R help - Jun 2010 - Transforming simulation data which is spread across many files into a barplot

I'm an R newbie, and I'm just trying to use some of it's graphing
capabilities, but I'm a bit stuck - basically in massaging the already
available data into a format R likes.

I have a simulation environment which produces logs, which represent a
number of different things.  I then run a python script on this data, and
putting it in a nicer format.  Essentially, the python script reduces the
number of files by two orders of magnitude.

What I'm left with, is a number of files, which each have two columns of
data in them.
The files look something like this:
--1000.log--
Sent Received
405.0 3832.0
176.0 1742.0
176.0 1766.0
176.0 1240.0
356.0 3396.0
...

This file - called 1000.log - represents a data point at 1000. What I'd like
to do is to use a loop, to read in 50 or so of these files, and then produce
a stacked barplot.  Ideally, the stacked barplot would have 1 bar per file,
and two stacks per bar.  The first stack would be the mean of the sent, and
the second would be the mean of the received.

I've used a loop to read files in R before, something like this ---

for (i in 1:50){
    tmpFile <- paste(base, i*100, ".log", sep="")
    tmp <- read.table(tmpFile)
}

--- But I really don't know how to handle massaging this data into the
matrix I need.

I hope this makes sense, I find it a little hard to describe.

Can anyone give me some help jumping into this one?

Thanks

-- 
Ian Bentley
M.Sc. Candidate
Queen's University
Kingston, Ontario

	[[alternative HTML version deleted]]

On Fri, Jun 11, 2010 at 1:32 PM, Ian Bentley <ian.bentley at gmail.com>
wrote:
> I'm an R newbie, and I'm just trying to use some of it's
graphing
> capabilities, but I'm a bit stuck - basically in massaging the already
> available data into a format R likes.
>
> I have a simulation environment which produces logs, which represent a
> number of different things. ?I then run a python script on this data, and
> putting it in a nicer format. ?Essentially, the python script reduces the
> number of files by two orders of magnitude.
>
> What I'm left with, is a number of files, which each have two columns
of
> data in them.
> The files look something like this:
> --1000.log--
> Sent Received
> 405.0 3832.0
> 176.0 1742.0
> 176.0 1766.0
> 176.0 1240.0
> 356.0 3396.0
> ...
>
> This file - called 1000.log - represents a data point at 1000. What I'd
like
> to do is to use a loop, to read in 50 or so of these files, and then
produce
> a stacked barplot. ?Ideally, the stacked barplot would have 1 bar per file,
> and two stacks per bar. ?The first stack would be the mean of the sent, and
> the second would be the mean of the received.
>
> I've used a loop to read files in R before, something like this ---
>
> for (i in 1:50){
> ? ?tmpFile <- paste(base, i*100, ".log", sep="")
> ? ?tmp <- read.table(tmpFile)
> }
>
# Load data
library(plyr)

paths <- dir(base, pattern = "\\.log", full = TRUE)
names(paths) <- basename(paths)

df <- ddply(paths, read.table)

# Compute averages:
avg <- ddply(df, ".id", summarise,
  sent = mean(sent),
  received = mean(received)

You can read more about plyr at http://had.co.nz/plyr.

Hadley

-- 
Assistant Professor / Dobelman Family Junior Chair
Department of Statistics / Rice University
http://had.co.nz/

Try this:

base <- "file" # replace as appropriate
N <- 50
filenames <- paste(base, seq_len(N)*100, ".log", sep =
"")
mat <- sapply(filenames, function(fn)
	colMeans(read.table(fn, col.names = c("Sent", "Received")))
)
barplot(mat)


On Fri, Jun 11, 2010 at 2:32 PM, Ian Bentley <ian.bentley at gmail.com>
wrote:
> I'm an R newbie, and I'm just trying to use some of it's
graphing
> capabilities, but I'm a bit stuck - basically in massaging the already
> available data into a format R likes.
>
> I have a simulation environment which produces logs, which represent a
> number of different things. ?I then run a python script on this data, and
> putting it in a nicer format. ?Essentially, the python script reduces the
> number of files by two orders of magnitude.
>
> What I'm left with, is a number of files, which each have two columns
of
> data in them.
> The files look something like this:
> --1000.log--
> Sent Received
> 405.0 3832.0
> 176.0 1742.0
> 176.0 1766.0
> 176.0 1240.0
> 356.0 3396.0
> ...
>
> This file - called 1000.log - represents a data point at 1000. What I'd
like
> to do is to use a loop, to read in 50 or so of these files, and then
produce
> a stacked barplot. ?Ideally, the stacked barplot would have 1 bar per file,
> and two stacks per bar. ?The first stack would be the mean of the sent, and
> the second would be the mean of the received.
>
> I've used a loop to read files in R before, something like this ---
>
> for (i in 1:50){
> ? ?tmpFile <- paste(base, i*100, ".log", sep="")
> ? ?tmp <- read.table(tmpFile)
> }
>
> --- But I really don't know how to handle massaging this data into the
> matrix I need.
>
> I hope this makes sense, I find it a little hard to describe.
>
> Can anyone give me some help jumping into this one?
>
> Thanks
>
> --
> Ian Bentley
> M.Sc. Candidate
> Queen's University
> Kingston, Ontario
>
> ? ? ? ?[[alternative HTML version deleted]]
>
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