Plotting two dataframes that share only one field between them

R_ggplot_with_vline.R

events <- read.csv("events.csv")

> head(events)
                 timestamp event
1 2013-04-03 22:59:05.061Z     A
2 2013-04-03 22:59:05.061Z     B
3 2013-04-03 22:59:07.109Z     C
4 2013-04-03 22:59:07.115Z     D
5 2013-04-03 22:59:07.209Z     E


performance <- read.csv("performance.csv", header=TRUE,sep=";")
> head(performance)
  hostname interval               timestamp CPU  user nice system iowait steal  idle
1     box1        1 2013-04-03 22:59:02 UTC  -1 10.53    0   2.01   0.50  0.00 86.97
2     box1        1 2013-04-03 22:59:03 UTC  -1  0.25    0   0.00   0.00  0.00 99.75
3     box1        1 2013-04-03 22:59:04 UTC  -1  0.00    0   0.25   0.25  0.00 99.50
4     box1        1 2013-04-03 22:59:05 UTC  -1 10.72    0   1.00   0.25  0.00 88.03
5     box1        1 2013-04-03 22:59:06 UTC  -1 10.67    0  10.67   0.00  0.25 78.41
6     box1        1 2013-04-03 22:59:07 UTC  -1  5.01    0   9.02   3.51  0.00 82.46

performance$timestamp <- as.POSIXlt(perfomance$timestamp)
events$timestamp <- as.POSIXlt(events$timestamp)

> str(performance)
'data.frame':  8 obs. of  10 variables:
 $ hostname : Factor w/ 1 level "box1": 1 1 1 1 1 1 1 1
 $ interval : int  1 1 1 1 1 1 1 1
 $ timestamp: Factor w/ 8 levels "2013-04-03 22:59:02 UTC",..: 1 2 3 4 5 6 7 8
 $ CPU      : int  -1 -1 -1 -1 -1 -1 -1 -1
 $ user     : num  10.53 0.25 0 10.72 10.67 ...
 $ nice     : num  0 0 0 0 0 0 0 0
 $ system   : num  2.01 0 0.25 1 10.67 ...
 $ iowait   : num  0.5 0 0.25 0.25 0 ...
 $ steal    : num  0 0 0 0 0.25 0 0.25 0.5
 $ idle     : num  87 99.8 99.5 88 78.4 ...

# Plot the first dataset. Two line plots sharing the same X axis.
p <- ggplot(data=performance, aes(x=timestamp)) + geom_line(aes(y=idle, colour="% cpu idle")) + geom_line(aes(y=user, colour="% cpu user"))  +  scale_x_datetime(labels = date_format("%H:%M:%S"))

# Plot the vertical lines
p + geom_vline(data=events, linetype=4, aes(colour=factor(event),xintercept=as.numeric(timestamp)) )