Boolean indexing in NumPy - Mini Project: Build & Apply

Boolean Indexing with NumPy Arrays

📖 Scenario: You are working with a list of daily temperatures recorded over a week. You want to find which days were warmer than a certain temperature to plan outdoor activities.

🎯 Goal: Build a program that uses NumPy boolean indexing to select temperatures above a threshold.

📋 What You'll Learn

Create a NumPy array with exact temperature values

Create a threshold variable for temperature

Use boolean indexing to select temperatures above the threshold

Print the selected temperatures

💡 Why This Matters

🌍 Real World

Filtering data based on conditions is common in weather analysis, finance, and health monitoring to focus on important values.

💼 Career

Data scientists often use boolean indexing to quickly select relevant data points for analysis and visualization.

1

Create the temperature data array

Import NumPy as np and create a NumPy array called temps with these exact values: 22, 19, 25, 20, 18, 24, 21.

NumPy

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

Need a hint?

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

2

Set the temperature threshold

Create a variable called threshold and set it to the integer 20.

NumPy

import numpy as np
temps = np.array([22, 19, 25, 20, 18, 24, 21])
# Create the threshold variable and set it to 20
# Your code here

Need a hint?

Just assign the number 20 to a variable named threshold.

3

Select temperatures above the threshold using boolean indexing

Create a variable called warm_days that uses boolean indexing on temps to select only the temperatures greater than threshold.

NumPy

import numpy as np
temps = np.array([22, 19, 25, 20, 18, 24, 21])
threshold = 20
# Use boolean indexing to create warm_days with temps greater than threshold
# Your code here

Need a hint?

Use temps > threshold inside the brackets to filter the array.

4

Print the warm temperatures

Print the variable warm_days to display the temperatures above the threshold.

NumPy

import numpy as np
temps = np.array([22, 19, 25, 20, 18, 24, 21])
threshold = 20
warm_days = temps[temps > threshold]
# Print warm_days
# Your code here

Need a hint?

Use print(warm_days) to show the filtered temperatures.