An Elegant way to change columns type in dataframe in R

Question

I have a data.frame which contains columns of different types, such as integer, character, numeric, and factor.

I need to convert the integer columns to numeric for use in the next step of analysis.

Example: test.data includes 4 columns (though there are thousands in my real data set): age, gender, work.years, and name; age and work.years are integer, gender is factor, and name is character. What I need to do is change age and work.years into a numeric type. And I wrote one piece of code to do this.

test.data[sapply(test.data, is.integer)] <-lapply(test.data[sapply(test.data, is.integer)], as.numeric)

It looks not good enough though it works. So I am wondering if there is some more elegant methods to fulfill this function. Any creative method will be appreciated.

Answer 1

I think elegant code is sometimes subjective. For me, this is elegant but it may be less efficient compared to the OP's code. However, as the question is about elegant code, this can be used.

test.data[] <- lapply(test.data, function(x) if(is.integer(x)) as.numeric(x) else x)

Also, another elegant option is dplyr

library(dplyr)
library(magrittr)
test.data %<>% 
      mutate_each(funs(if(is.integer(.)) as.numeric(.) else .))