Boolean indexing for filtering in NumPy - Mini Project: Build & Apply

Boolean indexing for filtering

📖 Scenario: Imagine you have a list of daily temperatures recorded in a city. You want to find out which days were warm, meaning the temperature was above 20 degrees Celsius.

🎯 Goal: You will create a NumPy array of temperatures, set a threshold for warm days, use boolean indexing to filter the warm days, and then display those warm temperatures.

📋 What You'll Learn

Create a NumPy array called temperatures with the exact values: 15, 22, 19, 24, 18, 30, 21

Create a variable called warm_threshold and set it to 20

Use boolean indexing with temperatures and warm_threshold to create a new array called warm_days containing only temperatures above the threshold

Print the warm_days array

💡 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 and analyze subsets of data without loops, making their code faster and cleaner.

1

Create the temperatures array

Import NumPy as np and create a NumPy array called temperatures with these exact values: 15, 22, 19, 24, 18, 30, 21

NumPy

import numpy as np
# Create the temperatures array with the given values
# Your code here

Need a hint?

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

2

Set the warm day threshold

Create a variable called warm_threshold and set it to the number 20

NumPy

import numpy as np

temperatures = np.array([15, 22, 19, 24, 18, 30, 21])
# Set warm_threshold to 20
# Your code here

Need a hint?

Just assign the number 20 to the variable warm_threshold.

3

Filter warm days using boolean indexing

Use boolean indexing with temperatures and warm_threshold to create a new NumPy array called warm_days that contains only the temperatures greater than warm_threshold

NumPy

import numpy as np

temperatures = np.array([15, 22, 19, 24, 18, 30, 21])

warm_threshold = 20
# Create warm_days using boolean indexing
# Your code here

Need a hint?

Use temperatures > warm_threshold inside the square brackets to filter.

4

Print the warm days

Print the warm_days array to display the temperatures above the threshold

NumPy

import numpy as np

temperatures = np.array([15, 22, 19, 24, 18, 30, 21])

warm_threshold = 20

warm_days = temperatures[temperatures > warm_threshold]
# Print warm_days
# Your code here

Need a hint?

Use print(warm_days) to show the filtered temperatures.