Indexing returns views not copies in NumPy - Mini Project: Build & Apply

Indexing Returns Views Not Copies in NumPy

📖 Scenario: Imagine you have a list of daily temperatures for a week stored in a NumPy array. You want to look at just the middle three days and see how changing those values affects the original data.

🎯 Goal: You will create a NumPy array of temperatures, select a slice of it, modify the slice, and observe how the original array changes because indexing returns a view, not a copy.

📋 What You'll Learn

Create a NumPy array called temps with these exact values: [20, 22, 19, 23, 21, 18, 20]

Create a variable called mid_week that selects the middle three days from temps using slicing

Change the first value in mid_week to 25

Print the temps array to show the change

💡 Why This Matters

🌍 Real World

Understanding views vs copies helps when working with large datasets to avoid unexpected changes and save memory.

💼 Career

Data scientists often manipulate data slices; knowing when changes affect original data prevents bugs and improves efficiency.

1

Create the temperatures array

Create a NumPy array called temps with these exact values: [20, 22, 19, 23, 21, 18, 20]

NumPy

# Create the temps array with the given values
# Your code here

Need a hint?

Use np.array() to create the array with the exact values inside the brackets.

2

Select the middle three days

Create a variable called mid_week that selects the middle three days from temps using slicing with temps[2:5]

NumPy

import numpy as np

temps = np.array([20, 22, 19, 23, 21, 18, 20])

# Select the middle three days from temps
# Your code here

Need a hint?

Use slicing with temps[2:5] to get the middle three days (index 2, 3, and 4).

3

Modify the slice

Change the first value in mid_week to 25 by assigning mid_week[0] = 25

NumPy

import numpy as np

temps = np.array([20, 22, 19, 23, 21, 18, 20])

mid_week = temps[2:5]

# Change the first value in mid_week to 25
# Your code here

Need a hint?

Assign 25 to the first element of mid_week using index 0.

4

Print the original array

Print the temps array using print(temps) to show how it changed after modifying mid_week

NumPy

import numpy as np

temps = np.array([20, 22, 19, 23, 21, 18, 20])

mid_week = temps[2:5]

mid_week[0] = 25

# Print the temps array
# Your code here

Need a hint?

Use print(temps) to display the updated array.