Convert type of multiple columns of a dataframe at once

Question

I seem to spend a lot of time creating a dataframe from a file, database or something, and then converting each column into the type I wanted it in (numeric, factor, character etc). Is there a way to do this in one step, possibly by giving a vector of types ?

foo<-data.frame(x=c(1:10),                  y=c("red", "red", "red", "blue", "blue",                      "blue", "yellow", "yellow", "yellow",                      "green"),                 z=Sys.Date()+c(1:10))  foo$x<-as.character(foo$x) foo$y<-as.character(foo$y) foo$z<-as.numeric(foo$z) 

instead of the last three commands, I'd like to do something like

foo<-convert.magic(foo, c(character, character, numeric)) 

Answer 1

Edit See this related question for some simplifications and extensions on this basic idea.

My comment to Brandon's answer using switch:

convert.magic <- function(obj,types){     for (i in 1:length(obj)){         FUN <- switch(types[i],character = as.character,                                     numeric = as.numeric,                                     factor = as.factor)         obj[,i] <- FUN(obj[,i])     }     obj }  out <- convert.magic(foo,c('character','character','numeric')) > str(out) 'data.frame':   10 obs. of  3 variables:  $ x: chr  "1" "2" "3" "4" ...  $ y: chr  "red" "red" "red" "blue" ...  $ z: num  15254 15255 15256 15257 15258 ... 

For truly large data frames you may want to use lapply instead of the for loop:

convert.magic1 <- function(obj,types){     out <- lapply(1:length(obj),FUN = function(i){FUN1 <- switch(types[i],character = as.character,numeric = as.numeric,factor = as.factor); FUN1(obj[,i])})     names(out) <- colnames(obj)     as.data.frame(out,stringsAsFactors = FALSE) } 

When doing this, be aware of some of the intricacies of coercing data in R. For example, converting from factor to numeric often involves as.numeric(as.character(...)). Also, be aware of data.frame() and as.data.frame()s default behavior of converting character to factor.

Answer 2

If you want to automatically detect the columns data-type rather than manually specify it (e.g. after data-tidying, etc.), the function type.convert() may help.

The function type.convert() takes in a character vector and attempts to determine the optimal type for all elements (meaning that it has to be applied once per column).

df[] <- lapply(df, function(x) type.convert(as.character(x))) 

Since I love dplyr, I prefer:

library(dplyr) df <- df %>% mutate_all(funs(type.convert(as.character(.))))