NotEqualTo / Boolean Layer
Create boolean mask columns indicating where values differ from a specified value. Similar to pandas series != value or R's != operator. Returns True where values are different and False where equal. Null values result in null.
Common applications:
- Finding discrepancies
- Excluding specific values
- Anomaly detection
- Change detection
- Exception identification
Example:
| Index | Value | Not Equal to 'apple' |
|---|---|---|
| 0 | apple | false |
| 1 | orange | true |
| 2 | apple | false |
| 3 | null | null |
| 4 | APPLE | true |
Compare
[, ...]List of inequality comparisons to perform. Each comparison creates a new boolean column. Common scenarios:
- Multiple exclusion checks
- Difference detection
- Error condition testing
- Validation rules
At least one comparison must be specified.
SelectLeft
columnThe column to compare. The comparison respects the column's data type and performs type-appropriate inequality checking. Null values in this column result in null in the output.
RightValue
stringThe value to compare against. Must be compatible with the column's data type. Examples:
- Numeric: '42', '-1.5'
- String: 'apple', 'pending'
- Boolean: 'true', 'false'
Case-sensitive for string comparisons.
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.