[R] plotting time series using ggplots

[ONKELINX, Thierry]

Dear Alison,

Creating a dataset in long format instead of wide format makes things
much easier with ggplot2. You also need a variable with Year. Rownames
will not do.

rwl <- matrix(rnorm(800, 1, sd =0.5), nrow = 100)
colnames(rwl) <- paste('V', 1:8, sep = '')
rwl <- as.data.frame(rwl)
rwl$Year <- 1900:1999

library(ggplot2)
molten <- melt(rwl, id.vars = "Year")
ggplot(molten, aes(x = Year, y = value)) + geom_smooth()

moltenCI <- cast(Year ~ ., data = molten, fun = c(mean, sd, length))
moltenCI$Low <- with(moltenCI, mean - sd / sqrt(length - 1))
moltenCI$High <- with(moltenCI, mean + sd / sqrt(length - 1))

ggplot(moltenCI, aes(x = Year, y = mean, ymin = Low, ymax = High)) +
geom_ribbon(alpha = 0.5) + geom_line()


ggplot(molten, aes(x = Year, y = value, colour = variable)) +
geom_line()
ggplot(molten, aes(x = Year, y = value, colour = variable)) +
geom_smooth()


HTH,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen
Belgium

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium

tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be
www.inbo.be

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than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey
  

> -----Oorspronkelijk bericht-----
> Van: r-help-bounces op r-project.org 
> [mailto:r-help-bounces op r-project.org] Namens Alison Macalady
> Verzonden: donderdag 16 september 2010 8:51
> Aan: r-help op r-project.org
> Onderwerp: [R] plotting time series using ggplots
> 
> Hi,
> I would like to plot a bunch of tree ring width data (time 
> series) using ggplots, but I'm having trouble figuring out 
> how to do it.
> 
> My data is in a data.frame, with years as rownames and a 
> distinct tree ring series in each column. So, something like this:
> 
> rwl<-matrix(rnorm(800), nrow = 100)
> colnames(rwl) <- paste('V', 1:8, sep = '')
> rownames(rwl)<-c(1900:1999)
> rwl<-as.data.frame(rwl))
> 
> I have 2 specific things I'd like to do:
> 1) use stat_summary(), geom_line(), and either geom_smooth() or
> geom_ribbon() to plot the mean of the timeseries  (e.g. 
> V1:V8) and error bands or confidence limits around the mean 
> for each year. I cannot figure out how to do this except for 
> this really clunky way:
> 
> rwl$year<-as.numeric(rownames(rwl))
> h<-ggplot(rwl, aes(x=year))
> h+ geom_line(aes(y=V1))  #plots one of the timeseries
> ymax=as.data.frame( t(apply(rwl[1:8], 1, summary,na.rm=TRUE
> )) )[,4] ymin=as.data.frame( t(apply(rwl[1:8], 1, 
> summary,na.rm=TRUE )) )[,2] h + geom_ribbon(aes(ymin=ymin, 
> ymax=ymax)) 
> +geom_line(aes(y=rowMeans(rwl[1:8])))
> 
> 2) I'd like to be able to plot all of the timeseries 
> together, or plot them grouped by another variable (for 
> example site), but I can't figure out how to get ggplot to 
> plot all of the columns as Y data, without specifying each 
> separate timeseries with a distinct  
> +geom_line(aes(y="columnname").
> 
> Any suggestions on either problem would be greatly appreciated!
> 
> ~Ali
> --------------------
> Alison Macalady
> Ph.D. Candidate
> University of Arizona
> School of Geography and Development
> & Laboratory of Tree Ring Research
> 
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> 

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