Log / Computation Layer

Calculate the logarithm with a specified base for each value in a numeric column. Similar to numpy.log(), pandas.eval('log()'), or R's log() function.

Mathematical form: $y_{i} = lo g_{b} (x_{i})$ where $b$ is the specified base and $i$ is the row index.

Common applications:

Scale compression (reducing data range)
Information theory (bits of information)
Sound intensity (decibel calculations)
pH calculations (hydrogen ion concentration)
Earthquake magnitude (Richter scale)
Network analysis (graph distances)
Psychological scaling (Weber-Fechner law)

Note: Input values must be positive. Negative or zero inputs result in null values.

Table

Transforms

[, ...]

Select

column

The numeric column to compute logarithms for. Values must be positive (> 0). Common input types:

Raw measurements (sound power, light intensity)
Counts or frequencies (occurrence data)
Ratios or proportions (concentration levels)
Scale values (energy measurements)

Base

f64

2.718281828459045

The logarithm base (Base). Common values:

e ≈ 2.71828 (natural logarithm, default)
2 (binary logarithm, for computer science)
10 (common logarithm, for engineering)
Other bases for specific applications

Must be positive and not equal to 1.

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.