How to convert numbers into categories in R

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In my database, I have a Variable TP_CorRaca with the values 0, 1, 2, 3, 4, 5. Each number corresponds to a color.

Example:

0 - White

1 - black

2 - brown

...

I want to make that match to use the function lm().

r

2 answers

6

This is a case where factors are useful. Just turn your variable into a factor.

Creating an example vector:

set.seed(10)
exemplo_numero <- sample(0:5, 10, replace = TRUE)

You can use the function factor() explaining what each number is:

exemplo_fator <- factor(exemplo_numero, 
                        levels = 0:5,
                        labels  = c("branco", "preto", "pardo", "amarelo", "indigena", "não declarado"))
exemplo_fator
[1] amarelo  preto    pardo    indigena branco   preto    preto    preto    amarelo  pardo   
Levels: branco preto pardo amarelo indigena não declarado

2

Has the function recode of dplyr. Using the same example as @Carlos Cinelli

set.seed(10)
exemplo_numero <- sample(0:5, 10, replace = TRUE)

library(dplyr)
recode(exemplo_numero, `0` = "branco", `1` = "preto",`2`= "pardo", 
       `3` = "amarelo", `4` = "indigena", `5` = "não declarado")
#> [1] "amarelo"  "preto"    "pardo"    "indigena" "branco"   "preto"    "preto"    "preto"    "amarelo"  "pardo"

Note that the numbers need to be between "`" the same as the crase accent. The legal of the function recode are the other parameters such as .default and .missing. 

x <- c(1:4, NA)
recode(x, `1` = "z", `2` = "y", .default = "D")
#> [1] "z" "y" "D" "D" NA 
recode(x, `1` = "z", `2` = "y", .default = "D", .missing = "M")
#> [1] "z" "y" "D" "D" "M"

The .default can be used to fill in the values not mentioned in the code for some value. The .missing replaces valore NA for some value too.

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