IsNullMask / Boolean Layer
Create boolean mask columns indicating null values in specified columns. Similar to pandas isna() or R's is.na(). Returns True for null values and False otherwise.
Common applications:
- Missing data analysis
- Data quality assessment
- Null pattern detection
- Data cleaning workflows
- Input validation
Example:
| Index | Column A | Null Mask |
|---|---|---|
| 0 | 1 | false |
| 1 | null | true |
| 2 | 3 | false |
| 3 | null | true |
| 4 | 5 | false |
Table
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Table
Mask
[, ...]List of columns to check for null values. Each generates a separate boolean mask column. Useful for:
- Parallel null checking of multiple fields
- Bulk data quality assessment
- Creating missing data profiles
- Multi-column validation
At least one mask must be specified.
Select
columnThe column to check for null values. Any data type is supported. Common targets:
- Required fields for validation
- Sensor readings for quality control
- Survey responses for completion analysis
- Time series for gap detection
- Measurement data for reliability assessment
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.