[R] How to preserve date format while aggregating

[Prof Brian Ripley]

Those are not dates!  They are date-times.

aggregate is overkill for a single column.  Something simple like

DT <- seq(Sys.time(), by="4 hours", len=24)
grp <- rbinom(24, 1, p=0.5)
res <- tapply(DT, grp, min)
class(res) <- class(DT)
res

would suffice.

On Mon, 8 Sep 2008, Erich Studerus wrote:

> Here's how the dates look like after the sql-query:
>
> Oav$Date[1:3]
> [1] "1991-11-22 00:45:00 CET" "1991-12-13 00:01:00 CET" "1992-02-06 00:45:00
> CET"
>
>> class(oav$Date[1:3])
> [1] "POSIXt"  "POSIXct"
>
>> x<-as.numeric(oav$Date[1:3])
>> x
> [1] 690767100 692578860 697333500
>
>> class(x)<-"Date"
>> x
> [1] "3226-01-31" "8186-07-07" "1204-04-11"
>
> I wanteded to apply the aggregate function in R instead of in the SQL-query,
> because R is much more flexible and faster in manipulating large dataframes.
>
> Erich
>
>
>
> -----Ursprüngliche Nachricht-----
> Von: Dr Eberhard Lisse [mailto:el at lisse.NA]
> Gesendet: Montag, 8. September 2008 15:43
> An: Erich Studerus
> Cc: r-help at r-project.org
> Betreff: Re: [R] How to preserve date format while aggregating
>
> Erich,
>
> how does the data look, when it comes from SQL?
>
> And why not extract the data with SQL directly, so you don't
> have this issue in the first place?
>
> el
>
> on 9/8/08 3:15 PM Erich Studerus said the following:
>> Thanks, I've already tried that. The problem is, that the original date is
>> not restored when I change the numeric back to date. I get a totally
>> different date.
>> Maybe it has something to do with the original date format. My data are
>> directly imported from a SQL-database. The date column to which I want to
>> apply the aggregate function has the two classes POSIXt and POSIXct.
>> Changing the column to class "Date" before applying the aggregate function
>> did not help. I still get a different date, when I transform it back to
>> class "Date".
>> I would be glad, if someone knew a more elegant way to extract the rows
> with
>> minimum/earliest date per subject.
>>
>>
>> Erich
>>
>>
>> -----Ursprüngliche Nachricht-----
>> Von: jim holtman [mailto:jholtman at gmail.com]
>> Gesendet: Montag, 8. September 2008 14:24
>> An: Erich Studerus
>> Cc: r-help at r-project.org
>> Betreff: Re: [R] How to preserve date format while aggregating
>>
>> Try changing the 'class' of the numeric result back to Date:
>>
>>> x <- as.Date('2008-09-08')
>>> x
>> [1] "2008-09-08"
>>> y <- as.numeric(x)
>>> y
>> [1] 14130
>>> str(y)
>>  num 14130
>>> class(y) <- "Date"
>>> y
>> [1] "2008-09-08"
>>> str(y)
>> Class 'Date'  num 14130
>>
>>
>> On Mon, Sep 8, 2008 at 6:38 AM, Erich Studerus
>> <erich.studerus at bli.uzh.ch> wrote:
>>> Hi
>>>
>>> I have a dataframe in which some subjects appear in more than one row. I
>>> want to extract the subject-rows which have the minimum date per subject.
>> I
>>> tried the following aggregate function.
>>>
>>> attach(dataframe.xy)
>>>
>>> aggregate(Date,list(SubjectID),min)
>>>
>>> Unfortunately, the format of the Date-column changes to numeric, when I'm
>>> applying this function. How can I preserve the date format?
>>>
>>> Thanks
>>>
>>> Erich
>>>
>>> ______________________________________________
>>> R-help at r-project.org mailing list
>>> 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.
>>>
>>
>>
>>
>
> -- 
> Dr. Eberhard W. Lisse  \        / Obstetrician & Gynaecologist (Saar)
> el at lisse.NA el108-ARIN / *     |   Telephone: +264 81 124 6733 (cell)
> PO Box 8421             \     /   Please do NOT email to this address
> Bachbrecht, Namibia     ;____/        if it is DNS related in ANY way
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
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