I'm trying to use qplot() to plot a simple time series as one might do using plot(). The x variable is as.POSIXlt and the y is just some continuous measurement. Here is the code with some brief comments. Any help on why these data.frames behave differently would be very much appreciated. As you can see below, I can work around the problem, but I'm curious as to why is doesn't work as I would expect.
A few details:
platform: OS X 10.6.4
R version: R 2.11.0
Disclaimer: I realize that I could dig into the source code and figure this out myself. I've never used SO and thought that it might be a nice topic for this forum.
Disclaimer (2): I'm new to ggplot2
library(ggplot2)
ws.dat <- read.csv("~/path/to/filename.csv",header=F)
names(ws.dat) <- c("s","t","w")
ws.dat$new.t <- as.POSIXlt(ws.dat$t)
ws.dat[1:5,]
## s t w new.t
## 1 29522 2005-07-02 00:00:00 5.00 2005-07-02 00:00:00
## 2 29522 2005-07-02 00:10:00 5.29 2005-07-02 00:10:00
## 3 29522 2005-07-02 00:20:00 5.48 2005-07-02 00:20:00
## 4 29522 2005-07-02 00:30:00 5.54 2005-07-02 00:30:00
## 5 29522 2005-07-02 00:40:00 5.49 2005-07-02 00:40:00
## the following works
plot(as.POSIXlt(ws.dat$t), ws.dat$w)
## doesn't work
qplot(as.POSIXlt(t), w, data = ws.dat)
## Error in if (length(range) == 1 || diff(range) == 0) { :
## missing value where TRUE/FALSE needed
## doesn't work
ws.dat$new.t <- as.POSIXlt(ws.dat$t)
qplot(new.t, w, data = ws.dat)
## Same error as above
## Note - I could find a more elegant way of doing this; I'm just trying
## to reproduce as fast as possible.
new.df <- data.frame(ws.dat$new.t, ws.dat$w)
new.df[1:5,]
## ws.dat.new.t ws.dat.w
## 1 2005-07-02 00:00:00 5.00
## 2 2005-07-02 00:10:00 5.29
## 3 2005-07-02 00:20:00 5.48
## 4 2005-07-02 00:30:00 5.54
## 5 2005-07-02 00:40:00 5.49
## 'works as *I* would expect'; this is != 'works *as* expected'
qplot(ws.dat.new.t, ws.dat.w, data = new.df)