sales <- data.frame(
BillID = c(501,502,503,504,505,506),
CustomerName = c("Aman","Riya","Karan","Neha","Rohit","Simran"),
Gender = c("Male","Female","Male","Female","Male","Female"),
Membership = c("Gold","Silver","Gold","None","Silver","Gold"),
Category = 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 = c("Home","Store","Home","Store","Home","Home")
)
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
## 1 70 100 Home
## 2 25000 2000 Store
## 3 1000 150 Home
## 4 80 50 Store
## 5 22000 500 Home
## 6 900 300 Home
str(sales)
## 'data.frame': 6 obs. of 10 variables:
## $ BillID : num 501 502 503 504 505 506
## $ CustomerName: chr "Aman" "Riya" "Karan" "Neha" ...
## $ Gender : chr "Male" "Female" "Male" "Female" ...
## $ Membership : chr "Gold" "Silver" "Gold" "None" ...
## $ Category : chr "Grocery" "Electronics" "Clothing" "Grocery" ...
## $ Quantity : num 10 1 3 8 2 5
## $ CostPrice : num 50 20000 800 60 18000 700
## $ SellingPrice: num 70 25000 1000 80 22000 900
## $ Discount : num 100 2000 150 50 500 300
## $ DeliveryType: chr "Home" "Store" "Home" "Store" ...
summary(sales)
## BillID CustomerName Gender Membership
## Min. :501.0 Length:6 Length:6 Length:6
## 1st Qu.:502.2 Class :character Class :character Class :character
## Median :503.5 Mode :character Mode :character Mode :character
## Mean :503.5
## 3rd Qu.:504.8
## Max. :506.0
## Category Quantity CostPrice SellingPrice
## Length:6 Min. : 1.000 Min. : 50 Min. : 70
## Class :character 1st Qu.: 2.250 1st Qu.: 220 1st Qu.: 285
## Mode :character Median : 4.000 Median : 750 Median : 950
## Mean : 4.833 Mean : 6602 Mean : 8175
## 3rd Qu.: 7.250 3rd Qu.:13700 3rd Qu.:16750
## Max. :10.000 Max. :20000 Max. :25000
## Discount DeliveryType
## Min. : 50.0 Length:6
## 1st Qu.: 112.5 Class :character
## Median : 225.0 Mode :character
## Mean : 516.7
## 3rd Qu.: 450.0
## Max. :2000.0
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
## 1 70 100 Home
## 2 25000 2000 Store
## 3 1000 150 Home
## 4 80 50 Store
## 5 22000 500 Home
## 6 900 300 Home
sales$GrossRevenue <- sales$Quantity * sales$SellingPrice
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
## 1 70 100 Home 700
## 2 25000 2000 Store 25000
## 3 1000 150 Home 3000
## 4 80 50 Store 640
## 5 22000 500 Home 44000
## 6 900 300 Home 4500