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Jeff

2012-Jul-23 15:21 UTC

[R] Creating panel data

I'm new to R.
   I am trying to create panel data with a slight alteration from a typical
   dataset.
   At  present,  I  have  data  on a few hundred people with the dates of
   occurrences for several events (like marriage and employment). The dates are
   in year/quarter format, so 68.0 equals the 1st quarter of 1968 and 68.25
   equals the 2nd quarter of 1968. If the event never occurred, 0 is recorded
   for the Year Of Occurrence. Somewhat redundantly, I also have separate
   dichotomous  variables indicating whether the event ever occurred (0/1
   format).
   For example:
   x <- data.frame( id = c(1,2), Event1Occur = c(1,0), YearOfOccurEvent1   
c(68.25,0), Event2Occur = c(0,1), YearOfOccurEvent2 = c(0,68.5))
   I need to transform that dataframe so that I have a separate row for each
   time period (year/quarter) for each person, with variables for whether the
   event had already occurred during that time period. If the event occurred
   during an earlier time, it is presumed to still be occurring at later times.
   E.g., if the person got married in the first quarter of 1968, they are
   presumed to still be married at all later time periods. I need those time
   periods marked (0/1).
   For example:
   y   <-   data.frame(   id   =   c(   rep  (1,5),  rep  (2,5)),  Year=c
   (68.0,68.25,68.50,68.75,69.0))
   y $ Event1 <- c (0,1,1,1,1,0,0,0,0,0)
   y $ Event2 <- c (0,0,0,0,0,0,0,1,1,1)
   can someone get me started.
   Thanks
   Jeff

Bert Gunter

2012-Jul-23 15:38 UTC

head link

[R] Creating panel data

Sounds like you would find it worthwhile to read a good Intro R
tutorial  -- like the one that comes shipped with R. Have you done so?
If not, why not? If so, how about the data import/export manual?

I certainly wouldn't guarantee that these will answer all your
questions. They're just places to start BEFORE posting here. Setting
up proper data structures can be tricky (have you considered what form
the functions/packages with which you are going to analyze the data
want?). You might also find it useful to use Hadley Wickham's plyr
and/or reshape2 packages, whose aim is to standardize and simplify
data manipulation tasks. Vignettes/tutorials are available for both.

Cheers,
Bert

On Mon, Jul 23, 2012 at 8:21 AM, Jeff <r at jp.pair.com>
wrote:>
>    I'm new to R.
>    I am trying to create panel data with a slight alteration from a typical
>    dataset.
>    At  present,  I  have  data  on a few hundred people with the dates of
>    occurrences for several events (like marriage and employment). The dates
are
>    in year/quarter format, so 68.0 equals the 1st quarter of 1968 and 68.25
>    equals the 2nd quarter of 1968. If the event never occurred, 0 is
recorded
>    for the Year Of Occurrence. Somewhat redundantly, I also have separate
>    dichotomous  variables indicating whether the event ever occurred (0/1
>    format).
>    For example:
>    x <- data.frame( id = c(1,2), Event1Occur = c(1,0), YearOfOccurEvent1
>    c(68.25,0), Event2Occur = c(0,1), YearOfOccurEvent2 = c(0,68.5))
>    I need to transform that dataframe so that I have a separate row for
each
>    time period (year/quarter) for each person, with variables for whether
the
>    event had already occurred during that time period. If the event
occurred
>    during an earlier time, it is presumed to still be occurring at later
times.
>    E.g., if the person got married in the first quarter of 1968, they are
>    presumed to still be married at all later time periods. I need those
time
>    periods marked (0/1).
>    For example:
>    y   <-   data.frame(   id   =   c(   rep  (1,5),  rep  (2,5)), 
Year=c
>    (68.0,68.25,68.50,68.75,69.0))
>    y $ Event1 <- c (0,1,1,1,1,0,0,0,0,0)
>    y $ Event2 <- c (0,0,0,0,0,0,0,1,1,1)
>    can someone get me started.
>    Thanks
>    Jeff
> ______________________________________________
> 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.


-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

John Kane

2012-Jul-23 17:06 UTC

head link

[R] Creating panel data

This looks really ugly but it 'may' do what you want.  I was too lazy to
generate enough raw data to check.  Note i changed the names in x as they were a
bit clumsy.



 x <- data.frame( id = c(1,2), Event1= c(1,0), YEvent1    c(68.25,0), Event2
= c(0,1), YEvent2 = c(0,68.5))

y   <-   data.frame(   id   =   c(   rep  (1,5),  rep  (2,5)),  Year=c
   (68.0,68.25,68.50,68.75,69.0))
   y $ Event1 <- c (0,1,1,1,1,0,0,0,0,0)
   y $ Event2 <- c (0,0,0,0,0,0,0,1,1,1)


 x <- data.frame( id = c(1,2), Event1= c(1,0), YEvent1    c(68.25,0), Event2
= c(0,1), YEvent2 = c(0,68.5))

dd  <-  melt(x, id= c("id", "Event1",
"Event2"),
          value.name="year.quarter" )
dd1  <-  subset(dd, dd[, 5] != 0 )

dd1  <-  dd1[ , c(1,2,3,5)]


John Kane
Kingston ON Canada

> -----Original Message-----
> From: r at jp.pair.com
> Sent: Mon, 23 Jul 2012 11:33:37 -0500
> To: gunter.berton at gene.com
> Subject: Re: [R] Creating panel data
> 
> At 10:38 AM 7/23/2012, you wrote:
> >You might also find it useful to use Hadley Wickham's plyr
> >and/or reshape2 packages, whose aim is to standardize and simplify
> >data manipulation tasks.
>> 
> >Cheers,
> >Bert
> 
> 
> I have already used R enough to have correctly imported the actual
> data. After import, it is in the approximate format at the x
> dataframe I previously posted. I already found the plyr and reshape2
> packages and had assumed that the cast (or dcast) options might be
> the correct ones. Melt seemed to get me only what I already have. The
> examples I have seen thus far start with data in a various formats
> and end up in the format that I am starting with. In other words,
> they seem to do the exact opposite of what I'm trying to do. So I'm
> still stuck with how to get started and whether the functions in
> reshape2 are actually the correct ones to consider.
> 
> ...still looking for some help on this.
> 
> Jeff
> 
> ______________________________________________
> 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.
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