math_func
Applies a mathematical function to the values of a (single) numeric column.
See numpy’s documentation for further details about the supported functions.
Usage
The following examples show how the step can be used in a recipe.
To calculate the logarithm of a column’s values:
To calculate the logarithm of a column’s values:
Or to calculate the absolute (distance from 0, |x|) of a column’s values:
General syntax for using the step in a recipe. Shows the inputs and outputs the step is expected to receive and will produce respectively. For futher details see sections below.
Inputs & Outputs
The following are the inputs expected by the step and the outputs it produces. These are generally
columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced
by name e.g. "churn-clf").
Configuration
The following parameters can be used to configure the behaviour of the step by including them in
a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).
The name of the mathematical function to apply.
Values must be one of the following:
absolute angle arccos arccosh arcsin arcsinh arctan arctanh around cbrt ceil conj conjugate cos cosh cumprod cumsum deg2rad degrees exp exp2 expm1 fabs fix floor gradient i0 imag log log10 log1p log2 nan_to_num nancumprod nancumsum nanprod nansum negative positive prod rad2deg radians real real_if_close reciprocal rint round round_ sign sin sinc sinh sqrt square sum tan tanh trunc