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
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