np.einsum() for efficient computation in NumPy - Mini Project: Build & Apply

Using np.einsum() for Efficient Computation

📖 Scenario: Imagine you work in a small company that analyzes sales data. You have two sets of numbers: the quantity of items sold and the price per item. You want to find the total sales amount for each item quickly and efficiently.

🎯 Goal: You will learn how to use np.einsum() to multiply arrays element-wise and sum over specific axes, which is a fast way to do calculations like total sales.

📋 What You'll Learn

Create two numpy arrays with exact values

Define a configuration variable for the operation

Use np.einsum() with the correct subscripts to compute total sales

Print the resulting array showing total sales per item

💡 Why This Matters

🌍 Real World

In real business scenarios, fast and memory-efficient calculations like total sales help companies make quick decisions.

💼 Career

Data scientists and analysts often use <code>np.einsum()</code> to speed up numerical computations in data processing and machine learning.

1

Create the sales quantity and price arrays

Create a numpy array called quantities with values [2, 3, 5] representing items sold. Also create a numpy array called prices with values [10, 20, 30] representing price per item.

NumPy

# Create the numpy arrays quantities and prices
# Your code here

Need a hint?

Use np.array() to create arrays with the exact values given.

2

Define the einsum operation string

Create a string variable called operation and set it to 'i,i->' which tells np.einsum() to multiply elements of two 1D arrays and sum the result.

NumPy

import numpy as np
quantities = np.array([2, 3, 5])
prices = np.array([10, 20, 30])
# Define the einsum operation string
# Your code here

Need a hint?

The string 'i,i->' means multiply elements with index i from both arrays and sum all results.

3

Calculate total sales using np.einsum()

Use np.einsum() with the operation string and arrays quantities and prices to calculate the total sales amount. Store the result in a variable called total_sales.

NumPy

import numpy as np
quantities = np.array([2, 3, 5])
prices = np.array([10, 20, 30])
operation = 'i,i->'
# Calculate total_sales using np.einsum
# Your code here

Need a hint?

Call np.einsum() with the operation string and the two arrays in order.

4

Print the total sales amount

Print the variable total_sales to display the total sales amount.

NumPy

import numpy as np
quantities = np.array([2, 3, 5])
prices = np.array([10, 20, 30])
operation = 'i,i->'
total_sales = np.einsum(operation, quantities, prices)
# Print total_sales
# Your code here

Need a hint?

Use print(total_sales) to show the result.