csv file with multiple time-series

Question

Hi

I've imported a csv file with lots of columns and sections of data.

v <- read.csv2("200109.csv", header=TRUE, sep=",", skip="6", na.strings=c(""))

The layout of the file is something like this:

Dataset1
time, data, .....
0       0
0       <NA>
0       0

Dataset2
time, data, .....
00:00   0
0       <NA>
0       0

(The headers of the different datasets is exactly the same.

Now, I can plot the first dataset with:

plot(as.numeric(as.character(v$Calls.served.by.agent[1:30])), type="l")

I am curious if there is a better way to:

1. Get all the numbers read as numbers, without having to convert.

2. Address the different datasets in the file, in some meaningfull way.

Any hints would be appreciated. Thank you.

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Status update:

I haven't really found a good solution yet in R, but I've started writing a script in Lua to seperate each individual time-series into a seperate file. I'm leaving this open for now, because I'm curious how well R will deal with all these files. I'll get 8 files per day.