Slicing with start:stop:step in NumPy - Mini Project: Build & Apply

Slicing NumPy Arrays with start:stop:step

📖 Scenario: Imagine you have a list of daily temperatures recorded over two weeks. You want to analyze specific parts of this data by selecting certain days using slicing.

🎯 Goal: Learn how to use start:stop:step slicing on a NumPy array to select specific elements.

📋 What You'll Learn

Create a NumPy array with exact temperature values

Define slicing parameters as variables

Use slicing with start:stop:step on the array

Print the sliced array

💡 Why This Matters

🌍 Real World

Slicing data arrays is common when analyzing time series data like temperatures, stock prices, or sensor readings to focus on specific intervals.

💼 Career

Data scientists and analysts often use slicing to quickly extract relevant parts of datasets for visualization or further analysis.

1

Create the NumPy array of temperatures

Import NumPy as np and create a NumPy array called temps with these exact values: [22, 21, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34]

NumPy

import numpy as np
# Create the NumPy array called temps with the given values
# Your code here

Hint

Use np.array([...]) to create the array with the exact temperature values.

2

Set slicing parameters

Create three variables: start set to 2, stop set to 12, and step set to 3.

NumPy

import numpy as np
temps = np.array([22, 21, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34])
# Create variables start=2, stop=12, step=3
# Your code here

Hint

Assign the numbers 2, 12, and 3 to variables named start, stop, and step respectively.

3

Slice the array using start:stop:step

Create a new variable called sliced_temps that slices the temps array using the variables start, stop, and step with the syntax temps[start:stop:step].

NumPy

import numpy as np
temps = np.array([22, 21, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34])
start = 2
stop = 12
step = 3
# Slice temps using start:stop:step and assign to sliced_temps
# Your code here

Hint

Use the slicing syntax with the variables: temps[start:stop:step].

4

Print the sliced array

Print the variable sliced_temps to display the sliced temperatures.

NumPy

import numpy as np
temps = np.array([22, 21, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34])
start = 2
stop = 12
step = 3
sliced_temps = temps[start:stop:step]
# Print sliced_temps
# Your code here

Hint

Use print(sliced_temps) to show the result.

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