Why array processing matters in NumPy - See It in Action

Why array processing matters

📖 Scenario: Imagine you work in a grocery store. You have a list of prices for different fruits. You want to quickly find out the total cost if you buy one of each fruit. Doing this one by one is slow. Using arrays helps you do this fast and easily.

🎯 Goal: You will create a list of fruit prices, convert it to a NumPy array, and then calculate the total cost using array processing. This shows why array processing matters for fast and simple calculations.

📋 What You'll Learn

Create a list of fruit prices

Convert the list to a NumPy array

Calculate the total cost using array sum

Print the total cost

💡 Why This Matters

🌍 Real World

Stores and businesses often need to quickly calculate totals for many items. Using arrays helps them do this efficiently.

💼 Career

Data scientists and analysts use array processing to handle large datasets and perform fast calculations in many industries.

1

Create a list of fruit prices

Create a list called fruit_prices with these exact values: 1.2, 0.5, 2.0, 1.5, 0.8

NumPy

# Create the list fruit_prices with the given values
# Your code here

Need a hint?

Use square brackets to create a list and separate values with commas.

2

Convert the list to a NumPy array

Import NumPy as np and create a NumPy array called prices_array from the list fruit_prices

NumPy

fruit_prices = [1.2, 0.5, 2.0, 1.5, 0.8]
# Import numpy as np and convert fruit_prices to prices_array
# Your code here

Need a hint?

Use np.array() to convert a list to a NumPy array.

3

Calculate the total cost using array sum

Use the NumPy array prices_array and create a variable called total_cost that stores the sum of all prices using np.sum()

NumPy

import numpy as np
fruit_prices = [1.2, 0.5, 2.0, 1.5, 0.8]
prices_array = np.array(fruit_prices)
# Calculate total_cost by summing prices_array
# Your code here

Need a hint?

Use np.sum() to add all elements in the array.

4

Print the total cost

Print the variable total_cost to display the total price of all fruits

NumPy

import numpy as np
fruit_prices = [1.2, 0.5, 2.0, 1.5, 0.8]
prices_array = np.array(fruit_prices)
total_cost = np.sum(prices_array)
# Print the total_cost
# Your code here

Need a hint?

Use print(total_cost) to show the result.