Thank you for solving my problem, it worked out beautifully.
This was exactly what I was looking for, the ggplot2 package keeps
impressing me.
Thanks,
Eric
On Wed, Dec 7, 2011 at 6:01 AM, Hadley Wickham <had...@rice.edu> wrote:
> On Wed, Dec 7, 2011 at 4:02 AM, Eric Fail <eric.f...@gmx.us> wrote:
>> Dear list,
>>
>> I have been struggling with this for some time now, and for the last hour I
>> have been struggling to make a working example for the list. I hope someone
>> out there have some experience with plotting longitudinal data that they
>> will share.
>>
>> My data is some patient data with three different time stamps. First the
>> patients are identified at different times (first time stamp). Second, they
>> go through an assessment phase and begin their treatment (time stamp 2).
>> Finally they are admitted from the hospital at some point (time stamp 3),
>>
>> I would like to make a spaghetti plot with the assessment phase in one color
>> and the treatment phase in another color.
>>
>> I used ggplot2, and with this example data and only two time points; it
>> works fine (I call it my working example),
>>
>> library(ggplot2)
>> df <- data.frame(
>> date = seq(Sys.Date(), len=104, by="1 day")[sample(104, 52)],
>> patient = factor(rep(1:26, 2), labels = LETTERS)
>> )
>> df <- df[order(df$date), ]
>> dt <- qplot(date, patient, data=df, geom="line")
>> dt + scale_x_date()
>> df[ which(df$patient=='E'), c("patient", "date")]
>>
>> But, if I have three time points, R, for some reason I do not yet
>> understand, add the two second time points in some funny way.
>>
>> Finally, when that is solved; how do I colorize the different parts of the
>> line so the assessment phase gets one color and the treatment phase another?
>>
>> I want to be able to show how long we have been in contact with our
>> patients, how much of the contact time that was assessment and how much that
>> was actual treatment.
>>
>> Below is an example (I call it the not-working example)
>>
>> df2 <- data.frame(
>> date2 = seq(Sys.Date(), len= 156, by="2 day")[sample(156, 78)],
>> patient2 = factor(rep(1:26, 3), labels = LETTERS)
>> )
>>
>> df2 <- df2[order(df2$date2), ]
>> dt2 <- qplot(date2, patient2, data=df2, geom="line")
>> dt2 + scale_x_date(major="months", minor="weeks")
>> df2[ which(df2$patient2=='B'), c("patient2", "date2")]
>
> Did you mean something like this?
>
> library(ggplot2)
> library(plyr)
>
> df2 <- data.frame(
> date2 = seq(Sys.Date(), len= 156, by="2 day")[sample(156, 78)],
> patient2 = factor(rep(1:26, 3), labels = LETTERS)
> )
>
> df2 <- ddply(df2, "patient2", mutate, visit = order(date2))
>
> qplot(date2, patient2, data = df2, geom = "line") +
> geom_point(aes(colour = factor(visit)))
>
> # or this?
>
> library(ggplot2)
> library(plyr)
>
> df2 <- data.frame(
> date2 = seq(Sys.Date(), len= 156, by="2 day")[sample(156, 78)],
> patient2 = factor(rep(1:26, 3), labels = LETTERS)
> )
>
> df2 <- ddply(df2, "patient2", mutate, visit = order(date2))
>
> qplot(date2, patient2, data = df2, geom = "line", colour =
> factor(visit), group = patient2)
>
> # Obviously the lines are drawn between the observations so you only
> see the first two visits.
>
> Hadley
>
> --
> Assistant Professor / Dobelman Family Junior Chair
> Department of Statistics / Rice University
> http://had.co.nz/
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