Hi Jim.
I studied and implemented your solution in details. The idea is great, but after
a sharp revision I came to the conclusion that unfortunately it des not work
correctly: for the "am" side (10, 20, 30 minutes) it works well
because the hour is exactly the same, while for the "pm" side (40, 50,
00) the algorithm it doesn't because the hour related to 40 and 50 minutes
is different from the hour related to 00 (which is the following one). Am I
wrong?
I tried to fix it keeping the easy structure of the algorithm, but with no
success.
Any hint for that?
Thank you for your attention and 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----------------
________________________________________
Da: Jim Lemon [drjimlemon at gmail.com]
Inviato: gioved? 3 dicembre 2020 4.41
A: Stefano Sofia
Cc: r-help mailing list
Oggetto: Re: [R] change frequency of wind data correctly
Hi again,
Didn't realize that the example didn't even span a full day.
ssdf<-read.table(text="date_POSIX time_POSIX vmax
2018-02-01 00:00:00 27
2018-02-01 00:10:00 41
2018-02-01 00:20:00 46
2018-02-01 00:30:00 39
2018-02-01 00:40:00 34
2018-02-01 00:50:00 32
2018-02-01 01:00:00 37
2018-02-01 01:10:00 31
2018-02-01 01:20:00 26
2018-02-01 01:30:00 29
2018-02-01 01:40:00 24
2018-02-01 01:50:00 35",
header=TRUE,stringsAsFactors=FALSE)
# extract the hour
ssdf$hour<-
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",1)))
# get the time of day as seconds from the time field
ssdf$mins<-
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",2)))
# create an AM/PM variable
ssdf$ampm<-ifelse(ssdf$mins > 0 & ssdf$mins <=
30,"am","pm")
# drop first row
ssdf<-ssdf[-1,]
means<-aggregate(vmax~hour+ampm,ssdf,mean)
This does a full day. To do more, add the date_POSIX field to the
aggregate command. If you have the date and time in one field you'll
have to split that. That will distinguish the AM/PM means in each day
as well as hour.
Jim
On Thu, Dec 3, 2020 at 2:10 PM Jim Lemon <drjimlemon at gmail.com>
wrote:>
> Hi Stefano,
> I read in your date-time as two separate fields for convenience. You
> can split your single field at the space to get the same result.
>
> ssdf<-read.table(text="date_POSIX time_POSIX vmax
> 2018-02-01 00:00:00 27
> 2018-02-01 00:10:00 41
> 2018-02-01 00:20:00 46
> 2018-02-01 00:30:00 39
> 2018-02-01 00:40:00 34
> 2018-02-01 00:50:00 32",
> header=TRUE,stringsAsFactors=FALSE)
> # get the time of day as seconds from the time field
> ssdf$seconds<-as.numeric(strptime(ssdf$time_POSIX,"%H:%M:%S"))
> # subtract whatever current date strptime guesses for the date
> ssdf$seconds<-ssdf$seconds-min(ssdf$seconds)
> # create an AM/PM variable
> ssdf$ampm<-ifelse(ssdf$seconds > 0 & ssdf$seconds <=
1800,"am","pm")
> means<-aggregate(vmax~ampm,ssdf,mean)
>
> Jim
>
> On Thu, Dec 3, 2020 at 4:55 AM Stefano Sofia
> <stefano.sofia at regione.marche.it> wrote:
> >
> > Dear list users,
> > I have wind data with frequency of 10 minutes (three years data). For
simplicity let me use only max wind speed.
> > I need to reduce the frequency to 30 minutes, at 00 (taking the mean
of data at 40, 50 and 00 minutes) and at 30 (taking the mean of data at 10, 20
and 30 minutes) of each hour.
> >
> > The simple code here reported works well, but the column
"interval" groups data forward, not backward:
> >
> > init_day <- as.POSIXct("2018-02-01-00-00",
format="%Y-%m-%d-%H-%M", tz="Etc/GMT-1")
> > fin_day <- as.POSIXct("2018-02-01-02-00",
format="%Y-%m-%d-%H-%M", tz="Etc/GMT-1")
> > mydf <- data.frame(data_POSIX=seq(init_day, fin_day, by="10
mins"))
> > mydf$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----------------
> >
> > ________________________________
> >
> > AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere
informazioni confidenziali, pertanto ? destinato solo a persone autorizzate alla
ricezione. I messaggi di posta elettronica per i client di Regione Marche
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> > IMPORTANT NOTICE: This e-mail message is intended to be received only
by persons entitled to receive the confidential information it may contain.
E-mail messages to clients of Regione Marche may contain information that is
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> >
> > --
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> >
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >
https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-help&e=52342f8a&h=d46bc785&f=y&p=y
> > PLEASE do read the posting guide
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> > and provide commented, minimal, self-contained, reproducible code.
--
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I usually roll my own:
-----------
Sys.setenv( TZ = "GMT" )
ssdf$Dtm <- with( ssdf
, as.POSIXct( paste( date_POSIX, time_POSIX ) )
)
ceiling_dtmN <- function( dtm, mins ) {
tm_base <- as.POSIXct( trunc( min( dtm ), units = "days" ) )
x <- as.numeric( dtm - tm_base, units = "mins" )
xceil <- ceiling( x %/% mins ) * mins
tm_base + as.difftime( xceil, units = "mins" )
}
ssdf$Dtm30 <- ceiling_dtmN( ssdf$Dtm, mins = 30 )
ssdf
-----------
On Sun, 6 Dec 2020, Stefano Sofia wrote:
> Hi Jim.
> I studied and implemented your solution in details. The idea is great, but
after a sharp revision I came to the conclusion that unfortunately it des not
work correctly: for the "am" side (10, 20, 30 minutes) it works well
because the hour is exactly the same, while for the "pm" side (40, 50,
00) the algorithm it doesn't because the hour related to 40 and 50 minutes
is different from the hour related to 00 (which is the following one). Am I
wrong?
> I tried to fix it keeping the easy structure of the algorithm, but with no
success.
>
> Any hint for that?
> Thank you for your attention and your help
>
> Stefano
>
>
> (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Civil Protection - Marche Region
> Meteo Section
> Snow Section
> Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: stefano.sofia at regione.marche.it
> ---Oo---------oO----------------
>
> ________________________________________
> Da: Jim Lemon [drjimlemon at gmail.com]
> Inviato: gioved? 3 dicembre 2020 4.41
> A: Stefano Sofia
> Cc: r-help mailing list
> Oggetto: Re: [R] change frequency of wind data correctly
>
> Hi again,
> Didn't realize that the example didn't even span a full day.
>
> ssdf<-read.table(text="date_POSIX time_POSIX vmax
> 2018-02-01 00:00:00 27
> 2018-02-01 00:10:00 41
> 2018-02-01 00:20:00 46
> 2018-02-01 00:30:00 39
> 2018-02-01 00:40:00 34
> 2018-02-01 00:50:00 32
> 2018-02-01 01:00:00 37
> 2018-02-01 01:10:00 31
> 2018-02-01 01:20:00 26
> 2018-02-01 01:30:00 29
> 2018-02-01 01:40:00 24
> 2018-02-01 01:50:00 35",
> header=TRUE,stringsAsFactors=FALSE)
> # extract the hour
> ssdf$hour<-
>
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",1)))
> # get the time of day as seconds from the time field
> ssdf$mins<-
>
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",2)))
> # create an AM/PM variable
> ssdf$ampm<-ifelse(ssdf$mins > 0 & ssdf$mins <=
30,"am","pm")
> # drop first row
> ssdf<-ssdf[-1,]
> means<-aggregate(vmax~hour+ampm,ssdf,mean)
>
> This does a full day. To do more, add the date_POSIX field to the
> aggregate command. If you have the date and time in one field you'll
> have to split that. That will distinguish the AM/PM means in each day
> as well as hour.
>
> Jim
>
> On Thu, Dec 3, 2020 at 2:10 PM Jim Lemon <drjimlemon at gmail.com>
wrote:
>>
>> Hi Stefano,
>> I read in your date-time as two separate fields for convenience. You
>> can split your single field at the space to get the same result.
>>
>> ssdf<-read.table(text="date_POSIX time_POSIX vmax
>> 2018-02-01 00:00:00 27
>> 2018-02-01 00:10:00 41
>> 2018-02-01 00:20:00 46
>> 2018-02-01 00:30:00 39
>> 2018-02-01 00:40:00 34
>> 2018-02-01 00:50:00 32",
>> header=TRUE,stringsAsFactors=FALSE)
>> # get the time of day as seconds from the time field
>>
ssdf$seconds<-as.numeric(strptime(ssdf$time_POSIX,"%H:%M:%S"))
>> # subtract whatever current date strptime guesses for the date
>> ssdf$seconds<-ssdf$seconds-min(ssdf$seconds)
>> # create an AM/PM variable
>> ssdf$ampm<-ifelse(ssdf$seconds > 0 & ssdf$seconds <=
1800,"am","pm")
>> means<-aggregate(vmax~ampm,ssdf,mean)
>>
>> Jim
>>
>> On Thu, Dec 3, 2020 at 4:55 AM 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----------------
>>>
>>> ________________________________
>>>
>>> AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu?
contenere informazioni confidenziali, pertanto ? destinato solo a persone
autorizzate alla ricezione. I messaggi di posta elettronica per i client di
Regione Marche possono contenere informazioni confidenziali e con privilegi
legali. Se non si ? il destinatario specificato, non leggere, copiare, inoltrare
o archiviare questo messaggio. Se si ? ricevuto questo messaggio per errore,
inoltrarlo al mittente ed eliminarlo completamente dal sistema del proprio
computer. Ai sensi dell?art. 6 della DGR n. 1394/2008 si segnala che, in caso di
necessit? ed urgenza, la risposta al presente messaggio di posta elettronica pu?
essere visionata da persone estranee al destinatario.
>>> IMPORTANT NOTICE: This e-mail message is intended to be received
only by persons entitled to receive the confidential information it may contain.
E-mail messages to clients of Regione Marche may contain information that is
confidential and legally privileged. Please do not read, copy, forward, or store
this message unless you are an intended recipient of it. If you have received
this message in error, please forward it to the sender and delete it completely
from your computer system.
>>>
>>> --
>>> Questo messaggio stato analizzato da Libra ESVA ed risultato non
infetto.
>>> This message was scanned by Libra ESVA and is believed to be clean.
>>>
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>>>
https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-help&e=52342f8a&h=d46bc785&f=y&p=y
>>> PLEASE do read the posting guide
https://urlsand.esvalabs.com/?u=http%3A%2F%2Fwww.R-project.org%2Fposting-guide.html&e=52342f8a&h=9b25bfd5&f=y&p=y
>>> and provide commented, minimal, self-contained, reproducible code.
>
> --
>
> Questo messaggio stato analizzato con Libra ESVA ed risultato non
infetto.
>
>
> ________________________________
>
> AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere
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ricezione. I messaggi di posta elettronica per i client di Regione Marche
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il destinatario specificato, non leggere, copiare, inoltrare o archiviare questo
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6 della DGR n. 1394/2008 si segnala che, in caso di necessit? ed urgenza, la
risposta al presente messaggio di posta elettronica pu? essere visionata da
persone estranee al destinatario.
> IMPORTANT NOTICE: This e-mail message is intended to be received only by
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messages to clients of Regione Marche may contain information that is
confidential and legally privileged. Please do not read, copy, forward, or store
this message unless you are an intended recipient of it. If you have received
this message in error, please forward it to the sender and delete it completely
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>
> --
> Questo messaggio stato analizzato da Libra ESVA ed risultato non infetto.
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> ______________________________________________
> 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.
>
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...
DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live
Go...
Live: OO#.. Dead: OO#.. Playing
Research Engineer (Solar/Batteries O.O#. #.O#. with
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Hi,
Perhaps this might work for you. It leverages findInterval() and a
simple look-up-table of times to do the grouping. I made it return NA
when computing the mean when there are fewer than the three
observations.
Cheers,
Ben
n <- 144
x <- data.frame(
datetime = seq(from = as.POSIXct("2018-02-01 00:00:00", tz =
"UTC"),
by = "10 min",
length = n),
vmax = sample(10:50, n, replace = TRUE)
)
lut <- seq(from = x$datetime[1],
to = x$datetime[n],
by = "30 min") + 1 # add one second so that 00 sorts
with 40, 50, 00
# and the other grouping is 10, 20 30
x$interval <- findInterval(x$datetime, lut)
x
y <- aggregate(vmax ~ interval, data = x,
FUN = function(x){
if (length(x) < 3){
r <- NA
} else {
r <- mean(x)
}
r
})
y
On Sun, Dec 6, 2020 at 1:59 PM Stefano Sofia
<stefano.sofia at regione.marche.it> wrote:>
> Hi Jim.
> I studied and implemented your solution in details. The idea is great, but
after a sharp revision I came to the conclusion that unfortunately it des not
work correctly: for the "am" side (10, 20, 30 minutes) it works well
because the hour is exactly the same, while for the "pm" side (40, 50,
00) the algorithm it doesn't because the hour related to 40 and 50 minutes
is different from the hour related to 00 (which is the following one). Am I
wrong?
> I tried to fix it keeping the easy structure of the algorithm, but with no
success.
>
> Any hint for that?
> Thank you for your attention and your help
>
> Stefano
>
>
> (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Civil Protection - Marche Region
> Meteo Section
> Snow Section
> Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: stefano.sofia at regione.marche.it
> ---Oo---------oO----------------
>
> ________________________________________
> Da: Jim Lemon [drjimlemon at gmail.com]
> Inviato: gioved? 3 dicembre 2020 4.41
> A: Stefano Sofia
> Cc: r-help mailing list
> Oggetto: Re: [R] change frequency of wind data correctly
>
> Hi again,
> Didn't realize that the example didn't even span a full day.
>
> ssdf<-read.table(text="date_POSIX time_POSIX vmax
> 2018-02-01 00:00:00 27
> 2018-02-01 00:10:00 41
> 2018-02-01 00:20:00 46
> 2018-02-01 00:30:00 39
> 2018-02-01 00:40:00 34
> 2018-02-01 00:50:00 32
> 2018-02-01 01:00:00 37
> 2018-02-01 01:10:00 31
> 2018-02-01 01:20:00 26
> 2018-02-01 01:30:00 29
> 2018-02-01 01:40:00 24
> 2018-02-01 01:50:00 35",
> header=TRUE,stringsAsFactors=FALSE)
> # extract the hour
> ssdf$hour<-
>
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",1)))
> # get the time of day as seconds from the time field
> ssdf$mins<-
>
as.numeric(unlist(lapply(strsplit(ssdf$time_POSIX,":"),"[",2)))
> # create an AM/PM variable
> ssdf$ampm<-ifelse(ssdf$mins > 0 & ssdf$mins <=
30,"am","pm")
> # drop first row
> ssdf<-ssdf[-1,]
> means<-aggregate(vmax~hour+ampm,ssdf,mean)
>
> This does a full day. To do more, add the date_POSIX field to the
> aggregate command. If you have the date and time in one field you'll
> have to split that. That will distinguish the AM/PM means in each day
> as well as hour.
>
> Jim
>
> On Thu, Dec 3, 2020 at 2:10 PM Jim Lemon <drjimlemon at gmail.com>
wrote:
> >
> > Hi Stefano,
> > I read in your date-time as two separate fields for convenience. You
> > can split your single field at the space to get the same result.
> >
> > ssdf<-read.table(text="date_POSIX time_POSIX vmax
> > 2018-02-01 00:00:00 27
> > 2018-02-01 00:10:00 41
> > 2018-02-01 00:20:00 46
> > 2018-02-01 00:30:00 39
> > 2018-02-01 00:40:00 34
> > 2018-02-01 00:50:00 32",
> > header=TRUE,stringsAsFactors=FALSE)
> > # get the time of day as seconds from the time field
> >
ssdf$seconds<-as.numeric(strptime(ssdf$time_POSIX,"%H:%M:%S"))
> > # subtract whatever current date strptime guesses for the date
> > ssdf$seconds<-ssdf$seconds-min(ssdf$seconds)
> > # create an AM/PM variable
> > ssdf$ampm<-ifelse(ssdf$seconds > 0 & ssdf$seconds <=
1800,"am","pm")
> > means<-aggregate(vmax~ampm,ssdf,mean)
> >
> > Jim
> >
> > On Thu, Dec 3, 2020 at 4:55 AM 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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Bigelow Laboratory for Ocean Science
East Boothbay, Maine
http://www.bigelow.org/
https://eco.bigelow.org