Date / Temporal Layer
Extract the date component from datetime values, similar to pandas dt.date or SQL DATE(). Removes time components while respecting local timezone settings.
Example transformations:
| Input (DateTime) | Output (Date) |
|---|---|
| 2024-01-15 14:30:25 UTC | 2024-01-15 |
| 2024-01-15 23:59:59 -0500 | 2024-01-15 |
| 2024-01-16 00:00:01 +0800 | 2024-01-16 |
Common applications:
- Daily aggregations
- Date-based grouping
- Calendar analysis
- Business day calculations
- Event date tracking
- Reporting periods
Note: The operation uses the timestamp's local timezone for date determination, which may affect the resulting date near timezone boundaries.
Table
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Table
Transforms
[, ...]Select
columnDateTime column to extract date from. Common column types:
- created_at: Record timestamps
- event_time: Activity logs
- order_datetime: Transaction times
- last_modified: Update tracking Time component is removed, keeping only YYYY-MM-DD
AsColumn
nameName for the new column. If not provided, the system generates a unique name. If AsColumn matches an existing column, the existing column is replaced. The name should follow valid column naming conventions.