They are really good methods. Thank you very much.
Could I ask one more question. Is there obvious difference between these
two methods?
2013/7/4 Prof Brian Ripley <rip...@stats.ox.ac.uk>
> On 04/07/2013 08:04, Dante.py wrote:
>
>> I have a method which is not so smart --use grep to match the pattern.
>> for example:
>> dates <- c("02/27/92", "02/27/92", "01/14/92", "02/28/92", "02/01/91")
>> day <- as.Date(dates, "%m/%d/%y")
>> day:
>> [1] "1992-02-27" "1992-02-27" "1992-01-14" "1992-02-28" "1991-02-01"
>> If I want to search for 1991, I can use:
>> grep("1991-*", day)
>>
>>
>> Hope for a better solution.
>>
>
> Here are 2. The first is quite obvious, the second is faster but needs
> more knowledge.
>
> x <- format(day, "%Y")
> day[x >= "2007" & x <= "2009"]
>
> x <- as.POSIXlt(day)$year + 1900
> day[x >= 2007 & x <= 2009]
>
>
>
>>
>> 2013/7/4 Gallon Li <gallon...@gmail.com>
>>
>> i have converted my data into date format like below:
>>>
>>> day=as.Date(originaldate,"%m/%**d/%Y")
>>>> day[1:5]
>>>>
>>> [1] "2008-04-12" "2011-07-02" "2011-09-02" "2008-04-12" "2008-04-12"
>>>
>>> I wish to select only those observations from 2007 to 2009, how can I
>>> select from this list?
>>>
>>> [[alternative HTML version deleted]]
>>>
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>>>
>>
>>
>>
>>
>> ______________________________**________________
>> R-help@r-project.org mailing list
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>> PLEASE do read the posting guide http://www.R-project.org/**
>> posting-guide.html <http://www.R-project.org/posting-guide.html>
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
> --
> Brian D. Ripley, rip...@stats.ox.ac.uk
> Professor of Applied Statistics,
> http://www.stats.ox.ac.uk/~**ripley/<http://www.stats.ox.ac.uk/~ripley/>
> University of Oxford, Tel: +44 1865 272861 (self)
> 1 South Parks Road, +44 1865 272866 (PA)
> Oxford OX1 3TG, UK Fax: +44 1865 272595
>
--
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