R - Categorize a dataset - r

Question

Morning folks,
I'm trying to categorize a set of numerical values (Days Left divided by 365.2 which gives us approximately the numbers of years left until a maturity).
The results of this first calculation give me a vector of 3560 values (example: 0.81, 1.65, 3.26 [...], 0.2).
I'd like to categorise these results into intervals, [Between 0 and 1 Year, 0 and 2 Years, 0 and 3 years, 0 and 4 years, Over 4 years].
#Set the Data Frame
dfMaturity <- data.frame(Maturity = DATA$Maturity)
#Call the library and Run the function
MaturityX = ddply(df, .(Maturity), nrow)
#Set the Data Frame
dfMaturityID <- data.frame(testttto = DATA$Security.Name)
#Calculation of the remaining days
MaturityID = ddply(df, .(dfMaturityID$testttto), nrow)
survey <- data.frame(date=c(DATA$Maturity),tx_start=c("1/1/2022"))
survey$date_diff <- as.Date(as.character(survey$date), format="%m/%d/%Y")-
as.Date(as.character(survey$tx_start), format="%m/%d/%Y")
# Data for the table
MaturityName <- MaturityID$`dfMaturityID$testttto
MaturityZ <- survey$date
TimeToMaturity <- as.numeric(survey$date_diff)
# /!/ HERE IS WHERE I NEED HELP /!/ I'M TRYING TO CATEGORISE THE RESULTS OF THIS CALCULATION
Multiplier <- TimeToMaturity /365.2
cx <- cut(Multiplier, breaks=0:5)
The original datasource comes from an excel file (DATA$Maturity)
If it can helps you:
'''
print(Multiplier)
'''
gives us
print(Multiplier)
[1] 0.4956188 1.4950712 1.9989047 0.2464403 0.9994524 3.0010953 5.0000000 7.0016429 9.0005476
[10] 21.0021906 4.1621030 13.1626506 1.1610077 8.6664841 28.5377875 3.1626506 6.7497262 2.0920044
[19] 2.5602410 4.6495071 0.3368018 6.3225630 8.7130340 10.4956188 3.9019715 12.7957284 5.8378970
I copied the first three lines, but there is a total 3560 objects.
I'm open to any kind of help, I just want it to work :) thank you !

Answer 1

The cut function does that:
example <- c(0.81, 1.65, 3.26, 0.2)
cut(example, breaks = c(0, 1, 2, 3, 4),
labels = c("newborn", "one year old", "two", "three"))
Edit:
From the comment
I'd like then to create a table with for example: 30% of the objects has a maturity between 0 and 1 year
You could compute that using the function below:
example <- c(0.81, 1.65, 3.26, 0.2)
share <- function(x, lower = 0, higher= 1){
x <- na.omit(x)
sum((lower <= x) & (x < higher))/length(x)
}
share(1:10, lower = 0,higher = 3.5) # true for 1:3 out of 1:10 so 30%
share(1:10, lower = 4.5, higher = 5.5) # true for 5 so 10%)
share(example, 0, 3)