[R] More on scan()
apjaworski@mmm.com
apjaworski at mmm.com
Thu Dec 19 23:25:03 CET 2002
Here is one way of doing this.
(1) read the whole file in as a vector of strings one line at a time
x <- readLines("<path to your data file>")
(2) find the position of the "@DATA" string in your vector
s <- which(x == "@DATA")
(3) scan the file again skipping s lines
scan("<path to your data file>", skip=s, sep=",", ...)
You may want to consider using read.table instead of scan - it has the skip
parameter too. Finally you could actually reuse x from (1) above by
something like
x <- x[-(1:s])
loop through elements of x and use the strsplit command to extract
numbers from each line
I suspect that this would be more cumbersome and slower than re-reading the
file skiiping s lines from the top.
Cheers,
Andy
__________________________________
Andy Jaworski
Engineering Systems Technology Center
3M Center, 518-1-01
St. Paul, MN 55144-1000
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|---------+------------------------------>
| | Ko-Kang Kevin Wang |
| | <kwan022 at stat.auckl|
| | and.ac.nz> |
| | Sent by: |
| | r-help-admin at stat.m|
| | ath.ethz.ch |
| | |
| | |
| | 12/20/2002 04:08 |
| | |
|---------+------------------------------>
>-----------------------------------------------------------------------------------------------------------------------------|
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| To: R Help <r-help at stat.math.ethz.ch> |
| cc: |
| Subject: [R] More on scan() |
>-----------------------------------------------------------------------------------------------------------------------------|
Hi,
If I have a CSV file which has several comments at the top, and the data
start immediately after the line:
@DATA
Is it possible to use the scan() command to get the CSV data into R, by
only reading the lines after @DATA? If so, how can I do it?
Cheers,
Kevin
------------------------------------------------------------------------------
/* Time is the greatest teacher, unfortunately it kills its students */
Ko-Kang Kevin Wang
Master of Science (MSc) Student
Department of Statistics
University of Auckland
New Zealand
Homepage: http://www.stat.auckland.ac.nz/~kwan022
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