profitmus_prime.py

import pandas as pd
import seaborn as sns
import numpy as np
sales_data = pd.read_csv('datasets/Vendor_Data.csv')
# print(sales_data.columns)
# print(sales_data.head())
'''

flag = 0
increment_i <- increment
#flag = 1 is a condition when the increment vector remains the same
while (flag == 0) {
print(find_rev(increment_i))
increment_iplus1 <- incremental_new(increment_i)
if (min(increment_iplus1 == increment_i) == 1) {flag = 1}
increment_i <- increment_iplus1
}
increment_i
find_rev(increment_i)
/find_rev(increment)
price <- increment_i
write.csv(price,"price.csv")

#This function tries to get the next best increment vector
incremental_new <- function(initial_increments){
initial_rev <- find_rev(initial_increments)
intermediate_rev <- 0
for(i in 1:250){
increments <- initial_increments
if(increments[i] > -0.099) {increments[i] <- increments[i] - 0.01}
rev <- find_rev(increments)
if (rev > initial_rev) {final_increments <- increments
intermediate_rev <- rev
}
if(increments[i] < 0.19) {increments[i] <- initial_increments[i] + 0.01}
rev <- find_rev(increments)
if (rev > max(initial_rev,intermediate_rev)) {final_increments <- increments}
}
return(final_increments)
}
# This function will get us the overall revenue for the given increment vector
find_rev <- function(increment){
price <- data$Avg_Price_per_unit*(1+increment)
volumes <- data$Average_units_sold*(1-(data$Increase_sale_volume*increment*10))
multiplier <- (1-(data$Incremental_acquisition*increment*10))
total_multiplier <- prod(multiplier)
profit_wo_multiplier <- 0.05*(sum(price*volumes) - sum(volumes*data$Cost_per_unit))
profit_w_multiplier <- profit_wo_multiplier*total_multiplier
net_profit <- sum(profit_w_multiplier)
return(net_profit)}

'''
increament = np.zeros((250), dtype=int)
flag = 0
increament_i = increament
while flag==0:
    print(find_rev(increment_i))
    increment_iplus1 = incremental_new(increment_i)
    if (min(increment_iplus1 == increment_i) == 1):
        flag = 1
    increment_i = increment_iplus1