sales=data.frame(
        billID = c(501,502,503,504,505,506),
  customerName = c("aman","riya","karan","neha","rohit","simran"),
        gender = factor(c("male","female","male","female","male","female")),
    membership = factor(c("Gold","silver","Gold","none","silver","Gold")),
      category = factor(c("grocery","electronics","clothing","grocery","electronics","clothing")),
      quantity = c(10,1,3,8,2,5),
     costPrice = c(50,20000,800,60,18000,700),
  sellingPrice = c(70,25000,1000,80,22000,900),
      discount = c(100,2000,150,50,500,300),
  deliveryType = factor(c("home","store","home","store","home","home"))
  
)

sales$grossRevenue=sales$quantity*sales$sellingPrice
sales$TotalCost =sales$quantity * sales$costPrice
sales$NetRevenue = sales$grossRevenue-sales$discount
sales$Profit = sales$NetRevenue-sales$TotalCost

gold_home_profit = subset(sales, membership=="Gold" & Profit>5000 & deliveryType=="home")
loss_transactions <- subset(sales, Profit < 0)
electronics_filter <- subset(sales,
                             category=="electronics" &
                               quantity>=2 &
                               discount>1000 &
                               Profit>0)
premium_customers <- subset(sales, NetRevenue>20000 | membership=="Gold")

print(sales)

##   billID customerName gender membership    category quantity costPrice
## 1    501         aman   male       Gold     grocery       10        50
## 2    502         riya female     silver electronics        1     20000
## 3    503        karan   male       Gold    clothing        3       800
## 4    504         neha female       none     grocery        8        60
## 5    505        rohit   male     silver electronics        2     18000
## 6    506       simran female       Gold    clothing        5       700
##   sellingPrice discount deliveryType grossRevenue TotalCost NetRevenue Profit
## 1           70      100         home          700       500        600    100
## 2        25000     2000        store        25000     20000      23000   3000
## 3         1000      150         home         3000      2400       2850    450
## 4           80       50        store          640       480        590    110
## 5        22000      500         home        44000     36000      43500   7500
## 6          900      300         home         4500      3500       4200    700