How to calculate discount in R?-CodePudding

I have a dataset something like this, and it shows the price for each product:

df <- tribble(
  ~product_id, ~price,  
    '123',        35,                
    '445',        98, 
    '654',        194, 
    '135',        2000, 
    '156',         10, 
)

I now would like to make a discount based on the following conditions on the product price with this formula: price * (100 - discount rate) / 100

If price X, make Y% discount on the price

Less than 10$: 3%
10-20$: 5%
20-30$: 7%
30-90$: 10%
90-190$: 20%
190-2000$: 30%
Higher than 2000$: 50%

Thus, the desired output will be like this:

df <- tribble(
  ~product_id, ~price,  ~discount_rate,  ~final_price, 
  '123',        35,         10,             31.5,
  '445',        98,         20,             78.4,
  '654',        194,        30,             135.8,
  '135',        2000,       50,             1000,
  '156',        10,          5,             9.5,
)

How can I do this?

CodePudding user response：

Just create a column of 'discount_rate' with cut and then subtract the 'price' from the discounted price

library(dplyr)
df <- df %>% 
 mutate(discount_rate = as.integer(as.character(cut(price, 
   breaks = c(-Inf, 10, 20, 30, 90, 190, 2000, Inf), 
    labels = c(3, 5, 7, 10, 20, 30, 50), right = FALSE))),
  final_price = price - (price * discount_rate/100))

-output

# A tibble: 5 × 4
  product_id price discount_rate final_price
  <chr>      <dbl>         <int>       <dbl>
1 123           35            10        31.5
2 445           98            20        78.4
3 654          194            30       136. 
4 135         2000            50      1000  
5 156           10             5         9.5

CodePudding user response：

You may create a discount table.

library(fuzzyjoin)
library(dplyr)

discount_table <- data.frame(start = c(0, 10, 20, 30, 90, 190, 2000), 
                             end =   c(10, 20, 30, 90, 190, 2000, Inf), 
                             discount = c(0.03, 0.05, 0.07, 0.1, 0.2, 0.3, 0.5))

discount_table
#  start  end discount
#1     0   10     0.03
#2    10   20     0.05
#3    20   30     0.07
#4    30   90     0.10
#5    90  190     0.20
#6   190 2000     0.30
#7  2000  Inf     0.50

Join it with df using fuzzyjoin and calculate the new price.

fuzzy_left_join(df, discount_table, by = c('price' = 'start', 'price' = 'end'), 
                match_fun = c(`>=`, `<`)) %>%
  mutate(final_price = price - (price * discount), 
         discount = discount * 100)

#  product_id price start   end discount final_price
#  <chr>      <dbl> <dbl> <dbl>    <dbl>       <dbl>
#1 123           35    30    90       10        31.5
#2 445           98    90   190       20        78.4
#3 654          194   190  2000       30       136. 
#4 135         2000  2000   Inf       50      1000  
#5 156           10    10    20        5         9.5