Using your data:
test_data <- data.frame(
var0 = 100 + c(0, cumsum(runif(49, -20, 20))),
var1 = 150 + c(0, cumsum(runif(49, -10, 10))),
Dates = seq.Date(as.Date("2002-01-01"), by="1 month", length.out=100))
I create a stacked version which is what ggplot()
would like to work with:
stacked <- with(test_data,
data.frame(value = c(var0, var1),
variable = factor(rep(c("Var0","Var1"),
each = NROW(test_data))),
Dates = rep(Dates, 2)))
In this case producing stacked
was quite easy as we only had to do a couple of manipulations, but reshape()
and the reshape
and reshape2
might be useful if you have a more complex real data set to manipulate.
Once the data are in this stacked form, it only requires a simple ggplot()
call to produce the plot you wanted with all the extras (one reason why higher-level plotting packages like lattice
and ggplot2
are so useful):
require(ggplot2)
p <- ggplot(stacked, aes(Dates, value, colour = variable))
p + geom_line()
I'll leave it to you to tidy up the axis labels, legend title etc.
HTH