Matrix transpose operations in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the transpose of a matrix do?

It flips the matrix over its diagonal, switching the row and column indices of each element.

beginner

How do you transpose a matrix using NumPy?

Use the .T attribute on a NumPy array, like matrix.T.

beginner

What is the shape of the transpose of a matrix with shape (3, 5)?

The transpose will have shape (5, 3), swapping rows and columns.

beginner

True or False: Transposing a matrix twice returns the original matrix.

True. Transposing twice flips the matrix back to its original form.

intermediate

How can you transpose a 3D NumPy array along specific axes?

Use np.transpose(array, axes=(...)) to reorder axes as needed.

What does matrix.T do in NumPy?

A Returns the matrix multiplied by 2

B Returns the inverse of the matrix

C Returns the determinant of the matrix

D Returns the transpose of the matrix

matrix.T flips the matrix over its diagonal, swapping rows and columns.

If a matrix has shape (4, 7), what is the shape of its transpose?

A (7, 4)

B (4, 7)

C (1, 28)

D (28, 1)

Transposing swaps rows and columns, so (4, 7) becomes (7, 4).

Which NumPy function allows transposing with custom axis order?

A np.transpose()

B np.reshape()

C np.flatten()

D np.dot()

np.transpose() lets you specify axes order for transposing arrays.

What happens if you transpose a matrix twice?

A You get the inverse matrix

B You get a zero matrix

C You get the original matrix

D You get a matrix with doubled values

Transposing twice returns the matrix to its original form.

Which of these is NOT true about matrix transpose?

A It swaps rows and columns

B It multiplies each element by -1

C It flips the matrix over its diagonal

D It changes the shape of the matrix

Transpose does not change element values, only their positions.

Explain how to transpose a 2D matrix in NumPy and describe what happens to its shape.

Think about flipping the matrix over its diagonal.

Describe how to transpose a 3D NumPy array along specific axes and why this might be useful.

Consider how axes represent dimensions in arrays.