change frequency of wind data correctly
This afternoon I will work on that.
I am thinking to stick to Jim's algorithm, changing the hours related to 40 and 50 mins. If I add one hour to them, everything should work correctly, because wind data at 40, 50 and 00 would have exactly the same hours.
This would not be elegant, but efficient.
Also missing data might be easily handled, changing the "mean" function with a function that accepts NA.
But I will study all the solutions that have been kindly proposed.
Thank you all of you
Stefano
(oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
---Oo---------oO----------------
Da: Jeff Newmiller [jdnewmil at dcn.davis.ca.us]
Inviato: luned? 7 dicembre 2020 7.36
A: r-help at r-project.org; Richard O'Keefe; Stefano Sofia
Cc: r-help mailing list
Oggetto: Re: [R] change frequency of wind data correctly
Beware of missing or extra records with these approaches. Also may be tricky to get the time aligned to the hour properly.
On December 6, 2020 9:12:01 PM PST, Richard O'Keefe <raoknz at gmail.com> wrote:
>To be honest, I would do this one of two ways.
>
>(1) Use ?decimate from library(signal),
> decimating by a factor of three.
>
>(2) Convert the variable to an (n/3)*3 matrix using
> as.matrix then use rowMeans or apply.
>
>On Thu, 3 Dec 2020 at 06:55, Stefano Sofia
><stefano.sofia at regione.marche.it>
>wrote:
>
>> Dear list users,
>> I have wind data with frequency of 10 minutes (three years data). For
>> simplicity let me use only max wind speed.
>> I need to reduce the frequency to 30 minutes, at 00 (taking the
>mean of
>> data at 40, 50 and 00 minutes) and at 30 (taking the mean of data at
>10, 20
>> and 30 minutes) of each hour.
>>
>> The simple code here reported works well, but the column "interval"
>groups
>> data forward, not backward:
>>
>> init_day <- as.POSIXct("2018-02-01-00-00", format="%Y-%m-%d-%H-%M",
>> tz="Etc/GMT-1")
>> fin_day <- as.POSIXct("2018-02-01-02-00", format="%Y-%m-%d-%H-%M",
>> tz="Etc/GMT-1")
>> mydf <- data.frame(data_POSIX=seq(init_day, fin_day, by="10 mins"))
>> mydf$vmax <- round(rnorm(13, 35, 10))
>> mydf$interval <- cut(mydf$data_POSIX, , breaks="30 min")
>> means <- aggregate(vmax ~ interval, mydf, mean)
>>
>> data_POSIX vmax interval
>> 1 2018-02-01 00:00:00 27 2018-02-01 00:00:00
>> 2 2018-02-01 00:10:00 41 2018-02-01 00:00:00
>> 3 2018-02-01 00:20:00 46 2018-02-01 00:00:00
>> 4 2018-02-01 00:30:00 39 2018-02-01 00:30:00
>> 5 2018-02-01 00:40:00 34 2018-02-01 00:30:00
>> 6 2018-02-01 00:50:00 32 2018-02-01 00:30:00
>> ...
>>
>> I should work with
>>
>> data_POSIX vmax interval
>> 1 2018-02-01 00:00:00 27 2018-02-01 00:00:00
>> 2 2018-02-01 00:10:00 41 2018-02-01 00:30:00
>> 3 2018-02-01 00:20:00 46 2018-02-01 00:30:00
>> 4 2018-02-01 00:30:00 39 2018-02-01 00:30:00
>> 5 2018-02-01 00:40:00 34 2018-02-01 00:00:00
>> 6 2018-02-01 00:50:00 32 2018-02-01 00:00:00
>> ...
>>
>>
>> Is there a way to modify this code to groupp data correctly? (I would
>> prefer using only the base package)
>>
>> Thank you for your help
>> Stefano
>>
>>
>>
>> (oo)
>> --oOO--( )--OOo----------------
>> Stefano Sofia PhD
>> Civil Protection - Marche Region
>> Meteo Section
>> Snow Section
>> Via del Colle Ameno 5
>> 60126 Torrette di Ancona, Ancona
>> Uff: 071 806 7743
>> E-mail: stefano.sofia at regione.marche.it
>> ---Oo---------oO----------------
>>
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