I have data at a number of days since an event. This data is sampled irregularly - my time points are like 0, 5, 6, 10, 104 days. I don't have specific date-time information - i.e. I have no idea when in real life the event I'm studying occurred.
I'd like to plot, using ggplot, my time series. I can use, say
p <- ggplot(data,aes(x=time,y=expression))
p <- p + geom_point()
but of course my x-axis variables are plotted next to each other, so that the distance between t=10 and t=104 is the same as t=5 and t=6. So I can make something up like
start <- ISOdate(2001, 1, 1, tz = "")
data$time <- start + data$time*60*60*12
which almost works, but now the ticks on my x-axis are horribly inaccurate date times. I could re-format them maybe? But can't see anyway to make the format "days from start". And by now I've been googling around for quite a while, with the nagging feeling that I'm missing something seriously obvious. Am I?
Not sure if this is what you're looking for (see this related question). You can reformat the axis and deal with irregularity by using the scale_x functions. For instance:
p <- qplot(1:3, 1:3, geom='line')
p + scale_x_continuous("", breaks=1:3,
labels = as.Date(c("2010-06-03", "2010-06-04", "2010-06-07")))
Incidentally, here's a function that I created for plotting multivariate zoo
objects:
qplot.zoo <- function(x) {
if(!inherits(x, "zoo")) stop("x must be a zoo object")
x.df <- data.frame(dates=index(x), coredata(x))
x.df <- melt(x.df, id="dates", variable="value")
ggplot(x.df, aes(x=dates, y=value, group=value, colour=value)) + geom_line() + opts(legend.position = "none")
}
Sounds like your time
variable is a factor or maybe a character vector, not a numeric value! If you do data$time <- as.numeric(data$time)
it may well solve your problem.
ggplot is pretty good at using the right sort of scale for the right sort of data. (Sadly, data import routines in R generally are less smart...)
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