I have a dataset where I want to create a new column and add values based on the value present in each row. below is the example
Sales Result of new column 100 Low 200 Low 300 Moderate 400 High 500 High
Below is the code i tried to get result
data$New_Column = for (Sal in data$Sales){
if(Sal > 300){
print("High")
} else if(Sal == 300){
print("Moderate")
}else{
print("Low")
}
}
Thank You
You would usually not do that in a loop in R since most of the relevant functions can work directly with vectors.
Here is one option using data.table::fcase() and another using ifelse() from base R:
library(data.table)
data$New_Column <- fcase(
data$Sales > 300, "High",
data$Sales == 300, "Moderate",
data$Sales < 300, "Low"
)
# Using base R only:
data$New_Column <-
ifelse(data$Sales == 300, "Moderate", ifelse(data$Sales > 300, "High", "Low"))
# Sales New_Column
# 1 300 Moderate
# 2 500 High
# 3 200 Low
# 4 500 High
# 5 400 High
# 6 500 High
# 7 400 High
# 8 300 Moderate
Example input data
set.seed(13L)
data <- data.frame(
Sales = sample(seq(100, 500, 100), size = 8L, replace = TRUE)
)
Perhaps try using mutate instead of a loop:
newdat <- data %>>% mutate(New_Column, if(Sal==300 = "moderate"), ifelse(Sal>300, "High", "Low")
if is not vectorised, whereas ifelse is. Thus you would call ifelse(Sal == 300, "moderate", ifelse(Sal > 300, "High", "Low")). Also Sal==300 = "moderate" throws an error!
