Good afternoon Hang,
This is an example of what I've done with a csv file with a header
which is too big to read into memory.
# this is a file with about 50 columns and 28 million records
ap.fnam <- 'p2_all28m_records.csv'
# lets just explore the columns in Addresspoint...
# by reading in the header and the first row
p1 <- read.csv(ap.fnam, nrows=1)
# now which columns do we actually want?
# ok... in this case we only want the NCAT column...
cols.reqd <- grep('NCAT', names(p1))
# so we create a list containing this/these column(s) as a 'character'
# type and all other columns as 'NULL'...
col.classes <- ifelse(seq(ncol(p1)) %in% cols.reqd, 'character', 'NULL')
# this will likely take a little over a minute!
p9 <- read.csv(ap.fnam, colClasses=col.classes )
Hope this helps
Kind regards,
Sean
On 14 February 2011 17:40, Hang PHAN <hangp...@gmail.com> wrote:
> Hi,
> I have a very large data file(GB) from which I only want to extract one
> column to draw histogram. This would be done several times, so I would like
> to ask if there is anyway to plot this using R from the linux command line,
> something look like this
>
> cut -f1 xxx.txt |RplotHist ....
>
> Thanks and hope to hear from you.
> Best regards,
> Hang
>
> [[alternative HTML version deleted]]
>
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