Why array creation matters in NumPy - See It in Action

Why array creation matters

📖 Scenario: Imagine you are a data analyst working with sales data. You want to organize daily sales numbers into a structure that makes it easy to analyze and calculate totals.

🎯 Goal: You will create a NumPy array to hold sales data, set a threshold for high sales, filter the data based on this threshold, and finally display the filtered sales numbers.

📋 What You'll Learn

Create a NumPy array called sales with these exact values: 10, 25, 30, 5, 40

Create a variable called threshold and set it to 20

Use a NumPy expression to create a new array called high_sales that contains only sales values greater than threshold

Print the high_sales array

💡 Why This Matters

🌍 Real World

Data scientists often need to organize and filter data efficiently to find important information quickly.

💼 Career

Knowing how to create and filter arrays is a basic skill for data analysis and machine learning tasks.

1

Create the sales data array

Import NumPy as np and create a NumPy array called sales with these exact values: 10, 25, 30, 5, 40

NumPy

# Import numpy and create the sales array
# Your code here

Need a hint?

Use np.array([...]) to create the array.

2

Set the sales threshold

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

NumPy

import numpy as np
sales = np.array([10, 25, 30, 5, 40])
# Create the threshold variable
# Your code here

Need a hint?

Just assign the number 20 to threshold.

3

Filter sales above the threshold

Use a NumPy expression to create a new array called high_sales that contains only the values in sales greater than threshold

NumPy

import numpy as np
sales = np.array([10, 25, 30, 5, 40])
threshold = 20
# Create high_sales array with sales values greater than threshold
# Your code here

Need a hint?

Use boolean indexing: sales[sales > threshold].

4

Display the filtered sales

Print the high_sales array to show the sales numbers greater than the threshold

NumPy

import numpy as np
sales = np.array([10, 25, 30, 5, 40])
threshold = 20
high_sales = sales[sales > threshold]
# Print the high_sales array
# Your code here

Need a hint?

Use print(high_sales) to display the array.