# How to find Profit or loss using Python when CP of N items is equal to SP of M

In this article, we will learn a python program to find the profit or loss when the cost price CP of N items is equal to the selling price SP of M items.

Assume we have taken N, and M values which represent the cost price of N items are equal to the selling price of M items. We will now calculate the profit or loss percentage.

### Formula

profit/loss = ( (Cost Price) - (Selling Price) ) / (Selling Price) * 100


## What is the Selling Price(SP)?

The price a consumer pays to purchase a product or a commodity is known as the selling price. It is a price that is higher than the cost price and also includes a portion of the profit.

## What is the Cost Price(CP)?

Cost price is the cost at which the seller buys the product or the commodity. He follows that by adding a portion of gain or profits.

## What are Profit and Loss?

The amount gained from selling an item for more than its cost price is known as the profit.

Profit = Selling Price – Cost Price.


Loss is the amount lost by selling an item for less than its cost price.

Loss = Cost Price - Selling Price


### Algorithm (Steps)

Following are the Algorithms/steps to be followed to perform the desired task. −

• Create a function findProfitOrLoss() to calculate profit or loss percentage when the CP(cost price) of 'n' items is equal to the SP (selling price) of 'm' items by accepting the n, m values as arguments.

• Use the if conditional statement to check whether the n and m values are equal with the == operator.

• Print "Neither profit nor loss!!!" if the condition is true.

• Else calculate the profit or loss percentage.

• Create a variable to store profit/loss percentage results.

• Calculate the value of profit or loss by substituting the cost and selling prices to the above formula with the help of the abs() function(calculates the absolute value of a number passed)

• If the cost price is greater than the selling price then it is the case of loss then print the loss percentage.

• Else print the profit percentage.

• Create a variable to store the input n value.

• Create another variable to store the input m value.

• Call the above-defined findProfitOrLoss() function by passing n, m values to it to print the profit or loss percentage.

### Example

The following program returns the profit or loss percentage from the n, m input values using the above-given formula −

# creating a function to calculate profit or loss %
# when CP of 'n' items is equal to the SP of 'm' items
# by accepting the n, m values as arguments
def findProfitOrLoss(n, m):
# checking whether the value of n, m are equal
if (n == m):
# printing "Neither profit nor loss!!!" if the condition is true
print("Neither profit nor loss!!!")
else:
# variable to store profit/loss result
output = 0.0
# Calculating value of profit/loss
output = float(abs(n - m)) / m
#  checking whether n-m value value is less than 0
if (n - m < 0):
# printing the loss percentage upto 4 digits after decimals
print("The Loss percentage is: -",
'{0:.4}' .format(output * 100), "%")
else:
# printing the profit percentage upto 4 digits after decimals
print("The Profit percentage is: ", '{0:.6}' .
format(output * 100), "%")
# input n value
n = 10
# input m value
m = 7
# calling the above defined findProfitOrLoss() function
# by passing n, m values to it to print the profit or loss percentage
findProfitOrLoss(n, m)


### Output

On execution, the above program will generate the following output −

The Profit percentage is:  42.8571 %


Time Complexity − O(1)

Auxiliary Space − O(1)

We substituted the numbers in the formula such that there are no loops to traverse, hence it just takes linear time, i.e. O(1) Time Complexity.

## Conclusion

In this article, we learned how to use Python to calculate profit or loss when the cost price of N items equals the selling price of M items. This solution was implemented using a linear time complexity approach. We also learned how to use the format() function to format the float integer to n digits.

Updated on: 24-Jan-2023

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