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 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]]
Are you looking for a plot where each point represents a month? Or a plot where each point represents the accumulated precipitation so far that month? The latter seems closer to your computations so far, but doesn't seem like a typical way to present precipitation data... On January 27, 2019 7:25:17 AM PST, Diego Avesani <diego.avesani at gmail.com> wrote:>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 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 at 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.
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$DATAORA, PMES) Hope this helps, Rui Barradas ?s 15:25 de 27/01/2019, Diego Avesani escreveu:> Dear all, > > I have a set of data with has hourly value: > > # ID > # Lo > # L > # Q > Time, T, RH,PSFC,DIR,VEL10, PREC, RAD, CC,FOG > yyyy-mm-dd hh:mm, ?C, %, hPa, ?N, m/s, mm/h,W/m?, %,- > 2012-01-01 06:00, -0.1,100, 815,313, 2.6, 0.0, 0, 0,0 > 2012-01-01 07:00, -1.2, 93, 814,314, 4.8, 0.0, 0, 0,0 > 2012-01-01 08:00, 1.7, 68, 815,308, 7.5, 0.0, 41, 11,0 > 2012-01-01 09:00, 2.4, 65, 815,308, 7.4, 0.0, 150, 33,0 > ..... > ..... > > I was able to read it, create my-own data frame and to plot the total > cumulative function. > This is basically what I have done: > > dati <- read.csv(file="116.txt", header=FALSE, sep="," , > na.strings="-999",skip = 6) > colnames(dati)=c("DATAORA","T", "RH","PSFC","DIR","VEL10", "PREC", "RAD", > "CC","FOG") > > dati$DATAORA<-as.POSIXct(strptime(dati$DATAORA,format="%Y-%m-%d %H:%M")) > > > P <- cumsum(dati$PREC) > plot(dati$DATAORA, P) > > I would like to select the data according to an starting and ending date. > In addition, I would like to plot the monthly and not the total one. > I mean, I would like to have a cumulative plot for each month of the > selected year. > > I am struggling with "ddply" but probably it is the wrong way. > > Could someone help me? Really Really thanks, > > > Diego > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
Very succinct, Rui! One warning to Diego.... automatic data recorders tend to use the local standard timezone year-round. R by default assumes that timestamps converted from character to POSIXct using the current timezone on your computer... which may not be in the same zone that the logger was in but even more commonly the computer follows daylight savings time. This leads to NAs showing up in your converted timestamps in spring and duplicated values in autumn as the data are misinterpreted. The easiest solution can be to use Sys.setenv( TZ="GMT" ) though if you need the actual timezone you can use a zone name of the form "Etc/GMT+5" (5 hrs west of GMT). Note that Rui's solution will only work correctly near the month transition if you pretend the data timezone is GMT or UTC. (Technically these are different so your mileage may vary but most implementations treat them as identical and I have not encountered any cases where they differ.) On January 27, 2019 10:03:44 AM PST, Rui Barradas <ruipbarradas at sapo.pt> wrote:>Hello, > >See if the following can get you started. >It uses package CRAN zoo, function as.yearmon. > >dati$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 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 at 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 at 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.