On Jul 6, 2012, at 2:49 PM, C W wrote:
Hey, David
table(count.fields()) is telling me have 11 columns, but I have way
more, more like 30 columns.
> table(count.fields("persistency.csv"))
1 2 3 4 5 6 7 8 9 11
439384 39617 16130 21993 12556 1900 988 713 61 1
I don't usually put back the list address when responding to a private
email, but I'm breaking my rule. You should not send private follow-
ups for threads that start on the list unless there is something that
other readers might not benefit from seeing.
If it is a CSV file then you need to tell count.fields to use commas:
table(count.fields("persistency.csv", sep=","))
--
David.
-M
On Fri, Jul 6, 2012 at 2:36 PM, David Winsemius <dwinsem...@comcast.net
> wrote:
On Jul 6, 2012, at 1:39 PM, C W wrote:
Quick question, what the memory size in R?
I converted to CSV, but only 53300 of the 1,000,000 rows were read
in. Did
R run out of memory? If so, is there a work around?
You probably have mismatched quotes. Consider using quote="". Also
consider doing this:
table(count.fields(file-name)) # with a valid file name
That count.fields function is very useful since it accepts the same
arguments as the read.tables functions, with defaults of:
quote = "\"'", skip = 0, blank.lines.skip = TRUE, comment.char = "#")
--
David.
Thanks,
Mike
On Fri, Jul 6, 2012 at 1:24 PM, Duncan Murdoch <murdoch.dun...@gmail.com
>wrote:
On 06/07/2012 1:11 PM, C W wrote:
Hi all
I have a large SAS data set, how do I get it read in R?
The data is too big (about 400,000 rows by 100 columns) to be saved
as an
Excel file. How should I get it read in R? Any packages? I don't
seem
to
find any.
You could write it out in some plain delimited format, e.g. CSV or
tab-delimited. Watch out for special characters in strings that
confuse R
when it reads it in (e.g. commas in unquoted CSV strings, quotes
within
strings, etc.)
Duncan Murdoch
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David Winsemius, MD
West Hartford, CT
David Winsemius, MD
West Hartford, CT
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