Struct OrdinalEncoder 

pub struct OrdinalEncoder {
    pub columns: Vec<String>,
    pub mapping: HashMap<String, HashMap<String, i64>>,
    /* private fields */
}

Replaces each category with an ordinal (ordered integer) value. Categories are sorted alphabetically and assigned increasing integers starting at 0.

Fields

columns: Vec<String>

mapping: HashMap<String, HashMap<String, i64>>

Mapping from column to (category -> ordinal index)

Implementations

impl OrdinalEncoder

pub fn new(columns: Vec<String>) -> Self

Create a new OrdinalEncoder for the specified columns.

pub async fn fit(&mut self, df: &DataFrame) -> FeatureFactoryResult<()>

Fit computes the ordinal mapping.

pub fn transform(&self, df: DataFrame) -> FeatureFactoryResult<DataFrame>

Transform replaces each category with its ordinal index.

Trait Implementations

impl Transformer for OrdinalEncoder

fn fit<'life0, 'life1, 'async_trait>( &'life0 mut self, df: &'life1 DataFrame, ) -> Pin<Box<dyn Future<Output = FeatureFactoryResult<()>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Fit the transformer given a DataFrame.

fn transform(&self, df: DataFrame) -> FeatureFactoryResult<DataFrame>

Transform the input DataFrame, returning a new DataFrame with the transformation applied.

fn is_stateful(&self) -> bool

Returns true if the transformer is stateful (i.e. requires a call to fit before transform can be called).