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fast step  math

Normalizes a numerical column by subtracting the mean and dividing by its standard deviation.

The resulting column's values will have a mean of 0.0 and a standard deviation of 1.0. Both types of scaling can be toggled separately via the with_mean and with_std parameters.


The following are the step's expected inputs and outputs and their specific types.

Step signature
normalize(input: number, {"param": value}) -> (output: number)

where the object {"param": value} is optional in most cases and if present may contain any of the parameters described in the corresponding section below.


To normalize using both mean and standard deviation:

Example call (in recipe editor)
normalize(ds.input) -> (ds.normalized)
More examples

Using a custom configuration to only subtract the mean:

Example call (in recipe editor)
normalize(ds.input, {
  "with_mean": true,
  "with_std": false,
}) -> (ds.normalized)


input: column:number

A numeric column to normalize.


output: column:number

A numeric column containing the normalized value.


with_mean: boolean = True

Whether to subtract the mean.

with_std: boolean = True

Whether to divide by the standard deviation.