Coerce multiple columns to factors at once
Choose some columns to coerce to factors:
cols <- c("A", "C", "D", "H")
Use lapply()
to coerce and replace the chosen columns:
data[cols] <- lapply(data[cols], factor) ## as.factor() could also be used
Check the result:
sapply(data, class)
# A B C D E F G
# "factor" "integer" "factor" "factor" "integer" "integer" "integer"
# H I J
# "factor" "integer" "integer"
Here is an option using dplyr
. The %<>%
operator from magrittr
update the lhs object with the resulting value.
library(magrittr)
library(dplyr)
cols <- c("A", "C", "D", "H")
data %<>%
mutate_each_(funs(factor(.)),cols)
str(data)
#'data.frame': 4 obs. of 10 variables:
# $ A: Factor w/ 4 levels "23","24","26",..: 1 2 3 4
# $ B: int 15 13 39 16
# $ C: Factor w/ 4 levels "3","5","18","37": 2 1 3 4
# $ D: Factor w/ 4 levels "2","6","28","38": 3 1 4 2
# $ E: int 14 4 22 20
# $ F: int 7 19 36 27
# $ G: int 35 40 21 10
# $ H: Factor w/ 4 levels "11","29","32",..: 1 4 3 2
# $ I: int 17 1 9 25
# $ J: int 12 30 8 33
Or if we are using data.table
, either use a for
loop with set
setDT(data)
for(j in cols){
set(data, i=NULL, j=j, value=factor(data[[j]]))
}
Or we can specify the 'cols' in .SDcols
and assign (:=
) the rhs to 'cols'
setDT(data)[, (cols):= lapply(.SD, factor), .SDcols=cols]
The more recent tidyverse
way is to use the mutate_at
function:
library(tidyverse)
library(magrittr)
set.seed(88)
data <- data.frame(matrix(sample(1:40), 4, 10, dimnames = list(1:4, LETTERS[1:10])))
cols <- c("A", "C", "D", "H")
data %<>% mutate_at(cols, factor)
str(data)
$ A: Factor w/ 4 levels "5","17","18",..: 2 1 4 3
$ B: int 36 35 2 26
$ C: Factor w/ 4 levels "22","31","32",..: 1 2 4 3
$ D: Factor w/ 4 levels "1","9","16","39": 3 4 1 2
$ E: int 3 14 30 38
$ F: int 27 15 28 37
$ G: int 19 11 6 21
$ H: Factor w/ 4 levels "7","12","20",..: 1 3 4 2
$ I: int 23 24 13 8
$ J: int 10 25 4 33