Slicing with start:stop:step in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the slicing notation start:stop:step mean in numpy arrays?

It means to select elements from the array starting at index start, up to but not including stop, taking every stepth element.

beginner

What happens if you omit start in start:stop:step slicing?

If start is omitted, slicing starts from the beginning of the array (index 0).

intermediate

How does a negative step value affect slicing in numpy?

A negative step means slicing goes backwards, selecting elements in reverse order.

beginner

Given arr = np.array([10, 20, 30, 40, 50]), what does arr[1:4:2] return?

It returns array([20, 40]) because it starts at index 1 (20), goes up to index 4 (not including 4), taking every 2nd element.

beginner

What is the result of arr[::-1] for a numpy array arr?

It returns the array reversed, selecting all elements with a step of -1.

In numpy slicing arr[start:stop:step], what does stop represent?

A The last element included in the slice

B The step size between elements

C The number of elements to select

D The index where slicing stops, not including this index

The stop index is where slicing stops, but this index is not included in the result.

What does arr[::2] do?

A Selects every second element from the start to the end

B Selects elements in reverse order

C Selects elements from index 2 to the end

D Selects elements from index 0 to 2

Omitting start and stop means the whole array is sliced, taking every 2nd element.

What is the output of arr[3:0:-1] for arr = np.array([5,10,15,20,25])?

A [20 15 10 5]

B [20 15 10]

C [25 20 15]

D [20 15]

Starts at index 3 (20), goes backwards to index 1 (not including 0), stepping -1.

If step is negative, what must be true about start and stop?

A <code>start</code> equals <code>stop</code>

B <code>start</code> must be less than <code>stop</code>

C <code>start</code> must be greater than <code>stop</code>

D No relation needed

When stepping backwards, slicing moves from a higher index to a lower index.

What does arr[:] do?

A Returns a copy of the whole array

B Returns an empty array

C Returns elements from index 1 to end

D Returns elements from index 0 to 1

Omitting start, stop, and step returns the whole array as a slice (a view or copy).

Explain how slicing with start:stop:step works in numpy arrays.

Think about how you pick items from a list skipping some.

Describe what happens when you use a negative step in numpy slicing and give an example.

Imagine reading a list from the end to the start.