Financial data analysis pattern in Data Analysis Python - Mini Project: Build & Apply

Financial data analysis pattern

📖 Scenario: You work as a financial analyst. You have a small dataset of monthly sales figures for different products. Your task is to analyze this data to find which products have sales above a certain threshold.

🎯 Goal: Build a simple Python program that stores sales data, sets a sales threshold, filters products with sales above the threshold, and prints the filtered results.

📋 What You'll Learn

Create a dictionary with product names as keys and monthly sales as values.

Create a variable to hold the sales threshold.

Use a dictionary comprehension to filter products with sales above the threshold.

Print the filtered dictionary showing products with sales above the threshold.

💡 Why This Matters

🌍 Real World

Financial analysts often need to filter and analyze sales data to identify top-performing products.

💼 Career

This pattern helps in preparing reports and making data-driven decisions in finance and sales roles.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact entries: 'Laptop': 1200, 'Smartphone': 850, 'Tablet': 400, 'Headphones': 150, 'Smartwatch': 300.

Data Analysis Python

# Create the sales_data dictionary with product names and sales
# Your code here

Hint

Use curly braces {} to create a dictionary with keys and values separated by colons.

2

Set the sales threshold

Create a variable called threshold and set it to 500.

Data Analysis Python

sales_data = {'Laptop': 1200, 'Smartphone': 850, 'Tablet': 400, 'Headphones': 150, 'Smartwatch': 300}
# Create the threshold variable and set it to 500
# Your code here

Hint

Just assign the number 500 to the variable threshold.

3

Filter products with sales above threshold

Use a dictionary comprehension to create a new dictionary called high_sales that contains only the products from sales_data with sales greater than threshold. Use product and sales as the loop variables.

Data Analysis Python

sales_data = {'Laptop': 1200, 'Smartphone': 850, 'Tablet': 400, 'Headphones': 150, 'Smartwatch': 300}
threshold = 500
# Create high_sales dictionary with products having sales > threshold
# Your code here

Hint

Use {key: value for key, value in dict.items() if condition} to filter the dictionary.

4

Print the filtered high sales products

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

Data Analysis Python

sales_data = {'Laptop': 1200, 'Smartphone': 850, 'Tablet': 400, 'Headphones': 150, 'Smartwatch': 300}
threshold = 500
high_sales = {product: sales for product, sales in sales_data.items() if sales > threshold}
# Print the high_sales dictionary
# Your code here

Hint

Use print(high_sales) to show the filtered dictionary.