Struct DatetimeFeatures 

pub struct DatetimeFeatures {
    pub columns: Vec<String>,
}

Extracts features from datetime columns. For each column in self.columns, it adds the following new features: <column>_year, <column>_month, <column>_day, <column>_hour, <column>_minute, <column>_second, and <column>_weekday.

Fields

columns: Vec<String>

Implementations

impl DatetimeFeatures

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

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

Stateless transformer: fit does nothing.

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

Transform validates that each target column exists and is a datetime type, then returns a new DataFrame with the additional extracted features.

Trait Implementations

impl Transformer for DatetimeFeatures

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).