Dear Jeff, Dear Rui, Dear all,
Forget about the monthly things. I was trying to do two things at the
same time.
I try to explain myself. Thanks for your time and I really appreciate
your help.
I have? a long file with hourly precipitation from 2000 to 2018. I would
like to select only on e year or even half of a year and plot the
cumulative precipitation of it in order to compare it with the
simulation data that I have.
So far I was able only to read all the file:
dati <- read.csv(file="116.txt", header=FALSE, sep="," ,
na.strings="-999",skip = 6)
and to plot the entire cumulative:
P <- cumsum(dati$PREC)
plot(dati$DATAORA, P)
How can I choose only, for example, 2013 in order to have P?
thanks again
Diego
On Mon, 28 Jan 2019 at 02:36, Jeff Newmiller <jdnewmil at dcn.davis.ca.us
<mailto:jdnewmil at dcn.davis.ca.us>> wrote:
I have no idea what you mean when you say "select starting date and
ending
date properly form [sic] datai$DATA". For one thing there is no column
called DATA, and for another I don't know what starting dates and
ending
dates you might be interested in. If you need help to subset by time,
perhaps you should ask a question about that instead.
Here is a reproducible example of making monthly data and
manipulating it
using artificial data:
###############
library(zoo)
Sys.setenv( TZ = "GMT" )
set.seed(42)
dati <- data.frame( DATAORA = as.POSIXct( "2012-01-01" )
? ? ? ? ? ? ? ? ? ? ? ? ? ? ?+ as.difftime( seq( 0, 365*3*24
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ), units="hours" )
? ? ? ? ? ? ? ? ? ?)
# terrible simulation of precipitation
dati$PREC <- 0.1 * trunc( 50 * rbeta( nrow( dati ), 1, 80 ) )
dati$ym <- as.yearmon( dati$DATAORA )
# aggregate usually reduces the number of rows given to it
datim <- aggregate( list( PREC = dati$PREC ) # data to summarize
? ? ? ? ? ? ? ? ? ?, dati[ , "ym", drop=FALSE ] # columns to group on
? ? ? ? ? ? ? ? ? ?, FUN = sum? # calculation on data
? ? ? ? ? ? ? ? ? ?)
plot(PREC ~ ym, data=datim) # This is how I would usually look at it
as.year <- function(x) floor( as.numeric( x ) ) # from help file on
as.yearmon
datim$y <- as.year( datim$ym )
# ave typically does not change the number of rows given to it
datim$PMES <- ave( datim$PREC, datim$y, FUN = cumsum)
plot(PMES ~ ym, data=datim) # My guess as to what you asked for?
###############
On Sun, 27 Jan 2019, Diego Avesani wrote:
> 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$DATA in order to
> perform the cumulative function.
>
> Could you help me on that.
>
> Again, really really thanks
>
> Diego
>
>
>
> On Sun, 27 Jan 2019 at 21:37, Jeff Newmiller
<jdnewmil at dcn.davis.ca.us <mailto:jdnewmil at dcn.davis.ca.us>> wrote:
>? ? ? ?Very succinct, Rui!
>
>? ? ? ?One warning to Diego.... automatic data recorders tend to
use the local standard timezone year-round. R by
>? ? ? ?default assumes that timestamps converted from character to
POSIXct using the current timezone on your
>? ? ? ?computer... which may not be in the same zone that the
logger was in but even more commonly the computer
>? ? ? ?follows daylight savings time. This leads to NAs showing up
in your converted timestamps in spring and
>? ? ? ?duplicated values in autumn as the data are misinterpreted.
The easiest solution can be to use
>
>? ? ? ?Sys.setenv( TZ="GMT" )
>
>? ? ? ?though if you need the actual timezone you can use a zone
name of the form "Etc/GMT+5" (5 hrs west of GMT).
>
>? ? ? ?Note that Rui's solution will only work correctly near the
month transition if you pretend the data timezone
>? ? ? ?is GMT or UTC. (Technically these are different so your
mileage may vary but most implementations treat them
>? ? ? ?as identical and I have not encountered any cases where
>
>? ? ? ?On January 27, 2019 10:03:44 AM PST, Rui Barradas
<ruipbarradas at sapo.pt <mailto:ruipbarradas at sapo.pt>> wrote:
>? ? ? ?>Hello,
>? ? ? ?>
>? ? ? ?>See if the following can get you started.
>? ? ? ?>It uses package CRAN zoo, function as.yearmon.
>? ? ? ?>
>? ? ? ?>dati$MES <- zoo::as.yearmon(dati$DATAORA)
>? ? ? ?>PMES <- ave(dati$PREC, dati$MES, FUN = cumsum)
>? ? ? ?>
>? ? ? ?>plot(dati$DATAORA, PMES)
>? ? ? ?>
>? ? ? ?>
>? ? ? ?>Hope this helps,
>? ? ? ?>
>? ? ? ?>Rui Barradas
>? ? ? ?>
>? ? ? ?>?s 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/m?,? %,-
>? ? ? ?>> 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
>? ? ? ?>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
>? ? ? ?>date.
>? ? ? ?>> In addition, I would like to plot the monthly and not
>? ? ? ?>> I mean, I would like to have a cumulative plot for each
>? ? ? ?>> selected year.
>? ? ? ?>>
>? ? ? ?>> I am struggling with "ddply" but probably it is the
>? ? ? ?>>
>? ? ? ?>> Could someone help me?? Really Really thanks,
>? ? ? ?>>
>? ? ? ?>>
>? ? ? ?>> Diego
>? ? ? ?>>
>? ? ? ?>>? ? ? [[alternative HTML version deleted]]
>? ? ? ?>>
>? ? ? ?>> ______________________________________________
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