Cut / Manipulation Layer

Convert continuous numeric data into categorical intervals (bins). Similar to pandas' cut() or R's cut().

Mathematical representation for n bins: $interval_{i} = {[b_{i}, b_{i + 1}) (b_{i}, b_{i + 1}] right-closed left-closed$ where $b_{i}$ represents break points.

Common applications:

Score grouping (0-60, 61-70, 71-80, 81-90, 91-100)
Duration categorization (0-5min, 5-15min, 15+min)
Value segmentation (Economy, Standard, Premium)
Range analysis (Low, Medium, High)
Performance grading (A, B, C, D, F)
Risk categorization (Low-risk, Medium-risk, High-risk)
Experience levels (Beginner, Intermediate, Advanced)
Distance grouping (Local, Regional, National, International)

Table

Select

column

Numeric column to bin. Common input types:

Continuous measurements
Raw scores or ratings
Numeric indicators
Sequential values
Quantitative metrics

Breaks

[f64, ...]

Break points defining bin boundaries. Examples:

Score ranges: [0, 60, 70, 80, 90, 100]
Time periods: [0, 5, 15, 30, 60]
Value tiers: [0, 100, 500, 1000, 5000]
Percentiles: [0, 25, 50, 75, 100] Must be in ascending order.

Labels

[string, ...]

Names for the resulting bins. Examples:

Grades: ['F', 'D', 'C', 'B', 'A']
Levels: ['Beginner', 'Intermediate', 'Advanced']
Categories: ['Low', 'Medium', 'High']
Tiers: ['Bronze', 'Silver', 'Gold', 'Platinum'] Length must be number of breaks minus 1.

LeftClosed

bool

false

Defines interval closure:

false (default): Right-closed [a,b)
true: Left-closed (a,b] Example: with breaks [0,10] and value 10:
Right-closed: 10 belongs to next bin
Left-closed: 10 belongs to current bin

Name 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.