np.sort() for sorting arrays in NumPy - Mini Project: Build & Apply

Sorting Arrays with np.sort()

📖 Scenario: You work in a small shop that tracks daily sales numbers. You want to organize the sales data from smallest to largest to see trends easily.

🎯 Goal: Learn how to use np.sort() to sort a list of daily sales numbers in ascending order.

📋 What You'll Learn

Create a NumPy array with exact daily sales numbers

Use a variable to hold the sorted array

Use np.sort() to sort the array

Print the sorted array

💡 Why This Matters

🌍 Real World

Sorting sales data helps businesses quickly understand trends and make decisions.

💼 Career

Data scientists often sort data to prepare it for analysis and visualization.

1

Create the sales data array

Create a NumPy array called sales with these exact daily sales numbers: 250, 100, 300, 150, 200.

NumPy

import numpy as np
# Create the sales array with the exact numbers
# Your code here

Need a hint?

Use np.array() and put the numbers inside a list.

2

Prepare a variable for sorted sales

Create a variable called sorted_sales and set it to None for now.

NumPy

import numpy as np
sales = np.array([250, 100, 300, 150, 200])
# Create sorted_sales variable and set it to None
# Your code here

Need a hint?

Just write sorted_sales = None to create the variable.

3

Sort the sales array using np.sort()

Use np.sort() to sort the sales array and assign the result to sorted_sales.

NumPy

import numpy as np
sales = np.array([250, 100, 300, 150, 200])
sorted_sales = None
# Sort sales using np.sort() and assign to sorted_sales
# Your code here

Need a hint?

Call np.sort(sales) and save it in sorted_sales.

4

Print the sorted sales array

Print the sorted_sales array to see the sales numbers sorted from smallest to largest.

NumPy

import numpy as np
sales = np.array([250, 100, 300, 150, 200])
sorted_sales = np.sort(sales)
# Print the sorted_sales array
# Your code here

Need a hint?

Use print(sorted_sales) to display the sorted array.