Read column names as numbers when importing a data file to R

When you read in a data file from CSV or some other text format, R will examine the column headings and ensure that they are in correct “R-format”. If your headings are all numbers, for example years, then R will convert them to character strings and prepend “X” to each heading.

You can overcome this behaviour and force R to read the headings as they come. Your headings are still converted to character strings but these are easier to coerce to a numeric value.

Look at these data (you can view/get the datafile here):

Spp     1996 1997 1998 1999 2000
M.bro     88   47   13   33   86
Or.tip    90   14   36   24   47
Paint.l   50    0    0    0    4
Pea       48  110   85   54   65
Red.ad     6    3    8   10   15
Ring     190   80   96  179  145

The first column contains species names and the rest are numbers. The column names are mostly years (the sampling year). If you read these data into R the column names will be prepended with “X”, which is not helpful.

If you add check.names = FALSE as a parameter to read.xxxx() you’ll force R to accept the names of the columns as they are.

> bfy <- read.table(file.choose(), header = TRUE, sep = "\t", check.names = FALSE, row.names = 1)

> bfy
        1996 1997 1998 1999 2000
M.bro     88   47   13   33   86
Or.tip    90   14   36   24   47
Paint.l   50    0    0    0    4
Pea       48  110   85   54   65
Red.ad     6    3    8   10   15
Ring     190   80   96  179  145

> as.numeric(colnames(bfy))
[1] 1996 1997 1998 1999 2000

The data object will contain column names that are character but it is easy to coerce them to numeric with the as.numeric() command.

Of course this is a bit of a cheat… the column names are not real numbers. You cannot make the column names “properly” numeric but in this (character) form you can easily coerce them to be numeric when you need with the as.numeric() command.