Your column of data has some character data in it, perhaps an Excel #VALUE! or a blank or some such entry not strictly numeric.
When R reads in such a column, it makes that column variable into a 'factor' variable instead of a numeric variable, because the values are not all numeric. You can specify stringsAsFactors = FALSE to force R to leave character data as is if you do not want conversion to factors. If there is Excel cruft in a variable column, it will end up as a factor or character variable. You can try to make it numeric with df$x <- as.numeric(as.character(df$x)) (assuming you read the data into a dataframe called df) and R will replace the Excel cruft with NA values. Alternatively you can clean up the Excel data before importing it. HTH Steve McKinney -----Original Message----- From: [EMAIL PROTECTED] on behalf of K3 Sent: Fri 10/3/2008 4:09 PM To: r-help@r-project.org Subject: [R] help regarding levels When i try to extract a column of data from an excel file and assign it to a variable , say x, it does assign the column of data as well as different levels. it looks something like this when i print. [1] 6.91 5.89 7.44 8.82 80 Levels: 1.43 102.07 103.65 106.21 106.24 107.15 108.58 11.19 ... so how does this levels come into picture and what do they do. I couldnot run linear regression with x as a predictor just because of this levels. please explain. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.