IsNotNullMask / Boolean Layer
Create boolean mask columns indicating non-null values in specified columns. Similar to pandas notna() or R's !is.na(). Returns True for non-null values and False for null values.
Common applications:
- Valid data filtering
- Complete case analysis
- Data availability checks
- Quality control verification
- Valid record counting
Example:
Index | Column A | Not Null Mask |
---|---|---|
0 | 1 | true |
1 | null | false |
2 | 3 | true |
3 | null | false |
4 | 5 | true |
Mask
[, ...]List of non-null checking operations to perform. Each mask creates a new boolean column. Common scenarios:
- Validating required fields
- Checking data completeness
- Identifying usable records
- Filtering for analysis-ready data
At least one mask must be specified.
Select
columnThe column to check for non-null values. Works with any data type. The resulting mask will be a boolean column where:
- True indicates present/non-null value
- False indicates null/missing value
Useful for identifying complete records, valid measurements, or available data points.
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.