Thanks, Juliet.
It works for filtering columns.
I am also wondering if there is a way to filter rows.
Thanks again.
-james
One can use colClasses to set which columns get read in. For the
columns you don't
want you can set those to NULL. For example,
cc - c(NULL,rep(numeric,9))
myData -
I think you can use readLines(n=1) in loop to skip unwanted rows.
On Mon, Jun 1, 2009 at 12:56 AM, g...@ucalgary.ca wrote:
Thanks, Juliet.
It works for filtering columns.
I am also wondering if there is a way to filter rows.
Thanks again.
-james
One can use colClasses to set which columns
The sqldf package can read a subset of rows and columns into R without
reading the entire file into R. There are a few caveats:
- It does not support ftp so you will need to download the file to your
computer first as shown in the example below
- since value is an SQL keyword it turns value
Since there are many rows, using read.table we spent too much on reading
in rows that we do not want. We are wondering if there is a way to read
only rows that we are interested in. Thanks,
-james
I think you can use readLines(n=1) in loop to skip unwanted rows.
On Mon, Jun 1, 2009 at 12:56
There are several things you can tell read.table to make it faster.
First, as mentioned, setting colClasses helps. I think telling read.table how
many rows and columns there are also helps.
When this was not sufficient, I've had to do the data processing
using Python, Perl, or awk.
If that had
One can use colClasses to set which columns get read in. For the
columns you don't
want you can set those to NULL. For example,
cc - c(NULL,rep(numeric,9))
myData - read.table(myFile.txt,header=TRUE,colClasses=cc,nrow=numRows).
On Wed, May 27, 2009 at 12:27 PM, g...@ucalgary.ca wrote:
We are
We are reading big tables, such as,
Chemicals -
read.table('ftp://ftp.bls.gov/pub/time.series/wp/wp.data.7.Chemicals',header
= TRUE, sep = '\t', as.is =T)
I was wondering if it is possible to set a filter during loading so that
we just load what we want not the whole table each time. Thanks,
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