How to divide columns by condition on specific one?-CodePudding

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：

This should do it:

library(dplyr)
df <- data.frame (Sale  = c(100,200,500,150),
                  Cost = c(50,20,80,12),
                  Model = c("A","B","C","D"))
df %>% 
  mutate(across(c(Sale, Cost), ~.x/c(1,5,10)[as.numeric(cut(mean(Sale), breaks=c(-Inf, 50, 150, Inf)))]))
#>   Sale Cost Model
#> 1   10  5.0     A
#> 2   20  2.0     B
#> 3   50  8.0     C
#> 4   15  1.2     D

^{Created on 2022-05-10 by the reprex package (v2.0.1)}

CodePudding user response：

You could also use case_when

library(dplyr)
df %>% 
  mutate(Sale_2 = case_when(
    mean(Sale) > 150 ~ Sale/10, 
    mean(Sale) > 50  ~ Sale/5
  ), 
  Cost_2 = case_when(
    mean(Sale) > 150 ~ Cost/10, 
    mean(Sale) > 50  ~ Cost/5
  ))