Struct TimeSeriesTransformations

#[non_exhaustive]
pub struct TimeSeriesTransformations {
    pub filling: Option<HashMap<String, HashMap<FillingType, String>>>,
    pub aggregation: Option<HashMap<String, AggregationTransformationValue>>,
}

Transformations allowed on the dataset. Supported transformations are Filling and Aggregation. Filling specifies how to add values to missing values in the dataset. Aggregation defines how to aggregate data that does not align with forecast frequency.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

filling: Option<HashMap<String, HashMap<FillingType, String>>>

A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.

The supported filling methods and their corresponding options are:

• frontfill: none (Supported only for target column)

• middlefill: zero, value, median, mean, min, max

• backfill: zero, value, median, mean, min, max

• futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill to a value of 2, you must include two parameters: "backfill": "value" and "backfill_value":"2".

aggregation: Option<HashMap<String, AggregationTransformationValue>>

A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.

The supported aggregation methods are sum (default), avg, first, min, max.

Aggregation is only supported for the target column.

Implementations

impl TimeSeriesTransformations

pub fn filling(&self) -> Option<&HashMap<String, HashMap<FillingType, String>>>

A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.

The supported filling methods and their corresponding options are:

• frontfill: none (Supported only for target column)

• middlefill: zero, value, median, mean, min, max

• backfill: zero, value, median, mean, min, max

• futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill to a value of 2, you must include two parameters: "backfill": "value" and "backfill_value":"2".

pub fn aggregation( &self, ) -> Option<&HashMap<String, AggregationTransformationValue>>

A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.

The supported aggregation methods are sum (default), avg, first, min, max.

Aggregation is only supported for the target column.

impl TimeSeriesTransformations

pub fn builder() -> TimeSeriesTransformationsBuilder

Creates a new builder-style object to manufacture TimeSeriesTransformations.

Trait Implementations

impl Clone for TimeSeriesTransformations

fn clone(&self) -> TimeSeriesTransformations

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TimeSeriesTransformations

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for TimeSeriesTransformations

fn eq(&self, other: &TimeSeriesTransformations) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for TimeSeriesTransformations