Divide / Operator Layer

Perform element-wise division between numeric columns or divide a column by a constant value. Similar to pandas df['A'] / df['B'] or df['A'] / 5, numpy's divide, or R's division operator. Returns floating-point results to preserve precision.

Mathematical form: $y_{i} = \frac{x _{i}}{v}$ for constant division, or $y_{i} = \frac{x _{i}}{z _{i}}$ for column division, where $i$ is the row index.

Common applications:

Calculating rates (distance/time)
Computing percentages (part/whole × 100)
Finding averages (total/count)
Unit price calculations (total/quantity)
Normalizing data (value/maximum)
Ratio analysis (actual/expected)
Market share (sales/total_market)

Note: Division by zero results in null values.

Table

SelectLeft

column

The numerator column for division. Must be numeric type. Forms the dividend (number being divided) in calculations like total amount, full distance, or raw measurements.

SelectRight

oneof

Float

Value

f64

64-bit floating-point divisor. Provides about 15-17 decimal digits of precision. Common uses:

Rate calculations (÷60 for per-minute)
Percentage conversions (÷100 for decimal)
Unit scaling (÷1000 for kilo to base)
Sample normalization (÷standard_deviation) Must be non-zero to avoid null results

Column

Other

column

The denominator column for element-wise division. Must be numeric type. Common pairs:

total_cost ÷ units (unit cost)
distance ÷ time (speed)
value ÷ baseline (relative change)
signal ÷ reference (normalized reading)
responses ÷ attempts (success rate) Zero values in this column result in null outputs

AsColumn

name

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.