Slicing with start:stop:step in NumPy

Introduction

Slicing helps you pick parts of data easily. Using start:stop:step lets you choose where to begin, where to end, and how to jump through the data.

You want to get every other number from a list of measurements.

You need to extract a specific range of days from a time series.

You want to reverse the order of data points in an array.

You want to sample data points at regular intervals for analysis.

Syntax

NumPy

array[start:stop:step]

start is where slicing begins (inclusive). If omitted, it starts at the beginning.

stop is where slicing ends (exclusive). If omitted, it goes to the end.

step is how many steps to jump. If omitted, it defaults to 1.

Examples

Gets elements from index 1 up to but not including 4: [20 30 40]

NumPy

arr = np.array([10, 20, 30, 40, 50])
slice1 = arr[1:4]
print(slice1)

Gets every second element from the whole array: [10 30 50]

NumPy

arr = np.array([10, 20, 30, 40, 50])
slice2 = arr[::2]
print(slice2)

Gets elements from index 4 down to 2 in reverse order: [50 40 30]

NumPy

arr = np.array([10, 20, 30, 40, 50])
slice3 = arr[4:1:-1]
print(slice3)

Sample Program

This program shows how to slice a numpy array using start, stop, and step. It extracts parts of the array and prints them.

NumPy

import numpy as np

# Create an array of numbers from 0 to 9
arr = np.arange(10)

# Slice from index 2 to 7 (exclusive), stepping by 2
slice_a = arr[2:7:2]

# Slice the whole array, but every 3rd element
slice_b = arr[::3]

# Reverse the array
slice_c = arr[::-1]

print('Original array:', arr)
print('Slice 2 to 7 step 2:', slice_a)
print('Every 3rd element:', slice_b)
print('Reversed array:', slice_c)

Important Notes

If step is negative, slicing goes backward.

Leaving start or stop empty means start from the beginning or go until the end.

Summary

Slicing with start:stop:step lets you pick parts of an array easily.

You can skip elements by setting step greater than 1.

Negative step reverses the direction of slicing.

Practice

1. What does the step value control in a NumPy array slice like arr[start:stop:step]?

easy

A. How many elements to skip between each selected element

B. The total number of elements to select

C. The starting index of the slice

D. The ending index of the slice

Solution

1. Step 1: Understand the slice syntax

   The slice arr[start:stop:step] selects elements from start up to but not including stop, moving by step.

2. Step 2: Identify the role of step

   The step determines how many elements to skip between each selected element. For example, step=2 picks every second element.

3. Final Answer:

   How many elements to skip between each selected element -> Option A

4. Quick Check:

   Step controls skipping elements = A [OK]

Hint: Step is the gap between elements in slicing [OK]

Common Mistakes:

• Confusing step with start or stop index
• Thinking step is total count of elements
• Ignoring that step can be negative

2. Which of the following is the correct syntax to slice a NumPy array arr to get every 3rd element from index 1 to 10?

easy

A. arr[10:1:3]

B. arr[1:3:10]

C. arr[1:10:3]

D. arr[3:1:10]

Solution

1. Step 1: Recall slice order

   The slice syntax is arr[start:stop:step]. Here, start=1, stop=10, step=3 means from index 1 up to 9, every 3rd element.

2. Step 2: Check each option

   arr[1:10:3] matches the correct order and values. Others have wrong order or values that don't match the requirement.

3. Final Answer:

   arr[1:10:3] -> Option C

4. Quick Check:

   Correct slice syntax = D [OK]

Hint: Remember slice is start:stop:step in order [OK]

Common Mistakes:

• Mixing up stop and step positions
• Using step as stop index
• Reversing start and stop incorrectly

3. Given arr = np.array([10, 20, 30, 40, 50, 60, 70]), what is the output of arr[1:6:2]?

medium

A. [10 30 50 70]

B. [20 30 40 50 60]

C. [30 50]

D. [20 40 60]

Solution

1. Step 1: Identify slice indices

   The slice arr[1:6:2] starts at index 1 (value 20), stops before index 6, stepping by 2.

2. Step 2: Select elements

   Indexes selected: 1 (20), 3 (40), 5 (60). So output is [20 40 60].

3. Final Answer:

   [20 40 60] -> Option D

4. Quick Check:

   Elements at 1,3,5 = [20 40 60] [OK]

Hint: Pick elements at start, start+step, ... until stop-1 [OK]

Common Mistakes:

• Including stop index element
• Using wrong step size
• Starting from index 0 instead of 1

4. What is wrong with this code snippet?
arr = np.array([1,2,3,4,5])
slice = arr[4:1:-1]
What will slice contain?

medium

A. [4 3 2]

B. [5 4 3]

C. Empty array

D. IndexError

Solution

1. Step 1: Understand negative step slicing

   With step=-1, slicing goes backwards from start index 4 down to stop index 1 (exclusive).

2. Step 2: Identify elements selected

   Indexes selected: 4 (5), 3 (4), 2 (3). So slice contains [5 4 3].

3. Final Answer:

   [5 4 3] -> Option B

4. Quick Check:

   Backward slice from 4 to 2 = [5 4 3] [OK]

Hint: Negative step slices backward, stop is exclusive [OK]

Common Mistakes:

• Expecting forward slice with negative step
• Including stop index element
• Thinking it causes error

5. You have a NumPy array arr = np.arange(20). How would you slice it to get every 4th element in reverse order starting from the last element?

hard

A. arr[19::-4]

B. arr[::4]

C. arr[19:0:4]

D. arr[0:19:-4]

Solution

1. Step 1: Understand array and goal

   arr = np.arange(20) creates array from 0 to 19. We want every 4th element backward starting from last element (index 19).

2. Step 2: Check slicing options

   arr[19::-4] starts at index 19, goes backward to start (index 0), stepping by 4, which matches the goal.

3. Step 3: Verify other options

   A: arr[::4] every 4th forward [0,4,8,...], wrong direction. C: arr[19:0:4] positive step with start>stop gives empty. D: arr[0:19:-4] start<stop with negative step gives empty.

4. Final Answer:

   arr[19::-4] -> Option A

5. Quick Check:

   Reverse every 4th from last = arr[19::-4] [OK]

Hint: Use start index with negative step for reverse slicing [OK]

Common Mistakes:

• Using positive step with decreasing indices
• Wrong start or stop indices
• Assuming arr[::-4] always starts at last element