Indexing with ellipsis in NumPy - Mini Project: Build & Apply

Indexing with Ellipsis in NumPy

📖 Scenario: You work with multi-dimensional data arrays, like images or sensor data. Sometimes you want to select parts of these arrays without writing long index lists.

🎯 Goal: Learn how to use the ellipsis ... in NumPy indexing to select data easily from multi-dimensional arrays.

📋 What You'll Learn

Create a 3D NumPy array with specific values

Define an index variable using ellipsis

Use the ellipsis to select a slice from the array

Print the selected slice

💡 Why This Matters

🌍 Real World

Ellipsis helps when working with images, videos, or sensor data that have many dimensions. It makes selecting parts of data easier and your code cleaner.

💼 Career

Data scientists and analysts often handle multi-dimensional data. Knowing how to use ellipsis in NumPy indexing saves time and reduces errors in data selection.

1

Create a 3D NumPy array

Import NumPy as np and create a 3D NumPy array called data with shape (2, 3, 4) containing these exact values: [[[ 1, 2, 3, 4], [ 5, 6, 7, 8], [ 9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]].

NumPy

import numpy as np
# Create the 3D array 'data' with the exact values
# Your code here

Need a hint?

Use np.array() with nested lists to create the 3D array.

2

Define an ellipsis index variable

Create a variable called index and set it to the ellipsis ....

NumPy

import numpy as np
data = np.array([[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]])
# Create a variable 'index' and assign it the ellipsis ...
# Your code here

Need a hint?

The ellipsis is written as three dots ....

3

Use ellipsis to select the last row in each 2D slice

Use the variable index with the ellipsis to select the last row (index 2) from each 2D slice of data. Store the result in a variable called selected. Use the syntax data[index, 2, :].

NumPy

import numpy as np
data = np.array([[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]])
index = ...
# Use 'index' with ellipsis to select the last row (index 2) from each 2D slice
# Store it in 'selected'
# Your code here

Need a hint?

The ellipsis replaces the first dimension selector, so you only specify the last two indices.

4

Print the selected slice

Print the variable selected to display the selected rows from the array.

NumPy

import numpy as np
data = np.array([[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]])
index = ...
selected = data[index, 2, :]
# Print the 'selected' variable
# Your code here

Need a hint?

Use print(selected) to show the result.