transpose() for swapping axes in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the transpose() function do in NumPy?

It swaps the axes of an array, effectively flipping its dimensions. For example, it turns rows into columns and vice versa.

beginner

How do you use transpose() to swap the first and second axes of a 2D array?

You can call array.transpose() without arguments to swap the two axes of a 2D array.

intermediate

What is the difference between transpose() and .T in NumPy?

.T is a shortcut for transpose() on arrays of two or more dimensions. Both swap axes, but transpose() can take arguments to reorder axes in higher dimensions.

intermediate

How can you use transpose() to reorder axes in a 3D array?

You pass a tuple with the new order of axes to transpose(). For example, array.transpose(1, 0, 2) swaps the first two axes but keeps the third the same.

beginner

Why is swapping axes useful in data science?

Swapping axes helps reshape data to fit algorithms, visualize data differently, or prepare data for operations that expect a certain shape.

What does array.transpose() do to a 2D NumPy array?

A Adds a new axis

B Flattens the array

C Deletes the array

D Swaps rows and columns

transpose() swaps the rows and columns of a 2D array.

How do you swap the first and second axes of a 3D array arr using transpose()?

A <code>arr.transpose(1, 0, 2)</code>

B <code>arr.transpose(0, 2, 1)</code>

C <code>arr.transpose(2, 1, 0)</code>

D <code>arr.transpose()</code>

Passing (1, 0, 2) swaps the first two axes and keeps the third axis unchanged.

Which attribute is a shortcut for transpose() on 2D arrays?

A <code>.T</code>

B <code>.shape</code>

C <code>.reshape</code>

D <code>.flatten</code>

.T is a quick way to transpose 2D arrays.

If you have a 2D array with shape (3, 5), what shape will it have after transpose()?

A (15,)

B (3, 5)

C (5, 3)

D (1, 15)

Transpose swaps the axes, so (3, 5) becomes (5, 3).

Why might you want to swap axes in a dataset?

A To encrypt data

B To change how data is organized for analysis or visualization

C To increase the size of data

D To delete data

Swapping axes helps organize data in a way that fits your analysis or visualization needs.

Explain in your own words what transpose() does to a NumPy array and give a simple example.

Think about rows and columns switching places.

Describe how you would use transpose() to reorder axes in a 3D array and why this might be useful.

Consider how data shape affects analysis.