David,
Using the ?count.fields revealed that I only have 2410 columns. That fixed
the problem I had. I used, data_tmp[,842:2410] and that gave me the solution
I was looking for. This, ironically, also solved the other problem I had.
As for:
>
> You also say file.remove( fileout) , then you try
On Sep 14, 2008, at 5:39 PM, Adam D. I. Kramer wrote:
Hi Jason,
data[] is a data frame, remember--you need to specify rows AND
columns. So,
data[,c(2,12,17)] is what you should be doing in the first place, and
data[,842:2411] in the second place.
Actually, the construction df[c(2,12,17)]
On Sep 14, 2008, at 4:40 PM, Jason Thibodeau wrote:
> I cannot provide (all) the sample data (NDA) but here is the entire
> function:
> TEST_filter <- function(filein,fileout)
>
> {
> file.remove(fileout)
> nskip<-0
> while(1)
> {
>
Hi Jason,
data[] is a data frame, remember--you need to specify rows AND columns. So,
data[,c(2,12,17)] is what you should be doing in the first place, and
data[,842:2411] in the second place.
Not sure if the help you needed was using the comma, or the : syntax, or if
you're trying to read only
On Sep 14, 2008, at 4:01 PM, Jason Thibodeau wrote:
TEST_filter("line50grab.csv","line50grab_filterout.csv")
Error in `[.data.frame`(data_tmp, seq(842, 2411)) :
undefined columns selected
I am guessing that you wrapped some code into a function but you did
not provide the function. You ar
TEST_filter("line50grab.csv","line50grab_filterout.csv")
Error in `[.data.frame`(data_tmp, seq(842, 2411)) :
undefined columns selected
I know my file has about 3000 columns.
This happened when I used:
data_tmp <- read.csv(filein, header=TRUE, nrows=10, skip=nskip)
data
Jim, this is a GREAT help. I was trying something similar before, but I was
unable to detect EOF. Thanks for the help!
Also, David, your suggestion worked perfectly.
Thanks for all the help, everyone!
On Sun, Sep 14, 2008 at 2:08 PM, jim holtman <[EMAIL PROTECTED]> wrote:
> Have you tried:
>
>
Have you tried:
data_filter <- data[842:2411]
Also if you have a lot of data to read, I would suggest that you use a
connection, and it all the data is numeric, possibly 'scan'. If you
do use a connection, this would eliminate having to 'skip' each time
which could be time consuming on a large f
On Sep 14, 2008, at 12:22 PM, Jason Thibodeau wrote:
Hello,
I realize that using: x[x > 3 & x < 5] I can fetch all elements
between 3
and 5. However I read in from a CSV file, and I would like to fetch
all
columns from within a range ( 842-2411). In teh past, I have done
this to
fetch j
Hello,
I realize that using: x[x > 3 & x < 5] I can fetch all elements between 3
and 5. However I read in from a CSV file, and I would like to fetch all
columns from within a range ( 842-2411). In teh past, I have done this to
fetch just select few columns:
data <- read.csv(filein, header=TRUE, n
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