How would you extract and manipulate user engagement datasets using Python and standard data analysis libraries?
For this SQL exercise, use the provided user and engagement-event tables. Return users with engagement activity on at least two distinct days during January 2025.
country, user_id, user_name, engagement_days, total_events, total_watch_seconds, and engagement_rank.country, engagement_rank, and user_id.| Column | Type | Description |
|---|---|---|
| user_idPK | INT | Unique user identifier |
| user_name | VARCHAR(100) | Display name of the user |
| country | VARCHAR(50) | User country |
| signup_date | DATE | Date the user registered |
| Column | Type | Description |
|---|---|---|
| event_idPK | INT | Unique engagement event identifier |
| user_id | INT | User associated with the event |
| event_date | DATE | Calendar date of the event |
| event_type | VARCHAR(40) | Type of engagement event |
| watch_seconds | INT | Number of content-watch seconds recorded |