retail <- 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"))
)
print(retail)
## 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
## 1 70 100 Home
## 2 25000 2000 Store
## 3 1000 150 Home
## 4 80 50 Store
## 5 22000 500 Home
## 6 900 300 Home
summary(retail)
## BillID CustomerName Gender Membership Category
## Min. :501.0 Length:6 Female:3 Gold :3 Clothing :2
## 1st Qu.:502.2 Class :character Male :3 None :1 Electronics:2
## Median :503.5 Mode :character Silver:2 Grocery :2
## Mean :503.5
## 3rd Qu.:504.8
## Max. :506.0
## Quantity CostPrice SellingPrice Discount DeliveryType
## Min. : 1.000 Min. : 50 Min. : 70 Min. : 50.0 Home :4
## 1st Qu.: 2.250 1st Qu.: 220 1st Qu.: 285 1st Qu.: 112.5 Store:2
## Median : 4.000 Median : 750 Median : 950 Median : 225.0
## Mean : 4.833 Mean : 6602 Mean : 8175 Mean : 516.7
## 3rd Qu.: 7.250 3rd Qu.:13700 3rd Qu.:16750 3rd Qu.: 450.0
## Max. :10.000 Max. :20000 Max. :25000 Max. :2000.0