reshape() for changing dimensions in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the reshape() function do in NumPy?

It changes the shape or dimensions of an existing array without changing its data.

beginner

How do you reshape a 1D array of 6 elements into a 2D array with 2 rows and 3 columns?

Use array.reshape(2, 3) where array is your original 1D array.

intermediate

What happens if you try to reshape an array into a shape that does not match the total number of elements?

NumPy will raise an error because the total number of elements must remain the same.

intermediate

What does using -1 in the reshape dimensions mean?

It tells NumPy to automatically calculate that dimension based on the array size and other given dimensions.

beginner

Can reshape() change the total number of elements in the array?

No, reshape() only changes the shape, not the total number of elements.

What will np.array([1,2,3,4,5,6]).reshape(3,2) produce?

A A 1D array with 6 elements

B A 3x2 array with elements [[1,2],[3,4],[5,6]]

C An error because the shape is invalid

D A 2x3 array with elements [[1,2,3],[4,5,6]]

The reshape changes the 1D array into 3 rows and 2 columns.

What does reshape(-1, 1) do to a 1D array?

A Raises an error

B Converts it to a 2D row vector

C Flattens the array

D Converts it to a 2D column vector

Using -1 lets NumPy calculate the number of rows, making it a column vector.

If an array has 12 elements, which reshape is invalid?

A reshape(5,3)

B reshape(3,4)

C reshape(2,6)

D reshape(4,3)

5x3=15 which does not match 12 elements, so it is invalid.

What must remain the same before and after using reshape()?

A The data type

B The shape of the array

C The total number of elements

D The memory address

Reshape only changes dimensions, not the total number of elements.

Which of these is a valid way to reshape an array arr with 8 elements?

A arr.reshape(2, 4)

B arr.reshape(3, 3)

C arr.reshape(4, 3)

D arr.reshape(5, 2)

2x4=8 matches the total elements, so it is valid.

Explain how the reshape() function works in NumPy and why the total number of elements must stay the same.

Think about how you can rearrange items in boxes without adding or removing items.

Describe how using -1 in reshape helps when changing array dimensions.

It’s like telling NumPy: 'You figure out this size for me.'