Solved – Is it possible to directly read CSV columns as categorical data

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I need to analyze with R the data from a medical survey (with 100+ coded columns) that comes in a CSV. I will use rattle for some initial analysis but behind the scenes it's still R.

If I read.csv() the file, columns with numerical codes are treated as numerical data. I'm aware I could create categorical columns from them with factor() but doing it for 100+ columns is a pain.

I hope there is a better way to tell R to import the columns directly as factors. Or to at least to convert them in place afterwards.

Thank you!

Answer 1

You can use the colClasses argument to specify the classes of your data columns. For example:

data <- read.csv('foo.csv', colClasses=c('numeric', 'factor', 'factor'))

will assign numeric to the first column, factor to the second and third. Since you have so many columns, a shortcut might be:

data <- read.csv('foo.csv', colClasses=c('numeric', rep('factor', 37), 'character'))

or some such variation (i.e. assign numeric to first column, factor to next 37 columns, then character to the last one).