AI for data analysis and spreadsheet tasks in AI for Everyone - Mini Project: Build & Apply

AI for Data Analysis and Spreadsheet Tasks

📖 Scenario: You work in a small business that uses spreadsheets to track sales data. You want to use AI tools to help analyze the data quickly and find useful insights without writing complex code.

🎯 Goal: Learn how to prepare data, set simple analysis goals, apply AI-powered data analysis, and view the results to make better business decisions.

📋 What You'll Learn

Create a sales data dictionary with exact values

Set a sales threshold variable

Use AI-like logic to filter sales above the threshold

Print the filtered sales data

💡 Why This Matters

🌍 Real World

Businesses often use AI and simple data filters to quickly find important trends in sales or other data without complex coding.

💼 Career

Knowing how to prepare data and apply simple AI-like filters is useful for roles in data analysis, business intelligence, and spreadsheet management.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact entries: 'January': 1500, 'February': 1800, 'March': 1200, 'April': 2200, 'May': 1700.

AI for Everyone

# Create the sales_data dictionary with exact month and sales values
# Your code here

Need a hint?

Use curly braces to create a dictionary with month names as keys and sales numbers as values.

2

Set the sales threshold

Create a variable called sales_threshold and set it to 1600.

AI for Everyone

sales_data = {'January': 1500, 'February': 1800, 'March': 1200, 'April': 2200, 'May': 1700}
# Set sales_threshold to 1600
# Your code here

Need a hint?

Just assign the number 1600 to the variable sales_threshold.

3

Filter sales above the threshold

Create a new dictionary called high_sales that includes only the months and sales from sales_data where the sales are greater than sales_threshold. Use a dictionary comprehension with month and amount as variables.

AI for Everyone

sales_data = {'January': 1500, 'February': 1800, 'March': 1200, 'April': 2200, 'May': 1700}
sales_threshold = 1600
# Create high_sales dictionary with months having sales > sales_threshold
# Your code here

Need a hint?

Use a dictionary comprehension to pick only months where amount is greater than sales_threshold.

4

Print the filtered sales data

Print the high_sales dictionary to display the months with sales above the threshold.

AI for Everyone

sales_data = {'January': 1500, 'February': 1800, 'March': 1200, 'April': 2200, 'May': 1700}
sales_threshold = 1600
high_sales = {month: amount for month, amount in sales_data.items() if amount > sales_threshold}
# Print the high_sales dictionary
# Your code here

Need a hint?

Use the print function to show the high_sales dictionary.