# Normalize¶

`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.

#### Example¶

To normalize using both mean and standard deviation:

``````normalize(ds.input) -> (ds.normalized)
``````
More examples

Using a custom configuration to only subtract the mean:

``````normalize(ds.input, {
"with_mean": true,
"with_std": false,
}) -> (ds.normalized)
``````

## Usage¶

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

``````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.

### Inputs¶

input: column:number

A numeric column to normalize.

### Outputs¶

output: column:number

A numeric column containing the normalized value.

### Parameters¶

with_mean: boolean = True

Whether to subtract the mean.

with_std: boolean = True

Whether to divide by the standard deviation.