Struct vega_lite_4::TransformBuilder

pub struct TransformBuilder { /* private fields */ }

Builder for Transform.

Implementations

impl TransformBuilder

pub fn aggregate<VALUE: Into<Vec<AggregatedFieldDef>>>( &mut self, value: VALUE ) -> &mut Self

Array of objects that define fields to aggregate.

pub fn groupby<VALUE: Into<Vec<String>>>(&mut self, value: VALUE) -> &mut Self

The data fields to group by. If not specified, a single group containing all data objects will be used.

An optional array of fields by which to group the values. Imputation will then be performed on a per-group basis.

The data fields for partitioning the data objects into separate groups. If unspecified, all data points will be in a single group.

The data fields to group by.

The data fields for partitioning the data objects into separate windows. If unspecified, all data points will be in a single window.

The optional data fields to group by. If not specified, a single group containing all data objects will be used.

pub fn transform_as<VALUE: Into<LegendText>>( &mut self, value: VALUE ) -> &mut Self

The output fields at which to write the start and end bin values. This can be either a string or an array of strings with two elements denoting the name for the fields for bin start and bin end respectively. If a single string (e.g., "val") is provided, the end field will be "val_end".

The field for storing the computed formula value.

The output fields for the sample value and corresponding density estimate.

Default value: ["value", "density"]

The output field names for extracted array values.

Default value: The field name of the corresponding array field

The output field names for the key and value properties produced by the fold transform. Default value: ["key", "value"]

The output field names for the smoothed points generated by the loess transform.

Default value: The field names of the input x and y values.

The output fields on which to store the looked up data values.

For data lookups, this property may be left blank if from.fields has been specified (those field names will be used); if from.fields has not been specified, as must be a string.

For selection lookups, this property is optional: if unspecified, looked up values will be stored under a property named for the selection; and if specified, it must correspond to from.fields.

The output field names for the probability and quantile values.

Default value: ["prob", "value"]

The output field names for the smoothed points generated by the regression transform.

Default value: The field names of the input x and y values.

The output field to write the timeUnit value.

Output field names. This can be either a string or an array of strings with two elements denoting the name for the fields for stack start and stack end respectively. If a single string(e.g., "val") is provided, the end field will be "val_end".

pub fn bin<VALUE: Into<AngleBin>>(&mut self, value: VALUE) -> &mut Self

An object indicating bin properties, or simply true for using default bin parameters.

pub fn field<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field to bin.

The data field to apply time unit.

pub fn calculate<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

A expression string. Use the variable datum to refer to the current data object.

pub fn bandwidth<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

The bandwidth (standard deviation) of the Gaussian kernel. If unspecified or set to zero, the bandwidth value is automatically estimated from the input data using Scott’s rule.

A bandwidth parameter in the range [0, 1] that determines the amount of smoothing.

Default value: 0.3

pub fn counts<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

A boolean flag indicating if the output values should be probability estimates (false) or smoothed counts (true).

Default value: false

pub fn cumulative<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

A boolean flag indicating whether to produce density estimates (false) or cumulative density estimates (true).

Default value: false

pub fn density<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field for which to perform density estimation.

pub fn extent<VALUE: Into<Vec<f64>>>(&mut self, value: VALUE) -> &mut Self

A [min, max] domain from which to sample the distribution. If unspecified, the extent will be determined by the observed minimum and maximum values of the density value field.

A [min, max] domain over the independent (x) field for the starting and ending points of the generated trend line.

pub fn maxsteps<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

The maximum number of samples to take along the extent domain for plotting the density.

Default value: 200

pub fn minsteps<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

The minimum number of samples to take along the extent domain for plotting the density.

Default value: 25

pub fn steps<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

The exact number of samples to take along the extent domain for plotting the density. If specified, overrides both minsteps and maxsteps to set an exact number of uniform samples. Potentially useful in conjunction with a fixed extent to ensure consistent sample points for stacked densities.

pub fn filter<VALUE: Into<ConditionalValueDefNumberExprRefPredicateComposition>>( &mut self, value: VALUE ) -> &mut Self

The filter property must be a predication definition, which can take one of the following forms:

1. an expression string, where datum can be used to refer to the current data object. For example, {filter: "datum.b2 > 60"} would make the output data includes only items that have values in the field b2 over 60.

2. one of the field predicates: equal, lt, lte, gt, gte, range, oneOf, or valid,

3. a selection predicate, which define the names of a selection that the data point should belong to (or a logical composition of selections).

4. a logical composition of (1), (2), or (3).

pub fn flatten<VALUE: Into<Vec<String>>>(&mut self, value: VALUE) -> &mut Self

An array of one or more data fields containing arrays to flatten. If multiple fields are specified, their array values should have a parallel structure, ideally with the same length. If the lengths of parallel arrays do not match, the longest array will be used with null values added for missing entries.

pub fn fold<VALUE: Into<Vec<String>>>(&mut self, value: VALUE) -> &mut Self

An array of data fields indicating the properties to fold.

pub fn frame<VALUE: Into<Vec<Option<f64>>>>( &mut self, value: VALUE ) -> &mut Self

A frame specification as a two-element array used to control the window over which the specified method is applied. The array entries should either be a number indicating the offset from the current data object, or null to indicate unbounded rows preceding or following the current data object. For example, the value [-5, 5] indicates that the window should include five objects preceding and five objects following the current object.

Default value:: [null, null] indicating that the window includes all objects.

A frame specification as a two-element array indicating how the sliding window should proceed. The array entries should either be a number indicating the offset from the current data object, or null to indicate unbounded rows preceding or following the current data object. The default value is [null, 0], indicating that the sliding window includes the current object and all preceding objects. The value [-5, 5] indicates that the window should include five objects preceding and five objects following the current object. Finally, [null, null] indicates that the window frame should always include all data objects. If you this frame and want to assign the same value to add objects, you can use the simpler join aggregate transform. The only operators affected are the aggregation operations and the first_value, last_value, and nth_value window operations. The other window operations are not affected by this.

Default value:: [null, 0] (includes the current object and all preceding objects)

pub fn impute<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field for which the missing values should be imputed.

pub fn key<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

A key field that uniquely identifies data objects within a group. Missing key values (those occurring in the data but not in the current group) will be imputed.

pub fn keyvals<VALUE: Into<Keyvals>>(&mut self, value: VALUE) -> &mut Self

Defines the key values that should be considered for imputation. An array of key values or an object defining a number sequence.

If provided, this will be used in addition to the key values observed within the input data. If not provided, the values will be derived from all unique values of the key field. For impute in encoding, the key field is the x-field if the y-field is imputed, or vice versa.

If there is no impute grouping, this property must be specified.

pub fn method<VALUE: Into<TransformMethod>>( &mut self, value: VALUE ) -> &mut Self

The imputation method to use for the field value of imputed data objects. One of "value", "mean", "median", "max" or "min".

Default value: "value"

The functional form of the regression model. One of "linear", "log", "exp", "pow", "quad", or "poly".

Default value: "linear"

pub fn value<VALUE: Into<Value>>(&mut self, value: VALUE) -> &mut Self

The field value to use when the imputation method is "value".

The data field to populate pivoted fields. The aggregate values of this field become the values of the new pivoted fields.

pub fn joinaggregate<VALUE: Into<Vec<JoinAggregateFieldDef>>>( &mut self, value: VALUE ) -> &mut Self

The definition of the fields in the join aggregate, and what calculations to use.

pub fn loess<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field of the dependent variable to smooth.

pub fn on<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field of the independent variable to use a predictor.

pub fn transform_default<VALUE: Into<String>>( &mut self, value: VALUE ) -> &mut Self

The default value to use if lookup fails.

Default value: null

pub fn from<VALUE: Into<Lookup>>(&mut self, value: VALUE) -> &mut Self

Data source or selection for secondary data reference.

pub fn lookup<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

Key in primary data source.

pub fn probs<VALUE: Into<Vec<f64>>>(&mut self, value: VALUE) -> &mut Self

An array of probabilities in the range (0, 1) for which to compute quantile values. If not specified, the step parameter will be used.

pub fn quantile<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field for which to perform quantile estimation.

pub fn step<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

A probability step size (default 0.01) for sampling quantile values. All values from one-half the step size up to 1 (exclusive) will be sampled. This parameter is only used if the probs parameter is not provided.

pub fn order<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

The polynomial order (number of coefficients) for the ‘poly’ method.

Default value: 3

pub fn params<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

A boolean flag indicating if the transform should return the regression model parameters (one object per group), rather than trend line points. The resulting objects include a coef array of fitted coefficient values (starting with the intercept term and then including terms of increasing order) and an rSquared value (indicating the total variance explained by the model).

Default value: false

pub fn regression<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field of the dependent variable to predict.

pub fn time_unit<VALUE: Into<TimeUnitUnion>>( &mut self, value: VALUE ) -> &mut Self

The timeUnit.

pub fn sample<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

The maximum number of data objects to include in the sample.

Default value: 1000

pub fn offset<VALUE: Into<StackOffset>>(&mut self, value: VALUE) -> &mut Self

Mode for stacking marks. One of "zero" (default), "center", or "normalize". The "zero" offset will stack starting at 0. The "center" offset will center the stacks. The "normalize" offset will compute percentage values for each stack point, with output values in the range [0,1].

Default value: "zero"

pub fn sort<VALUE: Into<Vec<SortField>>>(&mut self, value: VALUE) -> &mut Self

Field that determines the order of leaves in the stacked charts.

A sort field definition for sorting data objects within a window. If two data objects are considered equal by the comparator, they are considered “peer” values of equal rank. If sort is not specified, the order is undefined: data objects are processed in the order they are observed and none are considered peers (the ignorePeers parameter is ignored and treated as if set to true).

pub fn stack<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The field which is stacked.

pub fn ignore_peers<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self

Indicates if the sliding window frame should ignore peer values (data that are considered identical by the sort criteria). The default is false, causing the window frame to expand to include all peer values. If set to true, the window frame will be defined by offset values only. This setting only affects those operations that depend on the window frame, namely aggregation operations and the first_value, last_value, and nth_value window operations.

Default value: false

pub fn window<VALUE: Into<Vec<WindowFieldDef>>>( &mut self, value: VALUE ) -> &mut Self

The definition of the fields in the window, and what calculations to use.

pub fn limit<VALUE: Into<f64>>(&mut self, value: VALUE) -> &mut Self

An optional parameter indicating the maximum number of pivoted fields to generate. The default (0) applies no limit. The pivoted pivot names are sorted in ascending order prior to enforcing the limit. Default value: 0

pub fn op<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The aggregation operation to apply to grouped value field values. Default value: sum

pub fn pivot<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self

The data field to pivot on. The unique values of this field become new field names in the output stream.

pub fn build(&self) -> Result<Transform, TransformBuilderError>

Builds a new Transform.

Errors

If a required field has not been initialized.

Trait Implementations

impl Clone for TransformBuilder

fn clone(&self) -> TransformBuilder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Default for TransformBuilder

fn default() -> Self

Returns the “default value” for a type.