Scenario

A SQLite database contains customer and order data across multiple tables. You need to analyze total order values per customer and export the results to Excel.

Task

Write a Python script at /home/interview/analyze_orders.py that:

1. Connects to the SQLite database at /home/interview/orders.db
2. Executes a SQL query to fetch customer and order data (join the tables)
3. Loads the results into a pandas DataFrame
4. Calculates total order value per customer using pandas
5. Saves the results to /home/interview/customer_totals.xlsx with columns: customer_id, customer_name, total_order_value

Note: pandas and openpyxl are already installed. The database contains customers and orders tables.

Database Schema

customers table:

• id (INTEGER)
• first_name (TEXT)
• last_name (TEXT)
• email (TEXT)

orders table:

• id (INTEGER)
• customer_id (INTEGER)
• order_date (TEXT)
• order_amount (REAL)