Struct DropMissingData 

pub struct DropMissingData {
    pub columns: Option<Vec<String>>,
}

Removes rows that contain a missing value in the given columns.

Fields

columns: Option<Vec<String>>

Optional list of column names to check for missing values. If None, all columns in the DataFrame are checked.

Implementations

impl DropMissingData

pub fn new() -> Self

pub fn with_columns(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 applies filtering and returns the modified DataFrame.

Trait Implementations

impl Default for DropMissingData

fn default() -> Self

Returns the “default value” for a type.

impl Transformer for DropMissingData

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).