I want to categorized one variable with the next conditionals:
0 - 4: "fail" 5 - 7: "good" 8 - 10: "excellent" None of the above: NA
I tried using the recode function
The values of variable is numeric
segur <- data$segur
Created a new variable using recode
dt1 <- recode(segur, "c(0,4)='suspenso';c(5, 7)='aceptable';c(8,10)='excelente'; else='NA'")
dt1
How can I fix?
using factor in base R
Data:
# set random seed
set.seed(1L)
# without any NA
x1 <- sample(x = 1:10, size = 20, replace=TRUE)
# with NA
x2 <- sample(x = c(1:10, NA), size = 20, replace=TRUE)
Code:
# without any NA
as.character(factor(x1, levels = c(0:10), labels = c(rep("fail", 5), rep("good", 3), rep("excellent", 3)), exclude=NA))
# with NA
as.character(factor(x2, levels = c(0:10), labels = c(rep("fail", 5), rep("good", 3), rep("excellent", 3)), exclude=NA))
I guess you can use cut like below
cut(segur, c(0, 4, 7, 10), labels = c("fail", "good", "excellent"))
Example
> segur
[1] 6 1 4 -2 -1 10 8 0 5 9
> cut(segur, c(0, 4, 7, 10), labels = c("fail", "good", "excellent"))
[1] good fail fail <NA> <NA> excellent excellent
[8] <NA> good excellent
Levels: fail good excellent
Here is a solution using the fmtr package. You can create a categorical format using the value and condition functions, and then apply the format to the numeric data using the fapply function. Here is an example:
library(fmtr)
# Create sample data
df <- read.table(header = TRUE, text = '
ID segur
1 0
2 8
3 5
4 11
5 7')
# Create format
fmt <- value(condition(x >= 0 & x <=4, "fail"),
condition(x >= 5 & x <=7, "good"),
condition(x >= 8 & x <= 10, "excellent"),
condition(TRUE, NA))
# Apply categorization
df$segur_cat <- fapply(df$segur, fmt)
# View results
df
# ID segur segur_cat
# 1 1 0 fail
# 2 2 8 excellent
# 3 3 5 good
# 4 4 11 <NA>
# 5 5 7 good
