How would you calculate a daily conversion rate from login and transaction events in Pandas?
For this SQL version, calculate the rate from distinct users who logged in on each date to those with at least one completed transaction on that same date. Include dates with logins but no conversions.
login_date, logged_in_users, converted_users, and conversion_rate_pct| Column | Type | Description |
|---|---|---|
| event_idPK | INT | Unique login event identifier |
| user_id | INT | User who generated the login event |
| event_timestamp | TIMESTAMPTZ | Timestamp of the login event |
| Column | Type | Description |
|---|---|---|
| transaction_idPK | INT | Unique transaction identifier |
| user_id | INT | User associated with the transaction |
| transaction_timestamp | TIMESTAMPTZ | Timestamp of the transaction event |
| status | VARCHAR(20) | Transaction processing status |