There is an issue that is being overlooked here.
The read.table() family of functions use type.convert() by default
internally to determine the resultant data types of the columns going
into the data frame from the source text file. Everything read in by
read.table() starts as character and then type.convert() (unless
overridden by 'colClasses') does its job.
If a column that "should be" numeric is being converted to a factor,
then there is a data integrity problem in that column. In other words,
there are non-numeric characters in that column, preventing the column
from being converted to numeric.
# All 'numeric' source data
int [1:5] 1 2 3 4 5
# a non-numeric character in the source vector
Factor w/ 6 levels "1","2","3","4",..: 1 2 3 4 5 6
Bottom line, Arup needs to go back and review his source data to
understand why the columns that should be numeric end up as factors.
on 02/06/2009 07:43 AM Wacek Kusnierczyk wrote:
if you use read.table for the import, reading about the colClasses
parameter in ?read.table may help.
On Thu, 5 Feb 2009 22:50:38, wrote:
I am importing a dataset in R where some of the variable are numerical and
some of them are character...but the problem is that R is treating
numerical variables as character (I am using "is.character" to judge the
type). Now the question is how can I convert these character variables into
numeric and also let me know about the other conversion like "numeric to
categorical","numeric to continuous" etc.Thank you.