[R] Subsetting data by date

[Williams, Robin]

And following on from my original question: 
In another file I have the dates in numeric format, (ddmmyy). How could
I extract the data between 01/05/97 and 30/09/97, etc? Do I need to
implement some sort of loop? 


Robin Williams 
Met Office summer intern - Health Forecasting 
robin.williams at metoffice.gov.uk 
-----Original Message-----
From: Gabor Grothendieck [mailto:ggrothendieck at gmail.com] 
Sent: Monday, July 21, 2008 3:26 PM
To: Williams, Robin
Cc: R-help at r-project.org
Subject: Re: [R] Subsetting data by date

Continuing on, to just get points from May to Sep

mo <- as.numeric(format(time(z), "%m"))
z.summer <- z[mo >= 5 & mo <= 9]

If in your case z is multivariate rather than univariate (as it is in
our example) then it would be:
z.summer <- z[mo >= 5 & mo <= 9, ]

On Mon, Jul 21, 2008 at 9:55 AM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
> Try this:
>
> Lines <- "Date,Temp
> 1-Apr-1997,50
> 3-Sept-2001,60"
>
> library(zoo)
>
> # function to reduce 4 char mos to 3 char convert.date <- function(x, 
> format) as.Date(sub("(-...).-", "\\1-", x), format)
>
> # z <- read.zoo("myfile.csv", header = TRUE, sep = ",", FUN = 
> convert.date, format = "%d-%b-%Y") z <- 
> read.zoo(textConnection(Lines), header = TRUE, sep = ",", FUN = 
> convert.date, format = "%d-%b-%Y")
>
> plot(z)
>
> If the dates are actually three letters, i.e. Sep and not Sept, then 
> you could eliminate convert.date and simplify the read.zoo line to:
>
> z <- read.zoo(textConnection(Lines), header = TRUE, sep = ",", format 
> = "%d-%b-%Y")
>
> See the zoo package documentation and its three vignettes as well as 
> ?read.zoo ?strptime and ?plot.zoo and also look at the dates article
in R News 4/1.
>
>
> On Mon, Jul 21, 2008 at 9:31 AM, Williams, Robin 
> <robin.williams at metoffice.gov.uk> wrote:
>> Hi all,
>>  Firstly I appologise if this question has been answered previously, 
>> however searching of the archives and the internet generally has not 
>> yielded any results.
>>
>>  I am looking in to the effects of summer weather conditions 
>> (temperature, humidity etc), on the incidences of a breathing 
>> disorder brought on through smoking (COPD). I am fairly new to R and 
>> completely new to the idea of writing R scripts, subsetting 
>> dataframes etc. I am working on a 12 week summer placement at the Met

>> Office, UK, having just finished my second year of a mathematics
course at university.
>>
>>  Basically I have data between January 1 1997 and December 31 2007.
>> However as I am only interest in the summer months (which I have 
>> defined to be between May 1 and September 30), I would like to 
>> extract the relevant data in R in a timely manner. Obviously I could 
>> go and open my csv files in excel, cut and paste the relevant data, 
>> etc, however I would like to maximise R's potential as I feel it will

>> stand me in better stead in the long run.
>>  Currently the dates are in the form
>> 1-Apr-1997,
>> 3-Sept-2001,
>> etc.
>>  I will create a data.frame with date as one of the variables, the 
>> others being (initially) temperature, humidity, and Admissions (the 
>> number of hospital admissions for COPD exaserbations).
>>  Please could somebody tell me if there is a simple way to extract 
>> the data I want, and if so perhaps a sample command to get me going? 
>> Do I first need to format the dates to some numeric-only format? As I

>> say, I could use Excel to create the files in the right format, but I

>> will be dealing with a lot more variables in the future (perhaps up 
>> to 8) and so this will become a pain-staking process.
>>
>>  Please reply either on or off list.
>>
>> Many thanks for any help.
>> Robin Williams
>> Met Office summer intern - Health Forecasting 
>> robin.williams at metoffice.gov.uk
>>
>>
>>        [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> 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.
>>
>