Why statistics with NumPy matters - See It in Action

Why statistics with NumPy matters

📖 Scenario: Imagine you run a small bakery. You want to understand how many cakes you sell each day to plan better. You have sales numbers for a week and want to find the average, the smallest, and the biggest sales day.

🎯 Goal: You will use NumPy to calculate basic statistics like mean, minimum, and maximum from your sales data. This helps you see patterns and make smart decisions.

📋 What You'll Learn

Create a NumPy array with exact daily sales numbers

Create a variable to hold the sales data

Use NumPy functions to find mean, min, and max

Print the results clearly

💡 Why This Matters

🌍 Real World

Businesses use statistics to understand sales trends and plan inventory or marketing.

💼 Career

Data analysts and scientists use NumPy daily to analyze data quickly and accurately.

1

Create the sales data array

Import NumPy as np and create a NumPy array called sales with these exact daily sales numbers: 20, 35, 30, 35, 27, 25, 40.

NumPy

import numpy as np
# Create the sales array with the exact numbers
# Your code here

Need a hint?

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

2

Calculate the average sales

Create a variable called average_sales and use np.mean() on the sales array to find the average number of cakes sold.

NumPy

import numpy as np
sales = np.array([20, 35, 30, 35, 27, 25, 40])
# Calculate the average sales using np.mean
# Your code here

Need a hint?

Use np.mean(sales) to get the average.

3

Find the minimum and maximum sales

Create two variables called min_sales and max_sales. Use np.min() on sales to find the smallest sales number and np.max() on sales to find the biggest sales number.

NumPy

import numpy as np
sales = np.array([20, 35, 30, 35, 27, 25, 40])
average_sales = np.mean(sales)
# Calculate min_sales and max_sales using np.min and np.max
# Your code here

Need a hint?

Use np.min(sales) and np.max(sales) to find smallest and biggest sales.

4

Print the statistics

Print the values of average_sales, min_sales, and max_sales with clear messages. Use three separate print() statements.

NumPy

import numpy as np
sales = np.array([20, 35, 30, 35, 27, 25, 40])
average_sales = np.mean(sales)
min_sales = np.min(sales)
max_sales = np.max(sales)
# Print average_sales, min_sales, and max_sales with messages
# Your code here

Need a hint?

Use print(f"Average sales: {average_sales}") style to show results clearly.