On May 26, 2011, at 5:15 PM, Struckmeier, Nathanael wrote:
Hello,
I've been banging my head against my monitor for some time now
trying to
import data into R. The problem is either in my use of syntax, my data
format, or my memory. I have described what I have tried below. Please
help.
=========My GOAL==============================
import a 4 column, 8,000 row table into R including headers.
=========WHAT I'VE ATTEMPTED==================
Original data was in Excel format.
Converted data to both a .txt and .csv (to see which worked better)
Imported data into R via commands as object "demand" (see below)
Please excuse the long file path.
demand=read.delim("C:\\Documents and Settings\\E066582\\My
Documents\\R\\R-2.13.0\\bin\\demand.txt", header=T)
demand=read.csv(("C:\\Documents and Settings\\E066582\\My
Documents\\R\\R-2.13.0\\bin\\demand.csv")
==========PROBLEMS==============================
In both cases, about half to three fourths of my data shows up as
object "demand" with about 4000 lines. My headers also fail to appear.
When my data is imported into R and I type the object name to bring it
up I receive a memory usage error.
==========SOLUTIONS============================
I've gone in and cleaned up my data, making sure there are no (') or
(#)
but it could still a formatting issue
My computer has 1.9GB RAM. I have looked but I can't figure out how
to
increase R memory usage.
Any ideas would be appreciated. If someone needs more information to
help me I'll supply it.
The "information" needed to address this is a public path to a place
where one of those files resides.
The problem is almost certainly not related to memory size. That is a
tiny file. You could also cut and paste the first 20 lines into a
message. Maybe there is something in the contents of the header that
is the problem.
--
David Winsemius, MD
West Hartford, CT
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