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You are a Customer Analytics Manager at Amazon. The Marketing team wants to identify repeat customers (those with 2 or more orders) for a loyalty program. Find customers who have placed at least 2 orders and show their order counts.
This is the pandas equivalent of SQL's HAVING clause.
| Column Name | Type |
|---|---|
| order_id | int64 |
| order_number | object |
| customer_id | int64 |
| order_datetime |
You are a Customer Analytics Manager at Amazon. The Marketing team wants to identify repeat customers (those with 2 or more orders) for a loyalty program. Find customers who have placed at least 2 orders and show their order counts.
This is the pandas equivalent of SQL's HAVING clause.
| Column Name | Type |
|---|---|
| order_id | int64 |
| order_number | object |
| customer_id | int64 |
| order_datetime |
| object |
| object |
| status | object |
| status | object |
| total_amount | float64 |
| total_amount | float64 |
| payment_status | object |
| payment_status | object |
| order_id | order_number | customer_id | order_datetime | status | total_amount | payment_status |
|---|---|---|---|---|---|---|
| 1 | ORD-10001 | 46 | 2025-08-20 07:01:34 | shipped | 55.32 | captured |
| 2 |
| order_id | order_number | customer_id | order_datetime | status | total_amount | payment_status |
|---|---|---|---|---|---|---|
| 1 | ORD-10001 | 46 | 2025-08-20 07:01:34 | shipped | 55.32 | captured |
| 2 |
| customer_id | order_count |
|---|---|
| 47 | 5 |
| 50 | 5 |
| 8 | 4 |
| 42 | 4 |
| 6 | 3 |
| customer_id | order_count |
|---|---|
| 47 | 5 |
| 50 | 5 |
| 8 | 4 |
| 42 | 4 |
| 6 | 3 |
Showing first 5 of 21 rows.
Showing first 5 of 21 rows.
1. Grouping:
2. Aggregation:
3. Filtering:
4. Output:
1. Grouping:
2. Aggregation:
3. Filtering:
4. Output:
| ORD-10002 |
| ORD-10002 |
| 19 |
| 19 |
| 2025-02-24 04:56:03 |
| 2025-02-24 04:56:03 |
| delivered |
| delivered |
| 662.48 |
| 662.48 |
| partial_refund |
| partial_refund |
| 3 | ORD-10003 | 21 | 2025-02-13 17:43:43 | shipped | 88.66 | captured |
| 3 | ORD-10003 | 21 | 2025-02-13 17:43:43 | shipped | 88.66 | captured |
| 4 | ORD-10004 | 8 | 2025-02-07 13:00:50 | shipped | 322.87 | captured |
| 4 | ORD-10004 | 8 | 2025-02-07 13:00:50 | shipped | 322.87 | captured |
| 5 | ORD-10005 | 8 | 2025-06-24 03:59:58 | packed | 629.34 | captured |
| 5 | ORD-10005 | 8 | 2025-06-24 03:59:58 | packed | 629.34 | captured |