Extract Trends With Window Functions

Extract and clean transaction data using grouping, sorting, and window functions to identify user behavior trends.

Use the provided user and transaction records. Include only completed transactions with a positive, non-null amount and a matching user.

Output

1. One row per user and transaction month.
2. Columns: month, user_id, user_name, transaction_count, total_amount, average_amount, and monthly_rank.
3. Rank users by monthly total amount, descending, with ties sharing a rank.
4. Sort by month ascending, monthly_rank ascending, and user_id ascending.