factor() is a function in base R (that is, not in any additional package) that encodes categorical variables in the most R-friendly way.
We’ll illustrate the use of factor() with the msleep dataset that comes from tidyverse. msleep contains some data about how much different kinds of mammals sleep. Here’s what the first few rows of msleep look like.
msleep |>head()
# A tibble: 6 × 11
name genus vore order conservation sleep_total sleep_rem sleep_cycle awake
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 Cheetah Acin… carni Carn… lc 12.1 NA NA 11.9
2 Owl mo… Aotus omni Prim… <NA> 17 1.8 NA 7
3 Mounta… Aplo… herbi Rode… nt 14.4 2.4 NA 9.6
4 Greate… Blar… omni Sori… lc 14.9 2.3 0.133 9.1
5 Cow Bos herbi Arti… domesticated 4 0.7 0.667 20
6 Three-… Brad… herbi Pilo… <NA> 14.4 2.2 0.767 9.6
# ℹ 2 more variables: brainwt <dbl>, bodywt <dbl>
# A tibble: 83 × 11
name genus vore order conservation sleep_total sleep_rem sleep_cycle awake
<chr> <chr> <fct> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 Cheet… Acin… carni Carn… lc 12.1 NA NA 11.9
2 Owl m… Aotus omni Prim… <NA> 17 1.8 NA 7
3 Mount… Aplo… herbi Rode… nt 14.4 2.4 NA 9.6
4 Great… Blar… omni Sori… lc 14.9 2.3 0.133 9.1
5 Cow Bos herbi Arti… domesticated 4 0.7 0.667 20
6 Three… Brad… herbi Pilo… <NA> 14.4 2.2 0.767 9.6
7 North… Call… carni Carn… vu 8.7 1.4 0.383 15.3
8 Vespe… Calo… <NA> Rode… <NA> 7 NA NA 17
9 Dog Canis carni Carn… domesticated 10.1 2.9 0.333 13.9
10 Roe d… Capr… herbi Arti… lc 3 NA NA 21
# ℹ 73 more rows
# ℹ 2 more variables: brainwt <dbl>, bodywt <dbl>
To make sure it’s worked, check the data type that str() gives us for vore:
str(msleep)
tibble [83 × 11] (S3: tbl_df/tbl/data.frame)
$ name : chr [1:83] "Cheetah" "Owl monkey" "Mountain beaver" "Greater short-tailed shrew" ...
$ genus : chr [1:83] "Acinonyx" "Aotus" "Aplodontia" "Blarina" ...
$ vore : Factor w/ 4 levels "carni","herbi",..: 1 4 2 4 2 2 1 NA 1 2 ...
$ order : chr [1:83] "Carnivora" "Primates" "Rodentia" "Soricomorpha" ...
$ conservation: chr [1:83] "lc" NA "nt" "lc" ...
$ sleep_total : num [1:83] 12.1 17 14.4 14.9 4 14.4 8.7 7 10.1 3 ...
$ sleep_rem : num [1:83] NA 1.8 2.4 2.3 0.7 2.2 1.4 NA 2.9 NA ...
$ sleep_cycle : num [1:83] NA NA NA 0.133 0.667 ...
$ awake : num [1:83] 11.9 7 9.6 9.1 20 9.6 15.3 17 13.9 21 ...
$ brainwt : num [1:83] NA 0.0155 NA 0.00029 0.423 NA NA NA 0.07 0.0982 ...
$ bodywt : num [1:83] 50 0.48 1.35 0.019 600 ...
vore is stored as a “Factor w/ 4 levels”, and those levels are labelled “carni”, “herbi”, “insecti”, and “omni”.
To change the order of levels in a factor
By default, factor levels use the labels’ alphabetical order. To change the factor levels, say to put “insecti” first and “carni” at the end, we can use levels argument of factor():
msleep <- msleep |>mutate(vore =factor( vore,levels =c('insecti', 'herbi', 'omni', 'carni') # make sure the labels you type match the existing labels exactly! ) ) msleep
# A tibble: 83 × 11
name genus vore order conservation sleep_total sleep_rem sleep_cycle awake
<chr> <chr> <fct> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 Cheet… Acin… carni Carn… lc 12.1 NA NA 11.9
2 Owl m… Aotus omni Prim… <NA> 17 1.8 NA 7
3 Mount… Aplo… herbi Rode… nt 14.4 2.4 NA 9.6
4 Great… Blar… omni Sori… lc 14.9 2.3 0.133 9.1
5 Cow Bos herbi Arti… domesticated 4 0.7 0.667 20
6 Three… Brad… herbi Pilo… <NA> 14.4 2.2 0.767 9.6
7 North… Call… carni Carn… vu 8.7 1.4 0.383 15.3
8 Vespe… Calo… <NA> Rode… <NA> 7 NA NA 17
9 Dog Canis carni Carn… domesticated 10.1 2.9 0.333 13.9
10 Roe d… Capr… herbi Arti… lc 3 NA NA 21
# ℹ 73 more rows
# ℹ 2 more variables: brainwt <dbl>, bodywt <dbl>
The preview doesn’t look any different, but we can see the factor levels have changed order in str(), because now “insecti” is listed first:
str(msleep)
tibble [83 × 11] (S3: tbl_df/tbl/data.frame)
$ name : chr [1:83] "Cheetah" "Owl monkey" "Mountain beaver" "Greater short-tailed shrew" ...
$ genus : chr [1:83] "Acinonyx" "Aotus" "Aplodontia" "Blarina" ...
$ vore : Factor w/ 4 levels "insecti","herbi",..: 4 3 2 3 2 2 4 NA 4 2 ...
$ order : chr [1:83] "Carnivora" "Primates" "Rodentia" "Soricomorpha" ...
$ conservation: chr [1:83] "lc" NA "nt" "lc" ...
$ sleep_total : num [1:83] 12.1 17 14.4 14.9 4 14.4 8.7 7 10.1 3 ...
$ sleep_rem : num [1:83] NA 1.8 2.4 2.3 0.7 2.2 1.4 NA 2.9 NA ...
$ sleep_cycle : num [1:83] NA NA NA 0.133 0.667 ...
$ awake : num [1:83] 11.9 7 9.6 9.1 20 9.6 15.3 17 13.9 21 ...
$ brainwt : num [1:83] NA 0.0155 NA 0.00029 0.423 NA NA NA 0.07 0.0982 ...
$ bodywt : num [1:83] 50 0.48 1.35 0.019 600 ...
To change the labels shown for factor levels
To relabel “carni” as “carnivore”, “insecti” as “insectivore”, and so on, we can also use the labels argument of factor().
msleep <- msleep |>mutate(vore =factor( vore,labels =c('insectivore', 'herbivore', 'omnivore', 'carnivore')# make sure the labels match the order of the levels, else you might relabel carnivores as insectivores etc.! ) ) msleep
# A tibble: 83 × 11
name genus vore order conservation sleep_total sleep_rem sleep_cycle awake
<chr> <chr> <fct> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 Cheet… Acin… carn… Carn… lc 12.1 NA NA 11.9
2 Owl m… Aotus omni… Prim… <NA> 17 1.8 NA 7
3 Mount… Aplo… herb… Rode… nt 14.4 2.4 NA 9.6
4 Great… Blar… omni… Sori… lc 14.9 2.3 0.133 9.1
5 Cow Bos herb… Arti… domesticated 4 0.7 0.667 20
6 Three… Brad… herb… Pilo… <NA> 14.4 2.2 0.767 9.6
7 North… Call… carn… Carn… vu 8.7 1.4 0.383 15.3
8 Vespe… Calo… <NA> Rode… <NA> 7 NA NA 17
9 Dog Canis carn… Carn… domesticated 10.1 2.9 0.333 13.9
10 Roe d… Capr… herb… Arti… lc 3 NA NA 21
# ℹ 73 more rows
# ℹ 2 more variables: brainwt <dbl>, bodywt <dbl>
This change is more apparent in the vore column!
And we can also see it using str():
str(msleep)
tibble [83 × 11] (S3: tbl_df/tbl/data.frame)
$ name : chr [1:83] "Cheetah" "Owl monkey" "Mountain beaver" "Greater short-tailed shrew" ...
$ genus : chr [1:83] "Acinonyx" "Aotus" "Aplodontia" "Blarina" ...
$ vore : Factor w/ 4 levels "insectivore",..: 4 3 2 3 2 2 4 NA 4 2 ...
$ order : chr [1:83] "Carnivora" "Primates" "Rodentia" "Soricomorpha" ...
$ conservation: chr [1:83] "lc" NA "nt" "lc" ...
$ sleep_total : num [1:83] 12.1 17 14.4 14.9 4 14.4 8.7 7 10.1 3 ...
$ sleep_rem : num [1:83] NA 1.8 2.4 2.3 0.7 2.2 1.4 NA 2.9 NA ...
$ sleep_cycle : num [1:83] NA NA NA 0.133 0.667 ...
$ awake : num [1:83] 11.9 7 9.6 9.1 20 9.6 15.3 17 13.9 21 ...
$ brainwt : num [1:83] NA 0.0155 NA 0.00029 0.423 NA NA NA 0.07 0.0982 ...
$ bodywt : num [1:83] 50 0.48 1.35 0.019 600 ...