Do you run into problems if you use something like:
cc <- rep("numeric",9)
mydata <- read.table("yourdata",header=TRUE,colClasses=cc,skip=1,nrows=numRows)
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read t
As you see in the data.. each section has table header followed by a row of
table column headers and then rows of data. I felt read.table may not be the
optimal function to extract both the texts (headers) and numerics
(rows&columns of data). As of now, I use "scan" to get the text boundaries
and u
How do you want to extract the data? You can use 'readLines' to read
in the data and then 'grep' to find the header lines and delete them.
On the other hand, do you want to separate each section into a
differnet object/list? You can again use readLines and determine
where the breaks are and then
Dear R experts..
I am trying to read data-sections in a large consolidated dataset,
containing section headers and the data . There are many options available
to implement, I was wondering what optimal function, to extract section
headers and data (w/ columns), could be used on the dataset that lo
4 matches
Mail list logo
