GreaterThanEqual / Operator Layer
Compare if values in a column are greater than or equal to a constant or another column's values. Similar to pandas df['A'] >= df['B'] or df['A'] >= 5, numpy.greater_equal(), or R's >= operator. Returns a boolean column.
Mathematical form:
Common applications:
- Minimum requirement checks (score >= passing)
- Age verification (age >= legal_age)
- Quality assurance (purity >= standard)
- Inventory management (stock >= min_level)
- Service level monitoring (uptime >= sla)
- Risk thresholds (rating >= investment_grade)
Note: Includes equality in comparison, suitable for inclusive range checks.
SelectLeft
columnThe primary column for comparison. Forms the left side of the greater-than-or-equal check (e.g., test score, current level, measured value).
SelectRight
oneofValue
i6464-bit signed integer minimum threshold. Range: -2^63 to 2^63-1. Use cases:
- Minimum requirements (credits >= 120)
- Version compatibility (api_version >= 2)
- Performance targets (speed >= 100)
- Quota management (usage >= limit)
Value
u6464-bit unsigned integer minimum threshold. Range: 0 to 2^64-1. Examples:
- Storage requirements (space >= needed)
- Access levels (privileges >= required)
- Batch sizes (quantity >= minimum_order)
- Buffer capacities (available >= reserved)
Value
f6464-bit floating-point minimum threshold. Common scenarios:
- Grade requirements (gpa >= 3.5)
- Confidence levels (probability >= 0.95)
- Financial metrics (roi >= 0.15)
- Quality thresholds (similarity >= 0.8)
PropagateNull
boolControls null value handling:
- true: propagates nulls (null >= value returns null)
- false: treats nulls as false
Default is true for standard SQL-like null behavior
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.