[R] aggregating data with quality control

[Stefano Sofia]

Dear R-list users,

I deal with semi-hourly data from automatic meteorological stations.

They have to pass a manual validation; suppose that status = "C" stands for correct and status = "D" for discarded.

Here a simple example with "Snow height" (HS):


mydf <- data.frame(data_POSIX=seq(as.POSIXct("2024-01-01 00:00:00", format = "%Y-%m-%d %H:%M:%S", tz="Etc/GMT-1"), as.POSIXct("2024-01-02 23:30:00", format = "%Y-%m-%d %H:%M:%S", tz="Etc/GMT-1"), by="30 min"))

mydf$hs <- round(runif(96, 0, 100))

mydf$status <- c(rep("C", 50), "S", rep("C", 45))


Evaluating the daily mean indipendently from the status is very easy:

aggregate(mydf$hs, by=list(format(mydf$data_POSIX, "%Y"), format(mydf$data_POSIX, "%m"), format(mydf$data_POSIX, "%d")), my.mean)


Things become more complicated when I need to export also the status: this should be "C" when all 48 data have status equal to "C", and status "D" when at least one value has status ="D".


I have no clue on how to do that in an efficient way.

Could some of you give me some clues on how to do that?


Thank you for your usual support

Stefano Sofia


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Stefano Sofia PhD
Civil Protection - Marche Region - Italy
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona (AN)
Uff: +39 071 806 7743
E-mail: stefano.sofia using regione.marche.it
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