Slicing with start:stop:step in NumPy - Step-by-Step Execution

Concept Flow - Slicing with start:stop:step

Start with array

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Apply slice start:stop:step

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Calculate indices from start to stop by step

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Extract elements at these indices

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Return sliced array

We take an array, pick elements starting at 'start', up to but not including 'stop', stepping by 'step', and return those elements.

Execution Sample

NumPy

import numpy as np
arr = np.array([10,20,30,40,50,60])
slice_arr = arr[1:5:2]
print(slice_arr)

This code slices the array from index 1 to 4 stepping by 2, extracting elements at indices 1 and 3.

Execution Table

Step	Action	Indices Calculated	Elements Selected	Resulting Slice
1	Start with array	-	[10, 20, 30, 40, 50, 60]	[10, 20, 30, 40, 50, 60]
2	Apply slice 1:5:2	Indices 1, 3	-	-
3	Extract elements at indices	-	[20, 40]	-
4	Return sliced array	-	-	[20, 40]

💡 Slicing stops before index 5; step 2 selects indices 1 and 3.

Variable Tracker

Variable	Start	After slice
arr	[10, 20, 30, 40, 50, 60]	[10, 20, 30, 40, 50, 60]
slice_arr	N/A	[20, 40]

Key Moments - 3 Insights

Why does the slice stop before index 5 and not include it?

In slicing, the stop index is exclusive, so elements are taken up to but not including index 5, as shown in execution_table step 2.

What happens if the step is negative?

A negative step means slicing goes backward. Indices are calculated from start down to stop+1, stepping backward. This changes which elements are selected.

What if start or stop is omitted?

If start is omitted, slicing starts at the beginning (index 0). If stop is omitted, slicing goes to the end of the array. Step defaults to 1 if omitted.

Visual Quiz - 3 Questions

Look at the execution table, what elements are selected at step 3?

A [30, 50]

B [10, 30]

C [20, 40]

D [40, 60]

💡 Hint

Check the 'Elements Selected' column in execution_table row 3.

At which step does the slicing calculate the indices to use?

A Step 2

B Step 1

C Step 3

D Step 4

💡 Hint

Look at the 'Indices Calculated' column in execution_table.

If the step was changed to 1, how would the resulting slice change?

A [10, 20, 30, 40]

B [20, 30, 40, 50]

C [20, 40]

D [30, 50, 60]

💡 Hint

Step 1 means selecting every element from start to stop-1, check variable_tracker for slice_arr.

Concept Snapshot

Slicing syntax: array[start:stop:step]
- start: index to begin (inclusive)
- stop: index to end (exclusive)
- step: how many indices to jump
Defaults: start=0, stop=array length, step=1
Returns a new array with selected elements.

Full Transcript

We start with a numpy array. When we slice with start:stop:step, numpy calculates indices from start up to but not including stop, jumping by step. Then it extracts elements at those indices and returns them as a new array. For example, arr[1:5:2] picks elements at indices 1 and 3. The stop index is exclusive, so index 5 is not included. If step is negative, slicing goes backward. Omitting start or stop uses defaults: start at 0, stop at array end. This slicing method is a quick way to pick parts of an array.