flatten() and ravel() for 1D conversion in NumPy - Mini Project: Build & Apply

Using flatten() and ravel() to Convert Arrays to 1D

📖 Scenario: Imagine you have a small photo represented as a 2D array of pixel brightness values. You want to convert this 2D photo into a simple list of pixels to analyze or store it easily.

🎯 Goal: You will create a 2D NumPy array, then use flatten() and ravel() methods to convert it into 1D arrays. Finally, you will print the results to see the difference.

📋 What You'll Learn

Create a 2D NumPy array with exact values

Create a variable to hold the flattened array using flatten()

Create a variable to hold the raveled array using ravel()

Print both 1D arrays to compare

💡 Why This Matters

🌍 Real World

Converting images or tables of data into a simple list helps in machine learning and data analysis tasks where flat input is needed.

💼 Career

Data scientists often reshape data arrays to prepare them for models or visualization tools.

1

Create a 2D NumPy array

Import NumPy as np and create a 2D NumPy array called photo with these exact values: [[10, 20, 30], [40, 50, 60]]

NumPy

# Import numpy as np and create the 2D array photo
# Your code here

Need a hint?

Use np.array() to create the 2D array with the exact nested list.

2

Create a flattened 1D array

Create a variable called flat_photo by applying the flatten() method on the photo array

NumPy

import numpy as np
photo = np.array([[10, 20, 30], [40, 50, 60]])
# Create flat_photo using photo.flatten()
# Your code here

Need a hint?

Call flatten() on photo and assign it to flat_photo.

3

Create a raveled 1D array

Create a variable called ravel_photo by applying the ravel() method on the photo array

NumPy

import numpy as np
photo = np.array([[10, 20, 30], [40, 50, 60]])
flat_photo = photo.flatten()
# Create ravel_photo using photo.ravel()
# Your code here

Need a hint?

Call ravel() on photo and assign it to ravel_photo.

4

Print the flattened and raveled arrays

Print the variables flat_photo and ravel_photo each on its own line to see the 1D arrays

NumPy

import numpy as np
photo = np.array([[10, 20, 30], [40, 50, 60]])
flat_photo = photo.flatten()
ravel_photo = photo.ravel()
# Print flat_photo and ravel_photo
# Your code here

Need a hint?

Use two print() statements, one for each variable.