. Please excuse my brevity.
>

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