Numpy Python Mini projects: Expense Tracker

               Expense tracker is one of the important applications in Numpy. It tracks the daily expenses, calculates the highest, lowest, average and total expenses.

Let us implement the expense tracker in numpy.

Implementation:

• First, built-in numpy library is included. It creates an array to read the input from the user.
• Print the array of elements.
• Next, total expenses are calculated by adding all elements in the array using sum() function.
• To find the ‘Average’ value by using mean() function in the numpy package.
• Other functions are included as follows.
• ‘max()’: it gives you the maximum value.
• ‘min()’: it finds the minimum value.
• It also checks the expense value is greater than 150 and calculates the sum and prints it.

Code:

import numpy as np1

# Let us create daily expenses

s_expenses = np1.array(list(map(int, input("Enter the weekly expenses separated by space: ").split())))

print("Expenses of the week:", s_expenses)

# Total expense calculation

total = np1.sum(s_expenses)

print("\nTotal Expense of the week: ₹", total)

# Find the Average expense

average = np1.mean(s_expenses)

print("Average Expense of the week: ₹", average)

# Maximum expense calculation

maximum = np1.max(s_expenses)

print("Highest Expense of the week: ₹", maximum)

# Minimum expense calculation

minimum = np1.min(s_expenses)

print("Lowest Expense of the week: ₹", minimum)

# Expenses greater than ₹150

high_expenses = s_expenses[s_expenses > 150]

print("\nExpenses Above ₹150:", high_expenses)

# Number of days with expenses above ₹150

count = np1.sum(s_expenses > 150)

print("Days Above ₹150:", count)

Output:

Enter the weekly expenses separated by space: 120 210 180 300 75 160 250 90

Expenses of the week: [120 210 180 300  75 160 250  90]

Total Expense of the week: ₹ 1385

Average Expense of the week: ₹ 173.125

Highest Expense of the week: ₹ 300

Lowest Expense of the week: ₹ 75

Expenses Above ₹150: [210 180 300 160 250]

Days Above ₹150: 5

That’s all. The Python Numpy program to implement the expense tracker was done successfully. Keep doing!!!