Exp / Computation Layer

Calculate the exponential function (e^x) for each value in a numeric column. Similar to numpy.exp(), pandas.exp(), or R's exp() function.

Mathematical form: $y_{i} = e^{x_{i}}$ where $e \approx 2.71828$ is Euler's number and $i$ is the row index.

Common applications:

Growth modeling (population, bacterial growth)
Financial calculations (continuous compound interest)
Statistical analysis (log-linear models)
Physical processes (radioactive decay)
Machine learning (activation functions)
Chemical kinetics (reaction rates)
Risk analysis (hazard functions)

Note: Results can grow very large for even moderate input values. Values above ~709 may result in overflow.

Table

Transforms

[, ...]

Select

column

The numeric column to compute exponential values for. Common input ranges:

Small values (-2 to 2) for normalized data
Negative values for decay processes
Rate constants in scientific calculations
Log-transformed data for reversal

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.