apply converts your data.frame to a character matrix. Use lapply:
lapply(a, class)
# $x1
# [1] "numeric"
# $x2
# [1] "factor"
# $x3
# [1] "factor"
In second command apply converts result to character matrix, using lapply:
a2 <- lapply(a, as.factor)
lapply(a2, class)
# $x1
# [1] "factor"
# $x2
# [1] "factor"
# $x3
# [1] "factor"
But for simple lookout you could use str:
str(a)
# 'data.frame': 100 obs. of 3 variables:
# $ x1: num -1.79 -1.091 1.307 1.142 -0.972 ...
# $ x2: Factor w/ 2 levels "a","b": 2 1 1 1 2 1 1 1 1 2 ...
# $ x3: Factor w/ 2 levels "a","b": 1 1 1 1 1 1 1 1 1 1 ...
Additional explanation according to comments:
Why does the lapply work while apply doesn’t?
The first thing that apply does is to convert an argument to a matrix. So apply(a) is equivalent to apply(as.matrix(a)). As you can see str(as.matrix(a)) gives you:
chr [1:100, 1:3] " 0.075124364" "-1.608618269" "-1.487629526" ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:3] "x1" "x2" "x3"
There are no more factors, so class return "character" for all columns.
lapply works on columns so gives you what you want (it does something like class(a$column_name) for each column).
You can see in help to apply why apply and as.factor doesn’t work :
In all cases the result is coerced by
as.vector to one of the basic vector
types before the dimensions are set,
so that (for example) factor results
will be coerced to a character array.
Why sapply and as.factor doesn’t work you can see in help to sapply:
Value (…) An atomic vector or matrix
or list of the same length as X (…)
If simplification occurs, the output
type is determined from the highest
type of the return values in the
hierarchy NULL < raw < logical <
integer < real < complex < character <
list < expression, after coercion of
pairlists to lists.
You never get matrix of factors or data.frame.
How to convert output to data.frame?
Simple, use as.data.frame as you wrote in comment:
a2 <- as.data.frame(lapply(a, as.factor))
str(a2)
'data.frame': 100 obs. of 3 variables:
$ x1: Factor w/ 100 levels "-2.49629293159922",..: 60 6 7 63 45 93 56 98 40 61 ...
$ x2: Factor w/ 2 levels "a","b": 1 1 2 2 2 2 2 1 2 2 ...
$ x3: Factor w/ 2 levels "a","b": 1 1 1 1 1 1 1 1 1 1 ...
But if you want to replace selected character columns with factor there is a trick:
a3 <- data.frame(x1=letters, x2=LETTERS, x3=LETTERS, stringsAsFactors=FALSE)
str(a3)
'data.frame': 26 obs. of 3 variables:
$ x1: chr "a" "b" "c" "d" ...
$ x2: chr "A" "B" "C" "D" ...
$ x3: chr "A" "B" "C" "D" ...
columns_to_change <- c("x1","x2")
a3[, columns_to_change] <- lapply(a3[, columns_to_change], as.factor)
str(a3)
'data.frame': 26 obs. of 3 variables:
$ x1: Factor w/ 26 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10 ...
$ x2: Factor w/ 26 levels "A","B","C","D",..: 1 2 3 4 5 6 7 8 9 10 ...
$ x3: chr "A" "B" "C" "D" ...
You could use it to replace all columns using:
a3 <- data.frame(x1=letters, x2=LETTERS, x3=LETTERS, stringsAsFactors=FALSE)
a3[, ] <- lapply(a3, as.factor)
str(a3)
'data.frame': 26 obs. of 3 variables:
$ x1: Factor w/ 26 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10 ...
$ x2: Factor w/ 26 levels "A","B","C","D",..: 1 2 3 4 5 6 7 8 9 10 ...
$ x3: Factor w/ 26 levels "A","B","C","D",..: 1 2 3 4 5 6 7 8 9 10 ...