I have code which divides the Sales column by 10 if the mean of sales is more than 150, else if the mean > 80, values are divided by 5 or keep the same in case < 80
df <- data.frame (Sale = c(100,200,500,150),
Cost = c(50,20,80,12),
Model = c("A","B","C","D"))
df$Sale = df$Sale
if(mean(df$Sale)>150){
df$Sale = df$Sale/10
}else if(mean(df$Sale)>50){
df$Sale = df$Sale/5
}
However, I have another numerical column 'Cost' and want to do the same based on condition of sales, something like this:
df[,Sales,Cost] = df[,Sales,Cost]
if(mean(df$Sale)>150){
df[Sales,Cost] = df[SalesCost]/10
}else if(mean(df$Sale)>50){
df[Sales,Cost] = df[Sales,Cost]/5
}
CodePudding user response:
You can use dplyr::across
to do the same function over multiple columns:
library(dplyr)
df %>%
mutate(across(c(Sale, Cost), ~ case_when(Sale > 150 ~ .x/10,
Sale > 50 ~ .x/5,
TRUE ~ .x)))
# Sale Cost Model
#1 20 10.0 A
#2 20 2.0 B
#3 50 8.0 C
#4 30 2.4 D