I have two factors tID and fff with the same levels but different lengths of 45000000 and 23000, respectively:
> head(factor(tID))
Fungi Metazoa Fungi Fungi Fungi Fungi
227321 79782 52586 1658174 573508 88771
Levels: 2 7 9 11 14 16 17 19 20 22 23 24 32 33 34 38 39 41 42 43 47 48 51 52 54 56 61 68 69 72 75 81 85 86 103 104 106 114 119 120 122 124 125 128 134 140 141 142 143 144 148 154 158 159 162 163 165 167 171 172 173 174 179 ... 1985254
head(fff)
[1] 4932 870730 34413 4932 4932 9606
Levels: 2 7 9 11 14 16 17 19 20 22 23 24 32 33 34 38 39 41 42 43 47 48 51 52 54 56 61 68 69 72 75 81 85 86 103 104 106 114 119 120 122 124 125 128 134 140 141 142 143 144 148 154 158 159 162 163 165 167 171 172 173 174 179 ... 1985254
Is there any faster way to map names from factor tID to fff?
I know I can do this using lappy() or sapply() but the factors contain 4.5 million elements so it's bit slow.
With names and match:
names(fa) <- names(fb)[match(fa, fb)]
you get:
> fa
name_1 name_1 name_1 name_6 name_6 name_6 name_11 name_11 name_11 name_16 name_16 name_16 name_21 name_21 name_21
a a a b b b c c c d d d e e e
Levels: a b c d e
For the new example in the question this should be:
names(fff) <- names(tID)[match(fff, tID)]
Example data:
fa <- factor(rep(letters[1:5], each = 3))
fb <- factor(rep(letters[1:5], each = 5))
fb <- setNames(fb, paste0('name_',seq_along(fb)))