Why math functions matter in NumPy - See It in Action

Why math functions matter

📖 Scenario: Imagine you are a data analyst working with a small set of numbers representing daily temperatures in Celsius. You want to understand these numbers better by using math functions to find their square roots, squares, and absolute values. This helps you see the data in new ways and prepare it for further analysis.

🎯 Goal: You will create a list of temperatures, set up a configuration variable for a threshold, apply math functions from the numpy library to transform the data, and finally print the results.

📋 What You'll Learn

Create a list of temperatures with exact values

Create a threshold variable to compare values

Use numpy math functions: square root, square, and absolute value

Print the transformed data

💡 Why This Matters

🌍 Real World

Math functions help data scientists transform and understand data better. For example, square roots can normalize data, squares can emphasize larger values, and absolute values remove negative signs to focus on magnitude.

💼 Career

Knowing how to use math functions with numpy is essential for data cleaning, feature engineering, and preparing data for machine learning models.

1

Create the temperature data list

Create a list called temperatures with these exact values: 16, -9, 25, -4, 0.

NumPy

# Create the list temperatures with the exact values
# Your code here

Need a hint?

Use square brackets to create a list and separate numbers with commas.

2

Set a threshold value

Create a variable called threshold and set it to 10.

NumPy

temperatures = [16, -9, 25, -4, 0]
# Create the variable threshold and set it to 10
# Your code here

Need a hint?

Just assign the number 10 to the variable named threshold.

3

Apply numpy math functions

Import numpy as np. Then create three new lists: sqrt_temps with the square roots of the absolute values of temperatures, square_temps with the squares of temperatures, and abs_temps with the absolute values of temperatures.

NumPy

temperatures = [16, -9, 25, -4, 0]
threshold = 10
# Import numpy as np
# Create sqrt_temps, square_temps, and abs_temps using numpy functions
# Your code here

Need a hint?

Use np.abs() to get absolute values, np.sqrt() for square roots, and np.square() for squares. Convert results to lists.

4

Print the transformed temperature lists

Print the lists sqrt_temps, square_temps, and abs_temps each on a separate line.

NumPy

import numpy as np

temperatures = [16, -9, 25, -4, 0]
threshold = 10

sqrt_temps = list(np.sqrt(np.abs(temperatures)))
square_temps = list(np.square(temperatures))
abs_temps = list(np.abs(temperatures))
# Print sqrt_temps, square_temps, and abs_temps each on its own line
# Your code here

Need a hint?

Use three separate print statements, one for each list.