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

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