np.newaxis for adding dimensions in NumPy - Mini Project: Build & Apply

Using np.newaxis to Add Dimensions in NumPy Arrays

📖 Scenario: Imagine you are working with data from a weather station. You have temperature readings for a week stored as a simple list. To prepare this data for a machine learning model, you need to add extra dimensions to the data array.

🎯 Goal: You will learn how to use np.newaxis to add new dimensions to a NumPy array. This helps reshape data for analysis or modeling.

📋 What You'll Learn

Create a NumPy array with exact temperature values

Create a variable to add a new axis

Use np.newaxis to add a dimension to the array

Print the reshaped array to see the new shape

💡 Why This Matters

🌍 Real World

Adding dimensions to arrays is common when preparing data for machine learning models, which often expect inputs in specific shapes.

💼 Career

Data scientists and analysts frequently reshape data arrays to fit model requirements or to perform broadcasting operations in NumPy.

1

Create the temperature data array

Create a NumPy array called temps with these exact temperature values: [22, 24, 19, 23, 25, 20, 21].

NumPy

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

Need a hint?

Use np.array() to create the array with the exact list of temperatures.

2

Create a variable for the new axis

Create a variable called axis and set it to np.newaxis.

NumPy

import numpy as np

temps = np.array([22, 24, 19, 23, 25, 20, 21])

# Create the variable 'axis' and set it to 'np.newaxis'
# Your code here

Need a hint?

Assign np.newaxis to the variable axis.

3

Add a new dimension to the array

Create a new array called temps_reshaped by adding a new axis to temps using the variable axis. Use temps[:, axis] to add a new dimension as a column vector.

NumPy

import numpy as np

temps = np.array([22, 24, 19, 23, 25, 20, 21])

axis = np.newaxis

# Use 'temps[:, axis]' to add a new dimension and create 'temps_reshaped'
# Your code here

Need a hint?

Use slicing with : and axis to add a new dimension.

4

Print the reshaped array

Print the variable temps_reshaped to see the array with the new dimension.

NumPy

import numpy as np

temps = np.array([22, 24, 19, 23, 25, 20, 21])

axis = np.newaxis

temps_reshaped = temps[:, axis]

# Print the reshaped array
# Your code here

Need a hint?

Use print(temps_reshaped) to display the reshaped array.