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

Need a 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

Need a 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

Need a 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

Need a hint?

Use print(sliced_temps) to show the result.